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Quantum correlations provide dramatic advantage over the corresponding classical resources in several communication tasks. However a broad class of probabilistic theories exists that attributes greater success than quantum theory in many of…

Quantum Physics · Physics 2020-11-09 Sutapa Saha , Some Sankar Bhattacharya , Tamal Guha , Saronath Halder , Manik Banik

With a combination of the quantum repeater and the cluster state approaches, we show that efficient quantum computation can be constructed even if all the entangling quantum gates only succeed with an arbitrarily small probability $p$. The…

Quantum Physics · Physics 2009-11-11 L. -M. Duan , R. Raussendorf

Consider a fixed universe of $N=2^n$ elements and the uniform distribution over elements of some subset of size $K$. Given samples from this distribution, the task of complement sampling is to provide a sample from the complementary subset.…

Quantum Physics · Physics 2026-02-02 Marcello Benedetti , Harry Buhrman , Jordi Weggemans

The Universal Turing Machine (TM) is a model for VonNeumann computers --- general-purpose computers. A human brain can inside-skull-automatically learn a universal TM so that he acts as a general-purpose computer and writes a computer…

Artificial Intelligence · Computer Science 2019-03-28 Juyang Weng

An oblivious computation is one that is free of direct and indirect information leaks, e.g., due to observable differences in timing and memory access patterns. This paper presents Lambda Obliv, a core language whose type system enforces…

Programming Languages · Computer Science 2019-11-14 David Darais , Ian Sweet , Chang Liu , Michael Hicks

Quantum algorithms that can speed up certain tasks, such as factorisation and unstructured search, have driven a decades-long development of quantum computers and quantum technologies. Yet, outside specialized applications, quantum…

Quantum Physics · Physics 2019-07-05 Carlos Perez-Delgado , Sai Vinjanampathy

We introduce a variant of PCPs, that we refer to as rectangular PCPs, wherein proofs are thought of as square matrices, and the random coins used by the verifier can be partitioned into two disjoint sets, one determining the row of each…

Computational Complexity · Computer Science 2022-11-24 Amey Bhangale , Prahladh Harsha , Orr Paradise , Avishay Tal

Quantum computers hold the promise to solve certain computational task much more efficiently than classical computers. We review the recent experimental advancements towards a quantum computer with trapped ions. In particular, various…

Quantum Physics · Physics 2008-11-20 H. Haeffner , C. F. Roos , R. Blatt

We introduce the notion of universal memcomputing machines (UMMs): a class of brain-inspired general-purpose computing machines based on systems with memory, whereby processing and storing of information occur on the same physical location.…

Neural and Evolutionary Computing · Computer Science 2015-12-17 Fabio L. Traversa , Massimiliano Di Ventra

Quantum computers are unnecessary for exponentially-efficient computation or simulation if the Extended Church-Turing thesis---a foundational tenet of computer science---is correct. The thesis would be directly contradicted by a physical…

I assess the potential of quantum computation. Broad and important applications must be found to justify construction of a quantum computer; I review some of the known quantum algorithms and consider the prospects for finding new ones.…

Quantum Physics · Physics 2009-10-30 John Preskill

We consider computations of a Turing machine subjected to noise. In every step, the action (the new state and the new content of the observed cell, the direction of the head movement) can differ from that prescribed by the transition…

Computational Complexity · Computer Science 2021-12-07 Ilir Çapuni , Peter Gács

We study Turing machines that are allowed absolutely no space overhead. The only work space the machines have, beyond the fixed amount of memory implicit in their finite-state control, is that which they can create by cannibalizing the…

Computational Complexity · Computer Science 2007-05-23 Lane A. Hemaspaandra , Proshanto Mukherji , Till Tantau

We propose a measure based upon the fundamental theoretical concept in algorithmic information theory that provides a natural approach to the problem of evaluating $n$-dimensional complexity by using an $n$-dimensional deterministic Turing…

Computational Complexity · Computer Science 2015-08-27 Hector Zenil , Fernando Soler-Toscano , Jean-Paul Delahaye , Nicolas Gauvrit

Cumulative memory -- the sum of space used per step over the duration of a computation -- is a fine-grained measure of time-space complexity that was introduced to analyze cryptographic applications like password hashing. It is a more…

Computational Complexity · Computer Science 2023-07-06 Paul Beame , Niels Kornerup

The Church-Turing thesis states that any sufficiently powerful computational model which captures the notion of algorithm is computationally equivalent to the Turing machine. This equivalence usually holds both at a computability level and…

Computational Complexity · Computer Science 2017-01-18 Amaury Pouly , Olivier Bournez , Daniel S. Graça

Variational quantum algorithms are proposed to solve relevant computational problems on near term quantum devices. Popular versions are variational quantum eigensolvers and quantum ap- proximate optimization algorithms that solve ground…

Quantum Physics · Physics 2022-04-15 Lennart Bittel , Martin Kliesch

We observe that fault-tolerant quantum computers have an optimal advantage over classical computers in approximating solutions to many NP optimization problems. This observation however gives nothing in practice.

Quantum Physics · Physics 2022-12-27 Mario Szegedy

Quantum random sampling is the leading proposal for demonstrating a computational advantage of quantum computers over classical computers. Recently, first large-scale implementations of quantum random sampling have arguably surpassed the…

Quantum Physics · Physics 2023-07-21 Dominik Hangleiter , Jens Eisert

Tsetlin Machines (TMs) have emerged as a compelling alternative to conventional deep learning methods, offering notable advantages such as smaller memory footprint, faster inference, fault-tolerant properties, and interpretability. Although…

Machine Learning · Computer Science 2024-11-14 K. Darshana Abeyrathna , Sara El Mekkaoui , Andreas Hafver , Christian Agrell