\begin{document}$m_{\phi^{0}}, \sqrt{s}$\end{document}) to investigate the process of \begin{document}$\gamma\gamma \rightarrow H^{+}H^{-}$\end{document}. Three particular numerical scenarios, i.e., low-\begin{document}$m_{H}$\end{document}, non-alignment, and short-cascade are employed. The decay channels for charged Higgs particles are examined using \begin{document}$h^{0}$\end{document} for low-\begin{document}$m_{H^{0}}$\end{document} and \begin{document}$H^{0}$\end{document}for non-alignment and short-cascade scenarios incorporating the new experimental and theoretical constraints along with the analysis for cross-sections. We find that, at a low energy, the cross-section is consistently higher for all scenarios. However, as\begin{document}$\sqrt{s}$\end{document} increases, it reaches a peak value at 1\begin{document}$~$\end{document}TeV for all benchmark scenarios. The branching ratio of the decay channels indicates that for non-alignment, the mode of decay \begin{document}$W^{\pm} h^{0}$\end{document} takes control, and for a short cascade, the prominent decay mode remains \begin{document}$t\overline {b}$\end{document}, whereas in the low-\begin{document}$m_{H}$\end{document}scenario, the dominant decay channel is of \begin{document}$W^{\pm} h^{0}$\end{document}. In our research, we employ contemporary machine-learning methodologies to investigate the production of high-energy Higgs bosons within a 3.0 TeV \begin{document}$\gamma\gamma$\end{document} collider. We have used multivariate approaches such as Boosted Decision Trees (BDT), LikelihoodD, and Multilayer Perceptron (MLP) to show the observability of heavy-charged Higgs Bosons versus the most significant Standard Model backgrounds. The purity of the signal efficiency and background rejection are measured for each cut value."> Probing heavy charged Higgs bosons at gamma-gamma colliders using a multivariate technique -
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