The Pan-STARRS Moving Object Processing System

We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern software package that produces automatic asteroid discoveries and identifications from catalogs of transient detections from next-generation astronomical survey telescopes. MOPS achieves >99.5% efficiency in producing orbits from a synthetic but realistic population of asteroids whose measurements were simulated for a Pan-STARRS4-class telescope. Additionally, using a nonphysical grid population, we demonstrate that MOPS can detect populations of currently unknown objects such as interstellar asteroids. MOPS has been adapted successfully to the prototype Pan-STARRS1 telescope despite differences in expected false detection rates, fill-factor loss, and relatively sparse observing cadence compared to a hypothetical Pan-STARRS4 telescope and survey. MOPS remains highly efficient at detecting objects but drops to 80% efficiency at producing orbits. This loss is primarily due to configurable MOPS processing limits that are not yet tuned for the Pan-STARRS1 mission. The core MOPS software package is the product of more than 15 person-years of software development and incorporates countless additional years of effort in third-party software to perform lower-level functions such as spatial searching or orbit determination. We describe the high-level design of MOPS and essential subcomponents, the suitability of MOPS for other survey programs, and suggest a road map for future MOPS development.

Toward Characterization Of The Type IIP Supernova Progenitor Population: A Statistical Sample Of Light Curves From Pan-STARRS1

In recent years, wide-field sky surveys providing deep multi-band imaging have presented a new path for indirectly characterizing the progenitor populations of core-collapse supernovae (SN): systematic light curve studies. We assemble a set of 76 grizy-band Type IIP SN light curves from Pan-STARRS1, obtained over a constant survey program of 4 years and classified using both spectroscopy and machine learning-based photometric techniques. We develop and apply a new Bayesian model for the full multi-band evolution of each light curve in the sample. We find no evidence of a sub-population of fast-declining explosions (historically referred to as "Type IIL" SNe). However, we identify a highly significant relation between the plateau phase decay rate and peak luminosity among our SNe IIP. These results argue in favor of a single parameter, likely determined by initial stellar mass, predominantly controlling the explosions of red supergiants. This relation could also be applied for supernova cosmology, offering a standardizable candle good to an intrinsic scatter of 0.2 mag. We compare each light curve to physical models from hydrodynamic simulations to estimate progenitor initial masses and other properties of the Pan-STARRS1 Type IIP SN sample. We show that correction of systematic discrepancies between modeled and observed SN IIP light curve properties and an expanded grid of progenitor properties, are needed to enable robust progenitor inferences from multi-band light curve samples of this kind. This work will serve as a pathfinder for photometric studies of core-collapse SNe to be conducted through future wide field transient searches.

The main-belt comets: The Pan-STARRS1 perspective

We analyze a set of 760 475 observations of 333 026 unique main-belt objects obtained by the Pan-STARRS1(PS1) survey telescope between 2012 May 20 and 2013 November 9, a period during which PS1 discoveredtwo main-belt comets, P/2012 T1 (PANSTARRS) and P/2013 R3 (Catalina-PANSTARRS). PS1 cometdetection procedures currently consist of the comparison of the point spread functions (PSFs) of movingobjects to those of reference stars, and the flagging of objects that show anomalously large radial PSFwidths for human evaluation and possible observational follow-up. Based on the number of missed discoveryopportunities among comets discovered by other observers, we estimate an upper limit comet discoveryefficiency rate of 70% for PS1. Additional analyses that could improve comet discovery yields infuture surveys include linear PSF analysis, modeling of trailed stellar PSFs for comparison to trailed movingobject PSFs, searches for azimuthally localized activity, comparison of point-source-optimized photometryto extended-source-optimized photometry, searches for photometric excesses in objects withknown absolute magnitudes, and crowd-sourcing. Analysis of the discovery statistics of the PS1 surveyindicates an expected fraction of 59 MBCs per 106 outer main-belt asteroids (corresponding to a totalexpected population of 140 MBCs among the outer main-belt asteroid population with absolute magnitudesof 12 < HV < 19:5), and a 95% confidence upper limit of 96 MBCs per 106 outer main-belt asteroids(corresponding to a total of 230 MBCs), assuming a detection efficiency of 50%. We note howeverthat significantly more sensitive future surveys (particularly those utilizing larger aperture telescopes)could detect many more MBCs than estimated here. Examination of the orbital element distribution ofall known MBCs reveals an excess of high eccentricities (0:1 < e < 0:3) relative to the background asteroidpopulation. Theoretical calculations show that, given these eccentricities, the sublimation rate for atypical MBC is orders of magnitude larger at perihelion than at aphelion, providing a plausible physicalexplanation for the observed behavior of MBCs peaking in observed activity strength near perihelion.These results indicate that the overall rate of mantle growth should be slow, consistent with observationalevidence that MBC activity can be sustained over multiple orbit passages.

