activity
20142025
most citedNetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems

147 citations · 988 across the 37 of their papers we have counts for

collaborators

37 papers

cond-mat.str-el2025★ 2 cited

Partial suppression of magnetism in the square lattice SU(3) Hubbard model

Samuel Bird, Sebastian Huber, Jannes Nys

The SU(N) Hubbard model is a natural extension of the SU(2) model. However, even the N=3 case remains poorly understood. We report a substantially new ground-state phase diagram of…

physics.chem-ph2025

Precise Quantum Chemistry calculations with few Slater Determinants

Clemens Giuliani, Jannes Nys, Rocco Martinazzo +2

Slater determinants have underpinned quantum chemistry for nearly a century, yet their full potential has remained challenging to exploit. In this work, we show that a variational…

cond-mat.stat-mech2024★ 2 cited

Phase diagram and crystal melting of helium-4 in two dimensions

David Linteau, Gabriel Pescia, Jannes Nys +2

We study the zero-temperature phase diagram of two-dimensional helium-4 using neural quantum states. Our variational description allows us to address liquid and solid phases using…

quant-ph2024★ 1 cited

Local fermion-to-qudit mappings: a practical recipe for four-level systems

Rodolfo Carobene, Stefano Barison, Andrea Giachero +1

In this paper, we present a new set of local fermion-to-qudit mappings for simulating fermionic lattice systems. We focus on the use of multi-level qudits, specifically ququarts. T…

quant-ph2024★ 6 cited

Predicting Topological Entanglement Entropy in a Rydberg analog simulator

Linda Mauron, Zakari Denis, Jannes Nys +1

Predicting the dynamical properties of topological matter is a challenging task, not only in theoretical and experimental settings, but also numerically. This work proposes a varia…

cond-mat.str-el2024★ 5 cited

Spectroscopy of two-dimensional interacting lattice electrons using symmetry-aware neural backflow transformations

Imelda Romero, Jannes Nys, Giuseppe Carleo

Neural networks have shown to be a powerful tool to represent the ground state of quantum many-body systems, including fermionic systems. However, efficiently integrating lattice s…

cond-mat.str-el2024★ 23 cited

Ab-initio variational wave functions for the time-dependent many-electron Schrödinger equation

Jannes Nys, Gabriel Pescia, Alessandro Sinibaldi +1

Understanding the real-time evolution of many-electron quantum systems is essential for studying dynamical properties in condensed matter, quantum chemistry, and complex materials,…

quant-ph2023

Real-time quantum dynamics of thermal states with neural thermofields

Jannes Nys, Zakari Denis, Giuseppe Carleo

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 dynamics.…

physics.comp-ph2023★ 3 cited

Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation

Kirill Neklyudov, Jannes Nys, Luca Thiede +4

Solving the quantum many-body Schrödinger equation is a fundamental and challenging problem in the fields of quantum physics, quantum chemistry, and material sciences. One of the c…

cond-mat.quant-gas2023★ 4 cited

Neural-network quantum states for ultra-cold Fermi gases

Jane Kim, Gabriel Pescia, Bryce Fore +5

Ultra-cold Fermi gases display diverse quantum mechanical properties, including the transition from a fermionic superfluid BCS state to a bosonic superfluid BEC state, which can be…

quant-ph2023★ 48 cited

Message-Passing Neural Quantum States for the Homogeneous Electron Gas

Gabriel Pescia, Jannes Nys, Jane Kim +2

We introduce a message-passing-neural-network-based wave function Ansatz to simulate extended, strongly interacting fermions in continuous space. Symmetry constraints, such as cont…

quant-ph2023★ 29 cited

Variational Quantum Time Evolution without the Quantum Geometric Tensor

Julien Gacon, Jannes Nys, Riccardo Rossi +2

The real- and imaginary-time evolution of quantum states are powerful tools in physics, chemistry, and beyond, to investigate quantum dynamics, prepare ground states or calculate t…

quant-ph2023★ 67 cited

Variational Benchmarks for Quantum Many-Body Problems

Dian Wu, Riccardo Rossi, Filippo Vicentini +30

The continued development of computational approaches to many-body ground-state problems in physics and chemistry calls for a consistent way to assess its overall progress. In this…

quant-ph2022★ 2 cited

Quantum circuits for solving local fermion-to-qubit mappings

Jannes Nys, Giuseppe Carleo

Local Hamiltonians of fermionic systems on a lattice can be mapped onto local qubit Hamiltonians. Maintaining the locality of the operators comes at the expense of increasing the H…

cond-mat.str-el2022★ 18 cited

Variational solutions to fermion-to-qubit mappings in two spatial dimensions

Jannes Nys, Giuseppe Carleo

Through the introduction of auxiliary fermions, or an enlarged spin space, one can map local fermion Hamiltonians onto local spin Hamiltonians, at the expense of introducing a set…

quant-ph2021★ 147 cited

NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems

Filippo Vicentini, Damian Hofmann, Attila Szabó +8

We introduce version 3 of NetKet, the machine learning toolbox for many-body quantum physics. NetKet is built around neural-network quantum states and provides efficient algorithms…

cond-mat.str-el2021★ 27 cited

Many-Body Quantum States with Exact Conservation of Non-Abelian and Lattice Symmetries through Variational Monte Carlo

Tom Vieijra, Jannes Nys

Optimization of quantum states using the variational principle has recently seen an upsurge due to developments of increasingly expressive wave functions. In order to improve on th…

nucl-th2020★ 2 cited

Modeling neutrino-nucleus interaction at intermediate energies

R. González-Jiménez, N. Jachowicz, A. Nikolakopoulos +5

We present the current status of the research activities of the Ghent group on neutrino-nucleus interactions. These consist in the modeling of some of the relevant neutrino-nucleus…

cond-mat.str-el2019★ 104 cited

Restricted Boltzmann Machines for Quantum States with Nonabelian or Anyonic Symmetries

Tom Vieijra, Corneel Casert, Jannes Nys +4

Although artificial neural networks have recently been proven to provide a promising new framework for constructing quantum many-body wave functions, the parameterization of a quan…

hep-ph2018★ 111 cited

Determination of the pole position of the lightest hybrid meson candidate

JPAC Collaboration, A. Rodas, A. Pilloni +9

Mapping states with explicit gluonic degrees of freedom in the light sector is a challenge, and has led to controversies in the past. In particular, the experiments have reported t…

hep-ph2018★ 37 cited

Pole position of the from -decay

JPAC Collaboration, M. Mikhasenko, A. Pilloni +8

We perform an analysis of the three-pion system with quantum numbers produced in the weak decay of leptons. The interaction is known to be dominated by the axia…

hep-ph2018★ 10 cited

Regge phenomenology of the and poles

JPAC collaboration, J. A. Silva-Castro, C. Fernandez-Ramirez +8

We use Regge phenomenology to study the structure of the poles of the and spectrum. We employ the available pole extractions from partial wave analysis of meson scatter…

nucl-th2018★ 22 cited

The isospin and neutron-to-proton excess dependence of short-range correlations

Jan Ryckebusch, Wim Cosyn, Sam Stevens +2

We provide a systematic study of the isospin composition and neutron-to-proton ratio dependence of nuclear short-range correlations (SRC) across the nu…

cond-mat.stat-mech2018★ 40 cited

Interpretable machine learning for inferring the phase boundaries in a nonequilibrium system

C. Casert, T. Vieijra, J. Nys +1

Still under debate is the question of whether machine learning is capable of going beyond black-box modeling for complex physical systems. We investigate the generalizing and inter…