arXiv subjects

Jens Jasche

Publications and source records attributed to Jens Jasche.

At least 37 records · Page 2Linked to original sources

arXiv2024

Bayesian Inference of Initial Conditions from Non-Linear Cosmic Structures using Field-Level Emulators

Analysing next-generation cosmological data requires balancing accurate modeling of non-linear gravitational structure formation and computational demands. We propose a solution by introducing a machine learning-based field-level emulator, within the Hamiltonian Monte Carlo-based Bayesian Origin Reconstruction from Galaxies (BORG) inference algorithm. Built on a V-net neural network architecture, the emulator enhances the predictions by first-order Lagrangian perturbation theory to be accurately aligned with full $N$-body simulations while significantly reducing evaluation time. We test its incorporation in BORG for sampling cosmic initial conditions using mock data based on non-linear large-scale structures from $N$-body simulations and Gaussian noise. The method efficiently and accurately explores the high-dimensional parameter space of initial conditions, fully extracting the cross-correlation information of the data field binned at a resolution of $1.95h^{-1}$ Mpc. Percent-level agreement with the ground truth in the power spectrum and bispectrum is achieved up to the Nyquist frequency $k_\mathrm{N} \approx 2.79h \; \mathrm{Mpc}^{-1}$. Posterior resimulations - using the inferred initial conditions for $N$-body simulations - show that the recovery of information in the initial conditions is sufficient to accurately reproduce halo properties. In particular, we show highly accurate $M_{200\mathrm{c}}$ halo mass function and stacked density profiles of haloes in different mass bins $[0.853,16]\times 10^{14}M_{\odot}h^{-1}$. As all available cross-correlation information is extracted, we acknowledge that limitations in recovering the initial conditions stem from the noise level and data grid resolution. This is promising as it underscores the significance of accurate non-linear modeling, indicating the potential for extracting additional information at smaller scales.

astro-ph.CO↗

arXiv2024

$\texttt{PineTree}$: A generative, fast, and differentiable halo model for wide-field galaxy surveys

Mock halo catalogues are indispensable data products for developing and validating cosmological inference pipelines. A major challenge in generating mock catalogues is modelling the halo or galaxy bias, which is the mapping from matter density to dark matter halos or observable galaxies. To this end, N-body codes produce state-of-the-art catalogues. However, generating large numbers of these N-body simulations for big volumes, requires significant computational time. We introduce and benchmark a differentiable and physics-informed neural network that can generate mock halo catalogues of comparable quality to those obtained from full N-body codes. The model design is computationally efficient for the training procedure and the production of large mock suites. We present a neural network, relying only on 18 to 34 trainable parameters, that produces halo catalogues from dark matter overdensity fields. The reduction of network weights is realised through incorporating symmetries motivated by first principles into our model architecture. We train our model using dark matter only N-body simulations across different resolutions, redshifts, and mass bins. We validate the final mock catalogues by comparing them to N-body halo catalogues using different N-point correlation functions. Our model produces mock halo catalogues consistent with the reference simulations, showing that this novel network is a promising way to generate mock data for upcoming wide-field surveys due to its computational efficiency. Moreover, we find that the network can be trained on approximate overdensity fields to reduce the computational cost further. We also present how the trained network parameters can be interpreted to give insights into the physics of structure formation. Finally, we discuss the current limitations of our model as well as more general requirements and pitfalls for approximate halo mock generation.

astro-ph.CO↗

arXiv2024

Constrained cosmological simulations of the Local Group using Bayesian hierarchical field-level inference

We present a novel approach based on Bayesian field-level inference capable of resolving individual galaxies within the Local Group (LG), enabling detailed studies of its structure and formation via posterior simulations. We extend the Bayesian Origin Reconstruction from Galaxies (BORG) algorithm with a multi-resolution approach, allowing us to reach smaller mass scales and apply observational constraints based on LG galaxies. Our updated data model simultaneously accounts for observations of mass tracers within the dark haloes of the Milky Way (MW) and M31, their observed separation and relative velocity, and the quiet surrounding Hubble flow represented through the positions and velocities of galaxies at distances from one to four Mpc. Our approach delivers representative posterior samples of $Λ$CDM realisations that are statistically and simultaneously consistent with all these observations, leading to significantly tighter mass constraints than found if the individual datasets are considered separately. In particular, we estimate the virial masses of the MW and M31 to be $\log_{10}(M_{200c}/M_\odot) = 12.07\pm0.08$ and $12.33\pm0.10$, respectively, their sum to be $\log_{10}(ΣM_{200c}/M_\odot)= 12.52\pm0.07$, and the enclosed mass within spheres of radius $R$ to be $\log_{10}(M(R)/M_\odot)= 12.71\pm0.06$ and $12.96\pm0.08$ for $R=1$ Mpc and 3 Mpc, respectively. The M31-MW orbit is nearly radial for most of our $Λ$CDM LG's, and most lie in a dark matter sheet that aligns approximately with the Supergalactic Plane, even though the surrounding density field was not used explicitly as a constraint. The approximate simulations employed in our inference are accurately reproduced by high-fidelity structure formation simulations, demonstrating the potential for future high-resolution, full-physics $Λ$CDM posterior simulations of LG look-alikes.

