Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

Ultrahigh-energy cosmic rays (UHECRs) can be accelerated by tidal disruption events of stars by black holes. We suggest a novel mechanism for UHECR acceleration wherein white dwarfs (WDs) are tidally compressed by intermediate-mass black holes (IMBHs), leading to their ignition and subsequent explosion as a supernova. Cosmic rays accelerated by the supernova may receive an energy boost when crossing the accretion-powered jet. The rate of encounters between WDs and IMBHs can be relatively high, as the number of IMBHs may be substantially augmented once account is taken of their likely presence in dwarf galaxies. Here we show that this kind of tidal disruption event naturally provides an intermediate composition for the observed UHECRs, and suggest that dwarf galaxies and globular clusters are suitable sites for particle acceleration to ultrahigh energies.

Abstract:

We analyse the properties of circumgalactic gas around simulated galaxies in the redshift range z ≥ 3, utilizing a new sample of cosmological zoom simulations. These simulations are intended to be representative of the observed samples of Lyman α (Ly α) emitters recently obtained with the multi unit spectroscopic explorer (MUSE) instrument (halo masses ~ 10 10 - 10 11 M⊙). We show that supernova feedback has a significant impact on both the inflowing and outflowing circumgalactic medium (CGM) by driving outflows, reducing diffuse inflow rates, and by increasing the neutral fraction of inflowing gas. By temporally stacking simulation outputs, we find that significant net mass exchange occurs between inflowing and outflowing phases: none of the phases are mass-conserving. In particular, we find that the mass in neutral outflowing hydrogen declines exponentially with radius as gas flows outwards from the halo centre. This is likely caused by a combination of both fountain-like cycling processes and gradual photoionization/collisional ionization of outflowing gas. Our simulations do not predict the presence of fast-moving neutral outflows in the CGM. Neutral outflows instead move with modest radial velocities (~ 50 km s -1 ), and the majority of the kinetic energy is associated with tangential rather than radial motion.

Abstract:

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues.