High energy time lags of gamma-ray bursts

¹ Dipartimento di Fisica e Chimica – Emilio Segrè, Università di Palermo, Via Archirafi 36, 90123 Palermo, Italy
² INAF – Osservatorio Astronomica di Brera, Via E. Bianchi 46, I-23807 Merate (LC), Italy
³ INFN – Sezione di Milano–Bicocca, Piazza della Scienza 3, 20126 Milano (MI), Italy
⁴ INFN, Sezione di Trieste, I-34127 Trieste, Italy
⁵ Dipartimento di Fisica, Università di Trento, Sommarive 14, 38122 Povo (TN), Italy
⁶ Istituto di Astrofisica Spaziale e Fisica Cosmica, Istituto nazionale di astrofisica, via Ugo La Malfa 153, Palermo I-90146, Italia
⁷ Department of Physics, University of Cagliari, SP Monserrato-Sestu, km 0.7, 09042 Monserrato, Italy
⁸ INAF – Osservatorio di Astrofisica e Scienza dello Spazio di Bologna, Via Piero Gobetti 101, I-40129 Bologna, Italy
⁹ Ioffe Institute, Politekhnicheskaya 26, 194021 St. Petersburg, Russia

^⋆ Corresponding author.

Received: 6 February 2025
Accepted: 27 March 2025

Abstract

Context. Positive lags between the arrival time of different photon energies are commonly observed in the prompt phase of gamma-ray bursts (GRBs), where soft photons lag behind harder ones. However, a fraction of GRBs display the opposite behavior. In particular, Fermi Large Area Telescope (LAT) observations revealed that high-energy photons are often characterized by a delayed onset.

Aims. We explore the potential of spectral lags as a diagnostic tool to identify distinct emission components or processes. By analyzing data from the Fermi Gamma-ray Burst Monitor (GBM) and the LAT Low Energy (LLE) technique, we explore the connection between lag behavior and high-energy spectral properties.

Methods. We analyze a sample of 70 GRBs from the LLE catalog. Spectral lags are computed using the discrete correlation function method, considering light curves extracted in four different energy bands, from 10 keV to 100 MeV. Additionally, we compare LLE time lags with properties of the prompt emission and with the spectral behavior at high energies.

Results. Time lags computed across different energy bands distributed between 10 keV and 1 MeV are predominantly positive (76%) as a possible consequence of a hard-to-soft spectral evolution of the prompt spectrum. Lags between the LLE (30–100 MeV) and the GBM (10–100 keV) bands show a variety of behaviors: 40% are positive, while 37% are negative. Such negative lags may suggest the delayed emergence of an additional emission component dominating at high energies. Indeed, the spectral analysis of LLE data for 56 GRBs shows that negative lags are associated with an LLE spectral index typically harder than the high-energy power law identified in GBM data.

Conclusions. Spectral lags of LLE data can be exploited as a diagnostic tool to identify and characterize emission components in GRBs, highlighting the importance of combining temporal and spectral analyses to advance our understanding of GRB emission mechanisms.