UWCScholar :: Browsing by Author "Karagiannis, Dionysios"

Browsing by Author "Karagiannis, Dionysios"

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Cosmological constraints from the power spectrum and bispectrum of 21cm intensity maps
(IOP Publishing, 2022) Karagiannis, Dionysios; Maartens, Roy; Randrianjanahary, Liantsoa F.
The 21cm emission of neutral hydrogen is a potential probe of the matter distribution in the Universe after reionisation. Cosmological surveys of this line intensity will be conducted in the coming years by the SKAO and HIRAX experiments, complementary to upcoming galaxy surveys. We present the first forecasts of the cosmological constraints from the combination of the 21cm power spectrum and bispectrum. Fisher forecasts are computed for the constraining power of these surveys on cosmological parameters, the BAO distance functions and the growth function. We also estimate the constraining power on dynamical dark energy and modified gravity. Finally we investigate the constraints on the 21cm clustering bias, up to second order. We take into account the effects on the 21cm correlators of the telescope beam, instrumental noise and foreground avoidance, as well as the Alcock-Paczynski effect and the effects of theoretical errors in the modelling of the correlators.
Euclid preparation: LXXII. three-dimensional galaxy clustering in configuration space: two-point correlation function estimation
(EDP Sciences, 2025) Karagiannis, Dionysios; De La Torre, Sylvain; Marulli, Federico
The two-point correlation function of the galaxy spatial distribution is a major cosmological observable that enables constraints on the dynamics and geometry of the Universe. The Euclid mission is aimed at performing an extensive spectroscopic survey of approximately 20 30 million Hα-emitting galaxies up to a redshift of about 2. This ambitious project seeks to elucidate the nature of dark energy by mapping the three-dimensional clustering of galaxies over a significant portion of the sky. This paper presents the methodology and software developed for estimating the three-dimensional two-point correlation function within the Euclid Science Ground Segment. The software is designed to overcome the significant challenges posed by the large and complex Euclid dataset, which involves millions of galaxies. The key challenges include efficient pair counting, managing computational resources, and ensuring the accuracy of the correlation function estimation. The software leverages advanced algorithms, including k-d tree, octree, and linked-list data partitioning strategies, to optimise the pair-counting process. These methods are crucial for handling the massive volume of data efficiently. The implementation also includes parallel processing capabilities using shared-memory open multi-processing to further enhance performance and reduce computation times. Extensive validation and performance testing of the software are presented. Those have been performed by using various mock galaxy catalogues to ensure that it meets the stringent accuracy requirement of the Euclid mission. The results indicate that the software is robust and can reliably estimate the two-point correlation function, which is essential for deriving cosmological parameters with high precision. Furthermore, the paper discusses the expected performance of the software during different stages of Euclid Wide Survey observations and forecasts how the precision of the correlation function measurements will improve over the mission's timeline, highlighting the software's capability to handle large datasets efficiently.
Multi-tracer power spectra and bispectra: formalism
(Institute of Physics, 2024) Karagiannis, Dionysios; Maartens, Roy; Fonseca, José; Camera, Stefano; Clarkson, Chris
The power spectrum and bispectrum of dark matter tracers are key and complementary probes of the Universe. Next-generation surveys will deliver good measurements of the bispectrum, opening the door to improved cosmological constraints and the breaking of parameter degeneracies, from the combination of the power spectrum and bispectrum. Multi-tracer power spectra have been used to suppress cosmic variance and mitigate the effects of nuisance parameters and systematics. We present a bispectrum multi-tracer formalism that can be applied to next-generation survey data. Then we perform a simple Fisher analysis to illustrate qualitatively the improved precision on primordial non-Gaussianity that is expected to come from the bispectrum multi-tracer. In addition, we investigate the parametric dependence of conditional errors from multi-tracer power spectra and multi-tracer bispectra, on the differences between the biases and the number densities of two tracers. Our results suggest that optimal constraints arise from maximising the ratio of number densities, the difference between the linear biases, the difference between the quadratic biases, and the difference between the products b 1 b Φ for each tracer, where b Φ is the bias for the primordial potential.