Absolute Magnitudes of Pan-STARRS PS1 Asteroids

Absolute magnitude (H) of an asteroid is a fundamental parameter describing the size and the apparent brightness of the body. Because of its surface shape, properties and changing illumination, the brightness changes with the geometry and is described by the phase function governed by the slope parameter (G). Although many years have been spent on detailed observations of individual asteroids to provide H and G, vast majority of minor planets have H based on assumed G and due to the input photometry from multiple sources the errors of these values are unknown. We compute H of ~ 180 000 and G of few thousands asteroids observed with the Pan-STARRS PS1 telescope in well defined photometric systems. The mean photometric error is 0.04 mag. Because on average there are only 7 detections per asteroid in our sample, we employed a Monte Carlo (MC) technique to generate clones simulating all possible rotation periods, amplitudes and colors of detected asteroids. Known asteroid colors were taken from the SDSS database. We used debiased spin and amplitude distributions dependent on size, spectral class distributions of asteroids dependent on semi-major axis and starting values of G from previous works. H and G (G12 respectively) were derived by phase functions by Bowell et al. (1989) and Muinonen et al. (2010). We confirmed that there is a positive systematic offset between H based on PS1 asteroids and Minor Planet Center database up to -0.3 mag peaking at 14. Similar offset was first mentioned in the analysis of SDSS asteroids and was believed to be solved by weighting and normalizing magnitudes by observatory codes. MC shows that there is only a negligible difference between Bowell's and Muinonen's solution of H. However, Muinonen's phase function provides smaller errors on H. We also derived G and G12 for thousands of asteroids. For known spectral classes, slope parameters agree with the previous work in general, however, the standard deviation of G in our sample is twice as larger, most likely due to sparse phase curve sampling. In the near future we plan to complete the H and G determination for all PS1 asteroids (500,000) and publish H and G values online. This work was supported by NASA grant No. NNX12AR65G.

Absolute Magnitudes of Pan-STARRS 1 Asteroids

It is well known that the absolute magnitudes (H) in the MPCORB and ASTORB orbital element catalogs suffer from a systematic offset. Juric at al. (2002) found 0.4 mag offset in the SDSS data and detailed light curve studies of WISE asteroids by Pravec et al. (2012) revealed size-dependent offsets of up to 0.5 mag. The offsets are thought to be caused by systematic errors introduced by earlier surveys using different photometric catalogs and filters. The next generation asteroid surveys provide an order of magnitude more asteroids and well-defined and calibrated magnitudes. The Pan-STARRS 1 telescope (PS1) has observed hundreds of thousands asteroids, submitted more than 2 million detections to the Minor Planet Center (MPC) and discovered almost 300 NEOs since the beginning of operations in late 2010. We transformed the observed apparent magnitudes of PS1-detected asteroids from the gP1,rP1,iP1,yP1,zP1 and wP1-bands into Johnson photometric system by assuming the mean S and C-type asteroid color (Fitzsimmons 2011 - personal communication, Schlafly et al. 2012, Magnier et al. 2012 - in preparation) and calculated the absolute magnitude (H) in the V-band and its uncertainty (Bowell et al., 1989) for more than 200,000 known asteroids having on average 6.7 detections per object. The H error with respect to the MPCORB catalog revealed a mean offset of -0.49+0.30 mag in good agreement with published values. We will also discuss the statistical and systematical errors in H and slope parameter G.

Discovery of Main-Belt Comet P/2006 VW139 by Pan-STARRS1

We describe the discovery of comet-like activity in main-belt asteroid (300163) 2006 VW139 (later re-designated as Comet P/2006 VW139) by Pan-STARRS1. We also detail follow-up photometric, spectroscopic, and dynamical analyses of the object.

Absolute magnitudes and slope parameters of Pan-STARRS PS1 asteroids -preliminary results

We present the study of absolute magnitude (H) and slope parameter (G) of 170,000 asteroids observed by the Pan-STARRS1 telescope during the period of 15 months within its 3-year all-sky survey mission. The exquisite photometry with photometric errors below 0.04 mag and well-defined filter and photometric system allowed to derive H and G with statistical and systematic errors. Our new approach lies in the Monte Carlo technique simulating rotation periods, amplitudes, and colors, and deriving most-likely H, G and their systematic errors. Comparison of H_M by Muinonen's phase function (Muinonen et al., 2010) with the Minor Planet Center database revealed a negative offset of 0.22±0.29 meaning that Pan-STARRS1 asteroids are fainter. We showed that the absolute magnitude derived by Muinonen's function is systematically larger on average by 0.14±0.29 and by 0.30±0.16 when assuming fixed slope parameter (G=0.15, G_{12}=0.53) than Bowell's absolute magnitude (Bowell et al., 1989). We also derived slope parameters of asteroids of known spectral types and showed a good agreement with the previous studies within the derived uncertainties. However, our systematic errors on G and G_{12} are significantly larger than in previous work, which is caused by poor temporal and phase coverage of vast majority of the detected asteroids. This disadvantage will vanish when full survey data will be available and ongoing extended and enhanced mission will provide new data.

