DOCSLIB.ORG

Mission, Tradition, and Data Revolution

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Mission, Tradition, and Data Revolution SH AP OT N S S COMPUTERS & , , COMPUTATION Mission Tradition F R L O I L H and Data Revolution M T H E Los Alamos has a rich legacy of First, the computer mines the data to figure leading computing revolutions, out what characteristics comprise a better a legacy that began before computers widget, then it explores avenues to arrive even existed. The elaborate calculations at the best widget possible. Human brains underpinning the Laboratory’s original are still required to evaluate performance, mission often took months, so in the race but the goal is for even this to be automated. against time, when every day mattered, On the other side of the Lab’s computing new methods of streamlining were coin lies simulation, a computing revolution continually devised. Those efforts— born long ago from brute force and necessity. both mechanical and mathematical— War and defense have long driven human paid off and secured permanent places innovation, and as the Lab transitioned at the Laboratory for computers and from a temporary war effort to a permanent computation, which have evolved in scientific institution, its first electronic tandem over the decades. computer, MANIAC I, was built to help model Today the Lab is on the leading edge thermonuclear processes for new weapons of a new revolution, born of opportunity. designs. Built in 1952, MANIAC I used With myriad digital devices now cheaply von Neumann architecture, an organization available, mass quantities of data are being scheme envisioned by Manhattan Project produced, and scientists realized that new scientist John von Neumann. Overseeing Improvement in computation capability ways of managing data are needed and MANIAC I was Nicholas Metropolis, who, over the past 25 years is illustrated by these climate simulations of an area around the new ways of utilizing data are possible. along with von Neumann and others Kuroshio current, off the coast of Japan. Thus the field of data science was born. at Los Alamos, devised the Monte Carlo CREDIT: Mat Maltrud/LANL Data science at the Lab falls into two broad method—a computational algorithm categories: pattern recognition-based based on repeated random sampling rather platforms, such as real-time traffic- than direct deterministic computation— navigation assistants or cyber-security which spawned a family of methods that software, that evaluate risks, rewards, remain essential to modern science. to the contrary. The scientists initially and characteristic behavior; and physics- Contemporary with von Neumann and thought the computer got it wrong, but based platforms that match models and Metropolis were Enrico Fermi, John Pasta, then they realized it was their thinking equations to empirical data, such as how Stanislaw Ulam, and Mary Tsingau, who that was off, not the computation. It was fluids flow through fractures in the earth’s together are credited with the birth, in 1955 new physics. It was unexpected and non- subsurface during processes like fracking at Los Alamos, of experimental mathematics intuitive, and it could not have been done or underground nuclear detonation. and nonlinear science. The Fermi-Pasta- without a computer. Presently, Los Alamos data scientists Ulam-Tsingau publication (Mary Tsingau, As long as supercomputers have are making advances in machine learning, the programmer who coded the first-ever existed, Los Alamos has been home to the such that data itself can be the algorithm, numerical simulation experiments on latest and greatest among them. After instead of a human-coded algorithm. MANIAC I, was initially excluded from the MANIAC I came the IBM 701, the first The data come from experiments, for byline of the publication) describes a paradox electronic digital computer, followed by example materials-science experiments in which complicated physical systems the faster IBM 704, then MANIAC II, then geared toward building a better widget. exhibit periodic behavior despite predictions the IBM 7030, or “Stretch,” which is often 4 1663 August 2018 hailed as the first true supercomputer. rely on high-performance computing Revolution in computing Continual innovation in supercomputers capabilities. Thirty years ago, the best is a tradition at Los Alamos over the last six decades has enabled these simulations could do was to parse and is central to the continual innovation in simulation, which, the weather geographically down to Laboratory’s mission. although it began with thermonuclear 200-kilometer squares; now they have processes, is now at the heart of many gotten down to just 10 kilometers. different research efforts at the Lab. Although data science and machine For example, numerical models used to learning are the young new arrivals, predict long-term climate shifts as well supercomputing and simulation are the as weather (e.g., hurricane trajectories) mainstays of the Laboratory’s high- performance computing program, and all have their place at the table. By