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In this article we give several new results on the complexity of algorithms that learn Boolean functions from quantum queries and quantum examples. Hunziker et al. conjectured that for any class C of Boolean functions, the number of quantum…

Quantum Physics · Physics 2007-05-23 Alp Atici , Rocco A. Servedio

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

Hybrid quantum-classical algorithms hold great promise for solving quantum control problems on near-term quantum computers. In this work, we employ the hybrid framework that integrates digital quantum simulation with classical optimization…

Quantum Physics · Physics 2025-07-01 Tangyou Huang , Jing-Jun Zhu , Zhong-Yi Ni

One of the most basic computational problems is the task of finding a desired item in an ordered list of N items. While the best classical algorithm for this problem uses log_2 N queries to the list, a quantum computer can solve the problem…

Quantum Physics · Physics 2007-05-23 Andrew M. Childs , Andrew J. Landahl , Pablo A. Parrilo

A leading approach to algorithm design aims to minimize the number of operations in an algorithm's compilation. One intuitively expects that reducing the number of operations may decrease the chance of errors. This paradigm is particularly…

In previous works, we showed that an optimal quantum algorithm can always be seen as a sum over classical histories in each of which the problem solver knows in advance one of the possible halves of the solution she will read in the future…

Quantum Physics · Physics 2017-06-28 Giuseppe Castagnoli

Combining quantum computers with classical compute power has become a standard means for developing algorithms that are eventually supposed to beat any purely classical alternatives. While in-principle advantages for solution quality or…

Quantum Physics · Physics 2026-01-23 Simon Thelen , Wolfgang Mauerer

Quantum computing promises to solve difficult optimization problems in chemistry, physics and mathematics more efficiently than classical computers, but requires fault-tolerant quantum computers with millions of qubits. To overcome errors…

Databases · Computer Science 2021-07-23 Tobias Fankhauser , Marc E. Solèr , Rudolf M. Füchslin , Kurt Stockinger

We consider the problem of finding one or more desired items out of an unsorted database. Patel has shown that if the database permits quantum queries, then mere digitization is sufficient for efficient search for one desired item. The…

Databases · Computer Science 2009-09-30 Heping Hu , Yingyu Zhang , Zhengding Lu

Quantum resources, such as entanglement or quantum communication, offer significant communication advantages in information processing. We develop an operational framework for realizing these communication advantages in resource-constrained…

Quantum Physics · Physics 2026-04-16 Brian Doolittle , Felix Leditzky , Eric Chitambar

Outsourcing tasks to previously unknown parties is becoming more common. One specific such problem involves matching a set of workers to a set of tasks. Even if the latter have precise requirements, the quality of individual workers is…

Machine Learning · Computer Science 2017-08-01 Philip Ekman , Sebastian Bellevik , Christos Dimitrakakis , Aristide Tossou

Machine learning employs dynamical algorithms that mimic the human capacity to learn, where the reinforcement learning ones are among the most similar to humans in this respect. On the other hand, adaptability is an essential aspect to…

Quantum Physics · Physics 2018-10-15 F. Albarrán-Arriagada , J. C. Retamal , E. Solano , L. Lamata

We propose a quantum algorithm for closest pattern matching which allows us to search for as many distinct patterns as we wish in a given string (database), requiring a query function per symbol of the pattern alphabet. This represents a…

Quantum Physics · Physics 2007-05-23 P. Mateus , Y. Omar

One of the primary goals of information theory is to provide limits on the amount of information it is possible to send through various types of communication channels, and to understand the encoding methods that will allow one to achieve…

Quantum Physics · Physics 2014-08-07 Michael R. Beran , Scott M. Cohen

Quantum computing is an emerging field on the multidisciplinary interface between physics, engineering, and computer science with the potential to make a large impact on computational intelligence (CI). The aim of this paper is to introduce…

Quantum communication can enhance internet technology by enabling novel applications that are provably impossible classically. The successful execution of such applications relies on the generation of quantum entanglement between different…

Quantum Physics · Physics 2021-11-29 Matthew Skrzypczyk , Stephanie Wehner

Quantum machine learning seeks a computational advantage in data processing by evaluating functions of quantum states, such as their similarity, that can be classically intractable to compute. For quantum advantage to be possible, however,…

An open quantum system leaks information into its environment. In some circumstances it is possible for an observer, say Alice, to recover that information, as a classical measurement record, in a variety of different ways, using different…

Quantum Physics · Physics 2025-11-18 Areeya Chantasri , Kiarn T. Laverick , Howard M. Wiseman

Quantum search algorithms offer a remarkable advantage of quadratic reduction in query complexity using quantum superposition principle. However, how an actual architecture may access and handle the database in a quantum superposed state…

Quantum Physics · Physics 2023-11-06 Jung Jun Park , Kyunghyun Baek , M. S. Kim , Hyunchul Nha , Jaewan Kim , Jeongho Bang

Due to statistical lower bounds on the learnability of many function classes under privacy constraints, there has been recent interest in leveraging public data to improve the performance of private learning algorithms. In this model,…

Machine Learning · Statistics 2024-02-16 Adam Block , Mark Bun , Rathin Desai , Abhishek Shetty , Steven Wu