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High-resolution simulations of non-thermal emission from LS 5039

Ralf Kissmann, David Huber, Philipp Gschwandtner

TL;DR

This work advances the modelling of LS 5039 by coupling high-resolution relativistic hydrodynamics with energetic-lepton transport to predict non-thermal emission across the orbit. By performing three full-orbit simulations with a large domain and detailed particle transport in post-processing, the authors capture the Coriolis shock and its role in particle acceleration, and they include synchrotron, inverse-Compton, Doppler boosting, and γγ absorption, supplemented by a magnetospheric outer-gap component to better reproduce HE gamma-ray data. The study finds improved alignment with soft X-ray and gamma-ray observations, highlights the need for a dynamical magnetic-field treatment and injection tuning, and discusses the potential requirement of a hadronic component to explain observations beyond 100 TeV. Overall, the results strengthen the wind-driven scenario for LS 5039 and outline concrete directions for refining magnetic-field modeling and particle-injection schemes to further improve the spectral and temporal fits.

Abstract

In a previous study, we investigated the relativistic wind dynamics in the LS 5039 system. In this work, we analyse energetic-particle transport within this modelling context, where we simulate the high-energy particle distribution and ensuing emission of non-thermal radiation. From these high-resolution simulations, we compute the non-thermal emission from this system and compare it to corresponding observations. We modelled the LS 5039 system assuming a wind-driven scenario. Our numerical model uses a joint simulation of the dynamical wind interaction together with the transport of energetic leptons from the shocked pulsar wind. We computed the non-thermal emission from this system in a post-processing step from the resulting distribution of energetic leptons. In this computation, we took into account the synchrotron and inverse Compton emission, relativistic beaming, and γγ-absorption in the stellar radiation field. We investigated the dynamical variation of the energetic particle spectra on both orbital and on short timescales. Our model successfully reproduces many of the spectral features of LS 5039. We also find a better correspondence between our predicted orbital light curves and the corresponding observations in soft x-rays, low-energy, and high-energy gamma rays than in our previous modelling efforts. We find that our high-resolution and large-scale simulations can successfully capture the relevant parts of the wind-collision region that are related to particle acceleration and emission of non-thermal radiation. The quality of the fit strengthens the wind-driven assumption underlying our model. Desirable extensions for the future include a dynamical magnetic-field model for the synchrotron regime, a revision of our injection parameters, and a consideration of an additional hadronic component that could explain recent observations in the 100~TeV regime.

High-resolution simulations of non-thermal emission from LS 5039

TL;DR

This work advances the modelling of LS 5039 by coupling high-resolution relativistic hydrodynamics with energetic-lepton transport to predict non-thermal emission across the orbit. By performing three full-orbit simulations with a large domain and detailed particle transport in post-processing, the authors capture the Coriolis shock and its role in particle acceleration, and they include synchrotron, inverse-Compton, Doppler boosting, and γγ absorption, supplemented by a magnetospheric outer-gap component to better reproduce HE gamma-ray data. The study finds improved alignment with soft X-ray and gamma-ray observations, highlights the need for a dynamical magnetic-field treatment and injection tuning, and discusses the potential requirement of a hadronic component to explain observations beyond 100 TeV. Overall, the results strengthen the wind-driven scenario for LS 5039 and outline concrete directions for refining magnetic-field modeling and particle-injection schemes to further improve the spectral and temporal fits.

Abstract

In a previous study, we investigated the relativistic wind dynamics in the LS 5039 system. In this work, we analyse energetic-particle transport within this modelling context, where we simulate the high-energy particle distribution and ensuing emission of non-thermal radiation. From these high-resolution simulations, we compute the non-thermal emission from this system and compare it to corresponding observations. We modelled the LS 5039 system assuming a wind-driven scenario. Our numerical model uses a joint simulation of the dynamical wind interaction together with the transport of energetic leptons from the shocked pulsar wind. We computed the non-thermal emission from this system in a post-processing step from the resulting distribution of energetic leptons. In this computation, we took into account the synchrotron and inverse Compton emission, relativistic beaming, and γγ-absorption in the stellar radiation field. We investigated the dynamical variation of the energetic particle spectra on both orbital and on short timescales. Our model successfully reproduces many of the spectral features of LS 5039. We also find a better correspondence between our predicted orbital light curves and the corresponding observations in soft x-rays, low-energy, and high-energy gamma rays than in our previous modelling efforts. We find that our high-resolution and large-scale simulations can successfully capture the relevant parts of the wind-collision region that are related to particle acceleration and emission of non-thermal radiation. The quality of the fit strengthens the wind-driven assumption underlying our model. Desirable extensions for the future include a dynamical magnetic-field model for the synchrotron regime, a revision of our injection parameters, and a consideration of an additional hadronic component that could explain recent observations in the 100~TeV regime.
Paper Structure (13 sections, 5 equations, 14 figures, 4 tables)

This paper contains 13 sections, 5 equations, 14 figures, 4 tables.

Figures (14)

  • Figure 1: Number density of accelerated leptons in the orbital plane. Results for energies of 1.5 GeV (bottom), 485.5 GeV (middle), and 5467.7 GeV (top) as indicated above the corresponding plots. We show our results for eight different orbital phases of the second orbit as indicated in the plot. In each case, we depict a range of densities from the peak value at periastron to a factor of $10^{-5}$ of this value. Additionally, the white arrows indicate the direction towards the observer. An example for corresponding fluid quantities is shown in Fig. \ref{['FigCompQuantities']} in Appendix \ref{['AppendComp']}.
  • Figure 2: Same as Fig. \ref{['FigElectronsPerpendicular']}, but perpendicular to the orbital plane, where the plane displaying the results is oriented along the line connecting the star and the pulsar.
  • Figure 3: Domain-integrated spectral energy distribution of energetic leptons for different sub-regions, as discussed in the text. Results are shown for an orbital phase $\phi=0.414$. For comparison, we give the total spectral energy distribution and the one in the inner region from HuberEtAl2021AnA649_71 for a very similar orbital phase ($\phi = 0.393$) via the corresponding curves with a lower opacity. See label 2021 in the legend.
  • Figure 4: Evolution of the domain-integrated spectral energy distributions of the energetic particles for the second and the third (at a lower opacity and using + as a marker) orbit of the simulation. Spectra are given as a function of the particle's Lorentz factor.
  • Figure 5: Temporal evolution of the integrated energy of energetic leptons $E_\text{total}^{\text{CR}}$ within the total computational domain for several bins of particle energy as indicated in the plot. We show the results for the second (left) and third (right) orbit of our simulation. Relevant orbital phases are indicated in the plot via vertical lines, where additionally periastron is at $\phi=0$. The error bars indicate the short-time variation in the six phases used to compute each data point.
  • ...and 9 more figures