Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page

Search for additional heavy neutral Higgs and gauge bosons in the ditau final state produced in 36 fb−1 of pp collisions at √s=13 TeV with the ATLAS detector

A search for heavy neutral Higgs bosons and Z′ bosons is performed using a data sample corresponding to an integrated luminosity of 36.1 fb−1 from proton-proton collisions at √s=13 TeV recorded by the ATLAS detector at the LHC during 2015 and 2016. The heavy resonance is assumed to decay to τ+τ− with at least one tau lepton decaying to final states with hadrons and a neutrino. The search is performed in the mass range of 0.2-2.25 TeV for Higgs bosons and 0.2-4.0 TeV for Z′ bosons. The data are in good agreement with the background predicted by the Standard Model. The results are interpreted in benchmark scenarios. In the context of the hMSSM scenario, the data exclude tan β > 1.0 for mA= 0.25 TeV and tan β > 42 for mA=1.5 TeV at the 95% confidence level. For the Sequential Standard Model, ZSSM′ with mZ′< 2.42 TeV is excluded at 95% confidence level, while Z NU′ with mZ ′ < 2.25 TeV is excluded for the non-universal G(221) model that exhibits enhanced couplings to third-generation fermions

Measurement of the Higgs boson coupling properties in the H → ZZ* → 4 decay channel at √s = 13 TeV with the ATLAS detector

The coupling properties of the Higgs boson are studied in the four-lepton (e, μ) decay channel using 36.1 fb−1 of pp collision data from the LHC at a centre-of-mass energy of 13 TeV collected by the ATLAS detector. Cross sections are measured for the main production modes in several exclusive regions of the Higgs boson production phase space and are interpreted in terms of coupling modifiers. The inclusive cross section times branching ratio for H → ZZ∗ decay and for a Higgs boson absolute rapidity below 2.5 is measured to be 1. 73 − 0.23 + 0.24 (stat.) − 0.08 + 0.10 (exp.) ± 0.04(th.) pb compared to the Standard Model prediction of 1.34±0.09 pb. In addition, the tensor structure of the Higgs boson couplings is studied using an effective Lagrangian approach for the description of interactions beyond the Standard Model. Constraints are placed on the non-Standard-Model CP-even and CP-odd couplings to Z bosons and on the CP-odd coupling to gluons

Coronavirus-Pandemie: Die Feiertage und den Jahreswechsel für einen harten Lockdown nutzen : 7. Ad-hoc-Stellungnahme zr Coronavirus-Pandemie - 08.Dezember 2020

Die gegenwärtige Situation ist nach wie vor ernst und droht sich weiter zu verschärfen. Trotz des seit Anfang November in Deutschland geltenden Teil-Lockdowns sind die Infektionszahlen auf einem sehr hohen Niveau. Jeden Tag sterben mehrere Hundert Menschen. Die Krankenhäuser und insbesondere das medizinische Personal sind bereits jetzt an ihren Grenzen und die Gesundheitsämter überlastet. Um die Kontrolle über das Infektionsgeschehen zurückzuerlangen, empfiehlt die Nationale Akademie der Wissenschaften Leopoldina in der Ad-hoc-Stellungnahme „Coronavirus-Pandemie: Die Feiertage und den Jahreswechsel für einen harten Lockdown nutzen“ ein zweistufiges Vorgehen. Die Rahmenbedingungen ‒ Weihnachtsferien in Bildungseinrichtungen und eingeschränkter Betrieb in vielen Unternehmen und Behörden – bieten die Chance, in der Eindämmung der Pandemie ein großes Stück voranzukommen