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Spherical $t$-designs on $\mathbb{S}^{d}\subset\mathbb{R}^{d+1}$ provide $N$ nodes for an equal weight numerical integration rule which is exact for all spherical polynomials of degree at most $t$. This paper considers the generation of…

Numerical Analysis · Mathematics 2017-09-07 Robert S. Womersley

In this manuscript, we present a novel approach for sampling from a continuous multivariate probability distribution, which may either be explicitly known (up to a normalization factor) or represented via empirical samples. Our method…

Machine Learning · Statistics 2025-03-14 Hamidreza Behjoo , Michael Chertkov

We explore the degrees of freedom required to jointly fit projected and redshift-space clustering of galaxies selected in three bins of stellar mass from the Sloan Digital Sky Survey Main Galaxy Sample (SDSS MGS) using a subhalo abundance…

Cosmology and Nongalactic Astrophysics · Physics 2022-11-30 Joseph DeRose , Matthew R. Becker , Risa H. Wechsler

We present a theoretical framework for analyzing spatial sampling of fields in three-dimensional space. The framework bridges Shannon's sampling and information theory to Bayesian probabilistic inference and experimental design. Based on…

A utility-function approach to optimal spatial sampling design is a powerful way to quantify what "optimality" means. The emphasis then should be to capture all possible contributions to utility, including scientific impact and the cost of…

Statistics Theory · Mathematics 2015-09-17 Noel Cressie , Raymond L. Chambers

A new method is presented that allows for efficient evaluation of spin-orbit coupling (SOC) in density-functional theory calculations. In the so-called second-variational scheme, where Kohn-Sham functions obtained in a scalar-relativistic…

Materials Science · Physics 2023-06-06 Cecilia Vona , Sven Lubeck , Hannah Kleine , Andris Gulans , Claudia Draxl

We investigate the sampling-based optimal path planning problem for robotics in complex and dynamic environments. Most existing sampling-based algorithms neglect environmental information or the information from previous samples. Yet, these…

Robotics · Computer Science 2025-11-20 Mingyang Feng , Shaoyuan Li , Xiang Yin

In this paper, we investigate in detail the structures of the variational characterization $A_{N,t}$ of the spherical $t$-design, its gradient $\nabla A_{N,t}$, and its Hessian $\mathcal{H}(A_{N,t})$ in terms of fast spherical harmonic…

Numerical Analysis · Mathematics 2023-12-06 Yuchen Xiao , Xiaosheng Zhuang

The quantum geometric tensor (QGT) embodies the geometry of the eigenstates of a system's Hamiltonian, and its full characterization across diverse quantum systems is essential. However, it is challenging to characterize the QGT of…

Mesoscale and Nanoscale Physics · Physics 2026-02-26 Shu-Hui Zhang , Jin Yang , Ding-Fu Shao , Jia-Ji Zhu , Wen-Long You , Wen Yang , Kai Chang

We study the large $N$-dimensional limit of the Hessian spectrum at the global minimum of some subclasses of the spherical mixed $p$-spin models. Specifically, we show that its empirical spectral measure converges in probability to a…

Mathematical Physics · Physics 2025-07-29 Hao Xu , Haoran Yang

We determine optimal designs for some regression models which are frequently used for describing three-dimensional shapes. These models are based on a Fourier expansion of a function defined on the unit sphere in terms of spherical harmonic…

Statistics Theory · Mathematics 2007-06-13 Holger Dette , Viatcheslav B. Melas , Andrey Pepelyshev

Spin squeezing provides crucial quantum resource for quantum metrology and quantum information science. Here we propose that one axis-twisted (OAT) spin squeezing can be generated from free evolution under a general coupled-spin model with…

Quantum Physics · Physics 2023-11-28 Yanzhen Wang , Xuanchen Zhang , Yong-Chun Liu

We study the problem of sampling a random signal with sparse support in frequency domain. Shannon famously considered a scheme that instantaneously samples the signal at equispaced times. He proved that the signal can be reconstructed as…

Information Theory · Computer Science 2012-11-22 Adel Javanmard , Andrea Montanari

We revisit the classical problem of finding an approximately stationary point of the average of $n$ smooth and possibly nonconvex functions. The optimal complexity of stochastic first-order methods in terms of the number of gradient…

Machine Learning · Computer Science 2022-06-07 Alexander Tyurin , Lukang Sun , Konstantin Burlachenko , Peter Richtárik

The evolution of the scanning modules for scanning transmission electron microscopes (STEM) has realized the possibility to generate arbitrary scan pathways, an approach currently explored to improve acquisition speed and to reduce electron…

Logconcave functions represent the current frontier of efficient algorithms for sampling, optimization and integration in R^n. Efficient sampling algorithms to sample according to a probability density (to which the other two problems can…

Data Structures and Algorithms · Computer Science 2009-06-16 Karthekeyan Chandrasekaran , Amit Deshpande , Santosh Vempala

We propose a trajectory-based method for simulating nonadiabatic dynamics in molecular systems with two coupled electronic states. Employing a quantum-mechanically exact mapping of the two-level problem to a spin-1/2 coherent state, we…

Chemical Physics · Physics 2020-03-03 Johan E. Runeson , Jeremy O. Richardson

This paper investigates aliasing effects emerging from the reconstruction from discrete samples of spin spherical random fields defined on the two-dimensional sphere. We determine the location in the frequency domain and the intensity of…

Probability · Mathematics 2026-01-26 Claudio Durastanti

We study the random sampling of band-limited functions of several variables. If a bandlimited function with bandwidth one has its essential support on a cube of volume $R^d$, then $\cO (R^d \log R^d)$ random samples suffice to approximate…

Probability · Mathematics 2017-06-21 Richard F. Bass , Karlheinz Gröchenig

This paper is concerned with the problem of frequency estimation from multiple-snapshot data. It is well-known that ESPRIT (and spatial-smoothing ESPRIT in presence of coherent sources or given limited snapshots) can locate the true…

Signal Processing · Electrical Eng. & Systems 2022-08-16 Zai Yang