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Related papers: Interactive Proofs For Quantum Computations

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Quantum Inverse Problem (QIP) is the problem of estimating an unknown quantum system $\rho$ from a set of measurements, whereas the classical counterpart is the Inverse Problem of estimating a distribution from a set of observations. In…

Quantum Physics · Physics 2021-01-19 Ningping Cao , Jie Xie , Aonan Zhang , Shi-Yao Hou , Lijian Zhang , Bei Zeng

This paper gives the first formal treatment of a quantum analogue of multi-prover interactive proof systems. It is proved that the class of languages having quantum multi-prover interactive proof systems is necessarily contained in NEXP,…

Computational Complexity · Computer Science 2007-05-23 Hirotada Kobayashi , Keiji Matsumoto

We define a language CQP (Communicating Quantum Processes) for modelling systems which combine quantum and classical communication and computation. CQP combines the communication primitives of the pi-calculus with primitives for measurement…

Quantum Physics · Physics 2007-05-23 Simon Gay , Rajagopal Nagarajan

Quantum counting is the task of determining the dimension of the subspace of states that are accepted by a quantum verifier circuit. It is the quantum analog of counting the number of valid solutions to NP problems -- a problem well-studied…

Quantum Physics · Physics 2025-03-17 Mason L. Rhodes , Sam Slezak , Anirban Chowdhury , Yiğit Subaşı

We present a protocol that transforms any quantum multi-prover interactive proof into a nonlocal game in which questions consist of logarithmic number of bits and answers of constant number of bits. As a corollary, this proves that the…

Quantum Physics · Physics 2016-10-12 Zhengfeng Ji

Quantum information processing (QIP) offers the promise of being able to do things that we cannot do with conventional technology. Here we present a new route for distributed optical QIP, based on generalized quantum non-demolition…

Quantum Physics · Physics 2009-11-11 W. J. Munro , Kae Nemoto , T. P. Spiller

The use of advanced quantum neuron models for pattern recognition applications requires fault tolerance. Therefore, it is not yet possible to test such models on a large scale in currently available quantum processors. As an alternative, we…

Quantum Physics · Physics 2022-02-18 London A. Cavaletto , Luca Candelori , Alex Matos-Abiague

Quantum Information Processing, which is an exciting area of research at the intersection of physics and computer science, has great potential for influencing the future development of information processing systems. The building of…

Logic in Computer Science · Computer Science 2015-11-06 Jaap Boender , Florian Kammüller , Rajagopal Nagarajan

Quantum computers, besides offering substantial computational speedups, are also expected to provide the possibility of preserving the privacy of a computation. Here we show the first such experimental demonstration of blind quantum…

We consider two-party quantum protocols starting with a transmission of some random BB84 qubits followed by classical messages. We show a general "compiler" improving the security of such protocols: if the original protocol is secure…

Quantum Physics · Physics 2009-08-31 Ivan Damgaard , Serge Fehr , Carolin Lunemann , Louis Salvail , Christian Schaffner

This paper considers three variants of quantum interactive proof systems in which short (meaning logarithmic-length) messages are exchanged between the prover and verifier. The first variant is one in which the verifier sends a short…

Quantum Physics · Physics 2011-06-22 Salman Beigi , Peter W. Shor , John Watrous

Quantum computers promise to efficiently solve not only problems believed to be intractable for classical computers, but also problems for which verifying the solution is also considered intractable. This raises the question of how one can…

Quantum Physics · Physics 2018-07-10 Alexandru Gheorghiu , Theodoros Kapourniotis , Elham Kashefi

We consider the problem of testing and learning from data in the presence of resource constraints, such as limited memory or weak data access, which place limitations on the efficiency and feasibility of testing or learning. In particular,…

Quantum Physics · Physics 2025-07-22 Matthias C. Caro , Jens Eisert , Marcel Hinsche , Marios Ioannou , Alexander Nietner , Ryan Sweke

Quantum computation teaches us that quantum mechanics exhibits exponential complexity. We argue that the standard scientific paradigm of "predict and verify" cannot be applied to testing quantum mechanics in this limit of high complexity.…

Quantum Physics · Physics 2012-06-19 Dorit Aharonov , Umesh Vazirani

Quantum systems, in general, output data that cannot be simulated efficiently by a classical computer, and hence is useful for solving certain mathematical problems and simulating quantum many-body systems. This also implies, unfortunately,…

Quantum Physics · Physics 2017-10-04 Keisuke Fujii , Masahito Hayashi

Quantum computing promises to enhance machine learning and artificial intelligence. Different quantum algorithms have been proposed to improve a wide spectrum of machine learning tasks. Yet, recent theoretical works show that, similar to…

Accurately estimating observables on noisy quantum devices remains a central challenge for near-term quantum algorithms. While quantum error mitigation techniques can reduce noise-induced bias, they often rely on unverifiable assumptions…

In this paper, we introduce a new public quantum interactive proof system and the first quantum alternating Turing machine: qAM proof system and qATM, respectively. Both are obtained from their classical counterparts (Arthur-Merlin proof…

Computational Complexity · Computer Science 2012-05-25 Abuzer Yakaryilmaz

As research on building scalable quantum computers advances, it is important to be able to certify their correctness. Due to the exponential hardness of classically simulating quantum computation, straight-forward verification through…

Quantum Physics · Physics 2019-12-23 Iskren Vankov , Daniel Mills , Petros Wallden , Elham Kashefi

The term "machine learning" especially refers to algorithms that derive mappings, i.e. intput/output transforms, by using numerical data that provide information about considered transforms. These transforms appear in many problems, related…

Quantum Physics · Physics 2022-10-03 Yannick Deville , Alain Deville