arXiv subjects

Konstantinos Tanidis

Publications and source records attributed to Konstantinos Tanidis.

10 recordsLinked to original sources

arXiv2026

EMU: Cross-correlating EMU Pilot Survey 1 with Dark Energy Survey to validate the radio galaxy bias and redshift distribution

Radio continuum galaxy surveys can provide a relatively fast map of the projected distribution of structure in the Universe, at the cost of lacking information about the radial distribution. We can use these surveys to learn about the growth of structure and the fundamental physics of the Universe, but doing so requires extra information to be provided in the modelling of the redshift distribution, $dN/dz$. In this work, we show how the cross-correlation of the two-dimensional radio continuum map with another galaxy map (in this case a photometric optical extragalactic survey), with a known redshift distribution, can be used to determine the redshift distribution through statistical inference. We use data from the Evolutionary Map of the Universe (EMU) Pilot Survey 1 and cross-correlate it with optical data from the Dark Energy Survey to fit the parameters of our $dN/dz$ model. We show that the recovered distribution has a similar shape to the distribution predicted by the current state-of-the-art simulation, and can fit the angular power spectrum data from cross-correlations very well, validating this model. These results will have significance for future cosmological analyses with large-scale radio continuum surveys such as the full EMU, or with the SKAO.

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arXiv2026

cloelib: A Flexible Python Library for Computing Cosmological Observables in the Euclid Era

cloelib is a Python library developed to compute cosmological observables within the Cosmology Likelihood for Observables in Euclid (CLOE) ecosystem (cloe-org). As cosmology enters a precision era driven by galaxy survey missions such as Euclid, there is a growing need for flexible, efficient, and differentiable software capable of supporting next-generation inference pipelines. cloelib addresses these demands through a modular architecture that interfaces seamlessly with established Boltzmann solvers whilst incorporating JAX-based automatic differentiation to enable gradient-based methods. The library defines consistent protocols for background evolution, perturbations, and non-linear structure formation, and supports a wide range of observables, including photometric and spectroscopic large-scale structure probes, as well as cross-correlations with the Cosmic Microwave Background and galaxy clusters. In its finalised form, cloelib is intended to serve as the reference theory computation infrastructure for Euclid's first cosmological release, bridging traditional numerical cosmology with modern optimisation techniques and emerging machine learning approaches to inference.

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arXiv2025

Reconstructing spatially-varying multiplicative bias for Stage IV weak lensing galaxy surveys with a quadratic estimator

We present a quadratic estimator that detects and reconstructs spatially-varying multiplicative ($m-$) bias in weak lensing shear measurements, by exploiting the $EB$ mode coupling that it generates. The method combines $E$ and $B$ modes with inverse-variance weights, to yield an unbiased reconstruction of $m(\boldsymbolθ)$ to first order. We study the ability of future Stage IV surveys to obtain an unbiased reconstruction of the $m$-bias in differing scenarios, considering differing bias morphologies, and characteristic scales, as well as differing metrics to quantify the signal-to-noise ratio of the reconstructed map. Considering an $m$ pattern repeating on $\sim 1^\circ\times1^\circ$ sky patches, as might be the case for an $m$ field caused by focal-plane systematics. With a Euclid-like redshift distribution, we find that $\sim5\%$ rms variations in $m$-bias may be detected at the 20$σ$ level, after stacking between $\sim400$ and $\sim1000$ patches (rising to between $\sim2800$ and $\sim7600$ for $1\%$ rms variations, data volumes that are becoming available with upcoming surveys), depending on the morphology of the $m$ pattern. We show that these results are robust against the cosmological model assumed in the reconstruction, as well as the presence of intrinsic alignments or baryonic effects, and that the method shows no spurious response to additive ($c-$) bias. These results demonstrate that percent-level, spatially-varying $m-$bias can be detected at high significance, enabling diagnosis and mitigation in the Stage IV weak lensing era.

