Exoplanet atmospheres with EChO: spectral retrievals using EChOSim

We demonstrate the effectiveness of the Exoplanet Characterisation Observatory mission concept for constraining the atmospheric properties of hot and warm gas giants and super Earths. Synthetic primary and secondary transit spectra for a range of planets are passed through EChOSim (Waldmann & Pascale 2014) to obtain the expected level of noise for different observational scenarios; these are then used as inputs for the NEMESIS atmospheric retrieval code and the retrieved atmospheric properties (temperature structure, composition and cloud properties) compared with the known input values, following the method of Barstow et al. (2013a). To correctly retrieve the temperature structure and composition of the atmosphere to within 2 {\sigma}, we find that we require: a single transit or eclipse of a hot Jupiter orbiting a sun-like (G2) star at 35 pc to constrain the terminator and dayside atmospheres; 20 transits or eclipses of a warm Jupiter orbiting a similar star; 10 transits/eclipses of a hot Neptune orbiting an M dwarf at 6 pc; and 30 transits or eclipses of a GJ1214b-like planet.Comment: 13 pages, 15 figures, 1 table. Accepted by Experimental Astronomy. The final publication will shortly be available at Springer via http://dx.doi.org/10.1007/s10686-014-9397-

Generation of an optimal target list for the Exoplanet Characterisation Observatory (EChO)

The Exoplanet Characterisation Observatory (EChO) has been studied as a space mission concept by the European Space Agency in the context of the M3 selection process. Through direct measurement of the atmospheric chemical composition of hundreds of exoplanets, EChO would address fundamental questions such as: What are exoplanets made of? How do planets form and evolve? What is the origin of exoplanet diversity? More specifically, EChO is a dedicated survey mission for transit and eclipse spectroscopy capable of observing a large, diverse and well-defined planetary sample within its four to six year mission lifetime. In this paper we use the end-to-end instrument simulator EChOSim to model the currently discovered targets, to gauge which targets are observable and assess the EChO performances obtainable for each observing tier and time. We show that EChO would be capable of observing over 170 relativity diverse planets if it were launched today, and the wealth of optimal targets for EChO expected to be discovered in the next 10 years by space and ground-based facilities is simply overwhelming. In addition, we build on previous molecular detectability studies to show what molecules and abundances will be detectable by EChO for a selection of real targets with various molecular compositions and abundances. EChO's unique contribution to exoplanetary science will be in identifying the main constituents of hundreds of exoplanets in various mass/temperature regimes, meaning that we will be looking no longer at individual cases but at populations. Such a universal view is critical if we truly want to understand the processes of planet formation and evolution in various environments. In this paper we present a selection of key results. The full results are available online (http://www.ucl.ac.uk/exoplanets/echotargetlist/).Comment: Accepted for publication in Experimental Astronomy, 20 pages, 10 figures, 3 table

The impact of initial antibiotic treatment failure: Real-world insights in patients with complicated, health care-associated intra-abdominal infection

Purpose: The RECOMMEND study (NCT02364284; D4280R00005) assessed the clinical management patterns and treatment outcomes associated with initial antibiotic therapy (IAT; antibiotics administered ≤48 hours post-initiation of antibiotic therapy) for health care-associated infections across five countries. Patients and methods: Data were collected from a retrospective chart review of patients aged ≥18 years with health care-associated complicated intra-abdominal infection (cIAI). Potential risk factors for IAT failure were identified using logistic regression analyses. Results: Of 385 patients with complete IAT data, bacterial pathogens were identified in 270 (70.1%), including Gram-negative isolates in 221 (81.9%) and Gram-positive isolates in 92 (34.1%). Multidrug-resistant (MDR) pathogens were identified in 112 patients (41.5% of patients with a pathogen identified). IAT failure rate was 68.3% and in-hospital mortality rate was 40.8%. Multivariate regression analysis demonstrated three factors to be significantly associated with IAT failure: patients admitted/transferred to the intensive care unit during index hospitalization, isolation of an MDR pathogen and previous treatment with β-lactam antibiotics. Conclusion: We reveal the real-world insights into the high rates of IAT failure and mortality observed among patients with cIAI. These data highlight the challenges associated with choosing IAT, the impact of MDR pathogens on IAT outcomes and the importance of tailoring IAT selection to account for local epidemiology and patient history

