0
+ var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1
+ var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1
+ var s_v = "^(" + C + ")?" + v; // vowel in stem
+
+ this.stemWord = function (w) {
+ var stem;
+ var suffix;
+ var firstch;
+ var origword = w;
+
+ if (w.length < 3)
+ return w;
+
+ var re;
+ var re2;
+ var re3;
+ var re4;
+
+ firstch = w.substr(0,1);
+ if (firstch == "y")
+ w = firstch.toUpperCase() + w.substr(1);
+
+ // Step 1a
+ re = /^(.+?)(ss|i)es$/;
+ re2 = /^(.+?)([^s])s$/;
+
+ if (re.test(w))
+ w = w.replace(re,"$1$2");
+ else if (re2.test(w))
+ w = w.replace(re2,"$1$2");
+
+ // Step 1b
+ re = /^(.+?)eed$/;
+ re2 = /^(.+?)(ed|ing)$/;
+ if (re.test(w)) {
+ var fp = re.exec(w);
+ re = new RegExp(mgr0);
+ if (re.test(fp[1])) {
+ re = /.$/;
+ w = w.replace(re,"");
+ }
+ }
+ else if (re2.test(w)) {
+ var fp = re2.exec(w);
+ stem = fp[1];
+ re2 = new RegExp(s_v);
+ if (re2.test(stem)) {
+ w = stem;
+ re2 = /(at|bl|iz)$/;
+ re3 = new RegExp("([^aeiouylsz])\\1$");
+ re4 = new RegExp("^" + C + v + "[^aeiouwxy]$");
+ if (re2.test(w))
+ w = w + "e";
+ else if (re3.test(w)) {
+ re = /.$/;
+ w = w.replace(re,"");
+ }
+ else if (re4.test(w))
+ w = w + "e";
+ }
+ }
+
+ // Step 1c
+ re = /^(.+?)y$/;
+ if (re.test(w)) {
+ var fp = re.exec(w);
+ stem = fp[1];
+ re = new RegExp(s_v);
+ if (re.test(stem))
+ w = stem + "i";
+ }
+
+ // Step 2
+ re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;
+ if (re.test(w)) {
+ var fp = re.exec(w);
+ stem = fp[1];
+ suffix = fp[2];
+ re = new RegExp(mgr0);
+ if (re.test(stem))
+ w = stem + step2list[suffix];
+ }
+
+ // Step 3
+ re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;
+ if (re.test(w)) {
+ var fp = re.exec(w);
+ stem = fp[1];
+ suffix = fp[2];
+ re = new RegExp(mgr0);
+ if (re.test(stem))
+ w = stem + step3list[suffix];
+ }
+
+ // Step 4
+ re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;
+ re2 = /^(.+?)(s|t)(ion)$/;
+ if (re.test(w)) {
+ var fp = re.exec(w);
+ stem = fp[1];
+ re = new RegExp(mgr1);
+ if (re.test(stem))
+ w = stem;
+ }
+ else if (re2.test(w)) {
+ var fp = re2.exec(w);
+ stem = fp[1] + fp[2];
+ re2 = new RegExp(mgr1);
+ if (re2.test(stem))
+ w = stem;
+ }
+
+ // Step 5
+ re = /^(.+?)e$/;
+ if (re.test(w)) {
+ var fp = re.exec(w);
+ stem = fp[1];
+ re = new RegExp(mgr1);
+ re2 = new RegExp(meq1);
+ re3 = new RegExp("^" + C + v + "[^aeiouwxy]$");
+ if (re.test(stem) || (re2.test(stem) && !(re3.test(stem))))
+ w = stem;
+ }
+ re = /ll$/;
+ re2 = new RegExp(mgr1);
+ if (re.test(w) && re2.test(w)) {
+ re = /.$/;
+ w = w.replace(re,"");
+ }
+
+ // and turn initial Y back to y
+ if (firstch == "y")
+ w = firstch.toLowerCase() + w.substr(1);
+ return w;
+ }
+}
+
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diff --git a/docs/build/_static/pygments.css b/docs/build/_static/pygments.css
new file mode 100644
index 0000000..08bec68
--- /dev/null
+++ b/docs/build/_static/pygments.css
@@ -0,0 +1,74 @@
+pre { line-height: 125%; }
+td.linenos .normal { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; }
+span.linenos { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; }
+td.linenos .special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; }
+span.linenos.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; }
+.highlight .hll { background-color: #ffffcc }
+.highlight { background: #f8f8f8; }
+.highlight .c { color: #3D7B7B; font-style: italic } /* Comment */
+.highlight .err { border: 1px solid #FF0000 } /* Error */
+.highlight .k { color: #008000; font-weight: bold } /* Keyword */
+.highlight .o { color: #666666 } /* Operator */
+.highlight .ch { color: #3D7B7B; font-style: italic } /* Comment.Hashbang */
+.highlight .cm { color: #3D7B7B; font-style: italic } /* Comment.Multiline */
+.highlight .cp { color: #9C6500 } /* Comment.Preproc */
+.highlight .cpf { color: #3D7B7B; font-style: italic } /* Comment.PreprocFile */
+.highlight .c1 { color: #3D7B7B; font-style: italic } /* Comment.Single */
+.highlight .cs { color: #3D7B7B; font-style: italic } /* Comment.Special */
+.highlight .gd { color: #A00000 } /* Generic.Deleted */
+.highlight .ge { font-style: italic } /* Generic.Emph */
+.highlight .gr { color: #E40000 } /* Generic.Error */
+.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
+.highlight .gi { color: #008400 } /* Generic.Inserted */
+.highlight .go { color: #717171 } /* Generic.Output */
+.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
+.highlight .gs { font-weight: bold } /* Generic.Strong */
+.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
+.highlight .gt { color: #0044DD } /* Generic.Traceback */
+.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
+.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
+.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
+.highlight .kp { color: #008000 } /* Keyword.Pseudo */
+.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
+.highlight .kt { color: #B00040 } /* Keyword.Type */
+.highlight .m { color: #666666 } /* Literal.Number */
+.highlight .s { color: #BA2121 } /* Literal.String */
+.highlight .na { color: #687822 } /* Name.Attribute */
+.highlight .nb { color: #008000 } /* Name.Builtin */
+.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
+.highlight .no { color: #880000 } /* Name.Constant */
+.highlight .nd { color: #AA22FF } /* Name.Decorator */
+.highlight .ni { color: #717171; font-weight: bold } /* Name.Entity */
+.highlight .ne { color: #CB3F38; font-weight: bold } /* Name.Exception */
+.highlight .nf { color: #0000FF } /* Name.Function */
+.highlight .nl { color: #767600 } /* Name.Label */
+.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
+.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
+.highlight .nv { color: #19177C } /* Name.Variable */
+.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
+.highlight .w { color: #bbbbbb } /* Text.Whitespace */
+.highlight .mb { color: #666666 } /* Literal.Number.Bin */
+.highlight .mf { color: #666666 } /* Literal.Number.Float */
+.highlight .mh { color: #666666 } /* Literal.Number.Hex */
+.highlight .mi { color: #666666 } /* Literal.Number.Integer */
+.highlight .mo { color: #666666 } /* Literal.Number.Oct */
+.highlight .sa { color: #BA2121 } /* Literal.String.Affix */
+.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
+.highlight .sc { color: #BA2121 } /* Literal.String.Char */
+.highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
+.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
+.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
+.highlight .se { color: #AA5D1F; font-weight: bold } /* Literal.String.Escape */
+.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
+.highlight .si { color: #A45A77; font-weight: bold } /* Literal.String.Interpol */
+.highlight .sx { color: #008000 } /* Literal.String.Other */
+.highlight .sr { color: #A45A77 } /* Literal.String.Regex */
+.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
+.highlight .ss { color: #19177C } /* Literal.String.Symbol */
+.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
+.highlight .fm { color: #0000FF } /* Name.Function.Magic */
+.highlight .vc { color: #19177C } /* Name.Variable.Class */
+.highlight .vg { color: #19177C } /* Name.Variable.Global */
+.highlight .vi { color: #19177C } /* Name.Variable.Instance */
+.highlight .vm { color: #19177C } /* Name.Variable.Magic */
+.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
\ No newline at end of file
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diff --git a/docs/build/_static/searchtools.js b/docs/build/_static/searchtools.js
new file mode 100644
index 0000000..7918c3f
--- /dev/null
+++ b/docs/build/_static/searchtools.js
@@ -0,0 +1,574 @@
+/*
+ * searchtools.js
+ * ~~~~~~~~~~~~~~~~
+ *
+ * Sphinx JavaScript utilities for the full-text search.
+ *
+ * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+"use strict";
+
+/**
+ * Simple result scoring code.
+ */
+if (typeof Scorer === "undefined") {
+ var Scorer = {
+ // Implement the following function to further tweak the score for each result
+ // The function takes a result array [docname, title, anchor, descr, score, filename]
+ // and returns the new score.
+ /*
+ score: result => {
+ const [docname, title, anchor, descr, score, filename] = result
+ return score
+ },
+ */
+
+ // query matches the full name of an object
+ objNameMatch: 11,
+ // or matches in the last dotted part of the object name
+ objPartialMatch: 6,
+ // Additive scores depending on the priority of the object
+ objPrio: {
+ 0: 15, // used to be importantResults
+ 1: 5, // used to be objectResults
+ 2: -5, // used to be unimportantResults
+ },
+ // Used when the priority is not in the mapping.
+ objPrioDefault: 0,
+
+ // query found in title
+ title: 15,
+ partialTitle: 7,
+ // query found in terms
+ term: 5,
+ partialTerm: 2,
+ };
+}
+
+const _removeChildren = (element) => {
+ while (element && element.lastChild) element.removeChild(element.lastChild);
+};
+
+/**
+ * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping
+ */
+const _escapeRegExp = (string) =>
+ string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string
+
+const _displayItem = (item, searchTerms, highlightTerms) => {
+ const docBuilder = DOCUMENTATION_OPTIONS.BUILDER;
+ const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX;
+ const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX;
+ const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY;
+ const contentRoot = document.documentElement.dataset.content_root;
+
+ const [docName, title, anchor, descr, score, _filename] = item;
+
+ let listItem = document.createElement("li");
+ let requestUrl;
+ let linkUrl;
+ if (docBuilder === "dirhtml") {
+ // dirhtml builder
+ let dirname = docName + "/";
+ if (dirname.match(/\/index\/$/))
+ dirname = dirname.substring(0, dirname.length - 6);
+ else if (dirname === "index/") dirname = "";
+ requestUrl = contentRoot + dirname;
+ linkUrl = requestUrl;
+ } else {
+ // normal html builders
+ requestUrl = contentRoot + docName + docFileSuffix;
+ linkUrl = docName + docLinkSuffix;
+ }
+ let linkEl = listItem.appendChild(document.createElement("a"));
+ linkEl.href = linkUrl + anchor;
+ linkEl.dataset.score = score;
+ linkEl.innerHTML = title;
+ if (descr) {
+ listItem.appendChild(document.createElement("span")).innerHTML =
+ " (" + descr + ")";
+ // highlight search terms in the description
+ if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js
+ highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted"));
+ }
+ else if (showSearchSummary)
+ fetch(requestUrl)
+ .then((responseData) => responseData.text())
+ .then((data) => {
+ if (data)
+ listItem.appendChild(
+ Search.makeSearchSummary(data, searchTerms)
+ );
+ // highlight search terms in the summary
+ if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js
+ highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted"));
+ });
+ Search.output.appendChild(listItem);
+};
+const _finishSearch = (resultCount) => {
+ Search.stopPulse();
+ Search.title.innerText = _("Search Results");
+ if (!resultCount)
+ Search.status.innerText = Documentation.gettext(
+ "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories."
+ );
+ else
+ Search.status.innerText = _(
+ `Search finished, found ${resultCount} page(s) matching the search query.`
+ );
+};
+const _displayNextItem = (
+ results,
+ resultCount,
+ searchTerms,
+ highlightTerms,
+) => {
+ // results left, load the summary and display it
+ // this is intended to be dynamic (don't sub resultsCount)
+ if (results.length) {
+ _displayItem(results.pop(), searchTerms, highlightTerms);
+ setTimeout(
+ () => _displayNextItem(results, resultCount, searchTerms, highlightTerms),
+ 5
+ );
+ }
+ // search finished, update title and status message
+ else _finishSearch(resultCount);
+};
+
+/**
+ * Default splitQuery function. Can be overridden in ``sphinx.search`` with a
+ * custom function per language.
+ *
+ * The regular expression works by splitting the string on consecutive characters
+ * that are not Unicode letters, numbers, underscores, or emoji characters.
+ * This is the same as ``\W+`` in Python, preserving the surrogate pair area.
+ */
+if (typeof splitQuery === "undefined") {
+ var splitQuery = (query) => query
+ .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu)
+ .filter(term => term) // remove remaining empty strings
+}
+
+/**
+ * Search Module
+ */
+const Search = {
+ _index: null,
+ _queued_query: null,
+ _pulse_status: -1,
+
+ htmlToText: (htmlString) => {
+ const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html');
+ htmlElement.querySelectorAll(".headerlink").forEach((el) => { el.remove() });
+ const docContent = htmlElement.querySelector('[role="main"]');
+ if (docContent !== undefined) return docContent.textContent;
+ console.warn(
+ "Content block not found. Sphinx search tries to obtain it via '[role=main]'. Could you check your theme or template."
+ );
+ return "";
+ },
+
+ init: () => {
+ const query = new URLSearchParams(window.location.search).get("q");
+ document
+ .querySelectorAll('input[name="q"]')
+ .forEach((el) => (el.value = query));
+ if (query) Search.performSearch(query);
+ },
+
+ loadIndex: (url) =>
+ (document.body.appendChild(document.createElement("script")).src = url),
+
+ setIndex: (index) => {
+ Search._index = index;
+ if (Search._queued_query !== null) {
+ const query = Search._queued_query;
+ Search._queued_query = null;
+ Search.query(query);
+ }
+ },
+
+ hasIndex: () => Search._index !== null,
+
+ deferQuery: (query) => (Search._queued_query = query),
+
+ stopPulse: () => (Search._pulse_status = -1),
+
+ startPulse: () => {
+ if (Search._pulse_status >= 0) return;
+
+ const pulse = () => {
+ Search._pulse_status = (Search._pulse_status + 1) % 4;
+ Search.dots.innerText = ".".repeat(Search._pulse_status);
+ if (Search._pulse_status >= 0) window.setTimeout(pulse, 500);
+ };
+ pulse();
+ },
+
+ /**
+ * perform a search for something (or wait until index is loaded)
+ */
+ performSearch: (query) => {
+ // create the required interface elements
+ const searchText = document.createElement("h2");
+ searchText.textContent = _("Searching");
+ const searchSummary = document.createElement("p");
+ searchSummary.classList.add("search-summary");
+ searchSummary.innerText = "";
+ const searchList = document.createElement("ul");
+ searchList.classList.add("search");
+
+ const out = document.getElementById("search-results");
+ Search.title = out.appendChild(searchText);
+ Search.dots = Search.title.appendChild(document.createElement("span"));
+ Search.status = out.appendChild(searchSummary);
+ Search.output = out.appendChild(searchList);
+
+ const searchProgress = document.getElementById("search-progress");
+ // Some themes don't use the search progress node
+ if (searchProgress) {
+ searchProgress.innerText = _("Preparing search...");
+ }
+ Search.startPulse();
+
+ // index already loaded, the browser was quick!
