arXiv subjects

Arka Banerjee

Publications and source records attributed to Arka Banerjee.

At least 55 records · Page 3Linked to original sources

arXiv2023

Symphony: Cosmological Zoom-in Simulation Suites over Four Decades of Host Halo Mass

We present Symphony, a compilation of $262$ cosmological, cold-dark-matter-only zoom-in simulations spanning four decades of host halo mass, from $10^{11}$$-$$10^{15}~M_{\mathrm{\odot}}$. This compilation includes three existing simulation suites at the cluster and Milky Way$-$mass scales, and two new suites: $39$ Large Magellanic Cloud-mass ($10^{11}~M_{\mathrm{\odot}}$) and $49$ strong-lens-analog ($10^{13}~M_{\mathrm{\odot}}$) group-mass hosts. Across the entire host halo mass range, the highest-resolution regions in these simulations are resolved with a dark matter particle mass of $\approx 3\times 10^{-7}$ times the host virial mass and a Plummer-equivalent gravitational softening length of $\approx 9\times 10^{-4}$ times the host virial radius, on average. We measure correlations between subhalo abundance and host concentration, formation time, and maximum subhalo mass, all of which peak at the Milky Way host halo mass scale. Subhalo abundances are $\approx 50\%$ higher in clusters than in lower-mass hosts at fixed sub-to-host halo mass ratios. Subhalo radial distributions are approximately self-similar as a function of host mass and are less concentrated than hosts' underlying dark matter distributions. We compare our results to the semianalytic model $\mathrm{\texttt{Galacticus}}$, which predicts subhalo mass functions with a higher normalization at the low-mass end and radial distributions that are slightly more concentrated than Symphony. We use $\mathrm{\texttt{UniverseMachine}}$ to model halo and subhalo star formation histories in Symphony, and we demonstrate that these predictions resolve the formation histories of the halos that host nearly all currently observable satellite galaxies in the universe. To promote open use of Symphony, data products are publicly available at http://web.stanford.edu/group/gfc/symphony.

astro-ph.CO↗

arXiv2022

Report of the Topical Group on Cosmic Probes of Dark Matter for Snowmass 2021

Cosmological and astrophysical observations currently provide the only robust, positive evidence for dark matter. Cosmic probes of dark matter, which seek to determine the fundamental properties of dark matter through observations of the cosmos, have emerged as a promising means to reveal the nature of dark matter. This report summarizes the current status and future potential of cosmic probes to inform our understanding of the fundamental nature of dark matter in the coming decade.

hep-ph↗

arXiv2022

Tracer-Field Cross-Correlations with $k$-Nearest Neighbor Distributions

In astronomy and cosmology, significant effort is devoted to characterizing and understanding spatial cross-correlations between points - e.g. galaxy positions, high energy neutrino arrival directions, X-ray and AGN sources, and continuous field - e.g. weak lensing and Cosmic Microwave Background (CMB) maps. Recently, we introduced the $k$-nearest neighbor formalism to better characterize the clustering of discrete (point) datasets. Here we extend it to the point-field cross-correlation analysis. It combines $k$NN measurements of the point data set with measurements of the field smoothed on many scales. The resulting statistics are sensitive to all orders in the joint clustering of the points and the field. We demonstrate that this approach, unlike the 2-pt cross-correlation, can measure the statistical dependence of two datasets even when there are no linear (Gaussian) correlations. We further demonstrate that this framework is far more effective than the two-point function in detecting cross-correlations when the continuous field is contaminated by high levels of noise. For a particularly high level of noise, the cross-correlations between halos and the underlying matter field in a cosmological simulation, between $10h^{-1}{\rm Mpc}$ and $30h^{-1}{\rm Mpc}$, is detected at $>5σ$ significance using the technique presented here, when the two-point cross-correlation significance is $\sim 1σ$. Finally, we show that the $k$NN cross-correlations of halos and the matter field can be well-modeled on quasilinear scales by the Hybrid Effective Field Theory (HEFT) framework, with the same set of bias parameters as are used for the two-point cross-correlations. The substantial improvement in the statistical power of detecting cross-correlations with this method makes it a promising tool for various cosmological applications.

