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Spatial interferometry, based on the measurement of total absorbed power, can be used to determine the state of coherence of the electromagnetic field to which any energy-absorbing structure is sensitive. The measured coherence tensor can…

Quantum Physics · Physics 2015-06-11 Stafford Withington , Christopher N. Thomas

Machine learning for the parameterization of subgrid-scale processes in climate models has been widely researched and adopted in a few models. A key challenge in developing data-driven parameterization schemes is how to properly represent…

Atmospheric and Oceanic Physics · Physics 2024-02-29 L. Minah Yang , Edwin P. Gerber

Improving distribution grid reliability is a major challenge for planning and operation of distribution systems having a high share of distributed generators (DGs). The rise of DGs share can lead to unplanned contingencies while on the…

Systems and Control · Electrical Eng. & Systems 2020-04-23 Sohail Khan , Sawsan Henein , Helfried Brunner

Power electronic devices such as HVDC and FACTS can be used to improve the damping of poorly damped inter-area modes in large power systems. This involves the use of wide-area feedback signals, which are transmitted via communication…

Systems and Control · Electrical Eng. & Systems 2022-11-17 K. K. Gajjar , Kaustav Dey , A. M. Kulkarni

Large-scale power system planning mostly uses linearized, active power only approximations of the power flow equations, ignores many operational constraints, and tests the operational feasibility of the resulting systems only under strongly…

Optimization and Control · Mathematics 2026-04-03 Gereon Recht , Oussama Alaya , Benedikt Jahn , Karl-Kiên Cao , Hendrik Lens

Learning to sample from complex unnormalized distributions is a fundamental challenge in computational physics and machine learning. While score-based and variational methods have achieved success in continuous domains, extending them to…

Machine Learning · Statistics 2026-03-11 Lei Li , Zhen Wang , Lishuo Zhang

Discrete diffusion models form a powerful class of generative models across diverse domains, including text and graphs. However, existing approaches face fundamental limitations. Masked diffusion models suffer from irreversible errors due…

Machine Learning · Computer Science 2026-04-21 Marcel Kollovieh , Sirine Ayadi , Stephan Günnemann

Precipitation results from complex processes across many scales, making its accurate simulation in Earth system models (ESMs) challenging. Existing post-processing methods can improve ESM simulations locally, but cannot correct errors in…

Atmospheric and Oceanic Physics · Physics 2025-01-03 Philipp Hess , Markus Drüke , Stefan Petri , Felix M. Strnad , Niklas Boers

The sensitivity of Ramsey interferometry experiments is governed by the interplay between the beam phase-space distribution and the magnetic field environment through which the spins propagate. Quantitative optimisation thus requires a…

Instrumentation and Detectors · Physics 2026-03-26 Linus B. Persson , Peter Fierlinger , Matthias Holl , Valentina Santoro

Converter-interfaced power sources (CIPSs), like wind turbine and energy storage, can be switched to the inertia emulation mode when the detected frequency deviation exceeds a pre-designed threshold, i.e. dead band, to support the frequency…

Systems and Control · Computer Science 2016-11-10 Bin Wang , Yichen Zhang , Kai Sun , Kevin Tomsovic

Given a sequence of observations from a discrete-time, finite-state hidden Markov model, we would like to estimate the sampling distribution of a statistic. The bootstrap method is employed to approximate the confidence regions of a…

Computation · Statistics 2009-09-29 Cheng-Der Fuh , Inchi Hu

The entropic sampling dynamics based on the reversible information transfer to and from the environment is applied to the globally coupled Ising model in the presence of an oscillating magnetic field. When the driving frequency is low…

Statistical Mechanics · Physics 2007-05-23 Beom Jun Kim , M. Y. Choi

Wide-area dynamic studies are of paramount importance to ensure the stability and reliability of power grids. The rising deployment synchrophasor and other sensing technologies has made data-driven modeling and analysis possible using the…

Systems and Control · Electrical Eng. & Systems 2022-05-09 Shaohui Liu , Hao Zhu , Vassilis Kekatos

Datasets with missing values are very common on industry applications, and they can have a negative impact on machine learning models. Recent studies introduced solutions to the problem of imputing missing values based on deep generative…

Machine Learning · Computer Science 2019-02-28 Ramiro D. Camino , Christian A. Hammerschmidt , Radu State

For noisy compressive sensing systems, the asymptotic distortion with respect to an arbitrary distortion function is determined when a general class of least-square based reconstruction schemes is employed. The sampling matrix is considered…

Information Theory · Computer Science 2017-04-27 Ali Bereyhi , Ralf Müller , Hermann Schulz-Baldes

A systematic method for the design of linear residual generators for combined fault detection and estimation in nonlinear systems is developed. The proposed residual generator is a linear functional observer built for an extended system…

Systems and Control · Electrical Eng. & Systems 2026-01-01 Sunjeev Venkateswaran , Costas Kravaris

We introduce a new technique called Drapes to enhance the sensitivity in searches for new physics at the LHC. By training diffusion models on side-band data, we show how background templates for the signal region can be generated either…

Data Analysis, Statistics and Probability · Physics 2023-12-20 Debajyoti Sengupta , Matthew Leigh , John Andrew Raine , Samuel Klein , Tobias Golling

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving…

Computational Physics · Physics 2017-01-04 Huan Lei , Xiu Yang , Zhen Li , George Karniadakis

A random-phase approximation (RPA) treatment of edge magnetoplasmons (EMP) is presented for strong magnetic fields, low temperatures, and integer filling factors \nu. It is valid for negligible dissipation and lateral confining potentials…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 O. G. Balev , P. Vasilopoulos

In this paper, a novel distributed controller for multimachine power systems is proposed to guarantee grid frequency restoration and accurate real and reactive power sharing among the generator units, while maintaining the generator inputs…

Systems and Control · Electrical Eng. & Systems 2024-02-15 Theodoros E. Kavvathas , George C. Konstantopoulos , Charalambos Konstantinou