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pr-2533/api/languages/cpp_api.html

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<dd><p>The number of trajectories to be used for an expectation calculation on simulation backends that support trajectory simulation. </p>
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</dd></dl>
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<dl class="cpp var">
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<dt class="sig sig-object cpp" id="_CPPv4N5cudaq16ExecutionContext9outputLogE">
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<span class="target" id="classcudaq_1_1ExecutionContext_1acb803bc82b3d3a66c638c003a2a4e6ea"></span><span class="n"><span class="pre">std</span></span><span class="p"><span class="pre">::</span></span><span class="n"><span class="pre">string</span></span><span class="w"> </span><span class="sig-name descname"><span class="n"><span class="pre">outputLog</span></span></span><a class="headerlink" href="#_CPPv4N5cudaq16ExecutionContext9outputLogE" title="Permalink to this definition">¶</a><br /></dt>
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<dd><p>A string containing the output logging of a kernel launched with cudaq::run. </p>
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</dd></dl>
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pr-2533/applications/python/deutschs_algorithm.html

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<section id="Quantum-oracles">
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<h2>Quantum oracles<a class="headerlink" href="#Quantum-oracles" title="Permalink to this heading"></a></h2>
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<p><img alt="342733c00fbb4cd68df78e4316a2dfa3" class="no-scaled-link" src="../../_images/oracle.png" style="width: 300px; height: 150px;" /></p>
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<p><img alt="988afb67f4334360acd2cf5afdb22507" class="no-scaled-link" src="../../_images/oracle.png" style="width: 300px; height: 150px;" /></p>
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<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>
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<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>
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<h2>Deutsch’s Algorithm:<a class="headerlink" href="#Deutsch's-Algorithm:" title="Permalink to this heading"></a></h2>
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<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>
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<p>We step through the circuit diagram below and follow the math after the application of each gate.</p>
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<p><img alt="7fc95401925a423aafc269d07b939e89" class="no-scaled-link" src="../../_images/deutsch.png" style="width: 500px; height: 210px;" /></p>
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<p><img alt="3ae66d34086a42c4a2c05e05ff0240e6" class="no-scaled-link" src="../../_images/deutsch.png" style="width: 500px; height: 210px;" /></p>
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<div class="math notranslate nohighlight">
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\[\ket{\psi_0} = \ket{01}
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\tag{1}\]</div>

pr-2533/examples/python/executing_photonic_kernels.html

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</div>
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<div class="output_area docutils container">
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<div class="highlight"><pre>
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{ 02:361 11:240 20:399 }
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{ 02:379 11:255 20:366 }
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<div class="output_area docutils container">
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<div class="highlight"><pre>
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CUDA-Q Version (https://github.com/NVIDIA/cuda-quantum c594e2d9c494c0a07cfb154b5efb9397760428dd)
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CUDA-Q Version (https://github.com/NVIDIA/cuda-quantum 8505897ac27b90e4f1947966369f35184f7f3632)
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</pre></div></div>
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pr-2533/examples/python/executing_photonic_kernels.ipynb

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"iopub.execute_input": "2025-01-31T08:36:28.826553Z",
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"name": "stdout",
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"{ 02:361 11:240 20:399 }\n",
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"{ 02:379 11:255 20:366 }\n",
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"\n"
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"iopub.execute_input": "2025-01-31T08:36:31.535230Z",
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"iopub.status.busy": "2025-01-31T08:36:31.534955Z",
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"shell.execute_reply": "2025-01-31T08:36:31.574121Z"
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"metadata": {
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"execution": {
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"iopub.execute_input": "2025-01-30T01:08:32.362193Z",
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"shell.execute_reply": "2025-01-30T01:08:32.364236Z"
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"iopub.execute_input": "2025-01-31T08:36:31.580196Z",
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"iopub.status.busy": "2025-01-31T08:36:31.580040Z",
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"iopub.status.idle": "2025-01-31T08:36:31.583683Z",
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"shell.execute_reply": "2025-01-31T08:36:31.582795Z"
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"CUDA-Q Version (https://github.com/NVIDIA/cuda-quantum c594e2d9c494c0a07cfb154b5efb9397760428dd)\n"
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"CUDA-Q Version (https://github.com/NVIDIA/cuda-quantum 8505897ac27b90e4f1947966369f35184f7f3632)\n"
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pr-2533/examples/python/performance_optimizations.html

