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Hans A. Winther

Publications and source records attributed to Hans A. Winther.

At least 19 recordsLinked to original sources

Non-linear structure formation with elastic interactions in the dark sector

Cosmological models where dark matter interacts with dark energy via a pure momentum transfer and with no energy exchange (i.e. elastic) provide compelling scenarios for addressing the apparent lack of structures at low redshift. In particular, it has been shown that measurements of $S_8$ may show a statistically significant preference for the presence of elastic interactions. In this work we implement a specific realisation of these scenarios into an $N$-body code to explore the non-linear regime. We include two populations of particles to describe the interacting dark matter and the non-interacting baryons respectively. On linear scales we recover the suppression of structures obtained from Boltzmann codes, while non-linear scales exhibit an enhancement of the matter power. We find that fewer massive halos are formed at low redshift as a consequence of the elastic interaction and that dark matter halos are more compact than in the standard model. Furthermore, the ratio of dark matter and baryons density profiles is not constant. Finally, we corroborate that baryons efficiently cluster around dark matter halos so they provide good tracers of the dark matter velocity field despite the presence of the interaction. This shows that the interaction is not sufficiently strong as to disrupt virialised structures.

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Fast Generation of Weak Lensing Maps in Modified Gravity with COLA

Accurate predictions of weak lensing observables are essential for understanding the large-scale structure of the Universe and probing the nature of gravity. In this work, we present a lightcone implementation to generate maps of the weak lensing convergence field using the COmoving Lagrangian Acceleration (COLA) method. The lightcone is constructed in spherical shells from the source to the observer following an onion representation of the Universe. We validate the COLA-generated convergence maps in General Relativity by comparing five statistics to those of maps obtained with publically available high-resolution $N$-body simulations: the power spectrum, bispectrum, probability distribution function, peak counts and Minkowski functionals. The convergence power spectrum is accurate to within $5\%$ up to $\ell\sim500$ and to within $10\%$ up to $\ell\sim750$, confirming the accuracy of this method on both linear and non-linear scales. For the probability distribution function, peak counts and Minkowski functionals, we determine the map pixel resolution required for COLA to capture the statistical features of the $N$-body convergence maps. Our validation tests provide a baseline for the convergence map specifications at which we can trust COLA for each statistic considered. Using these map specifications, we extend our analyses to two representative theories of Modified Gravity, and demonstrate their imprints on the five convergence statistics considered. This work represents a step towards precise weak lensing predictions under both General Relativity and Modified Gravity with reduced computational cost, providing a robust framework to explore the nature of gravity using field-level inference.

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Modelling the BOSS void-galaxy cross-correlation function using a neural-network emulator

We introduce an emulator-based method to model the cross-correlation between cosmological voids and galaxies. This allows us to model the effect of cosmology on void finding and on the shape of the void-galaxy cross-correlation function, improving on previous template-based methods. We train a neural network using the AbacusSummit simulation suite and fit to data from the Sloan Digital Sky Survey Baryon Oscillation Spectroscopic Survey sample. We recover information on the growth of structure through redshift-space distortions (RSD), and the geometry of the Universe through the Alcock-Paczyński (AP) effect, measuring $Ω_{\rm m} = 0.330\pm 0.020$ and $σ_8 = 0.777^{+0.047}_{-0.062}$ for a $Λ\rm{CDM}$ cosmology. Comparing to results from a template-based method, we find that fitting the shape of the void-galaxy cross-correlation function provides more information and leads to an improvement in constraining power. In contrast, we find that errors on the AP measurements were previously underestimated if void centres were assumed to have the same response to the AP effect as galaxies - a common simplification. Overall, we recover a $28\%$ reduction in errors for $Ω_{\rm{m}}$ and similar errors on $σ_8$ with our new, more comprehensive, method. Given the statistical power of future surveys including DESI and Euclid, we expect the method presented to become the new baseline for the analysis of voids in these data.

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Emulating the Non-Linear Matter Power-Spectrum in Mixed Axion Dark Matter Models

In order to constrain ultra light dark matter models with current and near future weak lensing surveys we need the predictions for the non-linear dark matter power-spectrum. This is commonly extracted from numerical simulations or from using semi-analytical methods. For ultra light dark matter models such numerical simulations are often very expensive due to the need of having a very low force-resolution often limiting them to very small simulation boxes which do not contain very large scales. In this work we take a different approach by relying on fast, approximate $N$-body simulations. In these simulations, axion physics are only included in the initial conditions, allowing us to run a large number of simulations with varying axion and cosmological parameters. From our simulation suite we use machine learning tools to create an emulator for the ratio of the dark matter power-spectrum in mixed axion models - models where dark matter is a combination of CDM and axion - to that of $Λ$CDM. The resulting emulator only needs to be combined with existing emulators for $Λ$CDM to be able to be used in parameter constraints. We compare the emulator to semi-analytical methods, but a more thorough test to full simulations to verify the true accuracy of this approach is not possible at the present time and is left for future work.

