activity
20222026
most citedA practical guide to machine learning interatomic potentials -- Status and future

203 citations · 261 across the 21 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cond-mat.stat-mech2024★ 4 cited

Gyromorphs: a new class of functional disordered materials

Mathias Casiulis, Aaron Shih, Stefano Martiniani

We introduce a new class of functional correlated disordered materials, termed Gyromorphs, which uniquely combine liquid-like translational disorder with quasi-long-range rotationa…

physics.chem-ph2024★ 33 cited

On the design space between molecular mechanics and machine learning force fields

Yuanqing Wang, Kenichiro Takaba, Michael S. Chen +14

A force field as accurate as quantum mechanics (QM) and as fast as molecular mechanics (MM), with which one can simulate a biomolecular system efficiently enough and meaningfully e…

cond-mat.stat-mech2024★ 1 cited

The Basins of Attraction of Soft Sphere Packings Are Not Fractal

Praharsh Suryadevara, Mathias Casiulis, Stefano Martiniani

The energy landscape picture is a central tool to study many-body systems. In particular, the energy landscapes of glass-forming liquids, jammed packings, constraint satisfaction p…

cond-mat.soft2024★ 10 cited

A geometric condition for robot-swarm cohesion and cluster-flock transition

Mathias Casiulis, Eden Arbel, Charlotte van Waes +4

We present a geometric design rule for size-controlled clustering of self-propelled particles. We show that active particles that tend to rotate under an external force have an int…

physics.bio-ph2024★ 1 cited

Social Physics of Bacteria: Avoidance of an Information Black Hole

Trung V. Phan, Shengkai Li, Domenic Ferreris +7

Social physics explores responses to information exchange in a social network, and can be mapped down to bacterial collective signaling. Here, we explore how social inter-bacterial…