VERITAS discovery of very high energy gamma-ray emission from S3 1227+25 and multiwavelength observations

We report the detection of very high energy gamma-ray emission from the blazar S3 1227+25 (VER J1230+253) with the Very Energetic Radiation Imaging Telescope Array System (VERITAS). VERITAS observations of the source were triggered by the detection of a hard-spectrum GeV flare on May 15, 2015 with the Fermi-Large Area Telescope (LAT). A combined five-hour VERITAS exposure on May 16th and May 18th resulted in a strong 13$\sigma$ detection with a differential photon spectral index, $\Gamma$ = 3.8 $\pm$ 0.4, and a flux level at 9% of the Crab Nebula above 120 GeV. This also triggered target of opportunity observations with Swift, optical photometry, polarimetry and radio measurements, also presented in this work, in addition to the VERITAS and Fermi-LAT data. A temporal analysis of the gamma-ray flux during this period finds evidence of a shortest variability timescale of $\tau_{obs}$ = 6.2 $\pm$ 0.9 hours, indicating emission from compact regions within the jet, and the combined gamma-ray spectrum shows no strong evidence of a spectral cut-off. An investigation into correlations between the multiwavelength observations found evidence of optical and gamma-ray correlations, suggesting a single-zone model of emission. Finally, the multiwavelength spectral energy distribution is well described by a simple one-zone leptonic synchrotron self-Compton radiation model.Comment: 18 pages, 6 figures. Accepted for publication in the Astrophysical Journal (ApJ

New developments for a multidimensional maximum likelihood approach to analyzing VERITAS data

Gamma-ray observations from a few hundred MeV up to tens of TeV are a valuable tool for studying particle acceleration and diffusion within our galaxy. Constructing a coherent physical picture of particle accelerators such as supernova remnants, pulsar wind nebulae, and star-forming regions requires the ability to detect extended regions of gamma-ray emission, the ability to analyze small-scale spatial variation within these regions, and the ability to synthesize data from multi- ple observatories across multiple wavebands. Imaging atmospheric Cherenkov telescopes (IACTs) provide fine angular resolution (< 0.1 degree) for gamma rays above 100 GeV. However, their lim- ited fields of view typically make detection of extended sources challenging. Maximum likelihood methods are well-suited to simultaneous analysis of multiple fields with overlapping sources and combining data from multiple gamma-ray observatories. Such methods also offer an alternative ap- proach to estimating the IACT cosmic ray background and consequently an enhanced sensitivity to sources as large as the telescope field of view. I report here on the current status and performance of a maximum likelihood technique for the IACT, VERITAS. This likelihood method employs source models and a background model, fitted to VERITAS data. A gamma/hadron discrimination parameter, mean scaled width, is included in the likelihood making the method four-dimensional. A series of validation studies and crosschecks settled on a preferred function for the point spread function and criteria for controlling systematic and statistical errors in background models. A fully developed 4D-maximum likelihood method was performed on multiple test sources, using the open analysis framework Gammapy. The 4D-MLM results are comparable with those from classical analyses. The discrepancies are greatest at low energies, and further discussion outlines probable causes and future solutions. The 4D-MLM was applied to VERITAS observations on a moderately extended gamma-ray source (r ∼ 0.6◦), Gamma-Cygni. The observed morphology from the 4D-MLM analysis is consistent with previous IACT studies

New developments for a multidimensional maximum likelihood approach to analyzing VERITAS data