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Interference in Fuzzy Dark Matter Filaments: Idealised Models and Statistics

Fuzzy (wave) dark matter (FDM), the dynamical model underlying an ultralight bosonic dark matter species, produces a rich set of non-gravitational signatures that distinguishes it markedly from the phenomenologically related warm (particle) dark matter (WDM) scenario. The emergence of extended interference fringes hosted by cosmic filaments is one such phenomenon reported by cosmological simulations, and a detailed understanding of such may strengthen existing limits on the boson mass but also break the degeneracy with WDM, and provide a unique fingerprint of interference in cosmology. In this paper, we provide initial steps towards this goal. In particular, we show in a bottom-up approach, how the presence of interference in an idealised filament population can lead to a non-suppressive feature in the matter power spectrum -- an observation supported by fully-cosmological FDM simulations. To this end, we build on a theoretically motivated and numerically observed steady-state approximation for filaments and express the equilibrium dynamics of such in an expansion of FDM eigenstates. We optimise the size of the expansion by incorporating classical phase-space information. Ellipsoidal collapse considerations are used to construct a fuzzy filament mass function which, together with the reconstructed FDM wave function, allow us to efficiently compute the one-filament power spectrum. We showcase our non-perturbative interference model for a selection of boson masses and confirm our approach is able to produce the matter power boost observed in fully-cosmological FDM simulations. More precisely, we find an excess in correlation between the spatial scale associated with the FDM ground state and the quantum pressure scale. We speculate about applications of this effect in data analysis.

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Modeling nonlinear scales with COLA: preparing for LSST-Y1

Year 1 results of the Legacy Survey of Space and Time (LSST) will provide tighter constraints on small-scale cosmology, beyond the validity of linear perturbation theory. This heightens the demand for a computationally affordable prescription that can accurately capture nonlinearities in beyond-$Λ$CDM models. The COmoving Lagrangian Acceleration (COLA) method, a cost-effective \textit{N}-body technique, has been proposed as a viable alternative to high-resolution \textit{N}-body simulations for training emulators of the nonlinear matter power spectrum. In this study, we evaluate this approach by employing COLA emulators to conduct a cosmic shear analysis with LSST-Y1 simulated data across three different nonlinear scale cuts. We use the $w$CDM model, for which the \textsc{EuclidEmulator2} (\textsc{ee2}) exists as a benchmark, having been trained with high-resolution \textit{N}-body simulations. We primarily utilize COLA simulations with mass resolution $M_{\rm part}\approx 8 \times 10^{10} ~h^{-1} M_{\odot}$ and force resolution $\ell_{\rm force}=0.5 ~h^{-1}$Mpc, though we also test refined settings with $M_{\rm part}\approx 1 \times 10^{10} ~h^{-1}M_{\odot}$ and force resolution $\ell_{\rm force}=0.17 ~h^{-1}$Mpc. We find the performance of the COLA emulators is sensitive to the placement of high-resolution \textit{N}-body reference samples inside the prior, which only ensure agreement in their local vicinity. However, the COLA emulators pass stringent criteria in goodness-of-fit and parameter bias throughout the prior, when $Λ$CDM predictions of \textsc{ee2} are computed alongside every COLA emulator prediction, suggesting a promising approach for extended models.

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A simple prediction of the nonlinear matter power spectrum in Brans-Dicke gravity from linear theory

