arXiv subjects

Francisco-Shu Kitaura

Publications and source records attributed to Francisco-Shu Kitaura.

At least 37 records · Page 2Linked to original sources

arXiv2022

Cosmic Void Baryon Acoustic Oscillation Measurement: Evaluation of Sensitivity to Selection Effects

Cosmic voids defined as a subset of Delaunay Triangulation (DT) circumspheres have been used to measure the Baryon Acoustic Oscillations (BAO) scale; providing tighter constraints on cosmological parameters when combined with matter tracers. These voids are defined as spheres larger than a given radius threshold, which is constant over the survey volume. However, the response of these void tracers to observational systematics has not yet been studied. In this work we analyse the response of void clustering to selection effects. We find for the case of moderate (<20 per cent) incompleteness, void selection based on a constant radius cut yields robust measurements. This is particularly true for BAO-reconstructed galaxy samples, where large-scale void exclusion effects are mitigated. Moreover, we observe for the case of severe (up to 90 per cent) incompleteness -- such as can be found at the edges of the radial selection function -- that an accurate estimation of the void distribution is necessary for unbiased clustering measurements. In addition, we find that without reconstruction, using a constant threshold under these conditions produces a stronger void exclusion effect that can affect the clustering on large scales. A new void selection criteria dependent on the (local) observed tracer density that maximises the BAO peak significance prevents the aforementioned exclusion features from contaminating the BAO signal. Finally, we verify, with large simulations including light cone evolution, that both void sample definitions (local and constant) yield unbiased and consistent BAO scale measurements.

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arXiv2022

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Cosmological implications from multi-tracer BAO analysis with galaxies and voids

We construct cosmic void catalogues with the DIVE void finder upon SDSS BOSS DR12 and eBOSS DR16 galaxy samples with BAO reconstruction applied, and perform a joint BAO analysis using different types of galaxies and the corresponding voids. The BAO peak is evident for the galaxy-galaxy, galaxy-void, and void-void correlation functions of all datasets, including the ones cross correlating luminous red galaxy and emission line galaxy samples. Two multi-tracer BAO fitting schemes are then tested, one combining the galaxy and void correlation functions with a weight applied to voids, and the other using a single BAO dilation parameter for all clustering measurements of different tracers. Both methods produce consistent results with mock catalogues, and on average ~10 per cent improvements of the BAO statistical uncertainties are observed for all samples, compared to the results from galaxies alone. By combining the clustering of galaxies and voids, the uncertainties of BAO measurements from the SDSS data are reduced by 5 to 15 per cent, yielding 0.9, 0.8, 1.1, 2.3, and 2.9 per cent constraints on the distance $D_{_{\rm V}}(z)$, at effective redshifts of 0.38, 0.51, 0.70, 0.77, and 0.85, respectively. When combined with BAO measurements from SDSS MGS, QSO, and Ly$α$ samples, as well as the BBN results, we obtain $H_0 = 67.58 \pm 0.91\,{\rm km}\,{\rm s}^{-1}\,{\rm Mpc}^{-1}$, $Ω_{\rm m} = 0.290 \pm 0.015$, and $Ω_Λh^2 = 0.3241 \pm 0.0079$ in the flat-$Λ$CDM framework, where the 1$\,σ$ uncertainties are around 6, 6, and 17 per cent smaller respectively, compared to constraints from the corresponding anisotropic BAO measurements without voids and LRG-ELG cross correlations.

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arXiv2022

The cosmic web connection to the dark matter halo distribution through gravity

This work investigates the connection between the cosmic web and the halo distribution through the gravitational potential at the field level. We combine three fields of research, cosmic web classification, perturbation theory expansions of the halo bias, and halo (galaxy) mock catalogue making methods. In particular, we use the invariants of the tidal field and the velocity shear tensor as generating functions to reproduce the halo number counts of a reference catalogue from full gravity calculations, populating the dark matter field on a mesh well into the non-linear regime ($3\,h^{-1}\,{\rm Mpc}$ scales). Our results show an unprecedented agreement with the reference power spectrum within 1% up to $k=0.72\,h\,{\rm Mpc}^{-1}$. By analysing the three-point statistics on large scales (configurations of up to $k=0.2\,h\,{\rm Mpc}^{-1}$), we find evidence for non-local bias at the 4.8 $σ$ confidence level, being compatible with the reference catalogue. In particular, we find that a detailed description of tidal anisotropic clustering on large scales is crucial to achieve this accuracy at the field level. These findings can be particularly important for the analysis of the next generation of galaxy surveys in mock galaxy production.

