Richard? Maybe
Rechard.
Hey, we all make misteaks.
Correcting mistakes and moving on ... to the next mistakes ... is most important.
Los Alamos National Laboratory
and
Washington State Unversity computer science.
First posted
Wednesday February 8, 2006 09:19
Updated
Wednesday
February 8, 2006 12:38
Do you see the mistake in Soboleski's ACKNOLDEGMENTS?
Richard? Maybe Rechard.
Hey, we all make misteaks.Correcting mistakes and moving on ... to the next mistakes ... is most important.
The pooh guys are in favor of settlement. As well as the wrong cats, of course.
Other guys might also like peaceful settlement?
Metropolis, Nicolas. The Monte Carlo Method. Journal of the American Statistical Association, 1949. Volume 44, Number 247, September 1949 Numerical methods that are known as Monte Carlo methods can be loosely described as statistical simulation methods, where statistical simulation is defined in quite general terms to be any method that utilizes sequences of random numbers to perform the simulation. Monte Carlo methods have been used for centuries, but only in the past several decades has the technique gained the status of a full-fledged numerical method capable of addressing the most complex applications. The name ``Monte Carlo'' was coined by Metropolis (inspired by Ulam's interest in poker) during the Manhattan Project of World War II, because of the similarity of statistical simulation to games of chance, and because the capital of Monaco was a center for gambling and similar pursuits. Monte Carlo is now used routinely in many diverse fields, from the simulation of complex physical phenomena such as radiation transport in the earth's atmosphere and the simulation of the esoteric subnuclear processes in high energy physics experiments, to the mundane, such as the simulation of a Bingo game. See: Eckhardt, Roger (1987). Stan Ulam, John von Neumann, and the Monte Carlo method, Los Alamos Science, Special Issue (15), 131-137. Metropolis, Nicholas and Stanislaw Ulam (1949). The Monte Carlo method, Journal of the American Statistical Association, 44 (247), 335-341. Another account: Credit for inventing the Monte Carlo method often goes to Stanislaw Ulam, a Polish born mathematician who worked for John von Neumann on the United States’ Manhattan Project during World War II. Ulam is primarily known for designing the hydrogen bomb with Edward Teller in 1951. He invented the Monte Carlo method in 1946 while pondering the probabilities of winning a card game of solitaire. Quoted in Eckhardt (1987), Ulam describes the incident as: The first thoughts and attempts I made to practice [the Monte Carlo Method] were suggested by a question which occurred to me in 1946 as I was convalescing from an illness and playing solitaires. The question was what are the chances that a Canfield solitaire laid out with 52 cards will come out successfully? After spending a lot of time trying to estimate them by pure combinatorial calculations, I wondered whether a more practical method than “abstract thinking” might not be to lay it out say one hundred times and simply observe and count the number of successful plays. This was already possible to envisage with the beginning of the new era of fast computers, and I immediately thought of problems of neutron diffusion and other questions of mathematical physics, and more generally how to change processes described by certain differential equations into an equivalent form interpretable as a succession of random operations. Later … [in 1946, I] described the idea to John von Neumann, and we began to plan actual calculations. And another: Short History of Monte Carlo Simulation The name "Monte Carlo" appeared in the World War II times, and sometimes is attributed to the researcher Nicholas Metropolis, inspired in the interest of Stanislaw Ulam, his colleague of Manhattan Project at Los Alamos, in the poker game. Monte Carlo, the capital of Monaco, was a known reference for gambling. According Eckhardt, Ulam invented the Monte Carlo method in 1946 while pondering the probabilities of winning a card game of solitaire. However, Metropolis "attributes the germ of this statistical method to Enrico Fermi, who had used such ideas some 15 years earlier”.. According Liu (2001, p.vii-viii): "The basic idea underlying the method was first brought up by Ulam and deliberated between him and von Neumann in a car when they drove together from Los Alamos to Lamy. Allegedly, Nick Metropolis coined the name 'Monte Carlo', which played an essential role in popularizing the method". Liu comments that the Los Alamos scientists aiming to take advante of the first "super" computer MANIAC, invented a statistical sampling-based technique to solve problems related to stochastic neutron diffusion in atomic bomb project and for estimating eigenvalues of the Schrödinger equation. Winston (1996, p.22) wrote that the term was coined by mathematicians S. Ulam and J. von Neumann in the feasibility project of atomic bomb by simulations of nuclear fission, and they given the code name Monte Carlo for these simulations. The first Monte Carlo paper, "The Monte Carlo Method" by Metropolis & Ulam, was published in 1949 in the Journal of the American Statistical Association. Since then, several different areas has been using the Monte Carlo simulations. With the advent of personal computers and the popularization of faster computational machines, the Monte Carlo simulations has been increasing popular as an important alternative for the solution of complex problems. Shewhart, Walter Andrew. Statistical Method from the Viewpoint of Quality Control. With the editorial Assistance of W. Edwards Deming. Washington, DC, Department of Agriculture: 1939. First edition. 8vo, 1x,155pp, diagrams, tables etc in the text. Original cloth. A fine (+) copy. Very bright. $1250 Fine copy of a scarce and seminal work. "Whereas Shewhart's early writings and first book (1931) were focused on statistical control of industrial production processes, in his second book (above) he extended the applications of statistical process control to the measurement processes of science, and stressed the importance of operational definitions of basic quantities in science, industry and commerce….(this book) has profoundly influenced statistical methods of research in the behavioral, biological and physical sciences, and in engineering…" (DSB, XVIII, 818a) (Book ID 21322) $4,000.00
J. Kister, P. Stein, S. Ulam, W. Walden, and M. Wells. Experiments in chess. Journal of the ACM, 4(2):174-177, April 1957. Citations.
Origin of these unfortunate matters started with Rechard and Walden [who was a programmer for Ulam] at Washington State University computer science program which was eventually eliminated.
E. O. Thorp 1 and W. E. Walden 2
1 Mathematics Department, New Mexico State University, USA,
2 Los Alamos Scientific Laboratory, University of California, USAThorp was Walden's Ph.D. thesis advisor.
Walden's father was a dean at New Mexico State University.
These unfortunate matters resulted from pattern and practice of UN-PUBLISHED student computer science Ph.D. dissertations of Rechard and Walden students.
The students were upset!
As well they should be.
Responsibility is upon thesis advisor to guide student to original publishable thesis topic.
If thesis advisor can't do this, then maybe it's time to quit advising Ph.D. theses.
This was suggested to Rechard and Walden.Suggestion not appreciated.
Also, as Daniel Greenberg writes, "Average salary scales for professors show the marketplace value of different disciplines: law, $109,478; business, $79,931; biological and biomedical sciences, $63,988; mathematics, $61,761." He points out that the editor of Science Magazine even noted the absurdity: "Why do we keep wishing to expand the supply of scientists, even though there is no evidence of imminent shortages?"