astro-ph.GA↗

arXiv2024

An Anti-halo Void Catalogue of the Local Super-Volume

We construct an anti-halo void catalogue of $150$ voids with radii $R > 10\,h^{-1}\mathrm{\,Mpc}$ in the Local Super-Volume ($<135\,h^{-1}\mathrm{\,Mpc}$ from the Milky Way), using posterior resimulation of initial conditions inferred by field-level inference with Bayesian Origin Reconstruction from Galaxies (\codefont{BORG}). We describe and make use of a new algorithm for creating a single, unified void catalogue by combining different samples from the posterior. The catalogue is complete out to $135\,h^{-1}\mathrm{\,Mpc}$, with void abundances matching theoretical predictions. Finally, we compute stacked density profiles of those voids which are reliably identified across posterior samples, and show that these are compatible with $Λ$CDM expectations once environmental selection (e.g., the estimated $\sim 4\%$ under-density of the Local Super-Volume) is accounted for.

astro-ph.CO↗

arXiv2024

Towards Accurate Field-Level Inference of Massive Cosmic Structures

We investigate the accuracy requirements for field-level inference of cluster and void masses using data from galaxy surveys. We introduce a two-step framework that takes advantage of the fact that cluster masses are determined by flows on larger scales than the clusters themselves. First, we determine the integration accuracy required to perform field-level inference of cosmic initial conditions on these large scales, by fitting to late-time galaxy counts using the Bayesian Origin Reconstruction from Galaxies (BORG) algorithm. A 20-step COLA integrator is able to accurately describe the density field surrounding the most massive clusters in the Local Super-Volume ($<135\,h^{-1}\,\mathrm{Mpc}$), but does not by itself lead to converged virial mass estimates. Therefore we carry out `posterior resimulations', using full $N$-body dynamics while sampling from the inferred initial conditions, and thereby obtain estimates of masses for nearby massive clusters. We show that these are in broad agreement with existing estimates, and find that mass functions in the Local Super-Volume are compatible with $Λ$CDM.

astro-ph.CO↗

arXiv2023

Where shadows lie: reconstruction of anisotropies in the neutrino sky

The Cosmic Neutrino Background (CNB) encodes a wealth of information, but has not yet been observed directly. To determine the prospects of detection and to study its information content, we reconstruct the phase-space distribution of local relic neutrinos from the three-dimensional distribution of matter within 200 Mpc/h of the Milky Way. Our analysis relies on constrained realization simulations and forward modelling of the 2M++ galaxy catalogue. We find that the angular distribution of neutrinos is anti-correlated with the projected matter density, due to the capture and deflection of neutrinos by massive structures along the line of sight. Of relevance to tritium capture experiments, we find that the gravitational clustering effect of the large-scale structure on the local number density of neutrinos is more important than that of the Milky Way for neutrino masses less than 0.1 eV. Nevertheless, we predict that the density of relic neutrinos is close to the cosmic average, with a suppression or enhancement over the mean of (-0.3%, +7%, +27%) for masses of (0.01, 0.05, 0.1) eV. This implies no more than a marginal increase in the event rate for tritium capture experiments like PTOLEMY. We also predict that the CNB and CMB rest frames coincide for 0.01 eV neutrinos, but that neutrino velocities are significantly perturbed for masses larger than 0.05 eV. Regardless of mass, we find that the angle between the neutrino dipole and the ecliptic plane is small, implying a near-maximal annual modulation in the bulk velocity. Along with this paper, we publicly release our simulation data, comprising more than 100 simulations for six different neutrino masses.

astro-ph.CO↗

arXiv2023

Distinct distributions of elliptical and disk galaxies across the Local Supercluster as a $Λ$CDM prediction

