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# Physics# Cosmology and Nongalactic Astrophysics

Investigating Mixed Dark Matter Models with Axions

Researching the coexistence of dark matter types offers new insights into cosmic structures.

Tibor Dome, Simon May, Alex Laguë, David J. E. Marsh, Sarah Johnston, Sownak Bose, Alex Tocher, Anastasia Fialkov

― 5 min read


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Table of Contents

Dark matter is a type of matter that does not emit, absorb, or reflect light, making it invisible to current telescopes. It is thought to make up about 27% of the Universe's mass-energy content. Despite being unseen, dark matter has a significant impact on the Universe, influencing the formation and behavior of galaxies and galaxy clusters.

One leading candidate for dark matter is Ultralight Axions, a theoretical type of particle that could help explain certain phenomena observed in cosmic structures. These axions are incredibly light, with masses much lower than those of traditional matter particles. They are derived from theories in particle physics, including both field theory and string theory.

The Concept of Mixed Dark Matter Models

In recent research, scientists have begun to explore mixed dark matter (MDM) models where ultralight axions do not constitute all the dark matter in the universe. Instead, they can coexist with other types of dark matter, such as Cold Dark Matter (CDM). This approach allows researchers to investigate the effects of varying axion fractions while still adhering to observational data.

By relaxing the assumption that ultralight axions are the sole component of dark matter, researchers aim to develop a more versatile framework for understanding cosmic structures and the dynamics of the universe.

Simulation of Dark Matter Dynamics

To study these models, scientists implement large-scale simulations that use advanced computational techniques. These simulations help capture the dynamics of dark matter interactions across different scales. Key to these efforts is a gravity solver specifically designed for MDM, allowing researchers to track how dark matter behaves under various conditions.

The simulations focus on the large-scale structure of the universe, including the formation of Halos, which are clusters of dark matter and other matter that can host galaxies. By analyzing how these halos form and evolve, scientists can glean insights into the underlying physics of dark matter.

Findings from Halo Simulations

Through the simulations, researchers use techniques like the Rockstar halo finder to identify and categorize halos in different cosmological models. The results show that the mass functions and concentration relations of these halos align well with theoretical predictions, suggesting that the applied methods are valid.

For ultralight axion models, the halo mass functions indicate how many halos exist at different mass scales. The relationship between the mass of halos and their density offers further insights into how these structures are formed and evolve over time.

Axion Halo Mass and Cold Halo Mass Relations

A significant aspect of the research focuses on the relationship between the mass of axion halos and the mass of cold halos. By calibrating these relationships against simulation data, scientists can refine models to better predict how axion halos interact within the overall structure of dark matter.

Researchers have found that these relationships are more complex than previously thought, leading to the development of new analytical forms that capture the nuances of axion mass dynamics. The results suggest that lower mass halos show significant deviations from expected behavior, challenging traditional models of halo formation.

The Role of Cosmological Parameters

The cosmological parameters used in simulations play a crucial role in determining the behavior of dark matter. By adjusting these parameters, researchers can explore different scenarios and assess how varying axion fractions impact the larger dark matter landscape.

By incorporating a range of cosmological models, scientists can analyze the implications for structure formation across different epochs of the universe, providing greater context for observational data obtained from telescopes and other instruments.

Challenges in Mixed Dark Matter Models

While MDM models show promise, they also present various challenges. For instance, accurately modeling the interactions and dynamics of multiple dark matter components can be computationally demanding. Additionally, ensuring that simulations capture the complex behaviors of axion dynamics while remaining computationally efficient requires careful planning and execution.

Researchers must also address the limitations of their models, considering factors such as baryonic physics, which influences how normal matter interacts with dark matter. Integrating these effects into simulations is essential for developing a comprehensive understanding of the universe's structure.

Future Directions

Going forward, scientists are focused on refining their models and improving simulation methodologies. Advances in computational techniques and data analysis will enhance the ability to explore mixed dark matter scenarios, potentially leading to new insights about the nature of dark matter.

Future observations from telescopes and other instruments will also be critical for validating theoretical models and uncovering new evidence about the universe's structure and evolution. By continuously iterating on simulations and incorporating new data, researchers aim to develop a clearer picture of how ultralight axions and other dark matter components interact.

Summary

In summary, the study of mixed dark matter models involving ultralight axions represents a promising avenue for understanding the complexities of dark matter. By employing sophisticated simulations and refining theoretical frameworks, scientists are working to unpack the mysteries of the universe’s unseen matter and its role in shaping cosmic structures. The insights gained from these efforts have the potential to unlock new knowledge about the fundamental nature of reality itself.

Original Source

Title: Improved Halo Model Calibrations for Mixed Dark Matter Models of Ultralight Axions

Abstract: We study the implications of relaxing the requirement for ultralight axions to account for all dark matter in the Universe by examining mixed dark matter (MDM) cosmologies with axion fractions $f \leq 0.3$ within the fuzzy dark matter (FDM) window $10^{-25}$ eV $\lesssim m \lesssim 10^{-23}$ eV. Our simulations, using a new MDM gravity solver implemented in AxiREPO, capture wave dynamics across various scales with high accuracy down to redshifts $z\approx 1$. We identify halos with Rockstar using the CDM component and find good agreement of inferred halo mass functions (HMFs) and concentration-mass relations with theoretical models across redshifts $z=1-10$. This justifies our halo finder approach a posteriori as well as the assumptions underlying the MDM halo model AxionHMcode. Using the inferred axion halo mass - cold halo mass relation $M_{\text{a}}(M_{\text{c}})$ and calibrating a generalised smoothing parameter $\alpha$ to our MDM simulations, we present a new version of AxionHMcode. The code exhibits excellent agreement with simulations on scales $k< 20 \ h$ cMpc$^{-1}$ at redshifts $z=1-3.5$ for $f\leq 0.1$ around the fiducial axion mass $m = 10^{-24.5}$ eV $ = 3.16\times 10^{-25}$ eV, with maximum deviations remaining below 10%. For axion fractions $f\leq 0.3$, the model maintains accuracy with deviations under 20% at redshifts $z\approx 1$ and scales $k< 10 \ h$ cMpc$^{-1}$, though deviations can reach up to 30% for higher redshifts when $f=0.3$. Reducing the run-time for a single evaluation of AxionHMcode to below $1$ minute, these results highlight the potential of AxionHMcode to provide a robust framework for parameter sampling across MDM cosmologies in Bayesian constraint and forecast analyses.

Authors: Tibor Dome, Simon May, Alex Laguë, David J. E. Marsh, Sarah Johnston, Sownak Bose, Alex Tocher, Anastasia Fialkov

Last Update: 2024-09-17 00:00:00

Language: English

Source URL: https://arxiv.org/abs/2409.11469

Source PDF: https://arxiv.org/pdf/2409.11469

Licence: https://creativecommons.org/licenses/by/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to arxiv for use of its open access interoperability.

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