In relativistic heavy-ion collisions, where quark-gluon plasma forms, hadron production is anisotropic at both low and high transverse momentum, driven by flow dynamics and spatial anisotropies. To better understand these mechanisms, we use multiparticle correlations to reconstruct jet anisotropies. We simulate data using tenngen as a hydrolike background and combine it with pythia-8-generated jets, clustering them with the anti-$k_t$ algorithm. Jet anisotropies are unfolded using a Bayesian technique, ensuring the robustness of the reconstructed signals. Our results demonstrate that multiparticle cumulant methods can accurately capture the differential jet azimuthal anisotropies, providing crucial insights into high-$p_T$ behavior and the dynamics within heavy-ion collisions.

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• Collective flow
• Jets & heavy flavor physics
• Particle correlations & fluctuations