Docs preview for PR #2443.

Author: cuda-quantum-bot

pr-2443/applications/python/deutschs_algorithm.html

@@ -822,7 +822,7 @@ <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="609149f06d0e4042ba7574b69e25a4e7" class="no-scaled-link" src="../../_images/oracle.png" style="width: 300px; height: 150px;" /></p>
+<p><img alt="3f66a7b670c24291b82cd12bc42f523d" 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">
@@ -870,7 +870,7 @@ <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="d5360b19e1f04949819a5370fee8deb2" class="no-scaled-link" src="../../_images/deutsch.png" style="width: 500px; height: 210px;" /></p>
+<p><img alt="934726e23b39472685ceacde39a5528e" 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-2443/examples/python/executing_photonic_kernels.html

@@ -806,7 +806,7 @@ <h2>Sample<a class="headerlink" href="#Sample" title="Permalink to this heading"
 </div>
 <div class="output_area docutils container">
 <div class="highlight"><pre>
-{ 02:370 11:237 20:393 }
+{ 02:407 11:266 20:327 }
 
 </pre></div></div>
 </div>
@@ -894,7 +894,7 @@ <h2>Parallelization Techniques<a class="headerlink" href="#Parallelization-Techn
 </div>
 <div class="output_area docutils container">
 <div class="highlight"><pre>
-CUDA-Q Version  (https://github.com/NVIDIA/cuda-quantum e04b6f8ac7bd53bcf457e1bc12ffb838c707cf2f)
+CUDA-Q Version  (https://github.com/NVIDIA/cuda-quantum 2010d9904b679a4ef158ee79f5237b636cc75d03)
 </pre></div></div>
 </div>
 </section>

pr-2443/examples/python/executing_photonic_kernels.ipynb

@@ -23,10 +23,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2025-01-29T19:16:50.239874Z",
-     "iopub.status.busy": "2025-01-29T19:16:50.239557Z",
-     "iopub.status.idle": "2025-01-29T19:16:53.131780Z",
-     "shell.execute_reply": "2025-01-29T19:16:53.131298Z"
+     "iopub.execute_input": "2025-01-31T14:04:24.034241Z",
+     "iopub.status.busy": "2025-01-31T14:04:24.034066Z",
+     "iopub.status.idle": "2025-01-31T14:04:27.127070Z",
+     "shell.execute_reply": "2025-01-31T14:04:27.126432Z"
     }
    },
    "outputs": [
@@ -42,7 +42,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{ 02:370 11:237 20:393 }\n",
+      "{ 02:407 11:266 20:327 }\n",
       "\n"
      ]
     }
@@ -95,10 +95,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2025-01-29T19:16:53.134155Z",
-     "iopub.status.busy": "2025-01-29T19:16:53.133622Z",
-     "iopub.status.idle": "2025-01-29T19:16:53.179244Z",
-     "shell.execute_reply": "2025-01-29T19:16:53.178420Z"
+     "iopub.execute_input": "2025-01-31T14:04:27.129339Z",
+     "iopub.status.busy": "2025-01-31T14:04:27.128902Z",
+     "iopub.status.idle": "2025-01-31T14:04:27.172872Z",
+     "shell.execute_reply": "2025-01-31T14:04:27.171885Z"
     }
    },
    "outputs": [
@@ -183,18 +183,18 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2025-01-29T19:16:53.181509Z",
-     "iopub.status.busy": "2025-01-29T19:16:53.181183Z",
-     "iopub.status.idle": "2025-01-29T19:16:53.184990Z",
-     "shell.execute_reply": "2025-01-29T19:16:53.184405Z"
+     "iopub.execute_input": "2025-01-31T14:04:27.175283Z",
+     "iopub.status.busy": "2025-01-31T14:04:27.174999Z",
+     "iopub.status.idle": "2025-01-31T14:04:27.178622Z",
+     "shell.execute_reply": "2025-01-31T14:04:27.178028Z"
     }
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CUDA-Q Version  (https://github.com/NVIDIA/cuda-quantum e04b6f8ac7bd53bcf457e1bc12ffb838c707cf2f)\n"
+      "CUDA-Q Version  (https://github.com/NVIDIA/cuda-quantum 2010d9904b679a4ef158ee79f5237b636cc75d03)\n"
      ]
     }
    ],

pr-2443/examples/python/performance_optimizations.html

@@ -750,9 +750,9 @@ <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="75c22214af77446aad9d2e9487053221" src="../../_images/gate-fuse.png" /></p>
+<p><img alt="90d26d60a0574a589d134388579812aa" 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="07511b96bf1b45409a17d38f6a865800" src="../../_images/gatefusion.png" /></p>
+<p><img alt="3800788cfea14e859ce4f80b28b63183" src="../../_images/gatefusion.png" /></p>
 </section>
 </section>