OQuPy: A Python package to efficiently simulate non-Markovian open quantum systems with process tensors
Gerald E. Fux, Piper Fowler-Wright, Joel Beckles, Eoin P. Butler, Paul, R. Eastham, Dominic Gribben, Jonathan Keeling, Dainius Kilda, Peter Kirton,, Ewen D.C. Lawrence, Brendon W. Lovett, Eoin O'Neill, Aidan Strathearn,, Roosmarijn de Wit

TL;DR
OQuPy is an open-source Python package that efficiently simulates non-Markovian open quantum systems using process tensor methods, enabling advanced analysis of complex quantum dynamics with memory effects.
Contribution
The paper introduces a major update to OQuPy, implementing tensor network-based process tensor techniques for accurate and efficient simulation of non-Markovian quantum systems.
Findings
Efficient simulation of non-Markovian dynamics using process tensors.
Capability to compute multi-time correlations and optimize control protocols.
Simulation of interacting quantum chains and mean-field dynamics.
Abstract
Non-Markovian dynamics arising from the strong coupling of a system to a structured environment is essential in many applications of quantum mechanics and emerging technologies. Deriving an accurate description of general quantum dynamics including memory effects is however a demanding task, prohibitive to standard analytical or direct numerical approaches. We present a major release of our open source software package, OQuPy (Open Quantum System in Python), which provides several recently developed numerical methods that address this challenging task. It utilizes the process tensor approach to open quantum systems in which a single map, the process tensor, captures all possible effects of an environment on the system. The representation of the process tensor in a tensor network form allows an exact yet highly efficient description of non-Markovian open quantum systems (NM-OQS). The…
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Taxonomy
TopicsAdvanced Thermodynamics and Statistical Mechanics · Quantum, superfluid, helium dynamics · Quantum Computing Algorithms and Architecture