addressing In the 1980s, prior to Los Alamos engaging in climate-simulation research, the most complex processes in some the best resolution was 2.0 degrees, or about 200-kilometer squares. of the hardest problems facing science, national labs like Los Alamos are pushing the frontier of science and contributing In the early 1990s, the Connection Machine, a resident directly to national security and the global supercomputer, helped bring the resolution down to 0.28 degree, economy. The next milestone on that or about 30-kilometer squares. This simulation was presented to frontier is exascale computing, the ability President Clinton during one of his visits to the Laboratory and to perform a quintillion calculations per also won a Smithsonian Computer World award. second. It’s a tall order and a considerable leap from where we are now, but looking In the 2000s, additional evolution back on where we came from, there’s every of supercomputer hardware reason to have confidence that Los Alamos and architecture enabled the will have a leading role in this revolution resolution to reach 0.1 degree, as well. or 10-kilometer squares. —Eleanor Hutterer Most recently, improvements have centered around incorporating new features and new physics that make the simulations more realistic. Here, the inclusion of ice shelves around Antarctica— important for understanding climate change—makes use of the newest model capabilities. CREDIT: Phillip Wolfram, Matthew Hoffman, and Mark Petersen/LANL 1663 August 2018 5 The Laboratory has been home to consensus that it was impossible, set out Reines and Cowan relied on brute many Nobel laureates. But in only one to capture the elusive neutrino. Because force and brilliance, but this latest instance was the prize-winning work done neutrinos are so inert, the likelihood of Los Alamos neutrino detector has the during the winner’s tenure at Los Alamos. one interacting with a detector is remote, benefit of serendipity as well. It turns out That was in 1956, when Fred Reines and so a tremendous number of neutrinos is that the proton beam at the Los Alamos Clyde Cowan proved the existence of a new needed to be able to observe just one. Neutron Science Center—established in kind of subatomic particle, the neutrino. The duo initially intended to use an 1972 to study the short-lived subatomic Since then, neutrino science has continued underground nuclear bomb test at the Lab and elsewhere, leading to three as the source of this tremendous more Nobel Prizes. Now, new experiments number of neutrinos, but they at Los Alamos are poised on the brink of quickly determined that a nuclear a new discovery, which looks to be just as reactor would be better, so they exciting as any of them. took their detector—a rig about In 1930, theoretical physicist the size of a modern washing Wolfgang Pauli proposed that a new machine—to the reactor at particle—invisible and uncharged—was Hanford, Washington. needed to satisfy the law of conservation After preliminary work at of energy during radioactive decay of Hanford, the team decided to atomic nuclei. Pauli used the name build a bigger and better detector “neutron,” which was the same name given at the brand new reactor in to another, more massive particle. Pauli’s Savannah River, South Carolina. contemporary Enrico Fermi, who would It was there that they finally and later join the war effort at Los Alamos, conclusively observed the electron resolved the nomenclature problem by antineutrino—the antiparticle of giving the less massive particle the Italian the electron neutrino, whose very diminutive “-ino,” and viola! The neutrino. existence proved the existence Scientists now know that neutrinos of the other. Reines and Cowan are among the most abundant particles sent a jubilant telegram to Pauli in the universe—hundreds of trillions of in Switzerland informing him of them stream unobtrusively though our their success. Clyde Cowan died in bodies every second of every day. So far, 1974, and Fred Reines alone was three varieties are known: the electron awarded the Nobel Prize in 1995 neutrino, the muon neutrino, and the tau for their work. neutrino. Neutrinos are almost completely Nowadays most neutrino inert, interacting with other particles only detectors are much, much larger. by gravity and by the weak nuclear force. Usually they are international In fact, Fermi based his original postulation collaborations involving thousands of the weak nuclear force on Pauli’s of tons of liquid in enormous Fred Reines (left) and Clyde Cowan inspect their neutrino detector proposed, and still hypothetical at the time, vessels thousands of feet below the in 1955, a predecessor to the one they used in 1956 to prove the new particle. surface of the earth. But the latest existence of the elusive neutrino. Forty years later and 21 years after In the early 1950s, as the Laboratory neutrino detector at Los Alamos, though Cowan’s death, Reines alone was awarded the 1995 Nobel Prize in was expanding from a war-time weapons larger than the first, is still quite small, Physics for their shared discovery.
