Black hole masses and enrichment of z ~ 6 SDSS quasars

We present sensitive near-infrared spectroscopic observations for a sample of five z ~ 6 quasars. These are amongst the most distant, currently known quasars in the universe. The spectra have been obtained using ISAAC at the VLT and include the CIV, MgII and FeII lines. We measure the FeII/MgII line ratio, as an observational proxy for the Fe/alpha element ratio. We derive a ratio of 2.7+/-0.8 for our sample, which is similar to that found for lower redshift quasars, i.e., we provide additional evidence for the lack of evolution in the FeII/MgII line ratio of quasars up to the highest redshifts. This result demonstrates that the sample quasars must have undergone a major episode of iron enrichment in less than one Gyr and star formation must have commenced at z > 8. The linewidths of the MgII and CIV lines give two estimates for the black hole masses. A third estimate is given by assuming that the quasars emit at their Eddington luminosity. The derived masses using these three methods agree well, implying that the quasars are not likely to be strongly lensed. We derive central black hole masses of 0.3-5.2 10^9 solar masses. We use the difference between the redshift of MgII (a proxy for the systemic redshift of the quasar) and the onset of the Gunn Peterson trough to derive the extent of the ionized Stromgren spheres around our target quasars. The derived physical radii are about five Mpc. Using a simple ionization model, the emission of the central quasars would need of order 10^6-10^8 year to create these cavities in a surrounding intergalactic medium with a neutral fraction between 0.1 and 1.0. As the e-folding time scale for the central accreting black hole is on the order of a few times 10^7 year, it can grow by one e-folding or less within this time span.Comment: Accepted by ApJ, 15 pages, 8 figure

General Approach for Combining Diverse Rare Variant Association Tests Provides Improved Robustness Across a Wider Range of Genetic Architectures

The widespread availability of genome sequencing data made possible by way of next-generation technologies has yielded a flood of different gene-based rare variant association tests. Most of these tests have been published because they have superior power for particular genetic architectures. However, for applied researchers it is challenging to know which test to choose in practice when little is known a priori about genetic architecture. Recently, tests have been proposed which combine two particular individual tests (one burden and one variance components) to minimize power loss while improving robustness to a wider range of genetic architectures. In our analysis we propose an expansion of these approaches, yielding a general method that works for combining any number of individual tests. We demonstrate that running multiple different tests on the same dataset and using a Bonferroni correction for multiple testing is never better than combining tests using our general method. We also find that using a test statistic that is highly robust to the inclusion of non-causal variants (Joint-infinity) together with a previously published combined test (SKAT-O) provides improved robustness to a wide range of genetic architectures and should be considered for use in practice. Software for this approach is supplied. We support the increased use of combined tests in practice-- as well as further exploration of novel combined testing approaches using the general framework provided here--to maximize robustness of rare-variant testing strategies against a wide range of genetic architectures

The SINS/zC-SINF survey of z~2 galaxy kinematics: Outflow properties

Based on SINFONI Ha, [NII] and [SII] AO data of 30 z \sim 2 star-forming galaxies (SFGs) from the SINS and zcSINF surveys, we find a strong correlation of the Ha broad flux fraction with the star formation surface density of the galaxy, with an apparent threshold for strong outflows occurring at 1 Msun yr^-1 kpc^-2. Above this threshold, we find that SFGs with logm_\ast>10 have similar or perhaps greater wind mass loading factors (eta = Mdotout/SFR) and faster outflow velocities than lower mass SFGs. This trend suggests that the majority of outflowing gas at z \sim 2 may derive from high-mass SFGs, and that the z \sim 2 mass-metallicity relation is driven more by dilution of enriched gas in the galaxy gas reservoir than by the efficiency of outflows. The mass loading factor is also correlated with the SFR and inclination, such that more star-forming and face-on galaxies launch more powerful outflows. For galaxies that have evidence for strong outflows, we find that the broad emission is spatially extended to at least the half-light radius (\sim a few kpc). We propose that the observed threshold for strong outflows and the observed mass loading of these winds can be explained by a simple model wherein break-out of winds is governed by pressure balance in the disk. Using the ratio of the [SII] doublet in a broad and narrow component, we find that outflowing gas has a density of \sim10-100 cm^-3, significantly less than that of the star forming gas (600 cm^-3).Comment: 7 pages, 3 figures, accepted by Ap

Deformation of Crystals : Connections with Statistical Physics

We give a bird's-eye view of the plastic deformation of crystals aimed at the statistical physics community, as well as a broad introduction to the statistical theories of forced rigid systems aimed at the plasticity community. Memory effects in magnets, spin glasses, charge density waves, and dilute colloidal suspensions are discussed in relation to the onset of plastic yielding in crystals. Dislocation avalanches and complex dislocation tangles are discussed via a brief introduction to the renormalization group and scaling. Analogies to emergent scale invariance in fracture, jamming, coarsening, and a variety of depinning transitions are explored. Dislocation dynamics in crystals challenge nonequilibrium statistical physics. Statistical physics provides both cautionary tales of subtle memory effects in nonequilibrium systems and systematic tools designed to address complex scale-invariant behavior on multiple length scales and timescales

Context-driven discovery of gene cassettes in mobile integrons using a computational grammar

<p>Abstract</p> <p>Background</p> <p>Gene discovery algorithms typically examine sequence data for low level patterns. A novel method to computationally discover higher order DNA structures is presented, using a context sensitive grammar. The algorithm was applied to the discovery of gene cassettes associated with integrons. The discovery and annotation of antibiotic resistance genes in such cassettes is essential for effective monitoring of antibiotic resistance patterns and formulation of public health antibiotic prescription policies.</p> <p>Results</p> <p>We discovered two new putative gene cassettes using the method, from 276 integron features and 978 GenBank sequences. The system achieved <it>κ </it>= 0.972 annotation agreement with an expert gold standard of 300 sequences. In rediscovery experiments, we deleted 789,196 cassette instances over 2030 experiments and correctly relabelled 85.6% (<it>α </it>≥ 95%, <it>E </it>≤ 1%, mean sensitivity = 0.86, specificity = 1, F-score = 0.93), with no false positives.</p> <p>Error analysis demonstrated that for 72,338 missed deletions, two adjacent deleted cassettes were labeled as a single cassette, increasing performance to 94.8% (mean sensitivity = 0.92, specificity = 1, F-score = 0.96).</p> <p>Conclusion</p> <p>Using grammars we were able to represent heuristic background knowledge about large and complex structures in DNA. Importantly, we were also able to use the context embedded in the model to discover new putative antibiotic resistance gene cassettes. The method is complementary to existing automatic annotation systems which operate at the sequence level.</p

Sustainable computational science: the ReScience initiative

Computer science o ers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results, however computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel con dent their research is reproducible. But this is not exactly true. Jonathan Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. e actual scholarship is the full so ware environment, code, and data that produced the result. is implies new work ows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested, hardly ever actually executed to check that they produce the results advertised in the article. ReScience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically di erent from other traditional scienti c journals. ReScience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and so ware tests