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‎pr-2735/_sources/api/languages/cpp_api.rst.txt

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.. doxygenclass:: cudaq::spin_op
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‎pr-2735/api/languages/cpp_api.html

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‎pr-2735/applications/python/adapt_qaoa.html

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<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>
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<p>Below is a schematic representation of the ADAPT-QAOA algorithm explained above.</p>
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<div><p><img alt="1a066c5fc5d649eeb0e121d39ebf1138" class="no-scaled-link" src="../../_images/adapt-qaoa.png" style="width: 600px;" /></p>
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<div><p><img alt="7964b7536e0e4b30998178683306b6aa" class="no-scaled-link" src="../../_images/adapt-qaoa.png" style="width: 600px;" /></p>
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<div class="prompt highlight-none notranslate"><div class="highlight"><pre><span></span>[ ]:
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‎pr-2735/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="2034fc5ec94f4222a7eb176b34a1c265" class="no-scaled-link" src="../../_images/oracle.png" style="width: 300px; height: 150px;" /></p>
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<p><img alt="da5e8f821104429b800e0034e7bc0861" 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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<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="1d10204f61b44a039c2cd197b0a59008" 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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‎pr-2735/examples/python/performance_optimizations.html

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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="6269d921be9846ceb3daf9c210c2f79c" 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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<li><a href="api/languages/cpp_api.html#_CPPv4NK5cudaq15scalar_operator8evaluateERKNSt13unordered_mapINSt6stringENSt7complexIdEEEE">cudaq::scalar_operator::evaluate (C++ function)</a>
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<li><a href="api/languages/cpp_api.html#_CPPv4NK5cudaq15scalar_operator11is_constantEv">cudaq::scalar_operator::is_constant (C++ function)</a>
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