147 citations · 261 across the 8 of their papers we have counts for
8 papers
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…
Simulating continuous-space systems with quantum-classical wave functions
Friederike Metz, Gabriel Pescia, Giuseppe Carleo
Most non-relativistic interacting quantum many-body systems, such as atomic and molecular ensembles or materials, are naturally described in terms of continuous-space Hamiltonians.…
Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants
Beatriz Borges, Negar Foroutan, Deniz Bayazit +87
AI assistants are being increasingly used by students enrolled in higher education institutions. While these tools provide opportunities for improved teaching and education, they a…
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,…
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…
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…
Neural-Network Quantum States for Periodic Systems in Continuous Space
Gabriel Pescia, Jiequn Han, Alessandro Lovato +2
We introduce a family of neural quantum states for the simulation of strongly interacting systems in the presence of spatial periodicity. Our variational state is parameterized in…
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…