Quijote-png: Quasi-maximum likelihood estimation of primordial non-gaussianity in the nonlinear dark matter density field
(American Astronomical Society, 2022) Jung, Gabriel; Karagiannis, Dionysios; Liguori, Michele
Future large-scale structure surveys are expected to improve current bounds on primordial non-Gaussianity (PNG), with a significant impact on our understanding of early universe physics. The level of such improvements will however strongly depend on the extent to which late-time nonlinearities erase the PNG signal on small scales. In this work, we show how much primordial information remains in the bispectrum of the nonlinear dark matter density field by implementing a new, simulation-based methodology for joint estimation of PNG amplitudes ( fNL) and standard Lambda cold dark matter parameters. The estimator is based on optimally compressed statistics, which, for a given input density field, combine power spectrum and modal bispectrum measurements, and numerically evaluate their covariance and their response to changes in cosmological parameters. In this first analysis, we focus on the matter density field, and we train and validate the estimator using a large suite of N-body simulations (QUIJOTE-PNG), including different types of PNG (local, equilateral, orthogonal).
Quijote-png: Simulations of primordial non-gaussianity and the information content of the matter field power spectrum and bispectrum
(IOP Publishing, 2023) Coulton, William R; Villaescusa-Navarro, Francisco; Karagiannis, Dionysios
Primordial non-Gaussianity (PNG) is one of the most powerful probes of the early universe, and measurements of the large-scale structure of the universe have the potential to transform our understanding of this area. However, relating measurements of the late-time universe to the primordial perturbations is challenging due to the nonlinear processes that govern the evolution of the universe. To help address this issue, we release a large suite of N-body simulations containing four types of PNG: QUIJOTE-PNG. These simulations were designed to augment the QUIJOTE suite of simulations that explored the impact of various cosmological parameters on large-scale structure observables. Using these simulations, we investigate how much information on PNG can be extracted by extending power spectrum and bispectrum measurements beyond the perturbative regime at z = 0.0. This is the first joint analysis of the PNG and cosmological information content accessible with power spectrum and bispectrum measurements of the nonlinear scales. We find that the constraining power improves significantly up to kmax 0.3 Mpc h » -1 , with diminishing returns beyond as the statistical probes signal-to-noise ratios saturate. This saturation emphasizes the importance of accurately modeling all the contributions to the covariance matrix. Further, we find that combining the two probes is a powerful method of breaking the degeneracies with the ΛCDM parameters.
Quijote-png: The information content of the halo power spectrum and bispectrum
(IOP Publishing, 2023) Coulton, William R; Villaescusa-Navarro, Francisco; Karagiannis, Dionysios
We investigate how much can be learnt about four types of primordial non-Gaussianity (PNG) from small-scale measurements of the halo field. Using the QUIJOTE-PNG simulations, we quantify the information content accessible with measurements of the halo power spectrum monopole and quadrupole, the matter power spectrum, the halo–matter cross spectrum, and the halo bispectrum monopole. This analysis is the first to include small, nonlinear scales, up to kmax 0.5 h Mpc = -1 , and to explore whether these scales can break degeneracies with cosmological and nuisance parameters making use of thousands of N-body simulations. We perform all the halo measurements in redshift space with a single sample comprised of all halos with mass >3.2 × 1013 h−1 Me. For local PNG, measurements of the scale-dependent bias effect from the power spectrum using sample variance cancellation provide significantly tighter constraints than measurements of the halo bispectrum. In this case measurements of the small scales add minimal additional constraining power. In contrast, the information on equilateral and orthogonal PNG is primarily accessible through the bispectrum. For these shapes, small-scale measurements increase the constraining power of the halo bispectrum by up to 4×, though the addition of scales beyond k ≈ 0.3 h Mpc−1 improves constraints largely through reducing degeneracies between PNG and the other parameters.