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arXiv2022

Mapping Lyman-alpha forest three-dimensional large scale structure in real and redshift space

This work presents a new physically-motivated supervised machine learning method, Hydro-BAM, to reproduce the three-dimensional Lyman-$α$ forest field in real and in redshift space learning from a reference hydrodynamic simulation, thereby saving about 7 orders of magnitude in computing time. We show that our method is accurate up to $k\sim1\,h\,\rm{Mpc}^{-1}$ in the one- (PDF), two- (power-spectra) and three-point (bi-spectra) statistics of the reconstructed fields. When compared to the reference simulation including redshift space distortions, our method achieves deviations of $\lesssim2\%$ up to $k=0.6\,h\,\rm{Mpc}^{-1}$ in the monopole, $\lesssim5\%$ up to $k=0.9\,h\,\rm{Mpc}^{-1}$ in the quadrupole. The bi-spectrum is well reproduced for triangle configurations with sides up to $k=0.8\,h\,\rm{Mpc}^{-1}$. In contrast, the commonly-adopted Fluctuating Gunn-Peterson approximation shows significant deviations already neglecting peculiar motions at configurations with sides of $k=0.2-0.4\,h\,\rm{Mpc}^{-1}$ in the bi-spectrum, being also significantly less accurate in the power-spectrum (within 5$\%$ up to $k=0.7\,h\,\rm{Mpc}^{-1}$). We conclude that an accurate analysis of the Lyman-$α$ forest requires considering the complex baryonic thermodynamical large-scale structure relations. Our hierarchical domain specific machine learning method can efficiently exploit this and is ready to generate accurate Lyman-$α$ forest mock catalogues covering large volumes required by surveys such as DESI and WEAVE.

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arXiv2022

UNITSIM-Galaxies: data release and clustering of emission-line galaxies

New surveys such as ESA's Euclid mission are planned to map with unprecedented precision the large-scale structure of the Universe by measuring the 3D positions of tens of millions of galaxies. It is necessary to develop theoretically modelled galaxy catalogues to estimate the expected performance and to optimise the analysis strategy of these surveys. We populate two pairs of (1 Gpc/h)^3 volume dark-matter-only simulations from the UNIT project with galaxies using the SAGE semi-analytic model of galaxy formation, coupled to the photoionisation model get_emlines to estimate their H_alpha emission. These catalogues represent a unique suite that includes galaxy formation physics and - thanks to the fixed-pair technique used - an effective volume of ~(5 Gpc/h)^3, which is several times larger than the Euclid survey. We present the performance of these data and create five additional emission-line galaxy (ELG) catalogues by applying a dust attenuation model as well as adjusting the flux threshold as a function of redshift in order to reproduce Euclid-forecast dN/dz values. As a first application, we study the abundance and clustering of those model H_alpha ELGs: for scales greater than ~5 Mpc/h, we find a scale-independent bias with a value of $b\sim 1$ at redshift z ~ 0.5, that can increase nearly linearly to $b\sim 4$ at $z\sim 2$, depending on the ELG catalogue. Model galaxy properties, including their emission-line fluxes (with and without dust extinction) are publicly available.

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arXiv2021

The bias from hydrodynamic simulations: mapping baryon physics onto dark matter fields

This paper investigates the hierarchy of baryon physics assembly bias relations obtained from state-of-the-art hydrodynamic simulations with respect to the underlying cosmic web spanned by the dark matter field. Using the Bias Assignment Method (BAM) we find that non-local bias plays a central role. We classify the cosmic web based on the invariants of the curvature tensor defined not only by the gravitational potential, but especially by the over-density, as small scale clustering becomes important in this context. First, the gas density bias relation can be directly mapped onto the dark matter density field to high precision exploiting the strong correlation between them. In a second step, the neutral hydrogen is mapped based on the dark matter and the gas density fields. Finally, the temperature is mapped based on the previous quantities. This permits us to statistically reconstruct the baryon properties within the same simulated volume finding percent-precision in the two-point statistics and compatible results in the three-point statistics, in general within 1-$σ$, with respect to the reference simulation (with 5 to 6 orders of magnitude less computing time). This paves the path to establish the best set-up for the construction of mocks probing the intergalactic medium for the generation of such key ingredients in the statistical analysis of large forthcoming missions such as DESI, Euclid, J-PAS and WEAVE.

