Characterization of dimensional changes of cement pastes and mortars in fresh state applying an interferometric technique

The effect produced by the incorporation of additives in Portland cement based materials over dimensional changes occurring during the setting process was evaluated employing a fiber optic Fizeau interferometric sensor. The sensor system employed a broadband light source (SLED) centered at 1550 nm, whose spectral emission was modulated by the interferometer formed between the material surface and the end of the optical fiber used to illuminate the sample. An optical spectrum analyzer was used to monitor the variation of the modulated spectrum, while the mentioned process took place. The expansion or contraction experienced by materials with different compositions was observed and quantified. Results obtained point out the accuracy and the potential of the technique.Fil: Mesa Yandy, Angelica Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Investigaciones Opticas (i); Argentina. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Duchowicz, Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Investigaciones Opticas (i); Argentina. Universidad Austral. Facultad de Ingeniería; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Russo, Nelida Araceli. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigaciones Opticas (i); Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Zerbino, Raul Luis. Universidad Nacional de La Plata. Facultad de Ingenieria; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentin

Small Near-Earth Asteroids in the Palomar Transient Factory Survey: a Real-Time Streak-detection System

Near-Earth asteroids (NEAs) in the 1–100 meter size range are estimated to be ~1,000 times more numerous than the ~15,000 currently cataloged NEAs, most of which are in the 0.5–10 kilometer size range. Impacts from 10–100 meter size NEAs are not statistically life-threatening, but may cause significant regional damage, while 1–10 meter size NEAs with low velocities relative to Earth are compelling targets for space missions. We describe the implementation and initial results of a real-time NEA-discovery system specialized for the detection of small, high angular rate (visually streaked) NEAs in Palomar Transient Factory (PTF) images. PTF is a 1.2-m aperture, 7.3 deg^2 field of view (FOV) optical survey designed primarily for the discovery of extragalactic transients (e.g., supernovae) in 60-second exposures reaching ~20.5 visual magnitude. Our real-time NEA discovery pipeline uses a machine-learned classifier to filter a large number of false-positive streak detections, permitting a human scanner to efficiently and remotely identify real asteroid streaks during the night. Upon recognition of a streaked NEA detection (typically within an hour of the discovery exposure), the scanner triggers follow-up with the same telescope and posts the observations to the Minor Planet Center for worldwide confirmation. We describe our 11 initial confirmed discoveries, all small NEAs that passed 0.3–15 lunar distances from Earth. Lastly, we derive useful scaling laws for comparing streaked-NEA-detection capabilities of different surveys as a function of their hardware and survey-pattern characteristics. This work most directly informs estimates of the streak-detection capabilities of the Zwicky Transient Facility (ZTF, planned to succeed PTF in 2017), which will apply PTF's current resolution and sensitivity over a 47-deg^2 FOV

The IPAC Image Subtraction and Discovery Pipeline for the intermediate Palomar Transient Factory

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.Comment: 66 pages, 21 figures, 7 tables, accepted by PAS

Progenitor, Precursor and Evolution of the Dusty Remnant of the Stellar Merger M31-LRN-2015

M31-2015-LRN is a likely stellar merger discovered in the Andromeda Galaxy in 2015. We present new optical to mid-infrared photometry and optical spectroscopy for this event. Archival data shows that the source started to brighten $\sim$2 years before the nova event. During this precursor phase, the source brightened by $\sim$3 mag. The lightcurve at 6 and 1.5 months before the main outburst may show periodicity, with periods of 16$\pm$0.3 and 28.1$\pm$1.4 days respectively. This complex emission may be explained by runaway mass loss from the system after the binary undergoes Roche-lobe overflow, leading the system to coalesce in tens of orbital periods. While the progenitor spectral energy distribution shows no evidence of pre-existing warm dust in system, the remnant forms an optically thick dust shell at $\sim$4 months after the outburst peak. The optical depth of the shell increases dramatically after 1.5 years, suggesting the existence of shocks that enhance the dust formation process. We propose that the merger remnant is likely an inflated giant obscured by a cooling shell of gas with mass $\sim0.2$ M$_{\odot}$ ejected at the onset of the common envelope phase.Comment: 16 pages, 10 figures. Accepted for publication in MNRA

Real-bogus classification for the Zwicky Transient Facility using deep learning

Efficient automated detection of flux-transient, re-occurring flux-variable, and moving objects is increasingly important for large-scale astronomical surveys. We present BRAAI, a convolutional-neural-network, deep-learning real/bogus classifier designed to separate genuine astrophysical events and objects from false positive, or bogus, detections in the data of the Zwicky Transient Facility (ZTF), a new robotic time-domain survey currently in operation at the Palomar Observatory in California, USA. BRAAI demonstrates a state-of-the-art performance as quantified by its low false negative and false positive rates. We describe the open-source software tools used internally at Caltech to archive and access ZTF’s alerts and light curves (KOWALSKI ), and to label the data (ZWICKYVERSE). We also report the initial results of the classifier deployment on the Edge Tensor Processing Units that show comparable performance in terms of accuracy, but in a much more (cost-) efficient manner, which has significant implications for current and future surveys

Processing Images from the Zwicky Transient Facility

The Zwicky Transient Facility is a new robotic-observing program, in which a newly engineered 600-MP digital camera with a pioneeringly large field of view, 47~square degrees, will be installed into the 48-inch Samuel Oschin Telescope at the Palomar Observatory. The camera will generate $\sim 1$~petabyte of raw image data over three years of operations. In parallel related work, new hardware and software systems are being developed to process these data in real time and build a long-term archive for the processed products. The first public release of archived products is planned for early 2019, which will include processed images and astronomical-source catalogs of the northern sky in the $g$ and $r$ bands. Source catalogs based on two different methods will be generated for the archive: aperture photometry and point-spread-function fitting.Comment: 6 pages, 4 figures, submitted to RTSRE Proceedings (www.rtsre.org