+ if (Search.hasIndex()) Search.query(query);
+ else Search.deferQuery(query);
+ },
+
+ /**
+ * execute search (requires search index to be loaded)
+ */
+ query: (query) => {
+ const filenames = Search._index.filenames;
+ const docNames = Search._index.docnames;
+ const titles = Search._index.titles;
+ const allTitles = Search._index.alltitles;
+ const indexEntries = Search._index.indexentries;
+
+ // stem the search terms and add them to the correct list
+ const stemmer = new Stemmer();
+ const searchTerms = new Set();
+ const excludedTerms = new Set();
+ const highlightTerms = new Set();
+ const objectTerms = new Set(splitQuery(query.toLowerCase().trim()));
+ splitQuery(query.trim()).forEach((queryTerm) => {
+ const queryTermLower = queryTerm.toLowerCase();
+
+ // maybe skip this "word"
+ // stopwords array is from language_data.js
+ if (
+ stopwords.indexOf(queryTermLower) !== -1 ||
+ queryTerm.match(/^\d+$/)
+ )
+ return;
+
+ // stem the word
+ let word = stemmer.stemWord(queryTermLower);
+ // select the correct list
+ if (word[0] === "-") excludedTerms.add(word.substr(1));
+ else {
+ searchTerms.add(word);
+ highlightTerms.add(queryTermLower);
+ }
+ });
+
+ if (SPHINX_HIGHLIGHT_ENABLED) { // set in sphinx_highlight.js
+ localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" "))
+ }
+
+ // console.debug("SEARCH: searching for:");
+ // console.info("required: ", [...searchTerms]);
+ // console.info("excluded: ", [...excludedTerms]);
+
+ // array of [docname, title, anchor, descr, score, filename]
+ let results = [];
+ _removeChildren(document.getElementById("search-progress"));
+
+ const queryLower = query.toLowerCase();
+ for (const [title, foundTitles] of Object.entries(allTitles)) {
+ if (title.toLowerCase().includes(queryLower) && (queryLower.length >= title.length/2)) {
+ for (const [file, id] of foundTitles) {
+ let score = Math.round(100 * queryLower.length / title.length)
+ results.push([
+ docNames[file],
+ titles[file] !== title ? `${titles[file]} > ${title}` : title,
+ id !== null ? "#" + id : "",
+ null,
+ score,
+ filenames[file],
+ ]);
+ }
+ }
+ }
+
+ // search for explicit entries in index directives
+ for (const [entry, foundEntries] of Object.entries(indexEntries)) {
+ if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) {
+ for (const [file, id] of foundEntries) {
+ let score = Math.round(100 * queryLower.length / entry.length)
+ results.push([
+ docNames[file],
+ titles[file],
+ id ? "#" + id : "",
+ null,
+ score,
+ filenames[file],
+ ]);
+ }
+ }
+ }
+
+ // lookup as object
+ objectTerms.forEach((term) =>
+ results.push(...Search.performObjectSearch(term, objectTerms))
+ );
+
+ // lookup as search terms in fulltext
+ results.push(...Search.performTermsSearch(searchTerms, excludedTerms));
+
+ // let the scorer override scores with a custom scoring function
+ if (Scorer.score) results.forEach((item) => (item[4] = Scorer.score(item)));
+
+ // now sort the results by score (in opposite order of appearance, since the
+ // display function below uses pop() to retrieve items) and then
+ // alphabetically
+ results.sort((a, b) => {
+ const leftScore = a[4];
+ const rightScore = b[4];
+ if (leftScore === rightScore) {
+ // same score: sort alphabetically
+ const leftTitle = a[1].toLowerCase();
+ const rightTitle = b[1].toLowerCase();
+ if (leftTitle === rightTitle) return 0;
+ return leftTitle > rightTitle ? -1 : 1; // inverted is intentional
+ }
+ return leftScore > rightScore ? 1 : -1;
+ });
+
+ // remove duplicate search results
+ // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept
+ let seen = new Set();
+ results = results.reverse().reduce((acc, result) => {
+ let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(',');
+ if (!seen.has(resultStr)) {
+ acc.push(result);
+ seen.add(resultStr);
+ }
+ return acc;
+ }, []);
+
+ results = results.reverse();
+
+ // for debugging
+ //Search.lastresults = results.slice(); // a copy
+ // console.info("search results:", Search.lastresults);
+
+ // print the results
+ _displayNextItem(results, results.length, searchTerms, highlightTerms);
+ },
+
+ /**
+ * search for object names
+ */
+ performObjectSearch: (object, objectTerms) => {
+ const filenames = Search._index.filenames;
+ const docNames = Search._index.docnames;
+ const objects = Search._index.objects;
+ const objNames = Search._index.objnames;
+ const titles = Search._index.titles;
+
+ const results = [];
+
+ const objectSearchCallback = (prefix, match) => {
+ const name = match[4]
+ const fullname = (prefix ? prefix + "." : "") + name;
+ const fullnameLower = fullname.toLowerCase();
+ if (fullnameLower.indexOf(object) < 0) return;
+
+ let score = 0;
+ const parts = fullnameLower.split(".");
+
+ // check for different match types: exact matches of full name or
+ // "last name" (i.e. last dotted part)
+ if (fullnameLower === object || parts.slice(-1)[0] === object)
+ score += Scorer.objNameMatch;
+ else if (parts.slice(-1)[0].indexOf(object) > -1)
+ score += Scorer.objPartialMatch; // matches in last name
+
+ const objName = objNames[match[1]][2];
+ const title = titles[match[0]];
+
+ // If more than one term searched for, we require other words to be
+ // found in the name/title/description
+ const otherTerms = new Set(objectTerms);
+ otherTerms.delete(object);
+ if (otherTerms.size > 0) {
+ const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase();
+ if (
+ [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0)
+ )
+ return;
+ }
+
+ let anchor = match[3];
+ if (anchor === "") anchor = fullname;
+ else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname;
+
+ const descr = objName + _(", in ") + title;
+
+ // add custom score for some objects according to scorer
+ if (Scorer.objPrio.hasOwnProperty(match[2]))
+ score += Scorer.objPrio[match[2]];
+ else score += Scorer.objPrioDefault;
+
+ results.push([
+ docNames[match[0]],
+ fullname,
+ "#" + anchor,
+ descr,
+ score,
+ filenames[match[0]],
+ ]);
+ };
+ Object.keys(objects).forEach((prefix) =>
+ objects[prefix].forEach((array) =>
+ objectSearchCallback(prefix, array)
+ )
+ );
+ return results;
+ },
+
+ /**
+ * search for full-text terms in the index
+ */
+ performTermsSearch: (searchTerms, excludedTerms) => {
+ // prepare search
+ const terms = Search._index.terms;
+ const titleTerms = Search._index.titleterms;
+ const filenames = Search._index.filenames;
+ const docNames = Search._index.docnames;
+ const titles = Search._index.titles;
+
+ const scoreMap = new Map();
+ const fileMap = new Map();
+
+ // perform the search on the required terms
+ searchTerms.forEach((word) => {
+ const files = [];
+ const arr = [
+ { files: terms[word], score: Scorer.term },
+ { files: titleTerms[word], score: Scorer.title },
+ ];
+ // add support for partial matches
+ if (word.length > 2) {
+ const escapedWord = _escapeRegExp(word);
+ Object.keys(terms).forEach((term) => {
+ if (term.match(escapedWord) && !terms[word])
+ arr.push({ files: terms[term], score: Scorer.partialTerm });
+ });
+ Object.keys(titleTerms).forEach((term) => {
+ if (term.match(escapedWord) && !titleTerms[word])
+ arr.push({ files: titleTerms[word], score: Scorer.partialTitle });
+ });
+ }
+
+ // no match but word was a required one
+ if (arr.every((record) => record.files === undefined)) return;
+
+ // found search word in contents
+ arr.forEach((record) => {
+ if (record.files === undefined) return;
+
+ let recordFiles = record.files;
+ if (recordFiles.length === undefined) recordFiles = [recordFiles];
+ files.push(...recordFiles);
+
+ // set score for the word in each file
+ recordFiles.forEach((file) => {
+ if (!scoreMap.has(file)) scoreMap.set(file, {});
+ scoreMap.get(file)[word] = record.score;
+ });
+ });
+
+ // create the mapping
+ files.forEach((file) => {
+ if (fileMap.has(file) && fileMap.get(file).indexOf(word) === -1)
+ fileMap.get(file).push(word);
+ else fileMap.set(file, [word]);
+ });
+ });
+
+ // now check if the files don't contain excluded terms
+ const results = [];
+ for (const [file, wordList] of fileMap) {
+ // check if all requirements are matched
+
+ // as search terms with length < 3 are discarded
+ const filteredTermCount = [...searchTerms].filter(
+ (term) => term.length > 2
+ ).length;
+ if (
+ wordList.length !== searchTerms.size &&
+ wordList.length !== filteredTermCount
+ )
+ continue;
+
+ // ensure that none of the excluded terms is in the search result
+ if (
+ [...excludedTerms].some(
+ (term) =>
+ terms[term] === file ||
+ titleTerms[term] === file ||
+ (terms[term] || []).includes(file) ||
+ (titleTerms[term] || []).includes(file)
+ )
+ )
+ break;
+
+ // select one (max) score for the file.
+ const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w]));
+ // add result to the result list
+ results.push([
+ docNames[file],
+ titles[file],
+ "",
+ null,
+ score,
+ filenames[file],
+ ]);
+ }
+ return results;
+ },
+
+ /**
+ * helper function to return a node containing the
+ * search summary for a given text. keywords is a list
+ * of stemmed words.
+ */
+ makeSearchSummary: (htmlText, keywords) => {
+ const text = Search.htmlToText(htmlText);
+ if (text === "") return null;
+
+ const textLower = text.toLowerCase();
+ const actualStartPosition = [...keywords]
+ .map((k) => textLower.indexOf(k.toLowerCase()))
+ .filter((i) => i > -1)
+ .slice(-1)[0];
+ const startWithContext = Math.max(actualStartPosition - 120, 0);
+
+ const top = startWithContext === 0 ? "" : "...";
+ const tail = startWithContext + 240 < text.length ? "..." : "";
+
+ let summary = document.createElement("p");
+ summary.classList.add("context");
+ summary.textContent = top + text.substr(startWithContext, 240).trim() + tail;
+
+ return summary;
+ },
+};
+
+_ready(Search.init);
diff --git a/docs/build/_static/sphinx_highlight.js b/docs/build/_static/sphinx_highlight.js
new file mode 100644
index 0000000..8a96c69
--- /dev/null
+++ b/docs/build/_static/sphinx_highlight.js
@@ -0,0 +1,154 @@
+/* Highlighting utilities for Sphinx HTML documentation. */
+"use strict";
+
+const SPHINX_HIGHLIGHT_ENABLED = true
+
+/**
+ * highlight a given string on a node by wrapping it in
+ * span elements with the given class name.
+ */
+const _highlight = (node, addItems, text, className) => {
+ if (node.nodeType === Node.TEXT_NODE) {
+ const val = node.nodeValue;
+ const parent = node.parentNode;
+ const pos = val.toLowerCase().indexOf(text);
+ if (
+ pos >= 0 &&
+ !parent.classList.contains(className) &&
+ !parent.classList.contains("nohighlight")
+ ) {
+ let span;
+
+ const closestNode = parent.closest("body, svg, foreignObject");
+ const isInSVG = closestNode && closestNode.matches("svg");
+ if (isInSVG) {
+ span = document.createElementNS("http://www.w3.org/2000/svg", "tspan");
+ } else {
+ span = document.createElement("span");
+ span.classList.add(className);
+ }
+
+ span.appendChild(document.createTextNode(val.substr(pos, text.length)));
+ const rest = document.createTextNode(val.substr(pos + text.length));
+ parent.insertBefore(
+ span,
+ parent.insertBefore(
+ rest,
+ node.nextSibling
+ )
+ );
+ node.nodeValue = val.substr(0, pos);
+ /* There may be more occurrences of search term in this node. So call this
+ * function recursively on the remaining fragment.
+ */
+ _highlight(rest, addItems, text, className);
+
+ if (isInSVG) {
+ const rect = document.createElementNS(
+ "http://www.w3.org/2000/svg",
+ "rect"
+ );
+ const bbox = parent.getBBox();
+ rect.x.baseVal.value = bbox.x;
+ rect.y.baseVal.value = bbox.y;
+ rect.width.baseVal.value = bbox.width;
+ rect.height.baseVal.value = bbox.height;
+ rect.setAttribute("class", className);
+ addItems.push({ parent: parent, target: rect });
+ }
+ }
+ } else if (node.matches && !node.matches("button, select, textarea")) {
+ node.childNodes.forEach((el) => _highlight(el, addItems, text, className));
+ }
+};
+const _highlightText = (thisNode, text, className) => {
+ let addItems = [];
+ _highlight(thisNode, addItems, text, className);
+ addItems.forEach((obj) =>
+ obj.parent.insertAdjacentElement("beforebegin", obj.target)
+ );
+};
+
+/**
+ * Small JavaScript module for the documentation.
+ */
+const SphinxHighlight = {
+
+ /**
+ * highlight the search words provided in localstorage in the text
+ */
+ highlightSearchWords: () => {
+ if (!SPHINX_HIGHLIGHT_ENABLED) return; // bail if no highlight
+
+ // get and clear terms from localstorage
+ const url = new URL(window.location);
+ const highlight =
+ localStorage.getItem("sphinx_highlight_terms")
+ || url.searchParams.get("highlight")
+ || "";
+ localStorage.removeItem("sphinx_highlight_terms")
+ url.searchParams.delete("highlight");
+ window.history.replaceState({}, "", url);
+
+ // get individual terms from highlight string
+ const terms = highlight.toLowerCase().split(/\s+/).filter(x => x);
+ if (terms.length === 0) return; // nothing to do
+
+ // There should never be more than one element matching "div.body"
+ const divBody = document.querySelectorAll("div.body");
+ const body = divBody.length ? divBody[0] : document.querySelector("body");
+ window.setTimeout(() => {
+ terms.forEach((term) => _highlightText(body, term, "highlighted"));
+ }, 10);
+
+ const searchBox = document.getElementById("searchbox");
+ if (searchBox === null) return;
+ searchBox.appendChild(
+ document
+ .createRange()
+ .createContextualFragment(
+ '' +
+ '' +
+ _("Hide Search Matches") +
+ "
"
+ )
+ );
+ },
+
+ /**
+ * helper function to hide the search marks again
+ */
+ hideSearchWords: () => {
+ document
+ .querySelectorAll("#searchbox .highlight-link")
+ .forEach((el) => el.remove());
+ document
+ .querySelectorAll("span.highlighted")
+ .forEach((el) => el.classList.remove("highlighted"));
+ localStorage.removeItem("sphinx_highlight_terms")
+ },
+
+ initEscapeListener: () => {
+ // only install a listener if it is really needed
+ if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return;
+
+ document.addEventListener("keydown", (event) => {
+ // bail for input elements
+ if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return;
+ // bail with special keys
+ if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return;
+ if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) {
+ SphinxHighlight.hideSearchWords();
+ event.preventDefault();
+ }
+ });
+ },
+};
+
+_ready(() => {
+ /* Do not call highlightSearchWords() when we are on the search page.
+ * It will highlight words from the *previous* search query.
