Apr 18 – 19, 2026
University of Delaware, Sharp Laboratory
US/Eastern timezone
TimeTable of the meeting is now available. Registration for zoom attendance still open!

Just Follow the Arrows to Build Quantum Intuition for the Mach-Zehnder Interferometer

Apr 18, 2026, 2:15 PM
15m
University of Delaware, Sharp Laboratory

University of Delaware, Sharp Laboratory

104 The Green, Newark, DE 19716
Talk (15 min) Room 130 (auditorium)

Speaker

Jason Tran (Georgetown University)

Description

Quantum mechanics is both conceptually difficult and mathematically demanding for physics students. They often describe it as unintuitive, abstract, and disconnected from prior classical experiences, where the largest hurdle is the mathematical barrier to entry. But are there other approaches that can help build quantum intuition without requiring the advanced mathematics?

This presentation explores an alternative instructional approach inspired by Richard Feynman’s formulation of quantum mechanics via discrete path integrals in QED: The Strange Theory of Light and Matter, which uses “probability amplitude arrows” to determine probabilities for experimental outcomes. Rather than relying on advanced mathematical tools, this approach leverages intuitive vector addition and geometric reasoning to model how quantum probabilities emerge from alternative ways that events occur. We introduce the core ideas of this arrow-based framework and demonstrate how it provides a conceptually accessible entry point into quantum conceptual reasoning.

We focus on two single quantum optical experiments: the beam splitter and the Mach-Zehnder interferometer. Through these two examples, we illustrate how complex phenomena such as interference, superposition, and measurement can be developed using simple arrow constructions, reducing reliance on mathematical formalism, while preserving conceptual rigor. This approach can be easily incorporated into high school and undergraduate curricula and it is completely faithful to the physics, without simplifying the results.

Primary author

Jason Tran (Georgetown University)

Co-authors

James Freericks (Georgetown University) Leanne Doughty (Georgetown University)

Presentation materials

There are no materials yet.