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We describe the near real-time transient-source discovery engine for the intermediate Palomar Transient Factory (iPTF), currently in operations at the Infrared Processing and Analysis Center (IPAC), Caltech. We coin this system the IPAC/iPTF Discovery Engine (or IDE). We review the algorithms used for PSF-matching, image subtraction, detection, photometry, and machine-learned (ML) vetting of extracted transient candidates. We also review the performance of our ML classifier. For a limiting signal-to-noise ratio of 4 in relatively unconfused regions, bogus candidates from processing artifacts and imperfect image subtractions outnumber real transients by ≃10:1. This can be considerably higher for image data with inaccurate astrometric and/or PSF-matching solutions. Despite this occasionally high contamination rate, the ML classifier is able to identify real transients with an efficiency (or completeness) of ≃97% for a maximum tolerable false-positive rate of 1% when classifying raw candidates. All subtraction-image metrics, source features, ML probability-based real-bogus scores, contextual metadata from other surveys, and possible associations with known Solar System objects are stored in a relational database for retrieval by the various science working groups. We review our efforts in mitigating false-positives and our experience in optimizing the overall system in response to the multitude of science projects underway with iPTF.

We describe the near real-time transient-source discovery engine for the intermediate Palomar Transient Factory (iPTF), currently in operations at the Infrared Processing and Analysis Center (IPAC), Caltech. We coin this system the IPAC/iPTF Discovery Engine (or IDE). We review the algorithms used for PSF-matching, image subtraction, detection, photometry, and machine-learned (ML) vetting of extracted transient candidates. We also review the performance of our ML classifier. For a limiting signal-to-noise ratio of 4 in relatively unconfused regions, bogus candidates from processing artifacts and imperfect image subtractions outnumber real transients by ≃10:1. This can be considerably higher for image data with inaccurate astrometric and/or PSF-matching solutions. Despite this occasionally high contamination rate, the ML classifier is able to identify real transients with an efficiency (or completeness) of ≃97% for a maximum tolerable false-positive rate of 1% when classifying raw candidates. All subtraction-image metrics, source features, ML probability-based real-bogus scores, contextual metadata from other surveys, and possible associations with known Solar System objects are stored in a relational database for retrieval by the various science working groups. We review our efforts in mitigating false-positives and our experience in optimizing the overall system in response to the multitude of science projects underway with iPTF.

Las Cumbres Observatory (LCOGT) operates a global network of robotic 0.4, 1.0, and 2.0-meter telescopes to facilitate scientific research and education in time-domain astronomy. LCOGT's flagship educational program, Global Sky Partners (GSP), awards up to 1500 hours per year of telescope time to individuals and organizations that run their own, fully supported, educational programs. The GSP has a presence in 40 countries and 45% of the Partners target under-served, under-represented, and developing world audiences. The degradation and obsolescence of the original 0.4-meter telescope network prompted LCOGT to update the fleet of 10 telescopes to a new system consisting of predominantly off-the-shelf products. New PlaneWave DeltaRho 350 telescopes with Gemini Focuser/Rotators, LCOGT filter wheels, and QHY600 CMOS cameras, complement the original, custom-built mount. The deployment of all ten telescopes was completed in March 2024. We describe the design and performance of this new system and its components. We comment on modifications made to the QHY600 cameras, as well as on the treatment of random telegraph noise of its CMOS detectors within our data processing system BANZAI. The new telescope network supports the GSP program as well as multiple key science projects, including follow-up observations for the TESS satellite mission.

The results of a new spectroscopic survey of 66 z 4 quasars for Damped Lyman-α absorption systems are presented. The search led to the discovery of 26 new DLA candidates which are analysed in order to compute the comoving mass density of neutral gas in a non-zeroΛ Universe. The possible sources of uncertainty are discussed and the implications of our results for the theories of galaxy formation and evolution are emphasized. A subsequent paper will present details of the calculations summarised here and a more extensive explanation of the consequences of our observations for the understanding of the nature of DLAs.[PUBLICATION ABSTRACT]

We present luminosity functions derived from a spectroscopic survey of AGN selected from Spitzer Space Telescope imaging surveys. Selection in the mid-infrared is significantly less affected by dust obscuration. We can thus compare the luminosity functions of the obscured and unobscured AGN in a more reliable fashion than by using optical or X-ray data alone. We find that the AGN luminosity function can be well described by a broken power-law model in which the break luminosity decreases with redshift. At high redshifts (\\(z>1.6\\)), we find significantly more AGN at a given bolometric luminosity than found by either optical quasar surveys or hard X-ray surveys. The fraction of obscured AGN decreases rapidly with increasing AGN luminosity, but, at least at high redshifts, appears to remain at \\(\\approx 50\\)\\% even at bolometric luminosities \\(\\sim 10^{14}L_{\\odot}\\). The data support a picture in which the obscured and unobscured populations evolve differently, with some evidence that high luminosity obscured quasars peak in space density at a higher redshift than their unobscured counterparts. The amount of accretion energy in the Universe estimated from this work suggests that AGN contribute about 12\\% to the total radiation intensity of the Universe, and a high radiative accretion efficiency \\(\\approx 0.18^{+0.12}_{-0.07}\\) is required to match current estimates of the local mass density in black holes.

