SeeMPS

Introduction

SEEMPS is the SElf-Explaining Matrix-Product-State library.

It is a collection of Jupyter notebooks that literary programming Python implementation of Matrix-Product-State algorithms. The notebooks combine brief explanations of the algorithms and the details of the implementations. We have chosen the most essential algorithms in their simplest form, so as to provide a gentle introduction to the field.

The library is thought out as introduction to the world of Matrix Product States and DMRG-inspired algorithms. Its main goal is not performance, but rapid prototyping and testing of ideas, providing a good playground before dwelling in more advanced (C++, Julia) versions of the algorithms.

Requirements

The library is entirely developed in Python 3 using Numpy and Scipy, and a standard Jupyter environment. We recommend using Anaconda3 or Miniconda3, although any other distribution of Python should suffice.

Version: 0.0

Authors:

• Burçin Danaci (Istanbul Technical University)
• Juan José García Ripoll (Institute of Fundamental Physics)