arXiv subjects

Savvas Nesseris

Publications and source records attributed to Savvas Nesseris.

At least 37 records · Page 2Linked to original sources

arXiv2024

Probing $Λ$CDM through the Weyl potential and machine learning forecasts

For years, the cosmological constant $Λ$ and cold dark matter (CDM) model ($Λ\text{CDM}$) has stood as a cornerstone in modern cosmology and serves as the predominant theoretical framework for current and forthcoming surveys. However, the latest results shown by the Dark Energy Spectroscopic Instrument (DESI), along other cosmological data, show hints in favor of an evolving dark energy. Given the elusive nature of dark energy and the imperative to circumvent model bias, we introduce a novel null test, derived from Noether's theorem, that uses measurements of the Weyl potential (the sum of the spatial and temporal distortion) at different redshifts. In order to assess the consistency of the concordance model we quantify the precision of this null test through the reconstruction of mock catalogs based on $Λ\text{CDM}$ using forthcoming survey data, employing Genetic Algorithms, a machine learning technique. Our analysis indicates that with forthcoming LSST-like and DESI-like mock data our consistency test will be able to rule out several cosmological models at around 4$σ$ and help to check for tensions in the data.

astro-ph.CO↗

arXiv2024

Applying the Viterbi Algorithm to Planetary-Mass Black Hole Searches

The search for subsolar mass primordial black holes (PBHs) poses a challenging problem due to the low signal-to-noise ratio, extended signal duration, and computational cost demands, compared to solar mass binary black hole events. In this paper, we explore the possibility of investigating the mass range between subsolar and planetary masses, which is not accessible using standard matched filtering and continuous wave searches. We propose a systematic approach employing the Viterbi algorithm, a dynamic programming algorithm that identifies the most likely sequence of hidden Markov states given a sequence of observations, to detect signals from small mass PBH binaries. We formulate the methodology, provide the optimal length for short-time Fourier transforms, and estimate sensitivity. Subsequently, we demonstrate the effectiveness of the Viterbi algorithm in identifying signals within mock data containing Gaussian noise. Our approach offers the primary advantage of being agnostic and computationally efficient.

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arXiv2024

Non-Linearity-Free prediction of the growth-rate $fσ_8$ using Convolutional Neural Networks

The growth-rate $fσ_8(z)$ of the large-scale structure of the Universe is an important dynamic probe of gravity that can be used to test for deviations from General Relativity. However, for galaxy surveys to extract this key quantity from cosmological observations, two important assumptions have to be made: i) a fiducial cosmological model, typically taken to be the cosmological constant and cold dark matter ($Λ$CDM) model and ii) the modeling of the observed power spectrum, especially at non-linear scales, which is particularly dangerous as most models used in the literature are phenomenological at best. In this work, we propose a novel approach involving convolutional neural networks (CNNs), trained on the Quijote N-body simulations, to predict $fσ_8(z)$ directly and without assuming a model for the non-linear part of the power spectrum, thus avoiding the second of the assumptions above. This could serve as an initial step towards the future development of a method for parameter inference in Stage IV surveys. We find that the predictions for the value of $fσ_8$ from the CNN are in excellent agreement with the fiducial values since they outperform a maximum likelihood analysis and the CNN trained on the power spectrum. Therefore, we find that the CNN reconstructions provide a viable alternative to avoid the theoretical modeling of the non-linearities at small scales when extracting the growth rate.

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arXiv2024

Searching for local features in primordial power spectrum using genetic algorithms

We present a novel methodology for exploring local features directly in the primordial power spectrum using a genetic algorithm (GA) pipeline coupled with a Boltzmann solver and Cosmic Microwave Background data (CMB). After testing the robustness of our pipeline using mock data, we apply it to the latest CMB data, including Planck 2018 and CamSpec PR4. Our model-independent approach provides an analytical reconstruction of the power spectra that best fits the data, with the unsupervised machine learning algorithm exploring a functional space built off simple ``grammar'' functions. We find significant improvements upon the simple power-law behaviour, by $Δχ^2 \lesssim -21$, consistently with more traditional model-based approaches. These best-fits always address both the low$\ell$ anomaly in the TT spectrum and the residual high$\ell$ oscillations in the TT, TE and EE spectra. The proposed pipeline provides an adaptable tool for exploring features in the primordial power spectrum in a model-independent way, providing valuable hints to theorists for constructing viable inflationary models that are consistent with the current and upcoming CMB surveys.

