Matrix product state representation of quasielectron wave functions [PDF]
, 2017 Matrix product state techniques provide a very efficient way to numerically evaluate certain classes of quantum Hall wave functions that can be written as correlators in two-dimensional conformal field theories.
Jonas A. Kjall +4 more
semanticscholar +2 more sources
Equilibrium quantum impurity problems via matrix product state encoding of the retarded action [PDF]
Physical review B, 2023 In the $0+1$ dimensional imaginary-time path integral formulation of quantum impurity problems, the retarded action encodes the hybridization of the impurity with the bath.
B. Kloss +8 more
semanticscholar +1 more source
Quantum Circuit Matrix Product State Ansatz for Large-Scale Simulations of Molecules. [PDF]
Journal of Chemical Theory and Computation, 2023 As demonstrated in the density matrix renormalization group (DMRG) method, approximating many-body wave function of electrons using a matrix product state (MPS) is a promising way to solve electronic structure problems.
Yi Fan, Jie Liu, Zhenyu Li, Jinlong Yang
semanticscholar +1 more source
Improved real-space parallelizable matrix-product state compression and its application to unitary quantum dynamics simulation [PDF]
Physical review B, 2023 Towards the efficient simulation of near-term quantum devices using tensor network states, we introduce an improved real-space parallelizable matrix-product state (MPS) compression method. This method enables efficient compression of all virtual bonds in
Rongyang Sun +2 more
semanticscholar +1 more source
Matrix Product States with Large Sites [PDF]
Journal of Chemical Theory and Computation, 2022 We explore various ways to group orbitals into clusters in a matrix product state (MPS). We explain how a generic cluster MPS can often lead to an increase in computational cost and instead propose a special cluster structure, involving only the first and last orbitals/sites, with a wider scope for computational advantage.
Henrik R. Larsson +3 more
openaire +4 more sources
Matrix product state pre-training for quantum machine learning [PDF]
Quantum Science and Technology, 2021 Hybrid quantum–classical algorithms are a promising candidate for developing uses for NISQ devices. In particular, parametrised quantum circuits (PQCs) paired with classical optimizers have been used as a basis for quantum chemistry and quantum ...
J. Dborin +4 more
semanticscholar +1 more source
Generalization and Overfitting in Matrix Product State Machine Learning Architectures [PDF]
arXiv.org, 2022 While overfitting and, more generally, double descent are ubiquitous in machine learning, increasing the number of parameters of the most widely used tensor network, the matrix product state (MPS), has generally lead to monotonic improvement of test ...
A. Strashko, E. Stoudenmire
semanticscholar +1 more source
Testing matrix product states [PDF]
, 2022 Devising schemes for testing the amount of entanglement in quantum systems has played a crucial role in quantum computing and information theory. Here, we study the problem of testing whether an unknown state $|\psi\rangle$ is a matrix product state (MPS) in the property testing model.
Mehdi Soleimanifar, John Wright 0004
openaire +2 more sources
Non-Markovian stochastic Schrödinger equation: Matrix-product-state approach to the hierarchy of pure states [PDF]
Physical Review A, 2021 We derive a stochastic hierarchy of matrix product states (HOMPS) for non-Markovian dynamics in open quantum system at finite temperature, which is numerically exact and efficient.
Xing Gao +3 more
semanticscholar +1 more source
Multipartite Correlations in Quantum Collision Models
Entropy, 2022 Quantum collision models have proved to be useful for a clear and concise description of many physical phenomena in the field of open quantum systems: thermalization, decoherence, homogenization, nonequilibrium steady state, entanglement generation ...
Sergey Filippov
doaj +1 more source