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Using Resonant Inelastic X-ray Scattering, we measure the paramagnon dispersion and damping of undoped, antiferromagnetic Ca$_2$CuO$_2$Cl$_2$ as well as doped, superconducting Na$_{x}$Ca$_{2-x}$CuO$_2$Cl$_2$. Our estimation of the…

The development of short- and long-range magnetic order induced in a frustrated zig-zag ladder compound SrDy2O4 by an applied field is studied using neutron diffraction techniques. In zero field, SrDy2O4 lacks long-range magnetic order down…

Strongly Correlated Electrons · Physics 2017-04-25 O. A. Petrenko , O. Young , D. Brunt , G. Balakrishnan , P. Manuel , D. D. Khalyavin , C. Ritter

We analyze powder-averaged inelastic neutron scattering and magnetization data for the distorted honeycomb compound Cu$_5$SbO$_6$ using a first-order dimer expansion calculation and quantum Monte Carlo simulations. We show that, in contrast…

We study the renormalization of a single impurity potential in one-dimensional interacting electron systems in the presence of magnetic field. Using the bosonization technique and Bethe ansatz solutions, we determine the renormalization…

Strongly Correlated Electrons · Physics 2007-05-23 T. Hikihara , A. Furusaki , K. A. Matveev

Recently, a diffusion Monte Carlo algorithm was applied to the study of spin dependent interactions in condensed matter. Following some of the ideas presented therein, and applied to a Hamiltonian containing a Rashba-like interaction, a…

Strongly Correlated Electrons · Physics 2015-05-27 Alberto Ambrosetti , Pier Luigi Silvestrelli , Flavio Toigo , Lubos Mitas , Francesco Pederiva

The reconstruction of unsteady flow fields from limited measurements is a challenging and crucial task for many engineering applications. Machine learning models are gaining popularity for solving this problem due to their ability to learn…

Fluid Dynamics · Physics 2026-01-09 Marc Amorós-Trepat , Luis Medrano-Navarro , Qiang Liu , Luca Guastoni , Nils Thuerey

We present a powder inelastic neutron scattering study of magnetic excitations in Ba$_2$FeReO$_6$, a member of the double perovskite family of materials which exhibit half-metallic behavior and high Curie temperatures. We find clear…

Strongly Correlated Electrons · Physics 2013-06-04 K. W. Plumb , A. M. Cook , J. P. Clancy , A. I. Kolesnikov , B. C. Jeon , T. W. Noh , A. Paramekanti , Young-June Kim

Blind image restoration remains a significant challenge in low-level vision tasks. Recently, denoising diffusion models have shown remarkable performance in image synthesis. Guided diffusion models, leveraging the potent generative priors…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Jun Xiao , Zihang Lyu , Hao Xie , Cong Zhang , Yakun Ju , Changjian Shui , Kin-Man Lam

This paper is concerned with the numerical solution to a 3D coefficient inverse problem for buried objects with multi-frequency experimental data. The measured data, which are associated with a single direction of an incident plane wave,…

Numerical Analysis · Mathematics 2017-05-04 Dinh-Liem Nguyen , Michael V. Klibanov , Loc H. Nguyen , Michael A. Fiddy

In this paper we present a novel approach towards variance reduction for discretised diffusion processes. The proposed approach involves specially constructed control variates and allows for a significant reduction in the variance for the…

Probability · Mathematics 2017-09-19 Denis Belomestny , Stefan Häfner , Tigran Nagapetyan , Mikhail Urusov

Recently, generative diffusion priors have made huge strides as inverse problem solvers, including the ability to be adapted for inference on out-of-distribution data. Concurrently, implicit neural representations (INRs) have emerged as…

Image and Video Processing · Electrical Eng. & Systems 2026-03-12 Maliha Hossain , Haley Duba-Sullivan , Amirkoushyar Ziabari

This revisit gives a survey on the analytical methods for the inverse exponential Radon transform which has been investigated in the past three decades from both mathematical interests and medical applications such as nuclear medicine…

Image and Video Processing · Electrical Eng. & Systems 2020-02-06 Jason You

Diffuse scattering is a rich source of information about disorder in crystalline materials, which can be modelled using atomistic techniques such as Monte Carlo and molecular dynamics simulations. Modern X-ray and neutron scattering…

Materials Science · Physics 2018-12-21 Joseph A. M. Paddison

Systems of spins engineered with tunable density and reduced dimensionality enable a number of advancements in quantum sensing and simulation. Defects in diamond, such as nitrogen-vacancy (NV) centers and substitutional nitrogen (P1…

Single crystals of the lightly-doped spin-Peierls system Cu(1-x)Cd(x)GeO3 have been studied using bulk susceptibility, x-ray diffraction, and inelastic neutron scattering techniques. We investigate the triplet gap in the magnetic excitation…

Strongly Correlated Electrons · Physics 2009-11-13 S. Haravifard , K. C. Rule , H. A. Dabkowska , B. D. Gaulin , Z. Yamani , W. J. L. Buyers

A major family of sufficient dimension reduction (SDR) methods, called inverse regression, commonly require the distribution of the predictor $X$ to have a linear $E(X|\beta^\mathsf{T}X)$ and a degenerate $\mathrm{var}(X|\beta^\mathsf{T}X)$…

Methodology · Statistics 2023-08-30 Wei Luo , Yan Guo

We study the effects of spin-flip scatterings on the time-dependent transport properties through a magnetic quantum dot attached to normal and ferromagnetic leads. The transient spin-dynamics as well as the steady-state tunneling…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 Enrico Perfetto , Gianluca Stefanucci , Michele Cini

Reliable quantitative analysis in scanning (transmission) electron microscopy (S(T)EM) is often hindered by image drift during long-duration spectral mapping for elemental analysis or for various material functions. We here present…

Instrumentation and Detectors · Physics 2026-04-22 Zac Thollar , Kanto Maeda , Tetsuya Kubota , Taka-aki Yano , Qiwen Tan , Takumi Sannomiya

We have performed a large scale Monte Carlo simulation of a dilute classical Heisenberg model with ferromagnetic nearest neighbor and antiferromagnetic next-nearest neighbor interactions. We found that the model reproduces a reentrant…

Disordered Systems and Neural Networks · Physics 2009-11-11 S. Abiko , S. Niidera , F. Matsubara

Spin waves are promising candidates to carry, transport, and process information. Controlling the propagation characteristics of spin waves in magnetic materials is an essential ingredient for designing spin-wave based computing…

Applied Physics · Physics 2020-07-29 Morteza Mohseni , Burkard Hillebrands , Philipp Pirro , Mikhail Kostylev