6347081
Calibration of the ATLAS muon spectrometer precision chambers for initial LHC beam collisions
ATLAS is a general purpose experiment at the Large Hadron Collider (LHC) at CERN which began operation in September, 2009. ATLAS has a large muon spectrometer which is designed to measure muon momentum with a resolution ranging from 3% at 100 GeV/c to 10% at 1 TeV for a pseudorapidity range of 0-2.7. In this paper, we describe the derivation and validation of calibration constants for the Monitored Drift Tubes (MDTs) in the ATLAS muon spectrometer for use with initial LHC collisions. At LHC start-up, the luminosity was not sufficient for ordinary calibrations with collision muons, and so alternative methods were developed. The time-to-space (RT) functions were obtained from the University of Michigan gas monitor chamber and the ( t 0 s) were derived from LHC beamsplash events from 2009 and 2010. We have validated these calibration constants by performing muon track reconstruction using 900 GeV collision data from December, 2009 and 7 TeV data from 2010. We find that these calibration constants yield an MDT chamber hit resolution of 142 μ m and a residual width of 91 μ m.
18986664
Discovery Potential of the Standard Model Higgs Boson Through H -> WW Decay Mode with the ATLAS Detector at LHC
We report results of a study of the Standard Model Higgs boson discovery potential through the W-pair leptonic decay modes with the ATLAS detector at LHC at 14 TeV center-of-mass energy. We used MC samples with full detector simulation and reconstruction of the ATLAS experiment to estimate the ATLAS detection sensitivity for the reaction of pp -> H -> WW -> e\nu \mu\nu with no hard jet or two hard jets in the final states. The prospects for the Higgs boson searches at ATLAS are presented, including trigger efficiencies and data-driven methods to estimate the backgrounds using control samples in data. With 10/fb of integrated luminosity, one would expect to discover a Standard Model Higgs boson with ATLAS detector in Higgs boson mass range 135 < m_H < 190 GeV. If the Higgs boson does not exist, we will extend and confirm the exclusion produced by the Tevatron Higgs boson search result, which has ruled out the Higgs boson mass range of 160 < m_H < 170 GeV at 95% confidence level. If Higgs boson would be discovered, ATLAS could measure its mass with a precision of about 2 and 7 GeV for Higgs boson mass around 160 GeV and 130 GeV, respectively.
14739636
High-precision absolute distance measurement using dual-laser frequency scanned interferometry under realistic conditions
In this paper, we report on new high-precision absolute distance measurements performed with frequency scanned interferometry using a pair of single-mode optical fibers. Absolute distances were determined by counting the interference fringes produced while scanning the frequencies of the two chopped lasers. High-finesse Fabry–Perot interferometers were used to determine frequency changes during scanning. Dual lasers with oppositely scanning directions, combined with a multi-distance-measurement technique previously reported, were used to cancel drift errors and to suppress vibration effects and interference fringe uncertainties. Under realistic conditions, a precision about 0:2mm was achieved for a distance of 0.41 m. With a precision that exceeds requirements, the frequency scanned interferometry is a promising high-precision optical alignment technique for International Linear Collider silicon tracker detector.
117928786
Measurement of the $W^+W^-$ Cross Section in 7 TeV pp Collisions with the ATLAS Detector
17983245
Boosted decision trees, a powerful event classifier
Consider the problem of classification of events between signal and background, given a number of particle identification (PID) variables. A decision tree is a sequence of binary splits of the data. To train the tree a set of known training events are used. The results are measured using a separate set of known testing events. Consider all of the data to be on one node. The best PID variable and best place on that variable to split the data into separate signal and background is found. There are then two nodes. The process is repeated on these new nodes and is continued until a given number of final nodes (called “leaves”) are obtained, or until all leaves are pure or until a node has too few events. There are several popular criteria to determine the best PID variable and best place on which to split a node. The gini criterion is used here. Suppose that event i has weight Wi. The purity P of a node is defined as the weight of signal events on the node divided by the total weight of events on that node. For a given node: gini = P (1 − P ) ∑ i Wi. gini is zero for P = 1 or P = 0. The best split is chosen as the one which minimizes gini. The next node to split is chosen by finding that node whose splitting maximizes the change in gini. In this way a decision tree is built. Leaves with P ≥ 0.5 are signal leaves and the rest are background leaves. Decision trees are powerful, but unstable. A small change in the training data can produce a large change in the tree. This is remedied by the use of boosting. For boosting, the training events which were misclassified (a signal event fell on a background leaf or vice versa) have their weights increased (boosted), and a new tree is formed. This procedure is then repeated for the new tree. In this way many trees are built up. The score from the mth individual tree Tm is taken as +1 if the event falls on a signal leaf and −1 if the event falls on a background leaf. The final score is taken as a weighted sum of the scores of the individual leaves. Two methods for boosting are considered here. The first is called AdaBoost. Define errm = weight misclassified/total weight for tree m. Let αm = β log [(1 − errm)/errm], where β is a constant. In the statistical literature β has been taken as one, but for the MiniBooNE experiment, β = 0.5 has been found