Identifying Diffuse Spatial Structures in High-energy Photon Lists
Data from high-energy observations are usually obtained as lists of photon events. A common analysis task for such data is to identify whether diffuse emission exists, and to estimate its surface brightness, even in the presence of point sources that may be superposed. We have developed a novel nonp...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2023-01-01
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| Series: | The Astronomical Journal |
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| Online Access: | https://doi.org/10.3847/1538-3881/aca478 |
| _version_ | 1797701499203092480 |
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| author | Minjie Fan Jue Wang Vinay L. Kashyap Thomas C. M. Lee David A. van Dyk Andreas Zezas |
| author_facet | Minjie Fan Jue Wang Vinay L. Kashyap Thomas C. M. Lee David A. van Dyk Andreas Zezas |
| author_sort | Minjie Fan |
| collection | DOAJ |
| description | Data from high-energy observations are usually obtained as lists of photon events. A common analysis task for such data is to identify whether diffuse emission exists, and to estimate its surface brightness, even in the presence of point sources that may be superposed. We have developed a novel nonparametric event list segmentation algorithm to divide up the field of view into distinct emission components. We use photon location data directly, without binning them into an image. We first construct a graph from the Voronoi tessellation of the observed photon locations and then grow segments using a new adaptation of seeded region growing that we call Seeded Region Growing on Graph , after which the overall method is named SRGonG . Starting with a set of seed locations, this results in an oversegmented data set, which SRGonG then coalesces using a greedy algorithm where adjacent segments are merged to minimize a model comparison statistic; we use the Bayesian Information Criterion. Using SRGonG we are able to identify point-like and diffuse extended sources in the data with equal facility. We validate SRGonG using simulations, demonstrating that it is capable of discerning irregularly shaped low-surface-brightness emission structures as well as point-like sources with strengths comparable to that seen in typical X-ray data. We demonstrate SRGonG ’s use on the Chandra data of the Antennae galaxies and show that it segments the complex structures appropriately. |
| first_indexed | 2024-03-12T04:37:33Z |
| format | Article |
| id | doaj.art-f839a6f73f6d43489b701baa7f84eb81 |
| institution | Directory Open Access Journal |
| issn | 1538-3881 |
| language | English |
| last_indexed | 2024-03-12T04:37:33Z |
| publishDate | 2023-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | The Astronomical Journal |
| spelling | doaj.art-f839a6f73f6d43489b701baa7f84eb812023-09-03T09:55:18ZengIOP PublishingThe Astronomical Journal1538-38812023-01-0116526610.3847/1538-3881/aca478Identifying Diffuse Spatial Structures in High-energy Photon ListsMinjie Fan0Jue Wang1Vinay L. Kashyap2https://orcid.org/0000-0002-3869-7996Thomas C. M. Lee3https://orcid.org/0000-0001-7067-405XDavid A. van Dyk4https://orcid.org/0000-0002-0816-331XAndreas Zezas5https://orcid.org/0000-0001-8952-676XDepartment of Statistics, University of California , Davis, One Shields Avenue, Davis, CA 95616, USA ; tcmlee@ucdavis.eduDepartment of Statistics, University of California , Davis, One Shields Avenue, Davis, CA 95616, USA ; tcmlee@ucdavis.eduCenter for Astrophysics | Harvard & Smithsonian, 60 Garden Street, Cambridge, MA 02138, USADepartment of Statistics, University of California , Davis, One Shields Avenue, Davis, CA 95616, USA ; tcmlee@ucdavis.eduStatistics Section, Department of Mathematics, Imperial College London , 180 Queen’s Gate, London, SW7 2AZ, UKPhysics Department, deUniversity of Crete , P.O. Box 2208, GF-710 03, Heraklion, Crete, GreeceData from high-energy observations are usually obtained as lists of photon events. A common analysis task for such data is to identify whether diffuse emission exists, and to estimate its surface brightness, even in the presence of point sources that may be superposed. We have developed a novel nonparametric event list segmentation algorithm to divide up the field of view into distinct emission components. We use photon location data directly, without binning them into an image. We first construct a graph from the Voronoi tessellation of the observed photon locations and then grow segments using a new adaptation of seeded region growing that we call Seeded Region Growing on Graph , after which the overall method is named SRGonG . Starting with a set of seed locations, this results in an oversegmented data set, which SRGonG then coalesces using a greedy algorithm where adjacent segments are merged to minimize a model comparison statistic; we use the Bayesian Information Criterion. Using SRGonG we are able to identify point-like and diffuse extended sources in the data with equal facility. We validate SRGonG using simulations, demonstrating that it is capable of discerning irregularly shaped low-surface-brightness emission structures as well as point-like sources with strengths comparable to that seen in typical X-ray data. We demonstrate SRGonG ’s use on the Chandra data of the Antennae galaxies and show that it segments the complex structures appropriately.https://doi.org/10.3847/1538-3881/aca478Spatial point processesAstrostatistics techniquesVoronoi tessellationAstronomy data modeling |
| spellingShingle | Minjie Fan Jue Wang Vinay L. Kashyap Thomas C. M. Lee David A. van Dyk Andreas Zezas Identifying Diffuse Spatial Structures in High-energy Photon Lists The Astronomical Journal Spatial point processes Astrostatistics techniques Voronoi tessellation Astronomy data modeling |
| title | Identifying Diffuse Spatial Structures in High-energy Photon Lists |
| title_full | Identifying Diffuse Spatial Structures in High-energy Photon Lists |
| title_fullStr | Identifying Diffuse Spatial Structures in High-energy Photon Lists |
| title_full_unstemmed | Identifying Diffuse Spatial Structures in High-energy Photon Lists |
| title_short | Identifying Diffuse Spatial Structures in High-energy Photon Lists |
| title_sort | identifying diffuse spatial structures in high energy photon lists |
| topic | Spatial point processes Astrostatistics techniques Voronoi tessellation Astronomy data modeling |
| url | https://doi.org/10.3847/1538-3881/aca478 |
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