Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userPS1-STRM: Neural network source classification and photometric redshift catalogue for PS1 $3pi$ DR1
56
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
The Pan-STARRS1 (PS1) $3pi$ survey is a comprehensive optical imaging survey of three quarters of the sky in the $grizy$ broad-band photometric filters. We present the methodology used in assembling the source classification and photometric redshift (photo-z) catalogue for PS1 $3pi$ Data Release 1, titled Pan-STARRS1 Source Types and Redshifts with Machine learning (PS1-STRM). For both main data products, we use neural network architectures, trained on a compilation of public spectroscopic measurements that has been cross-matched with PS1 sources. We quantify the parameter space coverage of our training data set, and flag extrapolation using self-organizing maps. We perform a Monte-Carlo sampling of the photometry to estimate photo-z uncertainty. The final catalogue contains $2,902,054,648$ objects. On our validation data set, for non-extrapolated sources, we achieve an overall classification accuracy of $98.1%$ for galaxies, $97.8%$ for stars, and $96.6%$ for quasars. Regarding the galaxy photo-z estimation, we attain an overall bias of $left<Delta z_{mathrm{norm}}right>=0.0005$, a standard deviation of $sigma(Delta z_{mathrm{norm}})=0.0322$, a median absolute deviation of $mathrm{MAD}(Delta z_{mathrm{norm}})=0.0161$, and an outlier fraction of $O=1.89%$. The catalogue will be made available as a high-level science product via the Mikulski Archive for Space Telescopes at https://doi.org/10.17909//t9-rnk7-gr88.
rate research
Read More
We present the results of a systematic Milky Way satellite search performed across an array of publicly available wide-area photometric surveys. Our aim is to complement previous searches by widening the parameter space covered. Specifically, we focus on objects smaller than $1$ and include old, young, metal poor and metal rich stellar population masks. As a result we find 9 new likely genuine stellar systems in data from GAIA, DES, and Pan-STARRS, which were picked from the candidate list because of conspicuous counterparts in the cut-out images. The presented systems are all very compact ($r_h<1$) and faint ($M_Vgtrsim-3$), and are associated either with the Galactic disk, or the Magellanic Clouds. While most of the stellar systems look like Open Clusters, their exact classification is, as of today, unclear. With these discoveries, we extend the parameter space occupied by star clusters to sizes and luminosities previously unexplored and demonstrate that rather than two distinct classes of Globular and Open clusters, there appears to be a continuity of objects, unmarked by a clear decision boundary.
MiniJPAS is a ~1 deg^2 imaging survey of the AEGIS field in 60 bands, performed to demonstrate the scientific potential of the upcoming JPAS survey. Full coverage of the 3800-9100 AA range with 54 narrow and 6 broad optical filters allow for extremely accurate photo-z, which applied over 1000s of deg^2 will enable new applications of the photo-z technique such as measurement of baryonic acoustic oscillations. In this paper we describe the method used to obtain the photo-z included in the publicly available miniJPAS catalogue, and characterise the photo-z performance. We build 100 AA resolution photo-spectra from the PSF-corrected forced-aperture photometry. Systematic offsets in the photometry are corrected by applying magnitude shifts obtained through iterative fitting with stellar population synthesis models. We compute photo-z with a customised version of LePhare, using a set of templates optimised for the J-PAS filter-set. We analyse the accuracy of miniJPAS photo-z and their dependence on multiple quantities using a subsample of 5,266 galaxies with spectroscopic redshifts from SDSS and DEEP, that we find to be representative of the whole r<23 miniJPAS sample. Formal uncertainties for the photo-z that are calculated with the deltachi^2 method underestimate the actual redshift errors. The odds parameter has the stronger correlation with |Dz|, and accurately reproduces the probability of a redshift outlier (|Dz|>0.03) irrespective of the magnitude, redshift, or spectral type of the sources. We show that the two main summary statistics characterising the photo-z accuracy for a population of galaxies (snmad and eta) can be predicted by the distribution of odds in such population, and use this to estimate them for the whole miniJPAS sample. At r<23 there are 17,500 galaxies/deg^2 with valid photo-z estimates, of which 4,200 are expected to have |Dz|<0.003 (abridged).
We present optical photometric and spectroscopic coverage of the superluminous supernova (SLSN) PS1-11ap, discovered with the Pan-STARRS1 Medium Deep Survey at z = 0.524. This intrinsically blue transient rose slowly to reach a peak magnitude of M_u = -21.4 mag and bolometric luminosity of 8 x 10^43 ergs^-1 before settling onto a relatively shallow gradient of decline. The observed decline is significantly slower than those of the superluminous type Ic SNe which have been the focus of much recent attention. Spectroscopic similarities with the lower redshift SN2007bi and a decline rate similar to 56Co decay timescale initially indicated that this transient could be a candidate for a pair instability supernova (PISN) explosion. Overall the transient appears quite similar to SN2007bi and the lower redshift object PTF12dam. The extensive data set, from 30 days before peak to 230 days after, allows a detailed and quantitative comparison with published models of PISN explosions. We find that the PS1-11ap data do not match these model explosion parameters well, supporting the recent claim that these SNe are not pair instability explosions. We show that PS1-11ap has many features in common with the faster declining superluminous Ic supernovae and the lightcurve evolution can also be quantitatively explained by the magnetar spin down model. At a redshift of z = 0.524 the observer frame optical coverage provides comprehensive restframe UV data and allows us to compare it with the superluminous SNe recently found at high redshifts between z = 2-4. While these high-z explosions are still plausible PISN candidates, they match the photometric evolution of PS1-11ap and hence could be counterparts to this lower redshift transient.
We present a nuclear transient event, PS1-13cbe, that was first discovered in the Pan-STARRS1 survey in 2013. The outburst occurred in the nucleus of the galaxy SDSS J222153.87+003054.2 at $z = 0.12355$, which was classified as a Seyfert 2 in a pre-outburst archival Sloan Digital Sky Survey (SDSS) spectrum. PS1-13cbe showed the appearance of strong broad H$alpha$ and H$beta$ emission lines and a non-stellar continuum in a Magellan spectrum taken 57 days after the peak of the outburst that resembled the characteristics of a Seyfert 1. These broad lines were not present in the SDSS spectrum taken a decade earlier and faded away within two years, as observed in several late-time MDM spectra. We argue that the dramatic appearance and disappearance of the broad lines and factor of $sim 8$ increase in the optical continuum is most likely caused by variability in the pre-existing accretion disk than a tidal disruption event, supernova, or variable obscuration. The timescale for the turn-on of the optical emission of $sim 70$ days observed in this transient is among the shortest observed in a changing look active galactic nucleus.
We present an update to the PanSTARRS-1 Point Source Catalog (PS1 PSC), which provides morphological classifications of PS1 sources. The original PS1 PSC adopted stringent detection criteria that excluded hundreds of millions of PS1 sources from the PSC. Here, we adapt the supervised machine learning methods used to create the PS1 PSC and apply them to different photometric measurements that are more widely available, allowing us to add $sim$144 million new classifications while expanding the the total number of sources in PS1 PSC by $sim$10%. We find that the new methodology, which utilizes PS1 forced photometry, performs $sim$6-8% worse than the original method. This slight degradation in performance is offset by the overall increase in the size of the catalog. The PS1 PSC is used by time-domain surveys to filter transient alert streams by removing candidates coincident with point sources that are likely to be Galactic in origin. The addition of $sim$144 million new classifications to the PS1 PSC will improve the efficiency with which transients are discovered.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