Brans-Dicke (BD), one of the first proposed scalar-tensor theories of gravity, effectively makes the gravitational constant of general relativity (GR) time-dependent. Constraints on the BD parameter $ω$ serve as a benchmark for testing GR, which is recovered in the limit $ω\rightarrow \infty$. Current small-scale astrophysical constraints $ω\gtrsim 10^5$ are much tighter than large-scale cosmological constraints $ω\gtrsim 10^3$, but the two decouple if the true theory of gravity features screening. On the largest cosmological scales, BD approximates the most general second-order scalar-tensor (Horndeski) theory, so constraints here have wider implications. These constraints will improve with upcoming large-scale structure and cosmic microwave background surveys. To constrain BD with weak gravitational lensing, one needs its nonlinear matter power spectrum $P_\mathrm{BD}$. By comparing the boost $B = P_\mathrm{BD}/P_\mathrm{GR}$ from linear theory and nonlinear $N$-body simulations, we show that the nonlinear boost can simply be predicted from linear theory if the BD and GR universes are parameterized in a way that makes their early cosmological evolution and quasilinear power today similar. In particular, they need the same $H_0 / \sqrt{\smash[b]{G_{\rm eff}(a=0)}}$ and $σ_8$, where $G_{\rm eff}$ is the (effective) gravitational strength. Our prediction is $1\%$ accurate for $ω\geq 100$, $z \leq 3$, and $k \leq 1\,h/\mathrm{Mpc}$; and $2\%$ up to $k \leq 5\,h/\mathrm{Mpc}$. It also holds for $G_\mathrm{BD}$ that do not match Newton's constant today, so one can study GR with different gravitational constants $G_\mathrm{GR}$ by sending $ω\rightarrow \infty$. We provide a code that computes $B$ with the linear Einstein-Boltzmann solver hi_class and multiplies it by the nonlinear $P_\mathrm{GR}$ from EuclidEmulator2 to predict $P_\mathrm{BD}$.

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Alcock-Paczyński effect on void-finding: Implications for void-galaxy cross-correlation modelling

Under the assumption of statistical isotropy, and in the absence of directional selection effects, a stack of voids is expected to be spherically symmetric, which makes it an excellent object to use for an Alcock-Paczyński (AP) test. This is commonly done using the void-galaxy cross-correlation function (CCF), which has emerged as a competitive probe, especially in combination with the galaxy-galaxy auto correlation function. Current studies of the AP effect around voids assume that the void centre positions transform under the choice of fiducial cosmology in the same way as galaxy positions. We show that this assumption, though prevalent in the literature, is complicated by the response of void-finding algorithms to shifts in tracer positions. Using stretched simulation boxes to emulate the AP effect, we investigate how the void-galaxy CCF changes under AP, revealing an additional effect imprinted in the CCF that must be accounted for. The effect comes from the response of void finders to the distorted tracer field, reducing the amplitude of the AP signal in the CCF, and thus depends on the specific void finding algorithm used. We present results for four different void finding packages: $\texttt{revolver}$, $\texttt{vide}$, $\texttt{voxel}$, and the spherical void finder in the $\texttt{Pylians3}$ library, demonstrating how incorrect treatment of the AP effect results in biases in the recovered parameters for all of them. Finally, we propose a method to alleviate this issue without resorting to complex and finder-specific modelling of the void finder response to AP.

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Sesame: A power spectrum emulator pipeline for beyond-$Λ$CDM models

The mysterious nature of the dark sector of the $Λ$CDM model is one of the main motivators behind the study of alternative cosmological models. A central quantity of interest for these models is the matter power spectrum, which quantifies structure formation on various scales and can be cross-validated through theory, simulations, and observations. We present a tool that can be used to create emulators for the non-linear matter power spectrum, and similar global clustering statistics, for models beyond $Λ$CDM with very little computation effort and without the need for supercomputers. We use fast approximate N-body simulations to emulate the boost, $B(k,z)=P_{\text{beyond}-Λ\rm CDM}(k,z) / P_{Λ\rm CDM}(k, z)$, and then rely on existing high-quality emulators made for $Λ$CDM to isolate $P_{\text{beyond}-Λ\rm CDM}(k,z)$. Since both the $Λ$CDM and beyond-$Λ$CDM models are simulated in our approach, some of the lack of power on small scales is factored out, allowing us to extend the emulator to $k \sim 3-5\,h\,\mathrm{Mpc}^{-1}$ and still maintain good accuracy. In addition, errors from the simulation and emulation process can be estimated and factored into the covariance when using the emulator on data. As an example of using the pipeline, we create an emulator for the well-studied $f(R)$ model with massive neutrinos, using approximately 3000 CPU hours of computation time. Provided with the paper is a fully functioning pipeline that generates parameter samples, runs a Boltzmann solver to produce initial conditions, runs the simulations, and then gathers all the data and runs it through a machine learning module to develop the emulator. This tool, named Sesame, can be used by anyone to generate a power spectrum emulator for the cosmological model of their choice.