+ */
+ if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords();
+ SphinxHighlight.initEscapeListener();
+});
diff --git a/docs/build/_static/ssh_xilinx.PNG b/docs/build/_static/ssh_xilinx.PNG
new file mode 100644
index 0000000..287aab5
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diff --git a/docs/build/_static/unzip.PNG b/docs/build/_static/unzip.PNG
new file mode 100644
index 0000000..402ca1a
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diff --git a/docs/build/_static/voltage_divider&power_supply.jpg b/docs/build/_static/voltage_divider&power_supply.jpg
new file mode 100644
index 0000000..df95d20
Binary files /dev/null and b/docs/build/_static/voltage_divider&power_supply.jpg differ
diff --git a/docs/build/genindex.html b/docs/build/genindex.html
new file mode 100644
index 0000000..dd81df9
--- /dev/null
+++ b/docs/build/genindex.html
@@ -0,0 +1,257 @@
+
+
+
+
+
+ Index — QICK-DAWG documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ QICK-DAWG
+
+
+
+
+
+
+
+
+
+
Index
+
+
+
A
+ |
B
+ |
H
+ |
I
+ |
L
+ |
P
+ |
R
+ |
T
+
+
+
A
+
+
+
B
+
+
+
H
+
+
+
I
+
+
+
L
+
+
+
P
+
+
+
R
+
+
+
T
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/docs/build/hardware/Readme.html b/docs/build/hardware/Readme.html
new file mode 100644
index 0000000..a0624d5
--- /dev/null
+++ b/docs/build/hardware/Readme.html
@@ -0,0 +1,437 @@
+
+
+
+
+
+
+ Hardware Setup — QICK-DAWG documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ QICK-DAWG
+
+
+
+
+
+
+
+
+
+
+
+
+Hardware Setup
+In this document we outline the hardware setup for an all-in-one RFSoC4x2 enclosure. We show:
+
+Enclosure Overview
+a. Components list
+
+Enclosure Modification
+a. Drill Holes
+b. 3D Printed Cages
+c. Low-Frequency Differential Amplifier
+d. BNC to PMOD TTL
+
+Assembly
+a. Power
+b. Securing the RFSoC4x2
+c. Securing 3D printed cages
+d. Front Panel Assembly
+e. Input Signal Assembly
+f. Router and Ethernet Connection
+
+
+
+1. Enclosure Overview
+
+
+
+1a. Components
+
+
+parts_all.xlsx
lists the source, quantity, and cost for hardware modification components. parts_digikey.xlsx
can be uploaded directly into the Digikey shopping cart for easy purchase of Digikey items.
+
+
+2. Enclosure Modification
+
+2a. Drilling Holes
+Drill holes are made in the main body of the CH-14404 enclosure to secure 3D printed cages, the RFSoC4x2, an ethernet pass-through, and a power pass-through. Drill holes are also made in the front panel of the CH-144-4 enclosure for 6 SMA pass-throughs and 8 BNC pass-throughs. The schematic below shows the position and purpose of each drill hole. Enclosure_Main.STEP
and Enclosure_Front.STEP
give the exact size and position of each drill hole (found in the hardware folder).
+
+
+
+ Bud Industries CH-14404 Enclosure Screw Hole CAD Schematic
+ A = RFSoC4x2 with the PMOD oriented toward the enclosure front
+ B = Router with the ethernet ports facing the RFSoC4x2
+ Optional
+
+ C = DC Power Supply supply with voltage outputs orientated towards the RFSoC4x2
+ D = Voltage Divider
+ An external power supply can be used rather than C) DC Power Supply and D) Voltage Divider
+
+ E = Low-Frequency Differential Amplifier with V+ and V- facing the RFSoC4x2
+ F = Ethernet Pass-Through
+ G = Power Pass-Through
+
+
+
+
+ CH-14404 Enclosure Front Panel pass-through schematic. 6 SMA pass-throughs (Left) and 8 BNC pass-throughs (Right).
+
+
+
+
+2b. 3D Printed Cages
+The router and low-frequency differential amplifier are secured in the enclosure using 3D printed cages. It is especially important to immobilize the low-frequency differential amplifier since the wires and solder for the RFSoC4x2 to low-frequency differential amplifier connection are very delicate.
+The 3D printed low-frequency differential amplifier holder is made of Low_Freq_Diff_Amp_Base.STEP
and Low_Freq_Diff_Amp_Top.STEP
in the main hardware folder. Print these parts at 0.16mm tolerance. The low-frequency differential amplifier sits in the 3D printed base with the loops for V+, V-, and ground pointing down. The 3D printed top should be snug over the top of the 3D printed base. In a later step, the 3D printed low-frequency differential amplifier holder will be secured to the enclosure base with screws.
+
+
+
+
+
+
3D printed low-frequency differential amplifier holder base
+
+
+
+
3D printed low-frequency differential amplifier holder top
+
+
+
+
+
+Router_Holder.STEP
is the CAD part for the router holder and is found in the main hardware folder. Printing tolerance of 0.2mm is adequate for the router holder. The holder sits over the router and is held in place by screws from the underside of the enclosure into the part’s legs.
+
+
+
3D printed router holder
+
+
+
+2c. Low-Frequency Differential Amplifier
+to bypass the high-pass filter inherent to the analog to digital converters (ADCs) on the RFSOC4x2.
+Recall from the installation readme that the balun and capacitors on the analog-to-digital converters (ADCs) act as a high-pass filter, which filters our the low-frequency experimental defect data. The balun and capacitor need to be removed from one ADC to read in experiment data. Additionally, a low-frequency differential amplifier is required to process the low-frequency signal input after the balun has been removed. Follow step 1a in the installation readme to remove or bypass the balun and capacitors for one of the ADCs if not yet done. Now follow the modified step 1b to connect the low-frequency differential amplifier with the 3D printed holder for the low-frequency differential amplifier.
+
+
+Modified Installation Readme 1b. Connect the low-frequency differential amplifier
+
+
+
Texas Instruments LMH5401EVM low-frequency differential amplifier schematic with bias voltage for the RFSoC4x2
+
+To connect the low-frequency differential amplifier to the RFSoC4x2,
+
+solder a 3.3 V input wire to the red V+ post on the low-frequency differential amplifier
+solder a -1.8 V input wire to the yellow V- post on the low-frequency differential amplifier
+solder a ground wire to either the TPG1 or TPG2 post on the low-frequency amplifier
+screw a 0.7 V SMA wire to the Vcm (V common) SMA head on the top of the low-frequency differential amplifier
+MODIFIED - with the posts facing down, feed the soldered V+, V-, and ground wires through the base of the low-frequency differential amplifier 3D printed holder, and push the low-frequency differential amplifier down so that it is snug in the base
+cut a semi-flexible SMA cable in half and strip the insulation off of both ends to expose the center conductor
+screw the SMA heads of the cut SMA cable to Vp and Vm SMA heads on the low-frequency differential amplifier–screwing on the SMA cables now will limit the torsion on our delicate soldering in the next steps
+take the SMA cables attached to the low-frequency differential amplifier and solder them to the RFSoC4x2
+
+
+
+The image below is the circuit diagram for the RFSoC4x2. The top right solder pad–the pad for Vp–is labeled 6
. The middle right solder pad–the pad for Vm–is labeled 5
+
+
+
(Top Left) 6 contact pads underneath the balun (Bottom Left) Vm input soldered to pad 5 and Vp input soldered to pad 6 (Right) Inputs from low-frequency differential amplifier soldered to RFSoC4x2 ADC D
+
+Note that you can instead leave the balun in place and directly solder coax cables to the capacitor terminals, however, this is more difficult and it is easy to destroy the capacitor terminals with the solder iron.
+
+
+2d. BNC to PMOD TTL
+To use the PMOD to control a laser with digital TTLs we need to connect the PMOD to BNC on the front panel of the enclosure. To do so,
+
+select a BNC pass-through to be inserted to the front panel
+take a PMOD male to male connector and cut off one end
+strip the insulation from the cut end of the PMOD connector
+solder the exposed PMOD connector wire to the cup of the BNC connector
+secure the BNC pass-through to the enclosure front panel using the provided washer and nut
+the remaining PMOD connector male end can be plugged into the RFSoC4x2 PMOD
+
+
+
+
+
BNC to TTl connection in the RFSoC4x2 enclosure
+
+
+
+
Schematic for soldering PMOD cable to BNC head. Single ended male PMOD soldered to BNC cup.
+
+
+
+
+
+3. Assembling the Components
+
+3a. Power
+A single power source is plugged into the power pass-through in the back of the enclosure and pig-tail power splitters are used to power the RFSoC4x2, router, and optional internal low-frequency differential amplifier voltage supply. The power cord supplied with the RFSoC4x2 provides more voltage than necessary thus this source can be used to power the RFSoC4x2, router, and optional internal low-frequency differential amplifier voltage supply. To create the single power plug in:
+
+remove the hex nut and washer from the power pass-through jack (1 in schematic below)
+push the power pass-through jack through drill hole G (schematic 2a above) from the outside of the enclosure to the inside
+place washer back on the power pass-through jack and tighten the hex nut, the pass-through should be secured to the wall of the enclosure now
+measure and trim the two or three pigtail power cords (2 in schematic below). The power cords need to reach the router power input, RFSoC4x2 power input, and optional voltage supply. Refer to schematic 2a above. to estimate distances.
+solder two or three pigtails to the head of the power pass-through, connecting positive wires to the center jack and negative wires to the outer loop (3 and 4, respectively, in schematic below)
+
+
+
+
+
Power pass-through and pig-tail power splitting in the RFSoC4x2 enclosure. Power is split to the RFSoC4x2, router, and voltage source.
+
+
+
+
Schematic for soldering pigtail power wires to the power pass-through. 1) hex nut washer 2) pig-tail power cords 3) power pass-through center jack 4) power pass-through ground ring
+
+
+
+
+3b. Securing the RFSoC4x2
+Screws and hex standoff pillars are used to support and secure the RFSoC4x2 in the enclosure. To do so,
+
+pass a screw through an edge screw hole in the RFSoC4x2 into a hex pillar placed underneath the board, repeat for each of the 8 perimeter screw holes
+place the RFSoC4x2 in the enclosure in spot A (schematic 2a) with the PMODs facing the open end of the enclosure
+screw 8 x 4-40 0.25” up through the bottom of the enclosure into the bottom of the 8 x 0.5” hex pillars
+tighten the screws until the RFSoC4x2 is secure
+
+
+
+3c. Securing 3D Printed Cages
+To secure the 3D printed cage for the router,
+
+place the router inside enclosure in spot B (schematic 2a above) with the ethernet ports facing the RFSoC4x2
+place the 3D printed router cage on top of the router
+screw 4 4-40 0.25” screws through the bottom of the enclosure into the legs of the 3D printed router cage. Tighten the screws until the router is secure
+
+To secure the 3D printed support for the low-frequency differential amplifier,
+
+place the low-frequency differential amplifier in the 3D printed base in the enclosure in spot E (schematic 2a above))
+screw 4 4-40 0.25” screws through the bottom of the enclosure into the legs of the 3D printed low-frequency differential amplifier. Tighten the screws until the router is secure
+
+
+
+3d. Front Panel Assembly
+With the holes drilled in the CH-14404 enclosure front panel BNC and SMA pass-throughs can be secured in place. To do so,
+
+remove the washers and nuts from 6 SMA pass-throughs and 8 BNC pass-throughs
+through the front pass of the panel, place 6 SMA in the smaller left hand drill holes and 8 BNC in the right hand drill holes (schematic 2a)
+from the backside of the panel put the washers and nuts back on the SMA and BNC pass-throughs and tighten to secure
+
+The SMA and BNC pass-throughs should be secured in place on the front enclosure panel now.
+
+
+
+
Front panel of the RFSoC4x2 enclosure. Silk-screening was used to label SMA and BNC ports
+
+
+
+
+3f. Router and Ethernet Connection
+To add the ethernet pass-through to the enclosure:
+
+remove the washer from the ethernet pass-through base
+push the base of the ethernet pass-through through drill hole F from the outside of the enclosure
+screw the washer back on the ethernet-pass through from the inside of the enclosure
+
+The ethernet-pass through should now be secured to the wall of the enclosure. To connect the lab control computer to the RFSoC4x2,
+
+connect the router from the lab control computer to the ethernet pass through
+connect an ethernet cord from the ethernet pass through to the router
+connect an ethernet cord from the router to the RFSoC4x2
+
+Now the lab control computer can be used to communicate with and control with RFSoC4x2.
+
+
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diff --git a/docs/build/hardware/files.html b/docs/build/hardware/files.html
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+ Files — QICK-DAWG documentation
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+ QICK-DAWG
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+Files
+Click here to download the file: myfile’<./../_static/Enclosure_Front.STEP>’’
+
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+ QICK-DAWG — QICK-DAWG documentation
+
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+ QICK-DAWG
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+QICK-DAWG
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+
Programs/Pulse Sequences
+
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+ Installation — QICK-DAWG documentation
+
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+ QICK-DAWG
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+
+Installation
+The RFSoC4x2, as shown in the image below, is a board built and sold by Real Digital using AMD’s ZYNQ Ultrascale+ Gen 3 RFSoC ZU48DR chip. While the ZU48DR has 8 DACs and ADCs, the RFSOC4x2 only uses 4x digital to analog converters (5 GSa/s) and 2x analog to digital converters (9.85 GSa/s). Nonetheless, this number of inputs and outputs is nearly perfect for NV and quantum defect control. However, as the RFSOC4x2 is sold, the ADCs have a high frequency 1GHz high-pass balun inline which is tyipcally too high frequency for our measurements and thus must be modified.
+
+
+
+In this document we outline setup for using QICK-DAWG with RFSoC4x2. In this guide we show how to:
+
+Setup RFSoC4x2 Hardware
+a. Bipass/Remove the balun & capacitors
+b. Connect the lw frequency differential amplifier
+c. Connect PMOD digial outputs
+d. Assembling and powering on your RFSoC4x2 board
+e. (Optional) Full enclosure
+Upload and install QICK-DAWG and other software to you RFSoC4x2 board
+a. Flash your microSD card
+b. Remotely connect to your RFSoC4x2 through SSH
+c. Copy required files
+d. Install necessary packages
+
+
+1. Setup RFSoC4x2 Hardware
+
+Prerequisites
+
+RFSoC4x2 (with 12 volt 50 watt power supply)
+Managed Router (example)
+Low Frequency Differential Amplifier Texas Instruments LMH5401EVM
+3 x DC Output Voltage Supply (+3.2, +0.7, -1.8V for biasing the differential amplifier)
+SMA cables
+Computer with Ethernet port or ethernet adaptor
+Ethernet Cord(s) (at least one from RFSoC to router)
+Micro SD Card Reader
+
+
+
+
+1a. Bipass/Remove the Balun & Capacitors
+The signal measured by the photodiodes cannot be direcetly connected to the ADCs on the board, thus requiring modification the to the RFSoC4x2. The ADCs on the RFSoC4x2 have baluns and capacitors that act as high pass filters. When using photodiodes for photoluminesence detection, the signal is at low frequency thus the balun and capacitors on the board need to be removed or bipassed in order to get the signal into the ADC. Furthermore, as the ADCs take in a differential voltage signal, we have to add a differential amplifier which takes the signal from the photodetector in and outputs a biased signal to the ADCs for digitization (see section 1.b below).
+The input electronics for one ADC channel on the RFSoC4x2 is shown in the figure below.
+
+
+
+
+ WHERE IS THIS IMAGE CAPTION SHOWING UP.
