Preliminary List of Plenary/Invited Talks

P. Bhat (FNAL),
"RunII Physics at Fermilab and Advanced Data Analysis Methods"

The collider Run II now underway at the Fermilab Tevatron brings extraordinary opportunities for new discoveries, precision measurements, and exploration of parameter spaces of theoretical models. We hope to discover the Higgs boson and find evidence for new physics beyond the Standard Model such as Supersymmetry or Technicolor or something completely unexpected. We will pursue searches for hints for the existence of extra dimensions and other exotic signals. These opportunities, however, come with extraordinary challenges. In this talk, I will describe the physics pursuits of the CDF and DZero experiments in Run II and discuss why the use of multivariate and advanced statistical techniques will be crucial in achieving the physics goals.

N. Brook (LHCb, Bristol Univ.),
"LHCb Computing and the GRID"

The main requirements of the LHCb software environment in the context of GRID computing will be presented. Emphasis will be given to the preliminary experiences gained in the development of a distributed Monte Carlo production system.

R. Brun (Alice, CERN),
"Computing at ALICE"

The ALICE software is based on three major components AliRoot, Alien and ROOT that are in constant development and on exernal packages like Geant3, Pythia and Fluka. The AliRoot framework is totally written in C++ and includes classes for detailed detector simulation and reconstruction. This framework has been extensively used to test the complete chain from data acquisition to data storage and retrieval during several Alice data Challenges. The software is GRID-aware via the Alien system presented in another talk. The detector simulation part is based on the concept of a Virtual Monte Carlo. The same detector geometry classes and hits/digits are used to run with the Geant3 or Geant4 packages and an interface with Fluka is in preparation. When running with a very large number of classes (thousands) it is important to minimize the classes dependencies. Access to the large object collections is via the Folder mechanism available in Root. This structure is not only more scalable but allows simple user to easily browse and understand the various data structures. The fact that the Alice environment is based on a small number of components has greatly facilitated the maintenance, the developement and the adoption of the system by all physicists in the collaboration.

D. Buskulic (VIRGO, LAPP),
"Data Analysis Software Tools used during VIRGO Engineering Runs, review and future needs"

During last years, data flow and data storage needs for large gravitational waves interferometric detectors have reached an order of magnitude similar to high energy physics experiments.Software tools have been developed to handle and analyse those large amounts of data, with the specificities associated to gravitational waves search. We will make a review of the experience acquired during engineering runs on the VIRGO detector with the currently used data analysis software tools, pointing out the peculiarities inherent to our type of experiments. We will also show what are the possible future needs for the Virgo data offline analysis.

C. Charlot (CMS, LLR-Ecole Plytechnique CNRS),
"CMS Software and Computing"

CMS is one of the two general-purpose HEP experiments currently under construction for the Large Hadron Collider at CERN. The handling of multi-petabyte data samples in a worldwide context requires computing and software systems with unprecedented scale and complexity. We describe how CMS is meeting the many data analysis challenges in the LHC era. We cover in particular the status of our object-oriented software, our system of globally distributed regional centres and our strategies for Grid-enriched data analysis.

B. Denby (Versailles Univ.),
"Swarm Intelligence for Optimization Problems"

It has long been known that ensembles of social insects such as bees and ants exhibit intelligence far beyond that of the individual members. More recently, optimisation algorithms which attempt to mimic this 'swarm intelligence' have begun to appear, and have been applied with considerable success to a number of real world problems. The talk will first cite examples of naturally occurring swarm intelligence in bees and ants before passing to a concrete application of Ant Colony Optimisation to adaptive routing in a satellite telecommunications network. Analogies to other types of optimisation such as gradient descent and simulated annealing will be also given. Finally, some ideas of further applications in scientific research will be suggested.