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<section id="Gate-Fusion">
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<h2>Gate Fusion<a class="headerlink" href="#Gate-Fusion" title="Permalink to this heading"></a></h2>
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<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>
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<p><img alt="2bf598db89054ce991173c3e12ff0189" src="../../_images/gate-fuse.png" /></p>
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<p><img alt="80aea6249e374f82a895703bf3b3df98" src="../../_images/gate-fuse.png" /></p>
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<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>
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<p><img alt="46a59b1f8d8d4e559106629e703f5cac" src="../../_images/gatefusion.png" /></p>
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<p><img alt="d3274086178249c6a1e3082eb1c8cdf7" src="../../_images/gatefusion.png" /></p>
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</section>
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pr-2533/genindex.html

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<li><a href="api/languages/cpp_api.html#_CPPv4N5cudaq16ExecutionContext18numberTrajectoriesE">cudaq::ExecutionContext::numberTrajectories (C++ member)</a>
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<li><a href="api/languages/cpp_api.html#_CPPv4N5cudaq16ExecutionContext9optResultE">cudaq::ExecutionContext::optResult (C++ member)</a>
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<li><a href="api/languages/cpp_api.html#_CPPv4N5cudaq16ExecutionContext9outputLogE">cudaq::ExecutionContext::outputLog (C++ member)</a>
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<li><a href="api/languages/cpp_api.html#_CPPv4N5cudaq16ExecutionContext20overlapComputeStatesE">cudaq::ExecutionContext::overlapComputeStates (C++ member)</a>
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<li><a href="api/languages/cpp_api.html#_CPPv4N5cudaq3QPU12launchKernelERKNSt6stringE15KernelThunkTypePvNSt8uint64_tENSt8uint64_tERKNSt6vectorIPvEE">cudaq::QPU::launchKernel (C++ function)</a>, <a href="api/languages/cpp_api.html#_CPPv4N5cudaq3QPU12launchKernelERKNSt6stringERKNSt6vectorIPvEE">[1]</a>
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<li><a href="api/languages/cpp_api.html#_CPPv4N5cudaq3QPU29launchSerializedCodeExecutionERKNSt6stringERN5cudaq30SerializedCodeExecutionContextE">cudaq::QPU::launchSerializedCodeExecution (C++ function)</a>
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<li><a href="api/languages/cpp_api.html#_CPPv4N5cudaq3QPU15onRandomSeedSetENSt6size_tE">cudaq::QPU::onRandomSeedSet (C++ function)</a>
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<td style="width: 33%; vertical-align: top;"><ul>
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<li><a href="api/languages/cpp_api.html#_CPPv4N5cudaq3QPU15onRandomSeedSetENSt6size_tE">cudaq::QPU::onRandomSeedSet (C++ function)</a>
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</li>
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<li><a href="api/languages/cpp_api.html#_CPPv4N5cudaq3QPU3QPUENSt6size_tE">cudaq::QPU::QPU (C++ function)</a>, <a href="api/languages/cpp_api.html#_CPPv4N5cudaq3QPU3QPUERR3QPU">[1]</a>, <a href="api/languages/cpp_api.html#_CPPv4N5cudaq3QPU3QPUEv">[2]</a>
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<li><a href="api/languages/cpp_api.html#_CPPv4N5cudaq3QPU21resetExecutionContextEv">cudaq::QPU::resetExecutionContext (C++ function)</a>

pr-2533/objects.inv

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pr-2533/searchindex.js

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