Understanding real-time flux-tube dynamics in more than one spatial dimension is key to unlocking the non-perturbative physics of confinement, and is now actively pursued by quantum computing and simulation experiments. However, describing such dynami
Understanding real-time flux-tube dynamics in more than one spatial dimension is key to unlocking the non-perturbative physics of confinement, and is now actively pursued by quantum computing and simulation experiments. However, describing such dynamics has proven to be extremely challenging with both experiments and state-of-the-art numerical simulations limited to small volumes and short timescales. Here we investigate flux tube statics and real-time evolution in a genuine two-dimensional Z_2 Higgs gauge theory at system sizes and timescales order of magnitude beyond present experiments and numerics. The key enabling element is the recently introduced Clifford-augmented matrix product states (CAMPS) framework, which we demonstrate to parametrically reduce the entanglement that must be represented in the matrix product state; both in the pure-gauge limit and in the presence of dynamical matter. We benchmark this capability through stringent tests of effective string theory, including universal spectral features and flux tube roughening properties in presence of matter. We then introduce a string-pull protocol that selectively excites transverse modes and reconstructs their finite-size spectrum in real time. In the rough regime, the response is collective, and our simulations show that this is also well captured by universal effective string theory predictions. Strong confinement instead produces long-lived, lattice-locked local dynamics persisting to times tJ \gtrsim 100. These results provide ab initio evidence that effective string theory captures nonequilibrium string dynamics and reveal a hitherto unexplored long-lived prethermal regime of strongly confined flux tubes, providing a novel angle on how confinement dictates dynamics in more than one spatial dimension.