Driven dynamics of localization phase transition in the Aubry-André model with initial gapless extended states

Recently, the driven dynamics of localization phase transition have garnered growing interest. However, studies so far have mainly considered initial localized states, whose driven dynamics follow the Kibble-Zurek mechanism (KZM). In this study, we investigate the driven dynamics of the localization phase transition in the Aubry-André model starting from a gapless extended state, which violates the adiabatic-impulse scenario of KZM. By linearly driving the quasiperiodic potential strength across the critical point, we numerically simulate the driven dynamics and analyze the scaling behavior of both the inverse participation ratio ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"> <a:mi mathvariant="script">I</a:mi> </a:math> ) and the dynamic deviation from the instantaneous ground-state energy <c:math xmlns:c="http://www.w3.org/1998/Math/MathML"> <c:mrow> <c:mo>(</c:mo> <c:mi mathvariant="script">D</c:mi> <c:mo>)</c:mo> </c:mrow> </c:math> . We demonstrate that the driven dynamics starting from initially extended states satisfies the criterion for the applicability of KZM and its extension, finite-time scaling (FTS). The scaling functions governing the driven dynamics of both <e:math xmlns:e="http://www.w3.org/1998/Math/MathML"> <e:mi mathvariant="script">I</e:mi> </e:math> and <g:math xmlns:g="http://www.w3.org/1998/Math/MathML"> <g:mi mathvariant="script">D</g:mi> </g:math> have been derived based on FTS and numerically validated. We found that the scaling functions exhibit significant differences at large <i:math xmlns:i="http://www.w3.org/1998/Math/MathML"> <i:mi>R</i:mi> </i:math> and small <j:math xmlns:j="http://www.w3.org/1998/Math/MathML"> <j:mi>R</j:mi> </j:math> , and also differ considerably from the scaling functions when the initial state is localized, highlighting the crucial role of initial-state behavior. The established scaling laws remain robust across a wide range of system sizes and driving rates, providing testable predictions for experimental realizations.