Load more

Recommended publications
  • Monte Carlo Simulation in Statistics with a View to Recent Ideas
    (sfi)2 Statistics for Innovation Monte Carlo simulation in statistics, with a view to recent ideas Arnoldo Frigessi [email protected] THE JOURNAL OF CHEMICAL PHYSICS VOLUME 21, NUMBER 6 JUNE, 1953 Equation of State Calculations by Fast Computing Machines NICHOLAS METROPOLIS, ARIANNA W. ROSENBLUTH, MARSHALL N. ROSENBLUTH, AND AUGUSTA H. TELLER, Los Alamos Scientific Laboratory, Los Alamos, New Mexico AND EDWARD TELLER, * Department of Physics, University of Chicago, Chicago, Illinois (Received March 6, 1953) A general method, suitable for fast computing machines, for investigating such properties as equations of state for substances consisting of interacting individual molecules is described. The method consists of a modified Monte Carlo integration over configuration space. Results for the two-dimensional rigid-sphere system have been obtained on the Los Alamos MANIAC and are presented here. These results are compared to the free volume equation of state and to a four-term virial coefficient expansion. The Metropolis algorithm from1953 has been cited as among the top 10 algorithms having the "greatest influence on the development and practice of science and engineering in the 20th century." MANIAC The MANIAC II 1952 Multiplication took a milli- second. (Metropolis choose the name MANIAC in the hope of stopping the rash of ”silly” acronyms for machine names.) Some MCMC milestones 1953 Metropolis Heat bath, dynamic Monte Carlo 1970 Hastings Political Analysis, 10:3 (2002) Society for Political Methodology 1984 Geman & Geman Gibbs
    [Show full text]
  • A Selected Bibliography of Publications By, and About, J
    A Selected Bibliography of Publications by, and about, J. Robert Oppenheimer Nelson H. F. Beebe University of Utah Department of Mathematics, 110 LCB 155 S 1400 E RM 233 Salt Lake City, UT 84112-0090 USA Tel: +1 801 581 5254 FAX: +1 801 581 4148 E-mail: [email protected], [email protected], [email protected] (Internet) WWW URL: http://www.math.utah.edu/~beebe/ 17 March 2021 Version 1.47 Title word cross-reference $1 [Duf46]. $12.95 [Edg91]. $13.50 [Tho03]. $14.00 [Hug07]. $15.95 [Hen81]. $16.00 [RS06]. $16.95 [RS06]. $17.50 [Hen81]. $2.50 [Opp28g]. $20.00 [Hen81, Jor80]. $24.95 [Fra01]. $25.00 [Ger06]. $26.95 [Wol05]. $27.95 [Ger06]. $29.95 [Goo09]. $30.00 [Kev03, Kle07]. $32.50 [Edg91]. $35 [Wol05]. $35.00 [Bed06]. $37.50 [Hug09, Pol07, Dys13]. $39.50 [Edg91]. $39.95 [Bad95]. $8.95 [Edg91]. α [Opp27a, Rut27]. γ [LO34]. -particles [Opp27a]. -rays [Rut27]. -Teilchen [Opp27a]. 0-226-79845-3 [Guy07, Hug09]. 0-8014-8661-0 [Tho03]. 0-8047-1713-3 [Edg91]. 0-8047-1714-1 [Edg91]. 0-8047-1721-4 [Edg91]. 0-8047-1722-2 [Edg91]. 0-9672617-3-2 [Bro06, Hug07]. 1 [Opp57f]. 109 [Con05, Mur05, Nas07, Sap05a, Wol05, Kru07]. 112 [FW07]. 1 2 14.99/$25.00 [Ber04a]. 16 [GHK+96]. 1890-1960 [McG02]. 1911 [Meh75]. 1945 [GHK+96, Gow81, Haw61, Bad95, Gol95a, Hew66, She82, HBP94]. 1945-47 [Hew66]. 1950 [Ano50]. 1954 [Ano01b, GM54, SZC54]. 1960s [Sch08a]. 1963 [Kuh63]. 1967 [Bet67a, Bet97, Pun67, RB67]. 1976 [Sag79a, Sag79b]. 1981 [Ano81]. 20 [Goe88]. 2005 [Dre07]. 20th [Opp65a, Anoxx, Kai02].
