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Quantum algorithms require less operations than classical algorithms. The exact reason of this has not been pinpointed until now. Our explanation is that quantum algorithms know in advance 50% of the solution of the problem they will find…

Quantum Physics · Physics 2015-05-13 Giuseppe Castagnoli

Demonstrating quantum advantage has been a pressing challenge in the field. Most claimed quantum speedups rely on a subroutine in which classical information can be accessed in a coherent quantum manner, which imposes a crucial constraint…

Quantum Physics · Physics 2025-11-04 Nhat A. Nghiem

Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning techniques to impressive results in regression, classification, data-generation and reinforcement learning tasks.…

Quantum information science explores the frontier of highly complex quantum states, the "entanglement frontier." This study is motivated by the observation (widely believed but unproven) that classical systems cannot simulate highly…

Quantum Physics · Physics 2012-11-13 John Preskill

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

Quantum computing promises to solve problems beyond the reach of classical computers, but today's quantum hardware is error-prone and much slower than classical hardware. Every quantum operation is costly, making it crucial to minimize…

Quantum Physics · Physics 2026-05-25 Lian Remme , Alexander Weinert , Andre Waschk , Lukas Burgholzer , Robert Wille

Recently developed quantum algorithms suggest that quantum computers can solve certain problems and perform certain tasks more efficiently than conventional computers. Among other reasons, this is due to the possibility of creating…

Quantum Physics · Physics 2007-05-23 Rolando D. Somma

Classical optimization algorithms in machine learning often take a long time to compute when applied to a multi-dimensional problem and require a huge amount of CPU and GPU resource. Quantum parallelism has a potential to speed up machine…

Quantum Physics · Physics 2019-11-21 Venkat R. Dasari , Mee Seong Im , Lubjana Beshaj

Quantum algorithms have the potential to provide exponential speedups over some of the best known classical algorithms. These speedups may enable quantum devices to solve currently intractable problems such as those in the fields of…

Quantum Physics · Physics 2018-12-13 Ciarán Ryan-Anderson

Machine Learning algorithms are extensively used in an increasing number of systems, applications, technologies, and products, both in industry and in society as a whole. They enable computing devices to learn from previous experience and…

Quantum Physics · Physics 2025-02-17 Lucas Lamata

Quantum computers offer a new paradigm of computing with the potential to vastly outperform any imagineable classical computer. This has caused a gold rush towards new quantum algorithms and hardware. In light of the growing expectations…

Quantum Physics · Physics 2023-07-04 Torsten Hoefler , Thomas Haener , Matthias Troyer

Quantum computing promises the ability to compute properties of quantum systems exponentially faster than classical computers. Quantum advantage is achieved when a practical problem is solved more efficiently on a quantum computer than on a…

Quantum Physics · Physics 2025-12-03 William A. Simon , Peter J. Love

We consider classical and quantum algorithms which have a duality property: roughly, either the algorithm provides some nontrivial improvement over random or there exist many solutions which are significantly worse than random. This enables…

Quantum Physics · Physics 2019-11-13 M. B. Hastings

Quantum computers may achieve speedups over their classical counterparts for solving linear algebra problems. However, in some cases -- such as for low-rank matrices -- dequantized algorithms demonstrate that there cannot be an exponential…

Quantum Physics · Physics 2023-05-16 Ashley Montanaro , Changpeng Shao

An enduring challenge in computer science is reducing the runtime required to solve computational problems. Quantum computing has attracted significant attention due to its potential to deliver asymptotically faster solutions to certain…

Quantum Physics · Physics 2025-03-25 Mischa P. Woods

Quantum computers can execute algorithms that sometimes dramatically outperform classical computation. Undoubtedly the best-known example of this is Shor's discovery of an efficient quantum algorithm for factoring integers, whereas the same…

Quantum Physics · Physics 2017-08-23 Wim van Dam , Yoshitaka Sasaki

Quantum computing, leveraging quantum phenomena like superposition and entanglement, is emerging as a transformative force in computing technology, promising unparalleled computational speed and efficiency crucial for engineering…

Quantum Physics · Physics 2024-08-30 Osama Muhammad Raisuddin , Suvranu De

Quantum computing promises to provide the next step up in computational power for diverse application areas. In this review, we examine the science behind the quantum hype, and the breakthroughs required to achieve true quantum advantage in…

Quantum Physics · Physics 2025-09-26 R. Au-Yeung , B. Camino , O. Rathore , V. Kendon

Quantum computing promises transformational gains for solving some problems, but little to none for others. For anyone hoping to use quantum computers now or in the future, it is important to know which problems will benefit. In this paper,…

Data Structures and Algorithms · Computer Science 2023-10-25 Sukwoong Choi , William S. Moses , Neil Thompson

While recent progress in quantum hardware open the door for significant speedup in certain key areas (cryptography, biology, chemistry, optimization, machine learning, etc), quantum algorithms are still hard to implement right, and the…

Programming Languages · Computer Science 2022-04-11 Christophe Chareton , Sébastien Bardin , Dongho Lee , Benoît Valiron , Renaud Vilmart , Zhaowei Xu