We report on the current status in the development of a pilot automated data acquisition and reduction pipeline based around the operation of two nodes of remotely operated robotic telescopes based in California, USA and Cork, Ireland. The observatories are primarily used as a testbed for automation and instrumentation and as a tool to facilitate STEM (Science Technology Engineering Mathematics) promotion. The Ireland node is situated at Blackrock Castle Observatory (operated by Cork Institute of Technology) and consists of two optical telescopes – 6” and 16” OTAs housed in two separate domes while the node in California is its 6” replica. Together they form a pilot Telescope ARrAy known as TARA. QuickPhot is an automated data reduction pipeline designed primarily to throw more light on the microvariability of blazars employing precision optical photometry and using data from the TARA telescopes as they constantly monitor predefined targets whenever observing conditions are favourable. After carrying out aperture photometry, if any variability above a given threshold is observed, the reporting telescope will communicate the source concerned and the other nodes will follow up with multi-band observations, taking advantage that they are located in strategically separated time-zones. Ultimately we wish to investigate the applicability of Shock-in-Jet and Geometric models. These try to explain the processes at work in AGNs which result in the formation of jets, by looking for temporal and spectral variability in TARA multi-band observations. We are also experimenting with using a Twochannel Optical PHotometric Imaging CAMera (TOΦCAM) that we have developed and which has been optimised for simultaneous two-band photometry on our 16” OTA.
The scientific community is in the midst of a data analysis crisis. The increasing capacity of scientific CCD
instrumentation and their falling costs is contributing to an explosive generation of raw photometric data. This data must
go through a process of cleaning and reduction before it can be used for high precision photometric analysis. Many
existing data processing pipelines either assume a relatively small dataset or are batch processed by a High Performance
Computing centre. A radical overhaul of these processing pipelines is required to allow reduction and cleaning rates to
process terabyte sized datasets at near capture rates using an elastic processing architecture. The ability to access
computing resources and to allow them to grow and shrink as demand fluctuates is essential, as is exploiting the parallel
nature of the datasets. A distributed data processing pipeline is required. It should incorporate lossless data compression,
allow for data segmentation and support processing of data segments in parallel. Academic institutes can collaborate and
provide an elastic computing model without the requirement for large centralized high performance computing data
centers. This paper demonstrates how a base 10 order of magnitude improvement in overall processing time has been
achieved using the "ACN pipeline", a distributed pipeline spanning multiple academic institutes.
Electron Multiplying Charge Coupled Devices (EMCCDs) are CCD cameras with potentially single-photon detection ability. Signal amplification is achieved by way of a unique electron-multiplying structure built into the silicon, and the gain can be varied in order to overcome the read-noise floor, which is the usual limiting factor in reading out a conventional CCD at high frame rates. In combination with its high quantum efficiencies, the EMCCD holds great promise for time-resolved photometry. We report here results from two observing campaigns aimed at assessing the suitability of EMCCD technology for detecting short-timescale, low-amplitude variability in blazars. Data were taken on the 2.2m telescope at Calar Alto using both front-illuminated and back-illuminated EMCCD cameras from Andor Technology’s <i>iXon</i> range. Approximately 410,000 science frames were recorded over 10 nights. The results presented here illustrate the photometric stability achieved with the cameras, under typical observing conditions. In general, photometric precision down to the level of a few millimagnitudes is found to be possible. We argue that reliable photometry is best achieved with high data collection rates (typically 4 frames per second) coupled to ultra-low-noise detectors such as the EMCCD.
Developments in imaging technology over the past decade have provided impetus toward the realization of automated data reduction systems within the astronomical community. These developments, in particular advances in CCD technology, have meant that the data envelope associated with even modest observing programmes can reach gigabyte volumes. We describe the development of an automated data reduction system for differential photometry called PhotMate. For issues of reuse and interoperability the system was developed entirely within the IRAF environment and now forms the backbone of our data analysis procedure. We discuss the methodologies behind its implementation and the use of IRAF scripts for the realization of an automated process. Finally, we place the effectiveness of such a system in context by reference to two recent observing runs at the Calar Alto observatory where we tested a new low light level (L3) CCD. It is our belief that this observing campaign is an important indicator of future trends in observational optical astronomy. As the cost of such devices decreases, their usage will increase and with it the volume of data collectively generated, toppling large astronomical projects as the primary data generators.
Potential multi-path spectroscopic differential absorption systems for the measurement of trace gases in the atmosphere are presented. Recommendations are made for system designs to be used for tomographic differential optical absorption spectroscopy (DOAS) measurements. The difficulties in producing multiple simultaneous beams from a single artificial light source are discussed, while the need for further tomographic resolution information is highlighted. An innovative prototype scanning-DOAS system is presented. The system is designed to generate multiple sequential paths, without the need for bulky and expensive mechanical systems. The scanning DOAS system can easily be placed in an industrial production plant or in a street canyon for multiple direction monitoring. The scanning DOAS system is currently being tested at the Cork Institute of Technology (CIT).
We present the results of preliminary research investigating the generation of two-dimensional pollutant gas concentration maps of street canyons. This research uses computed tomography (CT) to reconstruct the spatial distribution of gas concentrations from path-integral data obtained using differential optical absorption spectroscopy (DOAS). This work represents a novel application
of these two techniques and is aimed at the validation of theoretical gas distribution models in selected urban settings. The derived results are based on model data and investigate the
viability of constrained geometry sensing networks and the accuracy of current computed tomography algorithms. We also present results on the use of an evolutionary algorithm applied to pollutant reconstruction in an open area as part of initial investigations
into its applicability to street canyon pollutant reconstruction. Future work will include the reconstruction of gas distributions in a real urban setting with the long-term goal of a system that is capable of performing this task in near real-time allowing the visualisation of short to medium time scale spatial dynamics.