Dark matter is a kind of matter in the cosmos that does not absorb, reflect, or emit light, making direct detection impossible. Astrophysicists and cosmologists around the world have been attempting to indirectly discover this elusive form of stuff in recent years in order to better comprehend its unique properties and makeup.
"Fuzzy dark matter," a hypothesised kind of dark matter made up of extremely light scalar particles, is one of the most promising candidates for dark matter. Due to its peculiar properties, this form of matter is known to be challenging to replicate.
Researchers from Spain's Universidad de Zaragoza and Germany's Institute for Astrophysics recently developed a new way for simulating the fuzzy dark matter that forms a galaxy halo. This strategy, which was described in a study published in Physical Review Letters, is based on a modification of an algorithm that the team had previously developed.
"One of the numerical challenges for studies focusing on fuzzy dark matter is that its distinguishing features, granular density fluctuations in collapsed halos and filaments, are orders of magnitude smaller than any cosmological simulation box large enough to accurately capture the dynamics of the cosmic web," said Bodo Schwabe, one of the study's authors. "As a result, for years, people have tried to combine cheap numerical methods for capturing large-scale dynamics with computationally costly algorithms that can accurately evolve these density variations."
Schwabe and his colleague Jens C. Niemeyer updated and enhanced an algorithm that they had proposed in previous work as part of their new study. So far, their technology is the only one that can be utilised to run fuzzy dark matter cosmological simulations successfully.
The researchers were able to model the collapse of the cosmic web into filaments and halos using their modified algorithm. The "n-body approach," which separates the "initial density field" into microscopic particles that freely evolve under the force of gravity, was used to accomplish this.
"The n-body method is a very stable, well-tested, and efficient method," Schwabe explained, "but it misses the density changes of the intervening fuzzy dark matter field in filaments and halos." "We switched to a different algorithm, known as the finite difference method, in a tiny sub-volume of our simulation box tracing the centre of a pre-selected halo, which directly evolves the fuzzy dark matter wave function and can thus capture its interfering modes yielding the characteristic granular density fluctuations."
While cosmological simulations using the n-body and finite difference approaches are common in astrophysics around the world, they are rarely utilised together. Schwabe and Niemeyer used these two approaches in their simulations, relying on the moderation between them on the surface of the sub-volume.
The mechanism they utilised, in particular, promotes n-body particles to coherent wave packets known as "Gaussian beams." The superposition of these elements resulted in a fuzzy dark matter wave function near their intersection, allowing them to run simulations.
"Our successful combination of n-body and finite difference approaches pave the door for realistic cosmological fuzzy dark matter simulations," Schwabe said. "These simulations may include the colliding of two or more fuzzy dark matter halos, the evolution of star clusters within a halo, or their interaction with the central solitonic core, whose random wandering could potentially heat up or disturb the star cluster."
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