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Register a new userA Multi-Fidelity Emulator for the Matter Power Spectrum using Gaussian Processes
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We present methods for emulating the matter power spectrum which effectively combine information from cosmological $N$-body simulations at different resolutions. An emulator allows estimation of simulation output by interpolating across the parameter space of a handful of simulations. We present the first implementation of multi-fidelity emulation in cosmology, where many low-resolution simulations are combined with a few high-resolution simulations to achieve an increased emulation accuracy. The power spectrums dependence on cosmology is learned from the low-resolution simulations, which are in turn calibrated using high-resolution simulations. We show that our multi-fidelity emulator can achieve percent-level accuracy on average with only $3$ high-fidelity simulations and outperforms a single-fidelity emulator that uses $11$ simulations. With a fixed number of high-fidelity training simulations, we show that our multi-fidelity emulator is $simeq 100$ times better than a single-fidelity emulator at $k leq 2 ,htextrm{Mpc}{^{-1}}$, and $simeq 20$ times better at $3 leq k < 6.4 ,htextrm{Mpc}{^{-1}}$. Multi-fidelity emulation is fast to train, using only a simple modification to standard Gaussian processes. Our proposed emulator shows a new way to predict non-linear scales by fusing simulations from different fidelities.
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Testing a subset of viable cosmological models beyond General Relativity (GR), with implications for cosmic acceleration and the Dark Energy associated with it, is within the reach of Rubin Observatory Legacy Survey of Space and Time (LSST) and a part of its endeavor. Deviations from GR-w(z)CDM models can manifest in the growth rate of structure and lensing, as well as in screening effects on non-linear scales. We explore the constraining power of small-scale deviations predicted by the f(R) Hu-Sawicki Modified Gravity (MG) candidate, by emulating this model with COLA (COmoving Lagrangian Acceleration) simulations. We present the experimental design, data generation, and interpolation schemes in cosmological parameters and across redshifts for the emulation of the boost in the power spectra due to Modified Gravity effects. Three preliminary applications of the emulator highlight the sensitivity to cosmological parameters, Fisher forecasting and Markov Chain Monte Carlo inference for a fiducial cosmology. This emulator will play an important role for future cosmological analysis handling the formidable amount of data expected from Rubin Observatory LSST.
We present a large suite of cosmological simulations, the FORGE (F-of-R Gravity Emulator) simulation suite, which is designed to build accurate emulators for cosmological observables in galaxy clustering, weak gravitational lensing and galaxy clusters, for the $f(R)$ gravity model. The total of 200 simulations explore the cosmological parameter space around the Planck(2018) cosmology with a Latin hypercube, for 50 combinations of $bar{f}_{R0}$, $Omega_m$, $sigma_8$ and $h$ with all other parameters fixed. For each parameter combination, or node, we ran four independent simulations, one pair using $1024^3$ particles in $500 h^{-1} Mpc$ simulation boxes to cover small scales, and another pair using $512^3$ simulation particles in $1500 h^{-1} Mpc$ boxes for larger scales. Each pair of initial conditions are selected such that sample variance on large scales is minimised on average. In this work we present an accurate emulator for the matter power spectrum in $f(R)$ gravity trained on FORGE. We have verified, using the cross-validation technique, that the emulator accuracy is better than $2.5%$ for the majority of nodes, particularly around the center of the explored parameter space, up to scales of $k = 10 h Mpc^{-1}$. We have also checked the power spectrum emulator against simulations which are not part of our training set and found excellent agreement. Due to its high accuracy on small scales, the FORGE matter power spectrum emulator is well suited for weak lensing analysis and can play a key tool in constraining $f(R)$ gravity using current and future observational data.
