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Noise is an important factor that influences the reliability of information acquisition, transmission, processing, and storage. In order to suppress the inevitable noise effects, a fault-tolerant information processing approach via quantum…

Quantum Physics · Physics 2026-03-27 Qi Song , Hongjing Li , Chengxi Yu , Jingzheng Huang , Ding Wang , Peng Huang , Guihua Zeng

Lossy Image compression is necessary for efficient storage and transfer of data. Typically the trade-off between bit-rate and quality determines the optimal compression level. This makes the image quality metric an integral part of any…

Computer Vision and Pattern Recognition · Computer Science 2021-07-16 Juan Carlos Mier , Eddie Huang , Hossein Talebi , Feng Yang , Peyman Milanfar

Compressive lensless imagers enable novel applications in an extremely compact device, requiring only a phase or amplitude mask placed close to the sensor. They have been demonstrated for 2D and 3D microscopy, single-shot video, and…

Image and Video Processing · Electrical Eng. & Systems 2021-06-23 Kristina Monakhova , Vi Tran , Grace Kuo , Laura Waller

An optical transmitter irradiates a target region containing a bright thermal-noise bath in which a low-reflectivity object might be embedded. The light received from this region is used to decide whether the object is present or absent.…

Transferring a quantum state of a light field to a memory is of particular importance. However, this transfer is usually hampered because the memory system is subjected to some noise and this can limit the performance of the state transfer…

Quantum Physics · Physics 2012-02-21 Go Tajimi , Naoki Yamamoto

Loss is inevitable for the optical system due to absorption of materials, scattering caused by the defects and surface roughness. In quantum optical circuits, the loss can not only reduce the intensity of signal, but also affect the…

Optics · Physics 2017-11-22 Ming Li , Chang-Ling Zou , Guang-Can Guo , Xi-Feng Ren

Bayesian inversion is central to the quantification of uncertainty within problems arising from numerous applications in science and engineering. To formulate the approach, four ingredients are required: a forward model mapping the unknown…

Machine Learning · Statistics 2025-05-15 O. Deniz Akyildiz , Mark Girolami , Andrew M. Stuart , Arnaud Vadeboncoeur

Non-linear image reconstruction and signal analysis deal with complex inverse problems. To tackle such problems in a systematic way, I present information field theory (IFT) as a means of Bayesian, data based inference on spatially…

Instrumentation and Methods for Astrophysics · Physics 2015-06-12 Torsten Enßlin

BosonSampling is an intermediate model of quantum computation where linear-optical networks are used to solve sampling problems expected to be hard for classical computers. Since these devices are not expected to be universal for quantum…

Quantum Physics · Physics 2016-01-27 Scott Aaronson , Daniel J. Brod

We show how to distribute with percentage success probabilities almost perfectly entangled qubit memory pairs over repeater channel segments of the order of the optical attenuation distance. In addition to some weak, dispersive light-matter…

Quantum Physics · Physics 2013-05-29 Ludmila Praxmeyer , Peter van Loock

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…

Theories in physics can provide a kind of map of the physical system under investigation, showing all of the possible types of behavior which may occur. Certain points on the map are of greater significance than others, because they…

Quantum Physics · Physics 2023-07-26 C. A. Downing , O. I. R. Fox

With applications ranging from metabolomics to histopathology, quantitative phase microscopy (QPM) is a powerful label-free imaging modality. Despite significant advances in fast multiplexed imaging sensors and deep-learning-based inverse…

Tensor recovery has recently arisen in a lot of application fields, such as transportation, medical imaging and remote sensing. Under the assumption that signals possess sparse and/or low-rank structures, many tensor recovery methods have…

Optimization and Control · Mathematics 2021-02-16 Xuemei Chen , Jing Qin

Conventional wisdom holds that quantum effects are fragile and can be destroyed by loss. Here, contrary to general belief, we show how to realize quantum revival of optical correlations at the single-photon level with the help of loss. We…

Quantum Physics · Physics 2022-02-08 Yunlan Zuo , Ran Huang , Le-Man Kuang , Xun-Wei Xu , Hui Jing

A fundamental problem in phase retrieval is to reconstruct an unknown signal from a set of magnitude-only measurements. In this work we introduce three novel quotient intensity-based models (QIMs) based a deep modification of the…

Numerical Analysis · Mathematics 2021-12-16 Jian-Feng Cai , Meng Huang , Dong Li , Yang Wang

Long-distance optical quantum channels are necessarily lossy, leading to errors in transmitted quantum information, entanglement degradation and, ultimately, poor protocol performance. Quantum states carrying information in the channel can…

Real photonic devices are subject to photon losses that can decohere quantum information encoded in the system. In the absence of full fault tolerance, quantum error mitigation techniques have been introduced to help manage errors in noisy…

Quantum Physics · Physics 2025-01-16 Adam Taylor , Gabriele Bressanini , Hyukjoon Kwon , M. S. Kim

We investigate phase estimation in a lossy interferometer using entangled coherent states, with particular focus on a scenario where no reference beam is employed. By calculating the quantum Fisher information, we reveal two key results:…

Quantum Physics · Physics 2025-06-02 Jun Tang , Dong-Qing Wang , Wei Zhong , Lan Zhou , Yu-Bo Sheng

Recovering scene color from images captured in scattering media is a fundamental inverse problem in optical imaging. Yet the problem is intrinsically ill-posed as multiple solutions can explain the same observation, and prediction error…

Computer Vision and Pattern Recognition · Computer Science 2026-05-06 Grigory Solomatov , Derya Akkaynak