Long-term degradation of optical devices on the moon

Forty years ago, Apollo astronauts placed the first of several retroreflector arrays on the lunar surface. Their continued usefulness for laser-ranging might suggest that the lunar environment does not damage optical devices. However, new laser ranging data reveal that the efficiency of the three Apollo reflector arrays is now diminished by a factor of ten at all lunar phases and by an additional factor of ten when the lunar phase is near full moon. These deficits did not exist in the earliest years of lunar ranging, indicating that the lunar environment damages optical equipment on the timescale of decades. Dust or abrasion on the front faces of the corner-cube prisms may be responsible, reducing their reflectivity and degrading their thermal performance when exposed to face-on sunlight at full moon. These mechanisms can be tested using laboratory simulations and must be understood before designing equipment destined for the moon.Comment: 9 pages; 4 figures; accepted for publication in Icaru

Displaying the Heterogeneity of the SN 2002cx-like Subclass of Type Ia Supernovae with Observations of the Pan-STARRS-1 Discovered SN2009ku

SN2009ku, discovered by Pan-STARRS-1, is a Type Ia supernova (SNIa), and a member of the distinct SN2002cx-like class of SNeIa. Its light curves are similar to the prototypical SN2002cx, but are slightly broader and have a later rise to maximum in g. SN2009ku is brighter (~0.6 mag) than other SN2002cx-like objects, peaking at M_V = -18.4 mag - which is still significantly fainter than typical SNeIa. SN2009ku, which had an ejecta velocity of ~2000 kms^-1 at 18 days after maximum brightness is spectroscopically most similar to SN2008ha, which also had extremely low-velocity ejecta. However, SN2008ha had an exceedingly low luminosity, peaking at M_V = -14.2 mag, ~4 mag fainter than SN2009ku. The contrast of high luminosity and low ejecta velocity for SN2009ku is contrary to an emerging trend seen for the SN2002cx class. SN2009ku is a counter-example of a previously held belief that the class was more homogeneous than typical SNeIa, indicating that the class has a diverse progenitor population and/or complicated explosion physics. As the first example of a member of this class of objects from the new generation of transient surveys, SN2009ku is an indication of the potential for these surveys to find rare and interesting objects.Comment: 7 pages, 3 figure

Breaking up prolonged sitting time with walking does not affect appetite or gut hormone concentrations but does induce an energy deficit and suppresses postprandial glycaemia in sedentary adults

Breaking up periods of prolonged sitting can negate harmful metabolic effects but the influence on appetite and gut hormones is not understood and is investigated in this study. Thirteen sedentary (7 female) participants undertook three 5-h trials in random order: (i) uninterrupted sitting (SIT), (ii) seated with 2-min bouts of light-intensity walking every 20 min (SIT + LA), and (iii) seated with 2-min bouts of moderate-intensity walking every 20 min (SIT + MA). A standardised test drink was provided at the start of each trial and an ad libitum pasta test meal provided at the end of each trial. Subjective appetite ratings and plasma acylated ghrelin, peptide YY, insulin, and glucose were measured at regular intervals. Area under the curve (AUC) was calculated for each variable. AUC values for appetite and gut hormone concentrations were unaffected in the activity breaks conditions compared with uninterrupted sitting (linear mixed modelling: p > 0.05). Glucose AUC was lower in SIT + MA than in SIT + LA (p = 0.004) and SIT (p = 0.055). There was no difference in absolute ad libitum energy intake between conditions (p > 0.05); however, relative energy intake was lower in SIT + LA (39%; p = 0.011) and SIT + MA (120%; p < 0.001) than in SIT. In conclusion, breaking up prolonged sitting does not alter appetite and gut hormone responses to a meal over a 5-h period. Increased energy expenditure from activity breaks could promote an energy deficit that is not compensated for in a subsequent meal

Pan-STARRS Pixel Analysis: Source Detection and Characterization

Over 3 billion astronomical sources have been detected in the more than 22 million orthogonal transfer CCD images obtained as part of the Pan-STARRS1 3π survey. Over 85 billion instances of those sources have been automatically detected and characterized by the Pan-STARRS Image Processing Pipeline photometry software, psphot. This fast, automatic, and reliable software was developed for the Pan-STARRS project but is easily adaptable to images from other telescopes. We describe the analysis of the astronomical sources by psphot in general as well as for the specific case of the third processing version used for the first two public releases of the Pan-STARRS 3π Survey data

Selection of Burst-like Transients and Stochastic Variables Using Multi-band 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 g P1, r P1, i P1, and z P1. 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 survey

A Map of Dust Reddening to 4.5 kpc from Pan-STARRS1

We present a map of the dust reddening to 4.5 kpc derived from Pan-STARRS1 stellar photometry. The map covers almost the entire sky north of declination –30° at a resolution of 7'-14', and is based on the estimated distances and reddenings to more than 500 million stars. The technique is designed to map dust in the Galactic plane, where many other techniques are stymied by the presence of multiple dust clouds at different distances along each line of sight. This reddening-based dust map agrees closely with the Schlegel et al. (SFD) far-infrared emission-based dust map away from the Galactic plane, and the most prominent differences between the two maps stem from known limitations of SFD in the plane. We also compare the map with Planck, finding likewise good agreement in general at high latitudes. The use of optical data from Pan-STARRS1 yields reddening uncertainty as low as 25 mmag E(B – V)

Correlations Between Charge Ordering and Local Magnetic Fields in Overdoped YBa2_2Cu3_3O6+x_{6+x}

Zero-field muon spin relaxation (ZF-$\mu$SR) measurements were undertaken on under- and overdoped samples of superconducting YBa$_2$Cu$_3$O$_{6+x}$ to determine the origin of the weak static magnetism recently reported in this system. The temperature dependence of the muon spin relaxation rate in overdoped crystals displays an unusual behavior in the superconducting state. A comparison to the results of NQR and lattice structure experiments on highly doped samples provides compelling evidence for strong coupling of charge, spin and structural inhomogeneities.Comment: 4 pages, 4 figures, new data, new figures and modified tex

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 (griz yP1) 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+3−2×10−5 and 8+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