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arXiv2024

Machine learning unveils the linear matter power spectrum of modified gravity

The matter power spectrum $P(k)$ is one of the main quantities connecting observational and theoretical cosmology. Although for a fixed redshift this can be numerically computed very efficiently by Boltzmann solvers, an analytical description is always desirable. However, accurate fitting functions for $P(k)$ are only available for the concordance model. Taking into account that forthcoming surveys will further constrain the parameter space of cosmological models, it is also of interest to have analytical formulations for $P(k)$ when alternative models are considered. Here, we use the genetic algorithms, a machine learning technique, to find a parametric function for $P(k)$ considering several possible effects imprinted by modifications of gravity. Our expression for the $P(k)$ of modified gravity shows a mean accuracy of around 1-2% when compared with numerical data obtained via modified versions of the Boltzmann solver CLASS, and thus it represents a competitive formulation given the target accuracy of forthcoming surveys.

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arXiv2024

Lensing convergence and anisotropic dark energy in galaxy redshift surveys

Analyses of upcoming galaxy surveys will require careful modelling of relevant observables such as the power spectrum of galaxy counts in harmonic space $C_\ell(z,z')$. We investigate the impact of disregarding relevant relativistic effects by considering a model of dark energy including constant sound speed $c_{\rm eff}^2$, constant equation of state $w$, and anisotropic stress sourced by matter perturbations $π$. Cosmological constraints were computed using cosmic microwave background anisotropies, baryon acoustic oscillations, supernovae type Ia, and redshift space distortions. Our results are consistent with $w=-1$, $c_{\rm eff}^2=1$, and $π=0$. Then, a forecast for the performance of an Euclid-like galaxy survey was carried out also adding information from other probes. Here we show that, regardless of the galaxy survey configuration, neglecting the effect of lensing convergence will lead to substantial shifts in the galaxy bias $b_0$ and the neutrino mass $\sum m_ν$. Shifts in the dark energy sound speed and anisotropic stress also appear, but they depend on the survey configuration and hence lack robustness. While neglecting lensing convergence also leads to a Hubble constant $H_0$ moving downwards, the significance of the shift is not big enough to play a relevant part in the current $H_0$ tension.

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arXiv2024

Constraining LLTB models with galaxy cluster counts from next generation surveys

The Universe's assumed homogeneity and isotropy is known as the cosmological principle. It is one of the assumptions that lead to the Friedmann-Lema\^ıtre-Robertson-Walker (FLRW) metric and it is a cornerstone of modern cosmology, because the metric plays a crucial role into the determination of the cosmological observables. Thus, it is of paramount importance to question this principle and perform observational tests that may falsify this hypothesis. Here we explore the use of galaxy cluster counts as a probe of a large-scale inhomogeneity, which is a novel approach for the study of inhomogeneous models, and to determine the precision with which future galaxy cluster surveys will be able to test the cosmological principle. We present forecast constraints on the inhomogeneous Lema\^ıtre-Tolman-Bondi (LTB) model with a cosmological constant and cold dark matter, from a combination of simulated data according to a compilation of `Stage-IV' galaxy surveys following a methodology that involves the use of a mass function correction from numerical $N$-body simulations of an LTB cosmology. When considering the \lcdm fiducial model as a baseline for constructing our mock catalogs, we find that our combination of the forthcoming cluster surveys, will improve the constraints on the cosmological principle parameters as well on the FLRW parameters by about $50\%$ with respect to previous similar forecasts performed using geometrical and linear growth of structure probes, with $\pm20\%$ variations depending on the level of knowledge of systematic effects.These results indicate that galaxy cluster abundances are sensitive probes of inhomogeneity, and that next-generation galaxy cluster surveys, will thoroughly test homogeneity at cosmological scales, tightening the constraints on possible violations of the cosmological principle in the framework of $Λ$LTB scenarios. (Abridged)

