Metadata-Version: 2.1
Name: qsurface
Version: 0.1.3
Summary: Open library from surface code simulations and visualizations
Home-page: https://github.com/watermarkhu/qsurface
Author: Mark Shui Hu
Author-email: watermarkhu@gmail.com
License: BSD-3
Project-URL: Documentation, https://qsurface.readthedocs.io/en/latest/
Description: 
        # Qsurface
        
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        Qsurface is a simulation package for the surface code, and is designed to modularize 3 aspects of a surface code simulation.
        
        1. The surface code
        2. The error model
        3. The used decoder
        
        New types of surface codes, error modules and decoders can be added to Qsurface by using the included templates for each of the three core module categories.
        
        The current included decoders are:
        
        * The *Mininum-Weight Perfect Matching* (`mwpm`) decoder.
        * [Delfosse's and Nickerson's](https://arxiv.org/pdf/1709.06218.pdf) *Union-Find* (`unionfind`) decoder, which has *almost-linear* worst-case time complexity.
        * Our modification to the Union-Find decoder; the *Union-Find Node-Suspension* (`ufns`) decoder, which improves the threshold of the Union-Find decoder to near MWPM performance, while retaining quasi-linear worst-case time complexity.
        
        The compatibility of these decoders with the included surface codes are listed below.
        
        | Decoders  | `toric` code | `planar` code |
        |-----------|--------------|---------------|
        |`mwpm`     |✅            |✅             |
        |`unionfind`|✅            |✅             |
        |`ufns`     |✅            |✅             |
        
        # Installation
        
        All required packages can be installed through:
        
        ```bash
        pip install qsurface
        ```
        
        ## Requirements
        
        * Python 3.7+
        * [Tkinter](https://docs.python.org/3/library/tkinter.html) or [PyQt5](https://riverbankcomputing.com/software/pyqt/intro) for interactive plotting.
        * Matplotlib 3.4+ for plotting on a 3D lattice (Refers to a future release of matplotlib, see [pull request](https://github.com/matplotlib/matplotlib/pull/18816))
        
        ### MWPM decoder
        
        The MWPM decoder utilizes `networkx` for finding the minimal weights in a fully connected graph. This implementation is however rather slow compared to Kolmogorov's [Blossom V](https://pub.ist.ac.at/~vnk/software.html) algorithm. Blossom V has its own license and is thus not included with Qsurface. We do provided a single function to download and compile Blossom V, and to setup the integration with Qsurface automatically.
        
        ```python
        >>> from qsurface.decoders import mwpm
        >>> mwpm.get_blossomv()
        ```
        
        # Usage
        
        To simulate the toric code and simulate with bitflip error for 10 iterations and decode with the MWPM decoder:
        
        ```python
        >>> from qsurface.main import initialize, run
        >>> code, decoder = initialize((6,6), "toric", "mwpm", enabled_errors=["pauli"])
        >>> run(code, decoder, iterations=10, error_rates = {"p_bitflip": 0.1})
        {'no_error': 8}
        ```
        
        Benchmarking of decoders can be enabled by attaching a *benchmarker* object to the decoder. See the docs for the syntax and information to setup benchmarking.
        
        ```python
        >>> from qsurface.main import initialize, run
        >>> benchmarker = BenchmarkDecoder({"decode":"duration"})
        >>> run(code, decoder, iterations=10, error_rates = {"p_bitflip": 0.1}, benchmark=benchmarker)
        {'no_error': 8,
        'benchmark': {'success_rate': [10, 10],
        'seed': 12447.413636559,
        'durations': {'decode': {'mean': 0.00244155000000319,
        'std': 0.002170364089572033}}}}
        ```
        
        ## Plotting
        
        The figures in Qsurface allows for step-by-step visualization of the surface code simulation (and if supported the decoding process). Each figure logs its history such that the user can move backwards in time to view past states of the surface (and decoder). Press `h` when the figure is open for more information.
        
        ```python
        >>> from qsurface.main import initialize, run
        >>> code, decoder = initialize((6,6), "toric", "mwpm", enabled_errors=["pauli"], plotting=True, initial_states=(0,0))
        >>> run(code, decoder, error_rates = {"p_bitflip": 0.1, "p_phaseflip": 0.1}, decode_initial=False)
        ```
        
        ![Interactive plotting on a 6x6 toric code.](https://raw.githubusercontent.com/watermarkhu/qsurface/master/images/toric-2d.gif "Iteractive plotting on a 2d axis")
        
        Plotting will be performed on a 3D axis if faulty measurements are enabled.
        
        ```python
        >>> code, decoder = initialize((3,3), "toric", "mwpm", enabled_errors=["pauli"], faulty_measurements=True, plotting=True, initial_states=(0,0))
        >>> run(code, decoder, error_rates = {"p_bitflip": 0.05, "p_bitflip_plaq": 0.05}, decode_initial=False)
        ```
        
        ![Interactive plotting on a toric code with faulty measurements.](https://raw.githubusercontent.com/watermarkhu/qsurface/master/images/toric-3d.gif "Iteractive plotting on a 3d axis")
        
        In IPython, inline images are created for each iteration of the plot, which can be tested in the [example notebook](https://mybinder.org/v2/gh/watermarkhu/qsurface/master?filepath=examples.ipynb).
        
        ## Command line interface
        
        Simulations can also be initiated from the command line
        
        ```bash
        $ python -m qsurface -e pauli -D mwpm -C toric simulation --p_bitflip 0.1 -n 10
        {'no_error': 8}
        ```
        
        For more information on command line interface:
        
        ```bash
        $ python -m qsurface -h
        usage: qsurface
        ...
        ```
        
        *This project is proudly funded by the [Unitary Fund](https://unitary.fund/).*
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >3.7.0
Description-Content-Type: text/markdown
