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Systems of linear equations are used to model a wide array of problems in all fields of science and engineering. Recently, it has been shown that quantum computers could solve linear systems exponentially faster than classical computers,…

Photonic quantum computing has recently emerged as a promising candidate for fault-tolerant quantum computing by photonic qubits. These protocols make use of nondeterministic gates, enabling universal quantum computation. However, the…

Quantum Physics · Physics 2024-07-11 Csaba Czabán , Zoltán Kolarovszki , Márton Karácsony , Zoltán Zimborás

Quantum technologies, such as quantum communication, sensing and imaging, need a platform which is flexible, miniaturizable and works at room temperature. Integrated photonics is a promising and fast-developing platform. This requires to…

Quantum Physics · Physics 2021-10-12 Andrei-Emanuel Dragomir , Cristian George Ivan , Radu Ionicioiu

We propose a general framework for differentiating shapes represented in binary images with respect to their parameters. This framework functions as an automatic differentiation tool for shape parameters, generating both binary density maps…

Computational Physics · Physics 2024-12-04 Zhaocheng Liu , Jim Bonar

We propose and analyze the design of a programmable photonic integrated circuit for high-fidelity quantum computation and simulation. We demonstrate that the reconfigurability of our design allows us to overcome two major impediments to…

Quantum Physics · Physics 2015-09-30 Jacob Mower , Nicholas C. Harris , Gregory R. Steinbrecher , Yoav Lahini , Dirk Englund

This note reviews the model of computation generated by photonic circuits, comprising edges that are traversed by photons in a single time-bin and vertices given by idealised lossless beam splitters and phase shifters. The circuit model is…

Quantum Physics · Physics 2022-11-28 Paul McCloud

Quantum machine learning aims to release the prowess of quantum computing to improve machine learning methods. By combining quantum computing methods with classical neural network techniques we aim to foster an increase of performance in…

High Energy Physics - Phenomenology · Physics 2021-03-17 Andrew Blance , Michael Spannowsky

Photons are a ubiquitous carrier of quantum information: they are fast, suffer minimal decoherence, and do not require huge cryogenic facilities. Nevertheless, their intrinsically weak photon-photon interactions remain a key obstacle to…

An important application for near-term quantum computing lies in optimization tasks, with applications ranging from quantum chemistry and drug discovery to machine learning. In many settings --- most prominently in so-called parametrized or…

Quantum Physics · Physics 2019-03-27 Maria Schuld , Ville Bergholm , Christian Gogolin , Josh Izaac , Nathan Killoran

Linear optics is a promising alternative for the realization of quantum computation protocols due to the recent advancements in integrated photonic technology. In this context usually qubit based quantum circuits are considered, however,…

Quantum Physics · Physics 2023-02-16 Márton Karácsony , László Oroszlány , Zoltán Zimborás

Parameterized Quantum Circuits (PQC) are drawing increasing research interest thanks to its potential to achieve quantum advantages on near-term Noisy Intermediate Scale Quantum (NISQ) hardware. In order to achieve scalable PQC learning,…

Quantum Physics · Physics 2025-01-29 Hanrui Wang , Zirui Li , Jiaqi Gu , Yongshan Ding , David Z. Pan , Song Han

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

Machine learning methods have revolutionized the discovery process of new molecules and materials. However, the intensive training process of neural networks for molecules with ever-increasing complexity has resulted in exponential growth…

Emerging Technologies · Computer Science 2022-12-27 Hui Zhang , Jonathan Wei Zhong Lau , Lingxiao Wan , Liang Shi , Hong Cai , Xianshu Luo , Patrick Lo , Chee-Kong Lee , Leong-Chuan Kwek , Ai Qun Liu

Recent progress in nonlinear optical materials and microresonators has brought quantum computing with bulk optical nonlinearities into the realm of possibility. This platform is of great interest, not only because photonics is an obvious…

A scheme for linear optical implementation of fault-tolerant quantum computation is proposed, which is based on an error-detecting code. Each computational step is mediated by transfer of quantum information into an ancilla system embedding…

Quantum Physics · Physics 2007-10-07 Jaeyoon Cho

Quantum technologies promise profound advances in communication security, sensing and computing. The underpinning hardware must be engineered to generate, manipulate and detect quantum phenomena with exceptional performance, whilst being…

Quantum Physics · Physics 2025-07-15 R. N. Clark , B. Puzio , O. M. Green , S. T. Pradyumna , O. Trojak , A. Politi , J. C. F. Matthews

We propose a new scheme for solid-state photonic quantum computation in which trapped photons in optical cavities are taken as a quantum bit. Quantum gates can be realized by coupling the cavities with quantum dots through waveguides. The…

Quantum Physics · Physics 2011-01-19 Makoto Yamaguchi , Takashi Asano , Yoshiya Sato , Susumu Noda

We report an experiment to demonstrate a quantum permutation determining algorithm with linear optical system. By employing photon polarization and spatial modes, we realize the quantum ququart states and all the essential permutation…

Quantum Physics · Physics 2015-06-19 Feiran Wang , Yunlong Wang , Ruifeng Liu , Dongxu Chen , Pei Zhang , Hong Gao , Fuli Li

Linear equations play a pivotal role in many areas of science and engineering, making efficient solutions to linear systems highly desirable. The development of quantum algorithms for solving linear systems has been a significant…

Quantum Physics · Physics 2025-02-20 Nhat A. Nghiem

Gradient estimation is a central challenge in training parameterized quantum circuits (PQCs) for hybrid quantum-classical optimization and learning problems. This difficulty arises from several factors, including the exponential…

Quantum Physics · Physics 2026-05-25 Mohsen Heidari , Masih Mozakka , Wojciech Szpankowski