    [Show full text]
  • The Convergence of Markov Chain Monte Carlo Methods 3
    The Convergence of Markov chain Monte Carlo Methods: From the Metropolis method to Hamiltonian Monte Carlo Michael Betancourt From its inception in the 1950s to the modern frontiers of applied statistics, Markov chain Monte Carlo has been one of the most ubiquitous and successful methods in statistical computing. The development of the method in that time has been fueled by not only increasingly difficult problems but also novel techniques adopted from physics. In this article I will review the history of Markov chain Monte Carlo from its inception with the Metropolis method to the contemporary state-of-the-art in Hamiltonian Monte Carlo. Along the way I will focus on the evolving interplay between the statistical and physical perspectives of the method. This particular conceptual emphasis, not to mention the brevity of the article, requires a necessarily incomplete treatment. A complementary, and entertaining, discussion of the method from the statistical perspective is given in Robert and Casella (2011). Similarly, a more thorough but still very readable review of the mathematics behind Markov chain Monte Carlo and its implementations is given in the excellent survey by Neal (1993). I will begin with a discussion of the mathematical relationship between physical and statistical computation before reviewing the historical introduction of Markov chain Monte Carlo and its first implementations. Then I will continue to the subsequent evolution of the method with increasing more sophisticated implementations, ultimately leading to the advent of Hamiltonian Monte Carlo. 1. FROM PHYSICS TO STATISTICS AND BACK AGAIN At the dawn of the twentieth-century, physics became increasingly focused on under- arXiv:1706.01520v2 [stat.ME] 10 Jan 2018 standing the equilibrium behavior of thermodynamic systems, especially ensembles of par- ticles.
    [Show full text]
  • Monte Carlo Sampling Methods
    [1] Monte Carlo Sampling Methods Jasmina L. Vujic Nuclear Engineering Department University of California, Berkeley Email: [email protected] phone: (510) 643-8085 fax: (510) 643-9685 UCBNE, J. Vujic [2] Monte Carlo Monte Carlo is a computational technique based on constructing a random process for a problem and carrying out a NUMERICAL EXPERIMENT by N-fold sampling from a random sequence of numbers with a PRESCRIBED probability distribution. x - random variable N 1 xˆ = ---- x N∑ i i = 1 Xˆ - the estimated or sample mean of x x - the expectation or true mean value of x If a problem can be given a PROBABILISTIC interpretation, then it can be modeled using RANDOM NUMBERS. UCBNE, J. Vujic [3] Monte Carlo • Monte Carlo techniques came from the complicated diffusion problems that were encountered in the early work on atomic energy. • 1772 Compte de Bufon - earliest documented use of random sampling to solve a mathematical problem. • 1786 Laplace suggested that π could be evaluated by random sampling. • Lord Kelvin used random sampling to aid in evaluating time integrals associated with the kinetic theory of gases. • Enrico Fermi was among the first to apply random sampling methods to study neutron moderation in Rome. • 1947 Fermi, John von Neuman, Stan Frankel, Nicholas Metropolis, Stan Ulam and others developed computer-oriented Monte Carlo methods at Los Alamos to trace neutrons through fissionable materials UCBNE, J. Vujic Monte Carlo [4] Monte Carlo methods can be used to solve: a) The problems that are stochastic (probabilistic) by nature: - particle transport, - telephone and other communication systems, - population studies based on the statistics of survival and reproduction.
    [Show full text]
  • The Markov Chain Monte Carlo Approach to Importance Sampling
    The Markov Chain Monte Carlo Approach to Importance Sampling in Stochastic Programming by Berk Ustun B.S., Operations Research, University of California, Berkeley (2009) B.A., Economics, University of California, Berkeley (2009) Submitted to the School of Engineering in partial fulfillment of the requirements for the degree of Master of Science in Computation for Design and Optimization at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY September 2012 c Massachusetts Institute of Technology 2012. All rights reserved. Author.................................................................... School of Engineering August 10, 2012 Certified by . Mort Webster Assistant Professor of Engineering Systems Thesis Supervisor Certified by . Youssef Marzouk Class of 1942 Associate Professor of Aeronautics and Astronautics Thesis Reader Accepted by . Nicolas Hadjiconstantinou Associate Professor of Mechanical Engineering Director, Computation for Design and Optimization 2 The Markov Chain Monte Carlo Approach to Importance Sampling in Stochastic Programming by Berk Ustun Submitted to the School of Engineering on August 10, 2012, in partial fulfillment of the requirements for the degree of Master of Science in Computation for Design and Optimization Abstract Stochastic programming models are large-scale optimization problems that are used to fa- cilitate decision-making under uncertainty. Optimization algorithms for such problems need to evaluate the expected future costs of current decisions, often referred to as the recourse function. In practice, this calculation is computationally difficult as it involves the evaluation of a multidimensional integral whose integrand is an optimization problem. Accordingly, the recourse function is estimated using quadrature rules or Monte Carlo methods. Although Monte Carlo methods present numerous computational benefits over quadrature rules, they require a large number of samples to produce accurate results when they are embedded in an optimization algorithm.
