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Article: DmpIRFs and DmpST: DAMPE instrument response functions and science tools for gamma-ray data analysis

TitleDmpIRFs and DmpST: DAMPE instrument response functions and science tools for gamma-ray data analysis
Authors
Keywordsgamma rays: general
instrumentation: detectors
methods: statistical
Issue Date2019
PublisherInstitute of Physics Publishing Ltd. The Journal's web site is located at http://iopscience.iop.org/1674-4527/
Citation
Research in Astronomy and Astrophysics, 2019, v. 19 n. 9, p. article no. 132 How to Cite?
AbstractObserving GeV gamma-rays is an important goal of the DArkMatter Particle Explorer (DAMPE) for indirect dark matter searching and high energy astrophysics. In this work, we present a set of accurate instrument response functions for DAMPE (DmpIRFs) including the effective area, point-spread function and energy dispersion, which are crucial for gamma-ray data analysis based on statistics from simulation data. A dedicated software named DmpST is developed to facilitate the scientific analyses of DAMPE gamma-ray data. Considering the limited number of photons and angular resolution of DAMPE, the maximum likelihood method is adopted in DmpST to better disentangle different source components. The basic mathematics and framework regarding this software are also introduced in this paper.
Persistent Identifierhttp://hdl.handle.net/10722/279485
ISSN
2017 Impact Factor: 1.227
2015 SCImago Journal Rankings: 0.883

 

DC FieldValueLanguage
dc.contributor.authorDuan, KK-
dc.contributor.authorJiang, W-
dc.contributor.authorLiang, YF-
dc.contributor.authorShen, ZQ-
dc.contributor.authorXu, ZL-
dc.contributor.authorFan, YZ-
dc.contributor.authorGargano, F-
dc.contributor.authorGarrappa, S-
dc.contributor.authorGuo, DY-
dc.contributor.authorLei, SJ-
dc.contributor.authorLi, X-
dc.contributor.authorMazziotta, MN-
dc.contributor.authorSalinas, MFM-
dc.contributor.authorSu, M-
dc.contributor.authorVagelli, V-
dc.contributor.authorYuan, Q-
dc.contributor.authorYue, C-
dc.contributor.authorZimmer, S-
dc.date.accessioned2019-11-01T07:18:17Z-
dc.date.available2019-11-01T07:18:17Z-
dc.date.issued2019-
dc.identifier.citationResearch in Astronomy and Astrophysics, 2019, v. 19 n. 9, p. article no. 132-
dc.identifier.issn1674-4527-
dc.identifier.urihttp://hdl.handle.net/10722/279485-
dc.description.abstractObserving GeV gamma-rays is an important goal of the DArkMatter Particle Explorer (DAMPE) for indirect dark matter searching and high energy astrophysics. In this work, we present a set of accurate instrument response functions for DAMPE (DmpIRFs) including the effective area, point-spread function and energy dispersion, which are crucial for gamma-ray data analysis based on statistics from simulation data. A dedicated software named DmpST is developed to facilitate the scientific analyses of DAMPE gamma-ray data. Considering the limited number of photons and angular resolution of DAMPE, the maximum likelihood method is adopted in DmpST to better disentangle different source components. The basic mathematics and framework regarding this software are also introduced in this paper.-
dc.languageeng-
dc.publisherInstitute of Physics Publishing Ltd. The Journal's web site is located at http://iopscience.iop.org/1674-4527/-
dc.relation.ispartofResearch in Astronomy and Astrophysics-
dc.rightsResearch in Astronomy and Astrophysics. Copyright © Institute of Physics Publishing Ltd.-
dc.rightsThis is an author-created, un-copyedited version of an article published in [insert name of journal]. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at http://dx.doi.org/[insert DOI].-
dc.subjectgamma rays: general-
dc.subjectinstrumentation: detectors-
dc.subjectmethods: statistical-
dc.titleDmpIRFs and DmpST: DAMPE instrument response functions and science tools for gamma-ray data analysis-
dc.typeArticle-
dc.identifier.emailSu, M: mengsu84@hku.hk-
dc.identifier.authoritySu, M=rp02150-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1088/1674-4527/19/9/132-
dc.identifier.scopuseid_2-s2.0-85072797882-
dc.identifier.hkuros308594-
dc.identifier.volume19-
dc.identifier.issue9-
dc.identifier.spagearticle no. 132-
dc.identifier.epagearticle no. 132-
dc.publisher.placeUnited Kingdom-

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