astro-ph.CO↗

arXiv2022

Tidal disruption of solitons in self-interacting ultralight axion dark matter

Ultralight axions (ULAs) are promising dark matter candidates that can have a distinct impact on the formation and evolution of structure on nonlinear scales relative to the cold, collisionless dark matter (CDM) paradigm. However, most studies of structure formation in ULA models do not include the effects of self-interactions, which are expected to arise generically. Here, we study how the tidal evolution of solitons is affected by ULA self-interaction strength and sign. Specifically, using the pseudospectral solver UltraDark.jl, we simulate the tidal disruption of self-interacting solitonic cores as they orbit a $10^{11}~M_{\mathrm{\odot}}$ Navarro-Frenk-White CDM host halo potential for a range of orbital parameters, assuming a fiducial ULA particle mass of $10^{-22}\mathrm{eV}$. We find that repulsive (attractive) self-interactions significantly accelerate (decelerate) soliton tidal disruption. We also identify a degeneracy between the self-interaction strength and soliton mass that determines the efficiency of tidal disruption, such that disruption timescales are affected at the $\sim 50\%$ level for variations in the dimensionless ULA self-coupling from $λ=-10^{-92}$ to $λ=10^{-92}$.

astro-ph.CO↗

arXiv2022

Detection of spatial clustering in the 1000 richest SDSS DR8 redMaPPer clusters with Nearest Neighbor distributions

Distances to the $k$-nearest-neighbor ($k$NN) data points from volume-filling query points are a sensitive probe of spatial clustering. Here we present the first application of $k$NN summary statistics to observational clustering measurement, using the 1000 richest redMaPPer clusters ($0.1\leqslant z\leqslant 0.3$) from the SDSS DR8 catalog. A clustering signal is defined as a difference in the cumulative distribution functions (CDFs) of $k$NN distances from fixed query points to the observed clusters versus a set of unclustered random points. We find that the $k=1,2$-NN CDFs of redMaPPer deviate significantly from the randoms' across scales of 35 to 155 Mpc, which is a robust signature of clustering. In addition to $k$NN, we also measure the two-point correlation function for the same set of redMaPPer clusters versus random points, which shows a noisier and less significant clustering signal within the same radial scales. Quantitatively, the $χ^2$ distribution for both the $k$NN-CDFs and the two-point correlation function measured on the randoms peak at $χ^2\sim 50$ (null hypothesis), whereas the $k$NN-CDFs ($χ^2\sim 300$, $p = 1.54\times 10^{-36}$) pick up a much more significant clustering signal than the two-point function ($χ^2\sim 100$, $p = 1.16\times 10^{-6}$) when measured on redMaPPer. Finally, the measured 3NN and 4NN CDFs deviate from the predicted $k=3, 4$-NN CDFs assuming an ideal Gaussian field, indicating a non-Gaussian clustering signal for redMaPPer clusters, although its origin might not be cosmological due to observational systematics. Therefore, $k$NN serves as a more sensitive probe of clustering complementary to the two point correlation function, providing a novel approach for constraining cosmology and galaxy-halo connection.

astro-ph.CO↗

arXiv2022

Beware of Fake $ν$s: The Effect of Massive Neutrinos on the Nonlinear Evolution of Cosmic Structure

Massive neutrinos suppress the growth of cosmic structure on small, non-linear, scales. It is thus often proposed that using statistics beyond the power spectrum can tighten constraints on the neutrino mass by extracting additional information from these non-linear scales. We study the information content regarding neutrino mass at the field level, quantifying how much of this information arises from the difference in non-linear evolution between a cosmology with 1 fluid (CDM) and 2 fluids (CDM + neutrinos). We do so by running two $N$-body simulations, one with and one without massive neutrinos; both with the same phases, and matching their linear power spectrum at a given, low, redshift. This effectively isolates the information encoded in the linear initial conditions from the non-linear cosmic evolution. We demonstrate that for $k \lesssim 1\,h/{\rm Mpc}$, and for a single redshift, there is negligible difference in the real-space CDM field between the two simulations. This suggests that all the information regarding neutrino mass is in the linear power spectrum set by the initial conditions. Thus any probe based on the CDM field alone will have negligible constraining power beyond that which exists at the linear level over the same range of scales. Consequently, any probe based on the halo field will contain little information beyond the linear power. We find similar results for the matter field responsible for weak lensing. We also demonstrate that there may be much information beyond the power spectrum in the 3d matter field, however, this is not observable in modern surveys via dark matter halos or weak lensing. Finally, we show that there is additional information to be found in redshift space.

astro-ph.CO↗

arXiv2022

Snowmass2021 Cosmic Frontier White Paper: Cosmological Simulations for Dark Matter Physics

