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pr-2481/_images/backends.png

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pr-2481/_images/circuitsimulators.png

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pr-2481/_images/qpus.png

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pr-2481/applications/python/deutschs_algorithm.html

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@@ -783,7 +783,7 @@ <h2>XOR <span class="math notranslate nohighlight">\(\oplus\)</span><a class="he
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</section>
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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="9d6aa539f2e24b10bc4da325f57f3946" class="no-scaled-link" src="../../_images/oracle.png" style="width: 300px; height: 150px;" /></p>
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<p><img alt="f426a570389f4468b425a045f628f336" 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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<div class="math notranslate nohighlight">
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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="54a1a982f8ea4707b22a5f1acc4772ea" class="no-scaled-link" src="../../_images/deutsch.png" style="width: 500px; height: 210px;" /></p>
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<p><img alt="cdd192fb4914492b80223248d9a02099" 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-2481/examples/python/performance_optimizations.html

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@@ -711,9 +711,9 @@ <h1>Optimizing Performance<a class="headerlink" href="#Optimizing-Performance" t
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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="4a01747e9afd4ad2ac264eeaa0ec6aeb" src="../../_images/gate-fuse.png" /></p>
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<p><img alt="591152ef158e4a1fb6cfb49f84947620" 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="8f2417000c5c428481b45d9a33fecc5c" src="../../_images/gatefusion.png" /></p>
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<p><img alt="464b758bec784a69ab75fd7d7ff8e14e" src="../../_images/gatefusion.png" /></p>
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</section>
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</section>
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pr-2481/searchindex.js

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