Quantum chemistry in the age of quantum computing
Practical challenges in simulating quantum systems on classical computers have been
widely recognized in the quantum physics and quantum chemistry communities over the …
widely recognized in the quantum physics and quantum chemistry communities over the …
Equation-of-Motion Methods for the Calculation of Femtosecond Time-Resolved 4-Wave-Mixing and N-Wave-Mixing Signals
Femtosecond nonlinear spectroscopy is the main tool for the time-resolved detection of
photophysical and photochemical processes. Since most systems of chemical interest are …
photophysical and photochemical processes. Since most systems of chemical interest are …
qubit-adapt-vqe: An adaptive algorithm for constructing hardware-efficient ansätze on a quantum processor
Quantum simulation, one of the most promising applications of a quantum computer, is
currently being explored intensely using the variational quantum eigensolver. The feasibility …
currently being explored intensely using the variational quantum eigensolver. The feasibility …
Measurement and entanglement phase transitions in all-to-all quantum circuits, on quantum trees, and in Landau-Ginsburg theory
A quantum many-body system whose dynamics includes local measurements at a nonzero
rate can be in distinct dynamical phases, with differing entanglement properties. We …
rate can be in distinct dynamical phases, with differing entanglement properties. We …
Tensor networks for dimensionality reduction and large-scale optimization: Part 1 low-rank tensor decompositions
Modern applications in engineering and data science are increasingly based on
multidimensional data of exceedingly high volume, variety, and structural richness …
multidimensional data of exceedingly high volume, variety, and structural richness …
Tensor ring decomposition
Tensor networks have in recent years emerged as the powerful tools for solving the large-
scale optimization problems. One of the most popular tensor network is tensor train (TT) …
scale optimization problems. One of the most popular tensor network is tensor train (TT) …
Tensor product methods and entanglement optimization for ab initio quantum chemistry
The treatment of high‐dimensional problems such as the Schrödinger equation can be
approached by concepts of tensor product approximation. We present general techniques …
approached by concepts of tensor product approximation. We present general techniques …
[HTML][HTML] Matrix product operators, matrix product states, and ab initio density matrix renormalization group algorithms
Current descriptions of the ab initio density matrix renormalization group (DMRG) algorithm
use two superficially different languages: an older language of the renormalization group …
use two superficially different languages: an older language of the renormalization group …
Machine learning by unitary tensor network of hierarchical tree structure
The resemblance between the methods used in quantum-many body physics and in
machine learning has drawn considerable attention. In particular, tensor networks (TNs) and …
machine learning has drawn considerable attention. In particular, tensor networks (TNs) and …
Measurement-induced phase transitions on dynamical quantum trees
Monitored many-body systems fall broadly into two dynamical phases,“entangling” or
“disentangling,” separated by a transition as a function of the rate at which measurements …
“disentangling,” separated by a transition as a function of the rate at which measurements …