Probability and statistical mechanics·OpenAI Math·Result 216
Critical and near-critical XY scaling and BKT universality
One of the 372 results in OpenAI's public mathematics catalogue, filed under probability and statistical mechanics: 6 preprints, the latest dated 5 October 2026. This page quotes OpenAI's own summary of the claim, links the papers and abstracts, and embeds the animation.
In one line: OpenAI reports a result titled ‘Critical and near-critical XY scaling and BKT universality’ (probability and statistical mechanics) in 6 preprints, the latest dated 5 October 2026. It has not been peer reviewed. The channel's animation, Every OpenAI Math Result, Part 2 of 4: PCP for PPAD, Birkhoff Conjecture and 82 More, is on YouTube.
Chapter 48 of 84 in Every OpenAI Math Result, Part 2 of 4: PCP for PPAD, Birkhoff Conjecture and 82 More · starts at 16:16 · watch from there on YouTube →
What OpenAI claims
For the square-lattice nearest-neighbor cosine XY model, proves critical axis correlations Cβc(r) ∼ Ar-1/4(log r)1/8 and the Berezinskii–Kosterlitz–Thouless essential singularity √(βc-β) log ξ(β) → B, with A,B > 0 after the free-box thermodynamic limit. For finite square-symmetric interactions containing nearest neighbors, discrete Gaussian heights converge to Gaussian fields throughout the rough phase, including its threshold, along geometric torus sizes. Critical center-magnetization and spin-field conclusions retain their stated height, renormalization, and field-input assumptions.
Papers (6)
The critical logarithmic correction for the planar XY model
OpenAI's abstract We prove the critical logarithmic correction for the nearest-neighbor cosine XY model on the square lattice. Let Cbc(r) be the two-point correlation at critical inverse temperature, obtained by taking the free-box thermodynamic limit while the two sites remain r lattice steps apart along a coordinate axis. Then
Critical Center Magnetization in the Planar XY Model
OpenAI's abstract Assuming the stated critical-height, local-renormalization, and spin-field inputs from the companion papers, we determine the center magnetization of the planar XY model in a square with aligned boundary spins at its mass-defined critical threshold. As n → ∞, the magnetization is AXYn-1/8(log n)1/16(1+o(1)), where AXY is a finite, strictly positive model-specific constant.
The Critical Spin Field of the Planar XY Model
OpenAI's abstract Using the companion critical Bessel-height and pin-limit theorems, we prove that at the mass-defined critical inverse temperature of the nearest-neighbor XY model on the square lattice, the spin field on a square with boundary angles fixed to zero converges along the full sequence to the full-variance imaginary exponential of a zero-Dirichlet Gaussian free field with stiffness 2/π. The normalization uses the exact center magnetization and the lattice Green-function factor. Convergence holds in law in H-3loc((-1,1)2); all mixed moments and joint laws of fields smeared against smooth compactly supported test functions in (-1,1)2 converge as well.
Essential Singularity of the Correlation Length in the Planar XY Model
OpenAI's abstract We prove the Berezinskii–Kosterlitz–Thouless essential singularity for the correlation length of the nearest-neighbor cosine XY model on the square lattice. Let m(b) be the mass obtained by taking first the free-box thermodynamic limit and then the separation limit along a coordinate axis. As the inverse temperature b approaches bc from the massive side,
The critical correlation exponent of the planar XY model
OpenAI's abstract For the ordinary nearest-neighbor XY model on the square lattice, we prove the Berezinskii–Kosterlitz–Thouless prediction that the critical spin-correlation exponent is 1/4. More precisely, at the mass-defined critical inverse temperature, the infinite-volume correlation is n-1/4+o(1). The infinite-volume limit through free square boxes is taken before the separation limit.
BKT universality for height and planar spin fields
OpenAI's abstract We prove Gaussian scaling limits for the two-dimensional discrete Gaussian height model throughout its rough phase, including the physical roughening threshold, for every finite square-symmetric interaction set containing the nearest neighbors. After the natural lattice normalization, the critical effective temperature has the universal value 8π. For the ordinary nearest-neighbor Villain and XY models at sufficiently low fixed temperatures, we also prove that their Green-function-normalized spin fields converge to the imaginary exponential of a Dirichlet Gaussian free field.
Status
Preprint. The papers have not been independently reviewed. Treat the result as OpenAI's claim until other mathematicians have checked it. If a video exists, it illustrates the statement; it is not the proof.
Quick answers
- Is it proven?
- Not independently yet. OpenAI posted 6 preprints, the latest dated 5 October 2026; it has not been peer reviewed, so treat the result as OpenAI's claim until other mathematicians have checked it.
- What exactly does OpenAI claim?
- For the square-lattice nearest-neighbor cosine XY model, proves critical axis correlations Cβc(r) ∼ Ar-1/4(log r)1/8 and the Berezinskii–Kosterlitz–Thouless essential singularity √(βc-β) log ξ(β) → B, with A,B > 0 after the free-box thermodynamic limit. For finite square-symmetric interactions containing nearest neighbors, discrete Gaussian heights converge to Gaussian fields throughout the rough phase, including its threshold, along geometric torus sizes. Critical center-magnetization and spin-field conclusions retain their stated height, renormalization, and field-input assumptions.
- Where is the proof?
- In the paper, The critical logarithmic correction for the planar XY model (PDF).
- Is there a video?
- Yes, on YouTube (29:10, chapter 48).
Also in
- Chapter 3 of 10 in Benjamini–Schramm Conjecture, Mézard–Parisi Formula, Voronoi Percolation and 7 More · starts at 0:41 · watch from there on YouTube →
The video
Every OpenAI Math Result, Part 2 of 4: PCP for PPAD, Birkhoff Conjecture and 82 More · Compilation · 29:10 · chapter 48 from 16:16 · description, sources and chapters →
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