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attpjaygambetta
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Fixing broken image link in Shor's algorithm tutorial (#399)
* Fixing broken image link in shor's algorithm tutorial * Saving notebook before commiting this time.
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community/algorithms/shor_algorithm.ipynb

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"source": [
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"As mentioned [earlier](#shorsalgorithm), many of the experimental demonstrations of Shor's algorithm rely on significant optimisations based on apriori knowledge of the expected results. We will follow the formulation in [this](http://science.sciencemag.org/content/351/6277/1068) paper, which demonstrates a reasonably scalable realisation of Shor's algorithm using $N = 15$. Below is the first figure from the paper, showing various quantum circuits, with the following caption: _Diagrams of Shor’s algorithm for factoring $N = 15$, using a generic textbook approach (**A**) compared with Kitaev’s approach (**B**) for a generic base $a$. (**C**) The actual implementation for factoring $15$ to base $11$, optimized for the corresponding single-input state. Here $q_i$ corresponds to the respective qubit in the computational register. (**D**) Kitaev’s approach to Shor’s algorithm for the bases ${2, 7, 8, 13}$. Here, the optimized map of the first multiplier is identical in all four cases, and the last multiplier is implemented with full modular multipliers, as depicted in (**E**). In all cases, the single QFT qubit is used three times, which, together with the four qubits in the computation register, totals seven effective qubits. (**E**) Circuit diagrams of the modular multipliers of the form $a \\bmod N$ for bases $a = {2, 7, 8, 11, 13}$._\n",
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"\n",
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"<img src=\"../../images/shoralgorithm.png\" alt=\"Note: In order for images to show up in this jupyter notebook you need to select File => Trusted Notebook\" width=\"500 px\" align=\"center\">\n"
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"<img src=\"images/shoralgorithm.png\" alt=\"Note: In order for images to show up in this jupyter notebook you need to select File => Trusted Notebook\" width=\"500 px\" align=\"center\">\n"
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"display_name": "Python [default]",
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"language": "python",
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"name": "python3"
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.3"
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"version": "3.6.4"
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}
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},
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"nbformat": 4,

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