Poster Session 4, 2:15 PM - 3:00 PM: Campus Center Auditorium [A23]

Presenter: Ayush Nadiger

Faculty Sponsor: Chris Cox

School: UMass Amherst

Research Area: Electrical and Computer Engineering

ABSTRACT

Trapped ions are a leading platform for quantum computing, but their performance is currently limited by "anomalous heating", a phenomenon where electric field noise from the trap electrodes destroys the ion's quantum information. While it is known that the distance between the ion and the electrode affects this noise, the impact of complex 3D trap shapes and microscopic surface roughness remains poorly understood. This research develops a novel computational framework to predict how trap shape influences heating rates. Rather than relying solely on experimental measurements, we model the trap interior as a billiard system, simulating how particles would bounce inside the vacuum chamber. By analyzing these trajectories, we investigate whether chaotic orbits correlate with higher noise levels. We employ Topological Data Analysis (TDA), a method from applied mathematics, to quantify the complex structure of these dynamics. The goal is to establish geometric design principles that minimize heating. By identifying which shapes and surface features generate the most noise, this work aims to guide the engineering of next-generation ion traps. This approach bridges the gap between abstract mathematical dynamics and practical quantum hardware, offering a new pathway to more robust and scalable quantum processors.