Quantum Chebyshev's Inequality and Applications

In this paper we provide new quantum algorithms with polynomial speed-up for a range of problems for which no such results were known, or we improve previous algorithms. First, we consider the approximation of the frequency moments $F_k$ of order $k \geq 3$ in the multi-pass streaming model with updates (turnstile model). We design a $P$-pass quantum streaming algorithm with memory $M$ satisfying a tradeoff of $P^2 M = \tilde{O}(n^{1-2/k})$, whereas the best classical algorithm requires $P M = \Theta(n^{1-2/k})$. Then, we study the problem of estimating the number $m$ of edges and the number $t$ of triangles given query access to an $n$-vertex graph. We describe optimal quantum algorithms that perform $\tilde{O}(\sqrt{n}/m^{1/4})$ and $\tilde{O}(\sqrt{n}/t^{1/6} + m^{3/4}/\sqrt{t})$ queries respectively. This is a quadratic speed-up compared to the classical complexity of these problems. For this purpose we develop a new quantum paradigm that we call Quantum Chebyshev's inequality. Namely we demonstrate that, in a certain model of quantum sampling, one can approximate with relative error the mean of any random variable with a number of quantum samples that is linear in the ratio of the square root of the variance to the mean. Classically the dependency is quadratic. Our algorithm subsumes a previous result of Montanaro [Mon15]. This new paradigm is based on a refinement of the Amplitude Estimation algorithm of Brassard et al. [BHMT02] and of previous quantum algorithms for the mean estimation problem. We show that this speed-up is optimal, and we identify another common model of quantum sampling where it cannot be obtained. For our applications, we also adapt the variable-time amplitude amplification technique of Ambainis [Amb10] into a variable-time amplitude estimation algorithm.Comment: 27 pages; v3: better presentation, lower bound in Theorem 4.3 is ne

Maximum predictive power and the superposition principle

In quantum physics the direct observables are probabilities of events. We ask how observed probabilities must be combined to achieve what we call maximum predictive power. According to this concept the accuracy of a prediction must only depend on the number of runs whose data serve as input for the prediction. We transform each probability to an associated variable whose uncertainty interval depends only on the amount of data and strictly decreases with it. We find that for a probability which is a function of two other probabilities maximum predictive power is achieved when linearly summing their associated variables and transforming back to a probability. This recovers the quantum mechanical superposition principle

Index of Unfairness

Objective. Objective scientific knowledge for many authors more valuable than true subjective belief is determined by research on primary data but a renewed analysis of already recorded or published data is common too. Ever since, an appropriate experimental or study design is an important and often a seriously underappreciated aspect of the informativeness and the scientific value of any (medical) study. The significance of study design for the reliability of the conclusions drawn and the ability to generalize the results from the sample investigated for the whole population cannot be underestimated. In contrast to an inappropriate statistical evaluation of a medical study, it is difficult to correct errors in study design after the study has been completed. Various mathematical aspects of study design are discussed in this article. Methods. In assessing the significance of a fair study design of a medical study, important measures of publication bias are introduced. Methods of data or publication bias analysis in different types of studies are illustrated through examples with fictive data. Formal mathematical requirements of a fair study design which can and should be fulfilled carefully with regard to the planning or evaluation of medical research are developed. Results. Various especially mathematical aspects of a fair study design are discussed in this article in detail. Depending on the particular question being asked, mathematical methods are developed which allow us to recognize data which are self-contradictory and to exclude these data from systematic literature reviews and meta-analyses. As a result, different individual studies can be summed up and evaluated with a higher degree of certainty. Conclusions. This article is intended to give the reader guidance in evaluating the design of studies in medical research even ex post which should enable the reader to categorize medical studies better and to assess their scientific quality more accurately

An adaptive, rate-optimal test of linearity for median regression models

This paper is concerned with testing the hypothesis that a conditional median function is linear against a nonparametric alternative with unknown smoothness. We develop a test that is uniformly consistent against alternatives whose distance from the linear model converges to zero at the fastest possible rate. The test accommodates conditional heteroskedasticity of unknown form. The numerical performance and usefulness of the test are illustrated by the results of Monte Carlo experiments and an empirical example