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arXiv2024

Honing cross-correlation tools for inference on ultra-high-energy cosmic-ray composition

The chemical composition of the highest-energy cosmic rays, namely the atomic number $Z$ of rays with energies $E\gtrsim40~\mathrm{EeV}$, remains to date largely unknown. Some information on the composition can be inferred from the deflections that charged ultra-high-energy cosmic rays experience while they traverse intervening magnetic fields. Indeed, such deflections distort and suppress the original anisotropy in the cosmic ray arrival directions; thus, given a source model, a measure of the anisotropy is also a measurement of the deflections, which in turn informs us on the chemical composition. In this work, we show that, by quantifying ultra-high-energy cosmic ray anisotropies through the angular cross-correlation between cosmic rays and galaxies, we would be able to exclude iron fractions $f_{\rm Fe}\geq{\cal O}(10\%)$ assuming a fiducial hydrogen map at $2\,σ$ level, and even smaller fractions in the reverse case of hydrogen on an iron map, going well below $f_{\rm H}\approx10\%$ when we mask the Galactic Centre up to latitudes of $40^\circ$. This is an improvement of a factor of a few compared to our previous method, and is mostly ascribable to a new test statistics which is sensitive to each harmonic multipole individually. Our method can be applied to real data as an independent test of the recent claim that current cosmic-ray data can not be reproduced by any existing model of the Galactic magnetic field, as well as an additional handle to compare any realistic, competing, data-driven composition models.

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arXiv2023

Model-independent constraints on clustering and growth of cosmic structures from BOSS DR12 galaxies in harmonic space

We present a new, model-independent measurement of the clustering amplitude of galaxies and the growth of cosmic large-scale structures from the Baryon Oscillation Spectroscopic Survey (BOSS) 12th data release (DR12). This is achieved by generalising harmonic-space power spectra for galaxy clustering to measure separately the magnitudes of the density and the redshift-space distortion terms, respectively related to the clustering amplitude of structures, $bσ_8(z)$, and their growth, $fσ_8(z)$. We adopt a tomographic approach with 15 redshift bins in $z\in[0.15,0.67]$. We restrict our analysis to strictly linear scales, implementing a redshift-dependent maximum multipole for each bin. The measurements do not appear to suffer from systematic effects and show excellent agreement with the theoretical predictions from the Planck cosmic microwave background analysis assuming a $Λ$CDM cosmology. Our results also agree with previous analyses by the BOSS collaboration. Furthermore, our method provides the community with a new tool for data analyses of the cosmic large-scale structure complementary to state-of-the-art approaches in configuration or Fourier space. Amongst its merits, we list: it being more agnostic with respect to the underlying cosmological model; its roots in a well-defined and gauge-invariant observable; the possibility to account naturally for wide-angle effects and even relativistic corrections on ultra-large scales; and the capability to perform an almost arbitrarily fine redshift binning with little computational effort. These aspects are all the more relevant for the oncoming generation of cosmological experiments such as Euclid, the Dark Energy Spectroscopic Instrument (DESI), the Legacy Survey of Space and Time (LSST), and the SKA Project.

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arXiv2022

Constraining ultra-high-energy cosmic ray composition through cross-correlations

The chemical composition of the highest end of the ultra-high-energy cosmic ray spectrum is very hard to measure experimentally, and to this day it remains mostly unknown. Since the trajectories of ultra-high-energy cosmic rays are deflected in the magnetic field of the Galaxy by an angle that depends on their atomic number $Z$, it could be possible to indirectly measure $Z$ by quantifying the amount of such magnetic deflections. In this paper we show that, using the angular harmonic cross-correlation between ultra-high-energy cosmic rays and galaxies, we could effectively distinguish different atomic numbers with current data. As an example, we show how, if $Z=1$, the cross-correlation can exclude a $39\%$ fraction of Fe56 nuclei at $2σ$ for rays above $100\text{EeV}$.

