Joseph Silk

Abstract:

Bayesian model averaging is a procedure to obtain parameter constraints that account for the uncertainty about the correct cosmological model. We use recent cosmological observations and Bayesian model averaging to derive tight limits on the curvature parameter, as well as robust lower bounds on the curvature radius of the Universe and its minimum size, while allowing for the possibility of an evolving dark energy component. Because flat models are favoured by Bayesian model selection, we find that model-averaged constraints on the curvature and size of the Universe can be considerably stronger than non-model-averaged ones. For the most conservative prior choice (based on inflationary considerations), our procedure improves on non-model-averaged constraints on the curvature by a factor of ~2. The curvature scale of the Universe is conservatively constrained to be Rc > 42 Gpc (99 per cent), corresponding to a lower limit to the number of Hubble spheres in the Universe NU > 251 (99 per cent). © 2011 The Authors. Monthly Notices of the Royal Astronomical Society © 2011 RAS.

Abstract:

We consider the Gumbel or extreme value statistics describing the distribution function p_G(x_max) of the maximum values of a random field x within patches of fixed size. We present, for smooth Gaussian random fields in two and three dimensions, an analytical estimate of p_G which is expected to hold in a regime where local maxima of the field are moderately high and weakly clustered. When the patch size becomes sufficiently large, the negative of the logarithm of the cumulative extreme value distribution is simply equal to the average of the Euler Characteristic of the field in the excursion x > x_max inside the patches. The Gumbel statistics therefore represents an interesting alternative probe of the genus as a test of non Gaussianity, e.g. in cosmic microwave background temperature maps or in three-dimensional galaxy catalogs. It can be approximated, except in the remote positive tail, by a negative Weibull type form, converging slowly to the expected Gumbel type form for infinitely large patch size. Convergence is facilitated when large scale correlations are weaker. We compare the analytic predictions to numerical experiments for the case of a scale-free Gaussian field in two dimensions, achieving impressive agreement between approximate theory and measurements. We also discuss the generalization of our formalism to non-Gaussian fields.

Abstract:

Murine cytomegalovirus (MCMV) is an important animal model of human cytomegalovirus (HCMV), a β-Herpesvirus that infects the majority of the world's population and causes disease in neonates and immunocompromised adults. CD8(+) T cells are a major part of the immune response to MCMV and HCMV. Processing of peptides for presentation to CD8(+) T cells may be critically dependent on the immunoproteasome, expression of which is affected by MCMV. However, the overall importance of the immunoproteasome in the generation of immunodominant peptides from MCMV is not known. We therefore examined the role of the immunoproteasome in stimulation of CD8(+) T cell responses to MCMV - both conventional memory responses and those undergoing long-term expansion or "inflation". We infected LMP7(-/-) and C57BL/6 mice with MCMV or with newly-generated recombinant vaccinia viruses (rVVs) encoding the immunodominant MCMV protein M45 in either full-length or epitope-only minigene form. We analysed CD8(+) T cell responses using intracellular cytokine stain (ICS) and MHC Class I tetramer staining for a panel of MCMV-derived epitopes. We showed a critical role for immunoproteasome in MCMV affecting all epitopes studied. Interestingly we found that memory "inflating" epitopes demonstrate reduced immunoproteasome dependence compared to non-inflating epitopes. M45-specific responses induced by rVVs remain immunoproteasome-dependent. These results help to define a critical restriction point for CD8(+) T cell epitopes in natural cytomegalovirus (CMV) infection and potentially in vaccine strategies against this and other viruses.

Abstract:

We present an analytical calculation of the extreme value statistics for dark matter halos - that is, the probability distribution of the most massive halo within some region of the universe of specified shape and size. Our calculation makes use of the counts-in-cells formalism for the correlation functions, and the halo bias derived from the Sheth-Tormen mass function. We demonstrate the power of the method on spherical regions, comparing the results to measurements in a large cosmological dark matter simulation and achieving good agreement. Particularly good fits are obtained for the most likely value of the maximum mass and for the high-mass tail of the distribution, relevant in constraining cosmologies by observations of most massive clusters.

Abstract:

We describe the processing of data from the Low Frequency Instrument (LFI) used in production of the Planck Early Release Compact Source Catalogue (ERCSC). In particular, we discuss the steps involved in reducing the data from telemetry packets to cleaned, calibrated, time-ordered data (TOD) and frequency maps. Data are continuously calibrated using the modulation of the temperature of the cosmic microwave background radiation induced by the motion of the spacecraft. Noise properties are estimated from TOD from which the sky signal has been removed using a generalized least square map-making algorithm. Measured 1/f noise knee-frequencies range from 100mHz at 30GHz to a few tens of mHz at 70GHz. A destriping code (Madam) is employed to combine radiometric data and pointing information into sky maps, minimizing the variance of correlated noise. Noise covariance matrices required to compute statistical uncertainties on LFI and Planck products are also produced. Main beams are estimated down to the approx -10dB level using Jupiter transits, which are also used for geometrical calibration of the focal plane.