+
+The combiation of the Balun, MABA-011118 and the two 100nF capactors (C302 and C303) result in a high pass filter. In order to collect the signal, we need to bypass or remove these components. Our barbaric method is to pull off the balun (under an RF shield) and desolder the capacitors as shown in the following image. The cacpacitors are then replaced with either 2x 0 ohm resistors or 2x short lenghts of wire.
+
+
+
+
+
+1b. Connect the low frequency differential amplifier
+To properly condidtion our signal for digitization, we use a Texas Instruments Texas Instruments LMH5401 EVM evaluation board. This board takes in one or two signals and outputs two voltages above (Vp ) and below (Vm ) a common voltage, Vcm . For full scale, the RFSoC4x2 requires an offset voltage of Vcm = 0.7V (note that this is also true for the ZCU216 evaluation board, but the ZCU111 evaluation board requires Vcm = 1.2 V). Addtionally, the differential amplifier requires two voltages for power, which are optimially set to Vcm + 2.5 = 3.2V and Vcm - 2.5 = -1.8. A labeled diagram of the LMH5401EVN is shown in the figure below.
+
+
+
+To connect the low frequency differential amplifier to the RFSoC4x2,
+
+solder a 3.3 V input wire to the red V+ post on the low frequency differential amplifier
+solder a -1.8 V input wire to the yellow V- post on the low frequency differential amplifier
+screw a 0.7 V SMA wire to the Vcm (V common) SMA head on the top of the low frequency differential amplifier
+cut a semi-flexible SMA cable in half and strip the insulation off of both ends to expose the center conductor
+screw the SMA heads of the cut SMA cable to Vp and Vm SMA heads on the low frequency differential amplifier–screwing on the SMA cables now will limit the torsion on our delicate soldering in the next steps
+take the SMA cables attached to the low frequency differential amplifier and solder them to the RFSoC4x2
+
+
+
+The image below is the circuit diagram for the RFSoC4x2. The top right solder pad–the pad for Vp–is labeled 6
. The middle right solder pad–the pad for Vm–is labeled 5
+
+
+
+
+Note that you can instead leave the balun in place and directly solder coax cables to the capacitor terminals, however, this is more difficult and it is easy to destroy the capacitor terminals with the solder iron.
+
+
+1c. Connect PMOD digial outputs
+To control the laser through TTL you must connect your laser to the PMOD located on the corner of the board. To connect, we cut the female head off a PMOD cable and soldered on a female BNC head instead. PMOD A 1-8 are enabled for QICK-DAWG–in the demo we use PMOD 1. The image below provides a schematic of the PMOD on the RFSoC4x2.
+
+
+
+
+
+1d. Assembling and powering on your RFSoC4x2 board
+With the hardware modified and differential amplifier connected, the RFSoC4x2 can be assembled to be connected to your computer. This connection is made through a managed ethernet router and by using the Pyro4 python package.
+
+Slide your micro SD card into its slot on the RFSoC4x2 board. Check that the BOOT switch is on SD mode.
+Connect an Ethernet cable from the board to the router and connect an Ethernet cable from the router to your computer.
+Connect the router and board to their respective power supplies. Be sure to use the 12 volt 50 watt power supply for the RFSoC4x2 board not the router.
+Flip the power switch on the RFSoC4x2 on. You should hear the fan above the RFSoC chip begin to whir and you should see green LED lights blinking all over the board. After about 30 seconds the boot light should turn green and the LED screen will display the board’s IP address.
+Your setup should resemble the schematic below.
+
+
+
+
+
+
+1e. (Optional) Full enclosure
+In our lab, we have assembled all the necessary components into a custom rack box with screw holes and 3D printed cages for fastening components down. We modified Bud Industries CH-14404 Enclosure . The following files are found in qickdawg/installation/enclosure
+
+Enclosure_Front.SLDPRT, CAD for custom enclsoure front panel holes for SMA and BNC pass through
+Enclosure_Main.SLDPRT, CAD for custom enclosure drill holes to secure components
+Low_Freq_Diff_Amp_Base.SLDRT, CAD for 3D printable differential amplifier support for mounting the differential amplifier near the RFSoC 4x2 board
+Low-Freq_Diff_Amp_Top.SLDPRT, CAD for 3D printable differential amplifier top
+Router_Holder.SLDPRT, CAD for 3D printable router cage for holding the router in the enclsoure
+
+
+
+
+
+
+
+2. Install QICK-DAWG and other software to you RFSoC4x2 board
+(Getting started directions adapted from QICK ZCU111 quick-start-guide )
+
+2a. Flashing your Micro SD Card
+
+(Windows)
+
+With your micro SD card plugged in to your computer, open Win32DiskImager. Select the PYNQ file as your image file and select your micro SD card as the device. Double check you are not flashing the image file to the wrong drive (not your computer hard drive )! To execute, click Write
.
+
+
+
+
+
+
+2b. Remotely connect to your RFSoC4x2
+To connect to your RFSoC4x2, you first need to find the IP address assigned to your board. Conveniently, the RFSoC4x2 has an LED screen on the top of the board that displays the IP address.
+Alternatively, you can log into your router and find the IP address and/or assign a static IP address.
+
+Copying Necessary Files to the RFSoC4x2
+We have written our own .bat file and jupyter notebook to streamline the installation process. The first step is to run the .bat file which copies all of the required files to the RFSoC4x2
+
+Clone qickdawg to your computer
+Open the command prompt
+Navigate to the folder that contains the QICKDAWG file FPGA_SETUP.bat
+In the command prompt type FPGA_SETUP.bat
and hit enter
+When prompted enter the IP address of your FPGA and password–xilinx
+
+FPGA_SETUP.bat
copies the following files to your RFSoC4x2:
+
+qick
+Serpent and Pyro4 packages
+run_server and qick_daemon Jupyter Notebook files
+qickdawg speicific firmware
+
+
+
+Connecting to the Jupyter Server
+With the required files copied to your RFSoC4x2, we will now install the required packages by running an .ipynb though the RFSoC4x2’s Jupyter Notebook server. To connect to the jupyter notebook server:
+
+
+
+
+From the home page, navigate to the installation folder, open Installation_Packages.ipynb and run all of the cells in install the packages. This should install qick, serpent, and pyro4 to your python environtment, which sholud be sufficient to run a pyro server and remotely connect to your RFSoC4x2
+
+
+Run the pyro server to remotely connect to QICK and the RFSoC4x2
+With all of hte packages installed, you can now run your pyro server to connect to an instance of qick. This is accomplished by running two jupyter notebooks.
+
+
+
+
+
+Second, we run the run_server/qick_daemon.ipynb
notebook, which uploads firmware to the RFSoC4x2 and creates a python socket to communicat with the board. This notebook has a string which contains the path to our alternative firmware and has a ns_host
variable which needs to be assigned to the ip address of your RFSoC4x2 board.
+
+
+
+
+With these two notebooks running you can now start communicating with your RFSoC4x2 from a python kernel on your main computer. From here, we recommend running through qickdawg/jupyter_notebooks/NVDemo_RFSoC4x2.ipynb
which contains significant documentation on how to run our basic NV characterization notebooks.
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diff --git a/docs/build/objects.inv b/docs/build/objects.inv
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diff --git a/docs/build/programs/cpmgxy8.html b/docs/build/programs/cpmgxy8.html
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+ CPMGXY-8 — QICK-DAWG documentation
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diff --git a/docs/build/programs/hahn_echo.html b/docs/build/programs/hahn_echo.html
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+ Hahn Echo — QICK-DAWG documentation
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+
+Hahn Echo
+
+
+
+class qickdawg. HahnEchoDelaySweep ( cfg )
+An NVAveragerProgram class that generates and executes a sequence used
+to measure the T2 decay of a hahn echo
+
+Parameters
+soccfg : qick.QickConfig
+cfg : .NVConfiguration
+
+instance of .NVConfiguration class with attributes:
+.adc_channel : int
+
+ADC channel for gathering data, usually 0 or 1
+
+
+.mw_channelint qick channel that provides microwave excitation
+0 or 1 for RFSoC4x2
+0 to 6 for ZCU111 or ZCU216
+
+.mw_nqzint nyquist zone for microwave generator (1 or 2)
+
+.mw_gainint gain of micrwave channel, in register values, from 0 to 2**15-1
+
+.pre_initbool boolian value that indicates whether to pre-pulse the laser to initialize
+the spin state
+
+.relax_delay_tregint Time between on/off cycles and reps in register units
+
+.readout_length_tregint Time for which the adc accumulates data in register units
+
+.laser_readout_offset_tregint Time offset between initial laser triggering and readout start
+
+.laser_gate_pmodint PMOD channel used to trigger laser source usually 0 to 6
+
+
+
+Returns
+.HahnEchoDelaySweep
+
+An instance of HahnEchoDelay sweep with compiled assembly language
+
+
+
+Methods
+
+initialize method that generates the assembly code that setups the adcs & mw generators,
+and performs other one-off setps
+
+body method that generates the assembly code that exectues in the middle of each sweep
+and rep
+
+plot_sequence generates a plot labeled with self.cfg attributes or the required inputs
+
+time_per_rep returns the approximatetime for one rep to complete
+
+total_time returns the approximate total time for the entire program to complete
+
+
+
+
+acquire ( raw_data = False , * arg , ** kwarg )
+Method that exectues the qick program and accumulates data from the data buffer until the proram is complete
+For NV measurements, the results are DC values and thus only have I values (rather than I and Q)
+
+Parameters
+
+socQickSoc qick.QickSoc instance
+
+reads_per_rep int number of readout triggers in the loop body
+
+load_pulses bool: if True, load pulse envelopes
+
+start_src str: “internal” (tProc starts immediately) or “external” (each round waits for an external trigger)
+
+progress bool: if true, displays progress bar
+
+debug bool: if true, displays assembly code for tProc program
+
+
+
+
+Returns
+
+ndarray raw accumulated IQ values (int32)
+if rounds>1, only the last round is kept
+dimensions : (n_ch, n_expts*n_reps*n_reads, 2)
+
+ndarray averaged IQ values (float)
+divided by the length of the RO window, and averaged over reps and rounds
+if shot_threshold is defined, the I values will be the fraction of points over threshold
+dimensions for a simple averaging program: (n_ch, n_reads, 2)
+dimensions for a program with multiple expts/steps: (n_ch, n_reads, n_expts, 2)
+
+
+
+
+
+
+
+body ( )
+Method that generates the assembly code that is looped over or repeated.
+For HahnEchoDelaySweep this peforms four measurements at a time and does two pulse
+sequences differing only by the phase of the final pulse. The sequences is:
+1. Set pulse phase to 0
+2. Pulse mw for pi/2
+3. delay by variable delay time
+4. pulse mw for 2x pi/2
+5. delay by variable delay time
+6. pulse mw for pi/2 (on second sequence change the phase to 180 degrees)
+7. Perform readout
+8. Loop over delay times
+9. Loop over reps
+10. Loop over rounds
+
+
+
+
+initialize ( )
+Method that generates the assembly code that is sets up adcs and sources.
+For HahnEchoDelaySweep this:
+1. Configures the adc to acquire points for self.cfg.readout_integration_t#
+2. Configures the microwave channel
+3. Configures the sweep parameters
+4. Initiailzes the spin state with a laser pulse
+
+
+
+
+plot_sequence ( )
+Function that plots the pulse sequence generated by this program
+
+Parameters
+
+cfg: .NVConfiguration or None(default None) If None, this plots the sequence with configuration labels
+If a .NVConfiguration object is supplied, the configuration value are added to the plot
+
+
+
+
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\ No newline at end of file
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+
+
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+
+
+ ODMR — QICK-DAWG documentation
+
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+ QICK-DAWG
+
+
+
+
+
+
+
+
+
+ODMR
+ODMR is optically detected nuclear magnetic resonance
+
+
+
+class qickdawg. LockinODMR ( cfg )
+An NVAveragerProgram class that generates and executes ODMR measurements by
+measuring photoluminescnece intensity (PL) as a function of microwave frequency
+taking the difference between PL for microwave drive on or off
+
+Parameters
+
+cfg instance of qickdawg.NVConfiguration class with attributes:
+.adc_channel (required)
+
+int channel which is reading data 0 or 1
+
+
+.mw_channel (required) qick channel that provides microwave excitation
+0 or 1 for RFSoC4x2
+0 to 6 for ZCU111 or ZCU216
+
+.mw_nqz (required) nyquist zone for microwave generator (1 or 2)
+
+.mw_start_freg(required) frequency generated by microwave channel in register units
+
+.mw_end_freg (required) frequency generated by micrewave channel at the end of the sweep
+
+.nsweep_points (required) number of points between mw_start_fMHz and mw_end_fMHz
+
+.mw_gain (required) gain of micrwave channel, in register values, from 0 to 2**15-1
+
+.pre_init (required) boolian value that indicates whether to pre-pulse the laser to initialize
+the spin state
+
+.relax_delay_treg (required) int that indicates how long to delay between on/off cycles and reps
+in register units
+
+.readout_integration_treg (required) int time for which PL intensity is averaged in register units
+
+.laser_gate_pmod(required) int PMOD channel used to trigger laser source
+0 to 4
+
+.reps(required) times the pulse sequence is repeated
+
+.reads_per_rep(required) times adcs are triggered per rep
+
+
+
+returns an instances of LockinODMR class with assembly language compiled
+
+
+
+
+Methods
+
+initialize method that generates the assembly code that setups the adcs & mw generators,
+and performs other one-off setps
+
+body method that generates the assembly code that exectues in the middle of each sweep
+and rep
+
+analyze_results takes the output of self.acquire() and returns odmr_contrast and other results
+
+plot_sequence generates a plot labeled with self.cfg attributes or the required inputs
+
+time_per_rep returns the approximatetime for one rep to complete
+
+total_time returns the approximate total time for the entire program to complete
+
+
+
+
+acquire ( raw_data = False , * arg , ** kwarg )
+Method that exectues the qick program and accumulates data from the data buffer until the proram is complete
+For NV measurements, the results are DC values and thus only have I values (rather than I and Q)
+
+Parameters
+
+socQickSoc qick.QickSoc instance
+
+reads_per_rep int number of readout triggers in the loop body
+
+load_pulses bool: if True, load pulse envelopes
+
+start_src str: “internal” (tProc starts immediately) or “external” (each round waits for an external trigger)
+
+progress bool: if true, displays progress bar
+
+debug bool: if true, displays assembly code for tProc program
+
+
+
+
+Returns
+
+ndarray raw accumulated IQ values (int32)
+if rounds>1, only the last round is kept
+dimensions : (n_ch, n_expts*n_reps*n_reads, 2)
+
+ndarray averaged IQ values (float)
+divided by the length of the RO window, and averaged over reps and rounds
+if shot_threshold is defined, the I values will be the fraction of points over threshold
+dimensions for a simple averaging program: (n_ch, n_reads, 2)
+dimensions for a program with multiple expts/steps: (n_ch, n_reads, n_expts, 2)
+
+
+
+
+
+
+
+analyze_results ( data )
+Method that takes in a 1D array of data points from self.acquire() and analyzes the
+results based on the number of reps, rounds, and frequency points
+
+Parameters
+
+data (1D np.array) data returned from self.acquire()
+
+returns (qickdawg.ItemAttribute instance) with attributes
+.frequencies (len(frequencies) np array, GHz units) - frequencies swept over
+.signal (nfrequency np.array, adc units) - average adc signal for microwave on
+.reference (nfrequency np.array, adc units) - average adc signal for mwicrowave off
+.odmr (nfrequency np.array, adc units)) - .signal minus .refrence
+.odmr_contrast (nfrequency np.array, % units) - (.signal - .reference)/.reference * 100
+
+
+
+
+
+
+
+body ( )
+Method that generates the assembly code that is looped over or repeated.