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arXiv2020

Developing a unified pipeline for large-scale structure data analysis with angular power spectra -- III. Implementing the multi-tracer technique to constrain neutrino masses

In this paper, we apply the multi-tracer technique to harmonic-space (i.e.\ angular) power spectra with a likelihood-based approach. This goes beyond the usual Fisher matrix formalism hitherto implemented in forecasts with angular statistics, opening up a window for future developments and direct application to available data sets. We also release a fully-operational modified version of the publicly available code CosmoSIS, where we consistently include all the add-ons presented in the previous papers of this series. The result is a modular cosmological parameter estimation suite for angular power spectra of galaxy number counts, allowing for single and multiple tracers, and including density fluctuations, redshift-space distortions, and weak lensing magnification. We demonstrate the improvement on parameter constraints enabled by the use of multiple tracers on a multi-tracing analysis of luminous red galaxies and emission line galaxies. We obtain an enhancement of $44\%$ on the $2σ$ upper bound on the sum of neutrino masses. Our code is publicly available at https://github.com/ktanidis/Modified_CosmoSIS_for_galaxy_number_count_angular_power_spectra.

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arXiv2020

Developing a unified pipeline for large-scale structure data analysis with angular power spectra -- II. A case study for magnification bias and radio continuum surveys

Following on our purpose of developing a unified pipeline for large-scale structure data analysis with angular (i.e. harmonic-space) power spectra, we now include the weak lensing effect of magnification bias on galaxy clustering in a publicly available, modular parameter estimation code. We thus forecast constraints on the parameters of the concordance cosmological model, dark energy, and modified gravity theories from galaxy clustering tomographic angular power spectra. We find that a correct modelling of magnification is crucial in order not to bias the estimation of cosmological parameters, especially in the case of deep galaxy surveys. Our case study adopts specifications of the Evolutionary Map of the Universe (EMU), which is a full-sky, deep radio-continuum survey, and is expected to probe the Universe up to redshift $z\sim6$. We assume the Limber approximation, and include magnification bias on top of density fluctuations and redshift-space distortions. By restricting our analysis to the regime where the Limber approximation holds true, we significantly minimise the computational time needed, compared to that of the exact calculation. We also show that there is a trend for more biased parameter estimates from neglecting magnification when the redshift bins are very wide. We conclude that this result implies a strong dependence on the lensing contribution, which is an integrated effect and becomes dominant when wide redshift bins are considered. Finally, we note that instead of being considered a contaminant, magnification bias encodes important cosmological information, and its inclusion leads to an alleviation of the degeneracy between the galaxy bias and the amplitude normalisation of the matter fluctuations.

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arXiv2020

Towards simulating a realistic data analysis with an optimised angular power spectrum of spectroscopic galaxy surveys

The angular power spectrum is a natural tool to analyse the observed galaxy number count fluctuations. In a standard analysis, the angular galaxy distribution is sliced into concentric redshift bins and all correlations of its harmonic coefficients between bin pairs are considered---a procedure referred to as `tomography'. However, the unparalleled quality of data from oncoming spectroscopic galaxy surveys for cosmology will render this method computationally unfeasible, given the increasing number of bins. Here, we put to test against synthetic data a novel method proposed in a previous study to save computational time. According to this method, the whole galaxy redshift distribution is subdivided into thick bins, neglecting the cross-bin correlations among them; each of the thick bin is, however, further subdivided into thinner bins, considering in this case all the cross-bin correlations. We create a simulated data set that we then analyse in a Bayesian framework. We confirm that the newly proposed method saves computational time and gives results that surpass those of the standard approach.

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arXiv2019

Developing a unified pipeline for large-scale structure data analysis with angular power spectra -- I. The importance of redshift-space distortions for galaxy number counts

We develop a cosmological parameter estimation code for (tomographic) angular power spectra analyses of galaxy number counts, for which we include, for the first time, redshift-space distortions (RSD) in the Limber approximation. This allows for a speed-up in computation time, and we emphasise that only angular scales where the Limber approximation is valid are included in our analysis. Our main result shows that a correct modelling of RSD is crucial not to bias cosmological parameter estimation. This happens not only for spectroscopy-detected galaxies, but even in the case of galaxy surveys with photometric redshift estimates. Moreover, a correct implementation of RSD is especially valuable in alleviating the degeneracy between the amplitude of the underlying matter power spectrum and the galaxy bias. We argue that our findings are particularly relevant for present and planned observational campaigns, such as the Euclid satellite or the Square Kilometre Array, which aim at studying the cosmic large-scale structure and trace its growth over a wide range of redshifts and scales.

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