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How can we remove some interactions in a constraint satisfaction problem (CSP) such that it still remains satisfiable? In this paper we study a modified survey propagation algorithm that enables us to address this question for a…

Statistical Mechanics · Physics 2009-11-11 A. Ramezanpour , S. Moghimi-Araghi

Stochastic local search algorithms are frequently used to numerically solve hard combinatorial optimization or decision problems. We give numerical and approximate analytical descriptions of the dynamics of such algorithms applied to random…

Statistical Mechanics · Physics 2009-11-10 Wolfgang Barthel , Alexander K. Hartmann , Martin Weigt

We present a phase formalism that passes the Barnett-Pegg acid test, i.e. phase fluctuations for a number state are the expected value $\pi^2/3$ which are the fluctuations for a classical random phase distribution. The formalism is shown to…

Quantum Physics · Physics 2013-03-13 J. M. Vargas-Martinez , H. Moya-Cessa

We study the problem of approximate ranking from observations of pairwise interactions. The goal is to estimate the underlying ranks of $n$ objects from data through interactions of comparison or collaboration. Under a general framework of…

Statistics Theory · Mathematics 2019-06-26 Chao Gao

The resolution of linear system with positive integer variables is a basic yet difficult computational problem with many applications. We consider sparse uncorrelated random systems parametrised by the density $c$ and the ratio $\alpha=N/M$…

Statistical Mechanics · Physics 2017-10-11 S. Colabrese , D. De Martino , L. Leuzzi , E. Marinari

We study the phase diagram and the algorithmic hardness of the random `locked' constraint satisfaction problems, and compare them to the commonly studied 'non-locked' problems like satisfiability of boolean formulas or graph coloring. The…

Disordered Systems and Neural Networks · Physics 2008-12-09 Lenka Zdeborová , Marc Mézard

Three algorithms are presented that determine the existence of satisfying assignments for 3SAT Boolean satisfiability expressions. One algorithm is presented for determining an instance of a satisfying assignment, where such exists. The…

Computational Complexity · Computer Science 2019-12-16 Charles Sauerbier

The satisfiability threshold for constraint satisfaction problems is that value of the ratio of constraints (or clauses) to variables, above which the probability that a random instance of the problem has a solution is zero in the large…

Statistical Mechanics · Physics 2020-07-21 Supriya Krishnamurthy , Sumedha

We show on theoretical grounds that, even in the presence of noise, probabilistic measurement strategies (which have a certain probability of failure or abstention) can provide, upon a heralded successful outcome, estimates with a precision…

Quantum Physics · Physics 2016-10-27 J. Calsamiglia , B. Gendra , R. Munoz-Tapia , E. Bagan

Iterative phase estimation has long been used in quantum computing to estimate Hamiltonian eigenvalues. This is done by applying many repetitions of the same fundamental simulation circuit to an initial state, and using statistical…

Quantum Physics · Physics 2019-07-25 Ian D. Kivlichan , Christopher E. Granade , Nathan Wiebe

We develop an algorithm for computing bounded reachability probability for hybrid systems, i.e., the probability that the system reaches an unsafe region within a finite number of discrete transitions. In particular, we focus on hybrid…

Logic in Computer Science · Computer Science 2015-05-13 Fedor Shmarov , Paolo Zuliani

Let $Z(F)$ be the number of solutions of a random $k$-satisfiability formula $F$ with $n$ variables and clause density $\alpha$. Assume that the probability that $F$ is unsatisfiable is $O(1/\log(n)^{1+\e})$ for $\e>0$. We show that…

Discrete Mathematics · Computer Science 2010-06-23 Emmanuel Abbe , Andrea Montanari

In this paper we present a convergence rate analysis of inexact variants of several randomized iterative methods. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic…

Optimization and Control · Mathematics 2019-03-20 Nicolas Loizou , Peter Richtárik

Message passing algorithms have proved surprisingly successful in solving hard constraint satisfaction problems on sparse random graphs. In such applications, variables are fixed sequentially to satisfy the constraints. Message passing is…

Artificial Intelligence · Computer Science 2019-06-05 Andrea Montanari , Federico Ricci-Tersenghi , Guilhem Semerjian

The progressive hedging algorithm (PHA) is a cornerstone among algorithms for large-scale stochastic programming problems. However, its traditional implementation is hindered by some limitations, including the requirement to solve all…

Optimization and Control · Mathematics 2025-03-13 Di Zhang , Yihang Zhang , Suvrajeet Sen

We show enough evidence that a structured version of Adiabatic Quantum Computation (AQC) is efficient for most satisfiability problems. More precisely, when the success probability is fixed beforehand, the computational resources grow…

Quantum Physics · Physics 2008-12-10 Juan Jose Garcia-Ripoll , Mari Carmen Bañuls

Propositional satisfiability (SAT) is one of the most fundamental problems in computer science. The worst-case hardness of SAT lies at the core of computational complexity theory. The average-case analysis of SAT has triggered the…

Discrete Mathematics · Computer Science 2019-05-03 Tobias Friedrich , Anton Krohmer , Ralf Rothenberger , Thomas Sauerwald , Andrew M. Sutton

We establish the satisfiability threshold for random $k$-SAT for all $k\ge k_0$, with $k_0$ an absolute constant. That is, there exists a limiting density $\alpha_*(k)$ such that a random $k$-SAT formula of clause density $\alpha$ is with…

Probability · Mathematics 2021-04-16 Jian Ding , Allan Sly , Nike Sun

We consider a type of optimal switching problems with non-uniform execution delays and ramping. Such problems frequently occur in the operation of economical and engineering systems. We first provide a solution to the problem by applying a…

Optimization and Control · Mathematics 2017-02-15 Magnus Perninge

When there are infinitely many scenarios, the current studies of two-stage stochastic programming problems rely on the relatively complete recourse assumption. However, such assumption can be unrealistic for many real-world problems. This…

Optimization and Control · Mathematics 2020-08-03 Rui Peng Liu