Publications associées à Accuracy Assessment of Atomistic Neural Network Potentials: The Impact of Cutoff Radius and Message Passing

Publications associées (12)

Search for Ηc (2s) →ωω and Ωφ and Measurements of Χcj → Ωω and Ωφ in Ψ(2s) Radiative Processes

Using (2712 +/- 14) x 10(6) psi(2S) events collected with the BESIII detector at the BEPCII collider, we search for the decays eta(c) (2S) -> omega omega and eta(c) (2S) -> omega phi via the process psi(2S) -> gamma eta(c)(2S). No statistically significant ...

AMER PHYSICAL SOC2025

Deconfined classical criticality in the anisotropic quantum spin-1 2 XY model on the square lattice

Christopher Marc Mudry

The anisotropic quantum spin- 1 2 XY model on a linear chain was solved by Lieb, Schultz, and Mattis [Ann. Phys. 16, 407 (1961)] and shown to display a continuous quantum phase transition at the O(2) symmetric point separating two gapped phases with compet ...

AMER PHYSICAL SOC2025

Balancing computational chemistry's potential with its environmental impact

Philippe Schwaller, Oliver Tobias Schilter

Computational chemistry techniques offer tremendous potential for accelerating the discovery of sustainable chemical processes and reactions. However, the environmental impacts of the substantial computing power required for these digital methods are often ...

ROYAL SOC CHEMISTRY2024

Magnetic structures in the explicitly time-dependent nontwist map

Lili Édes

We investigate how the magnetic structures of the plasma change in a large aspect ratio tokamak perturbed by an ergodic magnetic limiter, when a system parameter is non-adiabatically varied in time. We model such a scenario by considering the Ullmann-Calda ...

AIP Publishing2024

Adaptive projected variational quantum dynamics

Giuseppe Carleo, Stefano Barison, David Linteau

We propose an adaptive quantum algorithm to prepare accurate variational time evolved wave functions. The method is based on the projected variational quantum dynamics (pVQD) algorithm, that performs a global optimization with linear scaling in the number ...

Amer Physical Soc2024

MiMiCPy: An Efficient Toolkit for MiMiC-Based QM/MM Simulations

Ursula Röthlisberger, Sophia Kathryn Johnson, Andrea Levy

MiMiC is a highly flexible, extremely scalable multiscale modeling framework. It couples the CPMD (quantum mechanics, QM) and GROMACS (molecular mechanics, MM) codes. The code requires preparing separate input files for the two programs with a selection of ...

AMER CHEMICAL SOC2023

Nuclear Quantum Effects in Liquid Water at Near Classical Computational Cost Using the Adaptive Quantum Thermal Bath

Sara Bonella

We demonstrate the accuracy and efficiency of a recently introduced approach to account for nuclear quantum effects (NQEs) in molecular simulations: the adaptive quantum thermal bath (adQTB). In this method, zero-point energy is introduced through a genera ...

2021

Scalable Robust Graph Embedding with Spark

Karl Aberer, Quoc Viet Hung Nguyen, Chi Thang Duong

Graph embedding aims at learning a vector-based representation of vertices that incorporates the structure of the graph. This representation then enables inference of graph properties. Existing graph embedding techniques, however, do not scale well to larg ...

ASSOC COMPUTING MACHINERY2021

Application of machine learning techniques at the CERN Large Hadron Collider

Frédéric Blanc, Tatiana Pieloni, Michael Schenk, Leonid Rivkin, Loïc Thomas Davies Coyle

Machine learning techniques have been used extensively in several domains of Science and Engineering for decades. These powerful tools have been applied also to the domain of high-energy physics, in the analysis of the data from particle collisions, for ye ...

Trieste2020

Atomic Motif Recognition in (Bio)Polymers: Benchmarks From the Protein Data Bank

Michele Ceriotti, Piero Gasparotto, Benjamin Aaron Helfrecht, Federico Giberti

Rationalizing the structure and structure–property relations for complex materials such as polymers or biomolecules relies heavily on the identification of local atomic motifs, e.g., hydrogen bonds and secondary structure patterns, that are seen as buildin ...

2019

Leveraging Hardware Message Passing for Efficient Thread Synchronization

André Schiper, Thomas Ropars, Darko Petrovic

As the level of parallelism in manycore processors keeps increasing, providing efficient mechanisms for thread synchronization in concurrent programs is becoming a major concern. On cache-coherent shared-memory processors, synchronization efficiency is ult ...

Assoc Computing Machinery2014

Toward a Materials Genome Approach for Ionic Liquids: Synthesis Guided by Ab Initio Property Maps

Berend Smit

The Materials Genome Approach (MGA) aims to accelerate development of new materials by incorporating computational and data-driven approaches to reduce the cost of identification of optimal structures for a given application. Here, we use the MGA to guide ...

Amer Chemical Soc2014