اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدWhy multi-tracer surveys beat cosmic variance
166
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
Galaxy surveys that map multiple species of tracers of large-scale structure can improve the constraints on some cosmological parameters far beyond the limits imposed by a simplistic interpretation of cosmic variance. This enhancement derives from comparing the relative clustering between different tracers of large-scale structure. We present a simple but fully generic expression for the Fisher information matrix of surveys with any (discrete) number of tracers, and show that the enhancement of the constraints on bias-sensitive parameters are a straightforward consequence of this multi-tracer Fisher matrix. In fact, the relative clustering amplitudes between tracers are eigenvectors of this multi-tracer Fisher matrix. The diagonalized multi-tracer Fisher matrix clearly shows that while the effective volume is bounded by the physical volume of the survey, the relational information between species is unbounded. As an application, we study the expected enhancements in the constraints of realistic surveys that aim at mapping several different types of tracers of large-scale structure. The gain obtained by combining multiple tracers is highest at low redshifts, and in one particular scenario we analyzed, the enhancement can be as large as a factor of ~3 for the accuracy in the determination of the redshift distortion parameter, and a factor ~5 for the local non-Gaussianity parameter. Radial and angular distance determinations from the baryonic features in the power spectrum may also benefit from the multi-tracer approach.
قيم البحث
اقرأ أيضاً
Deep pencil beam surveys (<1 deg^2) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties are in practice limited by cosmic variance. This is the uncertainty in observational est
imates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper we provide tools for experiment design and interpretation. For a given survey geometry we present the cosmic variance of dark matter as a function of mean redshift z and redshift bin size Dz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, z, Dz and stellar mass m*. We also provide tabulated values and a software tool. We find that for GOODS at z=2 and with Dz=0.5 the relative cosmic variance of galaxies with m*>10^11 Msun is ~38%, while it is ~27% for GEMS and ~12% for COSMOS. For galaxies of m*~10^10 Msun the relative cosmic variance is ~19% for GOODS, ~13% for GEMS and ~6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at z=2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies cosmic variance is less serious.
Measuring the total neutrino mass is one of the most exciting opportunities available with next-generation cosmological data sets. We study the possibility of detecting the total neutrino mass using large-scale clustering in 21cm intensity mapping an
d photometric galaxy surveys, together with CMB information. We include the scale-dependent halo bias contribution due to the presence of massive neutrinos, and use a multi-tracer analysis in order to reduce cosmic variance. The multi-tracer combination of an SKAO-MID 21cm intensity map with Stage~4 CMB lensing dramatically shrinks the uncertainty on total neutrino mass to $sigma(M_ u) simeq 45,$meV, using only linear clustering information ($k_{rm max} = 0.1, h/$Mpc) and without a prior on optical depth. When we add to the multi-tracer the clustering information expected from LSST, the forecast is $sigma(M_ u) simeq 12,$meV.
Current and future generations of intensity mapping surveys promise dramatic improvements in our understanding of galaxy evolution and large-scale structure. An intensity map provides a census of the cumulative emission from all galaxies in a given r
egion and redshift, including faint objects that are undetectable individually. Furthermore, cross-correlations between line intensity maps and galaxy redshift surveys are sensitive to the line intensity and clustering bias without the limitation of cosmic variance. Using the Fisher information matrix, we derive simple expressions describing sensitivities to the intensity and bias obtainable for cross-correlation surveys, focusing on cosmic variance evasion. Based on these expressions, we conclude that the optimal sensitivity is obtained by matching the survey depth, defined by the ratio of the clustering power spectrum to noise in a given mode, between the two surveys. We find that mid- to far-infrared space telescopes could benefit from this technique by cross-correlating with coming galaxy redshift surveys such as those planned for the Nancy Grace Roman Space Telescope, allowing for sensitivities beyond the cosmic variance limit. Our techniques can therefore be applied to survey design and requirements development to maximize the sensitivities of future intensity mapping experiments to tracers of galaxy evolution and large-scale structure cosmology.
The next generation of Cosmic Microwave Background experiments will produce cosmic variance limited observations over a large fraction of sky and for a large range of multipoles. In this work we discuss different consistency tests that can be perform
ed with the upcoming data from the Simons Observatory and the Planck data. We quantify the level of expected cosmological parameter shifts probed by these tests. We discuss the effect of difference in frequency of observation and present forecasts on a direct measurement of the Planck T-to-E leakage beam. We find that instrumental systematics in either of the experiments will be assessed with an exquisite precision, well beyond the intrinsic uncertainties due to the CMB cosmic variance.
We use mock galaxy data from the VIMOS Public Extragalactic Redshift Survey (VIPERS) to test the performance of the Multi-Tracer Optimal Estimator (MTOE) of Abramo et al. as a tool to measure the monopoles of the power spectra of multiple tracers of
the large-scale structure, $P^{(0)}_alpha(k)$. We show that MTOE provides more accurate measurements than the standard technique of Feldman, Kaiser & Peacock (FKP), independently of the tracer-selection strategy adopted, on both small and large scales. The largest improvements on individual $P^{(0)}_alpha(k)$ are obtained using a colour-magnitude selection on small scales, due to MTOE being naturally better equipped to deal with shot noise: we report an average error reduction with respect to FKP of $sim$ 40$%$ at $k , [h$ Mpc$^{-1}]gtrsim 0.3$. On large scales ($k[h$ Mpc$^{-1}]lesssim0.1$), the gain in accuracy resulting from cosmic-variance cancellation is $sim$ 10$%$ for the ratios of $P^{(0)}_alpha(k)$. We have carried out a Monte-Carlo Markov Chain analysis to determine the impact of these gains on several quantities derived from $P^{(0)}_alpha(k)$. If we push the measurement to scales $0.3 < k , [h$ Mpc$^{-1}]< 0.5$, the average improvements are $sim$ 30 $%$ for the amplitudes of the monopoles, $sim$ 70 $%$ for the monopole ratios, and $sim$ 20 $%$ for the galaxy biases. Our results highlight the potential of MTOE to shed light upon the physics that operate both on large and small cosmological scales. The effect of MTOE on cosmological constraints using VIPERS data will be addressed in a separate paper.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
