Learning tensor networks with tensor cross interpolation: new algorithms and libraries
The tensor cross interpolation (TCI) algorithm is a rank-revealing algorithm for decomposing
low-rank, high-dimensional tensors into tensor trains/matrix product states (MPS). TCI learns …
low-rank, high-dimensional tensors into tensor trains/matrix product states (MPS). TCI learns …
Simulating the quantum Fourier transform, Grover's algorithm, and the quantum counting algorithm with limited entanglement using tensor networks
Quantum algorithms reformulate computational problems as quantum evolutions in a large
Hilbert space. Most quantum algorithms assume that the time evolution is perfectly unitary …
Hilbert space. Most quantum algorithms assume that the time evolution is perfectly unitary …
Real-frequency quantum field theory applied to the single-impurity Anderson model
A Ge, N Ritz, E Walter, S Aguirre, J von Delft, FB Kugler - Physical Review B, 2024 - APS
A major challenge in the field of correlated electrons is the computation of dynamical
correlation functions. For comparisons with experiment, one is interested in their real …
correlation functions. For comparisons with experiment, one is interested in their real …
Cross-extrapolation reconstruction of low-rank functions and application to quantum many-body observables in the strong coupling regime
We present a general-purpose algorithm to extrapolate a low-rank function of two variables
from a small domain to a larger one. It is based on the cross-interpolation formula. We apply …
from a small domain to a larger one. It is based on the cross-interpolation formula. We apply …
[HTML][HTML] Efficient MPS representations and quantum circuits from the Fourier modes of classical image data
B Jobst, K Shen, CA Riofrío, E Shishenina… - Quantum, 2024 - quantum-journal.org
Abstract Machine learning tasks are an exciting application for quantum computers, as it has
been proven that they can learn certain problems more efficiently than classical ones …
been proven that they can learn certain problems more efficiently than classical ones …
Strong coupling impurity solver based on quantics tensor cross interpolation
AJ Kim, P Werner - arXiv preprint arXiv:2411.19026, 2024 - arxiv.org
Numerical methods capable of handling nonequilibrium impurity models are essential for
the study of transport problems and the solution of the nonequilibrium dynamical mean field …
the study of transport problems and the solution of the nonequilibrium dynamical mean field …
Overcomplete intermediate representation of two-particle Green's functions and its relation to partial spectral functions
Two-particle response functions are a centerpiece of both experimental and theoretical
quantum many-body physics. Yet, due to their size and discontinuity structure, they are …
quantum many-body physics. Yet, due to their size and discontinuity structure, they are …
Tensor networks enable the calculation of turbulence probability distributions
Predicting the dynamics of turbulent fluid flows has long been a central goal of science and
engineering. Yet, even with modern computing technology, accurate simulation of all but the …
engineering. Yet, even with modern computing technology, accurate simulation of all but the …
Tensorized orbitals for computational chemistry
N Jolly, YN Fernández, X Waintal - arXiv preprint arXiv:2308.03508, 2023 - arxiv.org
Choosing a basis set is the first step of a quantum chemistry calculation and it sets its
maximum accuracy. This choice of orbitals is limited by strong technical constraints as one …
maximum accuracy. This choice of orbitals is limited by strong technical constraints as one …
QSpace-An open-source tensor library for Abelian and non-Abelian symmetries
A Weichselbaum - arXiv preprint arXiv:2405.06632, 2024 - arxiv.org
This is the documentation for the tensor library QSpace (v4. 0), a toolbox to exploitquantum
symmetry spaces' in tensor network states in the quantum many-body context. QSpace …
symmetry spaces' in tensor network states in the quantum many-body context. QSpace …