Modelling galaxy populations in the era of big data
© International Astronomical Union 2015. The coming decade will witness a deluge of data from next generation galaxy surveys such as the Square Kilometre Array and Euclid. How can we optimally and robustly analyse these data to maximise scientific returns from these surveys? Here we discuss recent w...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/56295 |
| _version_ | 1848759837319495680 |
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| author | Murray, Steven Power, C. Robotham, A. |
| author_facet | Murray, Steven Power, C. Robotham, A. |
| author_sort | Murray, Steven |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © International Astronomical Union 2015. The coming decade will witness a deluge of data from next generation galaxy surveys such as the Square Kilometre Array and Euclid. How can we optimally and robustly analyse these data to maximise scientific returns from these surveys? Here we discuss recent work in developing both the conceptual and software frameworks for carrying out such analyses and their application to the dark matter halo mass function. We summarise what we have learned about the HMF from the last 10 years of precision CMB data using the open-source HMFcalc framework, before discussing how this framework is being extended to the full Halo Model. |
| first_indexed | 2025-11-14T10:06:13Z |
| format | Journal Article |
| id | curtin-20.500.11937-56295 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:06:13Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-562952017-09-13T16:10:28Z Modelling galaxy populations in the era of big data Murray, Steven Power, C. Robotham, A. © International Astronomical Union 2015. The coming decade will witness a deluge of data from next generation galaxy surveys such as the Square Kilometre Array and Euclid. How can we optimally and robustly analyse these data to maximise scientific returns from these surveys? Here we discuss recent work in developing both the conceptual and software frameworks for carrying out such analyses and their application to the dark matter halo mass function. We summarise what we have learned about the HMF from the last 10 years of precision CMB data using the open-source HMFcalc framework, before discussing how this framework is being extended to the full Halo Model. 2015 Journal Article http://hdl.handle.net/20.500.11937/56295 10.1017/S1743921314010710 restricted |
| spellingShingle | Murray, Steven Power, C. Robotham, A. Modelling galaxy populations in the era of big data |
| title | Modelling galaxy populations in the era of big data |
| title_full | Modelling galaxy populations in the era of big data |
| title_fullStr | Modelling galaxy populations in the era of big data |
| title_full_unstemmed | Modelling galaxy populations in the era of big data |
| title_short | Modelling galaxy populations in the era of big data |
| title_sort | modelling galaxy populations in the era of big data |
| url | http://hdl.handle.net/20.500.11937/56295 |