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Quantum machine learning (QML) is a computational paradigm that seeks to apply quantum-mechanical resources to solve learning problems. As such, the goal of this framework is to leverage quantum processors to tackle optimization,…

Quantum Physics · Physics 2025-11-21 Su Yeon Chang , M. Cerezo

Machine learning is a fascinating and exciting field within computer science. Recently, this excitement has been transferred to the quantum information realm. Currently, all proposals for the quantum version of machine learning utilize the…

Quantum Physics · Physics 2017-02-28 Hoi-Kwan Lau , Raphael Pooser , George Siopsis , Christian Weedbrook

The higher than classical efficiency exhibited by some quantum algorithms is here ascribed to their non-mechanistic character, which becomes evident by joining the notions of entanglement and quantum measurement. Measurement analogically…

Quantum Physics · Physics 2007-05-23 Giuseppe Castagnoli , Dalida Monti

The main features of quantum computing are described in the framework of spin resonance methods. Stress is put on the fact that quantum computing is in itself nothing but a re-interpretation (fruitful indeed) of well-known concepts. The…

Quantum Physics · Physics 2009-10-31 Valerio Scarani

Polynomial--time constant--space quantum Turing machines (QTMs) and logarithmic--space probabilistic Turing machines (PTMs) recognize uncountably many languages with bounded error (Say and Yakary\i lmaz 2014, arXiv:1411.7647). In this…

Computational Complexity · Computer Science 2016-08-02 Maksims Dimitrijevs , Abuzer Yakaryılmaz

A proof of quantumness is a protocol through which a classical machine can test whether a purportedly quantum device, with comparable time and memory resources, is performing a computation that is impossible for classical computers.…

Computational Complexity · Computer Science 2026-04-21 A. C. Cem Say , M. Utkan Gezer

Quantum algorithms for tasks such as factorization, search, and simulation rely on control flow such as branching and iteration that depends on the value of data in superposition. High-level programming abstractions for control flow, such…

Programming Languages · Computer Science 2024-03-27 Charles Yuan , Agnes Villanyi , Michael Carbin

The Turing machine (TM) and the Church thesis have formalized the concept of computable number, this allowed to display non-computable numbers. This paper defines the concept of number "approachable" by a TM and shows that some (if not all)…

Computational Complexity · Computer Science 2010-03-03 Nicolas Brener

Herein we survey the main results concerning quantum automata and machines with classical control. These machines were originally proposed by Sernadas et al in [37], during the FCT QuantLog project. First, we focus on the expressivity of…

Quantum Physics · Physics 2017-09-06 Paulo Mateus , Daowen Qiu , Andre Souto

Quantum coherence characterizes the non-classical feature of a single party system with respect to a local basis. Based on a recently introduced resource framework, coherence can be regarded as a resource and be systematically manipulated…

Quantum Physics · Physics 2018-09-26 Yunchao Liu , Qi Zhao , Xiao Yuan

In this research, we present a quantum circuit design and implementation for a parallel universal linear bounded automata. This circuit is able to accelerate the inference of algorithmic structures in data for discovering causal generative…

Quantum Physics · Physics 2022-02-25 Aritra Sarkar , Zaid Al-Ars , Koen Bertels

Faster algorithms, novel cryptographic mechanisms, and alternative methods of communication become possible when the model underlying information and computation changes from a classical mechanical model to a quantum mechanical one. Quantum…

Quantum Physics · Physics 2009-12-29 Eleanor G. Rieffel

In this paper, the space complexity of nonuniform quantum computations is investigated. The model chosen for this are quantum branching programs, which provide a graphic description of sequential quantum algorithms. In the first part of the…

Quantum Physics · Physics 2007-05-23 M. Sauerhoff , D. Sieling

Machine learning algorithms learn a desired input-output relation from examples in order to interpret new inputs. This is important for tasks such as image and speech recognition or strategy optimisation, with growing applications in the IT…

Quantum Physics · Physics 2015-05-27 M. Schuld , I. Sinayskiy , F. Petruccione

Quantum computers have the potential to provide an advantage over classical computers in a number of areas. Numerous metrics to benchmark the performance of quantum computers, ranging from their individual hardware components to entire…

The origin of the uncertainty inherent in quantum measurements has been discussed since quantum theory's inception, but to date the source of the indeterminacy of measurements performed at an angle with respect to a quantum state's…

Quantum Physics · Physics 2024-02-27 Christoph Adami

Quantum computation and quantum information are of great current interest in computer science, mathematics, physical sciences and engineering. They will likely lead to a new wave of technological innovations in communication, computation…

Methodology · Statistics 2012-10-03 Yazhen Wang

A universal Turing machine is a powerful concept - a single device can compute any function that is computable. A universal spin model, similarly, is a class of physical systems whose low energy behavior simulates that of any spin system.…

Computational Complexity · Computer Science 2024-06-25 Tomáš Gonda , Gemma De les Coves

Scientists have demonstrated that quantum computing has presented novel approaches to address computational challenges, each varying in complexity. Adapting problem-solving strategies is crucial to harness the full potential of quantum…

Computational Complexity · Computer Science 2024-09-13 Arash Vaezi , Ali Movaghar , Mohammad Ghodsi , Seyed Mohammad Hussein Kazemi , Negin Bagheri Noghrehy , Seyed Mohsen Kazemi

Quantum computers are next-generation devices that hold promise to perform calculations beyond the reach of classical computers. A leading method towards achieving this goal is through quantum machine learning, especially quantum generative…

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