260
C. W. Fabjan and D. Fournier
Fig. 6.41 Estimated muon spectra from various sources in the ATLAS Muon Spectrometer
MET is a key signature, e.g. for SUSY and/or dark matter searches. Very highperformance jet spectroscopy is also one of the principal design considerations for
future Collider Detectors. The resolution and linearity of the jet energy reconstruction is the principle performance criterion.
The measured jet energy has to be related to the corresponding parton (quark,
gluon) energy in a sequence of complex steps. Initial and final state gluon
radiation and parton fragmentation affect the observable particle composition and
momenta in the jet, limiting the ‘intrinsic’ parton energy resolution to order
σ (E parton )/E ≈ 0.5/
√
E parton (GeV) [117]. Experimental factors—different response
as a function of particle species and momentum, nonlinearities, insensitive detector
areas, signal noise, magnetic field—require large corrections. Finally, jets are not
uniquely defined objects. Different procedures are used to attribute a particle to
a given jet. The choice of ‘jet algorithms’ influences the energy attributed to
the jet, as do the additional particles in the ‘underlying’ event or particles from
other collisions, recorded with the jet (‘pile-up’) [117, 118]. Two classes of jet
algorithms have been widely used: The cone-algorithm draws a cone in the η-ϕ
space with radius R =
√
[(ϕ) 2 + (η) 2 ] around a ‘seed’, an energy deposit above
a certain threshold, calculates the total transverse energy E T =
E Tparticles and
the E T position and iterates around the new cone position until a stable result is
obtained. This algorithm is sensitive to soft radiation effects; its well-defined jetboundary however eases corrections due to the underlying event produced in the
hadron collision. The k T —algorithm clusters particles according to their relative
transverse momenta over the η-ϕ space, controlled by a size parameter D. This
algorithm is theoretically attractive, because in principle infrared and collinear
C. W. Fabjan and D. Fournier
Fig. 6.41 Estimated muon spectra from various sources in the ATLAS Muon Spectrometer
MET is a key signature, e.g. for SUSY and/or dark matter searches. Very highperformance jet spectroscopy is also one of the principal design considerations for
future Collider Detectors. The resolution and linearity of the jet energy reconstruction is the principle performance criterion.
The measured jet energy has to be related to the corresponding parton (quark,
gluon) energy in a sequence of complex steps. Initial and final state gluon
radiation and parton fragmentation affect the observable particle composition and
momenta in the jet, limiting the ‘intrinsic’ parton energy resolution to order
σ (E parton )/E ≈ 0.5/
√
E parton (GeV) [117]. Experimental factors—different response
as a function of particle species and momentum, nonlinearities, insensitive detector
areas, signal noise, magnetic field—require large corrections. Finally, jets are not
uniquely defined objects. Different procedures are used to attribute a particle to
a given jet. The choice of ‘jet algorithms’ influences the energy attributed to
the jet, as do the additional particles in the ‘underlying’ event or particles from
other collisions, recorded with the jet (‘pile-up’) [117, 118]. Two classes of jet
algorithms have been widely used: The cone-algorithm draws a cone in the η-ϕ
space with radius R =
√
[(ϕ) 2 + (η) 2 ] around a ‘seed’, an energy deposit above
a certain threshold, calculates the total transverse energy E T =
E Tparticles and
the E T position and iterates around the new cone position until a stable result is
obtained. This algorithm is sensitive to soft radiation effects; its well-defined jetboundary however eases corrections due to the underlying event produced in the
hadron collision. The k T —algorithm clusters particles according to their relative
transverse momenta over the η-ϕ space, controlled by a size parameter D. This
algorithm is theoretically attractive, because in principle infrared and collinear