A developing project for simulating dynamics of 1D quantum systems using tensor networks.
The main project folder is named hellomps/
and is organized as follows:
networks/
contains commonly used tensor network architectures, MPS
for pure states and LPTN
for mixed states.
operations.py
integrates a variety of tensor networks operations, which are essential to the simulation algorithms.
mpo_projected.py
offers the abstract interface between projected MPO and iterative solvers, which is the central unit
to variational optimization problems, such as DMRG.
models/
provides models used for simulation, such as transverse field Ising model, Bose-Hubburd model, etc. This part
is still quite basic as for now.
algorithms/
implements ground state serach algorithms for MPS, real and imaginary time evolution algorithms for both MPS and LPTN.
- Sebastian Paeckel, Thomas Köhler, Andreas Swoboda, Salvatore R. Manmana, Ulrich Schollwöck, Claudius Hubig,
Time-evolution methods for matrix-product states Annals of Physics, Volume 411, 2019
- Werner, A. H. and Jaschke, D. and Silvi, P. and Kliesch, M. and Calarco, T. and Eisert, J. and Montangero, S.
Positive Tensor Network Approach for Simulating Open Quantum Many-Body Systems Phys. Rev. Lett. 116, 237201
- Jutho Haegeman, Christian Lubich, Ivan Oseledets, Bart Vandereycken, and Frank Verstraete
Unifying time evolution and optimization with matrix product states Phys. Rev. B 94, 165116