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Software challengesand solutionsPhysicists have been at the cutting edge of softwaredevelopment for as long as there has been software. It is surelyno coincidence that two of the biggest names in computingtoday – Tim Berners-Lee and Stephen Wolfram – are bothphysicists. This supplement to Physics World highlights someof the latest developments in software from the mind-bogglingdemands of the latest particle-physics experiments to thesimulation of materials from first principles based on quantumtheory. The challenges are not restricted to basic research.Elsewhere you can read about using software for applicationsin medical physics and in the design of new opticalcomponents for the fibre communications industry. Recentyears have also seen a tremendous improvement in the ITfacilities available to school pupils and university students,and on p9 we describe a scheme that has been commendedfor “best practice” in helping educational establishments toget best value from software licences. With the physicscommunity leading the way in the development of the Grid –the next generation of the Web – the involvement of physicistsin the future of software seems assured.

ContentsSoftware serves medical physicists 5Creating systems to improve treatment planning in radiotherapy places specific demands onsoftware, as researchers from North Western Medical Physics in Manchester explain

A quantum approach to simulation 6Computer codes can now model the behaviour of materials using first-principles quantum-mechanical calculations, as the Cavendish Lab’s Gábor Csányi and Chris J Pickard report

High-energy challenges for software 7It requires a large number of different software systems to carry out experiments in particlephysics, as Richard P Mount of the Stanford Linear Accelerator Center makes clear

Chest ensures value for money for universities 9A licensing service for academic institutions in the UK has cut the cost of software for bothuniversities and suppliers, as Nikki Green from Eduserv Chest explains

Broadband drives developments in telecoms industry 10Packages that rely on finite element modelling are essential in the design of new opticalcomponents for communications, as Serge Bidnyk from Enablence Inc highlights

It pays to adopt a natural approach 11The learning curve may be steep, but Mathematica is fun to use, according to Paul Abbott ofthe University of Western Australia

©2004 IOP Physics Publishing Ltd. All rights reserved.Dirac House, Temple Back, Bristol BS1 6BE, UK.

S O F T W A R E C H A L L E N G E S A N D S O L U T I O N S J U N E 2 0 0 4

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Publishing: full technical document system for presentation, print, and the web • interactive typesetting and graphics •sound • outlining • one-step export to TeX, LaTeX, XML, MathML, HTML, and XHTML

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Platforms: Windows, Macintosh, Linux, other Unix platforms • web and grid versions available

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Numeric computation: full support for arbitrary andmachine precision • hundreds of mathematical functions fullyimplemented for all parameters • fast sparse and densematrix operations • solvers for equations and differentialequations • finite and infinite sums and products • integraltransforms • global optimization • linear programming •automatic or manual algorithm selection • precision control

Symbolic computation: expanding • factoring •simplification • solvers for equations, differential equations,difference equations, and inequalities • sums • products •differentiation • integration • limits • power series • integraltransforms • algebraic and semi-algebraic domains

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Statistics and data analysis: descriptive statistics of uni-and multivariate data • generalized linear and nonlinearfitting • multidimensional interpolation • convolution •correlation • regression • ANOVA • confidence intervals •distributions • hypothesis testing • statistical plots

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© 2003 Wolfram Research, Inc. Mathematica is a registered trademark of Wolfram Research, Inc..NET/Link is a trademark of Wolfram Research, Inc. Mathematica is not associated with Mathematica Policy Research, Inc. or MathTech, Inc.

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The ability to identify the boundaries between tissue that iscancerous and nearby healthy organs is central to image-guided radiotherapy. Armed with a knowledge of these bound-aries, treatment plans can be developed that maximize theradiation dose delivered to the diseased area while minimizingthe exposure of sensitive organs.

Treatments are usually planned from Computed Tomo-graphy (CT) X-ray scans that generate a sequence of trans-verse image “slices” of the patient. The clinician thenmanually outlines the target tumour and organs at risk.However, as the grey scale in a CT image represents differentlevels of X-ray attenuation, there is no specific value thatdenotes cancerous tissue. This can make the identification ofdisease boundaries difficult.

