An Ignite-style talk that I will have given:
Rethinking Topological Quantum Logic
talk at Softmax AI Alignment-meeting
London (22 May 2025)
Exposition of:
Outline (preliminary):
I – Problem
quantum computers excessively more powerful than classical ones — in principle
possible dramatic enhancement for machine learning algorithms — in principle
but quantum is immensely noise intolerant existing quantum computers are puny
popular hope: live with the noise and fight it by software: “quantum error correction”
more profound approach: prevent noise on hardware by fundamental physical effects!
tantalizing candidate: topological quantum effects save information in knotted states
but theoretical understanding remained superficial & experimental claims remain dubious
because topological quantum is “non-perturbative physics”: a $1M “Millennium Problem”
II – Solution
recent understanding @CQTS [LMP 115 36 (2025)] of engineering topological quantum on M-branes
namely, topological states in “fractional quantum Hall systems carried by exotic magnetic flux quanta
but state-of-the-art understanding of magnetic flux quantization was a century old [Dirac 1931]
now novel math developed @CQTS [EoMP 4 (2025) 281] explains generalized exotic flux quantization
showsthere exists an exotic "flux quantization law" which knows fractional Hall quantum topology!
this novel law (“Hypothesis H”) predicts pathway to topological quantum logic via “defect anyons”
I [will have] just come from a meeting at ShabaniLab@NYU NY, discussing experimental prospects
gate opened towards scaling-up quantum computers & thus
towards practical quantum advantage in machine learning?
Created on May 4, 2025 at 09:10:36. See the history of this page for a list of all contributions to it.