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Solving ill-posed inverse problems requires careful formulation of prior beliefs over the signals of interest and an accurate description of their manifestation into noisy measurements. Handcrafted signal priors based on e.g. sparsity are…

Machine Learning · Computer Science 2025-08-14 Tristan S. W. Stevens , Hans van Gorp , Faik C. Meral , Junseob Shin , Jason Yu , Jean-Luc Robert , Ruud J. G. van Sloun

Starting from the developed generalized point process model of $1/f$ noise (B. Kaulakys et al, Phys. Rev. E 71 (2005) 051105; cond-mat/0504025) we derive the nonlinear stochastic differential equations for the signal exhibiting 1/f^{\beta}$…

Statistical Mechanics · Physics 2009-11-11 Bronislovas Kaulakys , Julius Ruseckas , Vygintas Gontis , Miglius Alaburda

We study notions of hyperuniformity for invariant locally square-integrable point processes in regular trees. We show that such point processes are never geometrically hyperuniform, and if the diffraction measure has support in the…

Probability · Mathematics 2024-09-18 Mattias Byléhn

Power-spectrum analysis is an important tool providing critical information about a signal. The range of applications includes communication-systems to DNA-sequencing. If there is interference present on a transmitted signal, it could be…

Instrumentation and Methods for Astrophysics · Physics 2015-03-18 Yogindra Abhyankar , Sajish C. , Yogesh Agarwal , C. R. Subrahmanya , Peeyush Prasad

Capturing the microscopic interactions that determine molecular reactivity poses a challenge across the physical sciences. Even a basic understanding of the underlying reaction mechanisms can substantially accelerate materials and compound…

Chemical Physics · Physics 2019-12-11 Carl Poelking , Yehia Amar , Alexei Lapkin , Lucy Colwell

The optical properties of defects in solids produce rich physics, from gemstone coloration to single-photon emission for quantum networks. Essential to describing optical transitions is electron-phonon coupling, which can be predicted from…

Materials Science · Physics 2026-04-21 Mark E. Turiansky , John L. Lyons , Noam Bernstein

The spectral fluctuations of complex quantum systems, in appropriate limit, are known to be consistent with that obtained from random matrices. However, this relation between the spectral fluctuations of physical systems and random matrices…

Quantum Physics · Physics 2020-09-16 S. Harshini Tekur , M. S. Santhanam

The marked power spectrum is capable of placing far tighter constraints on cosmological parameters (particularly the neutrino mass) than the conventional power spectrum. What new information does it contain beyond conventional statistics?…

Cosmology and Nongalactic Astrophysics · Physics 2020-08-19 Oliver H. E. Philcox , Elena Massara , David N. Spergel

The noise of a device under test (DUT) is measured simultaneously with two instruments, each of which contributes its own background. The average cross power spectral density converges to the DUT power spectral density. This method enables…

Instrumentation and Detectors · Physics 2010-03-02 Enrico Rubiola , Francois Vernotte

Boundary samples are special inputs to artificial neural networks crafted to identify the execution environment used for inference by the resulting output label. The paper presents and evaluates algorithms to generate transparent boundary…

Machine Learning · Computer Science 2021-06-15 Alexander Schlögl , Tobias Kupek , Rainer Böhme

Complex systems, such as the power grid, are essential for our daily lives. Many complex systems display (multi-)fractal behavior, correlated fluctuations and power laws. Whether the power-grid frequency, an indicator about the balance on…

Spectral deconvolution is essential for extracting peak structures that encode material properties and chemical structures, but conventional automated methods often fail when spectra contain high-intensity noise or unknown background…

Data Analysis, Statistics and Probability · Physics 2026-05-19 Hayato Okubo , Yoshifumi Amamoto , Toshimitsu Aritake , Hiroyuki Kumazoe , Shiryu Nakano , Evan Jamison , Satoshi Tanaka , Yoh-ichi Mototake

Procedural noise is a fundamental component of computer graphics pipelines, offering a flexible way to generate textures that exhibit "natural" random variation. Many different types of noise exist, each produced by a separate algorithm. In…

Guided by the intuition of coherent superposition of causal relations, recent works presented quantum processes without classical common-cause and direct-cause explanation, that is, processes which cannot be written as probabilistic…

The power-spectrum subband energy ratio (PSER) has been applied in a variety of fields, but reports on its statistical properties have been limited. As such, this study investigates these characteristics in the presence of additive Gaussian…

Signal Processing · Electrical Eng. & Systems 2020-11-19 Han Li , Yanzhu Hu , Song Wang , Zhen Meng

The study of phonon dynamics is pivotal for understanding material properties, yet it faces challenges due to the irreversible information loss inherent in powder inelastic neutron scattering spectra and the limitations of traditional…

Materials Science · Physics 2024-10-29 Yaokun Su , Chen Li

With the advancement of audio generation, generative models can produce highly realistic audios. However, the proliferation of deepfake general audio can pose negative consequences. Therefore, we propose a new task, deepfake general audio…

Sound · Computer Science 2024-06-13 Zeyu Xie , Baihan Li , Xuenan Xu , Zheng Liang , Kai Yu , Mengyue Wu

Noise on quantum devices is much more complex than it is commonly given credit. Far from usual models of decoherence, nearly all quantum devices are plagued both by a continuum of environments and temporal instabilities. These induce noisy…

Quantum Physics · Physics 2025-08-27 Gregory A. L. White , Petar Jurcevic , Charles D. Hill , Kavan Modi

We argue that the selective inclusion of data points based on latent objectives is common in practical situations, such as music sequences. Since this selection process often distorts statistical analysis, previous work primarily views it…

Machine Learning · Computer Science 2024-07-02 Yujia Zheng , Zeyu Tang , Yiwen Qiu , Bernhard Schölkopf , Kun Zhang

Spherical radial-basis-based kernel interpolation abounds in image sciences including geophysical image reconstruction, climate trends description and image rendering due to its excellent spatial localization property and perfect…

Machine Learning · Computer Science 2024-01-17 Xiaotong Liu , Jinxin Wang , Di Wang , Shao-Bo Lin
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