# S-Matrix and the Grid - Community Grids Lab

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```					  S-Matrix and the Grid
Geoffrey Fox
Professor of Computer Science, Informatics, Physics
Pervasive Technology Laboratories
Indiana University Bloomington IN 47401
December 12 2003

gcf@indiana.edu
http://www.infomall.org
1
S-Matrix and PWA
   We need an amplitude analysis to find most “interesting” resonances
   If this makes sense, we are effectively parameterizing photon-Reggeon
amplitude with resonance at “top” vertex in full (123 in diagram) or
partial (12, 23, 31) channel
• Complicated as off diagonal, one “fake” particle and often more
than 2 final particles
   This requires a lot of approximations whose effect can be estimated
with S-Matrix Theory
• Analyticity, Unitarity, Crossing, Regge Theory, Spin formalism,
Duality, Finite Energy Sum Rules
Regge in Top Vertex    1
                               
Reggeon                                    2
Exchange                    Exchange for
Production
Target                                                               3
2
Some Lessons from the past I
   All confusing effects exist and no fundamental (correct) way to
remove. So one should:
• Minimize effect of the hard (insoluble) problems such as
“particles from wrong vertex”, “unestimatable exchange
effects” sensitive to slope of unclear Regge trajectories,
absorption etc.
• Carefully identify where effects are “additive” and where
confusingly overlapping
   Note many of effects are intrinsically MORE important in
multiparticle case than in relatively well studied π N  π N
   Try to estimate impact of uncertainties from each effect on results
• It would be very helpful to get systematic very high statistic
studies of relatively clean cases where spectroscopy may be less
interesting but one can examine uncertainties
• Possibilities are A1 A2 A3 B1 peripherally produced and even π
N  π π N; K or π beams good
3
S-Matrix Approach
   S-Matrix ideas that work reasonably include:
   Regge theory for production process
   Two-component duality adding Regge dual to Regge to
background dual to the Pomeron
• Can help to identify if a resonance is classic qq or exotic
   Use of Regge exchange at top vertex to estimate high
partial waves in amplitude analysis
   Finite Energy Sum Rules for top vertex as constraints
on low mass amplitudes and most quantitative way of
   Ignore Regge Cuts in Production
   Unitarity effects not included directly due to duality
double counting                                                 4
Investigate Uncertainties
   There are several possible sources of error
• Errors in Quasi 2-body and limited number of amplitudes
approximation
• Unitarity (final state interactions)
• Errors in the two-component duality picture
• Exotic particles are produced and are just different
• Photon beams, π exchange or some other “classic effect” not
present in original πN analyses behaves unexpectedly
• Failure of quasi two body approximation
• Regge cuts cannot be ignored
• Background from other channels
   Develop tests for these in both “easy” cases (such as “old” meson
beam data) and in photon beam data at Jefferson laboratory
• Investigate all effects on any interesting result from PWA
5
Grid Computing: Making The Global
Infrastructure a Reality
   Note book with
Fran Berman and
Anthony J.G. Hey,
   ISBN: 0-470-85319-0
   Hardcover 1080 Pages
   Published March 2003
   http://www.grid2002.org
   I had more fun in days gone by; no
more do I write
   “Skeletons in the Regge
Cupboard” or
   “The Importance of being an
Amplitude”                           6
   A talk on Grid and e-Science was webcast in an Oracle
technology series
http://grids.ucs.indiana.edu/ptliupages/publications/GapAnalysis30June03v2.pdf
   This presentation is at
http://grids.ucs.indiana.edu/ptliupages/presentations
   Next Semester – course on “e-Science and the Grid”
given by Access Grid
   Write up for May Conference describes proposed
Physics Strategy
http://grids.ucs.indiana.edu/ptliupages/publications/gluonic_gcf.pdf
http://grids.ucs.indiana.edu/ptliupages/presentations/pwamay03.ppt

