9 pages, 3 figures.-- ArXiv pre-print available at: http://arxiv.org/abs/0809.0506 ; We use a Press-Schechter-like calculation to study how the abundance of voids changes in models with non-Gaussian initial conditions. While a positive skewness increases the cluster abundance, a negative skewness does the same for the void abundance. We determine the dependence of the void abundance on the non-Gaussianity parameter fnl for the local-model bispectrum —which approximates the bispectrum in some multi-field inflation models— and for the equilateral bispectrum, which approximates the bispectrum in single-field slow-roll inflation and in string-inspired DBI models of inflation. We show that the void abundance in large-scale-structure surveys currently being considered should probe values as small as f(nl) <~ 10 and f(nl)eq <~ 30, over distance scales ~ 10 Mpc. ; This work was supported at Caltech by DoE DE-FG03-92-ER40701 and the Gordon and Betty Moore Foundation. LV thanks M. LoVerde for providing the curves of Fig. 3(a,b) of Ref. [20] in table form. LV is supported by FP7-PEOPLE-2007-4-3 IRG n 202182 and CSIC I3 grant 200750I034. RJ is supported by grants from the Spanish Science Ministry and The European Union (FP7). ; Peer reviewed
Cosmological parameter estimation from forthcoming experiments promise to reach much greater precision than current constraints. As statistical errors shrink, the required control over systematic errors increases. Therefore, models or approximations that were sufficiently accurate so far, may introduce significant systematic biases in the parameter best-fit values and jeopardize the robustness of cosmological analyses. We generalize previously proposed expressions to estimate a priori the systematic error introduced in parameter inference due to the use of insufficiently good approximations in the computation of the observable of interest or the assumption of an incorrect underlying model. Although this methodology can be applied to measurements of any scientific field, we illustrate its power by studying the effect of modeling the angular galaxy power spectrum incorrectly. We also introduce Multi CLASS, a new, public modification of the Boltzmann code CLASS, which includes the possibility to compute angular cross-power spectra for two different tracers. We find that significant biases in most of the cosmological parameters are introduced if one assumes the Limber approximation or neglects lensing magnification in modern galaxy survey analyses, and the effect is in general larger for the multi-tracer case, especially for the parameter controlling primordial non-Gaussianity of the local type, f. ; JLB is supported by the Allan C. and Dorothy H. Davis Fellowship, and has been supported by the Spanish MINECO under grant BES-2015-071307, co-funded by the ESF during part of the development of this work. Funding for this work was partially provided by the Spanish MINECO under projects AYA2014-58747-P AEI/FEDER, UE, and MDM-2014-0369 of ICCUB (Unidad de Excelencia Mar´ıa de Maeztu). NB is supported by the Spanish MINECO under grant BES-2015-073372. AR has received funding from the People Programme (Marie Curie Actions) of the European Union H2020 Programme under REA grant agreement number 706896 (COSMOFLAGS). LV acknowledges support by European Union's Horizon 2020 research and innovation programme ERC (BePreSySe, grant agreement 725327).
The concept of blind analysis, a key procedure to remove the human-based systematic error called confirmation bias, has long been an integral part of data analysis in many research areas. In cosmology, blind analysis is recently making its entrance, as the field progresses into a fully fledged high-precision science. The credibility, reliability and robustness of results from future sky-surveys will dramatically increase if the effect of confirmation bias is kept under control by using an appropriate blinding procedure. Here, we present a catalog-level blinding scheme for galaxy clustering data apt to be used in future spectroscopic galaxy surveys. We shift the individual galaxy positions along the line of sight based on 1) a geometric shift mimicking the Alcock-Paczynski effect and 2) a perturbative shift akin to redshift-space distortions. This procedure has several advantages. After combining the two steps above, it is almost impossible to accidentally unblind. The procedure induces a shift in cosmological parameters without changing the galaxies' angular positions, hence without interfering with the effects of angular systematics. Since the method is applied at catalog level, there is no need to adopt several blinding schemes tuned to different summary statistics, likelihood choices or types of analyses. By testing the method on mock catalogs and the BOSS DR12 catalog we demonstrate its performance in blinding galaxy clustering data for relevant cosmological parameters sensitive to the background expansion rate and the growth rate of structures. We publicly release our data products at https://github.com/SamuelBrieden/BlindingCatalogs. ; Funding for this work was partially provided by the Spanish MINECO under projects AYA2014-58747-P AEI/FEDER, UE, PGC2018-098866-BI00,FEDER, UE, and MDM-2014-0369 of ICCUB (Unidad de Excelencia Mar´ıa de Maeztu). HGM and SB acknowledge the support from la Caixa Foundation (ID 100010434) which code LCF/BQ/PI18/11630024. LV acknowledges support by European Union's Horizon 2020 research and innovation programme ERC (BePreSySe, grant agreement 725327). JLB is supported by the Allan C. and Dorothy H. Davis Fellowship. We acknowledge support from the Spanish MICINNs Consolider-Ingenio 2010 Programme under grant MultiDark CSD2009-00064, MINECO Centro de Excelencia Severo Ochoa Programme under grant SEV- 2012-0249, and grant AYA2014-60641-C2-1-P.
In the era of precision cosmology, establishing the correct magnitude of statistical errors in cosmological parameters is of crucial importance. However, widely used approximations in galaxy surveys analyses can lead to parameter uncertainties that are grossly mis-estimated, even in a regime where the theory is well understood (e.g., linear scales). These approximations can be introduced at three different levels: in the form of the likelihood, in the theoretical modelling of the observable and in the numerical computation of the observable. Their consequences are important both in data analysis through e.g., Markov Chain Monte Carlo parameter inference, and when survey instrument and strategy are designed and their constraining power on cosmological parameters is forecasted, for instance using Fisher matrix analyses. In this work, considering the galaxy angular power spectrum as the target observable, we report one example of approximation for each of such three categories: neglecting off-diagonal terms in the covariance matrix, neglecting cosmic magnification and using the Limber approximation on large scales. We show that these commonly used approximations affect the robustness of the analysis and lead, perhaps counter-intuitively, to unacceptably large mis-estimates of parameters errors (from few 10% up to few 100%) and correlations. Furthermore, these approximations might even spoil the benefits of the nascent multi-tracer and multi-messenger cosmology. Hence we recommend that the type of analysis presented here should be repeated for every approximation adopted in survey design or data analysis, to quantify how it may affect the results. To this aim, we have developed Multi CLASS, a new extension of CLASS that includes the angular power spectrum for multiple (galaxy and other tracers such as gravitational waves) populations. The public release of Multi CLASS is associated with this paper. ; Funding for this work was partially provided by the Spanish MINECO under projects AYA2014- 58747-P AEI/FEDER, UE, and MDM-2014-0369 of ICCUB (Unidad de Excelencia María de Maeztu). NB is supported by the Spanish MINECO under grant BES-2015-073372. JLB is supported by the Allan C. and Dorothy H. Davis Fellowship, and has been supported by the Spanish MINECO under grant BES-2015-071307, co-funded by the ESF during part of the development of this work. AR has received funding from the People Programme (Marie Curie Actions) of the European Union H2020 Programme under REA grant agreement number 706896 (COSMOFLAGS). GS was supported by the Erasmus+ for Trainership grant during the early stages of this work, subsequently by grant from the "Maria de Maeztu de Ci`encies del Cosmos" project mentioned above. GS is supported by the INFN INDARK PD51 grant. LV acknowledges support by European Union's Horizon 2020 research and innovation programme ERC (BePreSySe, grant agreement 725327).
