Nuclear recoil limits from the ZEPLIN I liquid xenon WIMP dark matter detector

Alner, G. J.; Araújo, H. M.; Arnison, G. J.; Barton, J. C.; Bewick, A.; Bungau, Cristian; Camanzi, B.; Carson, M.; Davidge, D.; Dawson, J.; Davies, G.; Davies, Julia; Durkin, T.; Gamble, T.; Hart, Simon P.; Hollingworth, R. J.; Homer, G.J.; Howard, Alex; Ivaniouchenkov, I.; Jones, W. G.; Joshi, M.; Kudryavtsev, V. A.; Lawson, T. B.; Lebedenko, V.N.; Lewin, J.D.; Lightfoot, P. K.; Liubarsky, I.; Lehner, M. J.; Lüscher, R.; McMillan, J. E.; Morgan, B.; Nicholls, A.; Nicklin, G.; Paling, S. M.; Preece, R.; Roberts, John W.; Robinson, M.; Quenby, J. J.; Smith, N. J. T.; Smith, P.F.; Spooner, N. J. C.; Sumner, T. J.; Tovey, D. R.

doi:10.1016/j.newar.2005.01.045

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…For investigations of direct neutralino dark matter detection in context with the NMSSM we mention the approaches [168,[173][174][175][176]. On the experimental side we draw the attention to the experiments of the DAMA collaboration [177], CDMS [178], EDELWEISS [179], ZEPLIN I [180], as well as the XENON10 experiment [181]. Up to now there are no confirmed detections of any weakly interacting massive particle (WIMP).…”

Section: Direct Dark Matter Detectionmentioning

confidence: 99%

The Next-to-Minimal Supersymmetric Extension of the Standard Model Reviewed

Maniatis

2010

Int. J. Mod. Phys. A

418

390

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The next-to-minimal supersymmetric extension of the Standard Model (NMSSM) is one of the most favored supersymmetric models. After an introduction to the model, the Higgs sector and the neutralino sector are discussed in detail. Theoretical, experimental, and cosmological constraints are studied. Eventually, the Higgs potential is investigated in the approach of bilinear functions. Emphasis is placed on aspects which are different from the minimal supersymmetric extension.

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Section: Direct Dark Matter Detectionmentioning

confidence: 99%

The Next-to-Minimal Supersymmetric Extension of the Standard Model Reviewed

Maniatis

2010

Int. J. Mod. Phys. A

418

390

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“…Given the measured value n obs and an estimate of μ B from an independent background-only experiment, we construct uncertainty intervals (confidence intervals and Bayesian credibility intervals) for μ S . The statistical problem we study occurs in a variety of application areas including particle and astroparticle physics [1][2][3][4][5][6][7][8][9], isotopic ratio analysis (when the major isotope is large enough so that most of the variability in the ratio is due to the minor isotope) [10,11], detection of lowlevel radiation [12][13][14][15] and aerosol science and technology [16].…”

Section: Introductionmentioning

confidence: 99%

Frequentist coverage properties of uncertainty intervals for weak Poisson signals in the presence of background

Coakley

Splett

Simons

2010

Meas. Sci. Technol.

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Abstract. We construct uncertainty intervals for weak Poisson signals in the presence of background. We consider the case where a primary experiment yields a realization of the signal plus background, and a second experiment yields a realization of the background. The data acquisitions times, for the background-only experiment, T bg , and the primary experiment, T , are selected so that their ratio, T bg T , varies from 1 to 25. The upper choice of 25 is motivated by an experimental study at the National Institute of Standards and Technology (NIST). The expected number of background counts in the primary experiment varies from 0.2 to 2. We construct 90 and 95 percent confidence intervals based on a propagation-of-errors method as well as two implementations of a Neyman procedure where acceptance regions are constructed based on a likelihood-ratio criterion that automatically determines whether the resulting confidence interval is one-sided or two-sided. In one of the implementations of the Neyman procedure due to Feldman and Cousins, uncertainty in the expected background contribution is neglected. In the other implementation, we account for random uncertainty in the estimated expected background with a parametric bootstrap implementation of a method due to Conrad. We also construct minimum length Bayesian credibility intervals. For each method, we test for the presence of a signal based on the value of the lower endpoint of the uncertainty interval. In general, the propagation-of-errors method performs the worst compared to the other methods according to frequentist coverage and detection probability criteria, and sometimes produces nonsensical intervals where both endpoints are negative. The Neyman procedures generally yield intervals with better frequentist coverage properties compared to the Bayesian method except for some cases where T bg T = 1. In general, the Bayesian method yields intervals with lower detection probabilities compared to Neyman procedures. One of main conclusions is that when T bg T is 5 or more and the expected background is 2 or less, the FC method outperforms the other methods considered. For T bg T = 1, 2 we observe that the Neyman procedure methods yield false detection probabilities for the case of no signal that are higher than expected given the nominal frequentist coverage of the interval. In contrast, for T bg T = 1, 2, the false

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