Machine learning for transient discovery in Pan-STARRS1 difference imaging

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.

Selecting superluminous supernovae in faint galaxies from the first year of the Pan-STARRS1 Medium Deep Survey

The Pan-STARRS1 (PS1) survey has obtained imaging in five bands (grizyP1) over 10 Medium Deep Survey (MDS) fields covering a total of 70 square degrees. This paper describes the search for apparently hostless supernovae (SNe) within the first year of PS1 MDS data with an aim of discovering superluminous supernovae (SLSNe). A total of 249 hostless transients were discovered down to a limiting magnitude of MAB ∼ 23.5, of which 76 were classified as Type Ia supernovae (SNe Ia). There were 57 SNe with complete light curves that are likely core-collapse SNe (CCSNe) or type Ic SLSNe and 12 of these have had spectra taken. Of these 12 hostless, non-Type Ia SNe, 7 were SLSNe of type Ic at redshifts between 0.5 and 1.4. This illustrates that the discovery rate of type Ic SLSNe can be maximized by concentrating on hostless transients and removing normal SNe Ia. We present data for two possible SLSNe; PS1-10pm (z = 1.206) and PS1-10ahf (z = 1.1), and estimate the rate of type Ic SLSNe to be between 3+3−2×10−53+3−2×10−53+3−2×10−5 and 8+2−1×10−58+2−1×10−58+2−1×10−5 that of the CCSN rate within 0.3 ≤ z ≤ 1.4 by applying a Monte Carlo technique. The rate of slowly evolving, type Ic SLSNe (such as SN2007bi) is estimated as a factor of 10 lower than this range.

Selection of burst-like transients and stochastic variables using multi-brand image differencing in the Pan-STARRS1 Medium Deep Survey

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands gP1, rP1, iP1, and zP1. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.

Absolute magnitudes and slope parameters for 250,000 asteroids observed by Pan-STARRS PS1 - preliminary results

We present the results of a Monte Carlo technique to calculate the absolute magnitudes (H) and slope parameters (G) of about 240,000 asteroids observed by the Pan-STARRS1 telescope during the first 15 months of its 3-year all-sky survey mission. The system's exquisite photometry with photometric errors asteroids rotation period, amplitude and color to derive the most-likely H and G, but its major advantage is in estimating realistic statistical+systematic uncertainties and errors on each parameter. The method was confirmed by comparison with the well-established and accurate results for about 500 asteroids provided by Pravec et al. (2012) and then applied to determining H and G for the Pan-STARRS1 asteroids using both the Muinonen et al. (2010) and Bowell et al. (1989) phase functions. Our results confirm the bias in MPC photometry discovered by ( Jurić et al., 2002).

Potentially harmful excipients in neonatal medicines: A pan-European observational study

Objectives We aimed to describe administration of eight potentially harmful excipients of interest (EOI)-parabens, polysorbate 80, propylene glycol, benzoates, saccharin sodium, sorbitol, ethanol and benzalkonium chloride-to hospitalised neonates in Europe and to identify risk factors for exposure. Methods All medicines administered to neonates during 1 day with individual prescription and demographic data were registered in a web-based point prevalence study. Excipients were identified from the Summaries of Product Characteristics. Determinants of EOI administration (geographical region, gestational age (GA), active pharmaceutical ingredient, unit level and hospital teaching status) were identified using multivariable logistical regression analysis. Results Overall 89 neonatal units from 21 countries participated. Altogether 2095 prescriptions for 530 products administered to 726 neonates were recorded. EOI were found in 638 (31%) prescriptions and were administered to 456 (63%) neonates through a relatively small number of products (n=142; 27%). Parabens, found in 71 (13%) products administered to 313 (43%) neonates, were used most frequently. EOI administration varied by geographical region, GA and route of administration. Geographical region remained a significant determinant of the use of parabens, polysorbate 80, propylene glycol and saccharin sodium after adjustment for the potential covariates including anatomical therapeutic chemical class of the active ingredient. Conclusions European neonates receive a number of potentially harmful pharmaceutical excipients. Regional differences in EOI administration suggest that EOI-free products are available and provide the potential for substitution to avoid side effects of some excipients.

