AdvancedHMC.jl implements advanced Hamiltonian Monte Carlo (HMC) algorithms for Markov chain Monte Carlo sampling in Julia. The package provides modular components for constructing HMC samplers, including customizable metrics, trajectory integrators, and adaptation strategies. It supports state-of-the-art methods such as the No-U-Turn Sampler (NUTS) and integrates with the LogDensityProblems.jl interface for defining target probability distributions, with optional automatic differentiation backends. AdvancedHMC.jl is a backend for probabilistic programming frameworks such as Turing.jl or directly for flexible MCMC sampling workflows requiring fine-grained control.