The SCULPTER (Structure Creation Using Limited PointTopology Evidence in Radiotherapy) project at the ChristieHospital in Manchester aims to overcome this problem bygenerating the target shape from a few points on the imageswhere the evidence for a boundary is strong. As true 3D imagesbecome available through the use of a technique known ascone-beam X-ray volume imaging, the project should also pro-vide the ability to switch between different viewpoints andallow medical staff to be guided by features seen with othertechniques, such as magnetic resonance imaging.

SCULPTER is implemented in the Interactive Data Lan-guage (IDL) developed by Research Systems Inc (www.rsinc.com/idl/index.asp). The nature of medical physics researchrequires that any new software must allow the following: inter-action with a range of formatted and unformatted data stan-dards; visualization of multidimensional datasets; accessiblemathematical modelling; and manageable manipulation of thedata by the user. The last of these is essential because radio-therapy planning is, in essence, an interactive reduction ofgrey-level information to spatial structures that are used todetermine the treatment that will be delivered. Failure to dothis correctly can have potentially serious consequences.

To promote ease of interaction it is desirable, if not essential,to be able to hide mathematical processing and programmingdetails behind a robust, high-quality graphical user interface sothat the clinician is presented with an ergonomic, intuitivepackage. IDL enables this through the Widget utility.

As in all research disciplines, project continuity and hand-over are important, and the adoption of a single, easy-to-learnlanguage has significantly eased this process for SCULPTER.It has proved possible for a new scientific user to manipulatedynamic medical image sequences with just a few hours ofindependent learning, always expedited by the availability ofsource code for IDL routines. The array of implicit functionsand procedures provided with IDL significantly aids the rapidprototyping of software.

Although many of these facilities are available in other lan-guages, the combination of all of them in IDL, together withthe simplicity of implementation, has improved productivityseveral times over. It is now possible to concentrate on the sci-ence, and on applying and using it, rather than fighting with,and intellectualizing over, the programming language.

Gareth Price, Jonathan Sykes, Terry Willard and ChrisMoore are at North Western Medical Physics, ChristieHospital and Withington Hospital, Manchester(www.christie.nhs.uk/profinfo/departments/nwmp/radiotherapy/Developing_Technology/SCULPTER.htm)

Software serves medical physicists

Medical physicists at North Western Medical Physics, ChristieHospital in Manchester have used IDL to develop new softwareto allow more accurate radiotherapy treatment of cancer.

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In a happy coincidence, as many areas oftechnology reach the nanometre-scaleregime, advances in computer hardwareand algorithms have made it possible tomodel nanoscale systems using first-principles quantum-mechanical calcula-tions. Most of these simulations rely ondensity functional theory to describe theelectrons in the system. Although this isan approximate theory, experienceshows that it offers high accuracy for cal-culations of many mechanical, electronicor optical properties.

First-principles simulation codes suchas Castep have become a standard andinvaluable tool for the material sciences, as seen from the largenumber of scientific publications that combine first-principlespredictions with experiment. Originally developed by MikePayne and co-workers at the Cavendish Laboratory, Castep hasrecently been completely rewritten by the Castep DevelopersGroup, which has members at the universities of Cambridge,York and Durham, and the Rutherford Appleton Lab.

Castep is commercially marketed worldwide by AccelrysInc (www.accelrys.com) and is integrated into the company’sMaterials Studio simulation suite, which allows straightfor-ward control of calculations and visualization of the results

(see figure). Academic researchers in theUK can also obtain the code via the UKCar–Parrinello Consortium (www.cse.clrc.ac.uk/cmg/NETWORKS/UKCP).

At Cambridge we have used Castep toinvestigate impurities in carbon nano-tubes and inter-tube bridges in nanotuberopes. We were able to predict the exis-tence of several types of possible link-ages between neighbouring nanotubes(Phys. Rev. Lett. 91 105502; NatureMaterials 3 153). We then used theresults to understand how such bridgesmight influence the strength of nanotuberopes. The code allowed realistic models

containing several hundred carbon atoms to be simulated.For our work we used only a selection of the features of