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Cosmological measurements from void-galaxy and galaxy-galaxy clustering in the Sloan Digital Sky Survey

We present the cosmological implications of measurements of void-galaxy and galaxy-galaxy clustering from the Sloan Digital Sky Survey (SDSS) Main Galaxy Sample (MGS), Baryon Oscillation Spectroscopic Survey (BOSS), and extended BOSS (eBOSS) luminous red galaxy catalogues from SDSS Data Release 7, 12, and 16, covering the redshift range $0.07 < z < 1.0$. We fit a standard $Λ$CDM cosmological model as well as various extensions including a constant dark energy equation of state not equal to $-1$, a time-varying dark energy equation of state, and these same models allowing for spatial curvature. Results on key parameters of these models are reported for void-galaxy and galaxy-galaxy clustering alone, both of these combined, and all these combined with measurements from the cosmic microwave background (CMB) and supernovae (SN). For the combination of void-galaxy and galaxy-galaxy clustering, we find tight constraints of $Ω_\mathrm{m} = 0.356\pm 0.024$ for a base $Λ$CDM cosmology, $Ω_\mathrm{m} = 0.391^{+0.028}_{-0.021}, w = -1.50^{+0.43}_{-0.28}$ additionally allowing the dark energy equation of state $w$ to vary, and $Ω_\mathrm{m} = 0.331^{+0.067}_{-0.094}, w=-1.41^{+0.70}_{-0.31},\ \mathrm{and}\ Ω_\mathrm{k} = 0.06^{+0.18}_{-0.13}$ further extending to non-flat models. The combined SDSS results from void-galaxy and galaxy-galaxy clustering in combination with CMB+SN provide a 30% improvement in parameter $Ω_\mathrm{m}$ over CMB+SN for $Λ$CDM, a 5% improvement in parameter $Ω_\mathrm{m}$ when $w$ is allowed to vary, and a 32% and 68% improvement in parameters $Ω_\mathrm{m}$ and $Ω_\mathrm{k}$ when allowing for spatial curvature.

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Revisiting Vainshtein Screening for fast N-body simulations

We revisit a method to incorporate the Vainshtein screening mechanism in N-body simulations proposed by R. Scoccimarro in~\cite{Scoccimarro:2009eu}. We further extend this method to cover a subset of Horndeski theories that evade the bound on the speed of gravitational waves set by the binary neutron star merger GW170817. The procedure consists of the computation of an effective gravitational coupling that is time and scale dependent, $G_{\rm eff}\left(k,z\right)$, where the scale dependence will incorporate the screening of the fifth-force. This is a fast procedure that when contrasted to the alternative of solving the full equation of motion for the scalar field inside N-body codes, reduces considerably the computational time and complexity required to run simulations. To test the validity of this approach in the non-linear regime, we have implemented it in a COmoving Lagrangian Approximation (COLA) N-body code, and ran simulations for two gravity models that have full N-body simulation outputs available in the literature, nDGP and Cubic Galileon. We validate the combination of the COLA method with this implementation of the Vainshtein mechanism with full N-body simulations for predicting the boost function: the ratio between the modified gravity non-linear matter power spectrum and its General Relativity counterpart. This quantity is of great importance for building emulators in beyond-$Λ$CDM models, and we find that the method described in this work has an agreement of below $2\%$ for scales down to $k \approx 3h/$Mpc with respect to full N-body simulations.

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Measurements of cosmic expansion and growth rate of structure from voids in the Sloan Digital Sky Survey between redshift 0.07 and 1.0

We present measurements of the anisotropic cross-correlation of galaxies and cosmic voids in data from the Sloan Digital Sky Survey Main Galaxy Sample (MGS), Baryon Oscillation Spectroscopic Survey (BOSS) and extended BOSS (eBOSS) luminous red galaxy catalogues from SDSS Data Releases 7, 12 and 16, covering the redshift range $0.07<z<1.0$. As in our previous work analysing voids in subsets of these data, we use a reconstruction method applied to the galaxy data before void-finding in order to remove selection biases when constructing the void samples. We report results of a joint fit to the multipole moments of the measured cross-correlation for the growth rate of structure, $fσ_8(z)$, and the ratio $D_\mathrm{M}(z)/D_\mathrm{H}(z)$ of the comoving angular diameter distance to the Hubble distance, in six redshift bins. For $D_\mathrm{M}/D_\mathrm{H}$, we are able to achieve a significantly higher precision than that obtained from analyses of the baryon acoustic oscillations (BAO) and galaxy clustering in the same datasets. Our growth rate measurements are of lower precision but still comparable with galaxy clustering results. For both quantities, the results agree well with the expectations for a $Λ$CDM model. Assuming a flat Universe, our results correspond to a measurement of the matter density parameter $Ω_\mathrm{m}=0.337^{+0.026}_{-0.029}$. For more general models the degeneracy directions obtained are consistent with and complementary to those from other cosmological probes. These results consolidate void-galaxy cross-correlation measurements as a pillar of modern observational cosmology.