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arXiv2021

Higher Order Hamiltonian Monte Carlo Sampling for Cosmological Large-Scale Structure Analysis

We investigate higher order symplectic integration strategies within Bayesian cosmic density field reconstruction methods. In particular, we study the fourth-order discretisation of Hamiltonian equations of motion (EoM). This is achieved by recursively applying the basic second-order leap-frog scheme (considering the single evaluation of the EoM) in a combination of even numbers of forward time integration steps with a single intermediate backward step. This largely reduces the number of evaluations and random gradient computations, as required in the usual second-order case for high-dimensional cases. We restrict this study to the lognormal-Poisson model, applied to a full volume halo catalogue in real space on a cubical mesh of 1250 $h^{-1}$ Mpc side and 256$^3$ cells. Hence, we neglect selection effects, redshift space distortions, and displacements. We note that those observational and cosmic evolution effects can be accounted for in subsequent Gibbs-sampling steps within the COSMIC BIRTH algorithm. We find that going from the usual second to fourth-order in the leap-frog scheme shortens the burn-in phase by a factor of at least $\sim30$. This implies that 75-90 independent samples are obtained while the fastest second-order method converges. After convergence, the correlation lengths indicate an improvement factor of about 3.0 fewer gradient computations for meshes of 256$^3$ cells. In the considered cosmological scenario, the traditional leap-frog scheme turns out to outperform higher order integration schemes only at lower dimensional problems, e.g. meshes with 64$^3$ cells. This gain in computational efficiency can help to go towards a full Bayesian analysis of the cosmological large-scale structure for upcoming galaxy surveys.

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arXiv2021

Constraining Primordial Non-Gaussianity with Post-reconstructed Galaxy Bispectrum in Redshift Space

Galaxy bispectrum is a promising probe of inflationary physics in the early universe as a measure of primordial non-Gaussianity (PNG), whereas its signal-to-noise ratio is significantly affected by the mode coupling due to non-linear gravitational growth. In this paper, we examine the standard reconstruction method of linear cosmic mass density fields from non-linear galaxy density fields to de-correlate the covariance in redshift-space galaxy bispectra. In particular, we evaluate the covariance of the bispectrum for massive-galaxy-sized dark matter halos with reconstruction by using 4000 independent $N$-body simulations. Our results show that the bispectrum covariance for the post-reconstructed field approaches the Gaussian prediction at scale of $k<0.2\, h\, {\rm Mpc}^{-1}$. We also verify the leading-order PNG-induced bispectrum is not affected by details of the reconstruction with perturbative theory. We then demonstrate the constraining power of the post-reconstructed bispectrum for PNG at redshift of $\sim0.5$. Further, we perform a Fisher analysis to make a forecast of PNG constraints by galaxy bispectra including anisotropic signals. Assuming a massive galaxy sample in the SDSS Baryon Oscillation Spectroscopic Survey, we find that the post-reconstructed bispectrum can constrain the local-, equilateral- and orthogonal-types of PNG with $Δf_{\rm NL} \sim$13, 90 and 42, respectively, improving the constraints with the pre-reconstructed bispectrum by a factor of $1.3-3.2$. In conclusion, the reconstruction plays an essential role in constraining various types of PNG signatures with a level of $Δf_{\rm NL}<1$ from the galaxy bispectrum based on upcoming galaxy surveys.