7
   e-Business captures an emerging view of corporations as
dynamic virtual organizations linking employees, customers
and stakeholders across the world.
• The growing use of outsourcing is one example
   e-Science is the similar vision for scientific research with
international participation in large accelerators, satellites or
distributed gene analyses.
   The Grid integrates the best of the Web, traditional
enterprise software, high performance computing and Peer-
to-peer systems to provide the information technology
infrastructure for e-moreorlessanything.
   A deluge of data of unprecedented and inevitable size must
be managed and understood.
   People, computers, data and instruments must be linked.
   On demand assignment of experts, computers, networks and
storage resources must be supported                           8
What is a High Performance Computer?
   We might wish to consider three classes of multi-node computers
   1) Classic MPP with microsecond latency and scalable internode
bandwidth (tcomm/tcalc ~ 10 or so)
   2) Classic Cluster which can vary from configurations like 1) to 3)
but typically have millisecond latency and modest bandwidth
   3) Classic Grid or distributed systems of computers around the
network
• Latencies of inter-node communication – 100’s of milliseconds
but can have good bandwidth
   All have same peak CPU performance but synchronization costs
increase as one goes from 1) to 3)
   Cost of system (dollars per gigaflop) decreases by factors of 2 at
each step from 1) to 2) to 3)
   One should NOT use classic MPP if class 2) or 3) suffices unless
some security or data issues dominates over cost-performance
   One should not use a Grid as a true parallel computer – it can link
parallel computers together for convenient access etc.
9
Sources of Grid Technology
   Grids support distributed collaboratories or virtual
organizations integrating concepts from
   The Web
   Agents
   Distributed Objects (CORBA Java/Jini COM)
   Globus, Legion, Condor, NetSolve, Ninf and other High
Performance Computing activities
   Peer-to-peer Networks
   With perhaps the Web and P2P networks being the most
important for “Information Grids” and Globus for
“Compute Grids”
   Service Architecture based on Web Services most
critical feature
10
Typical Grid Architecture

Portal        User
Services     Services

System            Application          System
Services            Service            Services

Middleware

System             System           System
Services           Services         Services
“Core”
Grid
Raw (HPC)
Resources       Database
11
A typical Web Service
   In principle, services can be in any language (Fortran .. Java ..
Perl .. Python) and the interfaces can be method calls, Java RMI
Messages, CGI Web invocations, totally compiled away (inlining)
   The simplest implementations involve XML messages (SOAP) and
programs written in net friendly languages like Java and Python

Web Services                                     Payment
Credit Card
WSDL interfaces

Portal
Service        Security         Catalog

WSDL interfaces              Warehouse
Web Services                                   Shipping
control
12
What is Happening?
   Grid ideas are being developed in (at least) two
communities
• Web Service – W3C, OASIS
• Grid Forum (High Performance Computing, e-Science)
   Service Standards are being debated
   Grid Operational Infrastructure is being deployed
   Grid Architecture and core software being developed
   Particular System Services are being developed
“centrally” – OGSA framework for this in
   Lots of fields are setting domain specific standards and
building domain specific services
   There is a lot of hype
   Grids are viewed differently in different areas
• Largely “computing-on-demand” in industry (IBM, Oracle,
HP, Sun)
• Largely distributed collaboratories in academia        13
Technical Activities of Note
   Look at different styles of Grids such as Autonomic (Robust
Reliable Resilient)
   New Grid architectures hard due to investment required
   Critical Services Such as
• Security – build message based not connection based
• Metadata – Use Semantic Web, provenance
• Databases and repositories – instruments, sensors
• Computing – Submit job, scheduling, distributed file
systems
• Visualization, Computational Steering
• Fabric and Service Management
• Network performance
   Program the Grid – Workflow
   Access the Grid – Portals, Grid Computing Environments
14
Issues and Types of Grid Services
       1) Types of Grid                               7) Information Grid Services
•        R3                                          • OGSA-DAI/DAIT
•        Lightweight                                 • Integration with compute resources
•        P2P                                         • P2P and database models
•        Federation and Interoperability
       2) Core Infrastructure and Hosting             8) Compute/File Grid Services
Environment                                      • Job Submission
•        Service Management                          • Job Planning Scheduling
•        Component Model                                 Management
•        Messaging                                       Computers
       3) Security Services                             • Replica (cache) Management
•        Certificate Authority                       • Virtual Data
•        Authentication                              • Parallel Computing
•        Authorization
•        Policy                                    9) Other services including
       4) Workflow Services and Programming             • Grid Shell
Model                                         • Accounting
•        Enactment Engines (Runtime)                 • Fabric Management
•        Languages and Programming                   • Visualization Data-mining and
•        Compiler                                        Computational Steering
•        Composition/Development                     • Collaboration
       5) Notification Services                       10) Portals and Problem Solving
       6) Metadata and Information Services                Environments
•        Basic including Registry
•        Semantically rich Services and meta-      11) Network Services
data                                        • Performance
•        Information Aggregation (events)            • Reservation
15
•        Provenance                                  • Operations
OGSA OGSI & Hosting Environments
   Add OGSI to get a Grid service and a component model
   Add OGSA to get Interoperable Grid “correcting” differences in base platform

