LeonhardRichter / TDVP_and_QAOA

This is the repository associated to the bachelors thesis of Leonhard Richter.

TDVP and QAOA

This is the repository associated to the bachelor thesis of Leonhard Richter.

The Quantum Approximate Optimization Algorithm (QAOA) first introduced by Farhi et al.¹ is combined with the Time-Dependent Variational Principle for imaginary time evolution². In this repository, the TDVP and the QAOA are implemented for simulations using the QuTiP library^{3 4}.

The version of the code that is used in the thesis is found in XXXXXXX.

The main methods are found in qaoa_and_tdvp.py. There, all classes and functions, that are vital for the various algorithms are defined. MaxCut.py defines a class for instances of the Maximum Cut problem. quantum.py defines some basic functions for convenience. benchmark.py defines among others the function bench_series that is used in run_benchmarks.ipynb for generating the results presented in the thesis. The exact instance objects that are being considered in the thesis are 'pickled' in ./instances/n4_instances.p and in ./instances/n5_instances.p. Some other jupyter-notebooks collect the data processing and analysis.

Footnotes

1. Farhi, E., Goldstone, J., & Gutmann, S. (2014). A quantum approximate optimization algorithm. arXiv preprint arXiv:1411.4028 [quant-ph] ↩

2. Haegeman, J., Cirac, J. I., Osborne, T. J., Pižorn, I., Verschelde, H., & Verstraete, F. (2011). Time-dependent variational principle for quantum lattices. Physical review letters, 107(7), 070601. ↩

3. J. R. Johansson, P. D. Nation, and F. Nori: "QuTiP 2: A Python framework for the dynamics of open quantum systems.", Comp. Phys. Comm. 184, 1234 (2013) [DOI: 10.1016/j.cpc.2012.11.019]. ↩

4. J. R. Johansson, P. D. Nation, and F. Nori: "QuTiP: An open-source Python framework for the dynamics of open quantum systems.", Comp. Phys. Comm. 183, 1760–1772 (2012) [DOI: 10.1016/j.cpc.2012.02.021]. ↩