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arXiv2020

COSMIC BIRTH: Efficient Bayesian Inference of the Evolving Cosmic Web from Galaxy Surveys

We present COSMIC BIRTH: COSMological Initial Conditions from Bayesian Inference Reconstructions with THeoretical models: an algorithm to reconstruct the primordial and evolved cosmic density fields from galaxy surveys on the light-cone. The displacement and peculiar velocity fields are obtained from forward modelling at different redshift snapshots given some initial cosmic density field within a Gibbs-sampling scheme. This allows us to map galaxies, observed in a light-cone, to a single high redshift and hereby provide tracers and the corresponding survey completeness in Lagrangian space including phase-space mapping. These Lagrangian tracers in turn permit us to efficiently obtain the primordial density field, making the COSMIC BIRTH code general to any structure formation model. Our tests are restricted for the time being to Augmented Lagrangian Perturbation theory. We show how to robustly compute the non-linear Lagrangian bias from clustering measurements in a numerical way, enabling us to get unbiased dark matter field reconstructions at initial cosmic times. We also show that we can greatly recover the information of the dark matter field from the galaxy distribution based on a detailed simulation. Novel key ingredients to this approach are a higher-order Hamiltonian sampling technique and a non-diagonal Hamiltonian mass-matrix. This technique could be used to study the Eulerian galaxy bias from galaxy surveys and could become an ideal baryon acoustic reconstruction technique. In summary, this method represents a general reconstruction technique, including in a self-consistent way a survey mask, non-linear and non-local bias and redshift space distortions, with an efficiency about 10 times superior to previous comparable methods.

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arXiv2020

BIRTH of the COSMOS Field: Primordial and Evolved Density Reconstructions During Cosmic High Noon

This work presents the first comprehensive study of structure formation at the peak epoch of cosmic star formation over $1.4\leq z \leq 3.6$ in the COSMOS field, including the most massive high redshift galaxy proto-clusters at that era. We apply the extended COSMIC BIRTH algorithm to account for a multi-tracer and multi-survey Bayesian analysis at Lagrangian initial cosmic times. Combining the data of five different spectroscopic redshift surveys (zCOSMOS-deep, VUDS, MOSDEF, ZFIRE, and FMOS-COSMOS), we show that the corresponding unbiased primordial density fields can be inferred, if a proper survey completeness computation from the parent photometric catalogs, and a precise treatment of the non-linear and non-local evolution on the light-cone is taken into account, including (i) gravitational matter displacements, (ii) peculiar velocities, and (iii) galaxy bias. The reconstructions reveal a holistic view on the known proto-clusters in the COSMOS field and the growth of the cosmic web towards lower redshifts. The inferred distant dark matter density fields concurrently with other probes like tomographic reconstructions of the intergalactic medium will explore the interplay of gas and dark matter and are ideally suited to study structure formation at high redshifts in the light of upcoming deep surveys.

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arXiv2019

Improving baryon acoustic oscillation measurement with the combination of cosmic voids and galaxies

We develop a methodology to optimise the measurement of Baryon Acoustic Oscillation (BAO) from a given galaxy sample. In our previous work, we demonstrated that one can measure BAO from tracers in under-dense regions (voids). In this study, we combine the over-dense and under-dense tracers (galaxies & voids) to obtain better constraints on the BAO scale. To this end, we modify the de-wiggled BAO model with an additional parameter to describe both the BAO peak and the underlying exclusion pattern of void 2PCFs. We show that after applying BAO reconstruction to galaxies, the BAO peak scale of both galaxies and voids are unbiased using the modified model. Furthermore, we use a new 2PCF estimator for a multi-tracer analysis with galaxies and voids. In simulations, the joint sample improves by about 10% the constraint for the post-reconstruction BAO peak position compared to the result from galaxies alone, which is equivalent to an enlargement of the survey volume by 20%. Applying this method to the BOSS DR12 data, we have an 18% improvement for the low-z sample (0.2<z<0.5), but a worse constraint for the high-z sample (0.5<z<0.75), which is consistent with statistical fluctuations for the current survey volume. Future larger samples will give more robust improvements due to less statistical fluctuations.

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arXiv2019

One simulation to have them all: performance of the Bias Assignment Method against N-body simulations

