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Register a new userHAWC: Design, Operation, Reconstruction and Analysis
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Andrew J. Smith
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The High-Altitude Water Cherenkov (HAWC) Observatory was completed and began full opera- tion on March 20, 2015. The detector consists of an array of 300 water tanks, each containing 200 ktons of purified water and instrumented with 4 PMTs. Located at an elevation of 4100m a.s.l. near the Sierra Negra volcano in central Mexico, HAWC has a threshold for gamma-ray detection well below 1 TeV and a sensitivity to TeV-scale gamma-ray sources an order of magnitude better than previous air-shower arrays. The detector operates 24 hours/day and observes the overhead sky (2 sr), making it an ideal survey instrument. We describe the configuration of HAWC with an emphasis on how the design was optimized, describe the data acquired, reconstructed and an- alyzed. Finally, we will demonstrate the sensitivity of the detector using the observation of the Crab. This paper serves as a detailed technical description of the foundations of the numerous analyses presented at this meeting by members of the HAWC collaboration.
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The High-Altitude Water Cherenkov Gamma Ray Observatory (HAWC) is under construction 4100 meters above sea level at Sierra Negra, Mexico. We describe the design and cabling of the detector, the characterization of the photomultipliers, and the timing calibration system. We also outline a next-generation detector based on the water Cherenkov technique.
The Asteroid Terrestrial impact Last Alert System (ATLAS) system consists of two 0.5m Schmidt telescopes with cameras covering 29 square degrees at plate scale of 1.86 arcsec per pixel. Working in tandem, the telescopes routinely survey the whole sky visible from Hawaii (above $delta > -50^{circ}$) every two nights, exposing four times per night, typically reaching $o < 19$ magnitude per exposure when the moon is illuminated and $c < 19.5$ per exposure in dark skies. Construction is underway of two further units to be sited in Chile and South Africa which will result in an all-sky daily cadence from 2021. Initially designed for detecting potentially hazardous near earth objects, the ATLAS data enable a range of astrophysical time domain science. To extract transients from the data stream requires a computing system to process the data, assimilate detections in time and space and associate them with known astrophysical sources. Here we describe the hardware and software infrastructure to produce a stream of clean, real, astrophysical transients in real time. This involves machine learning and boosted decision tree algorithms to identify extragalactic and Galactic transients. Typically we detect 10-15 supernova candidates per night which we immediately announce publicly. The ATLAS discoveries not only enable rapid follow-up of interesting sources but will provide complete statistical samples within the local volume of 100 Mpc. A simple comparison of the detected supernova rate within 100 Mpc, with no corrections for completeness, is already significantly higher (factor 1.5 to 2) than the current accepted rates.
The High Altitude Water Cherenkov (HAWC) Observatory continuously observes gamma-rays between 100 GeV to 100 TeV in an instantaneous field of view of about 2 steradians above the array. The large amount of raw data, the importance of small number statistics, the large dynamic range of gamma-ray signals in time (1 - $10^8$ sec) and angular extent (0.1 - 100 degrees), and the growing need to directly compare results from different observatories pose some special challenges for the analysis of HAWC data. To address these needs, we have designed and implemented a modular analysis framework based on the method of maximum likelihood. The framework facilitates the calculation of a binned Poisson Log-likelihood value for a given physics model (i.e., source model), data set, and detector response. The parameters of the physics model (sky position, spectrum, angular extent, etc.) can be optimized through a likelihood maximization routine to obtain a best match to the data. In a similar way, the parameters of the detector response (absolute pointing, angular resolution, etc.) can be optimized using a well-known source such as the Crab Nebula. The framework was designed concurrently with the Multi-Mission Maximum Likelihood (3ML) architecture, and allows for the definition of a general collection of sources with individually varying spectral and spatial morphologies. Compatibility with the 3ML architecture allows to easily perform powerful joint fits with other observatories. In this contribution, we overview the design and capabilities of the HAWC analysis framework, stressing the overarching design points that have applicability to other astronomical and cosmic-ray observatories.
PAON4 is an L-band (1250-1500 MHz) small interferometer operating in transit mode deployed at the Nanc{c}ay observatory in France, designed as a prototype instrument for Intensity Mapping. It features four 5~meter diameter dishes in a compact triangular configuration, with a total geometric collecting area of $sim75 mathrm{m^2}$, and equipped with dual polarization receivers. A total of 36 visibilities are computed from the 8 independent RF signals by the software correlator over the full 250~MHz RF band. The array operates in transit mode, with the dishes pointed toward a fixed declination, while the sky drifts across the instrument. Sky maps for each frequency channel are then reconstructed by combining the time-dependent visibilities from the different baselines observed at different declinations. This paper presents an overview of the PAON4 instrument design and goals, as a prototype for dish arrays to map the Large Scale Structure in radio, using intensity mapping of the atomic hydrogen $21~mathrm{cm}$ line. We operated PAON4 over several years and use data from observations in different periods to assess the array performance. We present preliminary analysis of a large fraction of this data and discuss crucial issues for this type of instrument, such as the calibration strategy, instrument response stability, and noise behaviour.
In this paper we present the SOXS Scheduler, a web-based application aimed at optimising remote observations at the NTT-ESO in the context of scientific topics of both the SOXS Consortium and regular ESO proposals.This paper will give details of how detected transients from various surveys are inserted, prioritised, and selected for observations with SOXS at the NTT while keeping the correct sharing between GTO time (for the SOXSConsortium) and the regularly approved observing time from ESO proposals. For the 5-years of operation ofSOXS this vital piece of software will provide a night-by-night dynamical schedule, allowing the user to face rapid changes during the operations that might come from varying weather conditions or frequent target of opportunity (ToO) observations that require a rapid response. The scheduler is developed with high available and scalable architecture in mind and it implements the state-of-the-art technologies for API Restful application like Docker Containers, API Gateway, and Python-based Flask frameworks.
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