相关论文: Model independent calibrations of gamma ray bursts…

The examination of uncertainty in the predictions of machine learning (ML) models is receiving increasing attention. One uncertainty modeling technique used for this purpose is Monte-Carlo (MC)-Dropout, where repeated predictions are…

Mitigating data gaps in Gamma-ray bursts (GRBs) light curves (LCs) is crucial for cosmological research, enhancing the precision of parameters, assuming perfect satellite conditions for complete LC coverage with no gaps. This analysis…

Gamma-ray bursts (GRBs) being the most luminous among known cosmic objects carry an essential potential for cosmological studies if properly used as standard candles. In this paper we test with GRBs the cosmological predictions of the…

In the present work, by the help of the newly released Union2 compilation which consists of 557 Type Ia supernovae (SNIa), we calibrate 109 long Gamma-Ray Bursts (GRBs) with the well-known Amati relation, using the cosmology-independent…

Gamma-Ray Bursts (GRB) are the most energetic events in the Universe, and provide a complementary probe of dark energy by allowing the measurement of cosmic expansion history that extends to redshifts greater than 6. Unlike Type Ia…

Luminosity correlations of long Gamma-ray bursts (GRB) are extensively proposed as an effective complementarity to trace the Hubble diagram of Universe at high redshifts, which is of great importance to explore properties of dark energy.…

Gamma-ray bursts (GRBs) are spectacularly energetic events, with the potential to inform on the early universe and its evolution, once their redshifts are known. Unfortunately, determining redshifts is a painstaking procedure requiring…

Due to the wide range of timescales that are present in macromolecular systems, hierarchical multiscale strategies are necessary for their computational study. Coarse-graining (CG) allows to establish a link between different system…

We use the new gamma-ray bursts (GRBs) data, combined with the baryon acoustic oscillation(BAO) observation from the spectroscopic Sloan Digital Sky Survey (SDSS) data release, the newly obtained $A$ parameter at $z=0.6$ from the WiggleZ…

We present the Hubble diagram (HD) of 66 Gamma Ray Bursts (GRBs) derived using only data from their X - ray afterglow lightcurve. To this end, we use the recently updated L_X - T_a correlation between the break time T_a and the X - ray…

In this paper, we firstly calibrate the Amati relation (the $E_{\rm p}-E_{\rm iso}$ correlation) of gamma ray bursts (GRBs) at low redshifts ($z<0.8$) via Gaussian process by using the type Ia supernovae samples from Pantheon+ under the…

Recently, the Dark Energy Spectroscopic Instrument (DESI) collaboration has presented results indicating that dark energy may exhibit dynamical behavior. Calibrated gamma-ray burst (GRB) correlations can be employed to verify or reject a…

We present a machine learning (ML) based method for automated detection of Gamma-Ray Burst (GRB) candidate events in the range 60 keV - 250 keV from the AstroSat Cadmium Zinc Telluride Imager data. We use density-based spatial clustering to…

In the coming decade, a new generation of massively multiplexed spectroscopic surveys, such as PFS, WAVES, and MOONS, will probe galaxies in the distant universe in vastly greater numbers than was previously possible. In this work, we…

Differently from the equivalence time between either matter and radiation or dark energy and matter, the equivalence between dark energy and radiation occurs between two subdominant fluids, since it takes place in the matter dominated…

So far large and different data sets revealed the accelerated expansion rate of the Universe, which is usually explained in terms of dark energy. The nature of dark energy is not yet known, and several models have been introduced: a non…

In previous papers, a cosmological model with constant-rate particle creation and vacuum term decaying linearly with the Hubble parameter was shown to lead to a good concordance when tested against precise observations: the position of the…

We consider the Bayesian calibration of models describing the phenomenon of block copolymer (BCP) self-assembly using image data produced by microscopy or X-ray scattering techniques. To account for the random long-range disorder in BCP…

In many safety-critical applications such as autonomous driving and surgical robots, it is desirable to obtain prediction uncertainties from object detection modules to help support safe decision-making. Specifically, such modules need to…

The process of calibrating computer models of natural phenomena is essential for applications in the physical sciences, where plenty of domain knowledge can be embedded into simulations and then calibrated against real observations. Current…