Master\u27s Recital

Program listing performers and works performe

Context Generation Improves Open Domain Question Answering

Closed-book question answering (QA) requires a model to directly answer an open-domain question without access to any external knowledge. Prior work on closed-book QA either directly finetunes or prompts a pretrained language model (LM) to leverage the stored knowledge. However, they do not fully exploit the parameterized knowledge. To address this issue, we propose a two-stage, closed-book QA framework which employs a coarse-to-fine approach to extract relevant knowledge and answer a question. Our approach first generates a related context for a given question by prompting a pretrained LM. We then prompt the same LM for answer prediction using the generated context and the question. Additionally, to eliminate failure caused by context uncertainty, we marginalize over generated contexts. Experimental results on three QA benchmarks show that our method significantly outperforms previous closed-book QA methods (e.g. exact matching 68.6% vs. 55.3%), and is on par with open-book methods that exploit external knowledge sources (e.g. 68.6% vs. 68.0%). Our method is able to better exploit the stored knowledge in pretrained LMs without adding extra learnable parameters or needing finetuning, and paves the way for hybrid models that integrate pretrained LMs with external knowledge.Comment: 8 pages; Accepted at EACL202

Spectrophotometric Redshifts In The Faint Infrared Grism Survey: Finding Overdensities Of Faint Galaxies

We improve the accuracy of photometric redshifts by including low-resolution spectral data from the G102 grism on the Hubble Space Telescope, which assists in redshift determination by further constraining the shape of the broadband Spectral Energy Disribution (SED) and identifying spectral features. The photometry used in the redshift fits includes near-IR photometry from FIGS+CANDELS, as well as optical data from ground-based surveys and HST ACS, and mid-IR data from Spitzer. We calculated the redshifts through the comparison of measured photometry with template galaxy models, using the EAZY photometric redshift code. For objects with F105W $< 26.5$ AB mag with a redshift range of $0 < z < 6$, we find a typical error of $\Delta z = 0.03 * (1+z)$ for the purely photometric redshifts; with the addition of FIGS spectra, these become $\Delta z = 0.02 * (1+z)$, an improvement of 50\%. Addition of grism data also reduces the outlier rate from 8\% to 7\% across all fields. With the more-accurate spectrophotometric redshifts (SPZs), we searched the FIGS fields for galaxy overdensities. We identified 24 overdensities across the 4 fields. The strongest overdensity, matching a spectroscopically identified cluster at $z=0.85$, has 28 potential member galaxies, of which 8 have previous spectroscopic confirmation, and features a corresponding X-ray signal. Another corresponding to a cluster at $z=1.84$ has 22 members, 18 of which are spectroscopically confirmed. Additionally, we find 4 overdensities that are detected at an equal or higher significance in at least one metric to the two confirmed clusters.Comment: 17 pages, 13 figures. To appear in Ap

Emission Line Metallicities From The Faint Infrared Grism Survey and VLT/MUSE

We derive direct measurement gas-phase metallicities of $7.4 < 12 + \log(O/H) < 8.4$ for 14 low-mass Emission Line Galaxies (ELGs) at $0.3 < z < 0.8$ identified in the Faint Infrared Grism Survey (FIGS). We use deep slitless G102 grism spectroscopy of the Hubble Ultra Deep Field (HUDF), dispersing light from all objects in the field at wavelengths between 0.85 and 1.15 microns. We run an automatic search routine on these spectra to robustly identify 71 emission line sources, using archival data from VLT/MUSE to measure additional lines and confirm redshifts. We identify 14 objects with $0.3 < z < 0.8$ with measurable O[III]$\lambda$4363 \AA\ emission lines in matching VLT/MUSE spectra. For these galaxies, we derive direct electron-temperature gas-phase metallicities with a range of $7.4 < 12 + \log(O/H) < 8.4$. With matching stellar masses in the range of $10^{7.9} M_{\odot} < M_{\star} < 10^{10.4} M_{\odot}$, we construct a mass-metallicity (MZ) relation and find that the relation is offset to lower metallicities compared to metallicities derived from alternative methods (e.g.,$R_{23}$, O3N2, N2O2) and continuum selected samples. Using star formation rates (SFR) derived from the $H\alpha$ emission line, we calculate our galaxies' position on the Fundamental Metallicity Relation (FMR), where we also find an offset toward lower metallicities. This demonstrates that this emission-line-selected sample probes objects of low stellar masses but even lower metallicities than many comparable surveys. We detect a trend suggesting galaxies with higher Specific Star Formation (SSFR) are more likely to have lower metallicity. This could be due to cold accretion of metal-poor gas that drives star formation, or could be because outflows of metal-rich stellar winds and SNe ejecta are more common in galaxies with higher SSFR.Comment: 14 pages, 11 figures, accepted in Ap

Atmospheric neutrino flux supported by recent muon experiments

We present a new one-dimensional calculation of low and intermediate energy atmospheric muon and neutrino fluxes, using up-to-date data on primary cosmic rays and hadronic interactions. We study several sources of uncertainties relevant to our calculations. A comparison with the muon fluxes and charge ratios measured in several modern balloon-borne experiments suggests that the atmospheric neutrino flux is essentially lower than one used for the standard analyses of the sub-GeV and multi-GeV neutrino induced events in underground detectors.Comment: 23 pages, 7 figures, 2 tables. Typos corrected, figure layout improved, references added. Final version accepted for publication in PL