Over the past several decades, unexpected astronomical discoveries have been fueling a new wave of particle model building and are inspiring the next generation of ever-more-sophisticated simulations to reveal the nature of Dark Matter (DM). This coincides with the advent of new observing facilities coming online, including JWST, the Rubin Observatory, the Nancy Grace Roman Space Telescope, and CMB-S4. The time is now to build a novel simulation program to interpret observations so that we can identify novel signatures of DM microphysics across a large dynamic range of length scales and cosmic time. This white paper identifies the key elements that are needed for such a simulation program. We identify areas of growth on both the particle theory side as well as the simulation algorithm and implementation side, so that we can robustly simulate the cosmic evolution of DM for well-motivated models. We recommend that simulations include a fully calibrated and well-tested treatment of baryonic physics, and that outputs should connect with observations in the space of observables. We identify the tools and methods currently available to make predictions and the path forward for building more of these tools. A strong cosmic DM simulation program is key to translating cosmological observations to robust constraints on DM fundamental physics, and provides a connection to lab-based probes of DM physics.

astro-ph.CO↗

arXiv2022

Snowmass2021 Computational Frontier White Paper: Cosmological Simulations and Modeling

Powerful new observational facilities will come online over the next decade, enabling a number of discovery opportunities in the "Cosmic Frontier", which targets understanding of the physics of the early universe, dark matter and dark energy, and cosmological probes of fundamental physics, such as neutrino masses and modifications of Einstein gravity. Synergies between different experiments will be leveraged to present new classes of cosmic probes as well as to minimize systematic biases present in individual surveys. Success of this observational program requires actively pairing it with a well-matched state-of-the-art simulation and modeling effort. Next-generation cosmological modeling will increasingly focus on physically rich simulations able to model outputs of sky surveys spanning multiple wavebands. These simulations will have unprecedented resolution, volume coverage, and must deliver guaranteed high-fidelity results for individual surveys as well as for the cross-correlations across different surveys. The needed advances are as follows: (1) Development of scientifically rich and broadly-scoped simulations, which capture the relevant physics and correlations between probes (2) Accurate translation of simulation results into realistic image or spectral data to be directly compared with observations (3) Improved emulators and/or data-driven methods serving as surrogates for expensive simulations, constructed from a finite set of full-physics simulations (4) Detailed and transparent verification and validation programs for both simulations and analysis tools. (Abridged)

astro-ph.IM↗

arXiv2022

Signatures of Light Massive Relics on nonlinear structure formation

Cosmologies with Light Massive Relics (LiMRs) as a subdominant component of the dark sector are well-motivated from a particle physics perspective, and can also have implications for the $σ_8$ tension between early and late time probes of matter clustering. The effects of LiMRs on the Cosmic Microwave Background (CMB) and structure formation on large (linear) scales have been investigated extensively. In this paper, we initiate a systematic study of the effects of LiMRs on smaller, nonlinear scales using cosmological $N$-body simulations; focusing on quantities relevant for photometric galaxy surveys. For most of our study, we use a particular model of nonthermal LiMRs but the methods developed easily generalize to a large class of models of LiMRs -- we explicitly demonstrate this by considering the Dodelson-Widrow form of the velocity distribution. We find that, in general, the effects of LiMR on small scales are distinct from those of a $Λ$CDM universe, even when the value of $σ_8$ is matched between the models. We show that weak lensing measurements around massive clusters, between $\sim 0.1 h^{-1}$Mpc and $\sim 10 h^{-1}$Mpc, should have sufficient signal-to-noise in future surveys to distinguish between $Λ$CDM and LiMR models that are tuned to fit both CMB data and large (linear) scale structure data at late times. Furthermore, we find that different LiMR cosmologies which are indistinguishable by conventional linear probes can be distinguished by these probes if their velocity distributions are sufficiently different. LiMR models can, therefore, be best tested and constrained by jointly analyzing data from CMB and late-time structure formation on both large \textit{and} small scales.

astro-ph.CO↗

arXiv2022

Modeling Nearest Neighbor distributions of biased tracers using Hybrid Effective Field Theory

