Impact of Rubin Observatory LSST Template Acquisition Strategies on Early Science from the Transients and Variable Stars Science Collaboration: Non-time-critical Science Cases

Vera C. Rubin Observatory Legacy Survey of Space and Time, LSST, will revolutionize modern astronomy by producing an extremely deep (coadded depth ~27 mag) depth-limited survey of the entire southern sky (LSST Science Collaboration et al. 2009). The 8.4 m large-aperture, wide-field telescope, which is based in Cerro Pachón, will image the entire Southern sky every three nights in multiple bands (SDSS-u, g, r, i, z, y) and produce a fire-hose of data, 20 Tb each night, concluding in a 60 petabyte data set as the legacy of the 10 yr survey. Extracting meaningful light curves from variable objects requires difference imaging to both identify variability and calibrate light curve data products. Templates, co-added groups of visits that act as an image of the "static" sky, are a key component of Difference Imaging Analysis (DIA) and as such are of paramount importance for all science that involves variable objects. As the "non-time-critical" science cases discussed here are mostly periodic, they generally do not depend upon the survey alert stream; however, templates are still crucial for performing science and calibrations during the first year. We provide recommendations for observing strategies for template acquisition starting from commissioning and through Year 1 of the survey

Introducing a framework to assess newly created questions with Natural Language Processing

Statistical models such as those derived from Item Response Theory (IRT) enable the assessment of students on a specific subject, which can be useful for several purposes (e.g., learning path customization, drop-out prediction). However, the questions have to be assessed as well and, although it is possible to estimate with IRT the characteristics of questions that have already been answered by several students, this technique cannot be used on newly generated questions. In this paper, we propose a framework to train and evaluate models for estimating the difficulty and discrimination of newly created Multiple Choice Questions by extracting meaningful features from the text of the question and of the possible choices. We implement one model using this framework and test it on a real-world dataset provided by CloudAcademy, showing that it outperforms previously proposed models, reducing by 6.7% the RMSE for difficulty estimation and by 10.8% the RMSE for discrimination estimation. We also present the results of an ablation study performed to support our features choice and to show the effects of different characteristics of the questions' text on difficulty and discrimination.Comment: Accepted at the International Conference of Artificial Intelligence in Educatio

Red-giant stars in eccentric binaries

The unparalleled photometric data obtained by NASA’s Kepler Space Telescope has led to improved understanding of red-giant stars and binary stars. We discuss the characterization of known eccentric system, containing a solar-like oscillating red-giant primary component. We also report several new binary systems that are candidates for hosting an oscillating companion. A powerful approach to study binary stars is to combine asteroseimic techniques with light curve fitting. Seismology allows us to deduce the properties of red giants. In addition, by modeling the ellipsoidal modulations we can constrain the parameters of the binary system. An valuable independent source are ground-bases, high-resolution spectrographs

Constructions of generalized complex structures in dimension four

Four-manifold theory is employed to study the existence of (twisted) generalized complex structures. It is shown that there exist (twisted) generalized complex structures that have more than one type change loci. In an example-driven fashion, (twisted) generalized complex structures are constructed on a myriad of four-manifolds, both simply and non-simply connected, which are neither complex nor symplectic

Effect of dead space on avalanche speed

The effects of dead space (the minimum distance travelled by a carrier before acquiring enough energy to impact ionize) on the current impulse response and bandwidth of an avalanche multiplication process are obtained from a numerical model that maintains a constant carrier velocity but allows for a random distribution of impact ionization path lengths. The results show that the main mechanism responsible for the increase in response time with dead space is the increase in the number of carrier groups, which qualitatively describes the length of multiplication chains. When the dead space is negligible, the bandwidth follows the behavior predicted by Emmons but decreases as dead space increase