Message-Passing Neural Quantum States for the Homogeneous Electron Gas
- URL: http://arxiv.org/abs/2305.07240v3
- Date: Mon, 11 Dec 2023 09:27:55 GMT
- Title: Message-Passing Neural Quantum States for the Homogeneous Electron Gas
- Authors: Gabriel Pescia, Jannes Nys, Jane Kim, Alessandro Lovato, Giuseppe
Carleo
- Abstract summary: We introduce a message-passing-neural-network-based wave function Ansatz to simulate extended, strongly interacting fermions in continuous space.
We demonstrate its accuracy by simulating the ground state of the homogeneous electron gas in three spatial dimensions.
- Score: 41.94295877935867
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We introduce a message-passing-neural-network-based wave function Ansatz to
simulate extended, strongly interacting fermions in continuous space. Symmetry
constraints, such as continuous translation symmetries, can be readily embedded
in the model. We demonstrate its accuracy by simulating the ground state of the
homogeneous electron gas in three spatial dimensions at different densities and
system sizes. With orders of magnitude fewer parameters than state-of-the-art
neural-network wave functions, we demonstrate better or comparable ground-state
energies. Reducing the parameter complexity allows scaling to $N=128$
electrons, previously inaccessible to neural-network wave functions in
continuous space, enabling future work on finite-size extrapolations to the
thermodynamic limit. We also show the Ansatz's capability of quantitatively
representing different phases of matter.
Related papers
- Simulating continuous-space systems with quantum-classical wave functions [0.0]
Non-relativistic interacting quantum many-body systems are naturally described in terms of continuous-space Hamiltonians.
Current algorithms require discretization, which usually amounts to choosing a finite basis set, inevitably introducing errors.
We propose an alternative, discretization-free approach that combines classical and quantum resources in a global variational ansatz.
arXiv Detail & Related papers (2024-09-10T10:54:59Z) - Fourier Neural Operators for Learning Dynamics in Quantum Spin Systems [77.88054335119074]
We use FNOs to model the evolution of random quantum spin systems.
We apply FNOs to a compact set of Hamiltonian observables instead of the entire $2n$ quantum wavefunction.
arXiv Detail & Related papers (2024-09-05T07:18:09Z) - Machine learning one-dimensional spinless trapped fermionic systems with
neural-network quantum states [1.6606527887256322]
We compute the ground-state properties of fully polarized, trapped, one-dimensional fermionic systems interacting through a gaussian potential.
We use an antisymmetric artificial neural network, or neural quantum state, as an ansatz for the wavefunction.
We find very different ground states depending on the sign of the interaction.
arXiv Detail & Related papers (2023-04-10T17:36:52Z) - Signatures of a quantum phase transition on a single-mode bosonic model [0.0]
Equilibrium phase transitions emerge from the microscopic behavior of many-body systems.
They can be defined through the non-analytic behavior of thermodynamic potentials in the thermodynamic limit.
Taking previous ideas to the extreme, we argue that such a limit can be defined even in non-extended systems.
arXiv Detail & Related papers (2023-03-22T20:14:45Z) - Simulating 2+1D Lattice Quantum Electrodynamics at Finite Density with
Neural Flow Wavefunctions [5.049046327655608]
We present a neural flow wavefunction, Gauge-Fermion FlowNet, to simulate 2+1D lattice compact quantum electrodynamics with finite density dynamical fermions.
We investigate confinement and string breaking phenomena in different fermion density and hopping regimes.
arXiv Detail & Related papers (2022-12-14T18:59:07Z) - Tuning long-range fermion-mediated interactions in cold-atom quantum
simulators [68.8204255655161]
Engineering long-range interactions in cold-atom quantum simulators can lead to exotic quantum many-body behavior.
Here, we propose several tuning knobs, accessible in current experimental platforms, that allow to further control the range and shape of the mediated interactions.
arXiv Detail & Related papers (2022-03-31T13:32:12Z) - Accessing the topological Mott insulator in cold atom quantum simulators
with realistic Rydberg dressing [58.720142291102135]
We investigate a realistic scenario for the quantum simulation of such systems using cold Rydberg-dressed atoms in optical lattices.
We perform a detailed analysis of the phase diagram at half- and incommensurate fillings, in the mean-field approximation.
We furthermore study the stability of the phases with respect to temperature within the mean-field approximation.
arXiv Detail & Related papers (2022-03-28T14:55:28Z) - Neural-Network Quantum States for Periodic Systems in Continuous Space [66.03977113919439]
We introduce a family of neural quantum states for the simulation of strongly interacting systems in the presence of periodicity.
For one-dimensional systems we find very precise estimations of the ground-state energies and the radial distribution functions of the particles.
In two dimensions we obtain good estimations of the ground-state energies, comparable to results obtained from more conventional methods.
arXiv Detail & Related papers (2021-12-22T15:27:30Z) - Bosonic field digitization for quantum computers [62.997667081978825]
We address the representation of lattice bosonic fields in a discretized field amplitude basis.
We develop methods to predict error scaling and present efficient qubit implementation strategies.
arXiv Detail & Related papers (2021-08-24T15:30:04Z) - Quantum Simulation of the Bosonic Creutz Ladder with a Parametric Cavity [5.336258422653554]
We use a multimode superconducting parametric cavity as a hardware-efficient analog quantum simulator.
We realize a lattice in synthetic dimensions with complex hopping interactions.
The complex-valued hopping interaction further allows us to simulate, for instance, gauge potentials and topological models.
arXiv Detail & Related papers (2021-01-11T14:46:39Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.