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arXiv2024

Gravitational Waves in the Circular Restricted Three Body Problem

The prospect of unprecedented high-quality data of gravitational waves in the upcoming decades demands a theoretical effort to optimally study and analyze the signals that next generation detectors will provide. Here we study the gravitational wave emission and related dynamics during the inspiralling phase of the Circular Restricted Three Body Problem, a modification of the conventional binary scenario in which a small third object co-rotates with the parent binary system. Specifically, we obtain analytic expressions for the emitted power, frequency variation and other dynamical variables that describe the evolution of the system. As a key highlight, we find that the presence of the third body actually slows down the coalescence of the binary, which can be partially interpreted as an effective rescaling of the binary's chirp-mass. Our analysis assumes semi-Keplerian orbits for the particles and a highly mass asymmetric parent binary needed for the stability of orbits.

gr-qc↗

arXiv2024

Effects of orbital precession on hyperbolic encounters

The hyperbolic encounters of two massive objects are characterized by the emission of a gravitational wave burst, with most of the energy released during the closest approach (near the periastron). The detection of such events, different from the well-known inspiral emission, would be an interesting discovery and provide complementary information to observations of binary mergers of black holes and neutron stars in the observable Universe, shedding light, for instance, on the clustering properties of black holes and providing valuable hints on their formation scenario. Here, we analyze the dynamics of such phenomena in the simplest case where two compact objects follow unbound/hyperbolic orbits. Moreover, we explore the effects of orbital precession on the gravitational wave emission, since the precession encodes certain general relativistic effects between two bodies. We also provide templates for the strain of gravitational waves and the power spectrum for the emission, and analytical expressions for the memory effect associated with such signals.

gr-qc↗

arXiv2023

Machine learning cosmic inflation

We present a machine-learning approach, based on the genetic algorithms (GA), that can be used to reconstruct the inflationary potential directly from cosmological data. We create a pipeline consisting of the GA, a primordial code and a Boltzmann code used to calculate the theoretical predictions, and Cosmic Microwave Background (CMB) data. As a proof of concept, we apply our methodology to the Planck CMB data and explore the functional space of single-field inflationary potentials in a non-parametric, yet analytical way. We show that the algorithm easily improves upon the vanilla model of quadratic inflation and proposes slow-roll potentials better suited to the data, while we confirm the robustness of the Starobinsky inflation model (and other small-field models). Moreover, using unbinned CMB data, we perform a first concrete application of the GA by searching for oscillatory features in the potential in an agnostic way, and find very significant improvements upon the best featureless potentials, $Δχ^2 < -20$. These encouraging preliminary results motivate the search for resonant features in the primordial power spectrum with a multimodal distribution of frequencies. We stress that our pipeline is modular and can easily be extended to other CMB data sets and inflationary scenarios, like multifield inflation or theories with higher-order derivatives.

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arXiv2023

Tracking the validity of the quasi-static and sub-horizon approximations in modified gravity

Within the framework of modified gravity (MG), the quasi-static (QS) and sub-horizon (SH) approximations are widely used in analyses aiming to identify departures from the concordance model at late-times. In general, it is assumed that time derivatives are subdominant with respect to spatial derivatives given that the relevant physical modes are those well inside the Hubble radius. In practice, the perturbation equations under these approximations are reduced to a tractable algebraic system in terms of the gravitational potentials and the perturbations of involved matter fields. Here, in the framework of $f(R)$ theories, we revisit standard results when these approximations are invoked using a new parameterization scheme that allows us to track the relevance of each time-derivative term in the perturbation equations. This new approach unveils terms which are neglected in the standard procedure. We assess the relevance of these differences by comparing results from both approaches against full numerical solutions for two well-known toy-models: the designer $f(R)$ model and the Hu-Sawicki model. We find that: i) the SH approximation can be safely applied to linear perturbation equations for scales $0.06 h/$Mpc $\lesssim k \lesssim 0.2 h/$Mpc, ii) in this "safety region", the QS approximation provides a very accurate description of the late-time cosmological dynamics even when dark energy significantly contribute to the cosmic budget, and iii) our new methodology performs better than the standard procedure, even for several orders of magnitude in some cases. Although, the impact of this major improvement on the linear observables is minimal for the studied cases, this does not represent an invalidation for our approach. Instead, our findings indicate that the perturbation expressions derived under these approximations in more general MG theories, such as Horndeski, should be also revisited.

