This study employs Monte Carlo (MC) models and thermal-statistical analysis to investigate the production mechanisms of strange (
,
) and multi-strange (
,
) hadrons in high-multiplicity proton–proton collisions. Through systematic comparisons with experimental data, we
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This study employs Monte Carlo (MC) models and thermal-statistical analysis to investigate the production mechanisms of strange (
,
) and multi-strange (
,
) hadrons in high-multiplicity proton–proton collisions. Through systematic comparisons with experimental data, we evaluate the predictive power of EPOS, PYTHIA8, QGSJETII04, and Sibyll2.3d. EPOS, with its hydrodynamic evolution, successfully reproduces low-
and
yields in high-multiplicity classes (MC1–MC3), mirroring quark-gluon plasma (QGP) thermalization effects. PYTHIA8’s rope hadronization partially mitigates mid-
multi-strange baryon suppression but underestimates
and
yields due to the absence of explicit medium dynamics. QGSJETII04, tailored for cosmic-ray showers, overpredicts soft
yields from excessive soft Pomeron contributions and lacks multi-strange hadron predictions due to enforced decays. Sibyll2.3d’s forward-phase bias limits its accuracy at midrapidity. No model fully captures
and
production, though EPOS remains the closest. Complementary Tsallis distribution analysis reveals a distinct mass-dependent hierarchy in the extracted effective temperature (
) and non-extensivity parameter (
q). As multiplicity decreases,
rises while
q declines—a trend amplified for heavier particles. This suggests faster equilibration of heavier particles compared to lighter species. The interplay of these findings underscores the necessity of incorporating QGP-like medium effects and refined strangeness enhancement mechanisms in MC models to describe small-system collectivity.
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