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February 12, 2026Symmetry1 citationsOpen Access

Generalized Laplace Transform for Higher-Order Hybrid Fractional Cauchy Problems: Theory and Applications to Memory-Dependent Dynamics

SCSamten ChodenJSJakgrit SompongETEkkarath Thailert

Key Points

  • The aim is to establish a generalized Laplace transform framework for higher-order hybrid fractional Cauchy problems.
  • Developed a framework on weighted function spaces.
  • Derived explicit transformation formulas for δψ-derivatives and ψ-Hilfer fractional derivatives.
  • Formulated solutions using a bivariate Mittag–Leffler function.
  • Conducted numerical comparisons with classical integer-order models.
  • Demonstrated the symmetry between integer-order δψ operators and fractional ψ-Hilfer derivatives.
  • Closed-form solutions were established for specific hybrid fractional models.
  • Numerical simulations revealed significant differences in amplitude and damping behavior compared to integer-order counterparts.

Abstract

This paper develops a generalized Laplace transform framework on weighted function spaces Cδψ,γna,b, establishing a symmetry between integer-order δψ operators and fractional ψ-Hilfer derivatives at the level of transform representations. Explicit transformation formulas are derived for the nth-order δψ-derivative and the ψ-Hilfer fractional derivative of order α∈(m−1,m), with m≤n. These results form an analytical basis for the treatment of higher-order hybrid fractional Cauchy problems that systematically couple integer-order and fractional operators subject to mixed initial conditions. The general solution is expressed in closed form using a bivariate Mittag–Leffler function. To illustrate the utility of the approach, a representative second-order hybrid model is studied and compared numerically with its classical integer-order counterpart. The simulations reveal significant differences in the dynamical response, including variations in amplitude, damping behavior, and long-term evolution.

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Cite This Study

Choden et al. (2026) studied this question.

synapsesocial.com/papers/698d6edc5be6419ac0d54b0chttps://doi.org/10.3390/sym18020333
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