We investigate the application of Hybrid Effective Field Theory (HEFT) -- which combines a Lagrangian bias expansion with subsequent particle dynamics from $N$-body simulations -- to the modeling of $k$-Nearest Neighbor Cumulative Distribution Functions ($k{\rm NN}$-${\rm CDF}$s) of biased tracers of the cosmological matter field. The $k{\rm NN}$-${\rm CDF}$s are sensitive to all higher order connected $N$-point functions in the data, but are computationally cheap to compute. We develop the formalism to predict the $k{\rm NN}$-${\rm CDF}$s of discrete tracers of a continuous field from the statistics of the continuous field itself. Using this formalism, we demonstrate how $k{\rm NN}$-${\rm CDF}$ statistics of a set of biased tracers, such as halos or galaxies, of the cosmological matter field can be modeled given a set of low-redshift HEFT component fields and bias parameter values. These are the same ingredients needed to predict the two-point clustering. For a specific sample of halos, we show that both the two-point clustering \textit{and} the $k{\rm NN}$-${\rm CDF}$s can be well-fit on quasi-linear scales ($\gtrsim 20 h^{-1}{\rm Mpc}$) by the second-order HEFT formalism with the \textit{same values} of the bias parameters, implying that joint modeling of the two is possible. Finally, using a Fisher matrix analysis, we show that including $k{\rm NN}$-${\rm CDF}$ measurements over the range of allowed scales in the HEFT framework can improve the constraints on $σ_8$ by roughly a factor of $3$, compared to the case where only two-point measurements are considered. Combining the statistical power of $k{\rm NN}$ measurements with the modeling power of HEFT, therefore, represents an exciting prospect for extracting greater information from small-scale cosmological clustering.

astro-ph.CO↗

arXiv2021

Clustering in Massive Neutrino Cosmologies via Eulerian Perturbation Theory

We introduce an Eulerian Perturbation Theory to study the clustering of tracers for cosmologies in the presence of massive neutrinos. Our approach is based on mapping recently-obtained Lagrangian Perturbation Theory results to the Eulerian framework. We add Effective Field Theory counterterms, IR-resummations and a biasing scheme to compute the one-loop redshift-space power spectrum. To assess our predictions, we compare the power spectrum multipoles against synthetic halo catalogues from the Quijote simulations, finding excellent agreement on scales $k\lesssim 0.25 \,h \text{Mpc}^{-1}$. One can obtain the same fitting accuracy using higher wave-numbers, but then the theory fails to give a correct estimation of the linear bias parameter. We further discuss the implications for the tree-level bispectrum. Finally, calculating loop corrections is computationally costly, hence we derive an accurate approximation wherein we retain only the main features of the kernels, as produced by changes to the growth rate. As a result, we show how FFTLog methods can be used to further accelerate the loop computations with these reduced kernels.

astro-ph.CO↗

arXiv2021

The Effects of Dark Matter and Baryonic Physics on the Milky Way Subhalo Population in the Presence of the Large Magellanic Cloud

Given recent developments in our understanding of the Large Magellanic Cloud's (LMC) impact on the Milky Way's (MW) dark matter subhalo population, we compare the signatures of dark matter and baryonic physics on subhalos in MW systems with realistic LMC analogs. In particular, we study the effects of self-interacting dark matter (SIDM), warm dark matter (WDM), and the Galactic disk on the peak maximum circular velocity ($V_{\mathrm{peak}}$) function, radial distribution, and spatial distribution of MW and LMC-associated subhalos using cosmological dark matter-only zoom-in simulations of MW+LMC systems. For a fixed abundance of subhalos expected to host dwarf galaxies ($V_{\mathrm{peak}}\gtrsim 20\ \mathrm{km\ s}^{-1}$), SIDM and WDM can produce a similar mass-dependent suppression of the subhalo $V_{\mathrm{peak}}$ function, while disk disruption is mass independent. Subhalos in the inner regions of the MW are preferentially disrupted by both self-interactions and the disk, while suppression in WDM is radially independent. The relative abundance of LMC-associated subhalos is not strongly affected by disk disruption or WDM, but is significantly suppressed in SIDM due to self-interactions with the LMC at early times and with the MW during LMC infall at late times, erasing spatial anisotropy in the MW subhalo population. These results provide avenues to distinguish dark matter and baryonic physics by combining properties of the MW and LMC subhalo populations probed by upcoming observations of satellite galaxies and stellar streams.

