computing in the physical sciences

Feb. 19, 2005 W. Bauer 1

Introduction History Utilization Physics Bio Chem Grid Teaching Future Introduction

History of physics & computing Use of computers in the physical

sciences Examples from physics Computers at the interface of

biology, chemistry, and physics Use of the Internet for computing Teaching with the Computer “The Road Ahead”

History of physics & computingUse of computers in the physicalsciencesExamples from physicsComputers at the interface ofbiology, chemistry and physicsUse of the Internet for computing

“The Road Ahead”Teaching with the Computer

Wolfgang BauerDepartment of Physics and Astronomy

Michigan State University

Computing in thePhysical Sciences

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Introduction History Utilization Physics Bio Chem Grid Teaching Future

Complexity in Many-Body Systems

Mesoscopic Systems: Computersbecome essential

2 !

Np

! 102!10

5

logC

Introduction

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(very abbreviated) History of Physics

1700s1700s: Newton invents calculusto describe mechanics

1800s: Faraday et al. studyelectricity&magnetism in experiments

1900s: Theoreticalphysics (Planck,Einstein) exploresthe quantum world

2000s: Computational physics emergesas third branch of physics (von Neumann)

History

time

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History of Computers (Moore’s Law)History

Computer speed doubles every 18 months (Moore’s Law) Data storage doubles every 12 months Network speed doubles every 9 months Improvement 1988 to 2005

(length of my MSU tenure)• Computers: x 2,500• Storage: x 130,000• Networks: x 6,600,000

Physics limits not to bereached for another decadeor more Moore’s Law vs. storage improvements vs. optical

improvements. Graph from Scientific American (Jan-2001) by Cleo Vilett, source Vined, Khoslan,Kleiner, Caufield and Perkins.

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History of Computers (Speed Record)History

Earth Simulator

BlueGene

ASCI White

ASCI Red

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History of ComputersHistory

1946: ENIAC 1947: Transistor (Bardeen,Brattain, Shockley)

2000: 100 milliontransistors in each PC chip

1989: WWW, Berners-Lee, CERN 2004: BlueGene

Driven by demand from andinventions by physical scientists!

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Use of Computers:

Utilization

Email & Office SoftwareFor all of us: significant fraction of our workday

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Use of Computers: Programming

Utilization

Languages: FORTRAN C(++) Java

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Use of Computers: Symbolic Manipulation

Utilization

Programs: Mathematica Maple MathLab

Real MathematicsResearch:e.g. Kepler Conjecture

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Use of Computers: Data Collection

Utilization

Programs: Mathematica Maple MathLab

Real MathematicsResearch:e.g. Kepler Conjecture

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Use of Computers: Visualization

Type IA supernova explosion(BIG SPLASH)

Fusion Stellarator

Acceleratordesign

Atmospheric models

Multi-scale

model ofHIV

Materials: Quantum Corral

Collection: D. Dean, ORNL

Utilization

Nuclear Physics: STAR event (G.D. Westfall)

⇒ Insight

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Use of Computers: Enabling Science

Utilization

Three high-tech buzzwords:

relies on advances in

Progress in

And both are dependent on

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Computational Nano-Science

Prediction of materials’ structuresand properties

Ab initio calculations of quantumforces between atoms

Density functional theory

Physics

Example 1: Carbon pea-podmemory• U.S. Patent 6,473,351

Example 2: Time dependenceof buckyball fusion

Calculations done with EarthSimulator

David Tomanek, MSU-PA

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Computational Nuclear Physics

Big questions:• How are the heaviest elements

made in the universe?• What is the equation of state of

nuclear matter? Experimental Facilities

• NSCL, (future) RIA Computational

Tools• Transport

Theory• Reaction

Networks

Physics

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Computational Astrophysics Astrophysics has to answer questions

without any chance of doingexperiments

Running computer simulations andcomparing their output to staticobservations is only path to progress

Physics

E. Brown, with Flash Center, Chicago

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Example: Cholera protein• Vibrio cholerae• acts like a piston to push out cholera toxin• calculations predict structure

Computational Biochemistry

Protein folding• 3d structure from genetic code

sequence• Constrained molecular dynamics

calculations

Bio Chem

88 (3 GHz) processors 200 Gflop/sWedemeyer, Feig

ActiveActivesite:site:

Calculationprediction: knockout this residue andneutralize poison

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H

N

O

O

Imine Peroxide

•LBSW: P. Ling, A.I. Boldyrev, J. Simons, and C.A. Wight, J. Am. Chem. Soc. 120, 12327 (1998).•LGDS: S.L. Laursen, J.E. Grace Jr., R.L. DeKock, and S.A. Spronk, J. Am. Chem. Soc. 120, 12327 (1998).

