Forecasting the Sensitivity of Future MeV Gamma-Ray Telescopes in Constraining Dark Matter Decay and Annihilation

Core Concepts

This research paper forecasts the sensitivity of proposed MeV gamma-ray telescopes in constraining dark matter decay and annihilation, highlighting their potential to significantly improve current constraints, particularly for photon-rich final states.

Abstract

• Bibliographic Information: O’Donnell, K. E., & Slatyer, T. R. (2024). Constraints on Dark Matter with Future MeV Gamma-Ray Telescopes. arXiv preprint arXiv:2411.00087.
• Research Objective: This study aims to forecast the sensitivity of proposed MeV gamma-ray telescopes in constraining dark matter decay and annihilation for various Standard Model final states, comparing them to existing constraints.
• Methodology: The researchers employ the Fisher-matrix method to forecast constraints on dark matter decay lifetime and annihilation cross-section. They consider various decay/annihilation final states, including photons, electrons, muons, and pions, analyzing their photon spectra. The study incorporates background models for the Milky Way Galactic Center, Draco dwarf galaxy, and M31 galaxy, assuming an NFW dark matter density profile.
• Key Findings: The study reveals that the proposed instruments, particularly MAST, AdEPT, GECCO, e-ASTROGAM, and AMEGO, offer significant potential to improve current constraints on dark matter decay and annihilation. MAST demonstrates the strongest projected constraints within its energy range, while AdEPT excels outside this range. GECCO shows promise for lower-energy dark matter. The Galactic Center emerges as a more promising target for indirect detection compared to Draco and M31.
• Main Conclusions: The development of MeV gamma-ray telescopes holds substantial promise for advancing our understanding of dark matter. These instruments offer a significant leap in sensitivity, potentially enabling the detection or exclusion of dark matter signals, especially for photon-rich final states.
• Significance: This research provides valuable insights for the development and deployment of future MeV gamma-ray telescopes, guiding the search for dark matter and enhancing our understanding of the universe's composition.
• Limitations and Future Research: The study acknowledges limitations in neglecting instrumental and atmospheric backgrounds, which might impact sensitivity estimates. Future research could incorporate these backgrounds and explore alternative dark matter profiles beyond the NFW model. Additionally, analyzing lower-energy secondary photons from charged particle propagation could further refine the constraints on lepton decay and annihilation modes.

Stats

The observation time assumed for all projected constraints is Tobs = 10^6 s (approximately 11.6 days or 280 hours).
The study considers an observation region of 10° for both dark matter decay and annihilation.
The analysis focuses on six decay/annihilation final states: a photon pair, a photon and neutral pion, a neutral pion pair, an electron-positron pair, a muon/antimuon pair, and a pair of charged pions.
The research assumes an NFW (Navarro-Frenk-White) density profile for dark matter distribution.

Quotes

Key Insights Distilled From

Constraints on Dark Matter with Future MeV Gamma-Ray Telescopes

by Kayla E. O'D... at arxiv.org 11-04-2024

https://arxiv.org/pdf/2411.00087.pdf

Deeper Inquiries

How might the detection of dark matter through these telescopes impact our understanding of the evolution of the universe and galaxy formation?

Answer: Detecting dark matter through these MeV gamma-ray telescopes could revolutionize our understanding of the universe's evolution and galaxy formation in several ways:

Constraining Dark Matter Properties: Directly observing annihilation or decay products would provide crucial information about the nature of dark matter. This includes its mass, interaction cross-sections, and potential decay channels. Knowing these properties is essential for determining how dark matter fits into the broader picture of particle physics and cosmology.
Understanding the Early Universe: The properties of dark matter played a crucial role in the early universe, particularly during the formation of the first stars and galaxies. The observed abundance of dark matter today, combined with information about its interactions, can help us refine models of the early universe and potentially probe new physics beyond the Standard Model.
Mapping Dark Matter Distribution: These telescopes could map the distribution of dark matter in our galaxy and beyond. This would allow us to test the predictions of cosmological simulations, which generally assume a cold dark matter (CDM) scenario. By comparing the observed distribution with simulations, we can refine our understanding of how dark matter clumps together and influences the formation of large-scale structures.
Galaxy Formation and Evolution: Dark matter is believed to form the gravitational scaffolding upon which galaxies are built. Observing its distribution and properties can provide insights into the processes that drive galaxy formation and evolution. For example, the presence or absence of a dark matter "core" in dwarf galaxies can distinguish between different dark matter models and their impact on galaxy formation.
Unveiling New Physics: The detection of dark matter annihilation or decay products could point towards new particles and forces beyond the Standard Model. This would have profound implications for our understanding of fundamental physics and could open up entirely new avenues of research.
Overall, detecting dark matter through MeV gamma-ray telescopes would be a groundbreaking discovery with far-reaching implications for our understanding of the universe, from its earliest moments to the formation of galaxies like our own.

Could the assumption of an NFW dark matter profile be biasing the results, and how might alternative profiles affect the projected sensitivity of these instruments?

Answer: Yes, the assumption of a Navarro-Frenk-White (NFW) profile for dark matter could be biasing the results, and alternative profiles could significantly affect the projected sensitivity of these instruments. Here's why:

NFW Profile Assumptions: The NFW profile, while widely used, is based on simulations of cold dark matter and assumes a specific density distribution that increases towards the galactic center. However, other dark matter models and astrophysical processes could lead to different profiles.

