Refine
Has Fulltext
- no (3)
Document Type
- Article (3)
Language
- English (3)
Is part of the Bibliography
- yes (3)
Keywords
Institute
VERITAS and Fermi-LAT Observations of TeV Gamma-Ray Sources Discovered by HAWC in the 2HWC Catalog
(2018)
The High Altitude Water Cherenkov (HAWC) collaboration recently published their 2HWC catalog, listing 39 very high energy (VHE; >100 GeV) gamma-ray sources based on 507 days of observation. Among these, 19 sources are not associated with previously known teraelectronvolt (TeV) gamma-ray sources. We have studied 14 of these sources without known counterparts with VERITAS and Fermi-LAT. VERITAS detected weak gamma-ray emission in the 1 TeV-30 TeV band in the region of DA 495, a pulsar wind nebula coinciding with 2HWC J1953+294, confirming the discovery of the source by HAWC. We did not find any counterpart for the selected 14 new HAWC sources from our analysis of Fermi-LAT data for energies higher than 10 GeV. During the search, we detected gigaelectronvolt (GeV) gamma-ray emission coincident with a known TeV pulsar wind nebula, SNR G54.1+0.3 (VER J1930+188), and a 2HWC source, 2HWC J1930+188. The fluxes for isolated, steady sources in the 2HWC catalog are generally in good agreement with those measured by imaging atmospheric Cherenkov telescopes. However, the VERITAS fluxes for SNR G54.1+0.3, DA 495, and TeV J2032+4130 are lower than those measured by HAWC, and several new HAWC sources are not detected by VERITAS. This is likely due to a change in spectral shape, source extension, or the influence of diffuse emission in the source region.
We present deep VERITAS observations of the blazar PKS 1424+240, along with contemporaneous Fermi Large Area Telescope, Swift X-ray Telescope, and Swift UV Optical Telescope data between 2009 February 19 and 2013 June 8. This blazar resides at a redshift of z >= 0.6035, displaying a significantly attenuated gamma-ray flux above 100 GeV due to photon absorption via pair-production with the extragalactic background light. We present more than 100 hr of VERITAS observations over three years, a multiwavelength light curve, and the contemporaneous spectral energy distributions. The source shows a higher flux of (2.1 +/- 0.3) x 10(-7) photons m(-2) s(-1) above 120 GeV in 2009 and 2011 as compared to the flux measured in 2013, corresponding to (1.02 +/- 0.08) x 10-7 photons m(-2) s(-1) above 120 GeV. The measured differential very high energy (VHE; E >= 100 GeV) spectral indices are Gamma = 3.8 +/- 0.3, 4.3 +/- 0.6 and 4.5 +/- 0.2 in 2009, 2011, and 2013, respectively. No significant spectral change across the observation epochs is detected. We find no evidence for variability at gamma-ray opacities of greater than tau = 2, where it is postulated that any variability would be small and occur on timescales longer than a year if hadronic cosmic-ray interactions with extragalactic photon fields provide a secondary VHE photon flux. The data cannot rule out such variability due to low statistics.
In a recent BAMS article, it is argued that community-based Open Source Software (OSS) could foster scientific progress in weather radar research, and make weather radar software more affordable, flexible, transparent, sustainable, and interoperable.Nevertheless, it can be challenging for potential developers and users to realize these benefits: tools are often cumbersome to install; different operating systems may have particular issues, or may not be supported at all; and many tools have steep learning curves.To overcome some of these barriers, we present an open, community-based virtual machine (VM). This VM can be run on any operating system, and guarantees reproducibility of results across platforms. It contains a suite of independent OSS weather radar tools (BALTRAD, Py-ART, wradlib, RSL, and Radx), and a scientific Python stack. Furthermore, it features a suite of recipes that work out of the box and provide guidance on how to use the different OSS tools alone and together. The code to build the VM from source is hosted on GitHub, which allows the VM to grow with its community.We argue that the VM presents another step toward Open (Weather Radar) Science. It can be used as a quick way to get started, for teaching, or for benchmarking and combining different tools. It can foster the idea of reproducible research in scientific publishing. Being scalable and extendable, it might even allow for real-time data processing.We expect the VM to catalyze progress toward interoperability, and to lower the barrier for new users and developers, thus extending the weather radar community and user base.