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Related papers: Lost in Algorithms

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Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Since quantum systems produce counter-intuitive patterns believed not to be efficiently…

Quantum Physics · Physics 2018-05-14 Jacob Biamonte , Peter Wittek , Nicola Pancotti , Patrick Rebentrost , Nathan Wiebe , Seth Lloyd

In recent years, deep learning has had a profound impact on machine learning and artificial intelligence. At the same time, algorithms for quantum computers have been shown to efficiently solve some problems that are intractable on…

Quantum Physics · Physics 2015-05-25 Nathan Wiebe , Ashish Kapoor , Krysta M. Svore

Quantum computing is the process of performing calculations using quantum mechanics. This field studies the quantum behavior of certain subatomic particles for subsequent use in performing calculations, as well as for large-scale…

Quantum Physics · Physics 2023-12-07 David Peral García , Juan Cruz-Benito , Francisco José García-Peñalvo

The driving force in the pursuit for quantum computation is the exciting possibility that quantum algorithms can be more efficient than their classical analogues. Research on the subject has unraveled several aspects of how that can happen.…

Quantum Physics · Physics 2011-02-11 Apoorva Patel

In the effort to develop useful quantum computers simulating quantum machines with conventional computing resources is a key capability. Such simulations will always face limits preventing the emulation of quantum computers of substantial…

Quantum Physics · Physics 2023-02-20 Xiaosi Xu , Simon Benjamin , Jinzhao Sun , Xiao Yuan , Pan Zhang

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

Genetic algorithms are heuristic optimization techniques inspired by Darwinian evolution. Quantum computation is a new computational paradigm which exploits quantum resources to speed up information processing tasks. Therefore, it is…

Quantum Physics · Physics 2023-02-20 Rubén Ibarrondo , Giancarlo Gatti , Mikel Sanz

Quantum computing exhibits the unique capability to natively and efficiently encode various natural phenomena, promising theoretical speedups of several orders of magnitude. However, not all computational tasks can be efficiently executed…

Software Engineering · Computer Science 2025-04-28 Vincenzo De Maio , Ivona Brandic , Ewa Deelman , Jürgen Cito

In recent years, the emergence of the first quantum computers at a time when AI is undergoing a fruitful era has led many AI researchers to be tempted into adapting their algorithms to run on a quantum computer. However, in many cases the…

Neural and Evolutionary Computing · Computer Science 2024-01-18 Rafael Lahoz-Beltra

In the rapidly growing area of quantum information, the Deutsch algorithm is ubiquitous and, in most cases, the first one to be introduced to any student of this relatively new field of research. The reason for this historical relevance…

Quantum Physics · Physics 2019-03-18 Yohan Vianna , Mariana R. Barros , Malena Hor-Meyll

Quantum computing provides a new way for approaching problem solving, enabling efficient solutions for problems that are hard on classical computers. It is based on leveraging how quantum particles behave. With researchers around the world…

Quantum Physics · Physics 2021-09-29 Ahmed Shokry , Moustafa Youssef

Quantum computers take advantage of interfering quantum alternatives in order to handle problems that might be too time consuming with algorithms based on classical logic. Developing quantum computers requires new ways of thinking beyond…

Quantum Physics · Physics 2014-09-10 W. C. Parke

As we enter the post-Moore era, we experience the rise of various non-von-Neumann-architectures to address the increasing computational demand for modern applications, with quantum computing being among the most prominent and promising…

Quantum Computing (QC) refers to an emerging paradigm that inherits and builds with the concepts and phenomena of Quantum Mechanic (QM) with the significant potential to unlock a remarkable opportunity to solve complex and computationally…

Quantum computers promise to surpass the most powerful classical supercomputers when it comes to solving many critically important practical problems, such as pharmaceutical and fertilizer design, supply chain and traffic optimization, or…

Computation · Statistics 2022-04-05 Anna Lopatnikova , Minh-Ngoc Tran , Scott A. Sisson

Algorithmic robustness refers to the sustained performance of a computational system in the face of change in the nature of the environment in which that system operates or in the task that the system is meant to perform. Below, we motivate…

Artificial Intelligence · Computer Science 2023-11-14 David Jensen , Brian LaMacchia , Ufuk Topcu , Pamela Wisniewski

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 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

In the past decade quantum algorithms have been found which outperform the best classical solutions known for certain classical problems as well as the best classical methods known for simulation of certain quantum systems. This suggests…

Quantum Physics · Physics 2007-05-23 David A. Meyer

Neural algorithmic reasoning aims to capture computations with neural networks by training models to imitate the execution of classical algorithms. While common architectures are expressive enough to contain the correct model in the weight…

Machine Learning · Computer Science 2025-08-14 Gleb Rodionov , Liudmila Prokhorenkova