Explicit Stabilized Multirate Methods for the Monodomain Model in Cardiac Electrophysiology

Temel Kavramlar

Fully explicit stabilized multirate methods are efficient for solving stiff ordinary differential equations, with the emRKC method offering improved stability and efficiency for cardiac electrophysiology.

Özet

The content discusses explicit stabilized multirate methods, focusing on the emRKC method's application to the monodomain model in cardiac electrophysiology. It introduces mathematical models and numerical analysis techniques, emphasizing stability and efficiency in solving stiff ordinary differential equations. The article presents a detailed comparison of mRKC and emRKC methods through numerical experiments, highlighting their performance advantages. Additionally, it explores the structure of fE in the context of exponential Euler integration to enhance computational efficiency.
Mathematical Modelling and Numerical Analysis:

Explicit stabilized multirate methods are suitable for solving large multiscale systems of stiff ordinary differential equations.
The emRKC method is tailored for the monodomain model in cardiac electrophysiology.
Code profiling demonstrates that emRKC is faster and parallelizable without compromising accuracy.
Data Extraction:

"Several numerical experiments are conducted to evaluate the efficiency of both mRKC and emRKC."
"The new emRKC method typically outperforms a standard implicit-explicit baseline method."
Quotations:

"Fully explicit stabilized multirate (mRKC) methods are well-suited for the numerical solution of large multiscale systems of stiff ordinary differential equations."
"The new emRKC method typically outperforms a standard implicit-explicit baseline method for cardiac electrophysiology."

İstatistikler

Several numerical experiments are conducted to evaluate the efficiency of both mRKC and emRKC.
The new emRKC method typically outperforms a standard implicit-explicit baseline method.

Alıntılar

Fully explicit stabilized multirate (mRKC) methods are well-suited for the numerical solution of large multiscale systems of stiff ordinary differential equations.
The new emRKC method typically outperforms a standard implicit-explicit baseline method for cardiac electrophysiology.

Önemli Bilgiler Şuradan Elde Edildi

Explicit stabilized multirate methods for the monodomain model in cardiac electrophysiology

by Giacomo Rosi... : arxiv.org 03-26-2024

https://arxiv.org/pdf/2401.01745.pdf

Daha Derin Sorular

How do explicit stabilized multirate methods compare to implicit schemes in terms of computational cost

Explicit stabilized multirate methods are advantageous compared to implicit schemes in terms of computational cost. Explicit methods, such as the explicit stabilized Runge-Kutta-Chebyshev (RKC) method, strike a balance between explicit and implicit schemes by adapting the number of stages according to the stiffness of the system. This adaptability allows for more efficient parallel implementation and smoother dependence on stiffness, leading to improved stability properties. In contrast, implicit schemes require sophisticated solvers for linear or nonlinear systems, making them more computationally expensive per time step.

What implications does the use of exponential Euler integration have on improving computational efficiency

The use of exponential Euler integration in improving computational efficiency is significant because it stabilizes discrete dynamical systems unconditionally while being relatively cheap to compute when dealing with diagonal matrices like those found in stiff components such as fE in cardiac electrophysiology models. The exponential Euler method dampens large eigenvalues and ensures stability without imposing stringent constraints on the step size or increasing computational complexity significantly. By integrating fE using an exponential approach within a multirate framework like emRKC, accuracy can be maintained without sacrificing efficiency.

How can these mathematical models be applied beyond cardiac electrophysiology to other fields

These mathematical models developed for cardiac electrophysiology can be applied beyond this specific field to other areas that involve solving large multiscale systems of stiff ordinary differential equations (ODEs). For example:

Neuroscience: Modeling neural activity propagation through brain networks.
Chemical Engineering: Simulating chemical reactions with complex kinetics and diffusion processes.
Climate Science: Studying atmospheric dynamics involving multiple interacting variables.
Biomedical Engineering: Analyzing physiological processes at cellular levels with intricate interactions.
By applying these explicit stabilized multirate methods tailored for stiff ODEs efficiently across various disciplines, researchers can enhance numerical simulations' accuracy and speed up computations in diverse scientific domains.