arXiv subjects

Martin Reinecke

Publications and source records attributed to Martin Reinecke.

At least 19 recordsLinked to original sources

arXiv2026

Application of Bayesian Statistical Tools to SKA Telescopes Polarization Surveys to Study Magnetization of the Large-scale Structure of the Universe

Understanding cosmological magnetic fields requires a detailed knowledge of magnetism in the different environments of the large-scale structure of the Universe. Magnetic fields are well known to inhabit galaxy clusters, and recently their presence has been detected between galaxy clusters, along filaments extending up to 10-15 Mpc. Beyond that, there is limited information on the existence of magnetic fields in sheets and voids of the cosmic web. We propose a Bayesian statistical approach to study magnetic fields on large scales through observations of the Faraday rotation effect in large samples of polarized point-like background radio sources. We present the expectations to detect magnetization in environments of the large-scale structure with the SKA-Mid polarization survey planned by the SKAO Magnetism Science Working Group and with SKA-Low with AA4 telescopes, and discuss the required level of accuracy on the redshifts of the host galaxies for such a study. We find that about 50,000 mid-frequency Faraday rotation measurements complemented by high-precision redshifts are needed to constrain magnetization of dense environments as galaxy clusters. Investigation of magnetization in weakly-magnetized low-density enviroments, as filaments, will remain challenging, but low frequencies radio observations and spectroscopic redhifts for at least 17,000 will allow us to put first constraints.

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arXiv2026

Prime Focus Spectrograph on the Subaru Telescope: Overview of Science Operations

The paper presents the science operation framework for Prime Focus Spectrograph (PFS or 'Onohi'ula in its Hawaiian name) installed at the 8.2m Subaru Telescope on the summit of Maunakea. PFS is a massively multiplexed, wide-field, fiber-fed spectrograph covering 1.25 square degrees with 2386 science fibers. The instrument has been offered to the Subaru scientific community since March 2025. In order to fully exploit the unique capabilities of PFS, the Subaru Telescope has introduced a new, dedicated science operation framework for PFS. The default observing mode is queue observing, and multiple observing programs (in the same field) can be executed in the same exposure to achieve high observing efficiency. The quality of an exposure is based on the delivered signal-to-noise ratio and is quantified in terms of 'effective exposure time', and exposures are taken until the allocated 'fiber hours' for each program or target are achieved. The fiber hour is a new unit for observing time at Subaru; if we expose a fiber for 1 hour under the fiducial conditions, it is 1 fiber hour. Each observing program is granted the total fiber hours by the Time Allocation Committee. In addition to normal observing programs, which are selected through the standard peer-review process, there are two filler categories; community filler and observatory filler. As the names imply, the former is proposed by the community and the latter is prepared by the observatory. These filler targets are used whenever unassigned fibers are available. After an observing run, the data are fully reduced by the observatory and delivered to the users through the PFS Science Platform, a cloud-based data analysis environment. The paper gives a summary of all of this new framework and the actual implementation of it.

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arXiv2026

Fast partial-sky spherical harmonic transforms

We discuss in some details a novel algorithm for performing partial-sky spherical harmonic transforms (SHT), building on the Fourier-sphere method of Reinecke et al (2023) handling efficiently high numbers of arbitrary locations on the sphere. Our main motivations are Cosmic Microwave Background lensing from the South Pole Telescope, and the South Pole Observatory program targeting primordial gravitational waves from inflation, requiring high-resolution, numerically intensive work on small sky fractions. We achieve speed-up factors ranging from 3 to 10 on SPT-3G main field and BICEP3 deep footprint, and much more on smaller patches. More generally, the algorithm eliminates in our case study the usual disadvantages of arbitrary pixelisations in comparison to isolatitude pixelisations or flat-sky approximations, making it ideal for ambitious workflows that require repeated SHTs on limited sky regions.

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arXiv2025

FuGa3D: Fast full-sky analysis of Galaxy catalogs in 3D

We present FuGa3D, a code for fast computation of correlation functions and power spectra for galaxy survey observables, including galaxy clustering and cosmic shear. We define the redshift-space correlation function (RCF) as the correlation function defined in the parameter space of two redshifts and an angular separation angle. Assuming that there is no preferred direction in the sky, these parameters fully define the relative position of two galaxies, independently of the assumed cosmological model. Once the RCF is constructed, it is easy to compute derived correlation metrics, such as the real-space clustering correlation function and its multipoles. We further define the redshift-space power spectrum as the harmonic counterpart of the RCF, and show that it can be computed efficiently using the discrete galaxy coordinates. We validate the code with simulated mock catalogs. Computing the RCF and the two-point correlation function at 1.5 Mpc (3 Mpc) resolution for a MICE simulation with 46 million galaxies, took 47 node-min for clustering only, and 7.3 node-hours with shear analysis included.

