The search for resonances and hadron spectroscopy is a computationaly intense
endeavour. The data reduction of current data requires working with data sets
that are 10's of terrabytes in size and development of algorithems to both
maniipulat and compress these files are cruicial to the success of the process.
In terms of analysis, the partial wave analyses that are carried out require computer
resources to both generate large Monte Carlo data sets as well as analze the
data to extract resonsnce signatures.
Over the past several years, we have developed a large suite of tools at CMU that
facilitate this analysis. These include analysis tools for manipulating data from
the CLAS experiment at Jefferson Lab---
the COBRA tools which faciliate
easy access and compressed storage to CLAS data.
A tool for carrying out quantum field theory calculations has also been developed:
qft++ and an article has been written
describing this work: Numerical Object
Oriented Quantum Field Theory Calculations. This tool set allows us to compute
the needed physics amplitudes for our partial wave analysis using a covariant tensor
We have also developed a background subtraction method that is appropriat for
inclusion in unbinned maximum likelihood fits.
Separating Signals from Non-Interfering Backgrounds using Probabilistic Event Weightings
The precedure is a generalization of sideband subtraction to high-dimension data sets by
defining a set of nearest neighbors for each event. It allows each event to be assigned
a quality factor that indicates the probability the event is signal or background.
Our work is carried out on a 286-core processor farm
which we share with our lattice QCD colleagues at CMU. The farm has about 20 terrabytes
of data storage and is built primarily with dual-quad-core AMD chips in 32 blade servers
connected using a private channel-bonded gigabit network.
We are currently funded by an NSF Physics at the
information Frontier (PIF)
grant to develop grid-enabled partial wave
analysis tools. This latter effort is
collaborative bewteen Carnegie Mellon, University of Connecticut and Indiana University.