Docs preview for PR #2652.

Author: cuda-quantum-bot

pr-2652/applications/python/deutschs_algorithm.html

@@ -816,7 +816,7 @@ <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="75844093ed2145b48764f5e7d7b55ae3" class="no-scaled-link" src="../../_images/oracle.png" style="width: 300px; height: 150px;" /></p>
+<p><img alt="77e89a9b37e74f63899e9d723ffd7c8f" 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 logical 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">
@@ -864,7 +864,7 @@ <h2>Quantum parallelism<a class="headerlink" href="#Quantum-parallelism" title="
 <h2>Deutsch’s Algorithm:<a class="headerlink" href="#Deutsch's-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="10a9e32a839b45a1ae7673e09c01708d" class="no-scaled-link" src="../../_images/deutsch.png" style="width: 500px; height: 210px;" /></p>
+<p><img alt="3856154ce9564691955db1da09a74afd" 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-2652/examples/python/performance_optimizations.html

@@ -744,9 +744,9 @@ <h1>Optimizing Performance<a class="headerlink" href="#Optimizing-Performance" t
 <section id="Gate-Fusion">
 <h2>Gate Fusion<a class="headerlink" href="#Gate-Fusion" title="Permalink to this heading">¶</a></h2>
 <p>Gate fusion is an optimization technique where consecutive gates are combined into a single gate operation to improve the efficiency of the simulation (See figure below). By targeting the <code class="docutils literal notranslate"><span class="pre">nvidia-mgpu</span></code> backend and setting the <code class="docutils literal notranslate"><span class="pre">CUDAQ_MGPU_FUSE</span></code> environment variable, you can select the degree of fusion that takes place. A full command line example would look like <code class="docutils literal notranslate"><span class="pre">CUDAQ_MGPU_FUSE=4</span> <span class="pre">python</span> <span class="pre">c2h2VQE.py</span> <span class="pre">--target</span> <span class="pre">nvidia</span> <span class="pre">--target-option</span> <span class="pre">fp64,mgpu</span></code></p>
-<p><img alt="dc6fe5e9ed36479c9f82f04ea2559668" src="../../_images/gate-fuse.png" /></p>
+<p><img alt="0308202131fb457a97f4f5035b752a60" src="../../_images/gate-fuse.png" /></p>
 <p>The importance of gate fusion is system dependent, but can have a large influence on the performance of the simulation. See the example below for a 24 qubit VQE experiment where changing the fusion level resulted in significant performance boosts.</p>
-<p><img alt="d863a37c4beb45568f1bdf434e843682" src="../../_images/gatefusion.png" /></p>
+<p><img alt="23f01031402548258365d35197dd63ea" src="../../_images/gatefusion.png" /></p>
 </section>
 </section>