Differential Upregulation of BDNF mRNA in the Rat Hippocampus after Sing and Recurrent Hyperthermia-Induced Seizures

Thesis (M.D.) - Yale University, 2002

Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning

We study dynamical mass measurements of galaxy clusters contaminated by interlopers and show that a modern machine learning (ML) algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create two mock catalogs from Multidark's publicly available $N$-body MDPL1 simulation, one with perfect galaxy cluster membership information and the other where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power-law scaling relation to infer cluster mass from galaxy line-of-sight (LOS) velocity dispersion. Assuming perfect membership knowledge, this unrealistic case produces a wide fractional mass error distribution, with a width of $\Delta\epsilon\approx0.87$. Interlopers introduce additional scatter, significantly widening the error distribution further ($\Delta\epsilon\approx2.13$). We employ the support distribution machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to distributions of galaxy observables such as LOS velocity and projected distance from the cluster center, SDM yields better than a factor-of-two improvement ($\Delta\epsilon\approx0.67$) for the contaminated case. Remarkably, SDM applied to contaminated clusters is better able to recover masses than even the scaling relation approach applied to uncontaminated clusters. We show that the SDM method more accurately reproduces the cluster mass function, making it a valuable tool for employing cluster observations to evaluate cosmological models.Comment: 18 pages, 12 figures, accepted for publication at Ap

Probing the first galaxies with the SKA

Observations of anisotropies in the brightness temperature of the 21 cm line of neutral hydrogen from the period before reionization would shed light on the dawn of the first stars and galaxies. In this paper, we use large-scale semi-numerical simulations to analyse the imprint on the 21 cm signal of spatial fluctuations in the Lyman-alpha flux arising from the clustering of the first galaxies. We show that an experiment such as the Square Kilometer Array (SKA) can probe this signal at the onset of reionization, giving us important information about the UV emission spectra of the first stars and characterizing their host galaxies. SKA-pathfinders with ~ 10% of the full collecting area should be capable of making a statistical detection of the 21 cm power spectrum at redshifts z 67 MHz). We then show that the SKA should be able to measure the three dimensional power spectrum as a function of the angle with the line of sight and discuss the use of the redshift space distortions as a way to separate out the different components of the 21 cm power spectrum. We demonstrate that, at least on large scales where the Lyman-alpha fluctuations are linear, they can be used as a model independent way to extract the power spectra due to these Lyman-alpha fluctuations.Comment: 13 pages, 17 figures. New version to match version accepted by A&A. Improved discussions on the Lyman-alpha simulation, adiabatic cooling fluctuations, the Fisher matrix approach and the Poisson term calculation. New version of the code available at: http://www.SimFast21.or

PIERNIK mhd code - a multi-fluid, non-ideal extension of the relaxing-TVD scheme (I)

We present a new multi-fluid, grid MHD code PIERNIK, which is based on the Relaxing TVD scheme. The original scheme has been extended by an addition of dynamically independent, but interacting fluids: dust and a diffusive cosmic ray gas, described within the fluid approximation, with an option to add other fluids in an easy way. The code has been equipped with shearing-box boundary conditions, and a selfgravity module, Ohmic resistivity module, as well as other facilities which are useful in astrophysical fluid-dynamical simulations. The code is parallelized by means of the MPI library. In this paper we shortly introduce basic elements of the Relaxing TVD MHD algorithm, following Trac & Pen (2003) and Pen et al. (2003), and then focus on the conservative implementation of the shearing box model, constructed with the aid of the Masset's (2000) method. We present results of a test example of a formation of a gravitationally bounded object (planet) in a self-gravitating and differentially rotating fluid.Comment: 6 pages, 3 figures, conference proceedings of the Torun Exoplanets 200