Gamma-ray observations from a few hundred MeV up to tens of TeV are a valuable tool for studying particle acceleration and diffusion within our galaxy. Constructing a coherent physical picture of particle accelerators such as supernova remnants, pulsar wind nebulae, and star-forming regions requires the ability to detect extended regions of gamma-ray emission, the ability to analyze small-scale spatial variation within these regions, and the ability to synthesize data from multi- ple observatories across multiple wavebands. Imaging atmospheric Cherenkov telescopes (IACTs) provide fine angular resolution (< 0.1 degree) for gamma rays above 100 GeV. However, their lim- ited fields of view typically make detection of extended sources challenging. Maximum likelihood methods are well-suited to simultaneous analysis of multiple fields with overlapping sources and combining data from multiple gamma-ray observatories. Such methods also offer an alternative ap- proach to estimating the IACT cosmic ray background and consequently an enhanced sensitivity to sources as large as the telescope field of view. I report here on the current status and performance of a maximum likelihood technique for the IACT, VERITAS. This likelihood method employs source models and a background model, fitted to VERITAS data. A gamma/hadron discrimination parameter, mean scaled width, is included in the likelihood making the method four-dimensional. A series of validation studies and crosschecks settled on a preferred function for the point spread function and criteria for controlling systematic and statistical errors in background models. A fully developed 4D-maximum likelihood method was performed on multiple test sources, using the open analysis framework Gammapy. The 4D-MLM results are comparable with those from classical analyses. The discrepancies are greatest at low energies, and further discussion outlines probable causes and future solutions. The 4D-MLM was applied to VERITAS observations on a moderately extended gamma-ray source (r ∼ 0.6◦), Gamma-Cygni. The observed morphology from the 4D-MLM analysis is consistent with previous IACT studies

New developments for a multidimensional maximum likelihood approach to analyzing VERITAS data

Gamma-ray observations from a few hundred MeV up to tens of TeV are a valuable tool for studying particle acceleration and diffusion within our galaxy. Constructing a coherent physical picture of particle accelerators such as supernova remnants, pulsar wind nebulae, and star-forming regions requires the ability to detect extended regions of gamma-ray emission, the ability to analyze small-scale spatial variation within these regions, and the ability to synthesize data from multi- ple observatories across multiple wavebands. Imaging atmospheric Cherenkov telescopes (IACTs) provide fine angular resolution (< 0.1 degree) for gamma rays above 100 GeV. However, their lim- ited fields of view typically make detection of extended sources challenging. Maximum likelihood methods are well-suited to simultaneous analysis of multiple fields with overlapping sources and combining data from multiple gamma-ray observatories. Such methods also offer an alternative ap- proach to estimating the IACT cosmic ray background and consequently an enhanced sensitivity to sources as large as the telescope field of view. I report here on the current status and performance of a maximum likelihood technique for the IACT, VERITAS. This likelihood method employs source models and a background model, fitted to VERITAS data. A gamma/hadron discrimination parameter, mean scaled width, is included in the likelihood making the method four-dimensional. A series of validation studies and crosschecks settled on a preferred function for the point spread function and criteria for controlling systematic and statistical errors in background models. A fully developed 4D-maximum likelihood method was performed on multiple test sources, using the open analysis framework Gammapy. The 4D-MLM results are comparable with those from classical analyses. The discrepancies are greatest at low energies, and further discussion outlines probable causes and future solutions. The 4D-MLM was applied to VERITAS observations on a moderately extended gamma-ray source (r ∼ 0.6◦), Gamma-Cygni. The observed morphology from the 4D-MLM analysis is consistent with previous IACT studies

Gammapy V1.0

Gammapy is an open-source Python package for gamma-ray astronomy built on Numpy, Scipy and Astropy. It is used as core library for the Science Analysis tools of the Cherenkov Telescope Array (CTA), recommended by the H.E.S.S. collaboration to be used for Science publications, and is already widely used in the analysis of existing gamma-ray instruments, such as MAGIC, VERITAS and HAWC

Gammapy V1.0

Gammapy is an open-source Python package for gamma-ray astronomy built on Numpy, Scipy and Astropy. It is used as core library for the Science Analysis tools of the Cherenkov Telescope Array (CTA), recommended by the H.E.S.S. collaboration to be used for Science publications, and is already widely used in the analysis of existing gamma-ray instruments, such as MAGIC, VERITAS and HAWC

Gammapy V1.0

Gammapy is an open-source Python package for gamma-ray astronomy built on Numpy, Scipy and Astropy. It is used as core library for the Science Analysis tools of the Cherenkov Telescope Array (CTA), recommended by the H.E.S.S. collaboration to be used for Science publications, and is already widely used in the analysis of existing gamma-ray instruments, such as MAGIC, VERITAS and HAWC

Gammapy V1.0

Gammapy is an open-source Python package for gamma-ray astronomy built on Numpy, Scipy and Astropy. It is used as core library for the Science Analysis tools of the Cherenkov Telescope Array (CTA), recommended by the H.E.S.S. collaboration to be used for Science publications, and is already widely used in the analysis of existing gamma-ray instruments, such as MAGIC, VERITAS and HAWC