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As the matching condition in Grover search algorithm is transgressed due to inevitable errors in phase inversions, it gives a reduction in maximum probability of success. With a given degree of maximum success, we have derive the…

Quantum Physics · Physics 2007-05-23 Jin-Yuan Hsieh , Che-Ming Li , Der-San Chuu

Quantum algorithms and complexity have recently been studied not only for discrete, but also for some numerical problems. Most attention has been paid so far to the integration problem, for which a speed-up is shown by quantum computers…

Quantum Physics · Physics 2007-05-23 Boleslaw Kacewicz

We propose genetic algorithms, which are robust optimization techniques inspired by natural selection, to enhance the versatility of digital quantum simulations. In this sense, we show that genetic algorithms can be employed to increase the…

Quantum Physics · Physics 2016-06-22 U. Las Heras , U. Alvarez-Rodriguez , E. Solano , M. Sanz

Quantum combs play a vital role in characterizing and transforming quantum processes, with wide-ranging applications in quantum information processing. However, obtaining the explicit quantum circuit for the desired quantum comb remains a…

Quantum Physics · Physics 2025-02-26 Yin Mo , Lei Zhang , Yu-Ao Chen , Yingjian Liu , Tengxiang Lin , Xin Wang

We derive general discrimination of quantum states chosen from a certain set, given initial $M$ copies of each state, and obtain the matrix inequality, which describe the bound between the maximum probability of correctly determining and…

Quantum Physics · Physics 2009-10-31 Chuan-Wei Zhang , Chuan-Feng Li , Guang-Can Guo

Quantum computing holds the potential to revolutionize various fields by efficiently tackling complex problems. At its core are quantum circuits, sequences of quantum gates manipulating quantum states. The selection of the right quantum…

Software Engineering · Computer Science 2024-06-13 Xiaoyu Guo , Takahiro Muta , Jianjun Zhao

Anomaly detection in time-series data is a critical challenge with significant implications for network security. Recent quantum machine learning approaches, such as quantum kernel methods and variational quantum circuits, have shown…

Machine Learning · Computer Science 2025-10-31 Wajdi Hammami , Soumaya Cherkaoui , Jean-Frederic Laprade , Ola Ahmad , Shengrui Wang

We develop a unified framework for identifying bounds to maximum resonant nonlinear optical susceptibilities, and for "inverse designing" quantum-well structures that can approach such bounds. In special cases (e.g. second-harmonic…

The native gate set is fundamental to the performance of quantum devices, as it governs the accuracy of basic quantum operations and dictates the complexity of implementing quantum algorithms. Traditional approaches to extending gate sets…

In randomized benchmarking of quantum logical gates, partial twirling can be used for simpler implementation, better scaling, and higher accuracy and reliability. For instance, for two-qubit gates, single-qubit twirling is easier to realize…

Quantum Physics · Physics 2022-06-22 Kirill Dubovitskii , Yuriy Makhlin

Sequential methods for quantum hypothesis testing offer significant advantages over fixed-length approaches, which rely on a predefined number of state copies. Despite their potential, these methods remain underexplored for unambiguous…

Quantum Physics · Physics 2025-11-26 Jordi Pérez-Guijarro , Alba Pagès-Zamora , Javier R. Fonollosa

Identifying symmetries in quantum dynamics, such as identity or time-reversal invariance, is a crucial challenge with profound implications for quantum technologies. We introduce a unified framework combining group representation theory and…

Quantum Physics · Physics 2025-02-04 Masahito Hayashi , Yu-Ao Chen , Chenghong Zhu , Xin Wang

Safety is a critical concern for the success of urban air mobility, especially in dynamic and uncertain environments. This paper proposes a path planning algorithm based on RRT in conjunction with chance constraints in the presence of…

Robotics · Computer Science 2022-03-15 Pengcheng Wu , Lin Li , Junfei Xie , Jun Chen

We examine how to distinguish between unitary operators, when the exact form of the possible operators is not known. Instead we are supplied with "programs" in the form of unitary transforms, which can be used as references for identifying…

Quantum Physics · Physics 2011-09-23 Mark Hillery , Erika Andersson , Stephen M. Barnett , Daniel Oi

The problem of discriminating the state of a quantum system among a number of hypothetical states is usually addressed under the assumption that one has perfect knowledge of the possible states of the system. In this thesis, I analyze the…

Quantum Physics · Physics 2014-07-18 Gael Sentís

We investigate protocols for generating a state $t$-design by using a fixed separable initial state and a diagonal-unitary $t$-design in the computational basis, which is a $t$-design of an ensemble of diagonal unitary matrices with random…

Quantum Physics · Physics 2014-05-27 Yoshifumi Nakata , Masato Koashi , Mio Murao

Can a problem undecidable with classical resources be decidable with quantum ones? The answer expected is no; as both being Turing theories, they should not solve the Halting problem - a problem unsolvable by any Turing machine. Yet, we…

Quantum Physics · Physics 2021-12-28 Airin Antony

We consider N quantum systems initially prepared in pure states and address the problem of unambiguously comparing them. One may ask whether or not all $N$ systems are in the same state. Alternatively, one may ask whether or not the states…

Quantum Physics · Physics 2014-11-18 Anthony Chefles , Erika Andersson , Igor Jex

Designing high-fidelity quantum circuits remains challenging, and current paradigms often depend on heuristic, fixed-ansatz structures or rule-based compilers that can be suboptimal or lack generality. We introduce a neuro-symbolic…

Quantum Physics · Physics 2026-04-10 Antonin Sulc

Treating uncertainties in models is essential in many fields of science and engineering. Uncertainty quantification (UQ) on complex and computationally costly numerical models necessitates a combination of efficient model solvers, advanced…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-04-28 Linus Seelinger , Anne Reinarz , Jean Benezech , Mikkel Bue Lykkegaard , Lorenzo Tamellini , Robert Scheichl