Transitional YSOs: Candidates from Flat-Spectrum IRAS Sources

We are searching for Young Stellar Objects (YSOs) near the boundary between protostars and pre-main sequence objects, what we have termed transitional YSOs. We have identified a sample of 125 objects as candidate transitional YSOs on the basis of IRAS colors and optical appearance on DSS images. We find that the majority of our objects are associated with star-forming regions, confirming our expectation that the bulk of these are YSOs. We present optical, near-IR and high-resolution IRAS images of 92 objects accessible from the northern and 62 from the southern hemisphere. The objects have been classified on the basis of their morphology and spectral index. Of the 125 objects, 28 have a variety of characteristics very similar to other transitional YSOs, while another 22 show some of these characteristics, suggesting that these transitional YSOs are not as rare as predicted by theory.Comment: 4 pages, 3 figures, to appear in proc. 33rd ESLAB Symposium ``Star Formation from the Small to the Large Scale'', eds. F. Favata et al., ESA SP-44

M DWARF ACTIVITY in the PAN-STARRS1 MEDIUM-DEEP SURVEY: FIRST CATALOG and ROTATION PERIODS

We report on an ongoing project to investigate activity in the M dwarf stellar population observed by the Pan-STARRS1 Medium-Deep Survey (PS1-MDS). Using a custom-built pipeline, we refine an initial sample of ∼4 million sources in PS1-MDS to a sample of 184,148 candidate cool stars using color cuts. Motivated by the well-known relationship between rotation and stellar activity, we use a multiband periodogram analysis and visual vetting to identify 270 sources that are likely rotating M dwarfs. We derive a new set of polynomials relating M dwarf PS1 colors to fundamental stellar parameters and use them to estimate the masses, distances, effective temperatures, and bolometric luminosities of our sample. We present a catalog containing these values, our measured rotation periods, and cross-matches to other surveys. Our final sample spans periods of ≲1-130 days in stars with estimated effective temperatures of ∼2700-4000 K. Twenty-two of our sources have X-ray cross-matches, and they are found to be relatively X-ray bright as would be expected from selection effects. Our data set provides evidence that Kepler-based searches have not been sensitive to very slowly rotating stars (P rot 70 day), implying that the observed emergence of very slow rotators in studies of low-mass stars may be a systematic effect. We also see a lack of low-amplitude (<2%) variability in objects with intermediate (10-40 day) rotation periods, which, considered in conjunction with other observational results, may be a signpost of a loss of magnetic complexity associated with a phase of rapid spin-down in intermediate-age M dwarfs. This work represents just a first step in exploring stellar variability in data from the PS1-MDS and, in the farther future, Large Synoptic Survey Telescope

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype