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Quantum state tomography is a technique in quantum information science used to reconstruct the density matrix of an unknown quantum state, providing complete information about the quantum state. It is of significant importance in fields…

Quantum Physics · Physics 2025-07-23 Wenlong Zhao , Da Zhang , Huili Zhang , Haifeng Yu , Zhang-qi Yin

Scanning tunneling microscopy visualizations of quasiparticle interference (QPI) enable powerful insights into the k-space properties of superconducting, topological, Rashba and other exotic electronic phases, but their reliance on…

A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribution, and achieving accurate reconstruction on average, is…

Computer Vision and Pattern Recognition · Computer Science 2015-05-27 Guoshen Yu , Guillermo Sapiro

Compressed sensing is a theory which guarantees the exact recovery of sparse signals from a small number of linear projections. The sampling schemes suggested by current compressed sensing theories are often of little practical relevance…

Information Theory · Computer Science 2014-07-22 Jérémie Bigot , Claire Boyer , Pierre Weiss

Scanning superconducting quantum interference device microscopy (SSM) is a scanning probe technique that images local magnetic flux, which allows for mapping of magnetic fields with high field and spatial accuracy. Many studies involving…

Instrumentation and Detectors · Physics 2018-01-17 P. Reith , X. Renshaw Wang , H. Hilgenkamp

Electron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) theory exploits the inherent sparse signal structure to efficiently reconstruct…

Computational Physics · Physics 2020-12-02 Jonathan Schwartz , Huihuo Zheng , Marcus Hanwell , Yi Jiang , Robert Hovden

Sparse signals, encountered in many wireless and signal acquisition applications, can be acquired via compressed sensing (CS) to reduce computations and transmissions, crucial for resource-limited devices, e.g., wireless sensors. Since the…

Signal Processing · Electrical Eng. & Systems 2020-08-27 Markus Leinonen , Marian Codreanu

Time-frequency distributions have been used to provide high resolution representation in a large number of signal processing applications. However, high resolution and accurate instantaneous frequency (IF) estimation usually depend on the…

Information Theory · Computer Science 2015-03-02 Irena Orovic , Andjela Draganic , Srdjan Stankovic

Cameras for imaging in short and mid-wave infrared spectra are significantly more expensive than their counterparts in visible imaging. As a result, high-resolution imaging in those spectrum remains beyond the reach of most consumers. Over…

Computer Vision and Pattern Recognition · Computer Science 2015-04-17 Huaijin Chen , M. Salman Asif , Aswin C. Sankaranarayanan , Ashok Veeraraghavan

Femtosecond spectroscopy is an important tool for tracking rapid photoinduced processes in a variety of materials. To spatially map the processes in a sample would substantially expand the capabilities of the method. This is, however,…

Optics · Physics 2019-05-01 Ondřej Denk , Kaibo Zheng , Donatas Zigmantas , Karel Žídek

Scanning Transmission Electron Microscopy (STEM) offers high-resolution images that are used to quantify the nanoscale atomic structure and composition of materials and biological specimens. In many cases, however, the resolution is limited…

Signal Processing · Electrical Eng. & Systems 2021-12-23 Daniel Nicholls , Alex Robinson , Jack Wells , Amirafshar Moshtaghpour , Mounib Bahri , Angus Kirkland , Nigel Browning

Measurement samples are often taken in various monitoring applications. To reduce the sensing cost, it is desirable to achieve better sensing quality while using fewer samples. Compressive Sensing (CS) technique finds its role when the…

Information Theory · Computer Science 2016-11-18 Ying Li , Kun Xie , Xin Wang

Compressed sensing is designed to measure sparse signals directly in a compressed form. However, most signals of interest are only "approximately sparse", i.e. even though the signal contains only a small fraction of relevant (large)…

Information Theory · Computer Science 2013-04-04 Jean Barbier , Florent Krzakala , Marc Mézard , Lenka Zdeborová

A major challenge to implement the compressed sensing method for channel state information (CSI) acquisition lies in the design of a well-performed measurement matrix to reduce the dimension of sparse channel vectors. The widely adopted…

Information Theory · Computer Science 2020-07-14 Pengxia Wu , Zichuan Liu , Julian Cheng

We employ the compressed sensing (CS) algorithm and a heavily reduced data set to experimentally perform true quantum process tomography (QPT) on an NMR quantum processor. We obtain the estimate of the process matrix $\chi$ corresponding to…

Quantum Physics · Physics 2024-11-05 Akshay Gaikwad , Arvind , Kavita Dorai

Compressed sensing (CS) provides an elegant framework for recovering sparse signals from compressed measurements. For example, CS can exploit the structure of natural images and recover an image from only a few random measurements. CS is…

Machine Learning · Computer Science 2019-05-21 Yan Wu , Mihaela Rosca , Timothy Lillicrap

The application of Compressive sensing approach to the speech and musical signals is considered in this paper. Compressive sensing (CS) is a new approach to the signal sampling that allows signal reconstruction from a small set of randomly…

Sound · Computer Science 2015-02-06 Trifun Savic , Radoje Albijanic

Compressed sensing magnetic resonance imaging (CS-MRI) heavily relies on the low mutual coherence between the measurement matrix and the sparsity basis. However, under highly accelerated Cartesian undersampling, the severe structural…

Signal Processing · Electrical Eng. & Systems 2026-05-05 Siyuan Feng

Unlike charge and spin, the orbital degree of freedom of electrons in transition metal oxides is difficult to detect. We present the theoretical study of a new detection method in metallic orbitally active systems by analyzing the…

Strongly Correlated Electrons · Physics 2009-10-23 Wei-Cheng Lee , Congjun Wu

Quantum state tomography (QST) is an indispensable tool for characterizing many-body quantum systems. However, due to the exponential scaling of the cost of the protocol with system size, many approaches have been developed for quantum…

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