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This work studies the variational quantum eigensolver algorithm, designed to determine the ground state of a quantum mechanical system by combining classical and quantum hardware. Methods of reducing the number of required qubit…

Quantum Physics · Physics 2022-03-01 R. J. P. T. de Keijzer , V. E. Colussi , B. Škorić , S. J. J. M. F. Kokkelmans

We evaluate the quantum resource requirements for ATP/metaphosphate hydrolysis, one of the most important reactions in all of biology with implications for metabolism, cellular signaling, and cancer therapeutics. In particular, we consider…

Reliable adaptive beamforming is critical for large microphone arrays operating in highly dynamic acoustic environments. In scenarios characterized by fast-moving talkers and interferers, the available sample support for estimating the…

Signal Processing · Electrical Eng. & Systems 2026-05-13 Manan Mittal , Ryan M. Corey , John R. Buck , Andrew C. Singer

Quantum noise is conventionally viewed as a fundamental obstacle in near-term quantum computing, motivating extensive error correction and mitigation strategies. We present numerical evidence that challenges this consensus. Through…

Quantum Physics · Physics 2026-01-21 Linghua Zhu , Yulong Dong , Ziyu Zhang , Xiaosong Li

Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for VQA parameter optimization, it remains a significant…

Quantum Physics · Physics 2024-06-05 Zichang He , Bo Peng , Yuri Alexeev , Zheng Zhang

Solving challenging problems in quantum chemistry is one of the most promising applications of quantum computers. Within the quantum algorithms proposed for problems in excited state quantum chemistry, subspace-based quantum algorithms,…

Optimisation plays a central role in a wide range of scientific and industrial applications, and quantum computing has been widely proposed as a means to achieve computational advantages in this domain. To date, research into the design of…

Quantum Physics · Physics 2026-02-03 Stuart Ferguson , Petros Wallden

We evaluate the Sample-based Krylov Quantum Diagonalization (SKQD) algorithm on one- and two-dimensional Heisenberg models, including strongly correlated regimes in which the ground state is dense. Using problem-informed initial states and…

We propose a hybrid quantum approach to threshold and binarize a grayscale image through unsharp measurements (UM) relying on image histogram. Generally, the histograms are characterized by multiple overlapping normal distributions…

Quantum Physics · Physics 2024-01-02 Ayan Barui , Mayukha Pal , Prasanta K. Panigrahi

The development of various dynamic ansatz-constructing techniques has ushered in a new era, rendering the practical exploitation of Noisy Intermediate-Scale Quantum (NISQ) hardware for molecular simulations increasingly viable. However,…

Quantum Physics · Physics 2023-10-13 Sonaldeep Halder , Anish Dey , Chinmay Shrikhande , Rahul Maitra

Variational quantum algorithms (VQAs) offer the most promising path to obtaining quantum advantages via noisy intermediate-scale quantum (NISQ) processors. Such systems leverage classical optimization to tune the parameters of a…

Quantum Physics · Physics 2022-09-26 Sharu Theresa Jose , Osvaldo Simeone

Noise and imperfections are among the prevalent challenges in quantum software engineering for current NISQ systems. They will remain important in the post-NISQ area, as logical, error-corrected qubits will be based on software mechanisms.…

Quantum Physics · Physics 2025-09-17 Stefan Raimund Maschek , Jürgen Schwitalla , Maja Franz , Wolfgang Mauerer

Quantum annealing is a framework for solving combinatorial optimization problems. While it offers a promising path towards a practical application of quantum hardware, its performance in real-world devices is severely limited by…

The variational quantum eigensolver (VQE) is a hybrid algorithm that has the potential to provide a quantum advantage in practical chemistry problems that are currently intractable on classical computers. VQE trains parameterized quantum…

Quantum Physics · Physics 2023-11-10 Quoc Hoan Tran , Shinji Kikuchi , Hirotaka Oshima

Excess noise is a major obstacle to high-performance continuous-variable quantum key distribution (CVQKD), which is mainly derived from the amplitude attenuation and phase fluctuation of quantum signals caused by channel instability. Here,…

Quantum Physics · Physics 2022-07-22 Kexin Liang , Geng Chai , Zhengwen Cao , Qing Wang , Lei Wang , Jinye Peng

Noise on quantum devices is much more complex than it is commonly given credit. Far from usual models of decoherence, nearly all quantum devices are plagued both by a continuum of environments and temporal instabilities. These induce noisy…

Quantum Physics · Physics 2025-08-27 Gregory A. L. White , Petar Jurcevic , Charles D. Hill , Kavan Modi

We present a quantum chemistry benchmark for noisy intermediate-scale quantum computers that leverages the variational quantum eigensolver, active space reduction, a reduced unitary coupled cluster ansatz, and reduced density purification…

We consider quantum metrology in noisy environments, where the effect of noise and decoherence limits the achievable gain in precision by quantum entanglement. We show that by using tools from quantum error-correction this limitation can be…

Quantum Physics · Physics 2014-03-12 W. Dür , M. Skotiniotis , F. Fröwis , B. Kraus

Quantum systems can be used to measure various quantities in their environment with high precision. Often, however, their sensitivity is limited by the decohering effects of this same environment. Dynamical decoupling schemes are widely…

Quantum Physics · Physics 2018-07-18 David Layden , Paola Cappellaro

Variational quantum eigensolvers (VQEs) are among the most promising quantum algorithms for solving electronic structure problems in quantum chemistry, particularly during the Noisy Intermediate-Scale Quantum (NISQ) era. In this study, we…

Quantum Physics · Physics 2026-05-07 Abel Carreras , David Casanova , Román Orús