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It is a widely believed, though unproven, conjecture that the capability of postselection increases the language recognition power of both probabilistic and quantum polynomial-time computers. It is also unknown whether polynomial-time…

Computational Complexity · Computer Science 2014-04-11 Abuzer Yakaryilmaz , A. C. Cem Say

Quantum computing is a new model of computation, based on quantum physics. Quantum computers can be exponentially faster than conventional computers for problems such as factoring. Besides full-scale quantum computers, more restricted…

Formal Languages and Automata Theory · Computer Science 2018-07-05 Andris Ambainis , Abuzer Yakaryılmaz

The question of whether quantum real-time one-counter automata (rtQ1CAs) can outperform their probabilistic counterparts has been open for more than a decade. We provide an affirmative answer to this question, by demonstrating a…

Computational Complexity · Computer Science 2014-01-29 A. C. Cem Say , Abuzer Yakaryilmaz

In this paper, we investigate the computational and verification power of bounded-error postselecting realtime probabilistic finite state automata (PostPFAs). We show that PostPFAs using rational-valued transitions can do different variants…

Computational Complexity · Computer Science 2018-07-16 Maksims Dimitrijevs , Abuzer Yakaryılmaz

We realize constant-space quantum computation by measure-many two-way quantum finite automata and evaluate their language recognition power by analyzing patterns of their exotic behaviors and by exploring their structural properties. In…

Formal Languages and Automata Theory · Computer Science 2016-06-29 Tomoyuki Yamakami

This paper proposed a quantum analogue of classical queue automata by using the definition of the quantum Turing machine and quantum finite-state automata. However, quantum automata equipped with storage medium of a stack has been…

Quantum Physics · Physics 2018-10-30 Amandeep Singh Bhatia , Ajay Kumar

In this thesis, we introduce a new quantum Turing machine (QTM) model that supports general quantum operators, together with its pushdown, counter, and finite automaton variants, and examine the computational power of classical and quantum…

Computational Complexity · Computer Science 2011-02-03 Abuzer Yakaryilmaz

Quantum computing is concerned with computer technology based on the principles of quantum mechanics, with operations performed at the quantum level. Quantum computational models make it possible to analyze the resources required for…

Formal Languages and Automata Theory · Computer Science 2019-01-24 Amandeep Singh Bhatia , Ajay Kumar

Some of the most interesting and important results concerning quantum finite automata are those showing that they can recognize certain languages with (much) less resources than corresponding classical finite automata…

Formal Languages and Automata Theory · Computer Science 2019-02-20 Shenggen Zheng , Jozef Gruska , Daowen Qiu

The main purpose of this paper is to show that we can exploit the difference ($l_1$-norm and $l_2$-norm) in the probability calculation between quantum and probabilistic computations to claim the difference in their space efficiencies. It…

Quantum Physics · Physics 2007-05-23 Masami Amano , Kazuo Iwama , Rudy Raymond

Let $f$ denote length preserving function on words. A classical algorithm can be considered as $T$ iterated applications of black box representing $f$, beginning with input word $x$ of length $n$. It is proved that if $T=O(2^{n/(7+e)}), e…

Quantum Physics · Physics 2007-05-23 Yuri Ozhigov

Automata with monitor counters, where the transitions do not depend on counter values, and nested weighted automata are two expressive automata-theoretic frameworks for quantitative properties. For a well-studied and wide class of…

Formal Languages and Automata Theory · Computer Science 2023-06-22 Krishnendu Chatterjee , Thomas A. Henzinger , Jan Otop

This paper proposes a quantum-classical algorithm to evaluate and select classical artificial neural networks architectures. The proposed algorithm is based on a probabilistic quantum memory and the possibility to train artificial neural…

Probabilistic automata are an extension of nondeterministic finite automata in which transitions are annotated with probabilities. Despite its simplicity, this model is very expressive and many of the associated algorithmic questions are…

Formal Languages and Automata Theory · Computer Science 2022-05-20 Nathanaël Fijalkow , Cristian Riveros , James Worrell

We examine the characteristic features of reversible and quantum computations in the presence of supplementary external information, known as advice. In particular, we present a simple, algebraic characterization of languages recognized by…

Quantum Physics · Physics 2015-08-25 Tomoyuki Yamakami

We introduce a quantum-like classical computational model, called affine computation, as a generalization of probabilistic computation. After giving the basics of affine computation, we define affine finite automata (AfA) and compare it…

Formal Languages and Automata Theory · Computer Science 2016-06-07 Alejandro Díaz-Caro , Abuzer Yakaryılmaz

Standard quantum theory admits naturally statistical ensembles that are both pre-selected and post-selected, i.e., they involve both an initial and a final state. We argue that there is no compelling physical reason to preclude a…

General Relativity and Quantum Cosmology · Physics 2024-12-17 Charis Anastopoulos

To study relationship between quantum finite automata and probabilistic finite automata, we introduce a notion of probabilistic reversible automata (PRA, or doubly stochastic automata). We find that there is a strong relationship between…

Computational Complexity · Computer Science 2011-06-14 Marats Golovkins , Maksim Kravtsev

This paper furthers existing evidence that quantum computers are capable of computations beyond classical computers. Specifically, we strengthen the collapse of the polynomial hierarchy to the second level if: (i) Quantum computers with…

Quantum Physics · Physics 2024-10-29 Simon C. Marshall , Scott Aaronson , Vedran Dunjko

Generative modeling using samples drawn from the probability distribution constitutes a powerful approach for unsupervised machine learning. Quantum mechanical systems can produce probability distributions that exhibit quantum correlations…

Quantum Physics · Physics 2022-10-07 Xun Gao , Eric R. Anschuetz , Sheng-Tao Wang , J. Ignacio Cirac , Mikhail D. Lukin
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