Using the Geodesic Light-Cone (GLC) coordinates, one can obtain fully non-linear expressions for light-like cosmological observables. Indeed, by exploiting the intrinsic nature of these coordinates, one can construct an exact, non-perturbative metric that contains all the information about the inhomogeneities and anisotropies present in the observed universe. Meanwhile, it is also interesting...
In this manuscript, the background and perturbed cosmic dynamics have been investigated using an interacting dark-fluid model by assuming energy exchange between dark matter and dark energy through a diffusion mechanism. We solve the background expansion history for the late-time Universe and derive the full set of the evolution equations of the matter density contrast, $\delta(z)$ and...
We apply model-independent methods based on symmetries — specifically the 'LSS bootstrap' — to derive robust predictions across a wide range of alternative scenarios to $\Lambda$CDM. Our ongoing work aims to improve constraints on bootstrap parameters, i.e., cosmology-dependent coefficients in the matter kernels, by jointly analyzing the power spectrum (up to one-loop) and the tree-level...
The validity of popular cold and warm inflationary scenarios in cosmology is investigated by comparing and contrasting various models. Results indicate that warm inflation can provide a more realistic understanding of the early universe in the light of cosmic microwave background than the conventional cold inflation. The genesis of warm inflation from supersymmetry and string theory emphasise...
Amidst a myriad of sophisticated alternatives to general relativity, unimodular gravity stands unique as a relatively simple extension. In the Henneaux-Teitelboim (HT) formulation of unimodular gravity, the cosmological constant $\Lambda$ is promoted to a scalar field $\Lambda(x)$ at the level of the action. However, a non-dynamical vector density $\mathcal{T^{\mu}}$ ensures the constancy of...
In this work, we studied a model that dynamically realizes the equation of state $p + \rho = 0$ . The perturbations of such a system, which mimics a Dynamical Cosmological Constant (DCC), exhibit pathological behavior within the perfect fluid approximation. We show that going beyond the perfect fluid paradigm is essential for achieving a stable evolution and that the presence of an anisotropic...
Axionlike particles (ALPs) are promising candidates for dark matter. A tiny interaction between photons and ALPs gives rise to achromatic birefringence. The birefringence angle oscillates with a time-period determined by ALP mass. We exploit this property of ALPs to find stringent constraints on its coupling constant as well as mass by means of radio polarimetric observations of strong...
Machine Learning (ML) as emerged in the last decade as a powerful tool to solve complex, high-dimensional problems. This presentation will cover several aspects of my research related to ML techniques applied to tackle challenges in cosmology. Firstly, I will describe a new method to infer cosmological parameters from X-ray cluster number counts, using full-field emulation and simulation-based...
In this talk, I explore an extension of the standard cosmological model by introducing a dynamical dark energy (DDE) scenario, where the pressure evolves with cosmic time. Instead of assuming a constant dark energy component, we expand the pressure around the present epoch to capture possible deviations from a cosmological constant. This approach introduces one or two new parameters, depending...
We propose a new method to detect a class of composite dark matter models where the electromagnetic transitions between dark matter states result in spectral distortions in the Cosmic Microwave Background (CMB) spectrum. We show that the spectral distortion signature depends sensitively on the dark matter transition frequency and the strength of couplings of dark matter with the visible sector...
The Ultraviolet Near-Infrared Optical Northern Survey (UNIONS) is a photometric survey in the North. Its images can be used to study the Large-Scale structure of the Universe with cosmic shear. The standard approach relies on two-point statistics that only capture the Gaussian information in the shear field. Statistics can be build to extract its non-Gaussian information but usually relie on...
ShapeFit is a novel approach alternative to Full Modeling, and has been gaining popularity for analyzing the large scale structures of the universe. This approach provides information on the slope of the matter power spectrum at the pivot scale, m. There are two crucial steps to obtain this additional information: de-wiggling the power spectrum and calculating the derivative at the pivot...
The era of precision cosmology has provided an unprecedented opportunity to test fundamental physics using Cosmic Microwave Background (CMB) and Large-Scale Structure (LSS) data. In this talk, I will present our recent work on applying neural networks (NNs) for cosmological model selection, focusing on two case studies: CMB power spectra from Planck 2018 data and galaxy clustering surveys. Our...
Cosmic voids are a powerful tool to extract cosmological constraints and study galaxy properties’ dependence on the environment. The project develops a pipeline to constrain cosmological parameters using the Void Size Function (VSF) derived from LSST-like galaxy mock catalogs, employing the VIDE void finder. The analysis incorporates a theoretical model accounting for tracer bias,...
Ongoing galaxy surveys map the Universe’s large-scale structure with unprecedented fidelity across immense cosmological volumes. Cosmological inference at the field level demands thousands of N-body simulations. To fully exploit Stage-IV data, simulators must therefore produce fast, high-precision realisations spanning vast cosmological volumes and reaching deep into the non-linear regime. The...
Pairwise velocities of the large-scale structure encode valuable information about the growth of structure. They can be observed indirectly through redshift-space distortions and the kinetic Sunyaev–Zeldovich effect. Whether Gaussian or non-Gaussian, pairwise velocity has a broad distribution, but the cosmologically useful information lies primarily in the mean — the streaming velocities; the...
Cosmic voids are the largest objects emerging in the cosmic web, covering the majority of the volume of the Universe. They are a well-established probe to gather cosmological information from the large-scale structure, as well as interesting regions to study how the underdense environment affects the behavior of astrophysical objects. Unfortunately, identifying voids in a galaxy catalog is...
The gravitational collapse of dark matter halos from small density perturbations in the early universe is a highly stochastic and non-linear process that is best approximated through N-body simulations. In this work, we test and compare the ability of fully-convolutional neural networks and transformer-based neural networks to predict the formation of dark matter halos from initial conditions,...
I'll present the prospects of reconstructing the "cosmic distance ladder" of the Universe using our novel deep learning framework, [LADDER][1] (Learning Algorithm for Deep Distance Estimation and Reconstruction). Trained on apparent magnitude data from the Pantheon Type Ia supernovae compilation, LADDER uses full covariance information among data points to deliver predictions with...
Recent results from the DESI survey provide compelling evidence for a dynamical dark energy component, challenging the long-standing cosmological constant paradigm. In this talk, I will present a mechanism based on chameleon dark energy—an interacting quintessential scalar field dark energy and dark matter model mediated by a Yukawa-type coupling. This fifth-force framework not only allows for...
