924 resultados para REDSHIFT SURVEYS
Resumo:
Web surveys have been shown to be a viable, and relatively inexpensive, method of data collection with children. For this reason, the Kids’ Life and Times (KLT) was developed as an annual online survey of 10 and 11 year old children. Each year, approximately 4,000 children participate in the survey. Throughout the six years that KLT has been running, a range of questions has been asked that are both policy-relevant and important to the lives of children. Given the method employed by the survey, no extremely sensitive questions that might cause the children distress are included. The majority of questions on KLT are closed yielding quantitative data that are analysed statistically; however, one regular open-ended question is included at the end of KLT each year so that the children can suggest questions that they think should be asked on the survey the following year. While most of the responses are innocuous, each year a small minority of children suggest questions on child abuse and neglect. This paper reports the responses to this question and reflects on how researchers can, and should, deal with this issue from both a methodological and an ethical perspective.
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Efficient identification and follow-up of astronomical transients is hindered by the need for humans to manually select promising candidates from data streams that contain many false positives. These artefacts arise in the difference images that are produced by most major ground-based time-domain surveys with large format CCD cameras. This dependence on humans to reject bogus detections is unsustainable for next generation all-sky surveys and significant effort is now being invested to solve the problem computationally. In this paper, we explore a simple machine learning approach to real-bogus classification by constructing a training set from the image data of similar to 32 000 real astrophysical transients and bogus detections from the Pan-STARRS1 Medium Deep Survey. We derive our feature representation from the pixel intensity values of a 20 x 20 pixel stamp around the centre of the candidates. This differs from previous work in that it works directly on the pixels rather than catalogued domain knowledge for feature design or selection. Three machine learning algorithms are trained (artificial neural networks, support vector machines and random forests) and their performances are tested on a held-out subset of 25 per cent of the training data. We find the best results from the random forest classifier and demonstrate that by accepting a false positive rate of 1 per cent, the classifier initially suggests a missed detection rate of around 10 per cent. However, we also find that a combination of bright star variability, nuclear transients and uncertainty in human labelling means that our best estimate of the missed detection rate is approximately 6 per cent.
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We present observational data for a peculiar supernova discovered by the OGLE-IV survey and followed by the Public ESO Spectroscopic Survey for Transient Objects. The inferred redshift of z = 0.07 implies an absolute magnitude in the rest-frame I-band of M-1 similar to -17.6 mag. This places it in the luminosity range between normal Type Ia SNe and novae. Optical and near infrared spectroscopy reveal mostly Ti and Ca lines, and an unusually red color arising from strong depression of flux at rest wavelengths
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We investigate the use of type Ic superluminous supernovae (SLSN Ic) as standardizable candles and distance indicators. Their appeal as cosmological probes stems from their remarkable peak luminosities, hot blackbody temperatures, and bright rest-frame ultraviolet emission. We present a sample of 16 published SLSN, from redshifts 0.1 to 1.2, and calculate accurate K corrections to determine uniform magnitudes in 2 synthetic rest-frame filter bandpasses with central wavelengths at 400 nm and 520 nm. At 400 nm, we find an encouragingly low scatter in their uncorrected, raw mean magnitudes with M(400) = -21.86 ± 0.35 mag for the full sample of 16 objects. We investigate the correlation between their decline rates and peak magnitude and find that the brighter events appear to decline more slowly. In a manner similar to the Phillips relation for type Ia SNe (SNe Ia), we define a ΔM 20 decline relation. This correlates peak magnitude and decline over 20 days and can reduce the scatter in standardized peak magnitudes to ±0.22 mag. We further show that M(400) appears to have a strong color dependence. Redder objects are fainter and also become redder faster. Using this peak magnitudecolor evolution relation, a surprisingly low scatter of between ±0.08 mag and ±0.13 mag can be found in peak magnitudes, depending on sample selection. However, we caution that only 8 to 10 objects currently have enough data to test this peak magnitudecolor evolution relation. We conclude that SLSN Ic are promising distance indicators in the high-redshift universe in regimes beyond those possible with SNe Ia. Although the empirical relationships are encouraging, the unknown progenitor systems, how they may evolve with redshift, and the uncertain explosion physics are of some concern. The two major measurement uncertainties are the limited numbers of low-redshift, well-studied objects available to test these relationships and internal dust extinction in the host galaxies.