In this paper we demonstrate that the information encoded in \emph{one} single (sufficiently large) $N$-body simulation can be used to reproduce arbitrary numbers of halo catalogues, using approximated realisations of dark matter density fields with different initial conditions. To this end we use as a reference one realisation (from an ensemble of $300$) of the Minerva $N$-body simulations and the recently published Bias Assignment Method to extract the local and non-local bias linking the halo to the dark matter distribution. We use an approximate (and fast) gravity solver to generate $300$ dark matter density fields from the down-sampled initial conditions of the reference simulation and sample each of these fields using the halo-bias and a kernel, both calibrated from the arbitrarily chosen realisation of the reference simulation. We show that the power spectrum, its variance and the three-point statistics are reproduced within $\sim 2\%$ (up to $k\sim1.0\,h\,{\rm Mpc}^{-1}$), $\sim 5-10\%$ and $\sim 10\%$, respectively. Using a model for the real space power spectrum (with three free bias parameters), we show that the covariance matrices obtained from our procedure lead to parameter uncertainties that are compatible within $\sim 10\%$ with respect to those derived from the reference covariance matrix, and motivate approaches that can help to reduce these differences to $\sim 1\%$. Our method has the potential to learn from one simulation with moderate volumes and high-mass resolution and extrapolate the information of the bias and the kernel to larger volumes, making it ideal for the construction of mock catalogues for present and forthcoming observational campaigns such as Euclid or DESI.

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arXiv2019

The bias of dark matter tracers: assessing the accuracy of mapping techniques

We present a comparison between approximated methods for the construction of mock catalogs based on the halo-bias mapping technique. To this end, we use as reference a high resolution $N$-body simulation of 3840$^3$ dark matter particles on a 400$h^{-1}\rm{Mpc}$ cube box from the Multidark suite. In particular, we explore parametric versus non-parametric bias mapping approaches and compare them at reproducing the halo distribution in terms of the two and three point statistics down to $\sim 10^8\,{\rm M}_{\odot}\,h^{-1}$ halo masses. Our findings demonstrate that the parametric approach remains inaccurate even including complex deterministic and stochastic components. On the contrary, the non-parametric one is indistinguishable from the reference $N$-body calculation in the power-spectrum beyond $k=1\,h\,{\rm Mpc}^{-1}$, and in the bispectrum for typical configurations relevant to baryon acoustic oscillation analysis. We conclude, that approaches which extract the full bias information from $N$-body simulations in a non-parametric fashion are ready for the analysis of the new generation of large scale structure surveys.

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arXiv2019

Bayesian cosmic density field inference from redshift space dark matter maps

We present a self-consistent Bayesian formalism to sample the primordial density fields compatible with a set of dark matter density tracers after cosmic evolution observed in redshift space. Previous works on density reconstruction did not self-consistently consider redshift space distortions or included an additional iterative distortion correction step. We present here the analytic solution of coherent flows within a Hamiltonian Monte Carlo posterior sampling of the primordial density field. We test our method within the Zel'dovich approximation, presenting also an analytic solution including tidal fields and spherical collapse on small scales using augmented Lagrangian perturbation theory. Our resulting reconstructed fields are isotropic and their power spectra are unbiased compared to the true one defined by our mock observations. Novel algorithmic implementations are introduced regarding the mass assignment kernels when defining the dark matter density field and optimization of the time step in the Hamiltonian equations of motions. Our algorithm, dubbed barcode, promises to be specially suited for analysis of the dark matter cosmic web down to scales of a few Megaparsecs. This large scale structure is implied by the observed spatial distribution of galaxy clusters --- such as obtained from X-ray, SZ or weak lensing surveys --- as well as that of the intergalactic medium sampled by the Lyman alpha forest or perhaps even by deep hydrogen intensity mapping. In these cases, virialized motions are negligible, and the tracers cannot be modeled as point-like objects. It could be used in all of these contexts as a baryon acoustic oscillation reconstruction algorithm.

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arXiv2019

Comparing approximate methods for mock catalogues and covariance matrices I: correlation function

This paper is the first in a set that analyses the covariance matrices of clustering statistics obtained from several approximate methods for gravitational structure formation. We focus here on the covariance matrices of anisotropic two-point correlation function measurements. Our comparison includes seven approximate methods, which can be divided into three categories: predictive methods that follow the evolution of the linear density field deterministically (ICE-COLA, Peak Patch, and Pinocchio), methods that require a calibration with N-body simulations (Patchy and Halogen), and simpler recipes based on assumptions regarding the shape of the probability distribution function (PDF) of density fluctuations (log-normal and Gaussian density fields). We analyse the impact of using covariance estimates obtained from these approximate methods on cosmological analyses of galaxy clustering measurements, using as a reference the covariances inferred from a set of full N-body simulations. We find that all approximate methods can accurately recover the mean parameter values inferred using the N-body covariances. The obtained parameter uncertainties typically agree with the corresponding N-body results within 5% for our lower mass threshold, and 10% for our higher mass threshold. Furthermore, we find that the constraints for some methods can differ by up to 20% depending on whether the halo samples used to define the covariance matrices are defined by matching the mass, number density, or clustering amplitude of the parent N-body samples. The results of our configuration-space analysis indicate that most approximate methods provide similar results, with no single method clearly outperforming the others.

