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First-passage time for the g-subdiffusion process of vanishing particles
1Institute of Physics, Jan Kochanowski University, Uniwersytecka 7, 25-406 Kielce, Poland.
This study models subdiffusion and molecule survival using fractional calculus, deriving first-passage time distributions. The findings reveal how timescale changes influence molecular processes and their vanishing probabilities.
Area of Science:
- Physics
- Chemistry
- Mathematical Modeling
Background:
- Subdiffusion describes anomalous molecular movement where particles move slower than predicted by Brownian motion.
- Molecule survival equations model the probability of a molecule persisting over time, considering decay or disappearance.
- Fractional calculus offers advanced tools to describe complex, non-local temporal dynamics in physical and chemical processes.
Purpose of the Study:
- To develop a unified mathematical framework for subdiffusion with time-dependent vanishing probabilities.
- To derive the first-passage time distribution for this combined process.
- To analyze the interplay between subdiffusion dynamics and molecule disappearance rates.
Main Methods:
- Utilizing Caputo fractional time derivatives with respect to general time-scaling functions g1 and g2.
- Deriving the first-passage time probability distribution function.
- Analyzing the specific case where g1 is identical to g2, indicating a strong coupling between subdiffusion and survival.
Main Results:
- The study successfully derives the first-passage time distribution for subdiffusion with time-dependent molecule vanishing.
- It demonstrates how the functions g1 and g2 modify the characteristic timescales of both subdiffusion and survival.
- A significant finding is the ability to model the mutual influence of these processes when g1 and g2 are related.
Conclusions:
- The developed model provides a flexible approach to studying complex molecular dynamics involving anomalous diffusion and decay.
- The first-passage time distribution is a key metric for understanding the temporal behavior of such systems.
- The framework highlights the importance of considering coupled dynamics for accurate predictions in related scientific fields.
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