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MPSDynamics.jl: Tensor network simulations for finite-temperature (non-Markovian) open quantum system dynamics

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arxiv 2406.07052 v2 pith:H2Y4TPXK submitted 2024-06-11 quant-ph cond-mat.mes-hallphysics.chem-phphysics.comp-ph

classification quant-phcond-mat.mes-hallphysics.chem-phphysics.comp-ph
keywords packagempsdynamicsnetworkopenquantumsimulationsstatestensor
verification ladder T0 review T1 audit T2 compute T3 formal
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The MPSDynamics.jl package provides an easy to use interface for performing open quantum systems simulations at zero and finite temperatures. The package has been developed with the aim of studying non-Markovian open system dynamics using the state-of-the-art numerically exact Thermalized-Time Evolving Density operator with Orthonormal Polynomials Algorithm (T-TEDOPA) based on environment chain mapping. The simulations rely on a tensor network representation of the quantum states as matrix product states (MPS) and tree tensor network (TTN) states. Written in the Julia programming language, MPSDynamics.jl is a versatile open-source package providing a choice of several variants of the Time-Dependent Variational Principle (TDVP) method for time evolution (including novel bond-adaptive one-site algorithms). The package also provides strong support for the measurement of single and multi-site observables, as well as the storing and logging of data, which makes it a useful tool for the study of many-body physics. It currently handles long-range interactions, time-dependent Hamiltonians, multiple environments, bosonic and fermionic environments, and joint system-environment observables.

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Cited by 1 Pith paper

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  1. Tensor-network decoders for process tensor descriptions of non-Markovian noise

    quant-ph 2024-12 conditional novelty 6.0 of 10

    A tensor-network-based maximum likelihood decoder is constructed for quantum error correction under process-tensor noise, with an MPS approximation demonstrated on the five-qubit and Steane codes.

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