# Electrons' energy in GRB afterglows implied by radio peaks

## TL;DR

This paper introduces a radio peak-based method to constrain the electron energy fraction in GRB afterglows, revealing a narrow distribution around 0.13-0.15 and highlighting the importance of specific radio observations for modeling.

## Contribution

It presents a novel diagnostic approach using radio lightcurve peaks to estimate the electron energy fraction, offering an alternative to broadband modeling.

## Key findings

- $ extepsilon_e$ has a narrow distribution around 0.13-0.15
- Radio observations at $ extgreater{}10$ GHz within 0.3-30 days are optimal for constraining $ extepsilon_e$
- Previous broadband modeling results for $ extepsilon_e$ may be inconsistent due to different assumptions

## Abstract

Gamma-ray burst (GRB) afterglows have been observed across the electromagnetic spectrum, and physical parameters of GRB jets and their surroundings have been derived using broadband modeling. While well-sampled lightcurves across the broadband spectrum are necessary to constrain all the physical parameters, some can be strongly constrained by the right combination of just a few observables, almost independently of the other unknowns. We present a method involving the peaks of radio lightcurves to constrain the fraction of shock energy that resides in electrons, $\epsilon_e$. This parameter is an important ingredient for understanding the microphysics of relativistic shocks; Based on a sample of 36 radio afterglows, we find $\epsilon_e$ has a narrow distribution centered around $0.13-0.15$. Our method is suggested as a diagnostic tool for determining $\epsilon_e$, and to help constrain the broadband modeling of GRB afterglows. Some earlier measurements of the spreads in parameter values for $\epsilon_e$, the kinetic energy of the shock, and the density of the circumburst medium, based on broadband modeling across the entire spectrum, are at odds with our analysis of radio peaks. This could be due to different modeling methods and assumptions, and possibly missing ingredients in past and current modeling efforts. Furthermore, we show that observations at $\gtrsim10$~GHz performed $0.3-30$ days after the GRB trigger, are best suited for pinpointing the synchrotron peak frequency, and consequently $\epsilon_e$. At the same time, observations at lower radio frequencies can pin down the synchrotron self-absorption frequency and help constrain the other physical parameters of GRB afterglows.