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arXiv2025

Bayesian Imaging of Interferometric Data from Polarized Electromagnetic Signals

We present an imaging algorithm for polarimetric interferometric data from radio telescopes. It is based on Bayesian statistics and thereby able to provide uncertainties and to incorporate prior information such as positivity of the total emission (Stokes I) or consistency constraints (polarized fraction can only be between 0% and 100%). By comparing our results to the output of the de-facto standard algorithm called CLEAN, we show that these constraints paired with a consistent treatment of measurement uncertainties throughout the algorithm significantly improve image quality. In particular, our method reveals that depolarization canals in CLEAN images do not necessarily indicate a true absence of polarized emission, e.g., after frequency averaging, but can also stem from uncertainty in the polarization direction. This demonstrates that our Bayesian approach can distinguish between true depolarization and mere uncertainty, providing a more informative representation of polarization structures.

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arXiv2024

Fast, Accurate and Perturbative Forward Modeling of Galaxy Clustering Part II: Redshift Space

Forward modeling the galaxy density within the Effective Field Theory of Large Scale Structure (EFT of LSS) enables field-level analyses that are robust to theoretical uncertainties. At the same time, they can maximize the constraining power from galaxy clustering on the scales amenable to perturbation theory. In order to apply the method to galaxy surveys, the forward model must account for the full observational complexity of the data. In this context, a major challenge is the inclusion of redshift space distortions (RSDs) from the peculiar motion of galaxies. Here, we present improvements in the efficiency and accuracy of the RSD modeling in the perturbative LEFTfield forward model. We perform a detailed quantification of the perturbative and numerical error for the prediction of momentum, velocity and the redshift-space matter density. Further, we test the recovery of cosmological parameters at the field level, namely the growth rate $f$, from simulated halos in redshift space. For a rigorous test and to scan through a wide range of analysis choices, we fix the linear (initial) density field to the known ground truth but marginalize over all unknown bias coefficients and noise amplitudes. With a third-order model for gravity and bias, our results yield $<1\,\%$ statistical and $<1.5\,\%$ systematic error. The computational cost of the redshift-space forward model is only $\sim 1.5$ times of the rest frame equivalent, enabling future field-level inference that simultaneously targets cosmological parameters and the initial matter distribution.

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arXiv2024

Fast, Accurate and Perturbative Forward Modeling of Galaxy Clustering Part I: Galaxies in the Restframe

Forward models of the galaxy density field enable simulation based inference as well as field level inference of galaxy clustering. However, these analysis techniques require forward models that are both computationally fast and robust to modeling uncertainties in the relation between galaxies and matter. Both requirements can be addressed with the Effective Field Theory of Large Scale Structure. Here, we focus on the physical and numerical convergence of the LEFTfield model. Based on the perturbative nature of the forward model, we derive an analytic understanding of the leading numerical errors, and we compare our estimates to high-resolution and N-body references. This allows us to derive a set of best-practice recommendations for the numerical accuracy parameters, which are completely specified by the desired order of the perturbative solution and the cut-off scale. We verify these recommendations by an extended set of parameter recovery tests from fully nonlinear mock data and find very consistent results. A single evaluation of the forward model takes seconds, making cosmological analyses of galaxy clustering data based on forward models computationally feasible.

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arXiv2024

JAXbind: Bind any function to JAX

JAX is widely used in machine learning and scientific computing, the latter of which often relies on existing high-performance code that we would ideally like to incorporate into JAX. Reimplementing the existing code in JAX is often impractical and the existing interface in JAX for binding custom code either limits the user to a single Jacobian product or requires deep knowledge of JAX and its C++ backend for general Jacobian products. With JAXbind we drastically reduce the effort required to bind custom functions implemented in other programming languages with full support for Jacobian-vector products and vector-Jacobian products to JAX. Specifically, JAXbind provides an easy-to-use Python interface for defining custom, so-called JAX primitives. Via JAXbind, any function callable from Python can be exposed as a JAX primitive. JAXbind allows a user to interface the JAX function transformation engine with custom derivatives and batching rules, enabling all JAX transformations for the custom primitive.