Galaxies of different types are not equally distributed in the Local Universe. In particular, the supergalactic plane is prominent among the brightest ellipticals, but inconspicuous among the brightest disk galaxies. This striking difference provides a unique test for our understanding of galaxy and structure formation. Here we use the SIBELIUS DARK constrained simulation to confront the predictions of the standard Lambda Cold Dark Matter ($Λ$CDM) model and standard galaxy formation theory with these observations. We find that SIBELIUS DARK reproduces the spatial distributions of disks and ellipticals and, in particular, the observed excess of massive ellipticals near the supergalactic equator. We show that this follows directly from the local large-scale structure and from the standard galaxy formation paradigm, wherein disk galaxies evolve mostly in isolation, while giant ellipticals congregate in the massive clusters that define the supergalactic plane. Rather than being anomalous as earlier works have suggested, the distributions of giant ellipticals and disks in the Local Universe and in relation to the supergalactic plane are key predictions of the $Λ$CDM model.

astro-ph.GA↗

arXiv2023

Higher-order statistics of the large-scale structure from photometric redshifts

The large-scale structure is a major source of cosmological information. However, next-generation photometric galaxy surveys will only provide a distorted view of cosmic structures due to large redshift uncertainties. To address the need for accurate reconstructions of the large-scale structure in presence of photometric uncertainties, we present a framework that constrains the three-dimensional dark matter density jointly with galaxy photometric redshift probability density functions (PDFs), exploiting information from galaxy clustering. Our forward model provides Markov Chain Monte Carlo realizations of the primordial and present-day dark matter density, inferred jointly from data. Our method goes beyond 2-point statistics via field-level inference. It accounts for all observational uncertainties and the survey geometry. We showcase our method using mock catalogs that emulate next-generation surveys with a worst-case redshift uncertainty, equivalent to ${\sim}300$ Mpc. On scales $150$ Mpc, we improve the cross-correlation of the photometric galaxy positions with the ground truth from $28\%$ to $86\%$. The improvement is significant down to $13$ Mpc. On scales $150$ Mpc, we achieve a cross-correlation of $80-90\%$ with the ground truth for the dark matter density, radial peculiar velocities, tidal shear and gravitational potential.

astro-ph.CO↗

arXiv2022

Field-Based Physical Inference From Peculiar Velocity Tracers

We present a Bayesian hierarchical modelling approach to reconstruct the initial cosmic matter density field constrained by peculiar velocity observations. As our approach features a model for the gravitational evolution of dark matter to connect the initial conditions to late-time observations, it reconstructs the final density and velocity fields as natural byproducts. We implement this field-based physical inference approach by adapting the Bayesian Origin Reconstruction from Galaxies (BORG) algorithm, which explores the high-dimensional posterior through the use of Hamiltonian Monte Carlo sampling. We test the self-consistency of the method using random sets of mock tracers, and assess its accuracy in a more complex scenario where peculiar velocity tracers are non-linearly evolved mock haloes. We find that our framework self-consistently infers the initial conditions, density and velocity fields, and shows some robustness to model mis-specification. As compared to the state-of-the-art approach of constrained Gaussian random fields/Wiener filtering, our method produces more accurate final density and velocity field reconstructions. It also allows us to constrain the initial conditions by peculiar velocity observations, complementing in this aspect previous field-based approaches based on other cosmological observables.

astro-ph.CO↗

arXiv2022

Constraints on dark matter annihilation and decay from the large-scale structure of the nearby universe

Decaying or annihilating dark matter particles could be detected through gamma-ray emission from the species they decay or annihilate into. This is usually done by modelling the flux from specific dark matter-rich objects such as the Milky Way halo, Local Group dwarfs, and nearby groups. However, these objects are expected to have significant emission from baryonic processes as well, and the analyses discard gamma-ray data over most of the sky. Here we construct full-sky templates for gamma-ray flux from the large-scale structure within $\sim$200 Mpc by means of a suite of constrained $N$-body simulations (CSiBORG) produced using the Bayesian Origin Reconstruction from Galaxies algorithm. Marginalising over uncertainties in this reconstruction, small-scale structure, and parameters describing astrophysical contributions to the observed gamma-ray sky, we compare to observations from the Fermi Large Area Telescope to constrain dark matter annihilation cross sections and decay rates through a Markov Chain Monte Carlo analysis. We rule out the thermal relic cross section for $s$-wave annihilation for all $m_χ\lesssim 7 {\rm \, GeV}/c^2$ at 95\% confidence if the annihilation produces gluons or quarks less massive than the bottom quark. We infer a contribution to the gamma-ray sky with the same spatial distribution as dark matter decay at $3.3σ$. Although this could be due to dark matter decay via these channels with a decay rate $Γ\approx 6 \times 10^{-28} {\rm \, s^{-1}}$, we find that a power-law spectrum of index $p=-2.75^{+0.71}_{-0.46}$, likely of baryonic origin, is preferred by the data.

