We develop a general algorithm that enables the consistent embedding of any four-dimensional static and spherically symmetric geometry into any five-dimensional single-brane braneworld model, characterized by an injective and nonsingular warp factor. Furthermore, we supplement the algorithm by introducing a method that allows one to, in principle, reconstruct 5D field theories that support the...
Pushing beyond the boundaries of general relativity has long been a major goal in both theoretical and experimental physics, especially in the pursuit of a quantum theory of gravity and the explanation of cosmological phenomena like dark energy and cosmic acceleration. Constructing modified gravity models often leads to additional degrees of freedom, but these can also introduce problematic,...
The spectra of stable particles such as photons, positrons,
antiprotons and neutrinos are one of the main ingredients to calculate
the fluxes of cosmic rays and radiation searched for in indirect
detection experiments. The modeling of the whole process is however
very complicated since after dark matter annihilation or decay, a
number of phenomena occur: including resonance decays,...
Recent advances in machine learning (ML), particularly neural density
estimation like normalizing flows, diffusion models, and flow
matching, have opened new doors for high-precision, model-independent
density estimation.
These techniques are highly valuable for galactic dynamics studies, as
they allow us to estimate the distribution of stars in phase space
(position and velocity)...
