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High-throughput computational screening of polymers offers a powerful way to address the imbalance between the vast number of polymers synthesised for diverse applications and the relatively small subset that can be studied using atomistic…

Materials Science · Physics 2026-03-12 Lois Smith , Samuel Ericson , Vittoria Fantauzzo , Chin Yong , Paola Carbone , Alessandro Troisi

Learning matrix-valued distributions from high-dimensional and possibly incomplete training data is challenging: ambient-space generative modeling is computationally expensive and statistically fragile when the matrix dimension is large but…

Machine Learning · Computer Science 2026-04-29 Dongze Wu , Linglingzhi Zhu , Yao Xie

Machine learning has recently emerged as a powerful tool for generating new molecular and material structures. The success of state-of-the-art models stems from their ability to incorporate physical symmetries, such as translation,…

Machine Learning · Computer Science 2024-05-16 Bingqing Cheng

Polymerase chain reaction (PCR) underpins modern molecular biology, yet its deployment in emerging domains such as DNA data storage and distributed diagnostics remains constrained by bulky thermocyclers, complex thermal hardware, and…

We present a new scenario for the formation of cool cores in rich galaxy clusters based on results from recent high spatial dynamic range, adaptive mesh Eulerian hydrodynamic simulations of large-scale structure formation. We find that…

Astrophysics · Physics 2008-11-26 Patrick M. Motl , Jack O. Burns , Chris Loken , Michael L. Norman , Greg Bryan

Generative models for molecules have shown considerable promise for use in computational chemistry, but remain difficult to use for non-experts. For this reason, we introduce open-source infrastructure for easily building generative…

Machine Learning · Computer Science 2024-12-02 V Shreyas , Jose Siguenza , Karan Bania , Bharath Ramsundar

The development of large language models and multi-modal models has enabled the appealing idea of generating novel molecules from text descriptions. Generative modeling would shift the paradigm from relying on large-scale chemical screening…

Machine Learning · Computer Science 2025-08-25 Yifan Deng , Spencer S. Ericksen , Anthony Gitter

A numerical model and parallel software for 3D simulations of granular flows have been developed based on the Lagrangian particle (LP) method [R.Samulyak, X. Wang, H.-C. Chen, Lagrangian particle method for compressible fluid dynamics, J.…

Computational Physics · Physics 2022-06-29 Mario Zepeda , Roman Samulyak

Flows of particles through bottlenecks are ubiquitous in nature and industry, involving both dry granular materials and suspensions. However, practical limitations of conventional experimental setups hinder the full understanding of these…

Soft Condensed Matter · Physics 2025-07-02 Lars Kool , Jules Tampier , Philippe Bourrianne , Anke Lindner

We present an experimental study of the statistical properties of millimeter-size spheres floating on the surface of a turbulent flow. The flow is generated in a layer of liquid metal by an electromagnetic forcing. By using two magnet…

Fluid Dynamics · Physics 2016-07-04 Pablo Gutiérrez , Sébastien Aumaître

Generative models excel at synthesizing high-fidelity samples from complex data distributions, but they often violate hard constraints arising from physical laws or task specifications. A common remedy is to project intermediate samples…

Machine Learning · Computer Science 2025-09-30 Jinhao Liang , Yixuan Sun , Anirban Samaddar , Sandeep Madireddy , Ferdinando Fioretto

As an attempt to understand the homochirality of organic molecules in life, a chemical reaction model is proposed where the production of chiral monomers from achiral substrate is catalyzed by the polymers of the same enatiomeric type. This…

Biological Physics · Physics 2007-07-20 Yukio Saito , Hiroyuki Hyuga

An important goal of self-assembly is to achieve a preprogrammed structure with high fidelity. Here, we control the valence of DNA-functionalized emulsions to make linear and branched model polymers, or `colloidomers'. The distribution of…

Soft Condensed Matter · Physics 2018-10-03 Angus McMullen , Miranda Holmes-Cerfon , Francesco Sciortino , Alexander Y. Grosberg , Jasna Brujic

We propose a hierarchical normalizing flow model for generating molecular graphs. The model produces new molecular structures from a single-node graph by recursively splitting every node into two. All operations are invertible and can be…

Chemical Physics · Physics 2021-06-11 Maksim Kuznetsov , Daniil Polykovskiy

Efficiently retrieving an enormous chemical library to design targeted molecules is crucial for accelerating drug discovery, organic chemistry, and optoelectronic materials. Despite the emergence of generative models to produce novel…

Computational Engineering, Finance, and Science · Computer Science 2024-09-13 Zijun Chen , Yu Wang , Liuzhenghao Lv , Hao Li , Zongying Lin , Li Yuan , Yonghong Tian

Conformal prediction provides a distribution-free framework for uncertainty quantification via prediction sets with exact finite-sample coverage. In low dimensions these sets are easy to interpret, but in high-dimensional or structured…

Machine Learning · Statistics 2026-05-08 Trevor Harris

Flow matching has emerged as a promising generative approach that addresses the lengthy sampling times associated with state-of-the-art diffusion models and enables a more flexible trajectory design, while maintaining high-quality image…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Arnela Hadzic , Franz Thaler , Lea Bogensperger , Simon Johannes Joham , Martin Urschler

In the present work, the cyclic polymer chains (rings) in structurally disordered environment (e.g. in the cross-linked polymer gel) are studied exploiting the model of closed self-avoiding walks (SAWs) trajectories on $d=3$-dimensional…

Soft Condensed Matter · Physics 2020-11-04 K. Haydukivska , V. Blavatska

Flow matching has emerged as a simulation-free alternative to diffusion-based generative modeling, producing samples by solving an ODE whose time-dependent velocity field is learned along an interpolation between a simple source…

Machine Learning · Statistics 2026-04-10 Shivam Kumar , Yixin Wang , Lizhen Lin

We investigate the process of circularly polarized high harmonic generation in molecules using a bicircular laser field. In this context, we show that molecules offer a very robust framework for the production of circularly polarized…

Atomic Physics · Physics 2016-06-22 F Mauger , A. D. Bandrauk , T Uzer