astro-ph.CO↗

arXiv2022

Rubin-Euclid Derived Data Products: Initial Recommendations

This report is the result of a joint discussion between the Rubin and Euclid scientific communities. The work presented in this report was focused on designing and recommending an initial set of Derived Data products (DDPs) that could realize the science goals enabled by joint processing. All interested Rubin and Euclid data rights holders were invited to contribute via an online discussion forum and a series of virtual meetings. Strong interest in enhancing science with joint DDPs emerged from across a wide range of astrophysical domains: Solar System, the Galaxy, the Local Volume, from the nearby to the primaeval Universe, and cosmology.

astro-ph.IM↗

arXiv2022

Field-level inference of galaxy intrinsic alignment from the SDSS-III BOSS survey

As a large-scale overdensity collapses, it affects the orientation and shape of galaxies that form, by exerting tidal shear along their axes. Therefore, the shapes of elliptical galaxies align with the tidal field of cosmic structures. This intrinsic alignment provides insights into galaxy formation and the primordial universe, complements late-time cosmological probes and constitutes a significant systematic effect for weak gravitational lensing observations. In the present study, we provide constraints on the linear alignment model using a fully Bayesian field-level approach, using galaxy shape measurements from the SDSS-III BOSS LOWZ sample and three-dimensional tidal fields constrained with the LOWZ and CMASS galaxy samples of the SDSS-III BOSS survey. We find 4$σ$ evidence of intrinsic alignment, with an amplitude of $A_I=2.9 \pm 0.7$ at 20$h^{-1}\;\mathrm{Mpc}$.

astro-ph.CO↗

arXiv2022

The Milky Way's plane of satellites: consistent with $Λ$CDM

The "plane of satellites problem" describes the arrangement of the Milky Way's 11 brightest satellite galaxies in a remarkably thin plane, possibly supported by rotation. This is in apparent contradiction to the standard cosmological model, wherein the Galaxy is surrounded by a dispersion-supported dark matter halo. Here, we show that the reported exceptional anisotropy of the satellite system is strongly contingent on a lopsided radial distribution, which earlier simulations have failed to reproduce, combined with the close but fleeting conjunction of the two most distant satellites, Leo I and Leo II. Using Gaia proper motions, we show that the orbital pole alignment is much more common than previously reported, and reveal the plane of satellites to be transient rather than rotationally supported. Comparing to new simulations, where such short-lived planes are common, we find the Milky Way satellites to be compatible with standard model expectations.

astro-ph.GA↗

arXiv2022

Bayesian field-level inference of primordial non-Gaussianity using next-generation galaxy surveys

Detecting and measuring a non-Gaussian signature of primordial origin in the density field is a major science goal of next-generation galaxy surveys. The signal will permit us to determine primordial physics processes and constrain models of cosmic inflation. While traditional approaches utilise a limited set of statistical summaries of the galaxy distribution to constrain primordial non-Gaussianity, we present a field-level approach by Bayesian forward-modelling the entire three-dimensional galaxy survey. Our method naturally and fully self-consistently exploits the entirety of the large-scale structure, e.g., higher-order statistics, peculiar velocity fields, and scale-dependent galaxy bias, to extract information on the local non-Gaussianity parameter, $\fnl$. We demonstrate the performance of our approach through various tests with mock galaxy data emulating relevant features of the \sdssiii{}-like survey, and additional tests with a \textit{Stage IV} mock data set. These tests reveal that the method infers unbiased values of $\fnl$ by accurately handling survey geometries, noise, and unknown galaxy biases. We demonstrate that our method can achieve constraints of $σ_{\fnl} \approx 8.78$ for \sdssiii{}-like data, an improvement of a factor $\sim 2.5$ over currently published constraints. Tests with next-generation mock data show that significant further improvements are feasible with sufficiently high resolution. Furthermore, the results demonstrate that our method can consistently marginalise all nuisance parameters of the data model. The method further provides an inference of the three-dimensional primordial density field, providing opportunities to explore additional signatures of primordial physics.

astro-ph.CO↗

arXiv2022

SIBELIUS-DARK: a galaxy catalogue of the Local Volume from a constrained realisation simulation

