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Abstract Modeling the multiwavelength spectral energy distributions (SEDs) of blazars provides key insights into the underlying physical processes responsible for the emission. While SED modeling with self-consistent models is computationally demanding, it is essential for a comprehensive understanding of these astrophysical objects. We introduce a novel, efficient method for modeling the SEDs of blazars by the mean of a convolutional neural network (CNN). In this paper, we trained the CNN on a leptonic model that incorporates synchrotron and inverse Compton emissions, as well as self-consistent electron cooling and pair creation–annihilation processes. The CNN is capable of reproducing the radiative signatures of blazars with high accuracy. This approach significantly reduces the computational time, thereby enabling real-time fitting to multiwavelength data sets. As a demonstration, we used the trained CNN withMultiNestto fit the broadband SEDs of Mrk 421 and 1ES 1959+650, successfully obtaining their parameter posterior distributions. This novel framework for fitting the SEDs of blazars will be further extended to incorporate more sophisticated models based on external Compton and hadronic scenarios, allowing for multimessenger constraints in the analysis. The models will be made publicly available via a web interface at the Markarian Multiwavelength Data Center to facilitate self-consistent modeling of multimessenger data from blazar observations.
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Bjet_MCMC: A New Tool to Automatically Fit the Broadband Spectral Energy Distributions of Blazars
Abstract Multiwavelength observations are now the norm for studying blazars’ various states of activity, classifying them, and determining the possible underlying physical processes driving their emission. Broadband emission models became unavoidable tools for testing emission scenarios and setting the values of physical quantities such as the magnetic field strength, Doppler factor, or shape of the particle distribution of the emission zone(s). We announce here the first public release of a new tool,Bjet_MCMC, that can automatically fit the broadband spectral energy distributions (SEDs) of blazars. The complete code is available on GitHub and allows for testing leptonic synchrotron self-Compton models with or without external inverse-Compton processes from the thermal environment of supermassive black holes (accretion disk and broad-line region). The code is designed to be user-friendly and computationally efficient. It contains a core written in C++ and a fully parallelized SED fitting method. The original multi-SSC zone model ofBjetis also available on GitHub but is not included in the Markov Chain Monte Carlo fitting process at the moment. We present the features, performance, and results ofBjet_MCMC, as well as user advice.
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- PAR ID:
- 10491164
- Publisher / Repository:
- DOI PREFIX: 10.3847
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 962
- Issue:
- 2
- ISSN:
- 0004-637X
- Format(s):
- Medium: X Size: Article No. 140
- Size(s):
- Article No. 140
- Sponsoring Org:
- National Science Foundation
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