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This paper presents Text2Structure3D, a graph-based Machine Learning (ML) model that generates equilibrium structures from natural language prompts. Text2Structure3D is designed to support new intuitive ways of design exploration and…

Computational Engineering, Finance, and Science · Computer Science 2026-01-21 Lazlo Bleker , Zifeng Guo , Kaleb Smith , Kam-Ming Mark Tam , Karla Saldaña Ochoa , Pierluigi D'Acunto

With the growing demand for high-quality image generation on resource-constrained devices, efficient diffusion models have received increasing attention. However, such models suffer from approximation errors introduced by efficiency…

Machine Learning · Computer Science 2026-02-10 Yunshan Zhong , Weiqi Yan , Yuxin Zhang

Controlling the flow of matter down to micrometer-scale confinement is of central importance in materials and environmental sciences, with direct applications in nano-microfluidics, drug delivery and biothechnology. Currents of…

Soft Condensed Matter · Physics 2019-11-18 Helena Massana-Cid , Antonio Ortiz-Ambriz , Andrej Vilfan , Pietro Tierno

Diffusion is a dissipative transport phenomenon ubiquitously present in nature. Its details can now be analysed with modern effective field theory (EFT) techniques that use the closed-time-path (or Schwinger-Keldysh) formalism. We discuss…

High Energy Physics - Theory · Physics 2024-10-03 Sašo Grozdanov , Timotej Lemut , Jaka Pelaič , Alexander Soloviev

Diffusion-based generative graph models have been proven effective in generating high-quality small graphs. However, they need to be more scalable for generating large graphs containing thousands of nodes desiring graph statistics. In this…

Machine Learning · Computer Science 2023-06-01 Xiaohui Chen , Jiaxing He , Xu Han , Li-Ping Liu

In a recent article, Krapivsky and Redner (J. Stat. Mech. 093208 (2018)) established that the distribution of the first hitting times for a diffusing particle subject to hitting an absorber is independent of the direction of the external…

Statistical Mechanics · Physics 2020-01-29 Coline Larmier , Alain Mazzolo , Andrea Zoia

Spectral crowding of collective motional modes limits the fidelity of entangling interactions in trapped-ion quantum processors by inducing off-resonant coupling to spectator modes. We introduce a geometric-phase entangling interaction…

Graph is a prevalent discrete data structure, whose generation has wide applications such as drug discovery and circuit design. Diffusion generative models, as an emerging research focus, have been applied to graph generation tasks.…

Machine Learning · Computer Science 2024-11-05 Zhe Xu , Ruizhong Qiu , Yuzhong Chen , Huiyuan Chen , Xiran Fan , Menghai Pan , Zhichen Zeng , Mahashweta Das , Hanghang Tong

Topological phase transitions can be remarkably induced purely by manipulating gain and loss mechanisms, offering a novel approach to engineering topological properties. Recent theoretical studies have revealed gain-loss-induced topological…

Mesoscale and Nanoscale Physics · Physics 2025-02-27 Jin Liu , Wei-Wu Jin , Zhao-Fan Cai , Xin Wang , Yu-Ran Zhang , Xiaomin Wei , Wenbo Ju , Zhongmin Yang , Tao Liu

The increasing integration of Inverter-Based Resources (IBRs) is reshaping fault current characteristics, presenting significant challenges to traditional protection and fault location methods. This paper addresses a key limitation in fault…

Systems and Control · Electrical Eng. & Systems 2025-12-05 Alailton J. Alves Junior , Daniel Barbosa , Ricardo A. S. Fernandes , Denis V. Coury

We consider the problem of electron transport in segregated conductor-insulator composites in which the conducting particles are connected to all others via tunneling conductances, thus forming a global tunnelingconnected resistor network.…

Disordered Systems and Neural Networks · Physics 2012-01-23 B. Nigro , C. Grimaldi , P. Ryser

We establish the zero-diffusion limit for both continuous and discrete aggregation models over convex and bounded domains. Compared with a similar zero-diffusion limit derived in [44], our approach is different and relies on a coupling…

Analysis of PDEs · Mathematics 2018-09-07 Razvan C. Fetecau , Hui Huang , Daniel Messenger , Weiran Sun

AI-based molecule generation provides a promising approach to a large area of biomedical sciences and engineering, such as antibody design, hydrolase engineering, or vaccine development. Because the molecules are governed by physical laws,…

Machine Learning · Computer Science 2022-09-05 Lemeng Wu , Chengyue Gong , Xingchao Liu , Mao Ye , Qiang Liu

A class of generative models that unifies flow-based and diffusion-based methods is introduced. These models extend the framework proposed in Albergo and Vanden-Eijnden (2023), enabling the use of a broad class of continuous-time stochastic…

Machine Learning · Computer Science 2025-10-10 Michael S. Albergo , Nicholas M. Boffi , Eric Vanden-Eijnden

The analytical solution of the equation describing diffusion of intrinsic point defects has been obtained for a one-dimensional finite-length domain. This solution is intended for investigating and modeling the changes in defect…

Materials Science · Physics 2014-06-26 O. I. Velichko

We have previously discussed the diffusion limited problem of the bounded one-dimensional multitrap system where no external fiel is included and pay special attention to the transmission of the diffusing particles through the system of…

Classical Physics · Physics 2009-11-10 D. Bar

When particles are magnetized, a diffusion process is influenced by the ambient magnetic field. While the entropy increases, the constancy of the magnetic moment puts a constraint. Here, we compare the E-cross-B diffusion caused by random…

Plasma Physics · Physics 2018-01-25 Naoki Sato , Zensho Yoshida

The rate-limiting step of some enzymatic reactions is a physical step, i.e. diffusion. The efficiency of such reactions can be improved through an increase in the arrival rate of the substrate molecules, e.g. by a directed passage of…

Biological Physics · Physics 2007-05-23 Mehrdad Ghaemi , Nasrollah Rezaei-Ghaleh , Mohammad-Nabi Sarbolouki

Denoising diffusion bridge models (DDBMs) are a powerful variant of diffusion models for interpolating between two arbitrary paired distributions given as endpoints. Despite their promising performance in tasks like image translation, DDBMs…

Machine Learning · Computer Science 2025-05-01 Kaiwen Zheng , Guande He , Jianfei Chen , Fan Bao , Jun Zhu

In this work we present the results of a study of the possibility of using a homogeneous basis and a new generalization of coupled modes theory to describe inhomogeneous accelerating sections. It was shown that the single mode…

Accelerator Physics · Physics 2024-09-24 M. I. Ayzatsky
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