+For LockinODMR this has two acquisitions
+The first acquisition has the microwave channel on for .cfg.readout_integration_t# and
+
+averages the adc values over this time
+
+
+The second acquisition has the microwave channel off for .cfg.readout_integration_t# and averages the adc values over this time
+
+
+
+
+
+
+initialize ( )
+Method that generates the assembly code that initializes the pulse sequence.
+For LockinODMR this sets up the adc to integrate for self.cfg.readout_intregration_t#,
+setups hte microave channel to run fo the same amount of time, and setups the a
+qickdawg.NVQickSweep to sweep over frequencies
+
+
+
+
+plot_sequence ( )
+Function that plots the pulse sequence generated by this program
+
+Parameters
+
+cfg: .NVConfiguration or None(default None) If None, this plots the squence with configuration labels
+If a .NVConfiguration object is supplied, the configuraiton value are added to the plot
+
+
+
+
+
+
+
+time_per_rep ( )
+Method that returns the approximate time per rep, excluding any overhead
+
+returns (float) time for one rep in seconds
+
+
+
+
+
+
+total_time ( )
+Method that returns the approximate time for full qickdawg program to run
+
+returns (float) time for full qickdawg program in seconds
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/docs/build/programs/rabi_oscillations.html b/docs/build/programs/rabi_oscillations.html
new file mode 100644
index 0000000..09d5939
--- /dev/null
+++ b/docs/build/programs/rabi_oscillations.html
@@ -0,0 +1,274 @@
+
+
+
+
+
+
+ Rabi Oscillations — QICK-DAWG documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ QICK-DAWG
+
+
+
+
+
+
+
+
+
+Rabi Oscillations
+
+
+
+class qickdawg. RabiSweep ( cfg )
+An NVAveragerProgram class that generates and executes a sequence used
+to determine the pi (pi/2) pulse lenghts for your experimetanl configuration
+
+Parameters
+
+soccfg instance of qick.QickConfig class
+
+cfg instance of qickdawg.NVConfiguration class with attributes:
+.adc_channel (required)
+
+int channel which is reading data 0 or 1
+
+
+.mw_channel (required) qick channel that provides microwave excitation
+0 or 1 for RFSoC4x2
+0 to 6 for ZCU111 or ZCU216
+
+.mw_nqz (required) nyquist zone for microwave generator (1 or 2)
+
+.mw_gain (required) gain of micrwave channel, in register values, from 0 to 2**15-1
+
+.pre_init (required) boolian value that indicates whether to pre-pulse the laser to initialize
+the spin state
+
+.relax_delay_treg (required) int that indicates how long to delay between on/off cycles and reps
+in register units
+
+.readout_length_treg (required) int time for which the adc accumulates data
+the limit is 1020 points for the FPGA buffer
+
+
+.laser_readout_offset_treg (required)
+
+.laser_gate_pmod(required) int PMOD channel used to trigger laser source
+0 to 4
+
+
+
+returns an instances of LockinODMR class with assembly language compiled
+
+
+
+
+Methods
+
+initialize method that generates the assembly code that setups the adcs & mw generators,
+and performs other one-off setps
+
+body method that generates the assembly code that exectues in the middle of each sweep
+and rep
+
+plot_sequence generates a plot labeled with self.cfg attributes or the required inputs
+
+time_per_rep returns the approximatetime for one rep to complete
+
+total_time returns the approximate total time for the entire program to complete
+
+
+
+
+acquire ( raw_data = False , * arg , ** kwarg )
+Method that exectues the qick program and accumulates data from the data buffer until the proram is complete
+For NV measurements, the results are DC values and thus only have I values (rather than I and Q)
+
+Parameters
+
+socQickSoc qick.QickSoc instance
+
+reads_per_rep int number of readout triggers in the loop body
+
+load_pulses bool: if True, load pulse envelopes
+
+start_src str: “internal” (tProc starts immediately) or “external” (each round waits for an external trigger)
+
+progress bool: if true, displays progress bar
+
+debug bool: if true, displays assembly code for tProc program
+
+
+
+
+Returns
+
+ndarray raw accumulated IQ values (int32)
+if rounds>1, only the last round is kept
+dimensions : (n_ch, n_expts*n_reps*n_reads, 2)
+
+ndarray averaged IQ values (float)
+divided by the length of the RO window, and averaged over reps and rounds
+if shot_threshold is defined, the I values will be the fraction of points over threshold
+dimensions for a simple averaging program: (n_ch, n_reads, 2)
+dimensions for a program with multiple expts/steps: (n_ch, n_reads, n_expts, 2)
+
+
+
+
+
+
+
+body ( )
+Method that generates the assembly code that is looped over or repeated.
+For RabiSweep this peforms four measurements at a time and does two pulse sequences:
+1. Microwave pulse followed by readout and reference emasurement
+2. No micrwave pulse followed by readout and reference
+
+
+
+
+initialize ( )
+Method that generates the assembly code that is sets up adcs and sources.
+For RabiSweep this:
+configures the adc to acquire points for self.cfg.readout_integration_t#.
+configures the microwave channel
+configures the sweep parameters
+initiailzes the spin state with a laser pulse
+
+
+
+
+plot_sequence ( )
+Function that plots the pulse sequence generated by this program
+
+Parameters
+
+cfg: .NVConfiguration or None(default None) If None, this plots the squence with configuration labels
+If a .NVConfiguration object is supplied, the configuraiton value are added to the plot
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/docs/build/programs/ramsey_interferometry.html b/docs/build/programs/ramsey_interferometry.html
new file mode 100644
index 0000000..50ede04
--- /dev/null
+++ b/docs/build/programs/ramsey_interferometry.html
@@ -0,0 +1,279 @@
+
+
+
+
+
+
+ Ramsey Interferometry — QICK-DAWG documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ QICK-DAWG
+
+
+
+
+
+
+
+
+
+Ramsey Interferometry
+
+
+
+class qickdawg. Ramsey ( cfg )
+An NVAveragerProgram class that generates and executes a sequence used
+to measure ramsey
+
+Parameters
+soccfg : qick.QickConfig
+cfg : .NVConfiguration
+
+instance of .NVConfiguration class with attributes:
+.adc_channel : int
+
+ADC channel for gathering data, usually 0 or 1
+
+
+.mw_channelint qick channel that provides microwave excitation
+0 or 1 for RFSoC4x2
+0 to 6 for ZCU111 or ZCU216
+
+.mw_nqzint nyquist zone for microwave generator (1 or 2)
+
+.mw_gainint gain of micrwave channel, in register values, from 0 to 2**15-1
+
+.pre_initbool boolian value that indicates whether to pre-pulse the laser to initialize
+the spin state
+
+.relax_delay_tregint Time between on/off cycles and reps in register units
+
+.readout_length_tregint Time for which the adc accumulates data in register units
+
+.laser_readout_offset_tregint Time offset between initial laser triggering and readout start
+
+.laser_gate_pmodint PMOD channel used to trigger laser source usually 0 to 6
+
+
+
+Returns
+.Ramsey
+
+An instance of Rmasey with compiled assembly language
+
+
+
+Methods
+
+initialize method that generates the assembly code that setups the adcs & mw generators,
+and performs other one-off setps
+
+body method that generates the assembly code that exectues in the middle of each sweep
+and rep
+
+plot_sequence generates a plot labeled with self.cfg attributes or the required inputs
+
+time_per_rep returns the approximatetime for one rep to complete
+
+total_time returns the approximate total time for the entire program to complete
+
+
+
+
+acquire ( raw_data = False , * arg , ** kwarg )
+Method that exectues the qick program and accumulates data from the data buffer until the proram is complete
+For NV measurements, the results are DC values and thus only have I values (rather than I and Q)
+
+Parameters
+
+socQickSoc qick.QickSoc instance
+
+reads_per_rep int number of readout triggers in the loop body
+
+load_pulses bool: if True, load pulse envelopes
+
+start_src str: “internal” (tProc starts immediately) or “external” (each round waits for an external trigger)
+
+progress bool: if true, displays progress bar
+
+debug bool: if true, displays assembly code for tProc program
+
+
+
+
+Returns
+
+ndarray raw accumulated IQ values (int32)
+if rounds>1, only the last round is kept
+dimensions : (n_ch, n_expts*n_reps*n_reads, 2)
+
+ndarray averaged IQ values (float)
+divided by the length of the RO window, and averaged over reps and rounds
+if shot_threshold is defined, the I values will be the fraction of points over threshold
+dimensions for a simple averaging program: (n_ch, n_reads, 2)
+dimensions for a program with multiple expts/steps: (n_ch, n_reads, n_expts, 2)
+
+
+
+
+
+
+
+body ( )
+Method that generates the assembly code that is looped over or repeated.
+For Ramsey this peforms four measurements at a time and does two pulse
+sequences differing only by the phase of the final pulse. The sequences is:
+1. Set pulse phase to 0
+2. Pulse mw for pi/2
+5. delay by variable delay time
+6. pulse mw for pi/2 (on second sequence change the phase to 180 degrees)
+7. Perform readout
+8. Loop over delay times
+9. Loop over reps
+10. Loop over rounds
+
+
+
+
+initialize ( )
+Method that generates the assembly code that is sets up adcs and sources.
+For Ramsey this:
+1. Configures the adc to acquire points for self.cfg.readout_integration_t#.
+2. Configures the microwave channel
+3. Configures the sweep parameters
+4. Initiailzes the spin state with a laser pulse
+
+
+
+
+plot_sequence ( )
+Function that plots the pulse sequence generated by this program
+
+Parameters
+
+cfg: .NVConfiguration or None(default None) If None, this plots the squence with configuration labels
+If a .NVConfiguration object is supplied, the configuraiton value are added to the plot
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/docs/build/programs/readout_window.html b/docs/build/programs/readout_window.html
new file mode 100644
index 0000000..10887a9
--- /dev/null
+++ b/docs/build/programs/readout_window.html
@@ -0,0 +1,234 @@
+
+
+
+
+
+
+ Readout Window — QICK-DAWG documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ QICK-DAWG
+
+
+
+
+
+
+
+
+
+Readout Window
+
+
+
+class qickdawg. ReadoutWindow ( cfg )
+An NVAveragerProgram class that generates and executes a sequence used
+to calibrate the laser gating relative to the adc data accumulation.
+This is intended to be used with the function qickdawg.get_readout_window()
+to accumulate multiple windows with (to accomodate the 1020 point limit of the
+FPGA buffer) and microwave on and off to provide contrast between spin projections
+
+Parameters
+
+cfg instance of qickdawg.NVConfiguration class with attributes:
+.adc_channel (required)
+
+int channel which is reading data 0 or 1
+
+
+.mw_channel (required) qick channel that provides microwave excitation
+0 or 1 for RFSoC4x2
+0 to 6 for ZCU111 or ZCU216
+
+.mw_nqz (required) nyquist zone for microwave generator (1 or 2)
+
+.mw_gain (required) gain of micrwave channel, in register values, from 0 to 2**15-1
+
+.pre_init (required) boolian value that indicates whether to pre-pulse the laser to initialize
+the spin state
+
+.relax_delay_treg (required) int that indicates how long to delay between on/off cycles and reps
+in register units
+
+.readout_length_treg (required) int time for which the adc accumulates data
+the limit is 1020 points for the FPGA buffer
+
+
+.laser_readout_offset_treg (required)
+
+.laser_gate_pmod(required) int PMOD channel used to trigger laser source
+0 to 4
+
+
+
+returns an instances of LockinODMR class with assembly language compiled
+
+
+
+
+Methods
+
+initialize method that generates the assembly code that setups the adcs & mw generators,
+and performs other one-off setps
+
+body method that generates the assembly code that exectues in the middle of each sweep
+and rep
+
+plot_sequence generates a plot labeled with self.cfg attributes or the required inputs
+
+time_per_rep returns the approximatetime for one rep to complete
+
+total_time returns the approximate total time for the entire program to complete
+
+
+
+
+body ( )
+Method that generates the assembly code that is looped over or repeated.
+For Readoutwindow pre-initializes the spin state by turning just the laser on
+for self.cfg.laser_initalize_t#. After initialization, the micrwave channel is pulsed
+followed by the laser, then the adc is triggered. The laser and adc are offset by
+self.cfg.laser_readout_offset_t#
+
+
+
+
+initialize ( )
+Method that generates the assembly code that configures adcs, mw, etc.
+For ReadoutWindow this setups up the adc to acquire points for
+self.cfg.readout_length_t#. If the mw_pi2_t# > 0, this setups the
+microwave channel to pulse, otherwise there is mw pulse
+
+
+
+
+plot_sequence ( )
+Function that plots the pulse sequence generated by this program
+
+Parameters
+
+cfg: .NVConfiguration or None(default None) If None, this plots the squence with configuration labels
+If a .NVConfiguration object is supplied, the configuraiton value are added to the plot
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/docs/build/programs/t1_relaxation.html b/docs/build/programs/t1_relaxation.html
new file mode 100644
index 0000000..5c7cc9d
--- /dev/null
+++ b/docs/build/programs/t1_relaxation.html
@@ -0,0 +1,278 @@
+
+
+
+
+
+
+ T1 Relaxation — QICK-DAWG documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ QICK-DAWG
+
+
+
+
+
+
+
+
+
+T1 Relaxation
+
+
+
+class qickdawg. T1DelaySweep ( cfg )
+An NVAveragerProgram class that generates and executes a sequence used
+to measure the T1 Decay
+
+Parameters
+
+soccfg instance of qick.QickConfig class
+
+cfg instance of qickdawg.NVConfiguration class with attributes:
+.adc_channel (required)
+
+int channel which is reading data 0 or 1
+
+
+.mw_channel (required) qick channel that provides microwave excitation
+0 or 1 for RFSoC4x2
+0 to 6 for ZCU111 or ZCU216
+
+.mw_nqz (required) nyquist zone for microwave generator (1 or 2)
+
+.mw_gain (required) gain of micrwave channel, in register values, from 0 to 2**15-1
+
+.pre_init (required) boolian value that indicates whether to pre-pulse the laser to initialize
+the spin state
+
+.relax_delay_treg (required) int that indicates how long to delay between on/off cycles and reps
+in register units
+
+.readout_length_treg (required) int time for which the adc accumulates data
+the limit is 1020 points for the FPGA buffer
+
+
+.laser_readout_offset_treg (required)
+
+.laser_gate_pmod(required) int PMOD channel used to trigger laser source
+0 to 4
+
+
+
+
+
+
+Methods
+
+initialize method that generates the assembly code that setups the adcs & mw generators,
+and performs other one-off setps
+
+body method that generates the assembly code that exectues in the middle of each sweep
+and rep
+
+plot_sequence generates a plot labeled with self.cfg attributes or the required inputs
+
+time_per_rep returns the approximatetime for one rep to complete
+
+total_time returns the approximate total time for the entire program to complete
+
+
+
+
+acquire ( raw_data = False , * arg , ** kwarg )
+Method that exectues the qick program and accumulates data from the data buffer until the proram is complete
+For NV measurements, the results are DC values and thus only have I values (rather than I and Q)
+
+Parameters
+
+socQickSoc qick.QickSoc instance
+
+reads_per_rep int number of readout triggers in the loop body
+
+load_pulses bool: if True, load pulse envelopes
+
+start_src str: “internal” (tProc starts immediately) or “external” (each round waits for an external trigger)
+
+progress bool: if true, displays progress bar
+
+debug bool: if true, displays assembly code for tProc program
+
+
+
+
+Returns
+
+ndarray raw accumulated IQ values (int32)
+if rounds>1, only the last round is kept
+dimensions : (n_ch, n_expts*n_reps*n_reads, 2)
+
+ndarray averaged IQ values (float)
+divided by the length of the RO window, and averaged over reps and rounds
+if shot_threshold is defined, the I values will be the fraction of points over threshold
+dimensions for a simple averaging program: (n_ch, n_reads, 2)
+dimensions for a program with multiple expts/steps: (n_ch, n_reads, n_expts, 2)
+
+
+
+
+
+
+
+body ( )
+Method that generates the assembly code that is looped over or repeated.
