English
Related papers

Related papers: Machine learning for phase ordering dynamics of ch…

200 papers

On the basis of the recently proposed {\it Thermal Wave Model (TWM) for particle beams}, we give a description of the longitudinal charge particle dynamics in circular accelerating machines by taking into account both radiation damping and…

acc-phys · Physics 2015-06-24 R. Fedele , G. Miele , L. Palumbo

Models of many-body localization (MBL) exhibit slow numerical drifts towards delocalization with increasing system size, for which no satisfactory theory exists. Numerics indicates that these drifts are driven by the proliferation of…

Disordered Systems and Neural Networks · Physics 2026-05-08 Carlo Vanoni , David M. Long , Anushya Chandran

We analyze the interplay between a d-wave uniform superconducting and a pair-density-wave (PDW) order parameter in the neighborhood of a vortex. We develop a phenomenological nonlinear sigma-model, solve the saddle point equation for the…

Reinforcement learning (RL) has made significant advancements, achieving superhuman performance in various tasks. However, RL agents often operate under the assumption of environmental stationarity, which poses a great challenge to learning…

Machine Learning · Computer Science 2025-11-18 Guoqing Ma , Yuhan Zhang , Yuming Dai , Guangfu Hao , Yang Chen , Shan Yu

How condensed-matter simulations depend on the number of molecules being simulated ($N$) is sometimes itself a valuable piece of information. Liquid crystals provide a case in point. Light scattering and $2d$-IR experiments on…

Soft Condensed Matter · Physics 2024-12-20 Eleftherios Mainas , Richard M. Stratt

Pair density waves (PDW) are novel forms of superconducting states that exhibit periodically modulated pairing. A remaining challenge is to elucidate how intrinsic PDW order can emerge robustly in strongly correlated electrons. Here we…

Superconductivity · Physics 2025-12-09 Hao-Xin Wang , Yi-Jian Hu , Wen Huang , Hong Yao

We study the phase-ordering dynamics of a quasi-classical Holstein model. At half-filling, the zero-temperature ground state is a commensurate charge-density-wave (CDW) with alternating occupied and empty sites. This quasi-classical…

Statistical Mechanics · Physics 2025-12-09 Ho Jang , Yang Yang , Gia-Wei Chern

The appearance of an incommensurate charge density wave vector $\textbf{Q} = (Q_x,Q_y)$ on multiband intermetallic systems presenting commensurate charge density wave (CDW) and superconductivity (SC) orders is investigated. We consider a…

Strongly Correlated Electrons · Physics 2023-05-24 Nei Lopes , Daniel Reyes , Natanael C. Costa , Mucio A. Continentino , Christopher Thomas

Incommensurate charge density waves (CDW) have the extraordinary ability to display non-Ohmic behavior when submitted to an external field. The mechanism leading to this non trivial dynamics is still not well understood, although recent…

Strongly Correlated Electrons · Physics 2020-04-01 E. Bellec , I. Gonzalez-Vallejo , V. L. R. Jacques , A. A. Sinchenko , A. P. Orlov , P. Monceau , S. J. Leake , D. Le Bolloc'h

The charge density wave (CDW) state of 2H-NbSe$_2$ features commensurate domains separated by domain boundaries accompanied by phase slips known as discommensurations. We have unambiguously visualized the structure of CDW domains using a…

Strongly Correlated Electrons · Physics 2024-01-30 Shunsuke Yoshizawa , Keisuke Sagisaka , Hideaki Sakata

We present an approach to simulate the Schr\"odinger equation through continuous time quantum walks. The CTQW-based simulation applies unitary evolution driven by a quantum walk to generate probability amplitude distributions at various…

Quantum Physics · Physics 2025-09-16 Rachana Soni , Navneet Pratap Singh

Charge-density-wave (CDW) instability and pressure-induced superconductivity in bulk 1T-NbS2 are predicted theoretically by first-principles calculations. We reveal a CDW instability towards the formation of a stable commensurate CDW order,…

Strongly Correlated Electrons · Physics 2020-10-20 Wei Wang , Bosen Wang , Zhibin Gao , Gang Tang , Wen Lei , Xiaojun Zheng , Huan Li , Xing Ming , Carmine Autieri

Many real-world applications require aligning two temporal sequences, including bioinformatics, handwriting recognition, activity recognition, and human-robot coordination. Dynamic Time Warping (DTW) is a popular alignment method, but can…

Machine Learning · Computer Science 2021-09-21 Sridhar Mahadevan , Anup Rao , Georgios Theocharous , Jennifer Healey

The Dynamical Graph Grammar (DGG) formalism can describe complex system dynamics with graphs that are mapped into a master equation. An exact stochastic simulation algorithm may be used, but it is slow for large systems. To overcome this…

Quantitative Methods · Quantitative Biology 2024-07-16 Eric Medwedeff , Eric Mjolsness

Since their theoretical prediction by Peierls in the 30s, charge density waves (CDW) have been one of the most commonly encountered electronic phases in low dimensional metallic systems. The instability mechanism originally proposed…

A pair-density-wave (PDW) is a novel superconducting state with an oscillating order parameter. A microscopic mechanism that can give rise to it has been long sought but has not yet been established by any controlled calculation. Here we…

Strongly Correlated Electrons · Physics 2022-02-07 Kevin S. Huang , Zhaoyu Han , Steven A. Kivelson , Hong Yao

Electronic phases in quantum materials are often governed by nanoscale inhomogeneity, where local order develops within spatially confined regions or puddles. A prominent example is an incommensurate charge-density-wave (I-CDW) that…

Taking into account that a proper description of disordered systems should focus on distribution functions, the authors develop a powerful numerical scheme for the determination of the probability distribution of the local density of states…

Disordered Systems and Neural Networks · Physics 2013-06-20 Gerald Schubert , Alexander Weisse , Gerhard Wellein , Holger Fehske

Dynamical systems that evolve continuously over time are ubiquitous throughout science and engineering. Machine learning (ML) provides data-driven approaches to model and predict the dynamics of such systems. A core issue with this approach…

Machine Learning · Computer Science 2023-11-23 Aditi S. Krishnapriyan , Alejandro F. Queiruga , N. Benjamin Erichson , Michael W. Mahoney

Complex systems, which consist of a large number of interacting constituents, often exhibit universal behavior near a phase transition. A slowdown of certain dynamical observables is one such recurring feature found in a vast array of…