Discovery of a z = 0.65 post-starburst BAL quasar in the DES supernova fields

We present the discovery of a z = 0.65 low-ionization broad absorption line (LoBAL) quasar in a post-starburst galaxy in data from the Dark Energy Survey (DES) and spectroscopy from the Australian Dark Energy Survey (OzDES). LoBAL quasars are a minority of all BALs, and rarer still is that this object also exhibits broad Fe II (an FeLoBAL) and Balmer absorption. This is the first BAL quasar that has signatures of recently truncated star formation, which we estimate ended about 40 Myr ago. The characteristic signatures of an FeLoBAL require high column densities, which could be explained by the emergence of a young quasar from an early, dust-enshrouded phase, or by clouds compressed by a blast wave. The age of the starburst component is comparable to estimates of the lifetime of quasars, so if we assume the quasar activity is related to the truncation of the star formation, this object is better explained by the blast wave scenario

The Autonomy of Expression and the Becoming Musical of Classicism, Romanticism, and Modernism

The Autonomy of Expression and the Becoming Musical of Classicism, Romanticism, and Modernis

A rational inattention unemployment trap

We show that introducing rational inattention into a model with uninsurable unemployment risk can generate multiple steady states, when the model with full information has a unique steady state. The model features persistent, heterogeneous labour market expectations, consistent with survey evidence. In a heterogeneous agent New Keynesian model, rational inattention to the future hiring rate generates three steady states: an unemployment trap with mild deflation and a low (but positive) job hiring rate, a middle steady state with moderate employment and inflation, and an ‘employment trap’ with high employment and inflation. Large mutations in the distribution of household beliefs can shift the economy between steady states

Narrative-Driven Fluctuations in Sentiment: Evidence Linking Traditional and Social Media

This paper studies the role of narratives for macroeconomic fluctuations. Microfounding narratives as directed acyclic graphs, we show how exposure to different narratives can affect expectations in an otherwise-standard macroeconomic framework. We identify such competing narratives in news media reports on the US yield curve inversion in 2019, using techniques in natural language processing. Linking this to data from Twitter, we show that exposure to the narrative of an imminent recession causes consumers to display a more pessimistic sentiment, while exposure to a more neutral narrative implies no such change in sentiment. Applying the same technique to media narratives on inflation, we estimate that a shift to a viral narrative of inflation damaging the real economy in 2021 accounts for 42% of the fall in consumer sentiment in the second half of the year

Narrative-driven fluctuations in sentiment: evidence linking traditional and social media

This paper studies the role of narratives for macroeconomic fluctuations. Micro-founding narratives as directed acyclic graphs, we show how exposure to different narratives can affect expectations in an otherwise-standard macroeconomic framework. We identify such competing narratives in news media reports on the US yield curve inversion in 2019, using techniques in natural language processing. Linking this to data from Twitter, we show that exposure to the narrative of an imminent recession causes consumers to display a more pessimistic sentiment, while exposure to a more neutral narrative implies no such change in sentiment. Applying the same technique to media narratives on inflation, we estimate that a shift to a viral narrative of inflation damaging the real economy in 2021 accounts for 42% of the fall in consumer sentiment in the second half of the year

A study of quasar selection in the supernova fields of the Dark Energy Survey

We present a study of quasar selection using the supernova fields of the Dark Energy Survey (DES). We used a quasar catalog from an overlapping portion of the SDSS Stripe 82 region to quantify the completeness and efficiency of selection methods involving color, probabilistic modeling, variability, and combinations of color/ probabilistic modeling with variability. In all cases, we considered only objects that appear as point sources in the DES images. We examine color selection methods based on the Wide-field Infrared Survey Explorer (WISE) mid- IR W1 - W2 color, a mixture of WISE and DES colors (g − i and i - W1), and a mixture of Vista Hemisphere Survey and DES colors (g − i and i − K ). For probabilistic quasar selection, we used XDQSO, an algorithm that employs an empirical multi-wavelength flux model of quasars to assign quasar probabilities. Our variability selection uses the multi-band χ2-probability that sources are constant in the DES Year 1 griz-band light curves. The completeness and efficiency are calculated relative to an underlying sample of point sources that are detected in the required selection bands and pass our data quality and photometric error cuts. We conduct our analyses at two magnitude limits, i85% for both i-band magnitude limits and efficiencies of >80% to the bright limit and >60% to the faint limit; however, the giW1 and giW1+variability methods give the highest quasar surface densities. The XDQSOz method and combinations of W1W2/giW1/XDQSOz with variability are among the better selection methods when both high completeness and high efficiency are desired. We also present the OzDES Quasar Catalog of 1263 spectroscopically confirmed quasars from three years of OzDES observation in the 30 deg2 of the DES supernova fields. The catalog includes quasars with redshifts up to z4 and brighter than i = 22 mag, although the catalog is not complete up to this magnitude limit

DES Science Portal: Computing Photometric Redshifts

International audienceA significant challenge facing photometric surveys for cosmological purposes is the need to produce reliable redshift estimates. The estimation of photometric redshifts (photo- z s) has been consolidated as the standard strategy to bypass the high production costs and incompleteness of spectroscopic redshift samples. Training-based photo- z methods require the preparation of a high-quality list of spectroscopic redshifts, which needs to be constantly updated. The photo- z training, validation, and estimation must be performed in a consistent and reproducible way in order to accomplish the scientific requirements. To meet this purpose, we developed an integrated web-based data interface that not only provides the framework to carry out the above steps in a systematic way, enabling the ease testing and comparison of different algorithms, but also addresses the processing requirements by parallelizing the calculation in a transparent way for the user. This framework called the Science Portal (hereafter Portal) was developed in the context the Dark Energy Survey (DES) to facilitate scientific analysis. In this paper, we show how the Portal can provide a reliable environment to access vast datasets, provide validation algorithms and metrics, even in the case of multiple photo- z s methods. It is possible to maintain the provenance between the steps of a chain of workflows while ensuring reproducibility of the results. We illustrate how the Portal can be used to provide photo- z estimates using the DES first year (Y1A1) data. While the DES collaboration is still developing techniques to obtain more precise photo- z s, having a structured framework like the one presented here is critical for the systematic vetting of DES algorithmic improvements and the consistent production of photo- z s in future DES releases