Related papers: AI-driven spatio-temporal engine for finding gravi…
Absolute distances from strong lensing can anchor Type Ia Supernovae (SNe Ia) at cosmological distances giving a model-independent inference of the Hubble constant ($H_0$). Future observations could provide strong lensing time-delay…
The possible time variation of the fundamental constants of nature has been an active subject of research since the large-number hypothesis was proposed by Dirac. In this paper, we propose a new method to investigate a possible time…
The presence of a massive body between the Earth and a gravitational-wave source will produce the so-called gravitational lensing effect. In the case of strong lensing, it leads to the observation of multiple deformed copies of the initial…
When sensors collect spatio-temporal data in a large geographical area, the existence of missing data cannot be escaped. Missing data negatively impacts the performance of data analysis and machine learning algorithms. In this paper, we…
Strong lensing by massive galaxy clusters can provide magnification of the flux and even multiple images of the galaxies that lie behind them. This phenomenon facilitates observations of high-redshift supernovae (SNe), that would otherwise…
Recent rapid development of deep learning algorithms, which can implicitly capture structures in high-dimensional data, opens a new chapter in astronomical data analysis. We report here a new implementation of deep learning techniques for…
Gravitational lensing of high-redshift supernovae is potentially an important source of uncertainty when deriving cosmological parameters from the measured brightness of Type Ia supernovae, especially in deep surveys with scarce statistics.…
Event-based data are commonly encountered in edge computing environments where efficiency and low latency are critical. To interface with such data and leverage their rich temporal features, we propose a causal spatiotemporal convolutional…
Massive galaxy clusters at intermediate redshifts act as gravitational lenses that can magnify supernovae (SNe) occurring in background galaxies. We assess the possibility to use lensed SNe to put constraints on the mass models of galaxy…
In 2016, the first strongly lensed Type Ia supernova, iPTF16geu at redshift $z=0.409$ with four resolved images arranged symmetrically around the lens galaxy at $z=0.2163$, was discovered. Here, refined observations of iPTF16geu, including…
Strong lensing time delay measurement is a promising method to address the Hubble tension, offering a completely independent approach compared to both the cosmic microwave background analysis and the local distance ladder. As a third-party…
Magnification and de-magnification due to gravitational lensing will contribute to the brightness scatter of Type Ia supernovae (SNe Ia). The purpose of this paper is to investigate the possibility to decrease this scatter by correcting…
High-z Type Ia supernovae are expected to be gravitationally lensed by the foreground distribution of large-scale structure. The resulting magnification of supernovae is statistically measurable, and the angular correlation of the…
We present GausSN, a Bayesian semi-parametric Gaussian Process (GP) model for time-delay estimation with resolved systems of gravitationally lensed supernovae (glSNe). GausSN models the underlying light curve non-parametrically using a GP.…
We show that peculiar velocities of Type Ia supernovae can be used to derive constraints on the sum of neutrino masses, $\Sigma m_{\nu}$, and dark energy equation of state, $w = w_0+w_a(1-a)$, from measurements of the magnitude-redshift…
In this paper we use a generalized version of a method originally proposed by Holz and Wald to investigate the effects from gravitational lensing on Type Ia supernovae measurements. We find that results for different mass distributions in…
Probing the speed of light is as an important test of General Relativity but the measurements of $c$ using objects in the distant universe have been almost completely unexplored. In this letter, we propose an idea to use the multiple…
As big spatial data becomes increasingly prevalent, classical spatiotemporal (ST) methods often do not scale well. While methods have been developed to account for high-dimensional spatial objects, the setting where there are exceedingly…
Ongoing searches for supernovae (SNe) at cosmological distances have recently started to provide large numbers of events with measured redshifts and apparent brightnesses. Compared to quasars or galaxies, Type Ia SNe represent a population…
We present a novel method to produce empirical generative models of all kinds of astronomical transients from datasets of unlabeled light curves. Our hybrid model, that we call ParSNIP, uses a neural network to model the unknown intrinsic…