Multi-model inference ranking and applications to physics at the Large Hadron Collider

In the measurement of the Higgs Boson decaying into two photons the parametrization of an appropriate background model is essential for fitting the Higgs signal mass peak over a continuous background. This diphoton background modeling is crucial in the statistical process of calculating exclusion limits and the significance of observations in comparison to a background-only hypothesis. It is therefore ideal to obtain knowledge of the physical shape for the background mass distribution as the use of an improper function can lead to biases in the observed limits. Using an Information-Theoretic (I-T) approach for valid inference we apply Akaike Information Criterion (AIC) as a measure of the separation for a fitting model from the data. We then implement a multi-model inference ranking method to build a fit-model that closest represents the Standard Model background in 2013 diphoton data recorded by the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC). Potential applications and extensions of this model-selection technique are discussed with reference to CMS detector performance measurements as well as in potential physics analyses at future detectors.

Predation and selection in copepod populations of Alpine waters [Translation from: Bollettino di Zoologia 21 541-545, 1954]

Zooplankton was studied in four alpine lakes in Switzerland, France and Italy. The presence the presence of the invertebrate predator Heterocope in three lakes was stated. It is then discussed why in three of these four lakes, the copepod Arctodiaptomus denticornis is present in the absence of Arctodiaptomus bacillifer, and vice versa respectively in the second and first parts of the lacustrine summer.