OpenAI reports thermodynamic-first QAOA optimality for the SK model

For the zero-field Gaussian Sherrington–Kirkpatrick model, as system size tends to infinity first and QAOA depth then grows, the best limiting expected energy per spin approaches the Parisi ground-state value.

Curated contributions 1

Understand the problem ↓

OpenAI reports thermodynamic-first QAOA optimality for the SK model

  • Mathematics
  • Theoretical Physics

For the zero-field Gaussian Sherrington–Kirkpatrick model, as system size tends to infinity first and QAOA depth then grows, the best limiting expected energy per spin approaches the Parisi ground-state value. For every accuracy, one finite depth and deterministic angles work independently of system size and disorder.

AI involvementAI-led
ImportanceMajor
Technical verificationReported
Human understandingFew

Understanding the problem

Read the background

For the zero-field Gaussian Sherrington–Kirkpatrick model, as system size tends to infinity first and QAOA depth then grows, the best limiting expected energy per spin approaches the Parisi ground-state value. For every accuracy, one finite depth and deterministic angles work independently of system size and disorder.

Why it matters

If correct, proves eventual Parisi optimality of standard QAOA in the fixed-parameter thermodynamic formulation.

What counts as progress

Can fixed-parameter QAOA approach the SK ground-state energy when system size goes to infinity first?

Website timeline

Publication dates and editorial changes.