Squeezing information from radio surveys to probe the primordial universe
(Institute of Physics, 2025) Karagiannis, Dionysios; Fonseca, José; Camera, Stefano; Clarkson, Chris
A major goal of cosmology is to understand the nature of the field(s) which drove primordial Inflation. Through future observations, the statistics of large-scale structure will allow us to probe primordial non-Gaussianity of the curvature perturbation at the end of Inflation. We show how a new correlation statistic can significantly improve these constraints over conventional methods. Next-generation radio telescope arrays are under construction which will map the density field of neutral hydrogen to high redshifts. These telescopes can operate as an interferometer, able to probe small scales, or as a collection of single dishes, combining signals to map the large scales. We show how to fuse these operating modes in order to measure the squeezed bispectrum with higher precision and greater economy. This leads to constraints on primordial non-Gaussianity that will improve on measurements by Planck, and out-perform other surveys such as Euclid. We forecast that σ(f NLloc)∼ 3, achieved by using a small subset, O(102 - 103), of the total number of accessible triangles. The proposed method identifies a low instrumental noise, systematic-free scale regime, enabling clean squeezed bispectrum measurements. This provides a pristine window into local primordial non-Gaussianity, allowing tight constraints not only on primordial non-Gaussianity, but on any observable that peaks in squeezed configurations.
Taming assembly bias for primordial non-gaussianity
(Institute of Physics, 2024) Fondi, Emanuele; Verde, Licia; Karagiannis, Dionysios
Primordial non-Gaussianity of the local type induces a strong scale-dependent bias on the clustering of halos in the late-time Universe. This signature is particularly promising to provide constraints on the non-Gaussianity parameter fNL from galaxy surveys, as the bias amplitude grows with scale and becomes important on large, linear scales. However, there is a well-known degeneracy between the real prize, the fNL parameter, and the (non-Gaussian) assembly bias i.e., the halo formation history-dependent contribution to the amplitude of the signal, which could seriously compromise the ability of large-scale structure surveys to constrain fNL. We show how the assembly bias can be modeled and constrained, thus almost completely recovering the power of galaxy surveys to competitively constrain primordial non-Gaussianity. In particular, studying hydrodynamical simulations, we find that a proxy for the halo properties that determine assembly bias can be constructed from photometric properties of galaxies. Using a prior on the assembly bias guided by this proxy degrades the statistical errors on fNL only mildly compared to an ideal case where the assembly bias is perfectly known. The systematic error on fNL that the proxy induces can be safely kept under control.
The constraining power of the marked power spectrum: an analytical study
(Institute of Physics, 2025) Karagiannis, Dionysios; Marinucci, Marco; Jung, Gabriel
The marked power spectrum — a two-point correlation function of a weighted density field — has emerged as a promising tool for extracting cosmological information from the large-scale structure of the Universe. In this work, we present the first comprehensive analytical study of the marked power spectrum's sensitivity to primordial non-Gaussianity (PNG) of the non-local type. We extend previous effective field theory frameworks to incorporate PNG, developing a complete theoretical model that we validate against the Quijote simulation suite. Through a systematic Fisher analysis, we compare the constraining power of the marked power spectrum against traditional approaches combining the power spectrum and bispectrum (P+B). We explore different choices of mark parameters to evaluate their impact on parameter constraints, particularly focusing on equilateral and orthogonal PNG as well as neutrino masses. Our analysis shows that while marking up underdense regions yields optimal constraints in the low shot-noise regime, the marked power spectrum's performance for discrete tracers with BOSS-like number densities does not surpass that of P+B analysis at mildly non-linear scales (k ≲ 0.25 h/Mpc). However, the marked approach offers several practical advantages, including simpler estimation procedures and potentially more manageable systematic effects. Our theoretical framework reveals how the marked power spectrum incorporates higher-order correlation information through terms resembling tree-level bispectra and power spectrum convolutions. This work establishes a robust foundation for applying marked statistics to future large-volume surveys.

Browsing by Author "Karagiannis, Dionysios"

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