Dynamic Bayesian Combination of Multiple Imperfect Classifiers

Using the new Voxcharta.org system, I was the only physicist at my institute to upvote this paper, Dynamic Bayesian Combination of Multiple Imperfect Classifiers (pdf), more in the realm of machine learning or computer science than traditional astrophysics or astronomy. As such I was nominated to discuss it at our weekly journal club. Here I give a brief review of concepts needed to follow the paper, and then go in depth into how we can use the opinions of multiple lay people as to whether an object is a supernova or not to achieve a highly accurate classification at the expert level.

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Probing the dark matter issue in f(R)-gravity via gravitational lensing

A few days ago in gr-qc  journal club we discussed an interesting paper by a member of our own institute, Probing the dark matter issue in f(R)-gravity via gravitational lensing.1. Background Dark Matter We theoretically expect dark matter to exist based largely on  extensive observations of both dynamics (rotation curves and objects such as the […]

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Locally Cold Flows from Large-Scale Structure

Walls, filaments and voids: it is thought that the large scale distribution of matter is a complex network of galaxies and galaxy clusters connected by elongated filaments and sheetlike walls, outlining vast underdense regions known as voids and meeting at dense and compact regions known as haloes. Aragon-Calvo et. al. in [1] build upon the SpineWeb framework outlined in [2] , which has the capability of identifying these walls, filaments and clusters in cosmological simulations to examine the effect of environment (namely whether a galaxy is “living” in a wall or a void) on the dispersion of the Hubble flow around the Milky, which is significantly lower than theoretical expectations. They show that the measured dispersion could be a result of the fact that Milky Way resides inside a wall of radius around 10Mpc, which is supported by data.

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