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Using reinforcement learning with quantum systems

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entangl

The original contribution was done by Irtaza Khalid (in the context of an Urop project), and now followed up by Kin Lo and Timothy Liu for their Bsc project.

Installation

entangl is not available through pip or conda, and must be installed manually, by cloning the repository and adding the resulting directory to the PYTHONPATH environment variable (or otherwise making the inner floq folder visible to the Python search path).

The requirements are listed in the file requirements.txt and intended to be used with python 3

Overview

entangl provides to generate and

utility/ folder contains the main functions: qm.py should contain the relevant functions to simulate quantum mechanics (i.e. generation of quantum states, projective masurements, entanglement computation)

datagen.py encompasses tools to generate training/testing data

ann.py helper for the construction of artificial neural networks

examples/

There are a couple of examples in the examples/ folder, and there is more help available in the docstrings of the code. Try calling help() on classes and functions to find out more.

dataset/ is intended to be the storage place for small dataset used in the examples

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