An Ignite-style talk that I have given:
Rethinking Topological Quantum
slides: pdf (view in presentation mode)
video: yt
lightning talk at:
AI & Evolution Gathering
organized by Softmax,
@ The Royal Institution
London (22 May 2025)
Lightning summary of:
which in turn is an exposition of this article:
Related lecture notes:
Related talks:
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 – New Attack
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?
Last revised on May 29, 2025 at 09:58:27. See the history of this page for a list of all contributions to it.