PINNferring the Hubble Function with Uncertainties
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866929285816647680 |
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| author | Röver, Lennart Schäfer, Björn Malte Plehn, Tilman |
| author_facet | Röver, Lennart Schäfer, Björn Malte Plehn, Tilman |
| contents | The Hubble function characterizes a given Friedmann-Robertson-Walker spacetime and can be related to the densities of the cosmological fluids and their equations of state. We show how physics-informed neural networks (PINNs) emulate this dynamical system and provide fast predictions of the luminosity distance for a given choice of densities and equations of state, as needed for the analysis of supernova data. We use this emulator to perform a model-independent and parameter-free reconstruction of the Hubble function on the basis of supernova data. As part of this study, we develop and validate an uncertainty treatment for PINNs using a heteroscedastic loss and repulsive ensembles. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_13899 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | PINNferring the Hubble Function with Uncertainties Röver, Lennart Schäfer, Björn Malte Plehn, Tilman Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics High Energy Physics - Phenomenology The Hubble function characterizes a given Friedmann-Robertson-Walker spacetime and can be related to the densities of the cosmological fluids and their equations of state. We show how physics-informed neural networks (PINNs) emulate this dynamical system and provide fast predictions of the luminosity distance for a given choice of densities and equations of state, as needed for the analysis of supernova data. We use this emulator to perform a model-independent and parameter-free reconstruction of the Hubble function on the basis of supernova data. As part of this study, we develop and validate an uncertainty treatment for PINNs using a heteroscedastic loss and repulsive ensembles. |
| title | PINNferring the Hubble Function with Uncertainties |
| topic | Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics High Energy Physics - Phenomenology |
| url | https://arxiv.org/abs/2403.13899 |