gr-qc↗

arXiv2023

Constraints on extended Bekenstein models from cosmological, astrophysical, and local data

Searching for variations of nature's fundamental constants is a crucial step in our quest to go beyond our current standard model of fundamental physics. If they exist, such variations will be very likely driven by the existence of a new fundamental field. The Bekenstein model and its extensions introduce such a scalar field in a purely phenomenological way, inducing a variation of the fine-structure constant on cosmological scales. This theoretical framework is as simple and general as possible while still preserving all the symmetries of standard quantum electrodynamics. When allowing for couplings to the other sectors of the Universe, such as baryons, dark matter, and the cosmological constant, the Bekenstein model is expected to reproduce the low energy limits of several grand unification, quantum gravity, and higher dimensional theories. In this work, we constrain different versions of the Bekenstein model by confronting the full cosmological evolution of the field with an extensive set of astrophysical, cosmological, and local measurements. We show that couplings of the order of parts per million (ppm) are excluded for all the cases considered, imposing strong restrictions on theoretical frameworks aiming to deal with variations of the fine-structure constant.

astro-ph.CO↗

arXiv2023

Using machine learning to compress the matter transfer function $T(k)$

The linear matter power spectrum $P(k,z)$ connects theory with large scale structure observations in cosmology. Its scale dependence is entirely encoded in the matter transfer function $T(k)$, which can be computed numerically by Boltzmann solvers, and can also be computed semi-analytically by using fitting functions such as the well-known Bardeen-Bond-Kaiser-Szalay (BBKS) and Eisenstein-Hu (EH) formulae. However, both the BBKS and EH formulae have some significant drawbacks. On the one hand, although BBKS is a simple expression, it is only accurate up to $10\%$, which is well above the $1\%$ precision goal of forthcoming surveys. On the other hand, while EH is as accurate as required by upcoming experiments, it is a rather long and complicated expression. Here, we use the Genetic Algorithms (GAs), a particular machine learning technique, to derive simple and accurate fitting formulae for the transfer function $T(k)$. When the effects of massive neutrinos are also considered, our expression slightly improves over the EH formula, while being notably shorter in comparison.

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arXiv2023

The Effective Fluid approach for Modified Gravity and its applications

In this review we briefly summarize the so-called effective fluid approach, which is a compact framework that can be used to describe a plethora of different modified gravity models as general relativity (GR) and a dark energy (DE) fluid. This approach, which is complementary to the cosmological effective field theory, has several benefits as it allows for the easier inclusion of most modified gravity models into the state-of-the-art Boltzmann codes, that are typically hard-coded for GR and DE. Furthermore, it can also provide theoretical insights into their behavior, since in linear perturbation theory it is easy to derive physically motivated quantities such as the DE anisotropic stress or the DE sound speed. We also present some explicit applications of the effective fluid approach with $f(R)$, Horndeski and Scalar-Vector-Tensor models, namely how this approach can be used to easily solve the perturbation equations and incorporate the aforementioned modified gravity models into Boltzmann codes so as to obtain cosmological constraints using Monte Carlo analyses.

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arXiv2022

Machine learning constraints on deviations from general relativity from the large scale structure of the Universe

We use a particular machine learning approach, called the genetic algorithms (GA), in order to place constraints on deviations from general relativity (GR) via a possible evolution of Newton's constant $μ\equiv G_\mathrm{eff}/G_\mathrm{N}$ and of the dark energy anisotropic stress $η$, both defined to be equal to one in GR. Specifically, we use a plethora of background and linear-order perturbations data, such as type Ia supernovae, baryon acoustic oscillations, cosmic chronometers, redshift space distortions and $E_g$ data. We find that although the GA is affected by the lower quality of the currently available data, especially from the $E_g$ data, the reconstruction of Newton's constant is consistent with a constant value within the errors. On the other hand, the anisotropic stress deviates strongly from unity due to the sparsity and the systematics of the $E_g$ data. Finally, we also create synthetic data based on a next-generation survey and forecast the limits of any possible detection of deviations from GR. In particular, we use two fiducial models: one based on the cosmological constant $Λ$CDM model and another on a model with an evolving Newton's constant, dubbed $μ$CDM. We find that the GA reconstructions of $μ(z)$ and $η(z)$ can be constrained to within a few percent of the fiducial models and in the case of the $μ$CDM mocks, they can also provide a strong detection of several $σ$s, thus demonstrating the utility of the GA reconstruction approach.

