@book{numpy,
  title = {Guide to NumPy},
  year = {2015},
  isbn = {151730007X, 9781517300074},
  edition = {2nd},
  publisher = {CreateSpace Independent Publishing Platform},
  address = {USA},
}

@Misc{scipy,
  author =    {Eric Jones and Travis Oliphant and Pearu Peterson and others},
  title =     {{SciPy}: Open source scientific tools for {Python}},
  year =      {2001--},
  url = "http://www.scipy.org/",
  note = {[Online; accessed 17 August 2018]}
}

@article{dalcin2011parallel,
  title={Parallel distributed computing using Python},
  author={Dalcin, Lisandro D and Paz, Rodrigo R and Kler, Pablo A and Cosimo, Alejandro},
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  volume={34},
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  pages={1124--1139},
  year={2011},
  publisher={Elsevier},
  doi={10.1016/j.advwatres.2011.04.013}
}

@article{hernandez2005slepc,
  title={SLEPc: A scalable and flexible toolkit for the solution of eigenvalue problems},
  author={Hernandez, Vicente and Roman, Jose E and Vidal, Vicente},
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  volume={31},
  number={3},
  pages={351--362},
  year={2005},
  publisher={ACM},
  doi={10.1145/1089014.1089019}
}

@article{mpi4py,
  title={MPI for Python},
  author={Dalc{\'\i}n, Lisandro and Paz, Rodrigo and Storti, Mario},
  journal={Journal of Parallel and Distributed Computing},
  volume={65},
  number={9},
  pages={1108--1115},
  year={2005},
  publisher={Elsevier},
  doi={10.1016/j.jpdc.2005.03.010},
}

@misc{opt_einsum,
  author={Smith, Daniel GA and Gray, Johnnie},
  title={opt_einsum - A Python package for optimizing contraction order for einsum-like expressions},
  journal={Journal of Open Source Software},
  month={june},
  year={2018},
  doi={10.21105/joss.00753},
  url={https://doi.org/10.21105/joss.00753}
}

@article{tensor-networks,
  author={Jacob C Bridgeman and Christopher T Chubb},
  title={Hand-waving and interpretive dance: an introductory course on tensor networks},
  journal={Journal of Physics A: Mathematical and Theoretical},
  volume={50},
  number={22},
  pages={223001},
  url={http://stacks.iop.org/1751-8121/50/i=22/a=223001},
  year={2017},
  abstract={The curse of dimensionality associated with the Hilbert space of spin systems provides a significant obstruction to the study of condensed matter systems. Tensor networks have proven an important tool in attempting to overcome this difficulty in both the numerical and analytic regimes. These notes form the basis for a seven lecture course, introducing the basics of a range of common tensor networks and algorithms. In particular, we cover: introductory tensor network notation, applications to quantum information, basic properties of matrix product states, a classification of quantum phases using tensor networks, algorithms for finding matrix product states, basic properties of projected entangled pair states, and multiscale entanglement renormalisation ansatz states. The lectures are intended to be generally accessible, although the relevance of many of the examples may be lost on students without a background in many-body physics/quantum information. For each lecture, several problems are given, with worked solutions in an ancillary file.},
  doi={10.1088/1751-8121/aa6dc3},
}

@article{gray2016unravelling,
  title={Unravelling quantum dot array simulators via singlet-triplet measurements},
  author={Gray, Johnnie and Bayat, Abolfazl and Puddy, Reuben K and Smith, Charles G and Bose, Sougato},
  journal={Physical Review B},
  volume={94},
  number={19},
  pages={195136},
  year={2016},
  publisher={APS},
  doi={10.1103/PhysRevB.94.195136},
}

@article{gray2018many,
  title={Many-body localization transition: Schmidt gap, entanglement length, and scaling},
  author={Gray, Johnnie and Bose, Sougato and Bayat, Abolfazl},
  journal={Physical Review B},
  volume={97},
  number={20},
  pages={201105},
  year={2018},
  publisher={APS},
  doi={10.1103/PhysRevB.97.201105},
}

@article{gray2017measuring,
  title={Measuring Entanglement Negativity},
  author={Gray, Johnnie and Banchi, Leonardo and Bayat, Abolfazl and Bose, Sougato},
  journal={arXiv preprint arXiv:1709.04923},
  year={2017}
}
