Docs preview for PR #1015.

pr-1015/_sources/using/quick_start.rst.txt

@@ -6,7 +6,7 @@ Quick Start
 CUDA-Q streamlines hybrid application development and promotes productivity and scalability
 in quantum computing. It offers a unified programming model designed for a hybrid
 setting |---| that is, CPUs, GPUs, and QPUs working together. CUDA-Q contains support for 
-programming in Python and in C++. Learn more about the `key benefits of CUDA-Q <https://developer.nvidia.com/cuda-q>__`.
+programming in Python and in C++. Learn more about the `key benefits of CUDA-Q <https://developer.nvidia.com/cuda-q>`_.
 
 This Quick Start page guides you through installing CUDA-Q and running your first program.
 If you have already installed and configured CUDA-Q, or if you are using our 

pr-1015/api/languages/python_api.html

@@ -1698,7 +1698,7 @@ <h2>Data Types<a class="headerlink" href="#data-types" title="Permalink to this
 <em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">random</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#cudaq.SpinOperator.random" title="Permalink to this definition">¶</a></dt>
 <dd><dl class="py function">
 <dt class="sig sig-object py">
-<span class="sig-name descname"><span class="pre">random</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">qubit_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">term_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">722962623</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#cudaq.SpinOperator" title="cudaq.mlir._mlir_libs._quakeDialects.cudaq_runtime.SpinOperator"><span class="pre">cudaq.mlir._mlir_libs._quakeDialects.cudaq_runtime.SpinOperator</span></a></span></span></dt>
+<span class="sig-name descname"><span class="pre">random</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">qubit_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">term_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">150753240</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#cudaq.SpinOperator" title="cudaq.mlir._mlir_libs._quakeDialects.cudaq_runtime.SpinOperator"><span class="pre">cudaq.mlir._mlir_libs._quakeDialects.cudaq_runtime.SpinOperator</span></a></span></span></dt>
 <dd></dd></dl>
 
 <p>Return a random <a class="reference internal" href="#cudaq.SpinOperator" title="cudaq.SpinOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">SpinOperator</span></code></a> on the given number of qubits (<code class="code docutils literal notranslate"><span class="pre">qubit_count</span></code>) and composed of the given number of terms (<code class="code docutils literal notranslate"><span class="pre">term_count</span></code>). An optional seed value may also be provided.</p>

pr-1015/examples/python/tutorials/deutschs_algorithm.html

@@ -593,7 +593,7 @@ <h2>XOR <span class="math notranslate nohighlight">\(\oplus\)</span><a class="he
 </section>
 <section id="Quantum-oracles">
 <h2>Quantum oracles<a class="headerlink" href="#Quantum-oracles" title="Permalink to this heading">¶</a></h2>
-<p><img alt="cbcb56d32c414149b9b6fbb8a611d9c1" class="no-scaled-link" src="../../../_images/oracle.png" style="width: 300px; height: 150px;" /></p>
+<p><img alt="f05142b6966d41ba927394043565f38b" class="no-scaled-link" src="../../../_images/oracle.png" style="width: 300px; height: 150px;" /></p>
 <p>Suppose we have <span class="math notranslate nohighlight">\(f(x): \{0,1\} \longrightarrow \{0,1\}\)</span>. We can compute this function on a quantum computer using oracles which we treat as black box functions that yield the output with an appropriate sequence of logic gates.</p>
 <p>Above you see an oracle represented as <span class="math notranslate nohighlight">\(U_f\)</span> which allows us to transform the state <span class="math notranslate nohighlight">\(\ket{x}\ket{y}\)</span> into:</p>
 <div class="math notranslate nohighlight">
@@ -641,7 +641,7 @@ <h2>Quantum parallelism<a class="headerlink" href="#Quantum-parallelism" title="
 <h2>Deutschs’ Algorithm:<a class="headerlink" href="#Deutschs'-Algorithm:" title="Permalink to this heading">¶</a></h2>
 <p>Our aim is to find out if <span class="math notranslate nohighlight">\(f: \{0,1\} \longrightarrow \{0,1\}\)</span> is a constant or a balanced function? If constant, <span class="math notranslate nohighlight">\(f(0) = f(1)\)</span>, and if balanced, <span class="math notranslate nohighlight">\(f(0) \neq f(1)\)</span>.</p>
 <p>We step through the circuit diagram below and follow the math after the application of each gate.</p>
-<p><img alt="be3b36104e014640be4244d0a89cd209" class="no-scaled-link" src="../../../_images/deutsch.png" style="width: 500px; height: 210px;" /></p>
+<p><img alt="4dd137c06232424bb13c92090aa0329c" class="no-scaled-link" src="../../../_images/deutsch.png" style="width: 500px; height: 210px;" /></p>
 <div class="math notranslate nohighlight">
 \[\ket{\psi_0}  =  \ket{01}
 \tag{1}\]</div>

pr-1015/sphinx/using/quick_start.rst

@@ -6,7 +6,7 @@ Quick Start
 CUDA-Q streamlines hybrid application development and promotes productivity and scalability
 in quantum computing. It offers a unified programming model designed for a hybrid
 setting |---| that is, CPUs, GPUs, and QPUs working together. CUDA-Q contains support for 
-programming in Python and in C++. Learn more about the `key benefits of CUDA-Q <https://developer.nvidia.com/cuda-q>__`.
+programming in Python and in C++. Learn more about the `key benefits of CUDA-Q <https://developer.nvidia.com/cuda-q>`_.
 
 This Quick Start page guides you through installing CUDA-Q and running your first program.
 If you have already installed and configured CUDA-Q, or if you are using our 

pr-1015/using/quick_start.html

@@ -519,7 +519,7 @@ <h1>Quick Start<a class="headerlink" href="#quick-start" title="Permalink to thi
 <p>CUDA-Q streamlines hybrid application development and promotes productivity and scalability
 in quantum computing. It offers a unified programming model designed for a hybrid
 setting—that is, CPUs, GPUs, and QPUs working together. CUDA-Q contains support for
-programming in Python and in C++. Learn more about the <code class="code docutils literal notranslate"><span class="pre">key</span> <span class="pre">benefits</span> <span class="pre">of</span> <span class="pre">CUDA-Q</span> <span class="pre">&lt;https://developer.nvidia.com/cuda-q&gt;__</span></code>.</p>
+programming in Python and in C++. Learn more about the <a class="reference external" href="https://developer.nvidia.com/cuda-q">key benefits of CUDA-Q</a>.</p>
 <p>This Quick Start page guides you through installing CUDA-Q and running your first program.
 If you have already installed and configured CUDA-Q, or if you are using our
 <a class="reference external" href="https://catalog.ngc.nvidia.com/orgs/nvidia/teams/quantum/containers/cuda-quantum">Docker image</a>, you can move directly to our