Docs preview for PR #2696.

Author: cuda-quantum-bot

pr-2696/applications/python/adapt_qaoa.html

@@ -783,7 +783,7 @@ <h1>ADAPT-QAOA algorithm<a class="headerlink" href="#ADAPT-QAOA-algorithm" title
 parameter</p>
 <p>3- Optimize all parameters currently in the Ansatz <span class="math notranslate nohighlight">\(\beta_m, \gamma_m = 1, 2, ...k\)</span> such that <span class="math notranslate nohighlight">\(\braket{\psi (k)|H_C|\psi(k)}\)</span> is minimized, and return to the second step.</p>
 <p>Below is a schematic representation of the ADAPT-QAOA algorithm explained above.</p>
-<div><p><img alt="601490213c3644a8bba7f0d7d0aef9fb" class="no-scaled-link" src="../../_images/adapt-qaoa.png" style="width: 600px;" /></p>
+<div><p><img alt="68e1c097c83d4b9ab4f7989632a57d55" class="no-scaled-link" src="../../_images/adapt-qaoa.png" style="width: 600px;" /></p>
 </div><div class="nbinput nblast docutils container">
 <div class="prompt highlight-none notranslate"><div class="highlight"><pre><span></span>[ ]:
 </pre></div>

pr-2696/applications/python/deutschs_algorithm.html

@@ -840,7 +840,7 @@ <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="fb50401d8ef94028bd914d92482a4411" class="no-scaled-link" src="../../_images/oracle.png" style="width: 300px; height: 150px;" /></p>
+<p><img alt="bf3ef2a5105a4b349c5ea212198d73b6" 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">
@@ -888,7 +888,7 @@ <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="db3dfe731d1b4d5e9f7fd3cda0f0ac2b" class="no-scaled-link" src="../../_images/deutsch.png" style="width: 500px; height: 210px;" /></p>
+<p><img alt="a3c21de12b9a45358c9445af9c9ed781" 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-2696/applications/python/quantum_transformer.html

@@ -768,9 +768,9 @@ <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="053ae4633c2041e6ab7a2f0e95ea1d6a" src="../../_images/gate-fuse.png" /></p>
+<p><img alt="bea79f1ecfd542dd8e8c8489a9505580" 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="d4cd70572555472abac4f276cd35d2f1" src="../../_images/gatefusion.png" /></p>
+<p><img alt="02038969bae947dab37f75e4762cc14a" src="../../_images/gatefusion.png" /></p>
 </section>
 </section>
 

pr-2696/examples/python/performance_optimizations.html

@@ -113,12 +113,12 @@ def print_results(success, failed, skipped=[]):
             base_name = os.path.basename(notebook_filename)
             if base_name in notebooks_skipped:
                 continue  # Already skipped, no need to re-check
-            if validate(notebook_filename, available_backends):
-                if execute(notebook_filename):
-                    notebooks_success.append(notebook_filename)
-                else:
-                    notebooks_failed.append(notebook_filename)
-            else:
+            if not validate(notebook_filename, available_backends):
                 notebooks_skipped.append(base_name)
+                continue
+            if execute(notebook_filename):
+                notebooks_success.append(notebook_filename)
+            else:
+                notebooks_failed.append(notebook_filename)
 
         print_results(notebooks_success, notebooks_failed, notebooks_skipped)