Indirect Detection Methods

Dark Matter Indirect Detection Method

The origin of dark matter is one of the most enigmatic and perplexing mysteries in the realm of astrophysics and cosmology. It stems from the realization that the visible matter, such as stars, galaxies, and planets, accounts for only a small fraction of the total mass in the universe. The quest to understand the nature and properties of dark matter has led to various detection methods, including indirect detection, which focuses on observing the consequences of dark matter interactions rather than directly detecting the elusive particles themselves.

The indirect detection method relies on the observation of secondary standard model particles or radiation produced as a result of dark matter annihilation or decay in regions where dark matter is expected to be present, such as the centers of galaxies, galaxy clusters, or dwarf spheroidal galaxies. When dark matter particles come into contact and annihilate with one another, they release high-energy particles, including gamma rays, cosmic rays, neutrinos, positrons, etc. These secondary particles can be detected by specialized instruments, such as gamma-ray telescopes or neutrino observatories. The analysis strategy for indirect detection involves meticulously scrutinizing the astrophysical data, searching for an excess of these secondary particles above the expected background. This excess, if detected, could provide crucial insights into the nature of dark matter, including its mass, distribution, and potential annihilation or decay channels. However, the analysis of indirect detection data is inherently challenging due to the complex astrophysical backgrounds and the need to disentangle the dark matter signal from other sources. Sophisticated statistical and computational techniques are employed to model and subtract these backgrounds, ensuring that any observed excess can be attributed to dark matter. Ultimately, the indirect detection of dark matter remains a promising and active area of research, offering the potential to uncover the fundamental properties of dark matter.

Fermi Large Area Telescope Gamma-ray Observatory

The Fermi Large Area Telescope (Fermi-LAT) has been performing as the most efficient MeV-GeV gamma-ray space detector for over a decade, with comparatively better sensitivity than other earlier gamma-ray missions. The LAT scans the whole sky every ≈ 192 minutes from the low-Earth orbit of 565 km altitude at a 25.6-degree inclination with an eccentricity <0.01. The principal objective of the Fermi-LAT is to conduct a long-term high sensitivity observation of the celestial sources for a wide range of energy bands i.e. from ≈ 20 MeV to > 500 GeV. With its unprecedented angular-energy resolution and large effective area, Fermi-LAT has the potential to detect very faint emissions and can also address several unresolved issues in high-energy gamma-ray astrophysics. This feature is particularly crucial to observe the gamma-ray emission resulting from the dark matter annihilation.

Data structure & software requirements

After the classification of events detected by the Fermi-LAT, the gathered gamma-ray data are made publicly accessible through the Fermi Science Support Center (FSSC) data server. To conduct the analysis, Fermitools and Fermipy are essential tools. Notably, Fermipy stands out as a Python package that streamlines the analysis of Fermi-LAT data within the Fermitools framework. Both Fermitools and Fermipy can be easily installed using the Conda package manager, and their source codes are additionally also available on GitHub.

The Analysis

Detecting dark matter with the Fermi-LAT primarily involves searching for excess gamma-ray emissions from regions of space where dark matter is expected to be present. To effectively detect faint signals of dark matter, the Fermi-LAT should possess several key qualities and capabilities. High sensitivity is crucial, as it allows the LAT to detect low-energy gamma rays and faint signals, making it more likely to capture the subtle gamma-ray emissions expected from dark matter annihilation or decay. A large effective area helps collect more gamma-ray photons, enhancing its ability to detect weak signals, particularly when dealing with rare and faint dark matter events. Precise energy measurement capabilities enable the LAT to distinguish between different gamma-ray energy levels, helping identify unique features in the energy spectrum of dark matter signals. The high angular resolution allows the LAT to pinpoint the source of gamma rays, crucial for identifying the spatial distribution of potential dark matter sources and distinguishing them from other astrophysical objects.

1. MLFermiLATDwarfs: Indirect search of dark matter from Milky Way dwarf spheroidal galaxies

MLFermiLATDwarfs a publicly available Python code integrated into the ESCAPE services. This code serves as a framework for deriving constraints on the velocity-independent dark matter pair-annihilation cross-section, employing Fermi-LAT gamma-ray data from Milky Way dwarf spheroidal galaxies. It notably incorporates a machine learning-based assessment to account for both intrinsic and extrinsic astrophysical background emissions from these galaxies. The primary aim of this approach is to enhance the conventional Fermi-LAT analysis of dwarf spheroidal galaxies, enabling users to customize the code as per their requirements. The main difference arises from the treatment of the expected astrophysical gamma-ray background at the position of a particular dwarf galaxy. While the Fermi-LAT collaboration relies on a conventional assessment of the uncertainty of this background component via a selection of various models, the approach presented here is based on a data-driven technique utilizing the whole-sky data and an optimization procedure of the expected background levels. This framework draws inspiration from the methodology outlined in F. Calore et al. (JCAP 10, 2018, 029) and A. Alvarez et al. (JCAP 09, 2020, 004).

From publication

2. Brown_Dwarf_Analysis: Looking for the dark matter capture rate in Brown Dwarfs

Brown_Dwarf_Analysis is publicly available and is based on the analysis methods employed in the recent study by Bhattacharjee et al.,2023. In their study, the authors investigate the Fermi-LAT data obtained from 13 nearby cold and old Brown Dwarfs (BDs) and look for the dark matter capture rate in BDs. BDs serve as celestial objects bridging the gap between the least massive main-sequence stars and giant gas planets. The hypothesis driving this research is that if the universe’s dark matter consists of particles with non-negligible couplings to the standard model, BDs can effectively accumulate these particles through scatterings. Subsequently, dark matter particles can thermalize and annihilate into light, long-lived mediators, which eventually decay into photons outside the BD. The approach adopted in this study was to search for gamma-ray signals originating from these BDs using 13 years of Fermi-LAT data. In the absence of any observed gamma-ray excess, the study established limits on particle dark matter based on the null result. Following this framework, the authors set a stacked upper limit on the dark matter-nucleon elastic scattering cross-section at approximately 10⁻³⁸ cm² for dark matter masses below 10 GeV. These limits are competitive with direct detection bounds, especially for sub-GeV mass dark matter. These constraints possess the advantage of covering a broader range of parameter space in terms of mediator decay length and dark matter mass, while being less susceptible to uncertainties associated with dark matter modeling. The Brown_Dwarf_Analysis offered as open-source software, allows users to replicate the findings of Bhattacharjee et al.,2023, and further extend the code for the analysis of other celestial bodies.