    [Show full text]
  • Oral History Interview with Nicolas C. Metropolis
    An Interview with NICOLAS C. METROPOLIS OH 135 Conducted by William Aspray on 29 May 1987 Los Alamos, NM Charles Babbage Institute The Center for the History of Information Processing University of Minnesota, Minneapolis Copyright, Charles Babbage Institute 1 Nicholas C. Metropolis Interview 29 May 1987 Abstract Metropolis, the first director of computing services at Los Alamos National Laboratory, discusses John von Neumann's work in computing. Most of the interview concerns activity at Los Alamos: how von Neumann came to consult at the laboratory; his scientific contacts there, including Metropolis, Robert Richtmyer, and Edward Teller; von Neumann's first hands-on experience with punched card equipment; his contributions to shock-fitting and the implosion problem; interactions between, and comparisons of von Neumann and Enrico Fermi; and the development of Monte Carlo techniques. Other topics include: the relationship between Turing and von Neumann; work on numerical methods for non-linear problems; and the ENIAC calculations done for Los Alamos. 2 NICHOLAS C. METROPOLIS INTERVIEW DATE: 29 May 1987 INTERVIEWER: William Aspray LOCATION: Los Alamos, NM ASPRAY: This is an interview on the 29th of May, 1987 in Los Alamos, New Mexico with Dr. Nicholas Metropolis. Why don't we begin by having you tell me something about when you first met von Neumann and what your relationship with him was over a period of time? METROPOLIS: Well, he first came to Los Alamos on the invitation of Dr. Oppenheimer. I don't remember quite when the date was that he came, but it was rather early on. It may have been the fall of 1943.
    [Show full text]
  • Doing Mathematics on the ENIAC. Von Neumann's and Lehmer's
    Doing Mathematics on the ENIAC. Von Neumann's and Lehmer's different visions.∗ Liesbeth De Mol Center for Logic and Philosophy of Science University of Ghent, Blandijnberg 2, 9000 Gent, Belgium [email protected] Abstract In this paper we will study the impact of the computer on math- ematics and its practice from a historical point of view. We will look at what kind of mathematical problems were implemented on early electronic computing machines and how these implementations were perceived. By doing so, we want to stress that the computer was in fact, from its very beginning, conceived as a mathematical instru- ment per se, thus situating the contemporary usage of the computer in mathematics in its proper historical background. We will focus on the work by two computer pioneers: Derrick H. Lehmer and John von Neumann. They were both involved with the ENIAC and had strong opinions about how these new machines might influence (theoretical and applied) mathematics. 1 Introduction The impact of the computer on society can hardly be underestimated: it affects almost every aspect of our lives. This influence is not restricted to ev- eryday activities like booking a hotel or corresponding with friends. Science has been changed dramatically by the computer { both in its form and in ∗The author is currently a postdoctoral research fellow of the Fund for Scientific Re- search { Flanders (FWO) and a fellow of the Kunsthochschule f¨urMedien, K¨oln. 1 its content. Also mathematics did not escape this influence of the computer. In fact, the first computer applications were mathematical in nature, i.e., the first electronic general-purpose computing machines were used to solve or study certain mathematical (applied as well as theoretical) problems.
    [Show full text]
  • Lecture Notes on the Fermi-Pasta-Ulam-Tsingou Problem
    Lecture Notes on the Fermi-Pasta-Ulam-Tsingou Problem Andrew Larkoski November 9, 2016 Because this is a short week, we're going to just discuss some fun aspects of computational physics. Also, because last week's topic was the final homework (due the following Friday), just sit back and relax and forget about everything you have to do. Just kidding. Today, I'm going to discuss the Fermi-Pasta-Ulam-Tsingou (FPUT), problem. Actually, Laura Freeman did her thesis on this topic at Reed in 2008; you can pick up her thesis in the lounge or on the Reed Senior Thesis digital collections if you are interested. Laura actually interviewed Mary Tsingou for her thesis, so this is actually a fascinating historical document. In the early 1950's, Enrico Fermi, John Pasta, Stanislaw Ulam, and Mary Tsingou per- formed some of the earliest computer simulations on the MANIAC system at Los Alamos. (Remember MANIAC? Metropolis was the leader!) Their problem was very simple, but their results profound. They attempted to simulate a non-linear harmonic oscillator (i.e., spring) on a grid. Recall that Newton's equations for a spring on a grid is: mx¨j = k(xj+1 − 2xj + xj−1) ; (1) which is just a linear problem and so normal modes and eigenfrequencies can be found exactly, etc. The grid spacing is ∆x and so position xj is at xj = j∆x : (2) The problem that FPUT studied was slightly different, modified by non-linearities in x: mx¨j = k(xj+1 − 2xj + xj−1)[1 + α(xj+1 − xj−1)] : (3) When α = 0, this of course returns the linear system, but for α 6= 0 it is non-linear.
