The binary fraction of stars in dwarf galaxies: the case of Leo II

We combine precision radial velocity data from four different published works of the stars in the Leo II dwarf spheroidal galaxy. This yields a dataset that spans 19 years, has 14 different epochs of observation, and contains 372 unique red giant branch stars, 196 of which have repeat observations. Using this multi-epoch dataset, we constrain the binary fraction for Leo II. We generate a suite of Monte Carlo simulations that test different binary fractions using Bayesian analysis and determine that the binary fraction for Leo II ranges from $0.30^{+0.09}_{-0.10}$ to $0.34^{+0.11}_{-0.11}$, depending on the distributions of binary orbital parameters assumed. This value is smaller than what has been found for the solar neighborhood (~0.4-0.6) but falls within the wide range of values that have been inferred for other dwarf spheroidals (0.14-0.69). The distribution of orbital periods has the greatest impact on the binary fraction results. If the fraction we find in Leo II is present in low-mass ultra-faints, it can artificially inflate the velocity dispersion of those systems and cause them to appear more dark matter rich than in actuality. For a galaxy with an intrinsic dispersion of 1 km/s and an observational sample of 100 stars, the dispersion can be increased by a factor of 1.5-2 for Leo II-like binary fractions or by a factor of 3 for binary fractions on the higher end of what has been seen in other dwarf spheroidals.Comment: 14 pages, 11 figures, 3 tables. Published in A

The Binary Fraction of Stars in Dwarf Galaxies: The Cases of Draco and Ursa Minor

Measuring the frequency of binary stars in dwarf spheroidal galaxies (dSphs) requires data taken over long time intervals. We combine radial velocity measurements from five literature sources taken over the course of ~30 years to yield the largest multi-epoch kinematic sample for stars in the dSphs Draco and Ursa Minor. With this data set, we are able to implement an improved version of the Bayesian technique described in Spencer et al. to evaluate the binary fraction of red giant stars in these dwarf galaxies. Assuming Duquennoy & Mayor period and mass ratio distributions, the binary fractions in Draco and Ursa Minor are 0.50_(-0.06)^(+0.04) and 0.78_(-0.08)^(+0.09), respectively. We find that a normal mass ratio distribution is preferred over a flat distribution, and that log-normal period distributions centered on long periods µ_(log P > 3.5) are preferred over distributions centered on short ones. We reanalyzed the binary fractions in Leo II, Carina, Fornax, Sculptor, and Sextans, and find that there is <1% chance that binary fraction is a constant quantity across all seven dwarfs, unless the period distribution varies greatly. This indicates that the binary populations in Milky Way dSphs are not identical in regard to their binary fractions, period distributions, or both. We consider many different properties of the dwarfs (e.g., mass, radius, luminosity, etc.) and find that binary fraction might be larger in dwarfs that formed their stars quickly and/or have high velocity dispersions

Samuel Jenkins Junior Composition Recital

https://dc.ewu.edu/music_performances/1628/thumbnail.jp

On velocity-dependent dark matter annihilations in dwarf satellites

Milky Way dwarf spheroidal satellites are a prime target for Dark Matter (DM) indirect searches. Recently the importance of possible long-range interactions has been recognized, as they can boost the expected DM gamma ray signal by orders of magnitude through an effect commonly known as the Sommerfeld enhancement. However, for such analyses precise modelling of DM phase-space distribution becomes crucial and can introduce large uncertainties in the final result. We provide a pioneering attempt towards a comprehensive investigation of these systematics. First, the DM halo profiles are constrained using Bayesian inference on the available stellar kinematic datasets with a careful treatment of observational and theoretical uncertainties. We consider both cuspy and cored parametric DM density profiles, together with the case of a non-parametric halo modelling directly connected to observable quantities along the line-of-sight. After reconsidering the study case of ergodic systems, the basic ingredient of all previous analyses, we investigate for the first time scenarios where DM particles are allowed to have anisotropic velocity distributions. Referring to a generalized J-factor, sensitive to velocity-dependent effects, an enhancement (suppression) with respect to the isotropic phase-space distributions is obtained for the case of tangentially (radially) biased DM particle orbits. We provide new estimates for J-factors for the eight brightest Milky Way dwarfs also in the limit of velocity-independent DM annihilation, in good agreement with previous results in literature, and derive data-driven lower-bounds based on the non-parametric modelling of the halo density. This work presents a state-of-the-art analysis of the aforementioned effects and falls within the interest of current and future experimental collaborations involved in DM indirect detection programs

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead