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Obtaining accurate representations of the eigenstates of an array of coupled superconducting qubits is a crucial step in the design of circuit quantum electrodynamics (QED)-based quantum processors. However, exact diagonalization of the…

Cloud removal (CR) remains a challenging task in remote sensing image processing. Although diffusion models (DM) exhibit strong generative capabilities, their direct applications to CR are suboptimal, as they generate cloudless images from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Yi Liu , Wengen Li , Jihong Guan , Shuigeng Zhou , Yichao Zhang

Single-particle cryo-electron microscopy (cryo-EM) is an emerging imaging modality capable of visualizing proteins and macro-molecular complexes at near-atomic resolution. The low electron-doses used to prevent sample radiation damage,…

Image and Video Processing · Electrical Eng. & Systems 2020-11-24 Qinwen Huang , Ye Zhou , Xiaochen Du , Reed Chen , Jianyou Wang , Cynthia Rudin , Alberto Bartesaghi

We present a new algorithm, called Multiresolution Regularized Expectation Maximization (MREM), for the reconstruction of gamma-ray intensity maps from COMPTEL data. The algorithm is based on the iterative Richardson-Lucy scheme to which we…

We report an investigation of the suitability of quantum embedding for modeling the effects of the environment on the X-ray photoelectron spectra of hydrogen chloride and the chloride ions adsorbed on ice surfaces, as well as of chloride…

Chemical Physics · Physics 2023-05-10 Richard Asamoah Opoku , Céline Toubin , André Severo Pereira Gomes

SDE-based methods such as denoising diffusion probabilistic models (DDPMs) have shown remarkable success in real-world sample generation tasks. Prior analyses of DDPMs have been focused on the exponential Euler discretization, showing…

Machine Learning · Computer Science 2025-11-10 Matthew S. Zhang , Stephen Huan , Jerry Huang , Nicholas M. Boffi , Sitan Chen , Sinho Chewi

We describe a novel end-to-end approach using Machine Learning to reconstruct the power spectrum of cosmological density perturbations at high redshift from observed quasar spectra. State-of-the-art cosmological simulations of structure…

Cosmology and Nongalactic Astrophysics · Physics 2021-07-21 Maria Han Veiga , Xi Meng , Oleg Y. Gnedin , Nickolay Y. Gnedin , Xun Huan

The accuracy of the information that can be extracted from electron diffraction patterns is often limited by the presence of optical distortions. Existing distortion characterization techniques typically require knowledge of the reciprocal…

The density matrix renormalization group (DMRG) is applied to some one-dimensional reaction-diffusion models in the vicinity of and at their critical point. The stochastic time evolution for these models is given in terms of a non-symmetric…

Statistical Mechanics · Physics 2011-10-11 Enrico Carlon , Malte Henkel , Ulrich Schollwoeck

While the implementation of single particle coherent diffraction imaging for non-crystalline particles is complicated by current limitations in photon flux, hit rate, and sample delivery a concept of many-particle coherent diffraction…

Disordered Systems and Neural Networks · Physics 2013-02-22 R. P. Kurta , R. Dronyak , M. Altarelli , E. Weckert , I. A. Vartanyants

Single particle electron cryomicroscopy (cryo-EM) allows for structures of proteins and protein complexes to be determined from images of non-crystalline specimens. Cryo-EM data analysis requires electron microscope images of randomly…

Instrumentation and Detectors · Physics 2015-11-23 Jianhua Zhao , Marcus A. Brubaker , Samir Benlekbir , John L. Rubinstein

We present Frequency Marching, FM, an algorithm that refines three-dimensional electron density distributions from solution X-ray scattering data in both the small- and wide-angle regimes. This algorithm is based on a series of optimization…

Biological Physics · Physics 2020-12-25 Yen-Lin Chen , Lois Pollack

Determining the 3D structures of biological molecules is a key problem for both biology and medicine. Electron Cryomicroscopy (Cryo-EM) is a promising technique for structure estimation which relies heavily on computational methods to…

Machine Learning · Statistics 2015-01-29 Ali Punjani , Marcus A. Brubaker

This paper introduces a sparse projection matrix composed of discrete (digital) periodic lines that create a pseudo-random (p.frac) sampling scheme. Our approach enables random Cartesian sampling whilst employing deterministic and…

Image and Video Processing · Electrical Eng. & Systems 2024-01-09 Marlon Bran Lorenzana , Benjamin Cottier , Matthew Marques , Andrew Kingston , Shekhar S. Chandra

A new density matrix renormalisation group (DMRG) approach is presented for quantum systems of two spatial dimensions. In particular, it is shown that it is possible to create a multi-chain-type 2D DMRG approach which utilises previously…

Strongly Correlated Electrons · Physics 2009-11-10 Damian J. J. Farnell

This paper presents a new system to obtain dense object reconstructions along with 6-DoF poses from a single image. Geared towards high fidelity reconstruction, several recent approaches leverage implicit surface representations and deep…

Computer Vision and Pattern Recognition · Computer Science 2020-04-28 Aniket Pokale , Aditya Aggarwal , K. Madhava Krishna

The computation of strongly correlated quantum systems is challenging because of its potentially exponential scaling in the number of electron configurations. Variational calculation of the two-electron reduced density matrix (2-RDM)…

Quantum Physics · Physics 2021-04-01 David A. Mazziotti

Note: The final version of this article was published in Computers and Geosciences, Volume 206, January 2026, 106038. DOI: 10.1016/j.cageo.2025.106038. Readers should refer to the published version for the most up-to-date content.…

An active space variational calculation of the 2-electron reduced density matrix (2-RDM) is derived and implemented where the active orbitals are correlated within the pair approximation. The pair approximation considers only doubly…

Chemical Physics · Physics 2020-10-13 Kade Head-Marsden , David A. Mazziotti

Purpose: To develop a self-supervised scan-specific deep learning framework for reconstructing accelerated multiparametric quantitative MRI (qMRI). Methods: We propose REFINE-MORE (REference-Free Implicit NEural representation with MOdel…

Medical Physics · Physics 2025-08-05 Ruimin Feng , Albert Jang , Xingxin He , Fang Liu
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