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arXiv2024

$\texttt{cunuSHT}$: GPU Accelerated Spherical Harmonic Transforms on Arbitrary Pixelizations

We present $\texttt{cunusht}$, a general-purpose Python package that wraps a highly efficient CUDA implementation of the nonuniform spin-$0$ spherical harmonic transform. The method is applicable to arbitrary pixelization schemes, including schemes constructed from equally-spaced iso-latitude rings as well as completely nonuniform ones. The algorithm has an asymptotic scaling of $\mathrm{O}{(\ell_{\rm max}^3)}$ for maximum multipole $\ell_{\rm max}$ and achieves machine precision accuracy. While $\texttt{cunusht}$ is developed for applications in cosmology in mind, it is applicable to various other interpolation problems on the sphere. We outperform the fastest available CPU algorithm by a factor of up to 5 for problems with a nonuniform pixelization and $\ell_{\rm max}>4\cdot10^3$ when comparing a single modern GPU to a modern 32-core CPU. This performance is achieved by utilizing the double Fourier sphere method in combination with the nonuniform fast Fourier transform and by avoiding transfers between the host and device. For scenarios without GPU availability, $\texttt{cunusht}$ wraps existing CPU libraries. $\texttt{cunusht}$ is publicly available and includes tests, documentation, and demonstrations.

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arXiv2024

Ray-tracing vs. Born approximation in full-sky weak lensing simulations of the MillenniumTNG project

Weak gravitational lensing is a powerful tool for precision tests of cosmology. As the expected deflection angles are small, predictions based on non-linear N-body simulations are commonly computed with the Born approximation. Here we examine this assumption using ${\small DORIAN}$, a newly developed full-sky ray-tracing scheme applied to high-resolution mass-shell outputs of the two largest simulations in the MillenniumTNG suite, each with a 3000 Mpc box containing almost 1.1 trillion cold dark matter particles in addition to 16.7 billion particles representing massive neutrinos. We examine simple two-point statistics like the angular power spectrum of the convergence field, as well as statistics sensitive to higher order correlations such as peak and minimum statistics, void statistics, and Minkowski functionals of the convergence maps. Overall, we find only small differences between the Born approximation and a full ray-tracing treatment. While these are negligibly small at power-spectrum level, some higher order statistics show more sizable effects; ray-tracing is necessary to achieve percent level precision. At the resolution reached here, full-sky maps with 0.8 billion pixels and an angular resolution of 0.43 arcmin, we find that interpolation accuracy can introduce appreciable errors in ray-tracing results. We therefore implemented an interpolation method based on nonuniform fast Fourier transforms (NUFFT) along with more traditional methods. Bilinear interpolation introduces significant smoothing, while nearest grid point sampling agrees well with NUFFT, at least for our fiducial source redshift, $z_s=1.0$, and for the 1 arcmin smoothing we use for higher-order statistics.

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arXiv2024

How much information can be extracted from galaxy clustering at the field level?

We present optimal Bayesian field-level cosmological constraints from nonlinear tracers of the large-scale structure, specifically the amplitude $\sigma_8$ of linear matter fluctuations inferred from rest-frame simulated dark matter halos in a comoving volume of $8\,(h^{-1}\mathrm{Gpc})^3$. Our constraint on $\sigma_8$ is entirely due to nonlinear information, and obtained by explicitly sampling the initial conditions along with bias and noise parameters via a Lagrangian EFT-based forward model, LEFTfield. The comparison with a simulation-based inference analysis employing the power spectrum and bispectrum -- likewise using the LEFTfield forward model -- shows that, when including precisely the same modes of the same data up to $k_{\mathrm{max}}= 0.10\,h\,\mathrm{Mpc}^{-1}$ ($0.12\,h\,\mathrm{Mpc}^{-1}$), the field-level approach yields a factor of 3.5 (5.2) improvement on the $\sigma_8$ constraint, from 20.0% to 5.7% (17.0% to 3.3%). This study provides direct insights into cosmological information encoded in galaxy clustering beyond low-order $n$-point functions.