1485.5not observedν2 (HNO bend)

3165.53287.7ν1 (NH stretch)

Exp.:LGDSExp: LBSWFundamental Frequency

1054.5843.2ν4 (OO stretch)

1092.31381.6ν3 (NO stretch)

764.0790.7ν6 (torsion)

not observed670.1ν5 (NOO bend)

1499149415091492

3188318831983189

CCSDT-3(Q f)CCSD(TQ f)CR-CCSD(T)CCSD(T)

1071104710781042

1126112311161147

757757777764

650650653650

Computational Quantum Chemistry Coupled Cluster Methods

• Inclusion of many-particle correlation effects• Highly successful in quantum chemistry• Now also ported to nuclear physics• Extremely predictive

• Example: HNOO controversy - CC methods determined whichexperiment was right!

Bio Chem

P. Piecuch et al.

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Digital Evolution “Computer Viruses” Self-replicating pieces of code Random mutation Competition for space on hard drive

according to fitness criteria Many orders of magnitude faster

than watching E-coli bacteria growand divide

Bio Chem

timedi

stan

ce to

ance

stor

Richard Lenski, Charles Ofria, et al.

DigitalorganismsSOLVEcomputationalproblems.

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Computing with the Internet: SETI

Grid

> 1000 CPU years/day !

~60 TeraFLOP/s

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Large Hadron Collider@ CERN (>2008)

Computing for Data Reduction

Grid

ATLAS

Data storage and offline analysisATLAS: ~10 ~10 PetaByte/yearPetaByte/year (~100,000 PC hard drives of 100 GB)

Data rate: 40 MHz, 40 TB/sLevel 1 - Special hardware 75 kHz, 75 GB/sLevel 2 - embedded processors 5 kHz, 5 GB/sLevel 3 - dedicated PCs 100 Hz, 100 MB/s

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Introduction History Utilization Physics Bio Chem Grid Teaching Future Grid

105

104

103

102

Even

t Rat

e (H

z)

High Level-1 Trigger(1 MHz)

High No. ChannelsHigh Bandwidth(500 Gbit/s)

High Data Archive(PetaByte)

LHCB

KLOE HERA-B TeV II

CDF/D0H1

ZEUS

UA1 NA49ALICE

Event Size (bytes)104 105 106

ATLASCMS

106

107

Parts from:Hans HoffmanDOE/NSF Review, Nov 00

Data Streams for Different Experiments

STAR

Data Rates forHigh EnergyPhysicsExperiments PHENIX

FutureCurrentMSU

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Computing with the Internet: Grid

Grid

Tier0/1 facilityTier2 facility

10 Gbps link2.5 Gbps link622 Mbps linkOther link

Tier3 facility

InternationalVirtual GridLaboratory Graphic: Shawn McKee

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Computers in Teaching Core Business of Any University:

Information Technology has changed the way thatknowledge/information is created in the physical sciences

Information Technology is changing the way thatknowledge/information is delivered in the 21st century• Current virtual university delivery models have not even begun to

scratch the surface of what is possible with the availability of essentiallyinfinite bandwidth!

• Adaptive, immersive, customized learning environments!• Brick&Mortar advantages will go away!

We cannot afford to outsource the management ofInformation Technology to commercial entities!

Teaching

Creation, Application, andDissemination of KnowledgeInformation

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Computers in Teaching: LON-CAPA Research: artificial intelligence,

databases, expert systems, geneticalgorithms, self-organization

Content sharing across the net Customized content delivery for

individual students Seamless internationalization ~20 US universities in collaboration MSU leadership (NSF ITR)

Teaching

Library of >105 reusable resources(web page, movie, applet, graphic, …)World-wide LON-CAPA use

LINUX,Apache, GNUpublic license

# of

MS

U s

tude

nts

G. Kortemeyer et al.

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Predictions Predictions are hard …

• “Prediction is very difficult, especially about the future”(Niels Bohr)

But still useful …• Predictions are like Austrian train schedules. Austrian trains are always

late. So why do the Austrians bother to print train schedules? How elsewould they know by how much their trains are late?(Viktor Weisskopf, paraphrased)

So here we go …• Moore’s Law will continue for at least another 2 decades• Network bandwidth will become infinitesimally cheap and eventually

(~2 decades) saturate the human input bandwidth• Caution 1: “Software is a gas” (Nathan Myhrvold)• Caution 2: Growth in content will only be linear, not exponential

Future

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Future of Computing: Quantum Computer

Conventional computer:• N processors can process N

instructions simultaneously Quantum computer:

• N processors can process 2N

instructions simultaneously Example:

• N = 16: 216 = 65,536• N = 32: 232 = 4,294,967,296

Future collaboration potentialbetween PA, Math, CSE

Future

Proposed 16-bit quantumcomputer design: electronson liquid helium(M. Dykman et al.)

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Summary

Physical science has provided technologicalinnovation to advance computer science and willcontinue to do so

Computers have enabled a third branch of physicalscience (besides theory and experiment)

Physical scientists at MSU are among the biggestusers of computing resources, and manycomputational physical scientists are world-leaders

Future collaborations between physical andcomputer scientist are possible and desirable, inparticular in the fields of quantum computing, datacollection and reduction, and use of computers inteaching

computing in the physical sciences

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