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Disordered structures producing a non-iridescent color impression have been shown to feature a spherically shaped Fourier transform of their refractive-index distribution. We determine the direction and efficiency of scattering from thin…

Rigorous theories connecting physical properties of a heterogeneous material to its microstructure offer a promising avenue to guide the computational material design and optimization. We present here an efficient Fourier-space based…

Materials Science · Physics 2024-12-13 Wenlong Shi , Yang Jiao , Salvatore Torquato

Heterogeneous materials consisting of different phases are ideally suited to achieve a broad spectrum of desirable bulk physical properties by combining the best features of the constituents through the strategic spatial arrangement of the…

Materials Science · Physics 2017-10-10 Duyu Chen , Salvatore Torquato

We propose a decomposition method for the spectral peaks in an observed frequency spectrum, which is efficiently acquired by utilizing the Fast Fourier Transform. In contrast to the traditional methods of waveform fitting on the spectrum,…

Signal Processing · Electrical Eng. & Systems 2022-04-19 Kaan Gokcesu , Hakan Gokcesu

Hyperuniform continuous random fields suppress large-scale fluctuations while preserving rich local disorder, making them highly attractive for next-generation photonic, thermal and mechanical materials. However, traditional reconstruction…

Materials Science · Physics 2025-09-11 Liyu Zhong , Sheng Mao

Recent developments in machine learning and signal processing have resulted in many new techniques that are able to effectively capture the intrinsic yet complex properties of hyperspectral imagery. Tasks ranging from anomaly detection to…

Computer Vision and Pattern Recognition · Computer Science 2020-11-24 Ilya Kavalerov , Weilin Li , Wojciech Czaja , Rama Chellappa

Hyperuniform structures possess the ability to confine and drive light, although their fabrication is extremely challenging. Here we demonstrate that speckle patters obtained by a superposition of randomly arranged sources of Bessel beams…

Two microring resonators, one with gain and one with loss, coupled to each other and to a bus waveguide, create an effective non-Hermitian potential for light propagating in the waveguide. Due to geometry, coupling for each microring…

Optics · Physics 2019-04-10 Vladimir V. Konotop , Barry C. Sanders , Dmitry A. Zezyulin

It has been shown numerically that systems of particles interacting with "stealthy" bounded, long-ranged pair potentials (similar to Friedel oscillations) have classical ground states that are, counterintuitively, disordered, hyperuniform…

Statistical Mechanics · Physics 2015-06-03 S. Torquato , G. Zhang , F. H. Stillinger

Untrained neural networks (UNNs) offer high-fidelity electromagnetic inverse scattering reconstruction but are computationally limited by high-dimensional spatial-domain optimization. We propose a Real-Time Physics-Driven Fourier-Spectral…

Machine Learning · Computer Science 2026-02-17 Yutong Du , Zicheng Liu , Yi Huang , Bazargul Matkerim , Bo Qi , Yali Zong , Peixian Han

We present a generic scheme to construct corrected trapezoidal rules with spectral accuracy for integral operators with weakly singular kernels in arbitrary dimensions. We assume that the kernel factorization of the form,…

Numerical Analysis · Mathematics 2012-11-27 Jae-Seok Huh , George Fann

We introduce a fast Fourier spectral method for the spatially homogeneous Boltzmann equation with non-cutoff collision kernels. Such kernels contain non-integrable singularity in the deviation angle which arise in a wide range of…

Computational Physics · Physics 2020-10-28 Jingwei Hu , Kunlun Qi

Disordered stealthy hyperuniform dielectric composites exhibit novel electromagnetic wave transport properties in two and three dimensions. Here, we carry out the first study of the electromagnetic properties of one-dimensional (1D)…

Optics · Physics 2023-08-01 Jaeuk Kim , Salvatore Torquato

Disordered spatial networks describe structures and interactions across multiple length scales. The scattering and interference of waves within these networks result in structural phase transitions, localization, diffusion, and band gaps.…

Disordered Systems and Neural Networks · Physics 2026-05-07 Florin Hemmann , Vincent Glauser , Ullrich Steiner , Matthias Saba

Full characterization of the spectral behavior of generative models based on neural networks remains an open issue. Recent research has focused heavily on generative adversarial networks and the high-frequency discrepancies between real and…

Machine Learning · Computer Science 2022-01-20 Sara Björk , Jonas Nordhaug Myhre , Thomas Haugland Johansen

Inverse scattering involving microwave and ultrasound waves require numerical solution of nonlinear optimization problem. To alleviate the computational burden of a full three-dimensional (3-D) inverse problem, it is a common practice to…

Numerical Analysis · Mathematics 2022-07-14 Mert Hidayetoglu , Michael Oelze , Erhan Kudeki , Weng Cho Chew

In his monograph Chebyshev and Fourier Spectral Methods, John Boyd claimed that, regarding Fourier spectral methods for solving differential equations, ``[t]he virtues of the Fast Fourier Transform will continue to improve as the relentless…

Numerical Analysis · Mathematics 2023-02-03 Craig Gross , Mark Iwen

Hyperuniform many-particle systems are characterized by a structure factor $S({\mathbf{k}})$ that is precisely zero as $|\mathbf{k}|\rightarrow0$; and stealthy hyperuniform systems have $S({\mathbf{k}})=0$ for the finite range $0 <…

Statistical Mechanics · Physics 2023-11-08 Peter K. Morse , Jaeuk Kim , Paul J. Steinhardt , Salvatore Torquato

Resolving sources beyond the diffraction limit is important in imaging, communications, and metrology. Current image-based methods of super-resolution require phase information (either of the source points or an added filter) and perfect…

Optics · Physics 2025-12-16 S. A. Wadood , Shaurya Aarav , Kevin Liang , Jason W Fleischer

Packing spheres efficiently in large dimension $d$ is a particularly difficult optimization problem. In this paper we add an isotropic interaction potential to the pure hard-core repulsion, and show that one can tune it in order to maximize…

Disordered Systems and Neural Networks · Physics 2018-06-28 Thibaud Maimbourg , Mauro Sellitto , Guilhem Semerjian , Francesco Zamponi
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