English
Related papers

Related papers: Continuum Free-Energy Computing

200 papers

This paper presents a simulation free framework for solving reliability analysis problems. The method proposed is rooted in a recently developed deep learning approach, referred to as the physics-informed neural network. The primary idea is…

Machine Learning · Statistics 2020-06-16 Souvik Chakraborty

We investigate the computational power of creating steady-states of quantum dissipative systems whose evolution is governed by time-independent and local couplings to a memoryless environment. We show that such a model allows for efficient…

Quantum Physics · Physics 2009-09-24 Frank Verstraete , Michael M. Wolf , J. Ignacio Cirac

Finding better solutions to combinatorial optimization problems could have a large positive impact on many real-world application areas, such as logistics. For this reason, significant efforts have been made to design novel optimisation…

We present a real-space formulation and higher-order finite-difference implementation of periodic Orbital-free Density Functional Theory (OF-DFT). Specifically, utilizing a local reformulation of the electrostatic and kernel terms, we…

Computational Physics · Physics 2015-12-23 Swarnava Ghosh , Phanish Suryanarayana

We investigate relaxation dynamics along the entire first-order phase transition line by analyzing the time evolution of the free energy landscape in the three-dimensional kinetic Ising model. Near the critical temperature $T_{\rm c}$, the…

Statistical Mechanics · Physics 2025-08-28 Ranran Guo , Xiaobing Li , Yuming Zhong , Mingmei Xu , Jinghua Fu , Yuanfang Wu

Partial observations of continuous time-series dynamics at arbitrary time stamps exist in many disciplines. Fitting this type of data using statistical models with continuous dynamics is not only promising at an intuitive level but also has…

Machine Learning · Computer Science 2021-10-29 Ruizhi Deng , Marcus A. Brubaker , Greg Mori , Andreas M. Lehrmann

Voltage peaks on a conventional computer's power lines allow for the well-known dangerous DPA attacks. We show that measurement of a quantum computer's transient state during a computational step reveals information about a complete…

Computational Complexity · Computer Science 2008-01-12 Hans-Rudolf Thomann

We present a novel family of continuous, linear time-frequency transforms adaptable to a multitude of (nonlinear) frequency scales. Similar to classical time-frequency or time-scale representations, the representation coefficients are…

Functional Analysis · Mathematics 2024-03-20 Nicki Holighaus , Christoph Wiesmeyr , Peter Balazs

The fundamental energy cost of irreversible computing is given by the Landauer bound of $kT \ln2$~/bit. However, this limit is only achievable for infinite-time processes. We here determine the fundamental energy cost of finite-time…

Statistical Mechanics · Physics 2023-10-03 Michael Konopik , Till Korten , Eric Lutz , Heiner Linke

As an effective emulator of ill-conditioned power flow, continuous Newton methods (CNMs) have been extensively investigated using explicit and implicit numerical integration algorithms. Explicit CNMs are prone to non-convergence issues due…

Systems and Control · Electrical Eng. & Systems 2024-12-02 Ruizhi Yu , Wei Gu , Yijun Xu , Shuai Lu , Suhan Zhang

We present a differentiable soft-body physics simulator that can be composed with neural networks as a differentiable layer. In contrast to other differentiable physics approaches that use explicit forward models to define state…

Machine Learning · Computer Science 2021-09-13 Junior Rojas , Eftychios Sifakis , Ladislav Kavan

This study established a quantum-classical hybrid framework that integrates quantum computing paradigm with meshfree finite particle method. By harnessing quantum superposition and entanglement, it hybridized the critical computational…

Fluid Dynamics · Physics 2025-09-16 Yudong Li , Wenkui Shi , Yan Li , Chunfa Wang , Ling Tao , Zhuojia Fu , Moubin Liu , Zhiqiang Feng

Optimal Power Flow (OPF) is a core optimization problem in power system operation and planning, aiming to minimize generation costs while satisfying physical constraints such as power flow equations, generator limits, and voltage limits.…

Machine Learning · Computer Science 2025-12-02 Xuezhi Liu

The Landau problem in non-commutative quantum mechanics (NCQM) is studied. First by solving the Schr$\ddot{o}$dinger equations on noncommutative(NC) space we obtain the Landau energy levels and the energy correction that is caused by…

Mathematical Physics · Physics 2011-08-31 Sayipjamal Dulat , Kang Li

We establish the potential of continuous-variable Gaussian states of linear dynamical systems for machine learning tasks. Specifically, we consider reservoir computing, an efficient framework for online time series processing. As a…

Form a pure mathematical point of view, common functional forms representing different physical phenomena can be defined. For example, rates of chemical reactions, diffusion and heat transfer are all governed by exponential-type…

Machine Learning · Computer Science 2019-10-01 Navid Zobeiry , Keith D. Humfeld

Landau damping is the mechanism of plasma and beam stabilization; it arises through energy transfer from collective modes to the incoherent motion of resonant particles. Normally this resonance requires the resonant particle's frequency to…

Accelerator Physics · Physics 2018-01-31 Alexandru Macridin , Alexey Burov , Eric Stern , James Amundson , Panagiotis Spentzouris

Collisional processes are critical in the understanding of non-Maxwellian plasmas. The Landau form of the Fokker-Planck equation is the gold standard for modeling collisions in most plasmas, however O(N^2) work complexity inhibits its…

Plasma Physics · Physics 2023-06-07 M. F. Adams , D. P. Brennan , M. G. Knepley , P. Wang

The Phase-Field Method (PFM) is employed to simulate two-phase flows with the fully-coupled Cahn-Hilliard-Navier-Stokes (CHNS) equations governing the temporal evolution. The methodology minimizes the total energy functional, accounting for…

In-memory computing (IMC) is an emerging non-von Neumann paradigm that leverages the intrinsic physics of memory devices to perform computations directly within the memory array. Among the various candidates, phase-change memory (PCM) has…

Mesoscale and Nanoscale Physics · Physics 2025-09-29 Davide G. F. Lombardo , Siddharth Gautam , Alberto Ferraris , Manuel Le Gallo , Abu Sebastian , Ghazi Sarwat Syed
‹ Prev 1 4 5 6 7 8 10 Next ›