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We explore in the framework of Quantum Computation the notion of computability, which holds a central position in Mathematics and Theoretical Computer Science. A quantum algorithm that exploits the quantum adiabatic processes is considered…

Quantum Physics · Physics 2009-11-07 Tien D. Kieu

The goal of randomness extraction is to distill (almost) perfect randomness from a weak source of randomness. When the source yields a classical string X, many extractor constructions are known. Yet, when considering a physical randomness…

Quantum Physics · Physics 2014-05-14 Mario Berta , Omar Fawzi , Stephanie Wehner

We begin to study classical dimension theory from the computable analysis (TTE) point of view. For computable metric spaces, several effectivisations of zero-dimensionality are shown to be equivalent. The part of this characterisation that…

Logic · Mathematics 2015-07-01 Robert Kenny

We show that in the setting of fair-coin measure on the power set of the natural numbers, each sufficiently random set has an infinite subset that computes no random set. That is, there is an almost sure event $\mathcal A$ such that if…

Logic · Mathematics 2014-08-12 Bjørn Kjos-Hanssen

Measurements of quantum systems can be used to generate classical data that is truly unpredictable for every observer. However, this true randomness needs to be discriminated from randomness due to ignorance or lack of control of the…

Quantum Physics · Physics 2017-06-14 Felix Bischof , Hermann Kampermann , Dagmar Bruß

We introduce the notion of a reproducible algorithm in the context of learning. A reproducible learning algorithm is resilient to variations in its samples -- with high probability, it returns the exact same output when run on two samples…

Machine Learning · Computer Science 2023-04-17 Russell Impagliazzo , Rex Lei , Toniann Pitassi , Jessica Sorrell

In the classical RAM, we have the following useful property. If we have an algorithm that uses $M$ memory cells throughout its execution, and in addition is sparse, in the sense that, at any point in time, only $m$ out of $M$ cells will be…

Quantum Physics · Physics 2022-12-22 Harry Buhrman , Bruno Loff , Subhasree Patro , Florian Speelman

Current discrete randomness and information conservation inequalities are over total recursive functions, i.e. restricted to deterministic processing. This restriction implies that an algorithm can break algorithmic randomness conservation…

Computational Complexity · Computer Science 2013-10-15 Samuel Epstein

What is computable with limited resources? How can we verify the correctness of computations? How to measure computational power with precision? Despite the immense scientific and engineering progress in computing, we still have only…

Other Computer Science · Computer Science 2016-10-20 Attila Egri-Nagy

Generic computability has been studied in group theory and we now study it in the context of classical computability theory. A set A of natural numbers is generically computable if there is a partial computable function f whose domain has…

Group Theory · Mathematics 2014-02-26 Carl G. Jockusch , Paul E. Schupp

In this work we investigate how to quantify the coherence of quantum measurements. First, we establish a resource theoretical framework to address the coherence of measurement and show that any statistical distance can be adopted to define…

Quantum Physics · Physics 2020-08-11 Kyunghyun Baek , Adel Sohbi , Jaehak Lee , Jaewan Kim , Hyunchul Nha

Quantum mechanics predicts the existence of intrinsically random processes. Contrary to classical randomness, this lack of predictability can not be attributed to ignorance or lack of control. Here we find the optimal method to quantify the…

Quantum Physics · Physics 2015-12-07 Elsa Passaro , Daniel Cavalcanti , Paul Skrzypczyk , Antonio Acín

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

We study the optimization of any quantum process by minimizing the "randomness" in the measurement result at the output of that quantum process. We conceptualize and propose a measure of such randomness and inquire whether an optimization…

Quantum Physics · Physics 2021-03-30 Sreetama Das , Asutosh Kumar , Aditi Sen De , Ujjwal Sen

The notion of probability plays an important role in almost all areas of science and technology. In modern mathematics, however, probability theory means nothing other than measure theory, and the operational characterization of the notion…

Probability · Mathematics 2019-09-09 Kohtaro Tadaki

We introduce, for any bipartite Bell scenario, a measure that quantifies both the amount of nonlocality and the efficiency in device-independent quantum key distribution of a set of measurement outcomes probabilities. It is a proper measure…

Quantum Physics · Physics 2020-11-30 S. Camalet

Decomposable models and Bayesian networks can be defined as sequences of oligo-dimensional probability measures connected with operators of composition. The preliminary results suggest that the probabilistic models allowing for effective…

Artificial Intelligence · Computer Science 2013-02-08 Radim Jirousek

Quantum coherence is the key resource for quantum technology, with applications in quantum optics, information processing, metrology and cryptography. Yet, there is no universally efficient method for quantifying coherence either in…

Quantum Physics · Physics 2014-10-24 Davide Girolami

We show that for tripartite quantum pure states of qubits, all the kinds of entanglement in terms of SLOCC classification are experimentally measurable by simple projective measurements, provided that four copies of the composite quantum…

Quantum Physics · Physics 2009-11-13 Chang-shui Yu , He-shan Song

Previous studies have used a specific success metric within an algorithmic search framework to prove machine learning impossibility results. However, this specific success metric prevents us from applying these results on other forms of…

Machine Learning · Statistics 2020-01-06 Tyler Sam , Jake Williams , Abel Tadesse , Huey Sun , George Montanez
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