Castep: full unit cell and structural geometry optimization;ensemble density functional theory to treat metallic systems;and calculations of local density of electronic states. The code,which is also portable, can predict phonon dispersion curvesand optical spectra, and it can be used to perform moleculardynamics simulations.Gábor Csányi and Chris J Pickard are in the TCM Group atthe Cavendish Laboratory, Cambridge University (www-cmt.phy.cam.ac.uk)

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7S O F T W A R E C H A L L E N G E S A N D S O L U T I O N S J U N E 2 0 0 4

Careful measurements of the asymmetry between matter andantimatter made at the Stanford Linear Accelerator Center(SLAC) are often reported in Physics World. The articles con-centrate on the physics results emerging from the BaBar exper-iment and what they mean for our understanding of theuniverse. However, the results – and those from scores ofphysics experiments worldwide – wouldn’t be possible with-out the development and use of highly sophisticated software.

The BaBar experiment, for example, has more than 7 millionlines of code in its CVS repository (www.cvshome.org), andmost of this has been written in C++ by physicists. This corre-sponds to about 15 000 lines of code per physicist in the collab-oration. In addition to contributing to this formalizedintellectual capital, graduate students, postdocs and some fac-ulty members in the BaBar collaboration develop personalanalysis software that often amounts to tens of thousands oflines per physicist.

Estimates suggest that a significant part (possibly 10 or 20%)of the people cost of a particle-physics experiment is spent onwriting software. This can amount to more than $5m per yearfor an experiment such as BaBar, which involves about 500physicists, and will be proportionately greater for the 2000-physicist experiments that are due to start at the Large HadronCollider (LHC) at CERN in 2007.

Physicist-led software creation can result in long-lived andwell engineered products. However, organizing young physi-cists to simulate a well structured software house, with analy-sis, architecture, code development, quality assurance,exhaustive testing and documentation, is not always easy andis perhaps not even cost-effective.

Normally, software costs in physics are evaluated on thebasis that “physicists are free”. This approximation has themerits of ignoring the grey area between purely writing soft-ware and purely doing physics, and it is within this approxima-tion that I examine the role of software more systematically,starting with the accelerators that create collisions.

Accelerators comprise many complex devices, and com-puter-aided design tools are essential to their design and ongo-ing improvement. More specialized software is used to designthe electromagnetic structure of accelerators. This includes thewidely used MAFIA code (www.cst.de/Content/Products/MAFIA/Overview.aspx) and more specialized codes (sci-dac.nersc.gov/accelerator).

The accelerator-physics community is still far from havingfully predictive models for the behaviour of complex accelera-tors, but this goal seems attainable. During operation an accel-erator requires real-time measurement-and-control systems,usally developed and maintained by 10 or more software engi-neers. Limited use is made of widely applicable control andcommunication tools (e.g. EPICS:www.aps.anl.gov/epics).

An accelerator produces collisions whose products are

detected by one ormore detectors –massive devicesthat weigh thou-sands of tons andcontain millions ofsmaller parts. Theacquisition of datafrom detectors, andtheir control andmonitoring, are

controlled by many hundreds of thousands of lines of physi-cist-written (and thus “free”) code that must almost always bespecific to the detailed hardware in each experiment.

Collisions, and the resultant detector response, must also besimulated so that a comparison between real and simulateddata can be used to make precise measurements of physicalparameters and, as particle physicists always hope, new orcompletely unexpected discoveries. Simulation toolkits arewidely reused and are increasingly being developed withgreater applicability in mind, such as applications in space andmedicine. The best known example is the Geant 4 toolkit forthe simulation of the passage of particles through matter – theresult of more than 300 person-years of effort, most of it sup-plied by physicists (geant4.web.cern.ch/geant4). A potentialrival is the FLUKA simulation package (www.fluka.org).

Precision in particle physics requires high statistics, leadingto a decades-long preoccupation with the efficient manage-ment of data and a fascinating interplay between home-madeand commercial software. Mass-storage management is a typi-cal case. To put what follows in context, bear in mind that thecost of data-management software for a project like BaBar isclose to $1m per year when both cash and effort are included.

Traditionally, every major lab wrote its own system to man-age the flow of data between disk and tape. Between 1997 and2001 it seemed that IBM’s High Performance Storage System(HPSS: www4.clearlake.ibm.com/hpss/index.jsp) might relievelabs of this chore at the relatively low cost of about $150 000per year, but several have now reverted to writing and main-taining their own more tailored systems.