E. de Doncker (W. Michigan Univ.),
"Methods for enhancing numerical integration"

As we consider common strategies for numerical integration (Monte-Carlo, Quasi-Monte Carlo, adaptive), we can delineate their realm of applicability. The inherent accuracy and error bounds for basic integration methods are given via such measures as the degree of precision of cubature rules, the index of a family of lattice rules, and the discrepancy of (deterministic) uniformly distributed point sets. Strategies incorporating these basic methods are built on paradigms to reduce the error by, e.g., increasing the number of points in the domain or decreasing the mesh size, locally or uniformly. For these processes the order of convergence of the strategy is determined by the asymptotic behavior of the error, and may be too slow in practice for the type of problem at hand. For certain problem classes we may be able to improve the effectiveness of the method or strategy by such techniques as transformations, absorbing a difficult part of the integrand into a weight function, suitable partitioning of the domain and extrapolation or convergence acceleration processes. Situations warranting the use of these techniques (possibly in an "automated" way) will be described and illustrated by sample applications.

W. Dunin-Barkowski (IPPI/Texas Tech. Univ),
"Great Brain Discoveries: When White Spots Disappear?"

Knowledge progress about a particular object (e.g. , brain) has characteristics of exponential growth in a limited volume. As soon as you know that a visible part of the whole volume is filled (1/2, 1/10, 1/1000 or 1/10000 - doesn't matter), the time for the volume be all filled has almost come. The time scale is in units of a total duration of the process of the filling in the limited volume, if you have started from zero level. We didn't know how much we were ignorant about the brain even decade ago. The whole brain was just Terra Incognito. But recent progress in computational neuroscience shows that presently we know about 1/10 (and not less than 1/100000) of all brain network mechanisms. That's why we can say that we are dealing with white spots on the map of knowledge about the brain and not with the Terra Incognito any more. The time for full understanding of the brain is not far from now (several years by cautious estimates). A couple of well understood mechanisms of brain functioning (work of synchronous/asynchronous neuron ensembles in cortex, cerebellar data prediction machinery, etc.) will be exposed in the talk.

D. Green (IBM EMEA),
"IBM experience in GRID"

To many industry watchers Grid Technology represents the next wave of distributed computing in which companies can share IT infrastructure and IT services within or between enterprises - so go as far as saying that it will replace the internet. Grid Technology provides the answer to the question facing many IT managers: "How will my organisation ensure that its IT infrastructure is sufficiently flexible to support a rapidly changing global market?". It tackles the challenges faced when users need to access data/IT services from anywhere in the organisation and with the added complexity of potential for mergers/acquisitions while at the same time allowing for the possibility of embracing e-utility services. IBM was the first major company to commit to support the Grid movement and contribute to the open-source development community - some see this as a visionary move, giving a potential for IBM to dominate the IT industry for decades. The presentation arm you with an understanding of what IBM sees as 'Grid Computing' and how it may change the way we use IT. The discussion will provide an indication of the challenges facing an organisation wishing to invest in grid technology and explain why IBM is so interested in overcoming the many difficulties yet remaining to be solved.

F. James (CERN),
"Summary of Recent Ideas and Discussions on Statistics in HEP"

Starting with the Confidence Limits Workshop at CERN in January 2000, a series of four meetings has brought together particle physicists to discuss and try to settle some of the major outstanding problems of statistical data analysis that continue to cause disagreement among experts. These were the first international conferences devoted exclusively to statistics in HEP, but they will not be the last. In this talk, I will summarize the main ideas that have been treated, and in a few cases, points that have been agreed upon.

R. Jones (ATLAS, Univ. of Lancaster),
"ATLAS Computing and the Grid"

ATLAS is building a Grid infrastructure using middleware tools from both European and American Grid projects. As such, it plays an important role in ensuring coherence between projects. Various Grid applications are being build, some in collaboration with LHCb. These will be exercised and refined, along with our overall computing model, by means of a series of Data Challenges of increasing complexity.