+For T1DecaySweep this peforms four measurements at a time and does two pulse
+sequences differing as wot whether the microwave is on or off on the first pulse.
+The sequences is:
+1. Pulse mw for pi (just delay for second sequence)
+2. delay by variable delay time
+3. Perform readout
+4. Loop over delay times
+5. Loop over reps
+6. Loop over rounds
+
+
+
+
+initialize ( )
+Method that generates the assembly code that is sets up adcs and sources.
+For T1DecaySweep this:
+1. configures the adc to acquire points for self.cfg.readout_integration_t#.
+2. configures the microwave channel
+3. configures the sweep parameters
+4. initiailzes the spin state with a laser pulse
+
+
+
+
+plot_sequence ( )
+Function that plots the pulse sequence generated by this program
+
+Parameters
+
+cfg: .NVConfiguration or None(default None) If None, this plots the squence with configuration labels
+If a .NVConfiguration object is supplied, the configuraiton value are added to the plot
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/docs/build/search.html b/docs/build/search.html
new file mode 100644
index 0000000..82faa66
--- /dev/null
+++ b/docs/build/search.html
@@ -0,0 +1,138 @@
+
+
+
+
+
+ Search — QICK-DAWG documentation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ QICK-DAWG
+
+
+
+
+
+
+
+
+
+
+
+ Please activate JavaScript to enable the search functionality.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/docs/build/searchindex.js b/docs/build/searchindex.js
new file mode 100644
index 0000000..659d460
--- /dev/null
+++ b/docs/build/searchindex.js
@@ -0,0 +1 @@
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"alltitles": {"Hardware Setup": [[0, "hardware-setup"]], "1. Enclosure Overview": [[0, "enclosure-overview"]], "2. Enclosure Modification": [[0, "enclosure-modification"]], "2a. Drilling Holes": [[0, "a-drilling-holes"]], "2b. 3D Printed Cages": [[0, "b-3d-printed-cages"]], "2c. Low-Frequency Differential Amplifier": [[0, "c-low-frequency-differential-amplifier"]], "Modified Installation Readme 1b. Connect the low-frequency differential amplifier": [[0, "modified-installation-readme-1b-connect-the-low-frequency-differential-amplifier"]], "2d. BNC to PMOD TTL": [[0, "d-bnc-to-pmod-ttl"]], "3. Assembling the Components": [[0, "assembling-the-components"]], "3a. Power": [[0, "a-power"]], "3b. Securing the RFSoC4x2": [[0, "b-securing-the-rfsoc4x2"]], "3c. Securing 3D Printed Cages": [[0, "c-securing-3d-printed-cages"]], "3d. Front Panel Assembly": [[0, "d-front-panel-assembly"]], "3e. Input Signal Assembly": [[0, "e-input-signal-assembly"]], "3f. Router and Ethernet Connection": [[0, "f-router-and-ethernet-connection"]], "Installation": [[2, "installation"], [10, "installation"]], "1. Setup RFSoC4x2 Hardware": [[2, "setup-rfsoc4x2-hardware"]], "Prerequisites": [[2, "prerequisites"]], "Software": [[2, "software"]], "1a. Bipass/Remove the Balun & Capacitors": [[2, "a-bipass-remove-the-balun-capacitors"]], "1b. Connect the low frequency differential amplifier": [[2, "b-connect-the-low-frequency-differential-amplifier"]], "1c. Connect PMOD digial outputs": [[2, "c-connect-pmod-digial-outputs"]], "1d. Assembling and powering on your RFSoC4x2 board": [[2, "d-assembling-and-powering-on-your-rfsoc4x2-board"]], "1e. (Optional) Full enclosure": [[2, "e-optional-full-enclosure"]], "2. Install QICK-DAWG and other software to you RFSoC4x2 board": [[2, "install-qick-dawg-and-other-software-to-you-rfsoc4x2-board"]], "2a. Flashing your Micro SD Card": [[2, "a-flashing-your-micro-sd-card"]], "2b. Remotely connect to your RFSoC4x2": [[2, "b-remotely-connect-to-your-rfsoc4x2"]], "Copying Necessary Files to the RFSoC4x2": [[2, "copying-necessary-files-to-the-rfsoc4x2"]], "Connecting to the Jupyter Server": [[2, "connecting-to-the-jupyter-server"]], "Run the pyro server to remotely connect to QICK and the RFSoC4x2": [[2, "run-the-pyro-server-to-remotely-connect-to-qick-and-the-rfsoc4x2"]], "CPMGXY-8": [[3, "cpmgxy-8"]], "Hahn Echo": [[4, "hahn-echo"]], "Parameters": [[4, "parameters"], [4, "id1"], [4, "id2"], [5, "parameters"], [5, "id1"], [5, "id2"], [5, "id5"], [6, "parameters"], [6, "id1"], [6, "id2"], [7, "parameters"], [7, "id1"], [7, "id2"], [8, "parameters"], [8, "id1"], [9, "parameters"], [9, "id1"], [9, "id2"]], "Methods": [[4, "methods"], [5, "methods"], [6, "methods"], [7, "methods"], [8, "methods"], [9, "methods"]], "Returns": [[4, "returns"], [5, "returns"], [6, "returns"], [7, "returns"], [9, "returns"]], "ODMR": [[5, "odmr"]], "Rabi Oscillations": [[6, "rabi-oscillations"]], "Ramsey Interferometry": [[7, "ramsey-interferometry"]], "Readout Window": [[8, "readout-window"]], "T1 Relaxation": [[9, "t1-relaxation"]], "Introduction": [[10, "introduction"]], "Quantum Instrumentation Control Kit - Defect Arbitrary Waveform Generator": [[10, "quantum-instrumentation-control-kit-defect-arbitrary-waveform-generator"]], "Description": [[10, "description"]], "Hardware": [[10, "hardware"]], "Usage": [[10, "usage"]], "Support": [[10, "support"]], "Authors and acknowledgment": [[10, "authors-and-acknowledgment"]], "License": [[10, "license"]], "Project status": [[10, "project-status"]], "QICK-DAWG": [[1, "qick-dawg"]], "The basics": [[1, null]], "Programs/Pulse Sequences": [[1, null]], "Setup": [[1, null]], "Indices and tables": [[1, "indices-and-tables"]]}, "indexentries": {}})
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+ Introduction — QICK-DAWG documentation
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+ QICK-DAWG
+
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+
+
+Introduction
+
+
+Description
+The Quantum Instrumentation Control Kit - Defect Arbitrary Waveform Generator (QICK-DAWG) is an extension of QICK with the purpose of controlling nitrogen-vacancy in diamond and other quantum defects for quantum sensing and other quantum applications. QICK-DAWG utilizes Xilinx Radio Frequency System-on-Chip (RFSoC) Field Programmable Gate Array (FPGAs) evaluation boards which are significantly less expensive than hardware currently available and have the potential for superior capabilities.
+In this package we supply specific mw, laser, and readout pulsing code to characterize photoluminescence intensity, optically detected magnetic resonance (ODMR), spin readout, Rabi Oscillation, Hahn Echo T2 , and T1 relaxation. A Jupyter Notebook Demo is included for performing all of these measurements with an RFSoC4x2 to demonstrate typical measurements.
+
+
+
+Installation
+To install QICKDAWG software follow the README found here . Software installation includes:
+
+
+Usage
+QICKDAWG has programs for the characterization of:
+
+using a ZCU111 or RFSoC4x2. Support for the ZCU216 coming soon.
+
+
+
+Support
+To raise an issue use the Issues button on the side bar. Email Andy Mounce at amounce@sandia.gov for further support.
+
+
+Authors and acknowledgment
+Andy Mounce1 , Emmeline Riendeau1 ,2
+1 : Center for Integrated Nanotechnology (CINT), Sandia National Laboratories
+2 : Haverford College ‘24
+Thank you to Sho Uemura at Fermi Labs for helping us edit the QICK firmware.
+
+
+License
+Copyright 2023 National Technology & Engineering Solutions of Sandia, LLC (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the U.S. Government retains certain rights in this software.
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the “Software”), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
+IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
+DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR
+OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE
+OR OTHER DEALINGS IN THE SOFTWARE.
+
+
+Project status
+QICKDAWG project is active and updates will be added as changes are made.
+
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diff --git a/graphics/DEER.svg b/graphics/DEER.svg
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+ RADIO FREQUENCY ωdefect ON/OFF
+ MEASURE
+ LASER
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diff --git a/installation/Readme.md b/installation/Readme.md
index 52b7a74..190b526 100644
--- a/installation/Readme.md
+++ b/installation/Readme.md
@@ -1,4 +1,4 @@
-# RFSoC4x2 Setup
+# RFSoC4x2 setup
The RFSoC4x2, as shown in the image below, is a board built and sold by [Real Digital](https://www.realdigital.org/) using AMD’s ZYNQ Ultrascale+ Gen 3 RFSoC ZU48DR chip. While the ZU48DR has 8 DACs and ADCs, the RFSOC4x2 only uses 4x digital to analog converters (5 GSa/s) and 2x analog to digital converters (9.85 GSa/s). Nonetheless, this number of inputs and outputs is nearly perfect for NV and quantum defect control. However, as the RFSOC4x2 is sold, the ADCs have a high frequency 1GHz high-pass balun inline which is tyipcally too high frequency for our measurements and thus must be modified.
@@ -12,10 +12,10 @@ The RFSoC4x2, as shown in the image below, is a board built and sold by [Real Di
In this document we outline setup for using QICK-DAWG with RFSoC4x2. In this guide we show how to:
-1. Setup RFSoC4x2 Hardware
- a. Bipass/Remove the balun & capacitors
- b. Connect the lw frequency differential amplifier
- c. Connect PMOD digial outputs
+1. Setup RFSoC4x2 hardware
+ a. Bypass/remove the balun & capacitors
+ b. Connect the low frequency differential amplifier
+ c. Connect PMOD digital outputs
d. Assembling and powering on your RFSoC4x2 board
e. (Optional) Full enclosure
@@ -27,7 +27,7 @@ In this document we outline setup for using QICK-DAWG with RFSoC4x2. In this gui
-# 1. Setup RFSoC4x2 Hardware
+# 1. Setup RFSoC4x2 hardware
## ***Prerequisites***
- [RFSoC4x2](https://www.xilinx.com/support/university/xup-boards/RFSoC4x2.html) (with 12 volt 50 watt power supply)
@@ -45,9 +45,9 @@ In this document we outline setup for using QICK-DAWG with RFSoC4x2. In this gui
- [Pyro4](https://pypi.org/project/Pyro4/)
- [Serpent](https://pypi.org/project/serpent/)
-## 1a. Bipass/Remove the Balun & Capacitors
+## 1a. Bypass/remove the Balun & Capacitors
-The signal measured by the photodiodes cannot be direcetly connected to the ADCs on the board, thus requiring modification the to the RFSoC4x2. The ADCs on the RFSoC4x2 have baluns and capacitors that act as high pass filters. When using photodiodes for photoluminesence detection, the signal is at low frequency thus the balun and capacitors on the board need to be removed or bipassed in order to get the signal into the ADC. Furthermore, as the ADCs take in a differential voltage signal, we have to add a differential amplifier which takes the signal from the photodetector in and outputs a biased signal to the ADCs for digitization (see section 1.b below).
+The signal measured by the photodiodes cannot be direcetly connected to the ADCs on the board, thus requiring modification the to the RFSoC4x2. The ADCs on the RFSoC4x2 have baluns and capacitors that act as high pass filters. When using photodiodes for photoluminesence detection, the signal is at a low frequency thus the balun and capacitors on the board need to be removed or bypassed in order to get the signal into the ADC. Furthermore, as the ADCs take in a differential double ended voltage signal, we have to add a differential amplifier which takes the single ended signal from the photodetector in and outputs a double ended biased signal to the ADCs for digitization (see section 1.b below).
The input electronics for one ADC channel on the RFSoC4x2 is shown in the figure below.
@@ -60,7 +60,7 @@ The input electronics for one ADC channel on the RFSoC4x2 is shown in the figure
WHERE IS THIS IMAGE CAPTION SHOWING UP.
-The combiation of the Balun, MABA-011118 and the two 100nF capactors (C302 and C303) result in a high pass filter. In order to collect the signal, we need to bypass or remove these components. Our barbaric method is to pull off the balun (under an RF shield) and desolder the capacitors as shown in the following image. The cacpacitors are then replaced with either 2x 0 ohm resistors or 2x short lenghts of wire.
+The combination of the balun, MABA-011118 and the two 100nF capacitors (C302 and C303) result in a high pass filter. In order to collect the signal, we need to bypass or remove these components. Our barbaric method is to pull off the balun (under an RF shield) and desolder the capacitors as shown in the following image. The capacitors are then replaced with either 2x 0 ohm resistors or 2x short lengths of wire.
p) and below (Vm ) a common voltage, Vcm . For full scale, the RFSoC4x2 requires an offset voltage of Vcm = 0.7V (note that this is also true for the ZCU216 evaluation board, but the ZCU111 evaluation board requires Vcm = 1.2 V). Addtionally, the differential amplifier requires two voltages for power, which are optimially set to Vcm + 2.5 = 3.2V and Vcm - 2.5 = -1.8. A labeled diagram of the LMH5401EVN is shown in the figure below.
+To properly condition our signal for digitization, we use a Texas Instruments [Texas Instruments LMH5401 EVM](https://www.digikey.com/en/products/detail/texas-instruments/LMH5401EVM/5031896?s=N4IgTCBcDaIDIFkASBWALABgIwFEBqCIAugL5A) evaluation board. This board takes in one or two signals and outputs two voltages above (Vp ) and below (Vm ) a common voltage, Vcm . For full scale, the RFSoC4x2 requires an offset voltage of Vcm = 0.7V (note that this is also true for the ZCU216 evaluation board, but the ZCU111 evaluation board requires Vcm = 1.2 V). Additionally, the differential amplifier requires two voltages for power, which are optimally set to Vcm + 2.5 = 3.2V and Vcm - 2.5 = -1.8. A labeled diagram of the LMH5401EVN is shown in the figure below.
[1](#RFSoc4x2_Schematic)
Note that you can instead leave the balun in place and directly solder coax cables to the capacitor terminals, however, this is more difficult and it is easy to destroy the capacitor terminals with the solder iron.
