Exploring Parameter Constraints on Quintessential Dark Energy: The Exponential Model

We present an analysis of a scalar field model of dark energy with an exponential potential using the Dark Energy Task Force (DETF) simulated data models. Using Markov Chain Monte Carlo sampling techniques we examine the ability of each simulated data set to constrain the parameter space of the exponential potential for data sets based on a cosmological constant and a specific exponential scalar field model. We compare our results with the constraining power calculated by the DETF using their ``$w_0-w_a$'' parametrization of the dark energy. We find that respective increases in constraining power from one stage to the next produced by our analysis give results consistent with DETF results. To further investigate the potential impact of future experiments, we also generate simulated data for an exponential model background cosmology which can not be distinguished from a cosmological constant at DETF ``Stage 2'', and show that for this cosmology good DETF Stage 4 data would exclude a cosmological constant by better than 3$\sigma$.Comment: 11 pages including 10 figure

What does inflation really predict?

If the inflaton potential has multiple minima, as may be expected in, e.g., the string theory "landscape", inflation predicts a probability distribution for the cosmological parameters describing spatial curvature (Omega_tot), dark energy (rho_Lambda, w, etc.), the primordial density fluctuations (Omega_tot, dark energy (rho_Lambda, w, etc.). We compute this multivariate probability distribution for various classes of single-field slow-roll models, exploring its dependence on the characteristic inflationary energy scales, the shape of the potential V and and the choice of measure underlying the calculation. We find that unless the characteristic scale Delta-phi on which V varies happens to be near the Planck scale, the only aspect of V that matters observationally is the statistical distribution of its peaks and troughs. For all energy scales and plausible measures considered, we obtain the predictions Omega_tot ~ 1+-0.00001, w=-1 and rho_Lambda in the observed ballpark but uncomfortably high. The high energy limit predicts n_s ~ 0.96, dn_s/dlnk ~ -0.0006, r ~ 0.15 and n_t ~ -0.02, consistent with observational data and indistinguishable from eternal phi^2-inflation. The low-energy limit predicts 5 parameters but prefers larger Q and redder n_s than observed. We discuss the coolness problem, the smoothness problem and the pothole paradox, which severely limit the viable class of models and measures. Our findings bode well for detecting an inflationary gravitational wave signature with future CMB polarization experiments, with the arguably best-motivated single-field models favoring the detectable level r ~ 0.03. (Abridged)Comment: Replaced to match accepted JCAP version. Improved discussion, references. 42 pages, 17 fig

Genome-Wide Identification of Transcriptional Start Sites in the Plant Pathogen Pseudomonas syringae pv. tomato str. DC3000

RNA-Seq has provided valuable insights into global gene expression in a wide variety of organisms. Using a modified RNA-Seq approach and Illumina's high-throughput sequencing technology, we globally identified 5′-ends of transcripts for the plant pathogen Pseudomonas syringae pv. tomato str. DC3000. A substantial fraction of 5′-ends obtained by this method were consistent with results obtained using global RNA-Seq and 5′RACE. As expected, many 5′-ends were positioned a short distance upstream of annotated genes. We also captured 5′-ends within intergenic regions, providing evidence for the expression of un-annotated genes and non-coding RNAs, and detected numerous examples of antisense transcription, suggesting additional levels of complexity in gene regulation in DC3000. Importantly, targeted searches for sequence patterns in the vicinity of 5′-ends revealed over 1200 putative promoters and other regulatory motifs, establishing a broad foundation for future investigations of regulation at the genomic and single gene levels

Outer membrane protein folding from an energy landscape perspective

The cell envelope is essential for the survival of Gram-negative bacteria. This specialised membrane is densely packed with outer membrane proteins (OMPs), which perform a variety of functions. How OMPs fold into this crowded environment remains an open question. Here, we review current knowledge about OFMP folding mechanisms in vitro and discuss how the need to fold to a stable native state has shaped their folding energy landscapes. We also highlight the role of chaperones and the β-barrel assembly machinery (BAM) in assisting OMP folding in vivo and discuss proposed mechanisms by which this fascinating machinery may catalyse OMP folding