1σ marginalized per cent errors on f from the Fisher analyses at z = 0.5 and z = 1. We use the full anisotropic power spectrum P(k, μ). The results correspond to the kmax values given in Table 1 for z = 0.5 and z = 1. We show results with and without selected moderate priors on {σv, b1, N} (TNS) and {b1, N} (EFTofLSS), as described in the main text. We also show results with a more conservative kmax, as described in the main text.
| . | TNS-based model . | EFTofLSS-based model . | |
|---|---|---|---|
| z = 0.5 | P(k, μ) | |$2.3\,\mathrm{ per}\,\mathrm{ cent}$| | |$3.3\,\mathrm{ per}\,\mathrm{ cent}$| |
| P(k, μ) + 10 per cent prior | |$2.2\,\mathrm{ per}\,\mathrm{ cent}$| | |$2.9\,\mathrm{ per}\,\mathrm{ cent}$| | |
| z = 1.0 | P(k, μ) | |$1.5\,\mathrm{ per}\,\mathrm{ cent}$| | |$3.1\,\mathrm{ per}\,\mathrm{ cent}$| |
| P(k, μ) + 10 per cent prior | |$1.4\,\mathrm{ per}\,\mathrm{ cent}$| | |$2.8\,\mathrm{ per}\,\mathrm{ cent}$| | |
| |$P(k,\mu)_{k_{\mathrm{max}}=0.15}$| | |$4.6\,\mathrm{ per}\,\mathrm{ cent}$| | |$5.3\,\mathrm{ per}\,\mathrm{ cent}$| | |
| . | TNS-based model . | EFTofLSS-based model . | |
|---|---|---|---|
| z = 0.5 | P(k, μ) | |$2.3\,\mathrm{ per}\,\mathrm{ cent}$| | |$3.3\,\mathrm{ per}\,\mathrm{ cent}$| |
| P(k, μ) + 10 per cent prior | |$2.2\,\mathrm{ per}\,\mathrm{ cent}$| | |$2.9\,\mathrm{ per}\,\mathrm{ cent}$| | |
| z = 1.0 | P(k, μ) | |$1.5\,\mathrm{ per}\,\mathrm{ cent}$| | |$3.1\,\mathrm{ per}\,\mathrm{ cent}$| |
| P(k, μ) + 10 per cent prior | |$1.4\,\mathrm{ per}\,\mathrm{ cent}$| | |$2.8\,\mathrm{ per}\,\mathrm{ cent}$| | |
| |$P(k,\mu)_{k_{\mathrm{max}}=0.15}$| | |$4.6\,\mathrm{ per}\,\mathrm{ cent}$| | |$5.3\,\mathrm{ per}\,\mathrm{ cent}$| | |
1σ marginalized per cent errors on f from the Fisher analyses at z = 0.5 and z = 1. We use the full anisotropic power spectrum P(k, μ). The results correspond to the kmax values given in Table 1 for z = 0.5 and z = 1. We show results with and without selected moderate priors on {σv, b1, N} (TNS) and {b1, N} (EFTofLSS), as described in the main text. We also show results with a more conservative kmax, as described in the main text.
| . | TNS-based model . | EFTofLSS-based model . | |
|---|---|---|---|
| z = 0.5 | P(k, μ) | |$2.3\,\mathrm{ per}\,\mathrm{ cent}$| | |$3.3\,\mathrm{ per}\,\mathrm{ cent}$| |
| P(k, μ) + 10 per cent prior | |$2.2\,\mathrm{ per}\,\mathrm{ cent}$| | |$2.9\,\mathrm{ per}\,\mathrm{ cent}$| | |
| z = 1.0 | P(k, μ) | |$1.5\,\mathrm{ per}\,\mathrm{ cent}$| | |$3.1\,\mathrm{ per}\,\mathrm{ cent}$| |
| P(k, μ) + 10 per cent prior | |$1.4\,\mathrm{ per}\,\mathrm{ cent}$| | |$2.8\,\mathrm{ per}\,\mathrm{ cent}$| | |
| |$P(k,\mu)_{k_{\mathrm{max}}=0.15}$| | |$4.6\,\mathrm{ per}\,\mathrm{ cent}$| | |$5.3\,\mathrm{ per}\,\mathrm{ cent}$| | |
| . | TNS-based model . | EFTofLSS-based model . | |
|---|---|---|---|
| z = 0.5 | P(k, μ) | |$2.3\,\mathrm{ per}\,\mathrm{ cent}$| | |$3.3\,\mathrm{ per}\,\mathrm{ cent}$| |
| P(k, μ) + 10 per cent prior | |$2.2\,\mathrm{ per}\,\mathrm{ cent}$| | |$2.9\,\mathrm{ per}\,\mathrm{ cent}$| | |
| z = 1.0 | P(k, μ) | |$1.5\,\mathrm{ per}\,\mathrm{ cent}$| | |$3.1\,\mathrm{ per}\,\mathrm{ cent}$| |
| P(k, μ) + 10 per cent prior | |$1.4\,\mathrm{ per}\,\mathrm{ cent}$| | |$2.8\,\mathrm{ per}\,\mathrm{ cent}$| | |
| |$P(k,\mu)_{k_{\mathrm{max}}=0.15}$| | |$4.6\,\mathrm{ per}\,\mathrm{ cent}$| | |$5.3\,\mathrm{ per}\,\mathrm{ cent}$| | |
This PDF is available to Subscribers Only
View Article Abstract & Purchase OptionsFor full access to this pdf, sign in to an existing account, or purchase an annual subscription.