-## 1c. Connect PMOD digial outputs
+## 1c. Connect PMOD digital outputs
To control the laser through TTL you must connect your laser to the PMOD located on the corner of the board. To connect, we cut the female head off a PMOD cable and soldered on a female BNC head instead. PMOD A 1-8 are enabled for QICK-DAWG--in the demo we use PMOD 1. The image below provides a schematic of the PMOD on the RFSoC4x2.
@@ -163,7 +163,7 @@ In our lab, we have assembled all the necessary components into a custom rack bo
To connect to your RFSoC4x2, you first need to find the IP address assigned to your board. Conveniently, the RFSoC4x2 has an LED screen on the top of the board that displays the IP address.
Alternatively, you can log into your router and find the IP address and/or assign a static IP address.
-### Copying Necessary Files to the RFSoC4x2 ###
+### Copying necessary files to the RFSoC4x2 ###
We have written our own .bat file and jupyter notebook to streamline the installation process. The first step is to run the .bat file which copies all of the required files to the RFSoC4x2
- Clone qickdawg to your computer
@@ -178,7 +178,7 @@ We have written our own .bat file and jupyter notebook to streamline the install
- run_server and qick_daemon Jupyter Notebook files
- qickdawg speicific firmware
-### Connecting to the Jupyter Server
+### Connecting to the Jupyter server
With the required files copied to your RFSoC4x2, we will now install the required packages by running an .ipynb though the RFSoC4x2's Jupyter Notebook server. To connect to the jupyter notebook server:
- In a browser window type your RFSoC4x2 IP address as shown on the board's LED screen and use password `xilinx` as shown in the graphic below
@@ -203,7 +203,7 @@ With all of hte packages installed, you can now run your pyro server to connect
-- Second, we run the `run_server/qick_daemon.ipynb` notebook, which uploads firmware to the RFSoC4x2 and creates a python socket to communicat with the board. This notebook has a string which contains the path to our alternative firmware and has a `ns_host` variable which needs to be assigned to the ip address of your RFSoC4x2 board.
+- Second, we run the `run_server/qick_daemon.ipynb` notebook, which uploads firmware to the RFSoC4x2 and creates a python socket to communicate with the board. This notebook has a string which contains the path to our alternative firmware and has a `ns_host` variable which needs to be assigned to the ip address of your RFSoC4x2 board.
"
]
@@ -1306,33 +1313,22 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 8,
"metadata": {},
"outputs": [
{
- "name": "stderr",
- "output_type": "stream",
- "text": [
- " 27%|██▋ | 1089788/4000000 [00:21<00:57, 50240.67it/s]\n"
- ]
- },
- {
- "ename": "KeyboardInterrupt",
- "evalue": "",
- "output_type": "error",
- "traceback": [
- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32mc:\\snl\\qickdawg\\jupyter_notebooks\\NVDemo_RFSoC4x2.ipynb Cell 61\u001b[0m line \u001b[0;36m2\n\u001b[0;32m 23 \u001b[0m config\u001b[39m.\u001b[39mreps\u001b[39m=\u001b[39m\u001b[39m10000\u001b[39m\n\u001b[0;32m 25 \u001b[0m prog \u001b[39m=\u001b[39m qd\u001b[39m.\u001b[39mRamsey(config)\n\u001b[1;32m---> 26 \u001b[0m d \u001b[39m=\u001b[39m prog\u001b[39m.\u001b[39;49macquire(progress\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m)\n",
- "File \u001b[1;32mC:\\snl\\qickdawg\\nvpulsing\\ramsey.py:196\u001b[0m, in \u001b[0;36mRamsey.acquire\u001b[1;34m(self, raw_data, *arg, **kwarg)\u001b[0m\n\u001b[0;32m 194\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39macquire\u001b[39m(\u001b[39mself\u001b[39m, raw_data\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m, \u001b[39m*\u001b[39marg, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwarg):\n\u001b[1;32m--> 196\u001b[0m data \u001b[39m=\u001b[39m \u001b[39msuper\u001b[39;49m()\u001b[39m.\u001b[39;49macquire(reads_per_rep\u001b[39m=\u001b[39;49m\u001b[39m4\u001b[39;49m, \u001b[39m*\u001b[39;49marg, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwarg)\n\u001b[0;32m 198\u001b[0m \u001b[39mif\u001b[39;00m raw_data \u001b[39mis\u001b[39;00m \u001b[39mFalse\u001b[39;00m:\n\u001b[0;32m 199\u001b[0m data \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39manalyze_pulse_sequence_results(data)\n",
- "File \u001b[1;32mC:\\snl\\qickdawg\\nvpulsing\\nvaverageprogram.py:241\u001b[0m, in \u001b[0;36mNVAveragerProgram.acquire\u001b[1;34m(self, reads_per_rep, load_pulses, start_src, progress, debug)\u001b[0m\n\u001b[0;32m 238\u001b[0m qd\u001b[39m.\u001b[39msoc\u001b[39m.\u001b[39mstart_readout(total_reps, counter_addr\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mcounter_addr,\n\u001b[0;32m 239\u001b[0m ch_list\u001b[39m=\u001b[39m\u001b[39mlist\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mro_chs), reads_per_rep\u001b[39m=\u001b[39mreads_per_rep)\n\u001b[0;32m 240\u001b[0m \u001b[39mwhile\u001b[39;00m count\u001b[39m<\u001b[39mtotal_count:\n\u001b[1;32m--> 241\u001b[0m new_data \u001b[39m=\u001b[39m obtain(qd\u001b[39m.\u001b[39;49msoc\u001b[39m.\u001b[39;49mpoll_data())\n\u001b[0;32m 242\u001b[0m \u001b[39mfor\u001b[39;00m d, s \u001b[39min\u001b[39;00m new_data:\n\u001b[0;32m 243\u001b[0m \u001b[39m# print(len(new_data), count, total_count)\u001b[39;00m\n\u001b[0;32m 244\u001b[0m new_points \u001b[39m=\u001b[39m d\u001b[39m.\u001b[39mshape[\u001b[39m1\u001b[39m]\n",
- "File \u001b[1;32mc:\\Users\\cint-transport\\.conda\\envs\\testsetup\\Lib\\site-packages\\Pyro4\\core.py:185\u001b[0m, in \u001b[0;36m_RemoteMethod.__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 183\u001b[0m \u001b[39mfor\u001b[39;00m attempt \u001b[39min\u001b[39;00m \u001b[39mrange\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m__max_retries \u001b[39m+\u001b[39m \u001b[39m1\u001b[39m):\n\u001b[0;32m 184\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m--> 185\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m__send(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m__name, args, kwargs)\n\u001b[0;32m 186\u001b[0m \u001b[39mexcept\u001b[39;00m (errors\u001b[39m.\u001b[39mConnectionClosedError, errors\u001b[39m.\u001b[39mTimeoutError):\n\u001b[0;32m 187\u001b[0m \u001b[39m# only retry for recoverable network errors\u001b[39;00m\n\u001b[0;32m 188\u001b[0m \u001b[39mif\u001b[39;00m attempt \u001b[39m>\u001b[39m\u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m__max_retries:\n\u001b[0;32m 189\u001b[0m \u001b[39m# last attempt, raise the exception\u001b[39;00m\n",
- "File \u001b[1;32mc:\\Users\\cint-transport\\.conda\\envs\\testsetup\\Lib\\site-packages\\Pyro4\\core.py:453\u001b[0m, in \u001b[0;36mProxy._pyroInvoke\u001b[1;34m(self, methodname, vargs, kwargs, flags, objectId)\u001b[0m\n\u001b[0;32m 451\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39m# oneway call, no response data\u001b[39;00m\n\u001b[0;32m 452\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m--> 453\u001b[0m msg \u001b[39m=\u001b[39m message\u001b[39m.\u001b[39;49mMessage\u001b[39m.\u001b[39;49mrecv(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_pyroConnection, [message\u001b[39m.\u001b[39;49mMSG_RESULT], hmac_key\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_pyroHmacKey)\n\u001b[0;32m 454\u001b[0m \u001b[39mif\u001b[39;00m config\u001b[39m.\u001b[39mLOGWIRE:\n\u001b[0;32m 455\u001b[0m _log_wiredata(log, \u001b[39m\"\u001b[39m\u001b[39mproxy wiredata received\u001b[39m\u001b[39m\"\u001b[39m, msg)\n",
- "File \u001b[1;32mc:\\Users\\cint-transport\\.conda\\envs\\testsetup\\Lib\\site-packages\\Pyro4\\message.py:168\u001b[0m, in \u001b[0;36mMessage.recv\u001b[1;34m(cls, connection, requiredMsgTypes, hmac_key)\u001b[0m\n\u001b[0;32m 160\u001b[0m \u001b[39m@classmethod\u001b[39m\n\u001b[0;32m 161\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mrecv\u001b[39m(\u001b[39mcls\u001b[39m, connection, requiredMsgTypes\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, hmac_key\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m):\n\u001b[0;32m 162\u001b[0m \u001b[39m \u001b[39m\u001b[39m\"\"\"\u001b[39;00m\n\u001b[0;32m 163\u001b[0m \u001b[39m Receives a pyro message from a given connection.\u001b[39;00m\n\u001b[0;32m 164\u001b[0m \u001b[39m Accepts the given message types (None=any, or pass a sequence).\u001b[39;00m\n\u001b[0;32m 165\u001b[0m \u001b[39m Also reads annotation chunks and the actual payload data.\u001b[39;00m\n\u001b[0;32m 166\u001b[0m \u001b[39m Validates a HMAC chunk if present.\u001b[39;00m\n\u001b[0;32m 167\u001b[0m \u001b[39m \"\"\"\u001b[39;00m\n\u001b[1;32m--> 168\u001b[0m msg \u001b[39m=\u001b[39m \u001b[39mcls\u001b[39m\u001b[39m.\u001b[39mfrom_header(connection\u001b[39m.\u001b[39;49mrecv(\u001b[39mcls\u001b[39;49m\u001b[39m.\u001b[39;49mheader_size))\n\u001b[0;32m 169\u001b[0m msg\u001b[39m.\u001b[39mhmac_key \u001b[39m=\u001b[39m hmac_key\n\u001b[0;32m 170\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39m0\u001b[39m \u001b[39m<\u001b[39m config\u001b[39m.\u001b[39mMAX_MESSAGE_SIZE \u001b[39m<\u001b[39m (msg\u001b[39m.\u001b[39mdata_size \u001b[39m+\u001b[39m msg\u001b[39m.\u001b[39mannotations_size):\n",
- "File \u001b[1;32mc:\\Users\\cint-transport\\.conda\\envs\\testsetup\\Lib\\site-packages\\Pyro4\\socketutil.py:463\u001b[0m, in \u001b[0;36mSocketConnection.recv\u001b[1;34m(self, size)\u001b[0m\n\u001b[0;32m 462\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mrecv\u001b[39m(\u001b[39mself\u001b[39m, size):\n\u001b[1;32m--> 463\u001b[0m \u001b[39mreturn\u001b[39;00m receiveData(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49msock, size)\n",
- "File \u001b[1;32mc:\\Users\\cint-transport\\.conda\\envs\\testsetup\\Lib\\site-packages\\Pyro4\\socketutil.py:171\u001b[0m, in \u001b[0;36mreceiveData\u001b[1;34m(sock, size)\u001b[0m\n\u001b[0;32m 168\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m 169\u001b[0m \u001b[39mwhile\u001b[39;00m msglen \u001b[39m<\u001b[39m size:\n\u001b[0;32m 170\u001b[0m \u001b[39m# 60k buffer limit avoids problems on certain OSes like VMS, Windows\u001b[39;00m\n\u001b[1;32m--> 171\u001b[0m chunk \u001b[39m=\u001b[39m sock\u001b[39m.\u001b[39;49mrecv(\u001b[39mmin\u001b[39;49m(\u001b[39m60000\u001b[39;49m, size \u001b[39m-\u001b[39;49m msglen))\n\u001b[0;32m 172\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m chunk:\n\u001b[0;32m 173\u001b[0m \u001b[39mbreak\u001b[39;00m\n",
- "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
- ]
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "baeb1e8833e34a90b35946a100cdc4af",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ " 0%| | 0/4000000 [00:00, ?it/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
}
],
"source": [
@@ -1368,11 +1364,41 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 9,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "qd.Ramsey.plot_sequence(config)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
- "qd.Ramsey.plot_sequence(config)\n",
"\n",
"t = d.sweep_tus\n",
"x = d.contrast\n",
@@ -1403,9 +1429,30 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 11,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[]"
+ ]
+ },
+ "execution_count": 11,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"t = d.sweep_tus\n",
"x = d.contrast\n",
diff --git a/paper.bib b/paper.bib
new file mode 100644
index 0000000..1f1ac85
--- /dev/null
+++ b/paper.bib
@@ -0,0 +1,126 @@
+
+@article{ Stefanazzi:2022,
+ author = {Stefanazzi, Leandro and Treptow, Kenneth and Wilcer, Neal and Stoughton, Chris and Bradford, Collin and Uemura, Sho and Zorzetti, Silvia and Montella, Salvatore and Cancelo, Gustavo and Sussman, Sara and Houck, Andrew and Saxena, Shefali and Arnaldi, Horacio and Agrawal, Ankur and Zhang, Helin and Ding, Chunyang and Schuster, David I.},
+ title = "{The QICK (Quantum Instrumentation Control Kit): Readout and control for qubits and detectors}",
+ journal = {Review of Scientific Instruments},
+ volume = {93},
+ number = {4},
+ pages = {044709},
+ year = {2022},
+ month = {04},
+ issn = {0034-6748},
+ doi = {10.1063/5.0076249}
+}
+
+@misc{Bourdeauducq:2016,
+url={https://zenodo.org/records/51303},
+ title={ARTIQ 1.0 (1.0)},
+ author={Bourdeauducq, Sebastian and J{\"o}rdens, R and Zotov, P and Britton, J and Slichter, D and Leibrandt, D and Allcock, D and Hankin, A and Kermarrec, F and Sionneau, Y and others},
+ year={2016},
+ publisher={Zenodo}
+}
+
+@article{ Xu:2023,
+author = {Xu, Yilun and Huang, Gang and Balewski, Jan and Morvan, Alexis and Nowrouzi, Kasra and Santiago, David I. and Naik, Ravi K. and Mitchell, Brad and Siddiqi, Irfan},
+title = {Automatic Qubit Characterization and Gate Optimization with QubiC},
+year = {2022},
+issue_date = {March 2023},
+publisher = {Association for Computing Machinery},
+address = {New York, NY, USA},
+volume = {4},
+number = {1},
+doi = {10.1145/3529397},
+abstract = {As the size and complexity of a quantum computer increases, quantum bit (qubit) characterization and gate optimization become complex and time-consuming tasks. Current calibration techniques require complicated and verbose measurements to tune up qubits and gates, which cannot easily expand to the large-scale quantum systems. We develop a concise and automatic calibration protocol to characterize qubits and optimize gates using QubiC, which is an open source FPGA (field-programmable gate array)-based control and measurement system for superconducting quantum information processors. We propose multi-dimensional loss-based optimization of single-qubit gates and full XY-plane measurement method for the two-qubit CNOT gate calibration. We demonstrate the QubiC automatic calibration protocols are capable of delivering high-fidelity gates on the state-of-the-art transmon-type processor operating at the Advanced Quantum Testbed at Lawrence Berkeley National Laboratory. The single-qubit and two-qubit Clifford gate infidelities measured by randomized benchmarking are of 4.9(1.1) \texttimes{} 10-4 and 1.4(3) \texttimes{} 10-2, respectively.},
+journal = {ACM Transactions on Quantum Computing},
+month = {oct},
+articleno = {3},
+numpages = {12},
+keywords = {engineering software, quantum gate calibration, FPGA, qubit control, NISQ, gateware}
+}
+
+@INPROCEEDINGS{Kulik:2022,
+ author={Kulik, Paweł and Sowiński, Mikołaj and Kasprowicz, Grzegorz and Allcock, David and Ballance, Christopher and Bourdeauducq, Sébastien and Britton, Joseph and Gąska, Michał and Harty, Thomas and Jarosiński, Jakub and Jördens, Robert and Kiepiela, Marcin and Krackow, Norman and Nadlinger, David and Poźniak, Krzysztof and Przywózki, Tomasz and Slichter, Daniel and Świtakowski, Filip and Weber, Marius and Wojciechowski, Andrzej and Zhang, Weida},
+ booktitle={2022 IEEE International Conference on Quantum Computing and Engineering (QCE)},
+ title={Latest developments in the Sinara open hardware ecosystem},
+ year={2022},
+ volume={},
+ number={},
+ pages={799-802},
+ doi={10.1109/QCE53715.2022.00123}}
+
+@article{Shammah:2023,
+ title={Open Hardware in Quantum Technology},