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arXiv2023

Multi-Component Imaging of the Fermi Gamma-ray Sky in the Spatio-spectral Domain

We perform two distinct spatio-spectral reconstructions of the gamma-ray sky in the range of 0.56-316 GeV based on Fermi Large Area Telescope (LAT) data. Both describe the sky brightness to be composed of a diffuse-emission and a point-source component. The first model requires minimal assumptions and provides a template-free reconstruction as a reference. It makes use of spatial and spectral correlations to distinguish between the different components. The second model is physics-informed and further differentiates between diffuse emission of hadronic and leptonic origin. For this, we assume parametric, but spatially varying energy spectra to distinguish between the processes and use thermal Galactic dust observations to indicate the preferred sites of hadronic interactions. To account for instrumental effects we model the point-spread, the energy dispersion, and the exposure of the telescope throughout the observation. The reconstruction problem is formulated as a Bayesian inference task, that is solved by variational inference. We show decompositions of the Gamma-ray flux into diffuse and point-like emissions, and of the diffuse emissions into multiple physically motivated components. The diffuse decomposition provides an unprecedented view of the Galactic leptonic diffuse emission. It shows the Fermi bubbles and their spectral variations in high fidelity and other areas exhibiting strong cosmic ray electron contents, such as a thick disk in the inner Galaxy and outflow regions. Furthermore, we report a hard spectrum gamma ray arc in the northern outer bubble co-spatial with the reported X-ray arc by the eROSITA collaboration. All our spatio-spectral sky reconstructions and their uncertainty quantification are publicly available.

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arXiv2023

Cosmology inference at the field level from biased tracers in redshift-space

Cosmology inference of galaxy clustering at the field level with the EFT likelihood in principle allows for extracting all non-Gaussian information from quasi-linear scales, while robustly marginalizing over any astrophysical uncertainties. A pipeline in this spirit is implemented in the \texttt{LEFTfield} code, which we extend in this work to describe the clustering of galaxies in redshift space. Our main additions are: the computation of the velocity field in the LPT gravity model, the fully nonlinear displacement of the evolved, biased density field to redshift space, and a systematic expansion of velocity bias. We test the resulting analysis pipeline by applying it to synthetic data sets with a known ground truth at increasing complexity: mock data generated from the perturbative forward model itself, sub-sampled matter particles, and dark matter halos in N-body simulations. By fixing the initial-time density contrast to the ground truth, while varying the growth rate $f$, bias coefficients and noise amplitudes, we perform a stringent set of checks. These show that indeed a systematic higher-order expansion of the velocity bias is required to infer a growth rate consistent with the ground truth within errors. Applied to dark matter halos, our analysis yields unbiased constraints on $f$ at the level of a few percent for a variety of halo masses at redshifts $z=0,\,0.5,\,1$ and for a broad range of cutoff scales $0.08\,h/\mathrm{Mpc} \leq Λ\leq 0.20\,h/\mathrm{Mpc}$. Importantly, deviations between true and inferred growth rate exhibit the scaling with halo mass, redshift and cutoff that one expects based on the EFT of Large Scale Structure. Further, we obtain a robust detection of velocity bias through its effect on the redshift-space density field and are able to disentangle it from higher-derivative bias contributions.

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arXiv2023

Improved cosmic microwave background (de-)lensing using general spherical harmonic transforms

Deep cosmic microwave background polarization experiments allow a very precise internal reconstruction of the gravitational lensing signal in pricinple. For this aim, likelihood-based or Bayesian methods are typically necessary, where very large numbers of lensing and delensing remappings on the sphere are sometimes required before satisfactory convergence. We discuss here an optimized piece of numerical code in some detail that is able to efficiently perform both the lensing operation and its adjoint (closely related to delensing) to arbitrary accuracy, using nonuniform fast Fourier transform technology. Where applicable, we find that the code outperforms current widespread software by a very wide margin. It is able to produce high-resolution maps that are accurate enough for next-generation cosmic microwave background experiments on the timescale of seconds on a modern laptop. The adjoint operation performs similarly well and removes the need for the computation of inverse deflection fields. This publicly available code enables de facto efficient spherical harmonic transforms on completely arbitrary grids, and it might be applied in other areas as well.