Kvantu automātu un meklēšanas algoritmu iespējas un ierobežojumi

Kvantu skaitļošana ir nozare, kas pēta uz kvantu mehānikas likumiem balstīto skaitļošanas modeļu īpašības. Disertācija ir veltīta kvantu skaitļošanas algoritmiskiem aspektiem. Piedāvāti rezultāti trijos virzienos: Kvantu galīgi automāti Analizēta stāvokļu efektivitāte kvantu vienvirziena galīgam automātam. Uzlabota labāka zināmā eksponenciālā atšķirība [AF98] starp kvantu un klasiskajiem galīgajiem automātiem. Grovera algoritma analīze Pētīta Grovera algoritma noturība pret kļūdām. Vispārināts [RS08] loģisko kļūdu modelis un piedāvāti vairāki jauni rezultāti. Kvantu klejošana Pētīta meklēšana 2D režģī izmantojot kvantu klejošanu. Paātrināts [AKR05] kvantu klejošanas meklēšanas algoritms. Atslēgas vārdi: Kvantu galīgi automāti, eksponenciālā atšķirība, Grovera algoritms, noturība pret kļūdām, kvantu klejošana LITERATŪRA [AF98] A. Ambainis, R. Freivalds. 1-way quantum finite automata: strengths, weaknesses and generalizations. Proceedings of the 39th IEEE Conference on Foundations of Computer Science, 332-341, 1998. arXiv:quant-ph/9802062v3 [AKR05] A. Ambainis, J. Kempe, A. Rivosh. Coins make quantum walks faster. Proceedings of SODA’05, 1099-1108, 2005. [RS08] O. Regev, L. Schiff. Impossibility of a Quantum Speed-up with a Faulty Oracle. Proceedings of ICALP’2008, Lecture Notes in Computer Science, 5125:773-781, 2008.Quantum computation is the eld that investigates properties of models of computation based on the laws of the quantum mechanics. The thesis is ded- icated to algorithmic aspects of quantum computation and provides results in three directions: Quantum nite automata We study space-eciency of one-way quantum nite automata. We improve best known exponential separation [AF98] between quantum and classical one-way nite automata. Analysis of Grover's algorithm We study fault-tolerance of Grover's algorithm. We generalize the model of logical faults by [RS08] and present several new results. Quantum walks We study search by quantum walks on two-dimensional grid. We im- prove (speed-up) quantum walk search algorithm by [AKR05]. Keywords: Quantum nite automata, exponential separation, Grover's al- gorithm, fault-tolerance, quantum walks BIBLIOGRAPHY [AF98] A. Ambainis, R. Freivalds. 1-way quantum nite automata: strengths, weaknesses and gen- eralizations. Proceedings of the 39th IEEE Conference on Foundations of Computer Science, 332-341, 1998. arXiv:quant-ph/9802062v3 [AKR05] A. Ambainis, J. Kempe, A. Rivosh. Coins make quantum walks faster. Proceedings of SODA'05, 1099-1108, 2005. [RS08] O. Regev, L. Schi. Impossibility of a Quantum Speed-up with a Faulty Oracle. Proceedings of ICALP'2008, Lecture Notes in Computer Science, 5125:773-781, 2008

Mott law as lower bound for a random walk in a random environment

We consider a random walk on the support of a stationary simple point process on \RR^d, $d\geq 2$ which satisfies a mixing condition w.r.t. the translations or has a strictly positive density uniformly on large enough cubes. Furthermore the point process is furnished with independent random bounded energy marks. The transition rates of the random walk decay exponentially in the jump distances and depend on the energies through a factor of the Boltzmann-type. This is an effective model for the phonon-induced hopping of electrons in disordered solids within the regime of strong Anderson localisation. We show that the rescaled random walk converges to a Brownian motion whose diffusion coefficient is bounded below by Mott's law for the variable range hopping conductivity at zero frequency. The proof of the lower bound involves estimates for the supercritical regime of an associated site percolation problem

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