+ author={Shammah, Nathan and Roy, Anurag Saha and Almudever, Carmen G and Bourdeauducq, S{\'e}bastien and Butko, Anastasiia and Cancelo, Gustavo and Clark, Susan M and Heinsoo, Johannes and Henriet, Lo{\"\i}c and Huang, Gang and others},
+ journal={arXiv preprint arXiv:2309.17233},
+ year={2023},
+ doi={10.48550/arXiv.2309.17233}
+}
+
+
+@article{Butcher:2019,
+ title={Quantum diamond spectrometer for nanoscale NMR and ESR spectroscopy},
+ author={Bucher, Dominik B and Aude Craik, Diana PL and Backlund, Mikael P and Turner, Matthew J and Ben Dor, Oren and Glenn, David R and Walsworth, Ronald L},
+ journal={Nature Protocols},
+ volume={14},
+ number={9},
+ pages={2707--2747},
+ year={2019},
+ publisher={Nature Publishing Group UK London},
+ doi={10.5281/zenodo.1478113}
+}
+
+@article{Casola:2018,
+ title={Probing condensed matter physics with magnetometry based on nitrogen-vacancy centres in diamond},
+ author={Casola, Francesco and Van Der Sar, Toeno and Yacoby, Amir},
+ journal={Nature Reviews Materials},
+ volume={3},
+ number={1},
+ pages={1--13},
+ year={2018},
+ publisher={Nature Publishing Group},
+ doi={10.1038/natrevmats.2017.88}
+}
+@article{Henshaw:2023,
+doi = {10.1088/2633-4356/ace095},
+year = {2023},
+month = {jul},
+publisher = {IOP Publishing},
+volume = {3},
+number = {3},
+pages = {035001},
+author = {Jacob Henshaw and Pauli Kehayias and Luca Basso and Michael Jaris and Rong Cong and Michael Titze and {Tzu Ming} Lu and Michael P Lilly and Andrew M Mounce},
+title = {Mitigation of nitrogen vacancy photoluminescence quenching from material integration for quantum sensing},
+journal = {Materials for Quantum Technology },
+abstract = {The nitrogen-vacancy (NV) color center in diamond has demonstrated great promise in a wide range of quantum sensing. Recently, there have been a series of proposals and experiments using NV centers to detect spin noise of quantum materials near the diamond surface. This is a rich complex area of study with novel nano-magnetism and electronic behavior, that the NV center would be ideal for sensing. However, due to the electronic properties of the NV itself and its host material, getting high quality NV centers within nanometers of such systems is challenging. Band bending caused by space charges formed at the metal-semiconductor interface force the NV center into its insensitive charge states. Here, we investigate optimizing this interface by depositing thin metal films and thin insulating layers on a series of NV ensembles at different depths to characterize the impact of metal films on different ensemble depths. We find an improvement of coherence and dephasing times we attribute to ionization of other paramagnetic defects. The insulating layer of alumina between the metal and diamond provide improved photoluminescence and higher sensitivity in all modes of sensing as compared to direct contact with the metal, providing as much as a factor of 2 increase in sensitivity, decrease of integration time by a factor of 4, for NV T 1 relaxometry measurements.}
+}
+
+@article{Henshaw:2022,
+ title={Nanoscale solid-state nuclear quadrupole resonance spectroscopy using depth-optimized nitrogen-vacancy ensembles in diamond},
+ author={Henshaw, Jacob and Kehayias, Pauli and Saleh Ziabari, Maziar and Titze, Michael and Morissette, Erin and Watanabe, Kenji and Taniguchi, Takashi and Li, JIA and Acosta, Victor M and Bielejec, Edward S and others},
+ journal={Applied Physics Letters},
+ volume={120},
+ number={17},
+ year={2022},
+ publisher={AIP Publishing},
+ doi={10.1063/5.0083774}
+}
+@article{Wang:2022,
+ title={Noninvasive measurements of spin transport properties of an antiferromagnetic insulator},
+ author={Wang, Hailong and Zhang, Shu and McLaughlin, Nathan J and Flebus, Benedetta and Huang, Mengqi and Xiao, Yuxuan and Liu, Chuanpu and Wu, Mingzhong and Fullerton, Eric E and Tserkovnyak, Yaroslav and others},
+ journal={Science advances},
+ volume={8},
+ number={1},
+ pages={eabg8562},
+ year={2022},
+ publisher={American Association for the Advancement of Science},
+ doi={10.1126/sciadv.abg8562}
+}
+@ARTICLE{Xu:2021,
+ author={Xu, Yilun and Huang, Gang and Balewski, Jan and Naik, Ravi and Morvan, Alexis and Mitchell, Bradley and Nowrouzi, Kasra and Santiago, David I. and Siddiqi, Irfan},
+ journal={IEEE Transactions on Quantum Engineering},
+ title={QubiC: An Open-Source FPGA-Based Control and Measurement System for Superconducting Quantum Information Processors},
+ year={2021},
+ volume={2},
+ number={},
+ pages={1-11},
+ doi={10.1109/TQE.2021.3116540}}
diff --git a/paper.md b/paper.md
new file mode 100644
index 0000000..18f2ca7
--- /dev/null
+++ b/paper.md
@@ -0,0 +1,87 @@
+---
+title: 'Quantum Instrumentation Control Kit – Defect Arbitrary Waveform Generator (QICK-DAWG): A Quantum Sensing Control Framework for Quantum Defects'
+tags:
+ - QICK
+ - Nitrogen-Vacancy Centers
+ - NVs
+ - quantum defect characterization
+ - RFSoC4x2
+authors:
+- name: E. G. Riendeau
+ corresponding: emmelineriendeau@gmail.com
+ orcid: 0000-0002-0460-873X
+ affiliation: "1, 2" # (Multiple affiliations must be quoted)
+- name: L. Basso
+ affiliation: 2
+- name: J. J. Mah
+ affiliation: "2,3"
+- name: R. Cong
+ affiliation: "2,3"
+- name: M. A. Sadi
+ affiliation: "2,4"
+- name: J. Henshaw
+ affiliation: 2
+- name: K. M. Azizur-Rahman
+ affiliation: 2
+- name: A. Jones
+ affiliation: "2,5"
+- name: G. Joshi
+ affiliation: 2
+- name: M. P. Lilly
+ affiliation: 2
+- name: A. M. Mounce
+ corresponding: amounce@sandia.gov
+ orcid: 0000-0002-8115-2764
+ affiliation: 2
+affiliations:
+- name: Haverford College, US
+ index: 1
+- name: Center for Integrated Nanotechnologies (CINT), Sandia National Laboratories, US
+ index: 2
+- name: Brown University, US
+ index: 3
+- name: Purdue University, US
+ index: 4
+- name: Georgia Institute of Technology, US
+ index: 5
+date: 27 November 2023
+bibliography: paper.bib
+---
+
+# Summary
+The Quantum Instrumentation Control Kit - Defect Arbitrary Waveform Generator (QICK-DAWG), is an open-source software and firmware package for full quantum control and measurement of nitrogen-vacancy (NV) color-centers in diamond and other quantum defects in semiconductor materials for quantum sensing. QICK-DAWG extends the capabilities of the Quantum Instrumentation Control Kit (QICK, an open-source qubit firmware and software package) to quantum defects by implementing controlled laser pulsing and low frequency readout required for defect initialization, control, and measurement using recently available Radio Frequency System-on-Chip (RFSoC) Field Programmable Gate Arrays (FPGA). In addition to user-friendly software and firmware, QICK-DAWG adds documentation that guides users through hardware setup.
+
+Specifically, the QICK-DAWG package consists of FPGA firmware (modified from the original QICK firmware compiled in Vivado), Python software (that extends QICK for specific pulse programs and altered functionality), instructions for installation and hardware modifications, and a demo Jupyter Notebook . QICK-DAWG’s measurement programs consist of specific microwave, laser, and readout pulse sequences built in QICK’s Python framework for consistency and extensibility. Pulse sequence programs and data analysis scripts are included to collect and characterize photoluminescence (PL) intensity, optically detected magnetic resonance (ODMR) spectra, PL readout windows, Rabi oscillations, Ramsey interference spectra, Hahn echo spin-spin relaxation times T2, and spin-lattice relaxation times T1. Additional pulse sequence programs and data analysis scripts will be added in the future. QICK-DAWG also implements live-update of plots for PL intensities to optimize laser alignment, broadband ODMR spectra for magnetic field alignment, and Rabi oscillations to optimize microwave antenna alignment or positioning. A setup Readme.md file walks users through rudimentary hardware setup, installation, and modification required for low frequency data collection using RealDigital’s RFSoC4x2. The package also has a batch file with directions for easy installation setup for the RFSoC Linux kernel that drives firmware, controls, and reads from the FPGA for offline installation of packages. The demo Jupyter Notebook walks users through typical experimental flow and the configuration of each pulse sequence. Each measurement program includes a method that checks whether all required configurations for pulsing programs are present and a method which provides a visual representation of the plot sequence. Ultimately, QICK-DAWG is an extensible firmware and software package for quantum sensing using NV color-centers in diamond and other quantum defects using one control hub for consistency among different experimental setups or laboratories.
+
+# Related Work
+
+Recent open-source software and commercially available RFSoC FPGA evaluation boards provide a strong foundation for developing an open-source control measurement, software, and firmware package for NVs and other diamond quantum defects. Open-source software packages for quantum control and data acquisition such as ARTIQ [@Bourdeauducq:2016], Qubic [@Xu:2023], and QICK [@Stefanazzi:2022] have been continually developed over the past decade for a variety of quantum experiments. These packages have been developed in response to the shortcoming in both in-house and existing commercial based quantum control systems. Focusing on hardware, recently available RFSoC FPGAs including Xilinx’s ZCU216, Xilinx’s ZCU111 and Real Digital’s RFSoC4x2 can generate control pulses at high frequencies (6–10GHz) and digitize signals from photodiodes and single photon detector modules at high sample rates. The precise high-frequency pulse generation, readout capability, compact size, and relatively low cost of these RFSoC FPGAs make them ideal candidates for defect control hardware.
+
+QICK provides firmware, a high-level Python user interface, and accessible inexpensive hardware making it an ideal platform for extension. Both QICK and Qubic utilize RFSoC FPGAs, however only QICK provides firmware for Real Digital’s RFSoC4x2, the lowest cost commercial off the shelf FPGA board. QICK also provides a high-level Python user interface that supports rapid implementation and simple in lab parameter modification . Additionally, QICK is already a popular software package; QICK has been applied to superconducting, spin, atomic, molecular, and optical qubit systems, and has reached 40 labs in the last two years [@Shammah:2023]. Simple modification to QICK firmware, hardware and software is necessary for implementation of QICK in spin-based quantum control experiments like NVs and other diamond quantum defects. QICK-DAWG implements these modifications, extending QICK.
+
+
+
+# Statement of need
+Open quantum hardware (OQH ) is a broad category that covers the open-source tools and components needed to build and control quantum computers, technologies, and sensors. OQH has the potential to accelerate quantum research, quantum technology development, and increase accessibility of quantum computing and quantum sensing. The specific area of OQH that QICK-DAWG fills is open-source instrumentation, control, and data acquisition software.
+
+Currently, quantum sensing with quantum defects is accomplished by research groups assembling their own hardware consisting of many different instruments and creating their own software to control them [@Butcher:2019]. Timing between instruments, such as microwave generators and switches, arbitrary waveform generators, digital to analog converters, and/or photon counters, is typically provided by a fast FPGA TTL generator triggering independent instruments which can lead to timing offsets that must be accounted for. Thus, there is a lack of consistency in hardware and software for quantum defect-based quantum sensing, a niche that QICK-DAWG fills, in addition to simplified operation as all functionality happens on a single instrument’s timing.
+
+QICK-DAWG increases accessibility to NV and defect research through its open-source nature, reduced hardware cost, high-level Python-based user interface, and extensive documentation. In the included documentation and demo, the QICK-DAWG package utilizes the Real Digital RFSoC4x2 as this particular SoC has a relatively low cost. Thus, QICK-DAWG lowers the cost of entry for quantum sensing with RFSoCs by as much as an order of magnitude. QICK-DAWG implementation requires some rudimentary hardware modification and additional hardware that is detailed in the installation Readme document. Thus, QICK-DAWG supports full quantum control and data acquisition of NV centers and other diamond quantum defects—a spin-based open-source software niche not yet filled. Furthermore, through reduced equipment costs, high-level Python user interface, and extensive documentation, QICK-DAWG makes NV quantum measurements accessible to academic and small labs and does not require extensive background knowledge in quantum control hardware.
+
+# Current Implementation
+
+At Sandia National Laboratories, we are currently using QICK-DAWG to characterize ensembles of both NVs in diamond and boron-vacancy defects in hexagonal boron nitride. These quantum defects are characterized for PL intensity, T*2, T2, and T1. We characterize both the intrinsic properties of these quantum defects and dependent properties which change in the presence of other materials of interest, i.e., in a quantum sensing experiment. These methods allow us to understand the spin properties of low dimensional materials which cannot be accessed by traditional spin probes [@Henshaw:2023][@Henshaw:2022][@Casola:2018][@Wang:2022].
+
+
+# Acknowledgements
+
+We thank S. Uemura and S. Sussman for helping to modify QICK firmware and guidance on using QICK. We would also like to acknowledge J. Feder, J. Heremans, C. Yao, E. Henriksen, F. Balakirev, and J. Kitzman for inspirational and technical discussions.
+
+Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia (NTESS), LLC, a wholly owned subsidiary of Honeywell International, Inc., for the DOE’s National Nuclear Security Administration under contract DE-NA0003525. This work was funded, in part, by the Laboratory Directed Research and Development Program and performed, in part, at the Center for Integrated Nanotechnologies, an Office of Science User Facility operated for the U.S. Department of Energy (DOE) Office of Science. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government.
+
+This work was supported in part by the U.S. Department of Energy, Office of Science, Office of Workforce Development for Teachers and Scientists (WDTS) under the Science Undergraduate Laboratory Internships Program (SULI). This work was performed, in part, at the Center for Integrated Nanotechnologies (CINT), an Office of Science User Facility operated for the U.S. Department of Energy (DOE) Office of Science.
+
+
+
+# References
+
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