Systematic Uncertainties Associated with the Cosmological Analysis of the First PAN-STARRS1 Type Ia Supernova Sample

We probe the systematic uncertainties from the 113 Type Ia supernovae (SN Ia) in the Pan-STARRS1 (PS1) sample along with 197 SN Ia from a combination of low-redshift surveys. The companion paper by Rest et al. describes the photometric measurements and cosmological inferences from the PS1 sample. The largest systematic uncertainty stems from the photometric calibration of the PS1 and low-z samples. We increase the sample of observed Calspec standards from 7 to 10 used to define the PS1 calibration system. The PS1 and SDSS-II calibration systems are compared and discrepancies up to ∼0.02 mag are recovered. We find uncertainties in the proper way to treat intrinsic colors and reddening produce differences in the recovered value of w up to 3%. We estimate masses of host galaxies of PS1 supernovae and detect an insignificant difference in distance residuals of the full sample of 0.037 ± 0.031 mag for host galaxies with high and low masses. Assuming flatness and including systematic uncertainties in our analysis of only SNe measurements, we find w = -1.120^+0.360_-0.206(Stat)^+0.269_-0.291(Sys). With additional constraints from Baryon acoustic oscillation, cosmic microwave background (CMB) (Planck) and H₀ measurements, we find w = -1.166^+0.072_-0.069 and Ω_m = 0.280^+0.013_-0.012 (statistical and systematic errors added in quadrature). The significance of the inconsistency with w = -1 depends on whether we use Planck or Wilkinson Microwave Anisotropy Probe measurements of the CMB: w_{BAO+H0+SN+WMAP} = -1.124^+0.083_-0.065.

Cosmological Constraints from Measurements of Type Ia Supernovae Discovered During the First 1.5 Yr of the Pan-STARRS1 Survey

We present griz_P1 light curves of 146 spectroscopically confirmed Type Ia supernovae (SNe Ia; 0.03 < z < 0.65) discovered during the first 1.5 yr of the Pan-STARRS1 Medium Deep Survey. The Pan-STARRS1 natural photometric system is determined by a combination of on-site measurements of the instrument response function and observations of spectrophotometric standard stars. We find that the systematic uncertainties in the photometric system are currently 1.2% without accounting for the uncertainty in the Hubble Space Telescope Calspec definition of the AB system. A Hubble diagram is constructed with a subset of 113 out of 146 SNe Ia that pass our light curve quality cuts. The cosmological fit to 310 SNe Ia (113 PS1 SNe Ia + 222 light curves from 197 low-z SNe Ia), using only supernovae (SNe) and assuming a constant dark energy equation of state and flatness, yields w = -1.120^+0.360_-0.206(Stat)^+0.269_0.291(Sys). When combined with BAO+CMB(Planck)+H₀, the analysis yields Ω_M = 0.280^+0.013_0.012 and w = -1.166^+0.072_-0.069 including all identified systematics. The value of w is inconsistent with the cosmological constant value of -1 at the 2.3σ level. Tension endures after removing either the baryon acoustic oscillation (BAO) or the H₀ constraint, though it is strongest when including the H₀ constraint. If we include WMAP9 cosmic microwave background (CMB) constraints instead of those from Planck, we find w = -1.124^+0.083_-0.065, which diminishes the discord to <2σ. We cannot conclude whether the tension with flat ΛCDM is a feature of dark energy, new physics, or a combination of chance and systematic errors. The full Pan-STARRS1 SN sample with ∼three times as many SNe should provide more conclusive results.

Rapidly Evolving and Luminous Transients from Pan-STARRS1

In the past decade, several rapidly evolving transients have been discovered whose timescales and luminosities are not easily explained by traditional supernovae (SNe) models. The sample size of these objects has remained small due, at least in part, to the challenges of detecting short timescale transients with traditional survey cadences. Here we present the results from a search within the Pan-STARRS1 Medium Deep Survey (PS1-MDS) for rapidly evolving and luminous transients. We identify 10 new transients with a time above half-maximum (t_1/2) of less than 12 days and -16.5 > M > -20 mag. This increases the number of known events in this region of SN phase space by roughly a factor of three. The median redshift of the PS1-MDS sample is z = 0.275 and they all exploded in star-forming galaxies. In general, the transients possess faster rise than decline timescale and blue colors at maximum light (g_P1-rP1 ≲ -0.2). Best-fit blackbodies reveal photospheric temperatures/radii that expand/cool with time and explosion spectra taken near maximum light are dominated by a blue continuum, consistent with a hot, optically thick, ejecta. We find it difficult to reconcile the short timescale, high peak luminosity (L > 10⁴³erg s^-1), and lack of UV line blanketing observed in many of these transients with an explosion powered mainly by the radioactive decay of ⁵⁶Ni. Rather, we find that many are consistent with either (1) cooling envelope emission from the explosion of a star with a low-mass extended envelope that ejected very little (<0.03 M) radioactive material, or (2) a shock breakout within a dense, optically thick, wind surrounding the progenitor star. After calculating the detection efficiency for objects with rapid timescales in the PS1-MDS we find a volumetric rate of 4800-8000 events yr^-1Gpc^-3(4%-7% of the core-collapse SN rate at z = 0.2).