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arXiv2019

UNIT project: Universe $N$-body simulations for the Investigation of Theoretical models from galaxy surveys

We present the UNIT $N$-body cosmological simulations project, designed to provide precise predictions for nonlinear statistics of the galaxy distribution. We focus on characterizing statistics relevant to emission line and luminous red galaxies in the current and upcoming generation of galaxy surveys. We use a suite of precise particle mesh simulations (FastPM) as well as with full $N$-body calculations with a mass resolution of $\sim 1.2\times10^9\,h^{-1}$M$_{\odot}$ to investigate the recently suggested technique of Angulo & Pontzen 2016 to suppress the variance of cosmological simulations We study redshift space distortions, cosmic voids, higher order statistics from $z=2$ down to $z=0$. We find that both two- and three-point statistics are unbiased. Over the scales of interest for baryon acoustic oscillations and redshift-space distortions, we find that the variance is greatly reduced in the two-point statistics and in the cross correlation between halos and cosmic voids, but is not reduced significantly for the three-point statistics. We demonstrate that the accuracy of the two-point correlation function for a galaxy survey with effective volume of 20 ($h^{-1}$Gpc)$^3$ is improved by about a factor of 40, indicating that two pairs of simulations with a volume of 1 ($h^{-1}$Gpc)$^3$ lead to the equivalent variance of $\sim$150 such simulations. The $N$-body simulations presented here thus provide an effective survey volume of about seven times the effective survey volume of DESI or Euclid. The data from this project, including dark matter fields, halo catalogues, and their clustering statistics, are publicly available at http://www.unitsims.org.

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arXiv2019

Comparing approximate methods for mock catalogues and covariance matrices II: Power spectrum multipoles

We study the accuracy of several approximate methods for gravitational dynamics in terms of halo power spectrum multipoles and their estimated covariance matrix. We propagate the differences in covariances into parameter constrains related to growth rate of structure, Alcock-Paczynski distortions and biasing. We consider seven methods in three broad categories: algorithms that solve for halo density evolution deterministically using Lagrangian trajectories (ICE-COLA, Pinocchio and PeakPatch), methods that rely on halo assignment schemes onto dark-matter overdensities calibrated with a target N-body run (Halogen, Patchy) and two standard assumptions about the full density PDF (Gaussian and Lognormal). We benchmark their performance against a set of three hundred N-body simulations, running similar sets of approximate simulations with matched initial conditions, for each method. We find that most methods reproduce the monopole to within $5\%$, while residuals for the quadrupole are sometimes larger and scale dependent. The variance of the multipoles is typically reproduced within $10\%$. Overall, we find that covariances built from approximate simulations yield errors on model parameters within $10\%$ of those from the N-body based covariance.

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arXiv2018

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: a tomographic measurement of structure growth and expansion rate from anisotropic galaxy clustering in Fourier space

We perform a tomographic structure growth and expansion rate analysis using the monopole, quadrupole and hexadecapole of the redshift-space galaxy power spectrum derived from the Sloan Digital Sky Survey (SDSS-III) Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12 combined sample, which covers the redshift range of $0.20<z<0.75$. By allowing for overlap between neighbouring redshift slices in order to extract information on the light-cone, we successfully obtain joint BAO and RSD constraints with a precision of $2-3\%$ for $D_A$, $3-10\%$ for $H$ and $9-12\%$ for $fσ_8$ with a redshift resolution of $Δz\sim0.04$. Our measurement is consistent with that presented in arXiv:1709.05173, where the analysis is performed in configuration space. We apply our measurement to constrain the $f(R)$ gravity model, and find that the 95\% CL upper limit of ${\rm log_{10}}B_0$ can be reduced by 11\% by our tomographic BAO and RSD measurement.

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