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From architectures to applications: A review of neural quantum states
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 …
Efficient learning of ground and thermal states within phases of matter
We consider two related tasks:(a) estimating a parameterisation of a given Gibbs state and
expectation values of Lipschitz observables on this state;(b) learning the expectation values …
expectation values of Lipschitz observables on this state;(b) learning the expectation values …
Boltzmann machines and quantum many-body problems
Y Nomura - Journal of Physics: Condensed Matter, 2023 - iopscience.iop.org
Analyzing quantum many-body problems and elucidating the entangled structure of
quantum states is a significant challenge common to a wide range of fields. Recently, a …
quantum states is a significant challenge common to a wide range of fields. Recently, a …
Matrix-model simulations using quantum computing, deep learning, and lattice monte carlo
Matrix quantum mechanics plays various important roles in theoretical physics, such as a
holographic description of quantum black holes, and it underpins the only practical …
holographic description of quantum black holes, and it underpins the only practical …
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 …
Artificial intelligence (AI) for quantum and quantum for AI
Y Zhu, K Yu - Optical and Quantum Electronics, 2023 - Springer
The technological fields of AI and quantum technology have evolved in parallel, and have
demonstrated considerable potential to complement each other. Amalgamation of them …
demonstrated considerable potential to complement each other. Amalgamation of them …
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 …
Deep learning lattice gauge theories
Monte Carlo methods have led to profound insights into the strong-coupling behavior of
lattice gauge theories and produced remarkable results such as first-principles computations …
lattice gauge theories and produced remarkable results such as first-principles computations …
[HTML][HTML] Update of HΦ: Newly added functions and methods in versions 2 and 3
H Φ [aitch-phi] is an open-source software package of numerically exact and stochastic
calculations for a wide range of quantum many-body systems. In this paper, we present the …
calculations for a wide range of quantum many-body systems. In this paper, we present the …
Numerically “exact” simulations of a quantum Carnot cycle: Analysis using thermodynamic work diagrams
S Koyanagi, Y Tanimura - The Journal of Chemical Physics, 2022 - pubs.aip.org
We investigate the efficiency of a quantum Carnot engine based on open quantum dynamics
theory. The model includes time-dependent external fields for the subsystems controlling the …
theory. The model includes time-dependent external fields for the subsystems controlling the …