Abstract:A new model of the Milky Way (MW) halo component of the dispersion measure (DM) for extragalactic sources, such as fast radio bursts (FRBs), is presented in light of recent diffuse X-ray observations. In addition to the spherical component of isothermal gas (kT ∼ 0.3 keV) in hydrostatic equilibrium with the Galactic gravitational potential, our model includes a disk-like non-spherical hot gas component to reproduce the directional dependence of the observed X-ray emission measure (EM). The total gas mass (1.2 … Show more
“…1. For each source, we calculate the DM ex beyond the Milky Way by taking the observed DM and subtracting the contributions from the Galactic interstellar medium (ISM, Yao et al 2017) and an additional 30 pc cm −3 from the Galactic halo (Prochaska & Zheng 2019;Keating & Pen 2020;Yamasaki & Totani 2020). Despite the small number of bursts, we find that a significant fraction of repeaters have DM ex ∼ 10 3 pc cm −3 .…”
CHIME has now detected 18 repeating fast radio bursts (FRBs). We explore what can be learned about the energy distribution and activity level of the repeaters by fitting realistic FRB population models to the data. For a power-law energy distribution dN/dE∝E−γ for the repeating bursts, there is a critical index γcrit that controls whether the dispersion measure (DM, a proxy for source distance) distribution of repeaters is bottom or top-heavy. We find γcrit = 7/4 for Poisson wait-time distribution of repeaters in Euclidean space and further demonstrate how it is affected by temporal clustering of repetitions and cosmological effects. It is especially interesting that two of the CHIME repeaters (FRB 181017 and 190417) have large $\rm DM\sim 10^3\rm \, pc\, cm^{-3}$. These can be understood if: (i) the energy distribution is shallow $\gamma =1.7^{+0.3}_{-0.1}$ ($68\%$ confidence) or (ii) a small fraction of sources are extremely active. In the second scenario, these two high-DM sources should be repeating more than 100 times more frequently than FRB 121102, and the energy index is constrained to be $\gamma = 1.9^{+0.3}_{-0.2}$ ($68\%$ confidence). In either case, this γ is consistent with the energy dependence of the non-repeating ASKAP sample, which suggests that they are drawn from the same population. Finally, our model predicts how the CHIME repeating fraction should decrease with redshift, and this can be compared with observations to infer the distribution of activity level in the whole population.
“…1. For each source, we calculate the DM ex beyond the Milky Way by taking the observed DM and subtracting the contributions from the Galactic interstellar medium (ISM, Yao et al 2017) and an additional 30 pc cm −3 from the Galactic halo (Prochaska & Zheng 2019;Keating & Pen 2020;Yamasaki & Totani 2020). Despite the small number of bursts, we find that a significant fraction of repeaters have DM ex ∼ 10 3 pc cm −3 .…”
CHIME has now detected 18 repeating fast radio bursts (FRBs). We explore what can be learned about the energy distribution and activity level of the repeaters by fitting realistic FRB population models to the data. For a power-law energy distribution dN/dE∝E−γ for the repeating bursts, there is a critical index γcrit that controls whether the dispersion measure (DM, a proxy for source distance) distribution of repeaters is bottom or top-heavy. We find γcrit = 7/4 for Poisson wait-time distribution of repeaters in Euclidean space and further demonstrate how it is affected by temporal clustering of repetitions and cosmological effects. It is especially interesting that two of the CHIME repeaters (FRB 181017 and 190417) have large $\rm DM\sim 10^3\rm \, pc\, cm^{-3}$. These can be understood if: (i) the energy distribution is shallow $\gamma =1.7^{+0.3}_{-0.1}$ ($68\%$ confidence) or (ii) a small fraction of sources are extremely active. In the second scenario, these two high-DM sources should be repeating more than 100 times more frequently than FRB 121102, and the energy index is constrained to be $\gamma = 1.9^{+0.3}_{-0.2}$ ($68\%$ confidence). In either case, this γ is consistent with the energy dependence of the non-repeating ASKAP sample, which suggests that they are drawn from the same population. Finally, our model predicts how the CHIME repeating fraction should decrease with redshift, and this can be compared with observations to infer the distribution of activity level in the whole population.
“…Yamasaki & Totani (2020) (henceforth YT20) provide a two-component model fit to the observations of diffuse X-ray emission. YT20 predicts to be 30 – 245 over the whole sky, with a mean of 43 . Figure 2. Estimates of from the YT20 model (Yamasaki & Totani 2020). …”
Section: Galactic Electron Density Modelsmentioning
confidence: 99%
“…Following Yamasaki & Totani (2020), the total DM for an extragalactic source can be expressed as a sum of four components: where is the contribution from the interstellar medium (ISM) in the Milky Way (MW) disc, is the contribution from the extended Galactic halo, is that from the intergalactic medium (IGM), and is that from the host galaxy (including the source’s local environment). Note that on some sight lines, DM contributions from intervening galaxy halos may also need to be considered (e.g.…”
Section: Introductionmentioning
confidence: 99%
“…Following Yamasaki & Totani (2020), the total DM for an extragalactic source can be expressed as a sum of four components:…”
Section: Introductionmentioning
confidence: 99%
“…The two prevailing Galactic electron density models (GEDMs) are YMW16 (Yao et al 2017, ApJ, 835, 29) and NE2001 (Cordes & Lazio 2002, arXiv e-prints, pp astro–ph/0207156). Here, we introduce a software package PyGEDM which provides a unified application programming interface for these models and the YT20 (Yamasaki & Totani 2020, ApJ, 888, 105) model of the Galactic halo. We use PyGEDM to compute all-sky maps of Galactic dispersion measure (DM) for YMW16 and NE2001 and compare the large-scale differences between the two.…”
Galactic electron density distribution models are crucial tools for estimating the impact of the ionised interstellar medium on the impulsive signals from radio pulsars and fast radio bursts. The two prevailing Galactic electron density models (GEDMs) are YMW16 (Yao et al. 2017, ApJ, 835, 29) and NE2001 (Cordes & Lazio 2002, arXiv e-prints, pp astro–ph/0207156). Here, we introduce a software package PyGEDM which provides a unified application programming interface for these models and the YT20 (Yamasaki & Totani 2020, ApJ, 888, 105) model of the Galactic halo. We use PyGEDM to compute all-sky maps of Galactic dispersion measure (DM) for YMW16 and NE2001 and compare the large-scale differences between the two. In general, YMW16 predicts higher DM values towards the Galactic anticentre. YMW16 predicts higher DMs at low Galactic latitudes, but NE2001 predicts higher DMs in most other directions. We identify lines of sight for which the models are most discrepant, using pulsars with independent distance measurements. YMW16 performs better on average than NE2001, but both models show significant outliers. We suggest that future campaigns to determine pulsar distances should focus on targets where the models show large discrepancies, so future models can use those measurements to better estimate distances along those line of sight. We also suggest that the Galactic halo should be considered as a component in future GEDMs, to avoid overestimating the Galactic DM contribution for extragalactic sources such as FRBs.
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