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Magnetorotational instability (MRI) is one of the fundamental processes in astrophysics, driving angular momentum transport and mass accretion in a wide variety of cosmic objects. Despite much theoretical/numerical and experimental efforts…

Fluid Dynamics · Physics 2017-11-28 G. Mamatsashvili , F. Stefani , A. Guseva , M. Avila

Linear Quadratic Regulator (LQR) is often combined with feedback linearization (FBL) for nonlinear systems that have the nonlinearity additive to the input. Conventional approaches estimate and cancel the nonlinearity based on the first…

Systems and Control · Electrical Eng. & Systems 2024-12-04 Takahito Fujimori

Headline constraints on cosmological parameters from current weak lensing surveys are derived from two-point statistics that are known to be statistically sub-optimal, even in the case of Gaussian fields. We study the performance of a new…

Cosmology and Nongalactic Astrophysics · Physics 2023-02-15 Alessandro Maraio , Alex Hall , Andy Taylor

We compute scalar quasinormal mode (QNM) frequencies in rotating black hole solutions of the most general class of higher-derivative gravity theories, to quartic order in the curvature, that reduce to General Relativity for weak fields and…

General Relativity and Quantum Cosmology · Physics 2020-10-15 Pablo A. Cano , Kwinten Fransen , Thomas Hertog

We present a machine learning (ML) framework that predicts $G_0W_0$ quasiparticle energies across molecular dynamics (MD) trajectories with high accuracy and efficiency. Using only DFT-derived mean-field eigenvalues and exchange-correlation…

Materials Science · Physics 2025-05-06 Ragab. A. Abdelghany , Chih-En Hsu , Hung-Chung Hsueh , Yuan-Hong Tsai , Ming-Chiang Chung

Super-resolution (SR) models in cosmological simulations use deep learning (DL) to rapidly enhance low-resolution (LR) runs with statistically correct fine details. These models preserves large-scale structures by conditioning on an LR…

Cosmology and Nongalactic Astrophysics · Physics 2025-02-13 Xiaowen Zhang , Patrick Lachance , Ankita Dasgupta , Rupert A. C. Croft , Tiziana Di Matteo , Yueying Ni , Simeon Bird , Yin Li

Data assimilation (DA) integrates observational data with numerical models to improve the prediction of complex physical systems. However, traditional DA methods often struggle with nonlinear dynamics and multi-scale variability,…

Computational Engineering, Finance, and Science · Computer Science 2026-01-29 Hyeonggeun Yun , Quanling Deng

The quasinormal modes of black holes (BHs) in the large-angular-momentum limit can be computed within the eikonal approximation. This approximation is often extrapolated to low angular momentum to obtain a rough estimate of the dominant…

General Relativity and Quantum Cosmology · Physics 2026-03-11 Paolo Pani , Andrea P. Sanna

In this paper, the quasinormal modes of gravitational perturbation around some well-known regular black holes were evaluated by using the WKB approximation as well as the asymptotic iteration method. Through numerical calculation, we make a…

General Relativity and Quantum Cosmology · Physics 2017-02-14 Chen Wu

The generalized Gauss-Newton (GGN) approximation is often used to make practical Bayesian deep learning approaches scalable by replacing a second order derivative with a product of first order derivatives. In this paper we argue that the…

Machine Learning · Statistics 2021-02-26 Alexander Immer , Maciej Korzepa , Matthias Bauer

The existence of generalized steady states (GSSs) in nonlinear mechanical systems under moderate temporally aperiodic forcing has only been shown recently. Here we derive systematic expansions for such GSSs and construct a numerical…

Dynamical Systems · Mathematics 2026-02-20 Roshan S. Kaundinya , Isabella Thiel , Bálint Kaszás , Shobhit Jain , George Haller

Efficient high-rank approximations of the Hessian can accelerate seismic full waveform inversion (FWI) and uncertainty quantification (UQ). In FWI, approximations of the inverse of the Hessian may be used as preconditioners for Newton-type…

Numerical Analysis · Mathematics 2025-08-12 Mathew Hu , Nick Alger , Rami Nammour , Omar Ghattas

Similarity analysis is one of the crucial steps in most fMRI studies. Representational Similarity Analysis (RSA) can measure similarities of neural signatures generated by different cognitive states. This paper develops Deep…

Image and Video Processing · Electrical Eng. & Systems 2020-10-06 Muhammad Yousefnezhad , Jeffrey Sawalha , Alessandro Selvitella , Daoqiang Zhang

The next to leading order chiral corrections to the $SU(2)\times SU(2)$ Gell-Mann-Oakes-Renner (GMOR) relation are obtained using the pseudoscalar correlator to five-loop order in perturbative QCD, together with new finite energy sum rules…

High Energy Physics - Phenomenology · Physics 2012-01-25 J. Bordes , C. A. Dominguez , P. Moodley , J. Peñarrocha , K. Schilcher

The postulates of quantum mechanics impose only unitary transformations on quantum states, which is a severe limitation for quantum machine learning algorithms. Quantum Splines (QSplines) have recently been proposed to approximate quantum…

Hamiltonians of a wide-spread class of strongly coupled quantum system models are expressed as nonlinear functions of $sl(2)$ generators. It enables us to use the $sl(2)$ formalism, in particular, $sl(2)$ generalized coherent states (GCS)…

Quantum Physics · Physics 2007-05-23 Valery P. Karassiov

Molecular dynamics (MD) simulations are a central tool in science and engineering enabling the study of dynamical behavior and the link between microscopic structure and macroscopic function. Their high computational cost, however, has…

Chemical Physics · Physics 2026-01-22 Salman N. Salman , Sergey A. Shteingolts , Ron Levie , Dan Mendels

We conduct a linear analysis of axisymmetric magnetorotational instability (MRI) in a magnetized cylindrical Taylor-Couette (TC) flow for its standard version (SMRI) with a purely axial background magnetic field and two further types --…

Fluid Dynamics · Physics 2022-06-07 A. Mishra , G. Mamatsashvili , F. Stefani

The Nearest Neighbour Spacing (NNS) distribution can be computed for generalized symmetric 2x2 matrices having different variances in the diagonal and in the off-diagonal elements. Tuning the relative value of the variances we show that the…

Chaotic Dynamics · Physics 2022-01-12 Adway Kumar Das , Anandamohan Ghosh

We present a novel spectral solver for general relativistic magnetohydrodynamics on dynamical spacetimes. By combining a high order discontinuous spectral method on mapped Chebyshev Fourier grids, our scheme attains exponential convergence.…

High Energy Astrophysical Phenomena · Physics 2025-08-26 Beibei Li