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A crucial assumption to reduce computational complexity in spatial-temporal data analysis is separability, which factors the covariance structure into a purely spatial and a purely temporal component. In this paper, we develop statistical…

Statistics Theory · Mathematics 2026-03-30 Lujia Bai , Holger Dette , Zihao Yuan

Particle indistinguishability is at the heart of quantum statistics that regulates fundamental phenomena such as the electronic band structure of solids, Bose-Einstein condensation and superconductivity. Moreover, it is necessary in…

Disentangling anatomical and contrast information from medical images has gained attention recently, demonstrating benefits for various image analysis tasks. Current methods learn disentangled representations using either paired multi-modal…

Image and Video Processing · Electrical Eng. & Systems 2022-05-11 Lianrui Zuo , Yihao Liu , Yuan Xue , Shuo Han , Murat Bilgel , Susan M. Resnick , Jerry L. Prince , Aaron Carass

We propose a method to build an astronomical interferometer using continuous variable quantum teleportation to overcome the transmission loss between distant telescopes. The scheme relies on two-mode squeezed states shared by distant…

Quantum Physics · Physics 2025-09-03 Yunkai Wang , Yujie Zhang , Virginia O. Lorenz

We developed a lattice dynamical theory of an atomically-thin compressional piezoelectric resonator. Acoustic and optical dynamic displacement response functions are derived and account for frequency-dependent electromechanical coupling.…

Mesoscale and Nanoscale Physics · Physics 2024-10-07 Karl H. Michel , Cem Sevik , Milorad V. Milosevic

Within the framework of quantization of the macroscopic electromagnetic field, equations of motion and an effective Hamiltonian for treating both the resonant dipole-dipole interaction between two-level atoms and the resonant atom-field…

Quantum Physics · Physics 2016-08-16 Ho Trung Dung , Ludwig Knöll , Dirk-Gunnar Welsch

We implement superconducting YBCO planar resonators with two fundamental modes for circuit quantum electrodynamics experiments. We first demonstrate good tunability in the resonant microwave frequencies and in their interplay as it emerges…

Mesoscale and Nanoscale Physics · Physics 2018-12-04 Claudio Bonizzoni , Filippo Troiani , Alberto Ghirri , Marco Affronte

The theory of disordered elastic systems is one of the most powerful frameworks to assess the physics of multiple systems that span from ferromagnets to migrating biological cells. In this formalism, one assumes that the system can be…

Disordered Systems and Neural Networks · Physics 2022-11-28 Nirvana Caballero , Thierry Giamarchi

Dispersion in the interstellar medium is a well known phenomenon that follows a simple relationship, which has been used to predict the time delay of dispersed radio pulses since the late 1960s. We performed wide-band simultaneous…

A spilt-ring resonator experiment suitable for senior physics undergraduates is described and demonstrated in detail. The apparatus consists of a conducting hollow cylinder with a narrow slit along its length and can be accurately modelled…

Physics Education · Physics 2018-11-06 J. S. Bobowski

We study the possibility of occurrence of vibrational resonance in a softening Duffing oscillator in the underdamped and overdamped cases both theoretically as well as numerically. The oscillator is driven by two periodic forces.…

Chaotic Dynamics · Physics 2021-07-20 Ivan Skhem Sawkmie , Donrich Kharkongor

We study the sampling of spatial fields using sensors that are location-unaware but deployed according to a known statistical distribution. It has been shown that uniformly distributed location-unaware sensors cannot infer bandlimited…

Information Theory · Computer Science 2016-12-01 Ankur Mallick , Animesh Kumar

We report the observation of discrete displacement of nanomechanical oscillators with gigahertz-range resonance frequencies at millikelvin temperatures. The oscillators are nanomachined single-crystal structures of silicon, designed to…

Other Condensed Matter · Physics 2009-11-11 Alexei Gaidarzhy , Guiti Zolfagharkhani , Robert L. Badzey , Pritiraj Mohanty

Granular systems are not always homogeneous and can be composed of grains with very different mechanical properties. To improve our understanding of the behavior of real granular systems, in this experimental study, we compress 2D…

Soft Condensed Matter · Physics 2021-07-14 Jonathan Barés , Manuel Cárdenas-Barrantes , David Cantor , Émilien Azéma , Mathieu Renouf

Pre-displaced micromechanical resonators made from high-stress material give rise to new rich static and dynamic behavior. Here, an analytical model is presented to describe the mechanics of such pre-displaced resonators. The bending and…

Classical Physics · Physics 2022-11-28 Xiong Yao , David Hoch , Menno Poot

Multi-qubit quantum sensors are rapidly emerging as platforms that extend the capabilities of conventional single-qubit sensing. In this work we show how suitable pulse sequences applied to a two-qubit sensor enable separate extraction of…

We explore statistical fluctuations over the ensemble of quantum trajectories in a model of two-dimensional free fermions subject to projective monitoring of local charge across the measurement-induced phase transition. Our observables are…

Quantum Physics · Physics 2026-02-11 Igor Poboiko , Igor V. Gornyi , Alexander D. Mirlin

The search for new superconducting materials approaching room temperature benefits from having a variety of testing methodologies to confirm and characterize the presence of superconductivity. Often the first signatures of new…

Superconductivity · Physics 2019-07-02 Charles L. Dean , Milind N. Kunchur

We investigate the AC conductivity of binary random impedance networks, with emphasis on its dependence on the ratio of the complex conductances of both phases. We propose an algorithm to determine the conductance of a finite network, in…

Disordered Systems and Neural Networks · Physics 2009-10-31 Th. Jonckheere , J. M. Luck

Learning to disentangle and represent factors of variation in data is an important problem in AI. While many advances have been made to learn these representations, it is still unclear how to quantify disentanglement. While several metrics…

Machine Learning · Computer Science 2022-05-10 Marc-André Carbonneau , Julian Zaidi , Jonathan Boilard , Ghyslain Gagnon
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