In partial fulfillment of the requirements for the degree of 

Doctor of Philosophy in Computational Science and Engineering

School of Physics Thesis Dissertation Defense

Lynn Jin 

Advisor: Dr. Flavio H. Fenton, School of Physics, Georgia Institute of Technology

Propagation Dynamics in Cardiac Tissue: From Alternans Formation to Defibrillation

Date: Friday, November 21, 2025 

Time: 1:00 p.m.

Location: CODA C0915

Meeting Link: Lynn Jin Thesis Dissertation Defense

Committee Members: 

Dr. Elizabeth M. Cherry, School of Computational Science and Engineering, Georgia Institute of Technology

Dr. JC Gumbart, School of Physics, Georgia Institute of Technology

Dr. Xiuwei Zhang, School of Computational Science and Engineering, Georgia Institute of Technology

Dr. Alessandro Loppini, Departmental Faculty of Medicine and Surgery, Campus Bio-Medico University of Rome

Abstract: 

Cardiovascular disease is the leading cause of death worldwide, and many fatal events are caused by cardiac arrhythmias. Clinically, T-wave alternans is an important marker of arrhythmia and death. Electrical cardioversion is the standard shock-based treatment used to restore normal rhythm clinically, but current devices rely on high-energy shocks, which can be painful and may cause tissue damage. To develop safer, low-energy alternatives, we need to better understand alternans dynamics and how external electric fields interact with unstable electrical activity in the heart.

This thesis focuses on two related questions. First, we study how spatial coupling in cardiac tissue affects alternans and wave stability by introducing fractional diffusion, a modeling approach that captures the physiological characteristics of structural heterogeneity. Using the Beeler–Reuter model and the Fenton–Karma model, we identify the conditions under which fractional diffusion only changes the spatial length scale of alternans without altering alternans dynamics. This helps tackling the alternans size mismatch problem between experiments and numerical simulations, improving the predictive power of simulations.

Second, we simulate fibrillation in two-dimensional tissue and study the efficacy of rotational electric fields for defibrillation. Through voltage maps and phase singularity analysis, we present examples demonstrating that rotational fields can defibrillate better than static electric fields when applied at the same amplitude, suggesting that the use of rotational electric field may be a more effective low-energy defibrillation approach.

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