3,026 research outputs found
Direct jet reconstruction in p + p and Cu + Cu at PHENIX
The Relativistic Heavy Ion Collider collides heavy nuclei at
ultrarelativistic energies, creating a strongly interacting, partonic medium
that is opaque to the passage of high energy quarks and gluons. Direct jet
reconstruction applied to these collision systems provides a crucial constraint
on the mechanism for in-medium parton energy loss and jet-medium interactions.
However, traditional jet reconstruction algorithm operating in the large soft
background at RHIC give rise to fake jets well above the intrinsic production
rate of high-pT partons, impeding the detection of the low cross section jet
signal at RHIC energies. We developed a new jet reconstruction algorithm that
uses a Gaussian filter to locate and reconstruct the jet energy. This algorithm
is combined with a fake jet rejection scheme that provides efficient jet
reconstruction with acceptable fake rate in a background environment up to the
central Au + Au collision at sqrt(s_NN) = 200 GeV. We present results of its
application in p + p and Cu + Cu collisions using data from the PHENIX
detector, namely p + p cross section, Cu + Cu jet yields, the Cu + Cu nuclear
modification factor, and Cu + Cu jet-jet azimuthal correlation.Comment: To be published in the proceedings of DPF-2009, Detroit, MI, July
2009, eConf C09072
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Direct Jet Reconstruction in Proton-Proton and Copper-Copper Collisions at √sNN = 200 GeV
Collision of heavy nuclei at the Relativistic Heavy Ion Collider (RHIC) recreates the state of high temperature quark-gluon plasma that existed shortly after the Big Bang. Measurement using single particle spectra and two-particle correlation shows that this medium is largely opaque to the transit of a high energy quark or gluon. Reconstructing the kinematics of these quarks and gluons can provide additional constraints for the property of their interaction with the medium. While the direct reconstruction of quantum chromodynamics jets, the final state showers of quarks and gluons, has become an indispensable tool at hadron and electron accelerator experiments, the application of this technique to heavy ion collisions at the RHIC energy has been considered a hard problem. The relatively low yield of high transverse momentum jets would have to be detected within a large, fluctuating background that can give rise to a false jet signal. At the RHIC PHENIX experiment, jet reconstruction also has to cope with the limited aperture of the central arm spectrometers. To overcome both problems, which can distort the jet signal in the traditional reconstruction algorithms, this thesis develops an algorithm that reconstructs the jets as maxima of the Gaussian filtered event transverse momentum distribution. The Gaussian angular weighting causes the algorithm to become more sensitive to the jet core versus the jet periphery. It is then combined with a fake jet rejection discriminant to remove the background fluctuation from the jet signal. This algorithm is used to obtain the first jet measurement in heavy ion environment at PHENIX, using data from the 2004/2005 RHIC run. The result includes the proton-proton inclusive jet spectrum, the proton-proton fragmentation function, the copper-copper jet nuclear modification factor, the copper-copper jet central-to-peripheral modification factor, and the copper-copper dijet azimuthal correlation. The measured copper-copper jet nuclear modification factor shows that there is a significant initial state effect to the jet suppression. The observation of no broadening in the copper-copper dijet azimuthal correlation indicates that the traditional energy loss picture via multiple soft scattering may not be applicable to the quark-gluon plasma
Explainable machine learning of the underlying physics of high-energy particle collisions
We present an implementation of an explainable and physics-aware machine
learning model capable of inferring the underlying physics of high-energy
particle collisions using the information encoded in the energy-momentum
four-vectors of the final state particles. We demonstrate the proof-of-concept
of our White Box AI approach using a Generative Adversarial Network (GAN) which
learns from a DGLAP-based parton shower Monte Carlo event generator. We show,
for the first time, that our approach leads to a network that is able to learn
not only the final distribution of particles, but also the underlying parton
branching mechanism, i.e. the Altarelli-Parisi splitting function, the ordering
variable of the shower, and the scaling behavior. While the current work is
focused on perturbative physics of the parton shower, we foresee a broad range
of applications of our framework to areas that are currently difficult to
address from first principles in QCD. Examples include nonperturbative and
collective effects, factorization breaking and the modification of the parton
shower in heavy-ion, and electron-nucleus collisions.Comment: 11 pages, 4 figure
Algebraic Bethe ansatz for the supersymmetric model with reflecting boundary conditions
In the framework of the graded quantum inverse scattering method (QISM), we
obtain the eigenvalues and eigenvectors of the supersymmetric model with
reflecting boundary conditions in FFB background. The corresponding Bethe
ansatz equations are obtained.Comment: Latex file, 23 Page
Reconstructed Jets at RHIC
To precisely measure jets over a large background such as pile up in high
luminosity p+p collisions at LHC, a new generation of jet reconstruction
algorithms is developed. These algorithms are also applicable to reconstruct
jets in the heavy ion environment where large event multiplicities are
produced. Energy loss in the medium created in heavy ion collisions are already
observed indirectly via inclusive hadron distributions and di-hadron
correlations. Jets can be used to study this energy loss in detail with reduced
biases. We review the latest results on jet-medium interactions as seen in A+A
collisions at RHIC, focusing on the recent progress on jet reconstruction in
heavy ion collisions.Comment: Proceedings for the 26th Winter Workshop on Nuclear Dynamic
Momentum matching and band-alignment type in van der Waals heterostructures: Interfacial effects and materials screening
Momentum-matched type II van der Waals heterostructures (vdWHs) have been
designed by assembling layered two-dimensional semiconductors (2DSs) with
special band-structure combinations - that is, the valence band edge at the
Gamma point (the Brillouin-zone center) for one 2DS and the conduction band
edge at the Gamma point for the other [Ubrig et al., Nat. Mater. 19, 299
(2020)]. However, the band offset sizes, band-alignment types, and whether
momentum matched or not, all are affected by the interfacial effects between
the component 2DSs, such as the quasichemical-bonding (QB) interaction between
layers and the electrical dipole moment formed around the vdW interface. Here,
based on density-functional theory calculations, first we probe the interfacial
effects (including different QBs for valence and conduction bands, interface
dipole, and, the synergistic effects of these two aspects) on band-edge
evolution in energy and valley (location in the Brillouin zone) and the
resulting changes in band alignment and momentum matching for a typical vdWH of
monolayer InSe and bilayer WS2, in which the band edges of subsystems satisfy
the special band-structure combination for a momentum-matched type II vdWH.
Then, based on the conclusions of the studied interfacial effects, we propose a
practical screening method for robust momentum-matched type II vdWHs. This
practical screening method can also be applied to other band alignment types.
Our current study opens a way for practical screening and designing of vdWHs
with robust momentum-matching and band alignment type
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