Publications by Jannes Willy E. Nys

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

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 symmetries into neural representations remains a significant challenge. In th ...

NATURE PORTFOLIO2025

Predicting topological entanglement entropy in a Rydberg analogue simulator

Giuseppe Carleo, Jannes Willy E. Nys

Predicting the dynamical properties of topological matter is a challenging task, not only in theoretical and experimental settings, but also computationally. Numerical studies are often constrained to studying simplified models and lattices. Here we propos ...

2025

Phase Diagram and Crystal Melting of Helium-4 in Two Dimensions

Giuseppe Carleo, Gabriel Maria Pescia, David Linteau, Jannes Willy E. Nys

American Physical Society (APS)2025

Variational benchmarks for quantum many-body problems

Giuseppe Carleo, Riccardo Rossi, Andreas Martin Läuchli Herzig, Filippo Vicentini, Dian Wu, Jannes Willy E. Nys

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 work, we introduce a metric of variational accuracy, the V-score, obtained ...

American Association for the Advancement of Science2024

Message-passing neural quantum states for the homogeneous electron gas

Giuseppe Carleo, Gabriel Maria Pescia, Jannes Willy E. Nys

We introduce a message-passing neural-network (NN)-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 ...

2024

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

Giuseppe Carleo, Gabriel Maria Pescia, Alessandro Sinibaldi, Jannes Willy E. Nys

Understanding the real-time evolution of many-electron quantum systems is essential for studying dynamical properties in condensed matter, quantum chemistry, and complex materials, yet it poses a significant theoretical and computational challenge. Our wor ...

Nature Research2024

Neural-network quantum states for ultra-cold Fermi gases

Giuseppe Carleo, Gabriel Maria Pescia, Jannes Willy E. Nys

Ultra-cold Fermi gases exhibit a rich array of quantum mechanical properties, including the transition from a fermionic superfluid Bardeen-Cooper-Schrieffer (BCS) state to a bosonic superfluid Bose-Einstein condensate (BEC). While these properties can be p ...

Berlin2024

Machine learning exotic hadrons

Jannes Willy E. Nys

We show that a neural network trained with synthetic differential intensities calculated with scattering length approximated amplitudes classifies the Pc(4312)+ signal as a virtual state located at the 4th Riemann sheet with very high certainty. This is in ...

2024

Real-time quantum dynamics of thermal states with neural thermofields

Giuseppe Carleo, Jannes Willy E. Nys

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. Most existing approximating methods are designed to represent static thermal ...

2024

Variational quantum time evolution without the quantum geometric tensor

Giuseppe Carleo, Riccardo Rossi, Julien Sebastian Gacon, Jannes Willy E. Nys, Stefan Woerner

Realand imaginary -time quantum state evolutions are crucial in physics and chemistry for exploring quantum dynamics, preparing ground states, and computing thermodynamic observables. On near -term devices, variational quantum time evolution is a promising ...

Amer Physical Soc2024