Describing variations of the Fisher-matrix across parameter space
Forecasts in cosmology, both with Monte Carlo Markov-chain methods and with the Fisher-matrix formalism, depend on the choice of the fiducial model because both the signal strength of any observable and the model non-linearities linking observables to cosmological parameters vary in the general case...
Gespeichert in:
| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
20 May 2016
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| In: |
Monthly notices of the Royal Astronomical Society
Year: 2016, Jahrgang: 460, Heft: 3, Pages: 3398-3406 |
| ISSN: | 1365-2966 |
| DOI: | 10.1093/mnras/stw1221 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: http://dx.doi.org/10.1093/mnras/stw1221
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| Verfasserangaben: | Björn Malte Schäfer and Robert Reischke |
| Zusammenfassung: | Forecasts in cosmology, both with Monte Carlo Markov-chain methods and with the Fisher-matrix formalism, depend on the choice of the fiducial model because both the signal strength of any observable and the model non-linearities linking observables to cosmological parameters vary in the general case. In this paper we propose a method for extrapolating Fisher-forecasts across the space of cosmological parameters by constructing a suitable basis. We demonstrate the validity of our method with constraints on a standard dark energy model extrapolated from a ΛCDM-model, as can be expected from two-bin weak lensing tomography with an Euclid-like survey, in the parameter pairs (Ωm, σ8), (Ωm, w0) and (w0, wa). Our numerical results include very accurate extrapolations across a wide range of cosmological parameters in terms of shape, size and orientation of the parameter likelihood, and a decomposition of the change of the likelihood contours into modes, which are straightforward to interpret in a geometrical way. We find that in particular the variation of the dark energy figure of merit is well captured by our formalism. |
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| Beschreibung: | Gesehen am 06.11.2016 |
| Beschreibung: | Online Resource |
| ISSN: | 1365-2966 |
| DOI: | 10.1093/mnras/stw1221 |