Improving photoelectron counting and particle identification in scintillation detectors with Bayesian techniques

Many current and future dark matter and neutrino detectors are designed to measure scintillation light with a large array of photomultiplier tubes (PMTs). The energy resolution and particle identification capabilities of these detectors depend in part on the ability to accurately identify individual photoelectrons in PMT waveforms despite large variability in pulse amplitudes and pulse pileup. We describe a Bayesian technique that can identify the times of individual photoelectrons in a sampled PMT waveform without deconvolution, even when pileup is present. To demonstrate the technique, we apply it to the general problem of particle identification in single-phase liquid argon dark matter detectors. Using the output of the Bayesian photoelectron counting algorithm described in this paper, we construct several test statistics for rejection of backgrounds for dark matter searches in argon. Compared to simpler methods based on either observed charge or peak finding, the photoelectron counting technique improves both energy resolution and particle identification of low energy events in calibration data from the DEAP-1 detector and simulation of the larger MiniCLEAN dark matter detector

Triplet lifetime in gaseous argon

MiniCLEAN is a single-phase liquid argon dark matter experiment. During the initial cooling phase, impurities within the cold gas ($<$140 K) were monitored by measuring the scintillation light triplet lifetime, and ultimately a triplet lifetime of 3.480 $\pm$ 0.001 (stat.) $\pm$ 0.064 (sys.) $\mu$s was obtained, indicating ultra-pure argon. This is the longest argon triplet time constant ever reported. The effect of quenching of separate components of the scintillation light is also investigated

Analysis of vacuum and argon gas fill data from the MiniCLEAN dark matter experiment

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Physics, 2015.Cataloged from PDF version of thesis.Includes bibliographical references (pages 183-193).The existence of particle dark matter provides a consistent framework for understanding many astronomical observations. The rotation curves of galaxies and galaxyclusters, for example, indicate the majority of mass in these structures is unseen. The existence of weakly-interacting massive particles (WIMPs) was proposed in the early 1980s to account for the anomalous rotation curves and provide a mechanism for producing the cold dark matter relic density, which along with dark energy is thought to dominate the current energy density of our universe. Efforts to observe the rare interaction of WIMPs with normal matter have continued since their proposal, and so far have set limits on the WIMP-nucleon interaction cross-section extending to 1 x 10-9 pb. Contemporary experiments seek to observe ~ one WIMP-nucleus scatter per year per 100 kg of detector mass. These experiments must be conducted deep underground with stringent cleanliness requirements. The MiniCLEAN dark matter experiment is a single-phase liquid argon scintillation detector which uses the wavelength-shifting fluor tetraphenyl butadiene and cryogenic photomultiplier tubes for light detection. The active spherical region of the detector contains 500 kg of liquid argon at temperature 87 K. Background events which could mimic a WIMP signal are mitigated through pulse-shape discrimination and position reconstruction. At an intermediate stage of ongoing detector assembly 2 km underground at SNOLAB in Ontario, the complete instrumented inner vessel was commissioned by collecting photomultiplier waveform data for periods when the vessel was evacuated and when filled with warm argon gas. Alpha decay events from radon progeny on the wavelength-shifting surface occur in this data at a measured rate of 19.0 ± 0.4 /h/m2 MiniCLEAN's projected sensitivity to spin-independent WIMP-nucleon scattering, derived from simulation of this surface rate, is [sigma]SI < 1.5 x 10-8 pb.by Stephen H. Jaditz.Ph. D

Performance of the CMS drift-tube chamber local trigger with cosmic rays

The performance of the Local Trigger based on the drift-tube system of the CMS experiment has been studied using muons from cosmic ray events collected during the commissioning of the detector in 2008. The properties of the system are extensively tested and compared with the simulation. The effect of the random arrival time of the cosmic rays on the trigger performance is reported, and the results are compared with the design expectations for proton-proton collisions and with previous measurements obtained with muon beams

Performance of the CMS Level-1 trigger during commissioning with cosmic ray muons and LHC beams

The CMS Level-1 trigger was used to select cosmic ray muons and LHC beam events during data-taking runs in 2008, and to estimate the level of detector noise. This paper describes the trigger components used, the algorithms that were executed, and the trigger synchronisation. Using data from extended cosmic ray runs, the muon, electron/photon, and jet triggers have been validated, and their performance evaluated. Efficiencies were found to be high, resolutions were found to be good, and rates as expected

Commissioning and performance of the CMS silicon strip tracker with cosmic ray muons

During autumn 2008, the Silicon Strip Tracker was operated with the full CMS experiment in a comprehensive test, in the presence of the 3.8 T magnetic field produced by the CMS superconducting solenoid. Cosmic ray muons were detected in the muon chambers and used to trigger the readout of all CMS sub-detectors. About 15 million events with a muon in the tracker were collected. The efficiency of hit and track reconstruction were measured to be higher than 99% and consistent with expectations from Monte Carlo simulation. This article details the commissioning and performance of the Silicon Strip Tracker with cosmic ray muons

Identification and filtering of uncharacteristic noise in the CMS hadron calorimeter

Commissioning studies of the CMS hadron calorimeter have identified sporadic uncharacteristic noise and a small number of malfunctioning calorimeter channels. Algorithms have been developed to identify and address these problems in the data. The methods have been tested on cosmic ray muon data, calorimeter noise data, and single beam data collected with CMS in 2008. The noise rejection algorithms can be applied to LHC collision data at the trigger level or in the offline analysis. The application of the algorithms at the trigger level is shown to remove 90% of noise events with fake missing transverse energy above 100 GeV, which is sufficient for the CMS physics trigger operation. © 2010 IOP Publishing Ltd and SISSA