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In helioseismology, there is a well-known offset between observed and computed oscillation frequencies. This offset is known to arise from improper modeling of the near-surface layers of the Sun, and a similar effect must occur for models…

Astrophysics · Physics 2009-11-13 Hans Kjeldsen , Timothy R. Bedding , Joergen Christensen-Dalsgaard

It is well known that the observed amplitude of solar oscillations is lower in sunspots than in quiet regions of the Sun. We show that this local reduction in oscillation amplitudes combined with the phase-speed filtering procedure in…

Astrophysics · Physics 2009-11-11 S. P. Rajaguru , A. C. Birch , T. L. Duvall , M. J. Thompson , J. Zhao

Calculating dynamical spin correlations is essential for matching model magnetic exchange Hamiltonians to momentum-resolved spectroscopic measurements. A major numerical bottleneck is the diagonalization of the dynamical matrix, especially…

Strongly Correlated Electrons · Physics 2024-11-27 Harry Lane , Hao Zhang , David Dahlbom , Sam Quinn , Rolando D. Somma , Martin Mourigal , Cristian D. Batista , Kipton Barros

We calculate accurate solar models and report the detailed time dependences of important solar quantities. We use helioseismology to constrain the luminosity evolution of the sun and report the discovery of semi-convection in evolved solar…

Astrophysics · Physics 2008-11-26 John N. Bahcall , M. H. Pinsonneault , Sarbani Basu

Steady meridional flow makes no first-order perturbation to the frequencies of helioseismic normal modes. It does, however, Doppler shift the local wavenumber, thereby distorting the eigenfunctions. For high-degree modes, whose peaks in a…

Solar and Stellar Astrophysics · Physics 2014-11-20 Douglas Gough , Bradley W. Hindman

The kernel polynomial method allows to sample overall spectral properties of a quantum system, while sparse diagonalization provides accurate information about a few important states. We present a method combining these two approaches…

Decision forests induce supervised similarities through the partition structure of their trees. Yet forest proximity computation is still often treated as a quadratic operation in the number of samples, which limits scalability and…

Machine Learning · Computer Science 2026-04-21 Adrien Aumon , Guy Wolf , Kevin R. Moon , Jake S. Rhodes

The purpose of this article is to introduce a new class of kernels on SO(3) for approximation and interpolation, and to estimate the approximation power of the associated spaces. The kernels we consider arise as linear combinations of…

Classical Analysis and ODEs · Mathematics 2011-06-14 Thomas Hangelbroek , Dominik Schmid

We present a unified treatment of the Fourier spectra of spherically symmetric nonlocal diffusion operators. We develop numerical and analytical results for the class of kernels with weak algebraic singularity as the distance between source…

Numerical Analysis · Mathematics 2019-09-04 Yu Li , Richard Mikael Slevinsky

Using spectral-element and adjoint methods, we investigate body waves interacting with the Earth's most dramatic interface, the core-mantle boundary (CMB). Intermediate-to-high frequency seismograms are computed incorporating topography…

Geophysics · Physics 2022-10-26 Maria Koroni , Anselme Borgeaud , Andreas Fichtner , Frédéric Deschamps

From the observing campaigns of a number of helioseismic telescope networks such as the Global Oscillation Network Group (GONG) and also from the Solar Heliospheric Observatory satellite (SoHO), helioseismologists now have data on in excess…

Astrophysics · Physics 2007-05-23 Frank P. Pijpers

We present a data-driven method for computing approximate forward reachable sets using separating kernels in a reproducing kernel Hilbert space. We frame the problem as a support estimation problem, and learn a classifier of the support as…

Optimization and Control · Mathematics 2020-11-20 Adam J. Thorpe , Kendric R. Ortiz , Meeko M. K. Oishi

Improved performance in higher-order spectral density estimation is achieved using a general class of infinite-order kernels. These estimates are asymptotically less biased but with the same order of variance as compared to the classical…

Statistics Theory · Mathematics 2007-06-13 Arthur Berg , Dimitris Politis

I present a new algorithm, CALCLENS, for efficiently computing weak gravitational lensing shear signals from large N-body light cone simulations over a curved sky. This new algorithm properly accounts for the sky curvature and boundary…

Cosmology and Nongalactic Astrophysics · Physics 2012-10-15 Matthew R. Becker

We propose a novel approach for designing kernels for support vector machines (SVMs) when the class label is linked to the observation through a latent state and the likelihood function of the observation given the state (the sensing model)…

Machine Learning · Computer Science 2014-03-14 Weicong Ding , Prakash Ishwar , Venkatesh Saligrama , W. Clem Karl

Learning the kernel functions used in kernel methods has been a vastly explored area in machine learning. It is now widely accepted that to obtain 'good' performance, learning a kernel function is the key challenge. In this work we focus on…

Machine Learning · Computer Science 2016-01-08 Chetan Tonde , Ahmed Elgammal

The Helioseismic and Magnetic Imager (HMI) has just started producing data that will help determine what the sources and mechanisms of variability in the Sun's interior are. The instrument measures the Doppler shift and the polarization of…

Solar and Stellar Astrophysics · Physics 2010-12-20 Rebecca Centeno , Steve Tomczyk , Juan Manuel Borrero , Sebastien Couvidat , Keiji Hayashi , Todd Hoeksema , Yang Liu , Jesper Schou

Improving methods for determining the subsurface structure of sunspots from their seismic signature requires a better understanding of the interaction of waves with magnetic field concentrations. We aim to quantify the impact of changes in…

Solar and Stellar Astrophysics · Physics 2017-08-30 T. Felipe , D. C. Braun , A. C. Birch

Dispersive delays due to the Solar wind introduce excess noise in high-precision pulsar timing experiments, and must be removed in order to achieve the accuracy needed to detect, e.g., low-frequency gravitational waves. In current pulsar…

We discuss current advances in forward and inverse modeling for local helioseismology. We report theoretical uniqueness results, in particular the Novikov-Agaltsov reconstruction algorithm, which is relevant to solving the non-linear…

Solar and Stellar Astrophysics · Physics 2017-07-28 Laurent Gizon , Damien Fournier , Thorsten Hohage
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