Docs preview for PR #2533.

Author: cuda-quantum-bot

pr-2533/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="988afb67f4334360acd2cf5afdb22507" class="no-scaled-link" src="../../_images/oracle.png" style="width: 300px; height: 150px;" /></p>
+<p><img alt="d4567170ed2944bc8fa768123cff21d4" 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="3ae66d34086a42c4a2c05e05ff0240e6" class="no-scaled-link" src="../../_images/deutsch.png" style="width: 500px; height: 210px;" /></p>
+<p><img alt="24076f16504644b691d00790397b4ff6" 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-2533/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>
-{ 02:379 11:255 20:366 }
+{ 02:347 11:277 20:376 }
 
 </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 8505897ac27b90e4f1947966369f35184f7f3632)
+CUDA-Q Version  (https://github.com/NVIDIA/cuda-quantum c7f284926382599dbb3494269d41d6ba2b972c06)
 </pre></div></div>
 </div>
 </section>

pr-2533/examples/python/executing_photonic_kernels.ipynb

@@ -23,10 +23,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2025-01-31T08:36:28.826553Z",
-     "iopub.status.busy": "2025-01-31T08:36:28.826393Z",
-     "iopub.status.idle": "2025-01-31T08:36:31.532710Z",
-     "shell.execute_reply": "2025-01-31T08:36:31.531647Z"
+     "iopub.execute_input": "2025-02-02T09:30:02.077569Z",
+     "iopub.status.busy": "2025-02-02T09:30:02.077236Z",
+     "iopub.status.idle": "2025-02-02T09:30:04.695467Z",
+     "shell.execute_reply": "2025-02-02T09:30:04.695036Z"
     }
    },
    "outputs": [
@@ -42,7 +42,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{ 02:379 11:255 20:366 }\n",
+      "{ 02:347 11:277 20:376 }\n",
       "\n"
      ]
     }
@@ -95,10 +95,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2025-01-31T08:36:31.535230Z",
-     "iopub.status.busy": "2025-01-31T08:36:31.534955Z",
-     "iopub.status.idle": "2025-01-31T08:36:31.577603Z",
-     "shell.execute_reply": "2025-01-31T08:36:31.574121Z"
+     "iopub.execute_input": "2025-02-02T09:30:04.697756Z",
+     "iopub.status.busy": "2025-02-02T09:30:04.697466Z",
+     "iopub.status.idle": "2025-02-02T09:30:04.735492Z",
+     "shell.execute_reply": "2025-02-02T09:30:04.735100Z"
     }
    },
    "outputs": [
@@ -183,18 +183,18 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2025-01-31T08:36:31.580196Z",
-     "iopub.status.busy": "2025-01-31T08:36:31.580040Z",
-     "iopub.status.idle": "2025-01-31T08:36:31.583683Z",
-     "shell.execute_reply": "2025-01-31T08:36:31.582795Z"
+     "iopub.execute_input": "2025-02-02T09:30:04.738715Z",
+     "iopub.status.busy": "2025-02-02T09:30:04.738204Z",
+     "iopub.status.idle": "2025-02-02T09:30:04.740942Z",
+     "shell.execute_reply": "2025-02-02T09:30:04.740490Z"
     }
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CUDA-Q Version  (https://github.com/NVIDIA/cuda-quantum 8505897ac27b90e4f1947966369f35184f7f3632)\n"
+      "CUDA-Q Version  (https://github.com/NVIDIA/cuda-quantum c7f284926382599dbb3494269d41d6ba2b972c06)\n"
      ]
     }
    ],

pr-2533/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="80aea6249e374f82a895703bf3b3df98" src="../../_images/gate-fuse.png" /></p>
+<p><img alt="459f9594e0144146a1f45501344de069" 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="d3274086178249c6a1e3082eb1c8cdf7" src="../../_images/gatefusion.png" /></p>
+<p><img alt="ef9a77e43599401a838a803f8d2c492d" src="../../_images/gatefusion.png" /></p>
 </section>
 </section>