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This paper presents a dual-domain low-complexity expectation propagation (EP) detection framework for affine frequency division multiplexing (AFDM) systems. By analyzing the structural properties of the effective channel matrices in both…

Signal Processing · Electrical Eng. & Systems 2026-04-01 Qin Yi , Ping Yang , Zilong Liu , Zeping Sui , Yue Xiao , Gang Wu

We consider the asymmetric six--vertex model, {\it i.e.} the symmetric six--vertex model in an external field with both horizontal and vertical components, and the relevant asymmetric $XXZ$ chain. The model is widely used to describe the…

Condensed Matter · Physics 2011-07-19 Giuseppe Albertini , Silvio Renato Dahmen , Birgit Wehefritz

The Voltage-Dependent Anion Channel (VDAC) protein is the primary conduit for the regulated passage of ions and metabolites into and out of mitochondria. Calculating its solvation free energy is crucial for understanding its stability,…

Biomolecules · Quantitative Biology 2024-07-03 Liam Jemison , Matthew Stahl , Ranjan K. Dash , Dexuan Xie

Existing molecular machine learning force fields (MLFFs) generally focus on the learning of atoms, molecules, and simple quantum chemical properties (such as energy and force), but ignore the importance of electron density (ED) $\rho(r)$ in…

Chemical Physics · Physics 2025-09-25 Hongxin Xiang , Ke Li , Mingquan Liu , Zhixiang Cheng , Bin Yao , Wenjie Du , Jun Xia , Li Zeng , Xin Jin , Xiangxiang Zeng

The AlphaFold Protein Structure Database (AFDB) offers unparalleled structural coverage at near-experimental accuracy, positioning it as a valuable resource for data-driven protein design. However, its direct use in training deep models…

Machine Learning · Computer Science 2025-06-11 Cheng Tan , Zhenxiao Cao , Zhangyang Gao , Siyuan Li , Yufei Huang , Stan Z. Li

The free energy principle (FEP), along with the associated constructs of Markov blankets and ontological potentials, have recently been presented as the core components of a generalized modeling method capable of mathematically describing…

Neurons and Cognition · Quantitative Biology 2025-03-03 Jeff Beck , Maxwell J. D. Ramstead

High-precision molecular experiments testing the Standard Model of particle physics require an accurate understanding of the molecular structure at the hyperfine level, both for the control of the molecules and for the interpretation of the…

Atomic Physics · Physics 2025-11-19 Yuly Chamorro , Felix Kogel , Tim Langen , Anastasia Borschevsky

Autonomous Experimentation Platforms (AEPs) are advanced manufacturing platforms that, under intelligent control, can sequentially search the material design space (MDS) and identify parameters with the desired properties. At the heart of…

Machine Learning · Computer Science 2023-02-28 Ahmed Shoyeb Raihan , Imtiaz Ahmed

Predicting student success or failure is vital for timely interventions and personalized support. Early failure prediction is particularly crucial, yet limited data availability in the early stages poses challenges, one of the possible…

Computers and Society · Computer Science 2025-05-13 Ikram Gagaoua , Armelle Brun , Anne Boyer

The efficiency of minimum-energy configuration searching algorithms is closely linked to the energy landscape structure of complex systems. Here we characterize this structure by following the time evolution of two systems, vacancy…

In this review we focus on the determination of phase diagrams by computer simulation with particular attention to the fluid-solid and solid-solid equilibria. The calculation of the free energy of solid phases using the Einstein crystal and…

Statistical Mechanics · Physics 2009-01-14 C. Vega , E. Sanz , J. L. F. Abascal , E. G. Noya

The Bethe free energy approximation provides an effective way for relaxing NP-hard problems of probabilistic inference. However, its accuracy depends on the model parameters and particularly degrades if a phase transition in the model…

Machine Learning · Statistics 2024-10-24 Harald Leisenberger , Christian Knoll , Franz Pernkopf

The finite element methods (FEM) are important techniques in engineering for solving partial differential equations, but they depend heavily on element shape quality for stability and good performance. In this paper, we introduce the…

Numerical Analysis · Mathematics 2016-03-30 Rebecca Conley , Tristan J. Delaney , Xiangmin Jiao

The perturbative expansion introduced by Zwanzig [R. W. Zwanzig, J. Chem. Phys. {\bf 22}, 1420 (1954)] expresses the difference in Helmholtz free energy between a system of interest and that of a reference system as series of cumulants…

Computational Physics · Physics 2020-10-01 C. W. Greeff

The Free Energy Principle (FEP) is a theoretical framework for describing how (intelligent) systems self-organise into coherent, stable structures by minimising a free energy functional. Active Inference (AIF) is a corollary of the FEP that…

Artificial Intelligence · Computer Science 2023-10-17 Magnus Koudahl , Thijs van de Laar , Bert de Vries

We discuss the low energy effective dynamics of gapless excitations of the mass vortices of systems similar to the Ginzburg-Landau description of superfluid helium-3 in the bulk B phase. Our approach is to determine the vortex solution by…

Other Condensed Matter · Physics 2014-02-26 Adam J Peterson , Mikhail Shifman

Free Electron Lasers (FELs) are a solution for providing intense, coherent and bright radiation in the hard X-ray regime. Due to the low wall-plug efficiency of FEL facilities, it is crucial and additionally very useful to develop complete…

Computational Physics · Physics 2018-04-10 Arya Fallahi , Alireza Yahaghi , Franz X. Kärtner

Accurate prediction of protein-ligand binding affinity is crucial for rapid and efficient drug development. Recently, the importance of predicting binding affinity has led to increased attention on research that models the three-dimensional…

Machine Learning · Computer Science 2024-07-17 Seungyeon Choi , Sangmin Seo , Sanghyun Park

Energy-Based Models (EBMs) have proven to be a highly effective approach for modelling densities on finite-dimensional spaces. Their ability to incorporate domain-specific choices and constraints into the structure of the model through…

Machine Learning · Computer Science 2023-02-24 Jen Ning Lim , Sebastian Vollmer , Lorenz Wolf , Andrew Duncan

We introduce an efficient and robust method to compute alchemical free energy differences, resulting from the application of multiple walker Adaptive Biasing Force (ABF) in conjunction with strongly damped Langevin $\lambda$-dynamics.…