    [Show full text]
  • Institute for the Future, Mello Park, Calif: SPONS AGENCY ? National
    ;10 DOCUMENT RESUME AP ED 110' 011 IR 002 279 AUTHOR Amara, Roy TITLE. Toward Understanding, ,the Socialfmpactof Computers. IFF Report R-29. INSTITUTION 'Institute for the Future, MeLlo Park, Calif: SPONS AGENCY ?National Science Foundation, Washington, D.C. , . 'PUB DATE- ° May 74 . NOTE 141p. j 'AVA'ILABLE FROM Institute for the Future, 2740 Sand Hill Road, Menlo i Park, California 94015 (f10.00) 1.. / . EDRS PRICE MF-$0.76 PLUSATAGE,HC Not Available from EDRS. DESCRIPTORS" Adult Education; *Attitudes;. Computer"Pnograms; *Computers; Computer Science Education; Conference Reports;. Decision Makin Electronic Data Processing; Financial Policy; *,Future (of Society); Puplic Opinion; Scientific Literac .Simulation; Sodial . Attitudes; *Social Change; T_c ological Advancement; *Values 'IDENTIFIERS Computer Literacy; /FP; *Inttitute FOr The Future ABSTRACT r- Summaries of four,. workshops sponsored by the Institute For The Future' (IFF) are presented. Each'focuses on a ,particular aspect'of:the social impact of.computers:(1) computer models and simulatiohs Is aids to decision making;(2) the usd of computers in financitl'operations; 13) perceptions,attitudes, and literacy regarding computers knowledge about the capabilitirs ' and limitation's of computers in meeting humanneeds).; and (4) .individual access to domp ters. Workshop participants and e IFF * staff conclude that there is a need for. th to acqu re a deeper.understanding of 'how computers of ct the decisions individuals and organizations make, -the goods and services they produce, and tfleirorld that individual,perceive. It is also concluded that such improved understan ing must be acquiredin the near future. A programof education p the public 'is lyen propost4.... (Author/DGC) a v .4 , .
    [Show full text]
  • 75 YEARS Trinity Test the Dawn of America’S Scientific Innovation CONTENTS
    75 YEARS Trinity Test The Dawn of America’s Scientific Innovation CONTENTS 1 THE MANHATTAN PROJECT ........ 4 2 TRINITY TEST - JULY 16, 1945 ...... 6 3 1940s .............................................. 10 4 1950s ..........................................12 5 1960s ..........................................14 1970s ..........................................16 Beyond the advances in nuclear physics 6 and chemistry that made the “ 7 1980s ..........................................18 “ first functional atomic device possible, Trinity was arguably the greatest 1990s ..........................................20 scientific experiment ever conducted. 8 9 2000s ..........................................22 Lisa E. Gordon-Hagerty U.S. Under Secretary of Energy for Nuclear Security Administrator of the National Nuclear Security Administration 10 2010s ..........................................24 11 2020 and FORWARD ..................... 26 1 Manhattan Project: The Origin of the Trinity Test In the 1920s-1930s, a young Hungarian-German physicist Roosevelt responded by launching The Manhattan Project, Leo Szilard led the field of nuclear research, submitting a nationwide network of laboratories and manufacturing patents for a linear accelerator (1928) and cyclotron (1929), facilities designed to collaboratively assist in the before collaborating with Albert Einstein to develop the manufacture of a new atomic weapon. Einstein refrigerator. But when Hitler came into power in 1933, Szilard fled to England, encouraging his friends and family to do the same. In England, he first described the nuclear chain reaction (1933) and patented an early design for a nuclear fission reactor (1934). In 1938, Szilard joined Einstein in the United States, but the rumor that a group of Berlin chemists had split the uranium atom made them so concerned that in 1939, they sent an urgent letter to President Franklin D. Roosevelt, warning him that that Axis scientists were working to turn new nuclear discoveries into a superweapon.