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We present observations and analysis of PS1-10bzj, a superluminous supernova (SLSN) discovered in the Pan-STARRS Medium Deep Survey at a redshift z = 0.650. Spectroscopically, PS1-10bzj is similar to the hydrogen-poor SLSNe 2005ap and SCP 06F6, though with a steeper rise and lower peak luminosity (M bol ~= -21.4 mag) than previous events. We construct a bolometric light curve, and show that while PS1-10bzj's energetics were less extreme than previous events, its luminosity still cannot be explained by radioactive nickel decay alone. We explore both a magnetar spin-down and circumstellar interaction scenario and find that either can fit the data. PS1-10bzj is located in the Extended Chandra Deep Field South and the host galaxy is imaged in a number of surveys, including with the Hubble Space Telescope. The host is a compact dwarf galaxy (MB ≈ -18 mag, diameter
Resumo:
We present the Pan-STARRS1 discovery of PS1-10afx, a unique hydrogen-deficient superluminous supernova (SLSN) at redshift z = 1.388. The light curve peaked at z P1 = 21.7 mag, making PS1-10afx comparable to the most luminous known SNe, with Mu = -22.3 mag. Our extensive optical and near-infrared observations indicate that the bolometric light curve of PS1-10afx rose on the unusually fast timescale of ~12 days to the extraordinary peak luminosity of 4.1 × 1044 erg s-1 (M bol = -22.8 mag) and subsequently faded rapidly. Equally important, the spectral energy distribution is unusually red for an SLSN, with a color temperature of ~6800 K near maximum light, in contrast to previous hydrogen-poor SLSNe, which are bright in the ultraviolet (UV). The spectra more closely resemble those of a normal SN Ic than any known SLSN, with a photospheric velocity of ~11, 000 km s-1 and evidence for line blanketing in the rest-frame UV. Despite the fast rise, these parameters imply a very large emitting radius (gsim 5 × 1015 cm). We demonstrate that no existing theoretical model can satisfactorily explain this combination of properties: (1) a nickel-powered light curve cannot match the combination of high peak luminosity with the fast timescale; (2) models powered by the spindown energy of a rapidly rotating magnetar predict significantly hotter and faster ejecta; and (3) models invoking shock breakout through a dense circumstellar medium cannot explain the observed spectra or color evolution. The host galaxy is well detected in pre-explosion imaging with a luminosity near L*, a star formation rate of ~15 M ⊙ yr-1, and is fairly massive (~2 × 1010 M ⊙), with a stellar population age of ~108 yr, also in contrast to the young dwarf hosts of known hydrogen-poor SLSNe. PS1-10afx is distinct from known examples of SLSNe in its spectra, colors, light-curve shape, and host galaxy properties, suggesting that it resulted from a different channel than other hydrogen-poor SLSNe.
Resumo:
Based on models with calibrated parameters for infection, case fatality rates, and vaccine efficacy, basic childhood vaccinations have been estimated to be highly cost effective. We estimate the association of vaccination with mortality directly from survey data. Using 149 cross-sectional Demographic and Health Surveys, we determine the relationship between vaccination coverage and under five mortality at the survey cluster level. Our data include approximately one million children in 68,490 clusters in 62 countries. We consider the childhood measles, Bacille Calmette-Guérin (BCG), Diphtheria-Pertussis-Tetanus (DPT), Polio, and maternal tetanus vaccinations. Using modified Poisson regression to estimate the relative risk of child mortality in each cluster, we also adjust for selection bias caused by the vaccination status of dead children not being reported. Childhood vaccination, and in particular measles and tetanus vaccination, is associated with substantial reductions in childhood mortality. We estimate that children in clusters with complete vaccination coverage have relative risk of mortality 0.73 (95% Confidence Interval: 0.68, 0.77) that of children in a cluster with no vaccination. While widely used, basic vaccines still have coverage rates well below 100% in many countries, and our results emphasize the effectiveness of increasing their coverage rates in order to reduce child mortality.
Resumo:
Senior thesis written for Oceanography 444