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Quantum information offers the promise of being able to perform certain communication and computation tasks that cannot be done with conventional information technology (IT). Optical Quantum Information Processing (QIP) holds particular…

Quantum Physics · Physics 2009-11-11 W. J. Munro , Kae Nemoto , T. P. Spiller , S. D. Barrett , Pieter Kok , R. G. Beausoleil

With the aim of establishing a framework to efficiently perform the practical application of quantum chemistry simulation on near-term quantum devices, we envision a hybrid quantum--classical framework for leveraging problem decomposition…

The development of quantum computers has been the stimulus that enables the realization of Quantum Machine Learning (QML), an area that integrates the calculational framework of quantum mechanics with the adaptive properties of classical…

Computational Engineering, Finance, and Science · Computer Science 2025-09-04 Bhavna Bose , Saurav Verma

In this work, we give a hybrid quantum-classical algorithm for solving electronic structure problems of molecules using only linear quantum optical systems. The variational ansatz we proposed is a hybrid of non-interacting Boson dynamics…

The search for new, application-specific quantum computers designed to outperform any classical computer is driven by the ending of Moore's law and the quantum advantages potentially obtainable. Photonic networks are promising examples,…

Quantum Physics · Physics 2018-04-13 B. Opanchuk , L. Rosales-Zárate , M. D. Reid , P. D. Drummond

There is a growing consensus that large-scale, fault-tolerant quantum computing (FTQC) necessitates high-fidelity photonic interconnects to overcome the scaling limits of monolithic architectures. However, most current platforms were not…

Proper quality control (QC) is time consuming when working with large-scale medical imaging datasets, yet necessary, as poor-quality data can lead to erroneous conclusions or poorly trained machine learning models. Most efforts to reduce…

Many applications of quantum computing in the near term rely on variational quantum circuits (VQCs). They have been showcased as a promising model for reaching a quantum advantage in machine learning with current noisy intermediate scale…

Quantum Physics · Physics 2022-10-25 Jonas Landman , Slimane Thabet , Constantin Dalyac , Hela Mhiri , Elham Kashefi

An optical source that produces single photon pulses on demand has potential applications in linear optics quantum computation, provided that stringent requirements on indistinguishability and collection efficiency of the generated photons…

Quantum Physics · Physics 2009-11-10 A. Kiraz , M. Atature , A. Imamoglu

Quantum gates and simple quantum algorithms can be designed utilizing the diffraction phenomena of a photon within a multiplexed holographic element. The quantum eigenstates we use are the photon's linear momentum (LM) as measured by the…

The creation of large-scale, high-fidelity quantum computers is not only a fundamental scientific endeavour in itself, but also provides increasingly robust proofs of quantum computational advantage (QCA) in the presence of unavoidable…

Quantum walks, in virtue of the coherent superposition and quantum interference, possess exponential superiority over its classical counterpart in applications of quantum searching and quantum simulation. The quantum enhanced power is…

The interference of non-classical states of light enables quantum-enhanced applications reaching from metrology to computation. Most commonly, the polarisation or spatial location of single photons are used as addressable degrees-of-freedom…

There is a class of statistical problems that arises in several contexts, the Lattice QCD problem of particle physics being one that has attracted the most attention. In essence, the problem boils down to the estimation of an infinite…

Methodology · Statistics 2012-01-06 Joshua Landon , Frank X. Lee , Nozer D. Singpurwalla

In this paper, we propose a low complexity quantum principal component analysis (qPCA) algorithm. Similar to the state-of-the-art qPCA, it achieves dimension reduction by extracting principal components of the data matrix, rather than all…

Quantum Physics · Physics 2021-01-14 Chen He , Jiazhen Li , Weiqi Liu , Z. Jane Wang

Building a quantum analog of classical deep neural networks represents a fundamental challenge in quantum computing. A key issue is how to address the inherent non-linearity of classical deep learning, a problem in the quantum domain due to…

The Quantum Computer Condition (QCC) provides a rigorous and completely general framework for carrying out analyses of questions pertaining to fault-tolerance in quantum computers. In this paper we apply the QCC to the problem of…

Quantum Physics · Physics 2007-05-23 Gerald Gilbert , Michael Hamrick , F. Javier Thayer , Yaakov S. Weinstein

Optical computing harnesses the speed of light to perform vector-matrix operations efficiently. It leverages interference, a cornerstone of quantum computing algorithms, to enable parallel computations. In this work, we interweave quantum…

Quantum Physics · Physics 2024-10-14 Mwezi Koni , Hadrian Bezuidenhout , Isaac Nape

In this Near Intermediate-Scale Quantum era, there are two types of near-term quantum devices available on cloud: superconducting quantum processing units (QPUs) based on the discrete variable model and linear optics (photonics) QPUs based…

Quantum Physics · Physics 2022-06-16 Sophie Choe

With advanced micro- and nano-photonic structures, the vacuum photon-photon coupling rate is anticipated to approach the intrinsic loss rate and lead to unconventional quantum effects. Here, we investigate the classical-to-quantum…

Quantum Physics · Physics 2022-04-11 Yue-Xun Huang , Ming Li , Ke Lin , Yan-Lei Zhang , Guang-Can Guo , Chang-Ling Zou