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Machine learning nowadays becomes a useful instrument in many subjects. In this paper we use interpretable machine learning to build quantum algorithm. By studying the parameters of the machine learning algorithm we were able to construct…

Quantum Physics · Physics 2026-05-21 Matvei Fedin , Andrei Morozov

We propose a quantum algorithm to solve systems of nonlinear algebraic equations. In the ideal case the complexity of the algorithm is linear in the number of variables $n$, which means our algorithm's complexity is less than $O(n^{3})$ of…

Quantum Physics · Physics 2019-03-15 Peng Qian , Wei-Cong Huang , Gui-Lu Long

The manipulation of neutral atoms by light is at the heart of countless scientific discoveries in the field of quantum physics in the last three decades. The level of control that has been achieved at the single particle level within arrays…

We propose a Quantum Machine Learning (QML) framework that leverages quantum parallelism to process entire training datasets in a single quantum operation, addressing the computational bottleneck of sequential data processing in both…

Powerful generative artificial intelligence from large language models (LLMs) harnesses extensive computational resources for inference. In this work, we investigate the transformer architecture, a key component of these models, under the…

Quantum algorithms offer significant speed-ups over their classical counterparts in various applications. In this paper, we develop quantum algorithms for the Kalman filter widely used in classical control engineering using the block…

Quantum Algebra · Mathematics 2024-04-09 Hao Shi , Guofeng Zhang , Ming Zhang

Quantum computers hold promise to improve the efficiency of quantum simulations of materials and to enable the investigation of systems and properties more complex than tractable at present on classical architectures. Here, we discuss…

Quantum Physics · Physics 2022-05-03 Christian Vorwerk , Nan Sheng , Marco Govoni , Benchen Huang , Giulia Galli

Running quantum algorithms often involves implementing complex quantum circuits with such a large number of multi-qubit gates that the challenge of tackling practical applications appears daunting. To date, no experiments have successfully…

Adiabatic quantum computing has evolved in recent years from a theoretical field into an immensely practical area, a change partially sparked by D-Wave System's quantum annealing hardware. These multimillion-dollar quantum annealers offer…

Quantum Physics · Physics 2017-07-28 Timothy D. Goodrich , Travis S. Humble , Blair D. Sullivan

Variational quantum algorithms constitute one of the most widespread methods for using current noisy quantum computers. However, it is unknown if these heuristic algorithms provide any quantum-computational speedup, although we cannot…

Methods of quantum mechanics promise information-theoretic security for various protocols in cryptography. However, impossibility of some cryptographic applications such as standard bit commitment, oblivious transfer, multiparty secure…

Quantum Physics · Physics 2015-08-03 Muhammad Nadeem

Minor embedding is essential for mapping largescale combinatorial problems onto quantum annealers, particularly in quantum machine learning and optimization. This work presents an optimized, universal minor-embedding framework that…

Quantum Physics · Physics 2025-05-01 Salvatore Sinno , Thomas Groß , Nicholas Chancellor , Bhavika Bhalgamiya , Arati Sahoo

Quantum computing exploits quantum phenomena such as superposition and entanglement to realize a form of parallelism that is not available to traditional computing. It offers the potential of significant computational speed-ups in quantum…

Quantum computing is a promising paradigm that may overcome the current computational power bottlenecks. The increasing maturity of quantum processors provides more possibilities for the development and implementation of quantum algorithms.…

Quantum Physics · Physics 2025-10-15 Ge Yan , Wenjie Wu , Yuheng Chen , Kaisen Pan , Xudong Lu , Zixiang Zhou , Yuhan Wang , Ruocheng Wang , Junchi Yan

Quantum computing is expected to have transformative influences on many domains, but its practical deployments on industry problems are underexplored. We focus on applying quantum computing to operations management problems in industry, and…

Quantum Physics · Physics 2023-01-13 Hansheng Jiang , Zuo-Jun Max Shen , Junyu Liu

A central goal in quantum computing is the development of quantum hardware and quantum algorithms in order to analyse challenging scientific and engineering problems. Research in quantum computation involves contributions from both physics…

The ability to extract relevant information is critical to learning. An ingenious approach as such is the information bottleneck, an optimisation problem whose solution corresponds to a faithful and memory-efficient representation of…

Quantum Physics · Physics 2023-03-08 Masahito Hayashi , Yuxiang Yang

A new approach to efficient quantum computation with probabilistic gates is proposed and analyzed in both a local and non-local setting. It combines heralded gates previously studied for atom or atom-like qubits with logical encoding from…

Quantum Physics · Physics 2017-04-19 Johannes Borregaard , Anders S. Sørensen , Ignacio Cirac , Mikhail D. Lukin

Arbitrary exponentially large unitaries cannot be implemented efficiently by quantum circuits. However, we show that quantum circuits can efficiently implement any unitary provided it has at most polynomially many nonzero entries in any row…

Quantum Physics · Physics 2013-05-29 Stephen P. Jordan , Pawel Wocjan

Quantum algorithms could efficiently solve certain classically intractable problems by exploiting quantum parallelism. To date, whether the quantum entanglement is useful or not for quantum computing is still a question of debate. Here, we…

Quantum Physics · Physics 2018-01-24 He-Liang Huang , Ashutosh K. Goswami , Wan-Su Bao , Prasanta K. Panigrahi
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