Synchro-curvature description of γ-ray light curves and spectra of pulsars: concurrent fitting
We present a concurrent fitting of spectra and light curves of the whole population of detected gamma-ray pulsars. Using a synchro-curvature model we compare our theoretical output with the observational data published in the Third Fermi Pulsar Catalog, which has significantly increased the number o...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/398228 |
| Acceso en línea: | http://hdl.handle.net/10261/398228 |
| Access Level: | acceso abierto |
| Palabra clave: | Acceleration of particles Radiation mechanisms: non-thermal Pulsars: general Gamma-rays: stars X-rays: stars |
| Sumario: | We present a concurrent fitting of spectra and light curves of the whole population of detected gamma-ray pulsars. Using a synchro-curvature model we compare our theoretical output with the observational data published in the Third Fermi Pulsar Catalog, which has significantly increased the number of known gamma-ray pulsars. Our model properly fits all the spectra and reproduces well a considerable fraction of light curves. Light curve fitting is carried out with two different techniques, whose strong points and caveats are discussed. We use a weighted reduced of light curves in time domain, and the Euclidean distance of the Fourier transform of the light curves, i.e. transforming the light curves to the frequency domain. The performance of both methods is found to be qualitatively similar, but individual best-fitting solutions may differ. We also show that, in our model based on few effective parameters, the light curve fitting is basically insensitive to the timing and spectral parameters of the pulsar. Finally, we look for correlations between model and physical parameters, and recover trends found in previous studies but without any significant correlation involving geometrical parameters. |
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