English
Related papers

Related papers: Sparse Sampling for Fast Quasiparticle Interferenc…

200 papers

Simultaneous sparse approximation is a generalization of the standard sparse approximation, for simultaneously representing a set of signals using a common sparsity model. Generalizing the compressive sensing concept to the simultaneous…

Information Theory · Computer Science 2018-09-18 Arash Golibagh Mahyari , Selin Aviyente

Many algorithms have been developed to solve the inverse problem of coded aperture snapshot spectral imaging (CASSI), i.e., recovering the 3D hyperspectral images (HSIs) from a 2D compressive measurement. In recent years, learning-based…

Computer Vision and Pattern Recognition · Computer Science 2022-07-12 Yuanhao Cai , Jing Lin , Xiaowan Hu , Haoqian Wang , Xin Yuan , Yulun Zhang , Radu Timofte , Luc Van Gool

We present a quantum secure imaging (QSI) scheme based on the phase encoding and weak + vacuum decoy-state BB84 protocol of quantum key distribution (QKD). It allows us to implement a computational ghost imaging (CGI) system with more…

Quantum Physics · Physics 2024-10-03 Yi-Bo Zhao , Wan-Li Zhang , Dong Wang , Xiao-Tian Song , Liang-Jiang Zhou , Chi-Biao Ding

In the light of the progress in quantum technologies, the task of verifying the correct functioning of processes and obtaining accurate tomographic information about quantum states becomes increasingly important. Compressed sensing, a…

Quantum Physics · Physics 2017-05-15 A. Steffens , C. Riofrio , W. McCutcheon , I. Roth , B. A. Bell , A. McMillan , M. S. Tame , J. G. Rarity , J. Eisert

We investigate the problem of recovering a structured sparse signal from a linear observation model with an uncertain dynamic grid in the sensing matrix. The state-of-the-art expectation maximization based compressed sensing (EM-CS)…

Signal Processing · Electrical Eng. & Systems 2024-07-25 An Liu , Yufan Zhou , Wenkang Xu

Compressed sensing (CS) is a sampling theory that allows reconstruction of sparse (or compressible) signals from an incomplete number of measurements, using of a sensing mechanism implemented by an appropriate projection matrix. The CS…

Computer Vision and Pattern Recognition · Computer Science 2017-08-29 Duc Minh Nguyen , Evaggelia Tsiligianni , Nikos Deligiannis

Manifold amount of video data gets generated every minute as we read this document, ranging from surveillance to broadcasting purposes. There are two roadblocks that restrain us from using this data as such, first being the storage which…

Computer Vision and Pattern Recognition · Computer Science 2019-07-10 Sathyaprakash Narayanan , Yeshwanth Bethi , Chetan Singh Thakur

This paper introduces a novel framework and corresponding methods for sampling and reconstruction of sparse signals in shift-invariant (SI) spaces. We reinterpret the random demodulator, a system that acquires sparse bandlimited signals, as…

Signal Processing · Electrical Eng. & Systems 2022-01-24 Tin Vlašić , Damir Seršić

The Scanning Tunneling Microscope (STM) is a powerful instrument to study electronic density of states at surfaces down to atomic scale. Many interesting samples require studying variations as a function of the magnetic field, which is most…

Quantum state tomography (QST) via local measurements on reduced density matrices (LQST) is a promising approach but becomes impractical for large systems. To tackle this challenge, we developed an efficient quantum state tomography method…

In this work we explore the possibility of using sparse statistical modeling in condensed matter physics. The procedure is employed to two well known problems: elemental superconductors and heavy fermions, and was shown that in most cases…

Superconductivity · Physics 2026-01-21 J. McGee , S. V. Dordevic

Quasi-particle interference (QPI) is a powerful tool to characterize the symmetry of the superconducting order parameter in unconventional superconductors, by mapping the spatial dependence of elastic tunneling of electrons between the tip…

Full data acquisition in MRI is inherently slow, which limits clinical throughput and increases patient discomfort. Compressed Sensing MRI (CS-MRI) seeks to accelerate acquisition by reconstructing images from under-sampled k-space data,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Lev Ayzenberg , Shady Abu-Hussein , Raja Giryes , Hayit Greenspan

We establish methods for quantum state tomography based on compressed sensing. These methods are specialized for quantum states that are fairly pure, and they offer a significant performance improvement on large quantum systems. In…

Quantum Physics · Physics 2015-05-14 David Gross , Yi-Kai Liu , Steven T. Flammia , Stephen Becker , Jens Eisert

Quantum state tomography (QST) is the gold standard technique for obtaining an estimate for the state of small quantum systems in the laboratory. Its application to systems with more than a few constituents (e.g. particles) soon becomes…

Compressive Sensing (CS) theory asserts that sparse signal reconstruction is possible from a small number of linear measurements. Although CS enables low-cost linear sampling, it requires non-linear and costly reconstruction. Recent…

Machine Learning · Computer Science 2018-10-16 Aysen Degerli , Sinem Aslan , Mehmet Yamac , Bulent Sankur , Moncef Gabbouj

We employ a five-orbital tight-binding model to develop the mean field solution for various possible spin density wave states in the iron-chalcogenides. The quasiparticle interference (QPI) technique is applied to detect signatures of these…

Superconductivity · Physics 2016-05-09 Bhaskar Kamble , Alireza Akbari , Ilya Eremin

This paper presents a quadrature compressive sampling (QuadCS) and associated fast imaging scheme for synthetic aperture radar (SAR). Different from other analog-to-information conversions (AIC), QuadCS AICs using independent spreading…

Information Theory · Computer Science 2018-01-12 Huizhang Yang , Shengyao Chen , Feng Xi , Zhong Liu

Compressed sensing (CS) enables people to acquire the compressed measurements directly and recover sparse or compressible signals faithfully even when the sampling rate is much lower than the Nyquist rate. However, the pure random sensing…

Information Theory · Computer Science 2016-11-24 Kezhi Li , Shuang Cong