astro-ph.CO↗

arXiv2021

The Quijote simulations

The Quijote simulations are a set of 44,100 full N-body simulations spanning more than 7,000 cosmological models in the $\{Ω_{\rm m}, Ω_{\rm b}, h, n_s, σ_8, M_ν, w \}$ hyperplane. At a single redshift the simulations contain more than 8.5 trillions of particles over a combined volume of 44,100 $(h^{-1}{\rm Gpc})^3$; each simulation follow the evolution of $256^3$, $512^3$ or $1024^3$ particles in a box of $1~h^{-1}{\rm Gpc}$ length. Billions of dark matter halos and cosmic voids have been identified in the simulations, whose runs required more than 35 million core hours. The Quijote simulations have been designed for two main purposes: 1) to quantify the information content on cosmological observables, and 2) to provide enough data to train machine learning algorithms. In this paper we describe the simulations and show a few of their applications. We also release the Petabyte of data generated, comprising hundreds of thousands of simulation snapshots at multiple redshifts, halo and void catalogs, together with millions of summary statistics such as power spectra, bispectra, correlation functions, marked power spectra, and estimated probability density functions.

astro-ph.CO↗

arXiv2021

The Signatures of Self-Interacting Dark Matter and Subhalo Disruption on Cluster Substructure

The abundance, distribution and inner structure of satellites of galaxy clusters can be sensitive probes of the properties of dark matter. We run 30 cosmological zoom-in simulations with self-interacting dark matter (SIDM), with a velocity-dependent cross-section, to study the properties of subhalos within cluster-mass hosts. We find that the abundance of subhalos that survive in the SIDM simulations are suppressed relative to their cold dark matter (CDM) counterparts. Once the population of disrupted subhalos -- which may host orphan galaxies -- are taken into account, satellite galaxy populations in CDM and SIDM models can be reconciled. However, even in this case, the inner structure of subhalos are significantly different in the two dark matter models. We study the feasibility of using the weak lensing signal from the subhalo density profiles to distinguish between the cold and self-interacting dark matter while accounting for the potential contribution of orphan galaxies. We find that the effects of self-interactions on the density profile of subhalos can appear degenerate with subhalo disruption in CDM, when orphans are accounted for. With current error bars from the Subaru Hyper Suprime-Cam Strategic Program, we find that subhalos in the outskirts of clusters (where disruption is less prevalent) can be used to constrain dark matter physics. In the future, the Vera C. Rubin Observatory Legacy Survey of Space and Time will give precise measurements of the weak lensing profile and can be used to constrain $σ_T/m$ at the $\sim 1$ cm$^2$ g$^{-1}$ level at $v\sim 2000$ km s$^{-1}$.

astro-ph.CO↗

arXiv2021

Nearest Neighbor distributions: new statistical measures for cosmological clustering

The use of summary statistics beyond the two-point correlation function to analyze the non-Gaussian clustering on small scales is an active field of research in cosmology. In this paper, we explore a set of new summary statistics -- the $k$-Nearest Neighbor Cumulative Distribution Functions ($k{\rm NN}$-${\rm CDF}$). This is the empirical cumulative distribution function of distances from a set of volume-filling, Poisson distributed random points to the $k$-nearest data points, and is sensitive to all connected $N$-point correlations in the data. The $k{\rm NN}$-${\rm CDF}$ can be used to measure counts in cell, void probability distributions and higher $N$-point correlation functions, all using the same formalism exploiting fast searches with spatial tree data structures. We demonstrate how it can be computed efficiently from various data sets - both discrete points, and the generalization for continuous fields. We use data from a large suite of $N$-body simulations to explore the sensitivity of this new statistic to various cosmological parameters, compared to the two-point correlation function, while using the same range of scales. We demonstrate that the use of $k{\rm NN}$-${\rm CDF}$ improves the constraints on the cosmological parameters by more than a factor of $2$ when applied to the clustering of dark matter in the range of scales between $10h^{-1}{\rm Mpc}$ and $40h^{-1}{\rm Mpc}$. We also show that relative improvement is even greater when applied on the same scales to the clustering of halos in the simulations at a fixed number density, both in real space, as well as in redshift space. Since the $k{\rm NN}$-${\rm CDF}$ are sensitive to all higher order connected correlation functions in the data, the gains over traditional two-point analyses are expected to grow as progressively smaller scales are included in the analysis of cosmological data.

