| 1. |
- Huerta, E. A., et al.
(författare)
-
Enabling real-time multi-messenger astrophysics discoveries with deep learning
- 2019
-
Ingår i: Nature reviews physics. - : Springer Science and Business Media LLC. - 2522-5820. ; 1:10, s. 600-608
-
Forskningsöversikt (refereegranskat)abstract
- Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that probe the Universe using different cosmic messengers: electromagnetic waves, cosmic rays, gravitational waves and neutrinos. In this Expert Recommendation, we review the key challenges of real-time observations of gravitational wave sources and their electromagnetic and astroparticle counterparts, and make a number of recommendations to maximize their potential for scientific discovery. These recommendations refer to the design of scalable and computationally efficient machine learning algorithms; the cyber-infrastructure to numerically simulate astrophysical sources, and to process and interpret multi-messenger astrophysics data; the management of gravitational wave detections to trigger real-time alerts for electromagnetic and astroparticle follow-ups; a vision to harness future developments of machine learning and cyber-infrastructure resources to cope with the big-data requirements; and the need to build a community of experts to realize the goals of multi-messenger astrophysics. A group of experts suggests ways in which deep learning can be used to enhance the potential for discovery in multi-messenger astrophysics.
|
|
| 2. |
- Bianco, Federica B., et al.
(författare)
-
Presto-Color : A Photometric Survey Cadence for Explosive Physics and Fast Transients
- 2019
-
Ingår i: Publications of the Astronomical Society of the Pacific. - : IOP Publishing. - 0004-6280 .- 1538-3873. ; 131:1000
-
Tidskriftsartikel (refereegranskat)abstract
- We identify minimal observing cadence requirements that enable photometric astronomical surveys to detect and recognize fast and explosive transients and fast transient features. Observations in two different filters within a short time window (e.g., g-and-i, or r-and-z, within <0.5 hr) and a repeat of one of those filters with a longer time window (e.g., >1.5 hr) are desirable for this purpose. Such an observing strategy delivers both the color and light curve evolution of transients on the same night. This allows the identification and initial characterization of fast transient-or fast features of longer timescale transients-such as rapidly declining supernovae, kilonovae, and the signatures of SN ejecta interacting with binary companion stars or circumstellar material. Some of these extragalactic transients are intrinsically rare and generally all hard to find, thus upcoming surveys like the Large Synoptic Survey Telescope (LSST) could dramatically improve our understanding of their origin and properties. We colloquially refer to such a strategy implementation for the LSST as the Presto-Color strategy (rapid-color). This cadence's minimal requirements allow for overall optimization of a survey for other science goals.
|
|
| 3. |
- Ginsburg, Adam, et al.
(författare)
-
astroquery: An Astronomical Web-querying Package in Python
- 2019
-
Ingår i: Astronomical Journal. - : American Astronomical Society. - 1538-3881 .- 0004-6256. ; 157:3
-
Tidskriftsartikel (refereegranskat)abstract
- Astroquery is a collection of tools for requesting data from databases hosted on remote servers with interfaces exposed on the Internet, including those with web pages but without formal application program interfaces. These tools are built on the Python requests package, which is used to make HTTP requests, and astropy, which provides most of the data parsing functionality. astroquery modules generally attempt to replicate the web page interface provided by a given service as closely as possible, making the transition from browser-based to command-line interaction easy. astroquery has received significant contributions from throughout the astronomical community, including several from telescope archives. astroquery enables the creation of fully reproducible workflows from data acquisition through publication. This paper describes the philosophy, basic structure, and development model of the astroquery package. The complete documentation for astroquery can be found at http://astroquery.readthedocs.io/.
|
|
