Related papers: Machine learning cosmic backreaction and its effec…
The notion of concept drift refers to the phenomenon that the distribution generating the observed data changes over time. If drift is present, machine learning models can become inaccurate and need adjustment. While there do exist methods…
We present a new machine learning model for estimating photometric redshifts with improved accuracy for galaxies in Pan-STARRS1 data release 1. Depending on the estimation range of redshifts, this model based on neural networks can handle…
A leading way to constrain physical theories from cosmological observations is to test their predictions for the angular clustering statistics of matter tracers, a technique that is set to become ever more central with the next generation…
Symbolic regression is a machine learning technique that can learn the governing formulas of data and thus has the potential to transform scientific discovery. However, symbolic regression is still limited in the complexity and…
By means of a toy Swiss-cheese cosmological model we will discuss how to set up and carry out in a physically meaningful way the idea of back-reaction, according to which dark energy could be an effective source. We will follow two distinct…
We derive some basic equations related to the redshift drift and we show how some dark energy (DE) properties can be retrieved from it. We consider in particular three kinds of DE models which exhibit a characteristic signature in their…
Cosmological backreaction suggests a link between structure formation and the expansion history of the Universe. In order to quantitatively examine this connection, we dynamically investigate a volume partition of the Universe into over--…
Harrison's argument against the interpretation of the cosmological redshift as a Doppler effect is revisited, exaggerated, and discussed. The context, purpose, and limitations of the interpretations of this phenomenon are clarified.
Although cosmic expansion at very small distances is usually dismissed as entirely inconsequential, these extraordinarily small effects may in fact have a real and significant influence on our world. A calculation suggests that the minute…
Machine learning techniques offer a plethora of opportunities in tackling big data within the astronomical community. We present the set of Generalized Linear Models as a fast alternative for determining photometric redshifts of galaxies, a…
We present results exploring the role that probabilistic deep learning models can play in cosmology from large scale astronomical surveys through estimating the distances to galaxies (redshifts) from photometry. Due to the massive scale of…
The results from the Supernova Cosmology Project indicate a relation between cosmic distance and redshift that corresponds to an accelerating Universe, and, as a consequence, the presence of an energy component with negative pressure. This…
Phenomenological models are widely used in cosmology in relation to constraining different cosmological models, with two common examples being cosmographic expansions and modeling the equation-of-state parameter of dark energy. This work…
Relying on the obtained results in Rev.[1](physics/0505035), we derive the formula relating the red-shift of light signals coming from distant galaxies to the distance of these galaxies from us and the time of detecting of these light…
Structure occurs over a vast range of scales in the universe. Our large-scale cosmological models are coarse-grained representations of what exists, which have much less structure than there really is. An important problem for cosmology is…
In the concordance model of the Universe, the matter distribution - as observed in galaxy number counts or the intensity of line emission (such as the 21cm line of neutral hydrogen) - should have a kinematic dipole due to the Sun's motion…
In addition to being a probe of Cosmic Dawn and Epoch of Reionization astrophysics, the 21cm line at $z>6$ is also a powerful way to constrain cosmology. Its power derives from several unique capabilities. First, the 21cm line is sensitive…
Some observational consequences of a cosmological scenario driven by adiabatic matter creation are investigated. Exact expressions for the lookback time, age of the universe, luminosity distance, angular diameter, and galaxy number counts…
We present detailed predictions for the redshifted 21cm signal from the epoch of reionization. These predictions are obtained from radiative transfer calculations on the results of large scale (100/h Mpc), high dynamic range, cosmological…
In science, we are interested not only in forecasting but also in understanding how predictions are made, specifically what the interpretable underlying model looks like. Data-driven machine learning technology can significantly streamline…