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Very recently, Monz, et al. [arXiv:1507.08852] have reported the demonstration of factoring 15 using a scalable Shor algorithm with an ion-trap quantum computer. In this note, we remark that the report is somewhat misleading because there…

Quantum Physics · Physics 2016-11-02 Zhengjun Cao , Lihua Liu

We give new bounds on the circuit complexity of the quantum Fourier transform (QFT). We give an upper bound of O(log n + log log (1/epsilon)) on the circuit depth for computing an approximation of the QFT with respect to the modulus 2^n…

Quantum Physics · Physics 2007-05-23 Richard Cleve , John Watrous

The purpose of this note was to give a proof that Shor's algorithm for period search is polynomial using only the standard $2^{n}$ quantum Fourier thansform and some simple trigonometry. There is an error that was pointed out to the author…

Quantum Physics · Physics 2012-08-20 Nolan R. Wallach

Considering its relevance in the field of cryptography, integer factorization is a prominent application where Quantum computers are expected to have a substantial impact. Thanks to Shor's algorithm this peculiar problem can be solved in…

The Metropolis process (MP) and Simulated Annealing (SA) are stochastic local search heuristics that are often used in solving combinatorial optimization problems. Despite significant interest, there are very few theoretical results…

Data Structures and Algorithms · Computer Science 2023-12-22 Zongchen Chen , Dan Mikulincer , Daniel Reichman , Alexander S. Wein

Conditions on sure-success decidability of weights of Boolean functions are presented for a given number of generalized Grover iterations. It is shown that the decidability problem reduces to a system of algebraic equations of a single…

Quantum Physics · Physics 2013-01-21 K. Uyanik , S. Turgut

Let g : $\Omega$ = [0, 1] d $\rightarrow$ R denote a Lipschitz function that can be evaluated at each point, but at the price of a heavy computational time. Let X stand for a random variable with values in $\Omega$ such that one is able to…

Probability · Mathematics 2021-07-29 Lucie Bernard , Albert Cohen , Arnaud Guyader , Florent Malrieu

We establish an exact asymptotic formula for the square variation of certain partial sum processes. Let $\{X_{i}\}$ be a sequence of independent, identically distributed mean zero random variables with finite variance $\sigma$ and…

Probability · Mathematics 2011-06-07 Allison Lewko , Mark Lewko

Withdrawn by the author due to irreparable errors. We present a quantum algorithm that in the black-box model performs a search in an ordered list of N elements. Using 3/4 log N + O(1) queries, it achieves a success probability of at least…

Quantum Physics · Physics 2007-05-23 Hein Roehrig

The results of the study provide guidelines for the development and applications of algorithms. When the number of steps for calculating an assumption tends to infinity, probability theory can be applied to predict whether the assumption…

General Mathematics · Mathematics 2026-01-12 Yasuo Nishii

We present a quasi-Newton method for unconstrained stochastic optimization. Most existing literature on this topic assumes a setting of stochastic optimization in which a finite sum of component functions is a reasonable approximation of an…

Optimization and Control · Mathematics 2024-09-04 Matt Menickelly , Stefan M. Wild , Miaolan Xie

We study the distribution of the order of a random permutation of $[n]$ through the lens of R\'enyi entropy. In particular, we obtain an asymptotic for the R\'enyi $q$-entropy of the order in the full range $1 \leq q \leq \infty$. For $q >…

Combinatorics · Mathematics 2026-05-15 Adrian Beker

Shor's algorithm contains a classical post-processing part for which we aim to create an efficient, understandable method aside from continued fractions. Let r be an unknown positive integer. Assume that with some constant probability we…

Quantum Physics · Physics 2013-01-31 Allison Koenecke , Pawel Wocjan

We show that several quantum circuit families can be simulated efficiently classically if it is promised that their output distribution is approximately sparse i.e. the distribution is close to one where only a polynomially small, a priori…

Quantum Physics · Physics 2013-10-28 Martin Schwarz , Maarten Van den Nest

Let $X_1,\ldots,X_n$ be an i.i.d. sample from symmetric stable distribution with stability parameter $\alpha$ and scale parameter $\gamma$. Let $\varphi_n$ be the empirical characteristic function. We prove an uniform large deviation…

Statistics Theory · Mathematics 2020-08-12 Annika Krutto , Jüri Lember

We obtain asymptotic expansions for local probabilities of partial sums for uniformly bounded independent but not necessarily identically distributed integer-valued random variables. The expansions involve products of polynomials and…

Probability · Mathematics 2020-12-02 Dmitry Dolgopyat , Yeor Hafouta

The objective of this paper concerns at first the motivation and the method of Shor's algorithm including an excursion into quantum mechanics and quantum computing introducing an algorithmic description of the method. The corner stone of…

Discrete Mathematics · Computer Science 2022-06-03 Gérard Fleury , Philippe Lacomme

We consider a conservative ergodic measure-preserving transformation $T$ of the measure space $(X,\mathcal{B},\mu)$ with $\mu$ a $\sigma$-finite measure and $\mu(X)=\infty$. Given an observable $g:X\to \mathbb{R}$, it is well known from…

Dynamical Systems · Mathematics 2025-08-27 Claudio Bonanno , Tanja I. Schindler

Quantum computing represents a significant advancement in computational capabilities. Of particular concern is its impact on asymmetric cryptography through, notably, Shor's algorithm and the more recently developed Regev's algorithm for…

Quantum Physics · Physics 2025-07-11 Przemysław Pawlitko , Natalia Moćko , Marcin Niemiec , Piotr Chołda

We study the problem of optimizing a function under a \emph{budgeted number of evaluations}. We only assume that the function is \emph{locally} smooth around one of its global optima. The difficulty of optimization is measured in terms of…

Machine Learning · Computer Science 2019-02-26 Peter L. Bartlett , Victor Gabillon , Michal Valko
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