An Empirical Model For Intrinsic Alignments: Insights From Cosmological Simulations Article Swipe
Nicholas Van Alfen
,
Duncan Campbell
,
J. Blazek
,
C. Danielle Leonard
,
François Lanusse
,
Andrew P. Hearin
,
Rachel Mandelbaum
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.33232/001c.118783
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.33232/001c.118783
We extend current models of the halo occupation distribution (HOD) to include a flexible, empirical framework for the forward modeling of the intrinsic alignment (IA) of galaxies. A primary goal of this work is to produce mock galaxy catalogs for the purpose of validating existing models and methods for the mitigation of IA in weak lensing measurements. This technique can also be used to produce new, simulation-based predictions for IA and galaxy clustering. Our model is probabilistically formulated, and rests upon the assumption that the orientations of galaxies exhibit a correlation with their host dark matter (sub)halo orientation or with their position within the halo. We examine the necessary components and phenomenology of such a model by considering the alignments between (sub)halos in a cosmological dark matter only simulation. We then validate this model for a realistic galaxy population in a set of simulations in the Illustris-TNG suite. We create an HOD mock with Illustris-like correlations using our method, constraining the associated IA model parameters, with the between our model’s correlations and those of Illustris matching as closely as 1.4 and 1.1 for orientation–position and orientation–orientation correlation functions, respectively. By modeling the misalignment between galaxies and their host halo, we show that the 3-dimensional two-point position and orientation correlation functions of simulated (sub)halos and galaxies can be accurately reproduced from quasi-linear scales down to . We also find evidence for environmental influence on IA within a halo. Our publicly-available software provides a key component enabling efficient determination of Bayesian posteriors on IA model parameters using observational measurements of galaxy-orientation correlation functions in the highly nonlinear regime.
Related Topics
Concepts
Physics
Halo
Dark matter
Galaxy
Weak gravitational lensing
Position (finance)
Astrophysics
Orientation (vector space)
Statistical physics
Geometry
Mathematics
Redshift
Finance
Economics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.33232/001c.118783
- OA Status
- diamond
- Cited By
- 5
- References
- 83
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399334334
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4399334334Canonical identifier for this work in OpenAlex
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https://doi.org/10.33232/001c.118783Digital Object Identifier
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An Empirical Model For Intrinsic Alignments: Insights From Cosmological SimulationsWork title
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articleOpenAlex work type
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enPrimary language
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2024Year of publication
- Publication date
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2024-06-04Full publication date if available
- Authors
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Nicholas Van Alfen, Duncan Campbell, J. Blazek, C. Danielle Leonard, François Lanusse, Andrew P. Hearin, Rachel MandelbaumList of authors in order
- Landing page
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https://doi.org/10.33232/001c.118783Publisher landing page
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://doi.org/10.33232/001c.118783Direct OA link when available
- Concepts
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Physics, Halo, Dark matter, Galaxy, Weak gravitational lensing, Position (finance), Astrophysics, Orientation (vector space), Statistical physics, Geometry, Mathematics, Redshift, Finance, EconomicsTop concepts (fields/topics) attached by OpenAlex
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5Total citation count in OpenAlex
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2025: 3, 2024: 1, 2023: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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