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Velocity profiles of matter and biased tracers around voids

The velocity profile of galaxies around voids is a key ingredient for redshift space distortion (RSD) measurements made using the void-galaxy correlation function. In this paper we use simulations to test whether the velocity profile of the tracers used to find the voids matches the velocity profile of the dark matter around these voids. A mismatch is expected and found in the inner part of voids, where tracers are very sparse. We discuss how this difference is caused by a selection effect where the void centre positions are correlated to the particular realization of the sparse tracers and their spatial distribution. In turn, this then affects the RSD void-galaxy correlation analysis. We show this by evaluating the Jacobian of the real to redshift space mapping using the tracer or matter velocity profile. Differences of the order of 20\% in the velocity profile translate into differences of the order of few percent in the Jacobian. This small discrepancy propagates to the monopole and quadrupole of the void-tracer correlation function, producing modifications of comparable magnitude to those from changes in $fσ_8$ at the level of the statistical uncertainties from current analyses.

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Enabling matter power spectrum emulation in beyond-$Λ$CDM cosmologies with COLA

We compare and validate COLA (COmoving Lagrangian Acceleration) simulations against existing emulators in the literature, namely Bacco and Euclid Emulator 2. Our analysis focuses on the non-linear response function, i.e., the ratio between the non-linear dark matter power spectrum in a given cosmology with respect to a pre-defined reference cosmology, which is chosen to be the Euclid Emulator 2 reference cosmology in this paper. We vary three cosmological parameters, the total matter density, the amplitude of the primordial scalar perturbations and the spectral index. By comparing the COLA non-linear response function with those computed from each emulator in the redshift range $0 \leq z \leq 3$, we find that the COLA method is in excellent agreement with the two emulators for scales up to $k \sim 1 \ h$/Mpc as long as the deviations of the matter power spectrum from the reference cosmology are not too large. We validate the implementation of massive neutrinos in our COLA simulations by varying the sum of neutrino masses to three different values, $0.0$ eV, $0.058$ eV and $0.15$ eV. We show that all three non-linear prescriptions used in this work agree at the $1\%$ level at $k \leq 1 \ h$/Mpc. We then introduce the Effective Field Theory of Dark Energy in our COLA simulations using the $N$-body gauge method. We consider two different modified gravity models in which the growth of structure is enhanced or suppressed at small scales, and show that the response function with respect to the change of modified gravity parameters depends weakly on cosmological parameters in these models.

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Testing Gravity on Cosmic Scales: A Case Study of Jordan-Brans-Dicke Theory

We provide an end-to-end exploration of a distinct modified gravitational theory in Jordan-Brans-Dicke (JBD) gravity, from an analytical and numerical description of the background expansion and linear perturbations, to the nonlinear regime captured with a hybrid suite of $N$-body simulations, to the parameter constraints from existing cosmological probes. The nonlinear corrections to the matter power spectrum due to baryons, massive neutrinos, and modified gravity are simultaneously modeled and propagated in the cosmological analysis for the first time. In the combined analysis of the Planck CMB temperature, polarization, and lensing reconstruction, Pantheon supernova distances, BOSS measurements of BAO distances, the Alcock-Paczynski effect, and the growth rate, along with the joint ($3\times2$pt) dataset of cosmic shear, galaxy-galaxy lensing, and overlapping redshift-space galaxy clustering from KiDS and 2dFLenS, we constrain the JBD coupling constant, $ω_{\rm BD}>1540$ (95% CL), the effective gravitational constant, $G_{\rm matter}/G=0.997\pm0.029$, the sum of neutrino masses, $\sum m_ν<0.12$ eV (95% CL), and the baryonic feedback amplitude, $B<2.8$ (95% CL), all in agreement with the standard model expectation. We show that the uncertainty in the gravitational theory alleviates the tension between KiDS$\times$2dFLenS and Planck to below $1σ$ and the tension in the Hubble constant between Planck and the direct measurement of Riess et al. (2019) down to ~$3σ$; however, we find no substantial model selection preference for JBD gravity relative to $Λ$CDM. We further show that the neutrino mass bound degrades by up to a factor of three as the $ω_{\rm BD}$ parameterization becomes more restrictive and that a positive shift in $G_{\rm matter}/G$ suppresses the CMB damping tail in a way that might complicate future inferences of small-scale physics. (Abridged)