to be the optimum value. The misclassified events have their weight multiplied by em . The weights are then renormalized so the sum of all of the training event weights is one. The final score is T = ∑Ntree m=1 αmTm. The second method of boosting considered here is called -boost or, sometimes, shrinkage. Misclassified events have their weight multiplied by e , where is a constant. For the MiniBooNE experiment, = 0.03 has been optimum. (The results vary only mildly as β or are changed a bit.) The final score is T = ∑Ntree m=1 Tm. -boost changes weights a little at a time, while AdaBoost can be shown to try to optimize each change in weights to minimize e where T is the score and y is +1 for a signal event and −1 for a background event. The optimum value is F = log prob/(1 − prob), where prob is the probability that y = 1, given the observed PID variables. In practice, for MiniBooNE, the two boosting methods have performed almost equally well. Boosting is described as using many weak classifiers to build a strong classifier. This is seen in Figure 1. After the first few trees, the misclassification fraction for an individual tree is above 40%. In the MiniBooNE experiment some hundreds of possible PID variables have been suggested. The most powerful of these have been selected by accepting those which are used most often as the splitting variable. Some care needs to be taken as some-
14942523
Studies of stability and robustness for artificial neural networks and boosted decision trees
In this paper, we compare the performance, stability and robustness of Artificial Neural Networks (ANN) and Boosted Decision Trees (BDT) using MiniBooNE Monte Carlo samples. These methods attempt to classify events given a number of identification variables. The BDT algorithm has been discussed by us in previous publications. Testing is done in this paper by smearing and shifting the input variables of testing samples. Based on these studies, BDT has better particle identification performance than ANN. The degradation of the classifications obtained by shifting or smearing variables of testing results is smaller for BDT than for ANN.
211538661
STUDY OF J/ψ PRODUCTION IN Pb–Pb COLLISIONS AT 2.76 TeV WITH THE ALICE EXPERIMENT AT THE LHC∗
We present the measurement of J/ψ nuclear modification factor in Pb–Pb collisions at √ sNN = 2.76 TeV at both midand forward rapidity, from data collected in 2010 by the ALICE experiment. Results are compared to RHIC data and results from other experiments at LHC, as well as with existing models. The current status of two ongoing analyses on J/ψ production in ultra-peripheral collisions and J/ψ elliptic flow is also discussed.
13902096
Dilaton deformations in closed string field theory
The dilaton theorem implies that the contribution to the dilaton potential from cubic interactions of all levels must be cancelled by the elementary quartic self-coupling of dilatons. We use this expectation to test the quartic structure of closed string field theory and to study the rules for level expansion. We explain how to use the results of Moeller to compute quartic interactions of states that, just like the dilaton, are neither primary nor have a simple ghost dependence. Our analysis of cancellations is made richer by discussing simultaneous dilaton and marginal deformations. We find evidence for two facts: as the level is increased quartic interactions become suppressed and closed string field theory may be able to describe arbitrarily large dilaton deformations.
15090356
Dark Energy and Emergent Spacetime
A natural geometric framework of noncommutative spacetime is symplectic geometry rather than Riemannian geometry. The Darboux theorem in symplectic geometry then admits a novel form of the equivalence principle such that the electromagnetism in noncommutative spacetime can be regarded as a theory of gravity. Remarkably the emergent gravity reveals a noble picture about the origin of spacetime, dubbed as emergent spacetime, which is radically different from any previous physical theory all of which describe what happens in a given spacetime. In particular, the emergent gravity naturally explains the dynamical origin of flat spacetime, which is absent in Einstein gravity: A flat spacetime is not free gratis but a result of Planck energy condensation in a vacuum. This emergent spacetime picture, if it is correct anyway, turns out to be essential to resolve the cosmological constant problem, to understand the nature of dark energy and to explain why gravity is so weak compared to other forces.
12060341
ALE spaces from noncommutative U(1) instantons via exact Seiberg-Witten map
The exact Seiberg–Witten (SW) map of a noncommutative (NC) gauge theory gives the commutative equivalent as an ordinary gauge theory coupled to a field dependent effective metric. We study instanton solutions of this commutative equivalent whose self-duality equation turns out to be the exact SW map of NC instantons. We derive general differential equations governing U(1) instantons and we explicitly get an exact solution corresponding to the single NC instanton. Remarkably the effective metric induced by the single U(1) instanton is related to the Eguchi–Hanson metric—the simplest gravitational instanton. Surprisingly the instanton number is not quantized but depends on an integration constant. Our result confirms the expected non-perturbative breakdown of the SW map. However, the breakdown of the map arises in a consistent way: the instanton number plays the role of a parameter giving rise to a one-parameter family of Eguchi–Hanson metrics.
119119010
Area spectra of near extremal black holes
Motivated by Maggiore’s new interpretation of quasinormal modes, we investigate area spectra of a near extremal Schwarzschild–de Sitter black hole and a higher-dimensional near extremal Reissner–Nordstrom–de Sitter black hole. The result shows that the area spectra are equally spaced and irrelevant to the parameters of the black holes.