Impact of Alternative Profiles:

Cored Profiles: Some models predict a "core" in the dark matter distribution, where the density remains relatively constant near the galactic center. This would lead to lower dark matter densities in the inner regions, reducing the expected signal from annihilation or decay and weakening the projected constraints.
Spiky Profiles: Conversely, some models predict "spiky" profiles with higher dark matter densities in the central regions. This could enhance the annihilation signal, potentially leading to stronger constraints than those derived assuming an NFW profile.
Substructure: The presence of dark matter subhalos within a galaxy could also affect the observed signal. These subhalos could contribute additional annihilation or decay products, potentially boosting the signal strength.

Sensitivity to Profile Uncertainties: The sensitivity of MeV gamma-ray telescopes to dark matter annihilation or decay is directly related to the dark matter density along the line of sight. Therefore, uncertainties in the dark matter profile translate into uncertainties in the projected sensitivity of these instruments.
How alternative profiles affect sensitivity:

Cored profiles would generally decrease the expected signal, making detection more challenging and weakening the constraints on dark matter properties.
Spiky profiles could increase the signal, potentially improving the sensitivity of these instruments and leading to stronger constraints.
Substructure could either enhance or diminish the signal depending on the distribution and properties of subhalos, making it crucial to account for these effects in data analysis.
Addressing Profile Uncertainties:

Multi-Target Observations: Observing multiple targets with different dark matter profiles, such as dwarf galaxies and galaxy clusters, can help break degeneracies and constrain the dark matter distribution more robustly.
Combining Data Sets: Combining data from different instruments, including gamma-ray telescopes, gravitational lensing surveys, and stellar kinematic studies, can provide a more comprehensive picture of the dark matter distribution and help distinguish between different profiles.
Improved Simulations: More sophisticated simulations that incorporate a wider range of dark matter models and astrophysical processes are crucial for reducing uncertainties in the predicted dark matter profiles.
In conclusion, while the assumption of an NFW profile provides a useful benchmark, it's essential to consider alternative profiles and their potential impact on the projected sensitivity of MeV gamma-ray telescopes. By combining data from multiple sources and improving our theoretical models, we can better constrain the dark matter distribution and enhance our ability to detect and characterize this elusive component of the universe.

What advancements in detector technology beyond those currently proposed could further enhance our ability to detect and characterize dark matter in the MeV range?

Answer: While the proposed MeV gamma-ray telescopes represent significant advancements, several technological breakthroughs could further enhance our ability to detect and characterize dark matter in this energy range:
1. Enhanced Sensitivity and Energy Resolution:

Larger Effective Area: Increasing the effective area of detectors would allow them to capture more photons, improving sensitivity, particularly for faint dark matter signals. This could involve developing larger instruments or deploying constellations of smaller telescopes working in unison.
Improved Energy Resolution: Better energy resolution would enable finer discrimination between signal and background, particularly for spectral features like lines from dark matter annihilation. This could be achieved through advancements in detector materials, readout electronics, and background rejection techniques.
2. Background Reduction and Control:

Active Shielding: Implementing active shielding mechanisms, such as anti-coincidence detectors, can help reject background events originating from cosmic rays and other sources, improving the signal-to-noise ratio.
Improved Background Modeling: Developing more accurate and detailed models of astrophysical backgrounds is crucial for distinguishing them from potential dark matter signals. This requires a combination of theoretical modeling, simulations, and observations across multiple wavelengths.
3. Novel Detector Technologies:

Liquid Xenon Time Projection Chambers (LXeTPCs): LXeTPCs offer excellent energy resolution and background rejection capabilities. Scaling up this technology for space-based applications could significantly enhance sensitivity to MeV gamma rays.
Compton Telescopes with Improved Imaging: Advancements in Compton telescope technology, such as coded masks and improved tracking detectors, could provide better angular resolution, enabling more precise localization of dark matter signals.
Metamaterials and Photonic Crystals: Exploring the use of metamaterials and photonic crystals in gamma-ray detectors could lead to novel designs with enhanced sensitivity and directionality.
4. Multi-Messenger Approaches:

Combining Gamma-Ray and Neutrino Observations: Simultaneous observations with neutrino telescopes could provide complementary information about dark matter annihilation or decay, as some models predict the production of both gamma rays and neutrinos.
Correlating with Gravitational Wave Events: Searching for coincident gamma-ray signals with gravitational wave events from merging black holes or neutron stars could reveal connections between dark matter and these extreme astrophysical phenomena.
5. Advanced Data Analysis Techniques:

Machine Learning: Implementing machine learning algorithms can improve signal detection, background rejection, and data analysis efficiency, particularly for large and complex datasets.
Multi-Parameter Analysis: Developing sophisticated statistical methods that simultaneously analyze multiple parameters, such as energy, direction, and time, can enhance sensitivity to subtle dark matter signals.
By pursuing these technological advancements and combining them with innovative data analysis techniques, we can significantly improve our ability to detect and characterize dark matter in the MeV range, potentially unlocking one of the biggest mysteries in modern physics and cosmology.