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Testing the theory of gravity with DESI: estimators, predictions and simulation requirements

Shortly after its discovery, General Relativity (GR) was applied to predict the behavior of our Universe on the largest scales, and later became the foundation of modern cosmology. Its validity has been verified on a range of scales and environments from the Solar system to merging black holes. However, experimental confirmations of GR on cosmological scales have so far lacked the accuracy one would hope for -- its applications on those scales being largely based on extrapolation and its validity sometimes questioned in the shadow of the unexpected cosmic acceleration. Future astronomical instruments surveying the distribution and evolution of galaxies over substantial portions of the observable Universe, such as the Dark Energy Spectroscopic Instrument (DESI), will be able to measure the fingerprints of gravity and their statistical power will allow strong constraints on alternatives to GR. In this paper, based on a set of $N$-body simulations and mock galaxy catalogs, we study the predictions of a number of traditional and novel estimators beyond linear redshift distortions in two well-studied modified gravity models, chameleon $f(R)$ gravity and a braneworld model, and the potential of testing these deviations from GR using DESI. These estimators employ a wide array of statistical properties of the galaxy and the underlying dark matter field, including two-point and higher-order statistics, environmental dependence, redshift space distortions and weak lensing. We find that they hold promising power for testing GR to unprecedented precision. The major future challenge is to make realistic, simulation-based mock galaxy catalogs for both GR and alternative models to fully exploit the statistic power of the DESI survey and to better understand the impact of key systematic effects. Using these, we identify future simulation and analysis needs for gravity tests using DESI.

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Fast generation of mock galaxy catalogues in modified gravity models with COLA

We investigate the viability of producing galaxy mock catalogues with COmoving Lagrangian Acceleration (COLA) simulations in Modified Gravity (MG) models employing the Halo Occupation Distribution (HOD) formalism. In this work, we focus on two theories of MG: $f(R)$ gravity with the chameleon mechanism, and a braneworld model (nDGP) that incorporates the Vainshtein mechanism. We use a suite of full $N$-body simulations in MG as a benchmark to test the accuracy of COLA simulations. At the level of Dark Matter (DM), we show that COLA accurately reproduces the matter power spectrum up to $k \sim 1 h {\rm Mpc}^{-1}$, while it is less accurate in reproducing the velocity field. To produce halo catalogues, we find that the ROCKSTAR halo-finder does not perform well with COLA simulations. On the other hand, using a simple Friends-of-Friends (FoF) finder and an empirical mass conversion from FoF to spherical over-density masses, we are able to produce halo catalogues in COLA that are in good agreement with those in $N$-body simulations. To consider the effects of the MG fifth force on the halo profile, we derive simple fitting formulae for the concentration-mass and the velocity dispersion-mass relations that we calibrate using ROCKSTAR halo catalogues in $N$-body simulations. We then use these results to extend the HOD formalism to modified gravity simulations in COLA. We use an HOD model with five parameters that we tune to obtain galaxy catalogues in redshift space. We find that despite the great freedom of the HOD model, MG leaves characteristic imprints in the redshift space power spectrum multipoles and these features are well captured by the COLA galaxy catalogues.

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Investigating Cosmological GAN Emulators Using Latent Space Interpolation

Generative adversarial networks (GANs) have been recently applied as a novel emulation technique for large scale structure simulations. Recent results show that GANs can be used as a fast, efficient and computationally cheap emulator for producing novel weak lensing convergence maps as well as cosmic web data in 2-D and 3-D. However, like any algorithm, the GAN approach comes with a set of limitations, such as an unstable training procedure and the inherent randomness of the produced outputs. In this work we employ a number of techniques commonly used in the machine learning literature to address the mentioned limitations. In particular, we train a GAN to produce both weak lensing convergence maps and dark matter overdensity field data for multiple redshifts, cosmological parameters and modified gravity models. In addition, we train a GAN using the newest Illustris data to emulate dark matter, gas and internal energy distribution data simultaneously. Finally, we apply the technique of latent space interpolation to control which outputs the algorithm produces. Our results indicate a 1-20% difference between the power spectra of the GAN-produced and the training data samples depending on the dataset used and whether Gaussian smoothing was applied. Finally, recent research on generative models suggests that such algorithms can be treated as mappings from a lower-dimensional input (latent) space to a higher dimensional (data) manifold. We explore such a theoretical description as a tool for better understanding the latent space interpolation procedure.

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