Reconstructing jet anisotropies with cumulants

TL;DR

Understanding jet azimuthal anisotropies at high-$p_T$ in heavy-ion collisions is essential for revealing jet–medium interactions in the QGP. The authors combine a hydro-like TennGen background with Pythia-8 jets, cluster with anti-$k_T$, and use 2- and 4-particle cumulants with Bayesian unfolding to extract the differential jet anisotropies $v_n^{\mathrm{jet}}(p_T)$, mitigating non-flow and momentum-smearing effects. They demonstrate that unfolded cumulants faithfully reproduce input jet anisotropies across multiple harmonic orders and jet-$p_T$ dependences, validating robustness to various $v_n^{\mathrm{jet}}(p_T)$ forms via response-matrix variations. This work provides a practical framework to study jet-driven anisotropies in both large and small systems, offering a path to disentangle long- and short-range correlations and to improve understanding of jet quenching dynamics.

Abstract

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 multi-particle correlations to reconstruct jet anisotropies. We simulate data using \textsc{TennGen}\xspace as a hydro-like background and combine it with \textsc{Pythia-8}\xspace generated jets, clustering them with the anti-$k_{\mathrm{t}}$\xspace algorithm. Jet anisotropies are unfolded using a Bayesian technique, ensuring the robustness of the reconstructed signals. Our results demonstrate that multi-particle cumulant methods can accurately capture the differential jet azimuthal anisotropies, providing crucial insights into high-$p_{T}\xspace$ behavior and the dynamics within heavy-ion collisions.

Figures (4)

• Figure 1: The dependence of $v_{n}^{\mathrm{jet}}$ on jet $p_{T}$ for functions used to realign leading PYTHIA jets in Pythia-8+TennGen events. These include three $p_T$ independent constant values of $v^{\text{jet}}_{n}$ (red, black, and orange dotted lines), a $v^{\text{jet}}_{n}(p_T)$ which increases with $p_T$ (blue dotted line), and a physically unrealistic sinusoidal dependence on $p_T$ (green dotted line). The $y$-axis is scaled by $a_n$.
• Figure 2: Comparisons of the $v^{\text{jet}}_{2}\{2\}$ calculated with unfolded $\langle 2^{\prime}_{2} \rangle ^{\text{corr}}$ for Pythia-8+TennGen events with a $p_T$ independent truth $v_2^{\text{jet}} = 4\%$, unfolded with response matrices constructed from Pythia-8+TennGen events where $v_2^{\text{jet}} = 4\%$ (Response Matrix A), a scaled constant $v_2^{\text{jet}} = 5\times 4\%$ (Response Matrix B), and a linear $p_T$ dependence $v_2^{\text{jet}}(p_{T}) = 4\% + (0.1\%)\times p_T$ (Response Matrix C). The dashed line represents the true constant $v^{\text{jet}}_{2} = 4\%$ of the unfolded sample.
• Figure 3: The $p_{T}\xspace$ dependence of $v^{\text{jet}}_{n}\{2k\}$ for harmonic order $n = 2, 3$, and $4$, represented by the red squares, purple triangles, and blue circles, respectively. Values calculated using $2$- and $4$-particle correlations are differentiated by full ($k=1$) or open ($k=2$) symbols. The dashed line represents the true $v^{\text{jet}}_{n}(p_{T})$ values.
• Figure 4: Comparison of the $p_{T}\xspace$ dependence of the $v^{\text{jet}}_{2}\{2k\}$ for Au+Au collisions at 200 Ge V calculated with $2$-particle ($k=1$) and $4$-particle ($k=2$) correlations. The dashed line represents the true $v^{\text{jet}}_{n}(p_{T})$ values. The unfolded $v^{\text{jet}}_{2}\{2k\}$$v_2^{\text{jet}} = 4\%$$\textbf{(a)}$, a linear $p_T$ dependence $v_2^{\text{jet}}(p_{T}) = 4\% + (0.1\%)\times p_T$$\textbf{(b)}$, and a sinusoidal $p_T$ dependence $v^{\text{jet}}_{n} = 4\%\times[2+\cos{0.2 p_{T}}]$$\textbf{(c)}$.