Name: PHYSTAT Dark Matter 2019
Start: 2019-07-31T00:30:00+02:00
End: 2019-08-02T22:45:00+02:00
Location: Stockholm university

PHYSTAT Dark Matter 2019

from Wednesday 31 July 2019 (00:30) to Friday 2 August 2019 (22:45)

Monday 29 July 2019
Tuesday 30 July 2019
Wednesday 31 July 2019
09:30 Preamble and Intro to Statistics
Preamble and Intro to Statistics
09:30 - 11:00
Contributions

09:30 Introductory Statistics Talks - Glen Cowan Louis Lyons (Imperial College (GB))
11:00 Break
Break
11:00 - 11:30
11:30 Intro to Workshop
Intro to Workshop
11:30 - 12:40
Contributions

11:30 Intro to workshop - Jan Conrad

11:40 Status of direct detection experiments and their approaches to statistical inference - Jim Dobson

12:10 Including direct detection likelihoods in global fits - Felix Kahlhoefer (RWTH Aachen)
12:40 Lunch
Lunch
12:40 - 14:10
14:30 Blind Analysis, Look Elsewhere
Blind Analysis, Look Elsewhere
14:30 - 16:00
Contributions

14:30 Blinding and salting in dark matter searches. - Maria Elena Monzani (Stanford University)

15:00 Blinding Strategies for Dark Matter Searches - Ben Loer (Pacific Northwest National Laboratory)

15:30 Correcting for the look-elsewhere effect: why, when and how - Sara Algeri (University of Minnesota)
16:00 Break
Break
16:00 - 16:30
16:30 Experience Outside Dark Matter, and Limits
Experience Outside Dark Matter, and Limits
16:30 - 18:00
Contributions

16:30 The LHC Experience - Nicholas Wardle (Imperial College (GB))

17:00 Statistical Inference in Double-Beta Decay Searches - Matteo Agostini

17:30 Limit setting: evolution vs. inteligent design - Hagar Landsmann (Weizmann Inst. of Science)
18:00 Poster Session and Reception
Poster Session and Reception
18:00 - 20:25
Contributions

18:05 Statistical Analysis for COSINE-100 - Young Ju Ko (Institute for Basic Science (IBS))

18:05 WIMP Dark Matter Modulation Analysis on Data from Low Threshold Germanium Detectors - Hau-Bin Li (Academia Sinica, Taipei, Taiwan)

18:05 Improving the LUX PLR Code - SHAUN ALSUM (University of Wisconsin-Madison)

18:05 Bayesian and frequentist approaches to discoveries - Andrew Fowlie (Nanjing Normal University)

18:05 Uncertainties in the dark matter velocity distribution - Andrew Fowlie (Nanjing Normal University)

18:05 DAMA/LIBRA Phase I and II combined analysis in the standard WIMP scenario - Ianni Aldo (INFN - LNGS)

18:05 Using the profile-likelihood method to search for dark matter in DEAP-3600 - Ashlea Kemp (Royal Holloway, University of London)
Thursday 1 August 2019
09:00 Limit Setting Methods
Limit Setting Methods
09:00 - 10:30
Contributions

09:00 Likelihood asymptotics and beyond - Alessandra Brazzale

09:30 Improved Inference for the Signal Significance - Igor Volobouev (Texas Tech University (US))

10:00 Imposing overcoverage on small signals. - Knut Dundas Morå
10:30 Break
Break
10:30 - 11:00
11:00 Signal and Backgrounds
Signal and Backgrounds
11:00 - 12:00
Contributions

11:00 Detecting new signals under background mismodelling - Sara Algeri (University of Minnesota)

11:30 Partially specified models and nuisance parameters - Heather Battey (Imperial College London)
12:00

12:00 - 12:30

12:30 Lunch
Lunch
12:30 - 14:00
14:00 Signal and Backgrounds
Signal and Backgrounds
14:00 - 15:30
Contributions

14:00 Crystal-based Detector Background and Response Modeling - Robert Calkins (Southern Methodist University)

14:30 Background and detector response modeling in single electron-hole pair sensitive crystal detectors - Belina von Krosigk (University of Hamburg)

15:00 A statistical model for the leakage of backgrounds mitigated by pulseshape discrimination methods - Tina Pollmann (Technische Universität München)
15:30 Break
Break
15:30 - 16:00
16:00 Backgrounds/Response Modeling
Backgrounds/Response Modeling
16:00 - 16:30
Contributions

16:00 A novel approach to assess the impact of the Fano factor on the sensitivity of low-mass dark matter experiments - Daniel Durnford (University of Alberta)
16:30 Discussion 2
Discussion 2
16:30 - 17:00

18:00 Workshop dinner
Workshop dinner
18:00 - 22:30
Friday 2 August 2019
09:00 Nuisance Parameters (Form Factors/Halo)
Nuisance Parameters (Form Factors/Halo)
09:00 - 10:15
Contributions

09:00 Nuclear physics of dark matter direct detection - MARTIN HOFERICHTER (University of Washington)

09:35 Dark matter in the Milky Way - Christopher McCabe (King's College London)
10:15

10:15 - 10:30

10:30 Break
Break
10:30 - 11:00
11:00 Machine Learning
Machine Learning
11:00 - 12:00
Contributions

11:00 Machine learning in HEP - Jan Kieseler (CERN)

11:30 Dark Machines - using machine learning to solve dark matter related problems - Luc Hendriks (Nikhef) Luc Hendriks
12:00 Lunch
Lunch
12:00 - 13:30
13:30 Reflections on 20+ years of Feldman-Cousins: Hypothesis testing of a point null vs a continuous alternative - Robert Cousins Jr (University of California Los Angeles (US)) Robert Dacey Cousins Jr (Univ. of California Los Angeles (UCLA)) Robert Cousins Jr (University of California Los Angeles (US))
Reflections on 20+ years of Feldman-Cousins: Hypothesis testing of a point null vs a continuous alternative
- Robert Cousins Jr (University of California Los Angeles (US))
- Robert Dacey Cousins Jr (Univ. of California Los Angeles (UCLA))
- Robert Cousins Jr (University of California Los Angeles (US))
13:30 - 14:10
I will discuss aspects of the frequentist and Bayesian approaches to testing a point null hypothesis (say mu=0) versus a continuous alternative hypothesis (say mu>0). This test arises frequently in particle physics (including dark matter searches), where mu is the signal strength. The frequentist testing approach maps identically onto the frequentist theory of confidence intervals. Thus, as Feldman and Cousins eventually realized, the method advocated in their 1998 paper on confidence intervals maps identically onto the "classical" theory of hypothesis testing in Kendall and Stuart (which in addition includes nuisance parameters). Meanwhile, the traditional Bayesian approach to hypothesis testing (due to Jeffreys) is completely separate from the Bayesian approach to credible intervals, with no corresponding mapping. Direct sensitivity to the prior pdf for mu, even in the asymptotic limit of large sample size, is a consequence, as is the Jeffreys-Lindley paradox (arXiv:1310.3791). My talk will draw on parts of my “Lectures on Statistics in Theory: Prelude to Statistics in Practice” arXiv:1807.05996.
14:10 White Paper/Discussion 3
White Paper/Discussion 3
14:10 - 15:10

15:10 Break
Break
15:10 - 15:40
15:40 Summaries
Summaries
15:40 - 16:40
Contributions

15:40 Statisticians summary - Alessandra Brazzale

16:10 Physicists Summary - Hugh Lippincott (Fermilab)
16:40 Optional: White Paper 2
Optional: White Paper 2
16:40 - 17:40