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arXiv2023

Consistency tests of field level inference with the EFT likelihood

Analyzing the clustering of galaxies at the field level in principle promises access to all the cosmological information available. Given this incentive, in this paper we investigate the performance of field-based forward modeling approach to galaxy clustering using the effective field theory (EFT) framework of large-scale structure (LSS). We do so by applying this formalism to a set of consistency and convergence tests on synthetic datasets. We explore the high-dimensional joint posterior of LSS initial conditions by combining Hamiltonian Monte Carlo sampling for the field of initial conditions, and slice sampling for cosmology and model parameters. We adopt the Lagrangian perturbation theory forward model from [1], up to second order, for the forward model of biased tracers. We specifically include model mis-specifications in our synthetic datasets within the EFT framework. We achieve this by generating synthetic data at a higher cutoff scale $Λ_0$, which controls which Fourier modes enter the EFT likelihood evaluation, than the cutoff $Λ$ used in the inference. In the presence of model mis-specifications, we find that the EFT framework still allows for robust, unbiased joint inference of a) cosmological parameters - specifically, the scaling amplitude of the initial conditions - b) the initial conditions themselves, and c) the bias and noise parameters. In addition, we show that in the purely linear case, where the posterior is analytically tractable, our samplers fully explore the posterior surface. We also demonstrate convergence in the cases of nonlinear forward models. Our findings serve as a confirmation of the EFT field-based forward model framework developed in [2-7], and as another step towards field-level cosmological analyses of real galaxy surveys.

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arXiv2023

Bayesian radio interferometric imaging with direction-dependent calibration

Context: Radio interferometers measure frequency components of the sky brightness, modulated by the gains of the individual radio antennas. Due to atmospheric turbulence and variations in the operational conditions of the antennas these gains fluctuate. Thereby the gains do not only depend on time but also on the spatial direction on the sky. To recover high quality radio maps an accurate reconstruction of the direction and time-dependent individual antenna gains is required. Aims: This paper aims to improve the reconstruction of radio images, by introducing a novel joint imaging and calibration algorithm including direction-dependent antenna gains. Methods: Building on the \texttt{resolve} framework, we designed a Bayesian imaging and calibration algorithm utilizing the image domain gridding method for numerically efficient application of direction-dependent antenna gains. Furthermore by approximating the posterior probability distribution with variational inference, our algorithm can provide reliable uncertainty maps. Results: We demonstrate the ability of the algorithm to recover high resolution high dynamic range radio maps from VLA data of the radio galaxy Cygnus A. We compare the quality of the recovered images with previous work relying on classically calibrated data. Furthermore we compare with a compressed sensing algorithm also incorporating direction-dependent gains. Conclusions: Including direction-dependent effects in the calibration model significantly improves the dynamic range of the reconstructed images compared to reconstructions from classically calibrated data. Compared to the compressed sensing reconstruction, the resulting sky images have a higher resolution and show fewer artifacts. For utilizing the full potential of radio interferometric data, it is essential to consider the direction dependence of the antenna gains.

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arXiv2023

Impact of half-wave plate systematics on the measurement of cosmic birefringence from CMB polarization

Polarization of the cosmic microwave background (CMB) can probe new parity-violating physics such as cosmic birefringence (CB), which requires exquisite control over instrumental systematics. The non-idealities of the half-wave plate (HWP) represent a source of systematics when used as a polarization modulator. We study their impact on the CMB angular power spectra, which is partially degenerate with CB and miscalibration of the polarization angle. We use full-sky beam convolution simulations including HWP to generate mock noiseless time-ordered data, process them through a bin averaging map-maker, and calculate the power spectra including $TB$ and $EB$ correlations. We also derive analytical formulae which accurately model the observed spectra. For our choice of HWP parameters, the HWP-induced angle amounts to a few degrees, which could be misinterpreted as CB. Accurate knowledge of the HWP is required to mitigate this. Our simulation and analytical formulae will be useful for deriving requirements for the accuracy of HWP calibration.

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arXiv2022

Variable structures in M87* from space, time and frequency resolved interferometry

Observing the dynamics of compact astrophysical objects provides insights into their inner workings, thereby probing physics under extreme conditions. The immediate vicinity of an active supermassive black hole with its event horizon, photon ring, accretion disk, and relativistic jets is a perfect place to study general relativity and magneto-hydrodynamics. The observations of M87* with Very Long Baseline Interferometry (VLBI) by the Event Horizon Telescope (EHT) allows to investigate its dynamical processes on time scales of days. Compared to regular radio interferometers, VLBI networks typically have fewer antennas and low signal to noise ratios (SNRs). Furthermore, the source is variable, prohibiting integration over time to improve SNR. Here, we present an imaging algorithm that copes with the data scarcity and temporal evolution, while providing uncertainty quantification. Our algorithm views the imaging task as a Bayesian inference problem of a time-varying brightness, exploits the correlation structure in time, and reconstructs a ${2+1+1}$ dimensional time-variable and spectrally resolved image at once. We apply this method to the EHT observation of M87* and validate our approach on synthetic data. The time- and frequency-resolved reconstruction of M87* confirms variable structures on the emission ring. The reconstruction indicates extended and time-variable emission structures outside the ring itself.

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