We describe the near real-time transient-source discovery engine for the intermediate Palomar Transient Factory (iPTF), currently in operations at the Infrared Processing and Analysis Center (IPAC), Caltech. We coin this system the IPAC/iPTF Discovery Engine (or IDE). We review the algorithms used for PSF-matching, image subtraction, detection, photometry, and machine-learned (ML) vetting of extracted transient candidates. We also review the performance of our ML classifier. For a limiting signal-to-noise ratio of 4 in relatively unconfused regions, \"bogus\" candidates from processing artifacts and imperfect image subtractions outnumber real transients by ~ 10:1. This can be considerably higher for image data with inaccurate astrometric and/or PSF-matching solutions. Despite this occasionally high contamination rate, the ML classifier is able to identify real transients with an efficiency (or completeness) of ~ 97% for a maximum tolerable false-positive rate of 1% when classifying raw candidates. All subtraction-image metrics, source features, ML probability-based real-bogus scores, contextual metadata from other surveys, and possible associations with known Solar System objects are stored in a relational database for retrieval by the various science working groups. We review our efforts in mitigating false-positives and our experience in optimizing the overall system in response to the multitude of science projects underway with iPTF.

We examine the repeatability, reliability, and accuracy of differential exoplanet eclipse depth measurements made using the InfraRed Array Camera (IRAC) on the Spitzer Space Telescope during the post-cryogenic mission. We have re-analyzed an existing 4.5 {\\mu}m data set, consisting of 10 observations of the XO-3b system during secondary eclipse, using seven different techniques for removing correlated noise. We find that, on average, for a given technique, the eclipse depth estimate is repeatable from epoch to epoch to within 156 parts per million (ppm). Most techniques derive eclipse depths that do not vary by more than a factor 3 of the photon noise limit. All methods but one accurately assess their own errors: for these methods, the individual measurement uncertainties are comparable to the scatter in eclipse depths over the 10 epoch sample. To assess the accuracy of the techniques as well as to clarify the difference between instrumental and other sources of measurement error, we have also analyzed a simulated data set of 10 visits to XO-3b, for which the eclipse depth is known. We find that three of the methods (BLISS mapping, Pixel Level Decorrelation, and Independent Component Analysis) obtain results that are within three times the photon limit of the true eclipse depth. When averaged over the 10 epoch ensemble, 5 out of 7 techniques come within 60 ppm of the true value. Spitzer exoplanet data, if obtained following current best practices and reduced using methods such as those described here, can measure repeatable and accurate single eclipse depths, with close to photon-limited results.

We model the optical to far-infrared SEDs of a sample of six type-1 and six type-2 quasars selected in the mid-infrared. The objects in our sample are matched in mid-IR luminosity and selected based on their Spitzer IRAC colors. We obtained new targeted Spitzer IRS and MIPS observations and used archival photometry to examine the optical to far-IR SEDs. We investigate whether the observed differences between samples are consistent with orientation-based unification schemes. The type-1 objects show significant emission at 3 micron. They do not show strong PAH emission and have less far-IR emission on average when compared to the type-2 objects. The SEDs of the type-2 objects show a wide assortment of silicate features, ranging from weak emission to deep silicate absorption. Some also show strong PAH features. In comparison, silicate is only seen in emission in the type-1 objects. This is consistent with some of the type-2s being reddened by a foreground screen of cooler dust, perhaps in the host galaxy itself. We investigate the AGN contribution to the far-IR emission and find it to be significant. We also estimate the star formation rate for each of the objects by integrating the modeled far-IR flux and compare this with the SFR found from PAH emission. We find the type-2 quasars have a higher average SFR than the type-1 quasars based on both methods, though this could be due to differences in bolometric luminosities of the objects. While we find pronounced differences between the two types of objects, none of them are inconsistent with orientation-based unification schemes.

The cosmological evolution of neutral hydrogen is an efficient way of tracing structure formation with redshift. It indicates the rate of evolution of gas into stars and hence the gas consumption and rate star formation history of the Universe. In measuring HI, quasar absorbers have proven to be an ideal tool and we use observations from a recent survey for high-redshift quasar absorption systems together with data gathered from the literature to measure the cosmological comoving mass density of neutral gas. This paper assumes ΩM =0.3, ΩΛ=0.7 and h=0.65.