The comfort zone: Reflection on a taken-for-granted model

Reference to the comfort zone model is widespread within outdoor adventure education. It is based on the belief that when placed in a stressful situation people will respond by overcoming their hesitancy and grow. This model is often presented to students prior to activities with a perceived sense of risk and challenge which arouses strong emotional and physical responses to novel tasks (e.g., a ropes course). Students are encouraged to ‘stretch themselves’, to move outside their comfort zone and expand their preconceived limits and by inference learn. This article briefly explores the theories that underpin the comfort zone model and suggests that it is time to rethink how it is used

Impact of Bayesian prior on the characterization of binary black hole coalescences

In a regime where data are only mildly informative, prior choices can play a significant role in Bayesian statistical inference, potentially affecting the inferred physics. We show this is indeed the case for some of the parameters inferred from current gravitational-wave measurements of binary black hole coalescences. We reanalyze the first detections performed by the twin LIGO interferometers using alternative (and astrophysically motivated) prior assumptions. We find different prior distributions can introduce deviations in the resulting posteriors that impact the physical interpretation of these systems. For instance, (i) limits on the $90\%$ credible interval on the effective black hole spin $\chi_{\rm eff}$ are subject to variations of $\sim 10\%$ if a prior with black hole spins mostly aligned to the binary's angular momentum is considered instead of the standard choice of isotropic spin directions, and (ii) under priors motivated by the initial stellar mass function, we infer tighter constraints on the black hole masses, and in particular, we find no support for any of the inferred masses within the putative mass gap $M \lesssim 5 M_\odot$.Comment: 6 Pages, 2 Figures; see also 1712.06635 Data release at https://github.com/vitale82/GWprior

The MaxEnt extension of a quantum Gibbs family, convex geometry and geodesics

We discuss methods to analyze a quantum Gibbs family in the ultra-cold regime where the norm closure of the Gibbs family fails due to discontinuities of the maximum-entropy inference. The current discussion of maximum-entropy inference and irreducible correlation in the area of quantum phase transitions is a major motivation for this research. We extend a representation of the irreducible correlation from finite temperatures to absolute zero.Comment: 8 pages, 3 figures, 34th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, 21-26 September 2014, Ch\^ateau du Clos Luc\'e, Amboise, Franc