astro-ph.CO↗

arXiv2021

Cosmological cross-correlations and nearest neighbor distributions

Cross-correlations between datasets are used in many different contexts in cosmological analyses. Recently, $k$-Nearest Neighbor Cumulative Distribution Functions ($k{\rm NN}$-${\rm CDF}$) were shown to be sensitive probes of cosmological (auto) clustering. In this paper, we extend the framework of nearest neighbor measurements to describe joint distributions of, and correlations between, two datasets. We describe the measurement of joint $k{\rm NN}$-${\rm CDF}$s, and show that these measurements are sensitive to all possible connected $N$-point functions that can be defined in terms of the two datasets. We describe how the cross-correlations can be isolated by combining measurements of the joint $k{\rm NN}$-${\rm CDF}$s and those measured from individual datasets. We demonstrate the application of these measurements in the context of Gaussian density fields, as well as for fully nonlinear cosmological datasets. Using a Fisher analysis, we show that measurements of the halo-matter cross-correlations, as measured through nearest neighbor measurements are more sensitive to the underlying cosmological parameters, compared to traditional two-point cross-correlation measurements over the same range of scales. Finally, we demonstrate how the nearest neighbor cross-correlations can robustly detect cross correlations between sparse samples -- the same regime where the two-point cross-correlation measurements are dominated by noise.

astro-ph.CO↗

arXiv2021

A fast particle-mesh simulation of non-linear cosmological structure formation with massive neutrinos

Quasi-N-body simulations, such as FastPM, provide a fast way to simulate cosmological structure formation, but have yet to adequately include the effects of massive neutrinos. We present a method to include neutrino particles in FastPM, enabling computation of the CDM and total matter power spectra to percent-level accuracy in the non-linear regime. The CDM-neutrino cross-power can also be computed at a sufficient accuracy to constrain cosmological observables. To avoid the shot noise that typically plagues neutrino particle simulations, we employ a quasi-random algorithm to sample the relevant Fermi-Dirac distribution when setting the initial neutrino thermal velocities. We additionally develop an effective distribution function to describe a set of non-degenerate neutrinos as a single particle to speed up non-degenerate simulations. The simulation is accurate for the full range of physical interest, $M_ν\lesssim 0.6$eV, and applicable to redshifts $z\lesssim2$. Such accuracy can be achieved by initializing particles with the two-fluid approximation transfer functions (using the REPS package). Convergence can be reached in $\sim 25$ steps, with a starting redshift of $z=99$. Probing progressively smaller scales only requires an increase in the number of CDM particles being simulated, while the number of neutrino particles can remain fixed at a value less than or similar to the number of CDM particles. In turn, the percentage increase in runtime-per-step due to neutrino particles is between $\sim 5-20\%$ for runs with $1024^3$ CDM particles, and decreases as the number of CDM particles is increased. The code has been made publicly available, providing an invaluable resource to produce fast predictions for cosmological surveys and studying reconstruction.

astro-ph.CO↗

arXiv2020

A Lagrangian Perturbation Theory in the presence of massive neutrinos

We develop a Lagrangian Perturbation Theory (LPT) framework to study the clustering of cold dark matter (CDM) in cosmologies with massive neutrinos. We follow the trajectories of CDM particles with Lagrangian displacements fields up to third order in perturbation theory. Once the neutrinos become non-relativistic, their density fluctuations are modeled as being proportional to the CDM density fluctuations, with a scale-dependent proportionality factor. This yields a gravitational back-reaction that introduces additional scales to the linear growth function, which is accounted for in the higher order LPT kernels. Through non-linear mappings from Eulerian to Lagrangian frames, we ensure that our theory has a well behaved large scale behavior free of unwanted UV divergences, which are common when neutrino and CDM densities are not treated on an equal footing, and in resummation schemes that manifestly break Galilean invariance. We use our theory to construct correlation functions for both the underlying matter field, as well as for biased tracers using Convolution-LPT. Redshift-space distortions effects are modeled using the Gaussian Streaming Model. When comparing our analytical results to simulated data from the Quijote simulation suite, we find good accuracy down to $r=20 \,\text{Mpc} \, h^{-1}$ at redshift $z=0.5$, for the real space and redshift space monopole particle correlation functions with no free parameters. The same accuracy is reached for the redshift space quadrupole if we additionally consider an effective field theory parameter that shifts the pairwise velocity dispersion. For modeling the correlation functions of tracers we adopt a simple Lagrangian biasing scheme with only density and curvature operators, which we find sufficient to reach down to $r=20 \,\text{Mpc} \, h^{-1}$ when comparing to simulated halos.

astro-ph.CO↗