THE LIPSCHITZIAN FRACTIONAL DERIVATIVE: USING THE LIPSCHITZ EXPONENT TO UNIFY SPATIAL IRREGULARITY AND TEMPORAL MEMORY

Fractals Pub Date : 2026-08-22 DOI:10.1142/s0218348x26501318
YHOSVANY SOLER-CASTILLO,J. F. GÓMEZ-AGUILAR,C. JUNG,J. A. HERNÁNDEZ
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Abstract

The study proposes a new fractional operator termed the Lipschitzian Fractional Derivative (LFD) that directly links the differentiation order to the Lipschitz Exponent (LE) of functions. This means that instead of enforcing a fixed fractional order, the operator adjusts to the function’s actual smoothness or irregularity. The derivative naturally connects fractional calculus (order-based) and fractal calculus (dimension-based), since the LE can be understood as a measure of local fractal dimension. It is therefore a bridge operator. It unifies spatial irregularity (fractal dimension) and temporal smoothness (fractional order). This implies that memory effects and fractal geometry can be described simultaneously by a single operator. The Atangana operators provide a natural generalization of the Marchaud derivative in fractal contexts. They allow modeling of systems where both temporal memory and spatial fractality overlap, for example, diffusion in porous media, or anomalous transport in astrophysical systems. A natural way to combine smoothness-based fractional operators with dimension-based fractal operators is to tie the differentiation order directly to the LE. In this manner, the operator uses only one parameter rather than the two of Atangana’s operators to encode both the regularity of the function and the fractality of the geometry. This could lead to a common framework for researching singularities, anomalous diffusion, and fractal dynamics in applied mathematics, physics, and engineering.
李普希茨分数阶导数:利用李普希茨指数统一空间不规则性和时间记忆
本文提出了一种新的分数算子Lipschitz分数导数(LFD),它将函数的微分阶与函数的Lipschitz指数(LE)直接联系起来。这意味着操作符不是强制执行固定的分数顺序,而是根据函数的实际平滑性或不规则性进行调整。导数自然地将分数阶微积分(基于阶数)和分形微积分(基于维数)联系起来,因为LE可以理解为局部分形维数的度量。因此它是一个桥算符。它统一了空间不规则性(分维)和时间平滑性(分数阶)。这意味着记忆效应和分形几何可以用一个算子同时描述。Atangana算子提供了分形环境下Marchaud导数的自然推广。它们允许对时间记忆和空间分形重叠的系统进行建模,例如,多孔介质中的扩散,或天体物理系统中的异常输运。结合基于平滑的分数算子和基于维数的分形算子的一种自然方法是将微分阶直接与LE联系起来。通过这种方式,算子只使用一个参数而不是两个Atangana算子来编码函数的正则性和几何的分形。这可能导致在应用数学、物理和工程中研究奇点、异常扩散和分形动力学的共同框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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