astro-ph.CO↗

arXiv2022

Gravitational wave matched filtering by quantum Monte Carlo integration and quantum amplitude amplification

The speedup of heavy numerical tasks by quantum computing is now actively investigated in various fields including data analysis in physics and astronomy. In this paper, we propose a new quantum algorithm for matched filtering in gravitational wave (GW) data analysis based on the previous work by Gao et al., Phys. Rev. Research 4, 023006 (2022) [arXiv:2109.01535]. Our approach uses the quantum algorithm for Monte Carlo integration for the signal-to-noise ratio (SNR) calculation instead of the fast Fourier transform used in Gao et al. and searches signal templates with high SNR by quantum amplitude amplification. In this way, we achieve an exponential reduction of the qubit number compared with Gao et al.'s algorithm, keeping a quadratic speedup over classical GW matched filtering with respect to the template number.

astro-ph.IM↗

arXiv2022

A GREAT model comparison against the cosmological constant

Recently, a covariant formulation of non-equilibrium phenomena in the context of General Relativity was proposed in order to explain from first principles the observed accelerated expansion of the Universe, without the need for a cosmological constant, leading to the GREA theory. Here, we confront the GREA theory against the latest cosmological data, including type Ia supernovae, baryon acoustic oscillations, the cosmic microwave background (CMB) radiation, Hubble rate data from the cosmic chronometers and the recent $H_0$ measurements. We perform Markov Chain Monte Carlo analyses and a Bayesian model comparison, by estimating the evidence via thermodynamic integration, and find that when all the aforementioned data are included, but no prior on $H_0$, the difference in the log-evidence is $\sim -9$ in favor of GREA, thus resulting in overwhelming support for the latter over the cosmological constant and cold dark matter model ($Λ$CDM). When we also include priors on $H_0$, either from Cepheids or the Tip of the Red Giant Branch measurements, then due to the tensions with CMB data the GREA theory is found to be statistically equivalent with $Λ$CDM.

astro-ph.CO↗

arXiv2022

Late-transition vs smooth $H(z)$ deformation models for the resolution of the Hubble crisis

Gravitational transitions at low redshifts ($z_t<0.1$) have been recently proposed as a solution to the Hubble and growth tensions. Such transitions would naturally lead to a transition in the absolute magnitude $M$ of type Ia supernovae (SnIa) at $z_t$ (Late $M$ Transitions - $LMT$) and possibly in the dark energy equation of state parameter $w$ (Late $w-M$ Transitions - $LwMT$). Here, we compare the quality of fit to cosmological data of this class of models, with the corresponding quality of fit of the cosmological constant model ($Λ$CDM) and some of the best smooth $H(z)$ deformation models ($w$CDM, CPL, PEDE). We also perform model selection via the Akaike Information Criterion and the Bayes factor. We use the full CMB temperature anisotropy spectrum data, the baryon acoustic oscillations (BAO) data, the Pantheon SnIa data, the SnIa absolute magnitude $M$ as determined by Cepheid calibrators and the value of the Hubble constant $H_0$ as determined by local SnIa calibrated using Cepheids. We find that smooth $H(z)$ deformation models perform worse than transition models for the following reasons: 1) They have a worse fit to low-$z$ geometric probes (BAO and SnIa data); 2) They favor values of the SnIa absolute magnitude $M$ that are lower as compared to the value $M_c$ obtained with local Cepheid calibrators at $z<0.01$; 3) They tend to worsen the $Ω_\mathrm{m,0}-σ_\mathrm{8,0}$ growth tension. We also find that the $w-M$ transition model ($LwMT$) does not provide a better quality of fit to cosmological data than a pure $M$ transition model ($LMT$) where $w$ is fixed to the \lcdm value $w=-1$ at all redshifts. We conclude that the $LMT$ model has significant statistical advantages over smooth late-time $H(z)$ deformation models in addressing the Hubble crisis.

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