[Joint CQSE & NCTS Special Seminar] Building Quantum Error Correcting Codes with Tensor Networks and Machine Learning

Title: [Joint CQSE & NCTS Special Seminar] Building Quantum Error Correcting Codes with Tensor Networks and Machine Learning
Speaker: Dr. Vincent P. Su (UC Berkeley)
Time: 2024/01/04 (Thur.) 14:30-15:30
Place: NCTS Physics Lecture Hall, 4F, Chee-Chun Leung Cosmology Hall, NTU
Online: https://nationaltaiwanuniversity-zbh.my.webex.com/nationaltaiwanuniversity-zbh.my/j.php?MTID=ma5bfefeb53c8c00f5a99ff6116be1700 
 

Abstract
Quantum error correction design is a difficult but important problem on the road to
fault tolerance. In this talk, I will review one way to build larger quantum error
correcting codes from smaller ones. By treating the individual encoding unitaries as
tensors, small QECCs can be stitched together producing rich emergent behavior. For
example, the surface code can be built from many identical copies of a simple 4 qubit
code. By treating code building as a game, we are able to use machine learning methods
to build novel codes that i) saturate bounds on distance for CSS codes and ii)
outperform surface code variants for ~20 qubits at protecting logical information from
biased Pauli noise. Based on https://arxiv.org/abs/2305.06378
 
Biography
Vincent Su is currently wrapping up his PhD in Physics at UC Berkeley under the
supervision of Prof. Raphael Bousso. His interests include quantum error correction,
quantum information and machine learning. Previously, he completed his B.S. in
Physics and M.S. in Computer Science at Stanford.

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