Speaker
Description
A variety of high-energy pulsar models have been developed over the years. This theoretical activity was prompted by a consistent stream of pulsar discoveries, the rate of which rapidly increased since the launch of the Fermi Large Area Telescope (LAT) in 2008. Indeed, the recent Third Pulsar Catalog (3PC) now contains light curves and spectra of nearly 300 pulsars, along with some interesting correlations between timing and spectral parameters. This prompts further theoretical improvements to exploit the wealth of new data. Pulsar models typically focus on different physical regimes (e.g., global current flow, magnetic structure, pair creation microphysics, or emission and beaming). Magnetohydrodynamic (MHD) and particle-in-cell (PIC) models each have their respective strengths but are often computationally expensive to cover a suitably large parameter space. Machine learning has recently been invoked to speed up the process. As a practical interim step, we are exploring a geometric current sheet model that takes into account the latest developments in the field, but focuses on the beaming geometry rather than the energetics of the problem. This allows us to constrain the magnetospheric and emission and viewing geometry by fitting the dual-band light curves of several pulsars using this simplified framework. We will present first results from this model compared to those of the traditional outer gap and two-pole caustic models. We will incorporate both a traditional conal and a high-altitude radio model to enable the joint fitting of both phase-aligned and non-aligned radio and gamma-ray light curves.
| Stream | Science or Engineering |
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