We present SIBELIUS-DARK, a constrained realisation simulation of the local volume to a distance of 200~Mpc from the Milky Way. SIBELIUS-DARK is the first study of the \textit{Simulations Beyond The Local Universe} (SIBELIUS) project, which has the goal of embedding a model Local Group-like system within the correct cosmic environment. The simulation is dark-matter-only, with the galaxy population calculated using the semi-analytic model of galaxy formation, GALFORM. We demonstrate that the large-scale structure that emerges from the SIBELIUS constrained initial conditions matches well the observational data. The inferred galaxy population of SIBELIUS-DARK also match well the observational data, both statistically for the whole volume and on an object-by-object basis for the most massive clusters. For example, the $K$-band number counts across the whole sky, and when divided between the northern and southern Galactic hemispheres, are well reproduced by SIBELIUS-DARK. We find that the local volume is somewhat unusual in the wider context of $Λ$CDM: it contains an abnormally high number of supermassive clusters, as well as an overall large-scale underdensity at the level of $\approx 5$\% relative to the cosmic mean. However, whilst rare, the extent of these peculiarities does not significantly challenge the $Λ$CDM model. SIBELIUS-DARK is the most comprehensive constrained realisation simulation of the local volume to date, and with this paper we publicly release the halo and galaxy catalogues at $z=0$, which we hope will be useful to the wider astronomy community.

astro-ph.GA↗

arXiv2021

Optimal machine-driven acquisition of future cosmological data

We present maps classifying regions of the sky according to their information gain potential as quantified by the Fisher information. These maps can guide the optimal retrieval of relevant physical information with targeted cosmological searches. Specifically, we calculate the response of observed cosmic structures to perturbative changes in the cosmological model and chart their respective contributions to the Fisher information. Our physical forward modeling machinery transcends the limitations of contemporary analyses based on statistical summaries to yield detailed characterizations of individual 3D structures. We demonstrate this using galaxy counts data and showcase the potential of our approach by studying the information gain of the Coma cluster. We find that regions in the vicinity of the filaments and cluster core, where mass accretion ensues from gravitational infall, are the most informative about our physical model of structure formation in the Universe. Hence, collecting data in those regions would be most optimal for testing our model predictions. The results presented in this work are the first of their kind and elucidate the inhomogeneous distribution of cosmological information in the Universe. This study paves a new way forward to perform efficient targeted searches for the fundamental physics of the Universe, where search strategies are progressively refined with new cosmological data sets within an active learning framework.

astro-ph.CO↗

arXiv2021

The large-scale environment of thermonuclear and core-collapse supernovae

The new generation of wide-field time-domain surveys has made it feasible to study the clustering of supernova (SN) host galaxies in the large-scale structure (LSS) for the first time. We investigate the LSS environment of SN populations, using 106 dark matter density realisations with a resolution of $\sim$ 3.8 Mpc, constrained by the 2M++ galaxy survey. We limit our analysis to redshift $z<0.036$, using samples of 498 thermonuclear and 782 core-collapse SNe from the Zwicky Transient Facility's Bright Transient Survey and Census of the Local Universe catalogues. We detect clustering of SNe with high significance; the observed clustering of the two SNe populations is consistent with each other. Further, the clustering of SN hosts is consistent with that of the Sloan Digital Sky Survey (SDSS) Baryon Oscillation Spectroscopic Survey (BOSS) DR12 spectroscopic galaxy sample in the same redshift range. Using a tidal shear classifier, we classify the LSS into voids, sheets, filaments and knots. We find that both SNe and SDSS galaxies are predominantly found in sheets and filaments. SNe are significantly under-represented in voids and over-represented in knots compared to the volume fraction in these structures. This work opens the potential for using forthcoming wide-field deep SN surveys as a complementary LSS probe.

astro-ph.CO↗

arXiv2021

Constraints on quantum gravity and the photon mass from gamma ray bursts

Lorentz invariance violation in quantum gravity (QG) models or a nonzero photon mass, $m_γ$, would lead to an energy-dependent propagation speed for photons, such that photons of different energies from a distant source would arrive at different times, even if they were emitted simultaneously. By developing source-by-source, Monte Carlo-based forward models for such time delays from gamma ray bursts, and marginalising over empirical noise models describing other contributions to the time delay, we derive constraints on $m_γ$ and the QG length scale, $\ell_{\rm QG}$, using spectral lag data from the BATSE satellite. We find $m_γ< 4.0 \times 10^{-5} \, h \, {\rm eV}/c^2$ and $\ell_{\rm QG} < 5.3 \times 10^{-18} \, h \, {\rm \, GeV^{-1}}$ at 95% confidence, and demonstrate that these constraints are robust to the choice of noise model. The QG constraint is among the tightest from studies which consider multiple gamma ray bursts and the constraint on $m_γ$, although weaker than from using radio data, provides an independent constraint which is less sensitive to the effects of dispersion by electrons.

gr-qc↗