The light-cone (LC) effect causes the mean as well as the statistical properties of the redshifted 21-cm signal $T_{rm b}(hat{bf n}, u)$ to change with frequency $ u$ (or cosmic time). Consequently, the statistical homogeneity (ergodicity) of the signal along the line of sight (LoS) direction is broken. This is a severe problem particularly during the Epoch of Reionization (EoR) when the mean neutral hydrogen fraction ($bar{x}_{rm HI}$) changes rapidly as the universe evolves. This will also pose complications for large bandwidth observations. These effects imply that the 3D power spectrum $P(k)$ fails to quantify the entire second-order statistics of the signal as it assumes the signal to be ergodic and periodic along the LoS. As a proper alternative to $P(k)$, we use the multi-frequency angular power spectrum (MAPS) ${mathcal C}_{ell}( u_1, u_2)$ which does not assume the signal to be ergodic and periodic along the LoS. Here, we study the prospects for measuring the EoR 21-cm MAPS using future observations with the upcoming SKA-Low. Ignoring any contribution from the foregrounds, we find that the EoR 21-cm MAPS can be measured at a confidence level $ge 5sigma$ at angular scales $ell sim 1300$ for total observation time $t_{rm obs} ge 128,{rm hrs}$ across $sim 44,{rm MHz}$ observational bandwidth. We also quantitatively address the effects of foregrounds on MAPS detectability forecast by avoiding signal contained within the foreground wedge in $(k_perp, k_parallel)$ plane. These results are very relevant for the upcoming large bandwidth EoR experiments as previous predictions were all restricted to individually analyzing the signal over small frequency (or equivalently redshift) intervals.
We study the performance of the hybrid template-machine-learning photometric redshift (photo-$z$) algorithm Delight, which uses Gaussian processes, on a subset of the early data release of the Physics of the Accelerating Universe Survey (PAUS). We calibrate the fluxes of the $40$ PAUS narrow bands with $6$ broadband fluxes ($uBVriz$) in the COSMOS field using three different methods, including a new method which utilises the correlation between the apparent size and overall flux of the galaxy. We use a rich set of empirically derived galaxy spectral templates as guides to train the Gaussian process, and we show that our results are competitive with other standard photometric redshift algorithms. Delight achieves a photo-$z$ $68$th percentile error of $sigma_{68}=0.0081(1+z)$ without any quality cut for galaxies with $i_mathrm{auto}<22.5$ as compared to $0.0089(1+z)$ and $0.0202(1+z)$ for the BPz and ANNz2 codes, respectively. Delight is also shown to produce more accurate probability distribution functions for individual redshift estimates than BPz and ANNz2. Common photo-$z$ outliers of Delight and BCNz2 (previously applied to PAUS) are found to be primarily caused by outliers in the narrowband fluxes, with a small number of cases potentially indicating spectroscopic redshift failures in the reference sample. In the process, we introduce performance metrics derived from the results of BCNz2 and Delight, allowing us to achieve a photo-$z$ quality of $sigma_{68}<0.0035(1+z)$ at a magnitude of $i_mathrm{auto}<22.5$ while keeping $50$ per cent objects of the galaxy sample.
The epoch of reionization power spectrum is expected to evolve strongly with redshift, and it is this variation with cosmic history that will allow us to begin to place constraints on the physics of reionization. The primary obstacle to the measurement of the EoR power spectrum is bright foreground emission. We present an analysis of observations from the Donald C. Backer Precision Array for Probing the Epoch of Reionization (PAPER) telescope which place new limits on the HI power spectrum over the redshift range of $7.5<z<10.5$, extending previously published single redshift results to cover the full range accessible to the instrument. To suppress foregrounds, we use filtering techniques that take advantage of the large instrumental bandwidth to isolate and suppress foreground leakage into the interesting regions of $k$-space. Our 500 hour integration is the longest such yet recorded and demonstrates this method to a dynamic range of $10^4$. Power spectra at different points across the redshift range reveal the variable efficacy of the foreground isolation. Noise limited measurements of $Delta^2$ at $k=$0.2hMpc$^{-1}$ and z$=7.55$ reach as low as (48mK)$^2$ ($1sigma$). We demonstrate that the size of the error bars in our power spectrum measurement as generated by a bootstrap method is consistent with the fluctuations due to thermal noise. Relative to this thermal noise, most spectra exhibit an excess of power at a few sigma. The likely sources of this excess include residual foreground leakage, particularly at the highest redshift, and unflagged RFI. We conclude by discussing data reduction improvements that promise to remove much of this excess.
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