SLAC has shown that a commercial object database system,Objectivity DB (www.objectivity.com), can succeed in thedatabase-like task of storing and retrieving billions of objectsin a petabyte store, but it is now migrating towards the ROOTsystem developed by the particle-physics community (root.-cern.ch) for improved compatibility with other organizations.

Although many high-energy physicists use Microsoft prod-ucts frequently, Linux is the platform of preference for physicsanalysis, and LaTeX is invariably used to prepare publications.Excel might be used for budget planning, but not even seriousscientific analysis packages can displace tools written by thecommunity (e.g. PAW and ROOT) for interactive analysis andthe preparation of publishable plots.Richard P Mount is director of computing services andassistant director of the research division at the StanfordLinear Accelerator Center (www.slac.stanford.edu)

High-energy challenges for softwareThe particle-physics communityexpects a great deal from its software,as Richard P Mount explains

Geant 4 simulation of an event at the LHC.

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Images are courtesy of the SOHO/LASCO consortium. SOHO is a project ofinternational cooperation between ESA and NASA.

9S O F T W A R E C H A L L E N G E S A N D S O L U T I O N S J U N E 2 0 0 4

Eduserv Chest is a negotiation and licensing service for aca-demic institutions, with a mission to provide to them with best-value software licences under the most appropriate terms andconditions. By representing the buying power of all universi-ties in the UK and Ireland, we bring large savings to the com-munity that we represent.

We can also reduce the overhead costs for suppliers (whoneed fewer sales staff and eliminate both credit collection andadministration costs) and pass those savings on to our sites.Chest does not pursue any agreement that does not offer addedvalue to the community in terms of pricing and conditions. In15 years of operation the company has generated savingsagainst list prices well in excess of £1 bn.

Wherever practical, Chest negotiates for a site-wide licence(covering all of the staff and students at an institution),enabling “free at the point of use” accessibility. Where soft-ware is specialist in nature and the site licence model is notappropriate, we will seek a departmental, volume or concur-rent user licence, as required.

Many of the desktop applications at UK and Ireland univer-

sities will have been provided through a Chest agreement.Typically our agreements run for three years and offer the lat-est version of the software, including upgrades throughout thelicence period, plus technical product support for an annual feethat is significantly lower than is generally available. Manyagreements that we have negotiated for universities alsoinclude the right to use, in perpetuity, the version installed atthe end of the agreement.

Eduserv Chest is community driven and operates a “wishlist” for products that are not in our portfolio but that the acad-emic community would like to see made available, and henceaffordable, under a Chest agreement.

The benefits brought to the community by Chest have earnedplaudits from consortia around the world and our approach hasbeen emulated in a number of countries. Moreover, within theUK, the National Audit Office and the Office of GovernmentCommerce have both cited Chest as an example of best prac-tice.

So what would you, as a physicist working or teaching in auniversity, like to see in your CD wallet in the coming year?Do you currently use software that is out of date because theupgrade is too expensive? Would you like to see your studentsusing the latest technology but wonder how this could be madeaffordable? If your answer is yes to one or more of these ques-tions, simply visit our “wish list” at www.eduserv.org.uk/chest/future-agreements/index.html and let Chest do the workfor you.Nikki Green is the manager of Eduserv Chest (www.eduserv.org.uk)

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Service at +1-215-382-9800 worldwide or toll free at +1-800-447-SIAM in USAand Canada; Fax: +1-215-386-7999; E-mail: service@siam.org · Send check ormoney order to: SIAM, 3600 University City Science Center, Philadelphia, PA19104-2688 USA

10 S O F T W A R E C H A L L E N G E S A N D S O L U T I O N S J U N E 2 0 0 4

The telecoms industry has experienced an unprecedentedgrowth in the deployment of optical fibre to the home, with thegoal of delivering broadband content to individual users. So farmuch of this deployment has been in Asia, with Japan currentlyhaving more than 4 million optical fibre subscribers.

