Papers by Francis Sullivan
Physics Today, 2012
ABSTRACT Information & Computer Science 50-0319 QA76 2011-30265 CIP Dyson, George. Turing... more ABSTRACT Information & Computer Science 50-0319 QA76 2011-30265 CIP Dyson, George. Turing's cathedral: the origins of the digital universe. Pantheon Books, 2012. 401p index ISBN 9780375422775, $29.95
Physics Today, 2011
Computer simulation was first pioneered as a scientific tool in meteorology and nuclear physics i... more Computer simulation was first pioneered as a scientific tool in meteorology and nuclear physics in the period following World War II, but it has grown rapidly to become indispensible in a wide variety of scientific disciplines, including astrophysics, high-energy physics, climate science, engineering, ecology, and economics. Digital computer simulation helps study phenomena of great complexity, but how much do we know about the limits and possibilities of this new scientific practice? How do simulations compare to traditional ...
Journal of Statistical Physics, 1986
Computer Physics Communications, 1986
ABSTRACT
ACM Computing Surveys, 1996
Computational Statistics, 2014
ABSTRACT The method of Sinkhorn balancing that starts with a non-negative square matrix and itera... more ABSTRACT The method of Sinkhorn balancing that starts with a non-negative square matrix and iterates to produce a related doubly stochastic matrix has been used with some success to estimate the values of the permanent in some cases of physical interest. However, it is often claimed that Sinkhorn balancing is slow to converge and hence not useful for efficient computation. In this paper, we explain how some simple, low cost pre-processing allows one to guarantee that Sinkhorn balancing always converges linearly. We illustrate this approach by efficiently and accurately computing permanents and -permanents of some previously studied matrices.
Physical Review E, 2001
Our starting point is an algorithm of Kenyon, Randall, and Sinclair, which is built upon the idea... more Our starting point is an algorithm of Kenyon, Randall, and Sinclair, which is built upon the ideas of Jerrum and Sinclair, giving an approximation to crucial parameters of the monomer-dimer covering problem in polynomial time. We make two key improvements to their algorithm: we greatly reduce the number of simulations that must be run by estimating good values of the generating function parameter, and we greatly reduce the number of steps that must be taken in each simulation by aggregating to a simulation with at most five states. The result is an algorithm that is computationally feasible for modestly sized meshes. We use our algorithm on two-and three-dimensional problems, computing approximations to the coefficients of the generating function and some limiting values.
Encyclopedia of Operations Research and Management Science, 2001
Encyclopedia of Operations Research and Management Science, 2001
Physica D: Nonlinear Phenomena, 1992
ABSTRACT
Computing in Science and Engineering - C in S&E, 2000
Describes one technique for working with extremely large integers, having perhaps thousands of di... more Describes one technique for working with extremely large integers, having perhaps thousands of digits, using only standard hardware and software. This technique uses modular arithmetic in a way that lets us recover the actual integers if necessary
Computing in Science & Engineering, 2000
JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, a... more JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected].
Computing in Science and Engineering, 2000
Monte Carlo methods use sampling to produce approximate solutions to problems for which other met... more Monte Carlo methods use sampling to produce approximate solutions to problems for which other methods aren't practical. In this homework assignment, we study three uses of Monte Carlo methods: for function minimization, discrete optimization, and counting.
Computing in Science & Engineering, 2000
C o m P u t I n g P r E S C r I P t I o n S Editors: Francis Sullivan, [email protected] Ernst Mücke... more C o m P u t I n g P r E S C r I P t I o n S Editors: Francis Sullivan, [email protected] Ernst Mücke, ernst.
Computing in Science & Engineering, 2000
Computing in Science & Engineering, 2000
Computing in Science & Engineering, 2000
Computing in Science & Engineering, 2000
Computing in SCienCe & engineering
Computing in Science & Engineering, 2000
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Papers by Francis Sullivan