Concept

Many-body problem

Related publications (59)

Efficient and insightful descriptors for representing molecular and material space

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

EPFL2024

Self-correcting quantum many-body control using reinforcement learning with tensor networks

Friederike Metz

Quantum many-body control is a central milestone en route to harnessing quantum technologies. However, the exponential growth of the Hilbert space dimension with the number of qubits makes it challenging to classically simulate quantum many-body systems an ...

NATURE PORTFOLIO2023

A recipe for cracking the quantum scaling limit with machine learned electron densities

Mario Geiger

A long-standing goal of science is to accurately simulate large molecular systems using quantum mechanics. The poor scaling of current quantum chemistry algorithms on classical computers, however, imposes an effective limit of about a few dozen atoms on tr ...

IOP Publishing Ltd2023

Learning Physics-Consistent Particle Interactions

Olga Fink, David Simon Kammer, Zhichao Han

Interacting particle systems play a key role in science and engineering. Access to the governing particle interaction law is fundamental for a complete understanding of such systems. However, the inherent system complexity keeps the particle interaction hi ...

Oxford University Press2023

koopmans: An Open-Source Package for Accurately and Efficiently Predicting Spectral Properties with Koopmans Functionals

Nicola Marzari, Nicola Colonna, Edward Baxter Linscott, Ngoc Linh Nguyen, Giovanni Borghi, Riccardo De Gennaro, Andrea Ferretti

Over the past decade we have developed Koopmans functionals, a computationally efficient approach for predicting spectral properties with an orbital-density-dependent functional framework. These functionals impose a generalized piecewise linearity conditio ...

Washington2023

Hidden-nucleons neural-network quantum states for the nuclear many-body problem

Giuseppe Carleo

We generalize the hidden-fermion family of neural network quantum states to encompass both continuous and discrete degrees of freedom and solve the nuclear many-body Schrodinger equation in a systematically improvable fashion. We demonstrate that adding hi ...

AMER PHYSICAL SOC2022

Roadmap on Machine learning in electronic structure

Michele Ceriotti, Jigyasa Nigam, Andrea Grisafi, Max David Veit

In recent years, we have been witnessing a paradigm shift in computational materials science. In fact, traditional methods, mostly developed in the second half of the XXth century, are being complemented, extended, and sometimes even completely replaced by ...

IOP Publishing Ltd2022

Many-Body Self-Interaction and Polarons

Alfredo Pasquarello, Stefano Falletta

We address the many-body self-interaction in relation to polarons in density functional theory. Our study provides (i) a unified theoretical framework encompassing many-body and one-body forms of self-interaction and (ii) an efficient semilocal scheme for ...

2022

Intercalant-mediated Kitaev exchange in Ag3LiIr2O6

Oleg Yazyev, Ravi Yadav

The recently synthesized Ag3LiIr2O6 has been proposed as a Kitaev magnet in proximity to the quantum spin liquid phase. We explore its microscopic Hamiltonian and magnetic ground state using many-body quantum chemistry methods and exact diagonalization tec ...

AMER PHYSICAL SOC2022

Spectral properties of extended systems from Koopmans-compliant functionals

Riccardo De Gennaro

Electronic-structure simulations have been impacting the study of materials properties thanks to the simplicity of density-functional theory, a method that gives access to the ground state of the system. Although very important, ground-state properties rep ...

EPFL2022

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