The success of future fibre-to-the-home deployments willdepend on the availability of cheap, robust optical processorsthat allow multiple information channels to be received andtransmitted through a single optical fibre simultaneously. Forthe end user, optical processors establish a broadband bidirec-tional link with the content provider. Enablence Inc has usedthe FEMLAB multiphysics package from COMSOL (www.comsol.com) to design planar lightwave photonic processorsbased on our proprietary Dispersion Bridge technology.

Waveguide structures consist of a core region into which thelight from an optical fibre is transferred, and cladding materialthat is used as an optical insulator in the photonic chip.Creating waveguide structures can be very complicatedbecause arbitrary intensity distributions must be generatedthrough the core to ensure that the devices perform as required.

FEMLAB software was used as a computational platformbecause its powerful adaptive mesh capabilities work equallywell for waveguides of any geometry and refractive index con-trast, including those that comprise very thin layers or com-posite cores. Additionally, by using FEMLAB’s multiphysicscapabilities, it was possible to create algorithms that can simu-late inhomogeneous and anisotropic materials. This allowedmechanical stresses to be included in the analysis, whichmeant that we could model the impact of different growth andannealing temperatures during the manufacturing process.Such computations gave precise values for the stress-inducedvariations in the refractive index of the cores of the circuits.

Periodic boundaries are also an issue of concern. A devicemight have a large number of waveguide cores next to eachother that extend across the width of a device. However,restrictions on computer memory and processing time meanthat it is only feasible to perform detailed modelling on a smallregion. FEMLAB allowed boundaries to be set so that theyacted as a mirror on each side, approximating how cores in theactual device function.

Optical processors with unparalleled performance have nowbeen designed and made by Enablence. The Matlab packagewas used to optimize the device geometries, while FEMLABwas used to investigate device performance by computing thewaveguide modes and their propagation properties. This workresulted in the discovery of novel processor architectures thathave yielded high-performance, small-footprint devices.Serge Bidnyk is director of optical design at Enablence Inc(www.enablence.com)

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Mathematica 5.0 was released in 2003, some 15 years after ver-sion 1.0. As a “system for doing mathematics by computer”, itaddresses all technical requirements – computation, visualiza-tion, programming and publication – by providing more than1500 functions for symbolic and numerical computation,graphics, communication between different processes andtechnical document production. Designed by Stephen Wolf-ram, a theoretical physicist, it is coherent, comprehensive anda “natural” environment for analysing physical systems.

Mathematica’s computational kernel uses state-of-the-artalgorithms. Fast floating-point numerical computation is com-plemented by arbitrary precision arithmetic, interval arith-metic and symbolic computation. Hybrid symbolic-numericcomputation, using computer algebra to replace hand compu-tation, improves both the speed and the accuracy of the calcu-lations. More convenient than FORTRAN or C, it isstraightforward to use the MathLinkcommunication protocol to link in exter-nal code, if required.

The Notebooks graphical user inter-face combines text, interactive pro-grams, graphics, animations and sound.Notebooks can also replace traditionallaboratory notebooks for recording data,analysis, curve fitting and plotting,thereby simplifying the production oftechnical documents. Mathematica isalso an excellent teaching tool, and itsslide show environment is superior to PowerPoint: it may beless flashy but it can display equations, graphics and anima-tions interactively.

The package also offers a large number of features that willappeal to physicists, such as vector calculus (grad, div, curletc), Fourier and Laplace transforms, special functions (Besselfunctions, spherical harmonics and many more), Clebsch–Gordan coefficients, Feynman diagrams, and physical con-stants (library.wolfram.com/infocenter/BySubject/Science/Physics). Mathematica also allows the numerical and symboliccomputation of integrals and solutions to differential equa-tions. This combination of features makes the system uniquelyappropriate to researchers in the physical sciences.

The learning curve is steep, but there are parallels to learningphysics. Initially one may be overwhelmed by the number offunctions in the system. However, like physics, there are onlya small number of unifying principles that, once understood,allow rapid progress in understanding the whole system. Forexample, data and programs are just symbolic expressions.This means that any function can provide input for, or acceptoutput from, any other relevant function. The richness of thelanguage and the system design also encourage and rewardfurther study. Best of all, Mathematica is fun to use.Paul Abbott is a senior lecturer in the School of Physics,University of Western Australia (physics.uwa.edu.au)

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