相关论文: Modeling blazar broadband emission with convolutio…

Component separation is the process with which emission sources in astrophysical maps are generally extracted by taking multi-frequency information into account. It is crucial to develop more reliable methods for component separation for…

We present a numerical code, written in C, which can be used to simulate or to analyze the emission of Blazars over the entire electromagnetic spectrum. Our code can reproduce the following features: synchrotron emission, inverse Compton…

The blazar sequence is reflected in a correlation of the peak luminosity versus peak frequency of the synchrotron component of blazars. This correlation has been considered one of the fundamental pieces of evidence for the existence of a…

Driver assistance systems as well as autonomous cars have to rely on sensors to perceive their environment. A heterogeneous set of sensors is used to perform this task robustly. Among them, radar sensors are indispensable because of their…

Convolutional neural networks (CNNs) achieved the state-of-the-art performance in medical image segmentation due to their ability to extract highly complex feature representations. However, it is argued in recent studies that traditional…

We propose a new symplectic convolutional neural network (CNN) architecture by leveraging symplectic neural networks, proper symplectic decomposition, and tensor techniques. Specifically, we first introduce a mathematically equivalent form…

Recently Transformer and Convolution neural network (CNN) based models have shown promising results in EEG signal processing. Transformer models can capture the global dependencies in EEG signals through a self-attention mechanism, while…

We present the results of a multifrequency campaign from radio to hard X-ray energies on the blazar 3C 279 during an optical high-state in January 2006. We give the observational results (multifrequency light curves and spectra) and compile…

In April-May 1998 the blazar ON 231 (W Com, B2 1219+28) showed an extraordinary optical outburst alerted by the Perugia Astronomical Observatory. The source reached the most luminous state, observed at least since the beginning of the…

We present a comprehensive multi-wavelength investigation of BL Lac object OJ 287 using Swift and Fermi observatories spanning 2008-2025. The source exhibits significant flux variability across optical-UV, X-ray, and $\gamma$-ray regimes,…

Computational material modeling using advanced numerical techniques speeds up the design process and reduces the costs of developing new engineering products. In the field of multiscale modeling, huge computation efforts are expected for…

We are presenting a novel, Deep Learning based approach to estimate the normalized broadband spectral energy distribution (SED) of different stellar populations in synthetic galaxies. In contrast to the non-parametric multiband source…

Fermi-LAT analyses show that the gamma-ray photon spectral indices Gamma_gamma of a large sample of blazars correlate with the vFv peak synchrotron frequency v_s according to the relation Gamma_gamma = d - k log v_s. The same function, with…

We fit the spectral energy distributions (SEDs) of members of a large sample of Fermi 2LAC blazars to synchrotron and inverse Compton (IC) models. Our main results are as follows. (i) As suggested by previous works, the correlation between…

We consider whether deep convolutional networks (CNNs) can represent decision functions with similar accuracy as recurrent networks such as LSTMs. First, we show that a deep CNN with an architecture inspired by the models recently…

In this paper, we propose a Computer Assisted Diagnosis (CAD) system based on a deep Convolutional Neural Network (CNN) model, to build an end-to-end learning process that classifies breast mass lesions. We investigate the impact that has…

Convolutional neural networks (CNNs) can potentially provide powerful tools for classifying and identifying patterns in climate and environmental data. However, because of the inherent complexities of such data, which are often…

Lately a specific kind of blazars drew the attention of the gamma-ray astronomy community: the extreme TeV BL Lacs, blazars that present an extremely energetic and hard emission at very high-energy. Explaining their features is still an…

The emission from blazars is known to be variable at all wavelengths. The flux variability is often accompanied by spectral changes. Spectral energy distribution (SED) changes must be associated with changes in the spectra of emitting…

Developing an efficient sampler capable of generating independent and identically distributed (IID) samples from a Boltzmann distribution is a crucial challenge in scientific research, e.g. molecular dynamics. In this work, we intend to…