M. Kasemann (FNAL),
"The LCG project - common solutions for LHC"

Four LHC experiments are developing software for all aspects of data analysis. Joint efforts and common projects between the experiments and the LHC Computing Grid Project are underway to minimize costs and risks. However, the experiments are different from one another, the right balance between a single set of methods and tools and experiment specific solutions must be found. Data Challenges of increasing size and complexity will be performed as milestones along the way towards completion until LHC start-up to verify the solutions found and to measure the readiness for data analysis.

P. Krokovny (Belle, BINP),
"Belle computing"

Belle is a high luminosity asymmetric e+/e- collider experiment designed to investigate the origins of CP violation and other physics. An important aspect of this experiment is a computing system. The details of the Belle offline reconstruction and Monte Carlo production scheme will be discussed at the conference.

P. Kunszt (CERN),
"Status of the EU DataGrid Project"

The EU DataGrid project has as its aim to develop a large-scale research testbed for Grid computing. Three major application domains have already been running demonstrations: Particle physics, Earth observation and Biomedics. The project is in the middle of its second year and has successfully passed its first EU independent review. The DataGrid testbed is up and running at the several project sites and is growing in functionality with each new release. We discuss the status of the project and the evolution foreseen in the current year, especially in view of the potential impact of the Globus migration to OGSA. We also present the plans of the applications how to exploit this technology in the future. (For more information, see the Web page).

M. Kunze (CrossGRID, FZK),
"The CrossGrid Project"

There are many large-scale problems which require new approaches to computing, such as earth observation, environmental management, biomedicine, industrial and scientific modelling. The CrossGrid project addresses realistic problems in medicine, environmental protection, flood prediction, and physics analysis and is oriented towards specific end-users: Corresponding applications will be based on Grid technology and could be complex and difficult to use: the CrossGrid project aims at developing several tools which will make the Grid more friendly for average users. Portals for specific applications will be designed, which should allow for easy connection to the Grid, create a customised work environment, and provide users with all necessary information to get their job done.

L. Litov (NA48, JINR),
"Particle identification in the NA48 experiment using neural network"

The Na48 detector situated at CERN SPS accelerator is designed for precise measurement of direct CP-violation in the neutral kaon system. A large programme for investigation of rare Ks, K+/-, neutral hyperon decays and measurement of CP violating asymmetry in charged kaon decays with unprecedented precision is envisaged. In order to suppress the background for some of the rare kaon and neutral hyperon decays, a good particle identification is required. The possibility to use a feed-forward neural networks to separate electrons from hadrons is considered. To test the performance of the neural network, electrons and pions from clearly reconstructed experimental kaon decays have been used. It is shown, that the neural network can be a powerful tool for particle identification. A significant suppression of the background can be reached allowing a precise measurement of rare decays parameters.

M. Neubauer (CDF, MIT),
"Computing at CDF"

Run II at the Fermilab Tevatron Collider began in March 2001 and will continue to probe the high energy frontier in particle physics until the start of the LHC at CERN. It is expected that the CDF collaboration will store up to 10 Petabytes of data onto tape by the end of Run II. Providing efficient access to such a large volume of data for analysis by hundreds of collaborators world-wide will require new ways of thinking about computing in particle physics research. In this talk, I discuss the computing model at CDF designed to address the physics needs of the collaboration. Particular emphasis is placed on current development of a O(1000) processor PC cluster accessing O(200 TB) of disk at Fermilab serving as the Central Analysis Facility for CDF and the vision for incorporating this into a decentralized (GRID-like) framework.

G. Passarino (Univ. of Turin),
"A Frontier in Multiscale Multiloop Integrals: the Algebraic-Numerical Method."

Schemes for systematically achieving accurate numerical evaluation of arbitrary multi-loop Feynman diagrams are discussed. The role of a reliable approach to the direct and precise numerical treatment of these integrals in producing a complete calculation for two-loop Standard Model predictions is also reviewed.

