From architectures to applications: A review of neural quantum states
H Lange, A Van de Walle, A Abedinnia… - arXiv preprint arXiv …, 2024 - arxiv.org
Due to the exponential growth of the Hilbert space dimension with system size, the
simulation of quantum many-body systems has remained a persistent challenge until today …
simulation of quantum many-body systems has remained a persistent challenge until today …
Real-time quantum dynamics of thermal states with neural thermofields
Solving the time-dependent quantum many-body Schrödinger equation is a challenging
task, especially for states at a finite temperature, where the environment affects the …
task, especially for states at a finite temperature, where the environment affects the …
Quantum-inspired neural network model of optical illusions
IS Maksymov - Algorithms, 2024 - mdpi.com
Ambiguous optical illusions have been a paradigmatic object of fascination, research and
inspiration in arts, psychology and video games. However, accurate computational models …
inspiration in arts, psychology and video games. However, accurate computational models …
Adaptive quantum state tomography with active learning
Recently, tremendous progress has been made in the field of quantum science and
technologies: different platforms for quantum simulation as well as quantum computing …
technologies: different platforms for quantum simulation as well as quantum computing …
Systematic improvement of neural network quantum states using Lanczos
The quantum many-body problem lies at the center of the most important open challenges in
condensed matter, quantum chemistry, atomic, nuclear, and high-energy physics. While …
condensed matter, quantum chemistry, atomic, nuclear, and high-energy physics. While …
Variational Neural and Tensor Network Approximations of Thermal States
We introduce a variational Monte Carlo algorithm for approximating finite-temperature
quantum many-body systems, based on the minimization of a modified free energy. We …
quantum many-body systems, based on the minimization of a modified free energy. We …
Lee-Yang theory of quantum phase transitions with neural network quantum states
Predicting the phase diagram of interacting quantum many-body systems is a central
problem in condensed matter physics and related fields. A variety of quantum many-body …
problem in condensed matter physics and related fields. A variety of quantum many-body …
Thermodynamics based on neural networks
D Wagner, A Klümper, J Sirker - Physical Review B, 2024 - APS
We present three different neural network (NN) algorithms to calculate thermodynamic
properties as well as dynamic correlation functions at finite temperatures for quantum lattice …
properties as well as dynamic correlation functions at finite temperatures for quantum lattice …
Neural Network Thermodynamics
D Wagner, A Klümper, J Sirker - arXiv preprint arXiv:2311.13799, 2023 - arxiv.org
We present three different neural network algorithms to calculate thermodynamic properties
as well as dynamic correlation functions at finite temperatures for quantum lattice models …
as well as dynamic correlation functions at finite temperatures for quantum lattice models …
Systematic improvement of neural network quantum states using a Lanczos recursion
The quantum many-body problem lies at the center of the most important open challenges in
condensed matter, quantum chemistry, atomic, nuclear, and high-energy physics. While …
condensed matter, quantum chemistry, atomic, nuclear, and high-energy physics. While …