Title: Optimal bounds and computational complexity of perfect quantum state classification Speaker:  Jamie Sikora (Virginia Tech) Date & Time:  November 18, 2025, 11:00am Where to Attend:  ATL 3100A and Virtual Via Zoom: https://umd.zoom.us/j/91679364399 Meeting ID: 916 7936 4399
Identifying an unknown quantum state is one of the oldest and most fundamental problems in quantum information theory. In this talk, we examine a variant of this problem—quantum state classification—in which the learner is allowed multiple guesses, provided that one of them must be correct. A collection of quantum states is said to be k-learnable if the correct state can always be identified with at most k guesses and zero error. We present examples illustrating when perfect classification is possible, derive optimal bounds for various values of k, and characterize the computational complexity of deciding k-learnability.
This is joint work with Vincent Russo, Nathaniel Johnston, and Benjamin Lovitz (arXiv: 2510.20789, 2311.17047, 2206.08313). *We strongly encourage attendees to use their full name (and if possible, their UMD credentials) to join the zoom session.*