Not OGSA                    Domain -specific services

More specialized services: data
Possibly OGSA              replication, workflow, etc., etc.

OGSA                     authorization, monitoring, data
access, etc., etc.
Environment
OGSI on Web Services

Hosting Environment for WS
Given to us from on high
Network                     16
Integration of Data and Filters
   One has the OGSA-DAI Data repository interface
combined with WSDL of the (Perl, Fortran, Python
…) filter
   User only sees WSDL not data syntax
   Some non-trivial issues as to where the filtering
compute power is
• Microsoft says filter next to data

WSDL                      OGSA-DAI
Filter
DB
Of Filter                 Interface

17
Remote Grid Service                                 Remote Grid Service

10: Job                1: Job Management Service
Status       (Grid Service Interface to user or program client)

1: Plan Execution                  4: Job Submittal

2: Schedule and control Execution

8: Virtual
Data

7: Cache                             6: File and
Data       Data        5: Data Transfer        Storage
Replicas                               Access        Data

9: Grid MPI
Technology Components of (Services in)
a Computing Grid                          18
Grid Strategy
   LHC Computing will be very well established and
handling 10-100 times as much data as GlueX when we
need to go into production
   GriPhyn iVDGL EDG EGEE PPDG GridPP will
customize core Grid technology for accelerator-based
experiments
• Transport Data
• Cache Data
• Manage initial data analysis and Monte Carlo
   Not clear if GT2, GT3, OGSI but will certainly be Web
Service based
   Need to keep in close touch with these activities
   Build GlueX physics analysis consistent with this
infrastructure
19
Implementing Grids
    Need to design a service architecture for GlueX
• Build on services from HEP and other fields
• Need some specific gluexML meta-data specifying services
and properties specific to GlueX
• Specify data structures and method interfaces in XML
    Use portlets for user-interfaces as in http://www.ogce.org
    Break-up into services where-ever possible but only if
“coarse-grain”
Closely coupled Java/Python …      Coarse Grain Service Model

Module      Module          Service                    Service
Messages
B           A               B                          A
Method Calls              0.1 to 1000 millisecond latency
.001 to 1 millisecond                                            20
Collage of Portals
Earthquakes – NASA
Fusion – DoE
OGCE Components – NSF
Publications -- CGL

21
Application WS
Approach
   Convert every code into a Web Service
   Convert every utility like
“visualization” into a Web service               WS linking
to user and
   Have good support for authoring and               Other WS
(data sources)
manipulating meta-data
   Use existing code/database technology
Web/OGSA services”
Typical
• XML specification of models,                   codes
computational steering, scale supported
at “Web Service” level as don’t need
“high performance” here
• Allows use of Semantic Grid technology
22
User
Services         Portal              Grid
Services
Computing
Environments
Visualization
Modeling             Service       Fitting
Services                           Service
Data Access
Middleware     Service

System            System          System
“Core”
Services          Services        Services     Grid
(Globus)
Raw Data and
Compute
Resources Database
23
CERN LHC Data Analysis Grid

24

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