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Related papers: Generalised quasi-linear approximation of the HMRI

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The quasilinearization method (QLM) of solving nonlinear differential equations is applied to the quantum mechanics by casting the Schr\"{o}dinger equation in the nonlinear Riccati form. The method, whose mathematical basis in physics was…

Computational Physics · Physics 2007-05-23 R. Krivec , V. B. Mandelzweig

Quasinormal modes (QNMs) are usually characterized by their time dependence; oscillations at specific frequencies predicted by black hole (BH) perturbation theory. QNMs are routinely identified in the ringdown of numerical relativity…

General Relativity and Quantum Cosmology · Physics 2025-01-20 Richard Dyer , Christopher J. Moore

Due to the ease of modern data collection, applied statisticians often have access to a large set of covariates that they wish to relate to some observed outcome. Generalized linear models (GLMs) offer a particularly interpretable framework…

Computation · Statistics 2019-05-21 Brian L. Trippe , Jonathan H. Huggins , Raj Agrawal , Tamara Broderick

In order to sample marginalized and/or hard-to-reach populations, respondent-driven sampling (RDS) and similar techniques reach their participants via peer referral. Under a Markov model for RDS, previous research has shown that if the…

Statistics Theory · Mathematics 2022-06-08 Sebastien Roch , Karl Rohe

The general synthetic iterative scheme (GSIS) has proven its efficacy in modeling rarefied gas dynamics, where the steady-state solutions are obtained after dozens of iterations of the Boltzmann equation, with minimal numerical dissipation…

Computational Physics · Physics 2024-07-10 Liyan Luo , Lei Wu

We have derived precise analytic expressions for the quasinormal modes of test scalar, and Dirac fields in the background of the dilaton black hole. To achieve this, we employ the higher-order WKB expansion in terms of $1/\ell$. A…

General Relativity and Quantum Cosmology · Physics 2024-09-17 Zainab Malik

The generalized density matrix (GDM) method is used to calculate microscopically the parameters of the collective Hamiltonian. Higher order anharmonicities are obtained consistently with the lowest order results, the mean field…

Nuclear Theory · Physics 2011-09-23 L. Y. Jia

Closed loop quantum control uses measurement to control the dynamics of a quantum system to achieve either a desired target state or target dynamics. In the case when the quantum Hamiltonian is quadratic in ${x}$ and ${p}$, there are known…

Quantum Physics · Physics 2021-11-15 Sangkha Borah , Bijita Sarma , Michael Kewming , Gerard J. Milburn , Jason Twamley

In this paper, we investigate quasi-maximum likelihood (QML) estimation for the parameters of a cointegrated solution of a continuous-time linear state space model observed at discrete time points. The class of cointegrated solutions of…

Statistics Theory · Mathematics 2019-11-11 Vicky Fasen-Hartmann , Markus Scholz

The gradient descent (GD) method has been used widely to solve parameter estimation in generalized linear models (GLMs), a generalization of linear models when the link function can be non-linear. In GLMs with a polynomial link function, it…

Optimization and Control · Mathematics 2024-03-15 Qiujiang Jin , Tongzheng Ren , Nhat Ho , Aryan Mokhtari

We study the dynamical stability of hairy dyonic black holes in the Einstein-Maxwell-scalar gravity system against the massless scalar field perturbation. We numerically obtain the corresponding quasinormal modes (QNMs) using the series…

General Relativity and Quantum Cosmology · Physics 2023-08-14 Supragyan Priyadarshinee

We present kinematic simulations of a galactic dynamo model based on the large scale differential rotation and the small scale helical fluctuations due to supernova explosions. We report for the first time direct numerical simulations of…

Astrophysics of Galaxies · Physics 2009-11-13 Christophe Gissinger , Sebastien Fromang , Emmanuel Dormy

Resonant States (RS), also known as Quasi-Normal Modes (QNMs), are eigenstates that arise in spectral expansions of linear response functions of open systems. Manipulation of these spatially `divergent' oscillating functions requires a…

Optics · Physics 2021-04-15 Brian Stout , Remi Colom , Nicolas Bonod , Ross McPhedran

We compare two quantum approaches that use support vector machines for multi-class classification on a reduced Sloan Digital Sky Survey (SDSS) dataset: the quantum kernel-based QSVM and the Harrow-Hassidim-Lloyd least-squares SVM (HHL…

Quantum Physics · Physics 2025-09-15 Gabriela Pinheiro , Donovan Slabbert , Luis Kowada , Francesco Petruccione

There has been much recent interest in designing neural networks (NNs) with relaxed equivariance, which interpolate between exact equivariance and full flexibility for consistent performance gains. In a separate line of work, structured…

Machine Learning · Statistics 2025-04-21 Ashwin Samudre , Mircea Petrache , Brian D. Nord , Shubhendu Trivedi

Rapidly rotating spherical kinematic dynamos are computed using the combination of a quasi geostrophic (QG) model for the velocity field and a classical spectral 3D code for the magnetic field. On one hand, the QG flow is computed in the…

Classical Physics · Physics 2007-05-23 Nathanael Schaeffer , Philippe Cardin

Turbulent dynamo theories have faced difficulties in obtaining evolution of large-scale magnetic fields on short dynamical time-scales due to the constraint imposed by magnetic helicity balance. This has critical implications for…

Solar and Stellar Astrophysics · Physics 2021-12-03 Pallavi Bhat

It is shown that the scalar wave equation in the near-horizon limit respects a hidden SL(2,R) invariance in the Reissner-Nordstrom (RN) black hole spacetimes. We use the SL(2,R) symmetry to determine algebraically the purely imaginary…

High Energy Physics - Theory · Physics 2015-06-05 Yong-Wan Kim , Yun Soo Myung , Young-Jai Park

By employing an expansion in terms of the inverse multipole number, we derive analytic expressions for the quasinormal modes (QNMs) of scalar, Dirac, and Maxwell perturbations in the Hayward black hole (BH) background. The metric has three…

General Relativity and Quantum Cosmology · Physics 2024-10-08 Zainab Malik

Gaussian processes (GP) for machine learning have been studied systematically over the past two decades and they are by now widely used in a number of diverse applications. However, GP kernel design and the associated hyper-parameter…

Machine Learning · Computer Science 2020-10-28 Feng Yin , Lishuo Pan , Xinwei He , Tianshi Chen , Sergios Theodoridis , Zhi-Quan , Luo
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