    [Show full text]
  • A Bibliography of Publications of Stanis Law M. Ulam
    A Bibliography of Publications of Stanislaw M. Ulam Nelson H. F. Beebe University of Utah Department of Mathematics, 110 LCB 155 S 1400 E RM 233 Salt Lake City, UT 84112-0090 USA Tel: +1 801 581 5254 FAX: +1 801 581 4148 E-mail: [email protected], [email protected], [email protected] (Internet) WWW URL: http://www.math.utah.edu/~beebe/ 17 March 2021 Version 2.56 Abstract This bibliography records publications of Stanis law Ulam (1909–1984). Title word cross-reference $17.50 [Bir77]. $49.95 [B´ar04]. $5.00 [GM61]. α [OVPL15]. -Fermi [OVPL15]. 150 [GM61]. 1949 [Ano51]. 1961 [Ano62]. 1963 [UdvB+64]. 1970 [CFK71]. 1971 [Ula71b]. 1974 [Hua76]. 1977 [Kar77]. 1979 [Bud79]. 1984 [DKU85]. 2000 [Gle02]. 20th [Cip00]. 25th [Ano05]. 49.95 [B´ar04]. 1 2 60-year-old [Ano15]. 7342-438 [Ula71b]. ’79 [Bud79]. Abbildungen [MU31, SU34b, SU34a, SU35a, Ula34, Ula33a]. Abelian [MU30]. Abelsche [MU30]. Above [Mar87]. abstract [Ula30c, Ula39b, Ula78d]. abstrakten [Ula30c]. accelerated [WU64]. Accelerates [Gon96b]. Adam [Gle02]. Adaptive [Hol62]. additive [BU42, Ula30c]. Advances [Ano62, Ula78d]. Adventures [Met76, Ula76a, Ula87d, Ula91a, Bir77, Wil76]. Aerospace [UdvB+64]. ago [PZHC09]. Alamos [DKU85, MOR76a, HPR14, BU90, Ula91b]. Albert [RR82]. algebra [BU78, CU44, EU45b, EU46, Gar01a, TWHM81]. Algebraic [Bud79, SU73]. Algebras [BU75, BU76, EU50d]. Algorithm [JML13]. Algorithms [Cip00]. allgemeinen [Ula30d]. America [FB69]. American [UdvB+64, Gon96a, TWHM81]. Analogies [BU90]. analogy [Ula81c, Ula86]. Analysis [Goa87, JML13, RB12, Ula49, Ula64a, Jun01]. Andrzej [Ula47b]. anecdotal [Ula82c]. Annual [Ano05]. any [OU38a, Ula38b]. applicability [Ula69b]. application [EU50d, LU34]. Applications [Ula56b, Ula56a, Ula81a]. Applied [GM61, MOR76b, TWHM81, Ula67b]. appreciation [Gol99]. Approach [BPP18, Ula42].
    [Show full text]
  • SKIING the SUN New Mexico Essays by Michael Waterman
    SKIING THE SUN New Mexico Essays ——————————————————— by Michael Waterman ....he will eat dried buffalo meat and frijoles with chili, and he will be glad to drink water when he can get it. From the novel Death Comes for the Archbishop, written by Willa Cather in 1926-1927. In recent years I have written several essays about New Mexico, only one of which has appeared in print. The truth is that my motivation has not been to tell others these stories and thoughts, but instead to articulate them to myself. That is harder than it looks, at least it is when I do it! After the memorial article about Gian-Carlo Rota appeared in the Notices of the AMS (here it is titled “Silhouettes on the Mesa”), several people expressed an interest in Rota, Ulam and Metropolis, so I decided to post this material. As this appears on my scientific web page, I have only included the essays that relate to science and mathematics, or more accurately, to scientists and mathematicians. The only formulas in the manuscript appear in “Silhouettes” and should be easy to skip over. The title comes from a 1970s slogan advertising New Mexico, “Ski the Sun,” that referred to the fact that the New Mexico weather was so good that people didn’t need to ski in bad weather. Coming from Idaho where there wasn’t much sunshine in the winter, I was struck by the reluctance of people to venture outdoors in anything but ideal conditions. Then again there is an obvious connection to be made with that incredible ball of fire when the bomb exploded at White Sands on July 16, 1945.
    [Show full text]