L. Robertson (LCG, CERN),
"The LHC Computing Grid Project - Creating a Global Virtual Computing Centre for Particle Physics"

The computing needs of LHC will require enormous computational and data storage resources, far beyond the possibilities of a single computing centre. Grid technology offers a possible solution, tying together computing resources available to particle physics in the different countries taking part in LHC. A major activity of the LHC Computing Grid Project (LCG) is to develop and operate a global grid service, capable of handling multi-PetaByte data collections while providing levels of reliability, usability and efficiency comparable with those available in scientific computing centres.

P. Shawhan (LIGO, Caltech),
"LIGO Data Analysis"

The Laser Interferometer Gravitational-Wave Observatory (LIGO) project has constructed two 'observatories' in the United States which are poised to begin collecting scientifically interesting data. Members of the LIGO Scientific Collaboration have been using data from recent 'engineering runs' to develop and refine signal detection algorithms and data analysis procedures. I will describe a few distinct LIGO data-analysis tasks which vary greatly in their computational demands, and thus will be addressed in different ways. I will also comment on some of the organization and implementation challenges which have been encountered so far.

O. Tatebe (NIAIST, Tsukuba),
"Grid Datafarm Architecture for Petascale Data Intensive Computing"

The Grid Datafarm architecture is designed for global petascale data-intensive computing. It provides a cluster-of-cluster parallel filesystem with online petascale storage, scalable I/O bandwidth, and fault tolerance. Gfarm parallel I/O APIs and file affinity scheduling support scalable I/O bandwidth exploiting local I/O in a grid of clusters with tens of thousands of nodes in a single filesystem image. Fault tolerance and load balancing are automatically managed by file duplication or re-computation using a command history log. Preliminary performance evaluation has shown scalable disk I/O and network bandwidth on 64 nodes of the Presto III Athlon cluster. The Gfarm parallel I/O write and read operations has achieved data transfer rates of 1.74 GB/s and 1.97 GB/s, respectively, using 64 cluster nodes. The Gfarm parallel file copy reached 443 MB/s with 23 parallel streams on the Myrinet 2000. The Gfarm architecture is expected to enable petascale data-intensive Grid computing with an I/O bandwidth scales to the TB/s range and scalable computational power.

I. Terekhov (D0, FNAL),
"Distributed Computing at D0"

The D0 experiment at FNAL is one of the largest currently running experiments in HEP. Its amount of data, the size of the collaboration, and, most importantly, the degree to which the collaborators are distributed around the world, mandate a highly sophisticated, fully distributed meta-computing system. Its heart is the advanced data handling system called SAM which provides high-level services of a data grid. The areas of most rapid development are job and information management. Job management includes brokering, submission and execution od data analysis jobs; the information services allow monitoring of jobs and the system as a whole. For these, newer services, we actively deploy, integrate and and develop Grid technologies, while collaborating with computer scientists and the various Grid efforts both in the USA and Europe. In this paper, we present the present status and the current plans for the D0 meta-computing system.

A. Vaniachine (ATLAS, ANL),
"Data Challenges in ATLAS Computing"

ATLAS computing is steadily progressing towards a highly functional software suite, plus a World Wide computing model which gives all ATLAS equal and equal quality of access to ATLAS data. A key component in the period before the LHC is a series of Data Challenges of increasing scope and complexity. These Data Challenges will use as much as possible the Grid middleware being developed in Grid projects around the world. We are committed to ^—common solutions^“ and look forward to the LHC Computing Grid (LCG) being the vehicle for providing these in an effective way. In the context of the CERN Review of LHC Computing, the scope and goals of ATLAS Data Challenges are executed at the prototype tier centers, which will be built in the Phase 1 of the LCG project.
In close collaboration between the Grid and Data Challenge communities ATLAS is testing large-scale testbed prototypes around the world, deploying prototype components to integrate and test Grid software in a production environment, and running Data Challenge 1 production in 26 prototype tier centers in 17 countries on four continents.