Result 238, Probability and statistical mechanics

Optimal logarithmic mixing of the Thorp shuffle

Proves that the Thorp shuffle randomizes N=2dN=2^d labeled cards in Θ(log⁡N)\Theta(\log N) physical shuffles, settling its optimal mixing order for power-of-two deck sizes. Convergence is in total variation from the worst initial ordering and concerns the entire permutation, not just individual card positions.

Lean formalization Proof

The bigger picture

Why it matters

How many Thorp shuffles make an entire deck effectively random, rather than merely scattering individual cards? The claimed answer grows only logarithmically with deck size, and that growth rate cannot be improved for power-of-two decks.

What changes?

For decks of two to the power d labeled cards, the unreviewed manuscript reports that 1,600 times d complete physical shuffles suffice, while a counting argument requires at least twice d minus an absolute constant. The upper bound means that, as d grows, total-variation distance from uniform tends to zero, regardless of the initial ordering. This distance measures the largest probability discrepancy for any event involving the deck's full ordering, not just one card's position.

What does that help mathematicians do?

The full-ordering guarantee controls correlations that individual-card tests can miss: an apparently scattered deck can still favor particular joint arrangements. The reported bound makes every such event nearly as likely as under a uniformly random ordering. Meanwhile, counting the orderings the shuffle can reach supplies a matching-order obstruction. Together, these bounds identify the necessary growth rate, though not the best constant.

Are there practical applications?

The immediate value is foundational for the study of randomization: the result quantifies how repeated steps of this shuffle erase information about an arbitrary starting deck. It also provides a full-deck guarantee for this specific random permutation process. The asymptotic bounds do not, by themselves, specify a practical shuffle count for an ordinary deck, whose size is outside the stated power-of-two scope.

This section was generated by GPT-6 Astra Medium. This explanation is based on the result summary and manuscript abstracts below. This context is separate from OpenAI's source text.

12 manuscripts

Optimal-order mixing of the Thorp shuffle

September 26, 2026 14 pages

We prove that the Thorp shuffle on 2d2^d cards mixes in Θ(d)\Theta(d) complete shuffles. The full permutation law after 1600d1600d shuffles converges to uniform in total variation as d→∞d\to\infty, uniformly over the initial deck, while a support count gives a lower bound of 2d−O(1)2d-O(1).

Cite (BibTeX)
@misc{OAI:Optimal-order-mixing-of-the-Thorp-shuffle-September-26-2026,
  author = {{OpenAI}},
  title = {{Optimal-order mixing of the Thorp shuffle}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/Optimal-order-mixing-of-the-Thorp-shuffle-September-26-2026/paper.pdf}{OAI:Optimal-order-mixing-of-the-Thorp-shuffle-September-26-2026}},
  year = {2026}
}

Random coordinate frames and partial permutation laws

September 26, 2026 72 pages

For the Thorp shuffle on 2d2^d cards, we prove that the worst-start total-variation distance after 32800d32800d physical shuffles tends to zero as d→∞d\to\infty. Combining our fixed-list estimate with the companion Fourier transfer improves this bound to 512d512d shuffles. These results follow from bounds on partially observed permutation laws in random coordinate frames.

Cite (BibTeX)
@misc{OAI:Random-coordinate-frames-and-partial-permutation-laws-September-26-2026,
  author = {{OpenAI}},
  title = {{Random coordinate frames and partial permutation laws}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/Random-coordinate-frames-and-partial-permutation-laws-September-26-2026/main.pdf}{OAI:Random-coordinate-frames-and-partial-permutation-laws-September-26-2026}},
  year = {2026}
}

From partial permutation information to Fourier bounds

September 26, 2026 66 pages

We show how information about partial permutations controls full permutation laws. Let n tend to infinity through multiples of eight. If the images of a uniformly chosen 7n/87n/8 labels approach the uniform injection law in average total variation, and the sign mean tends to zero, then the product of two independent permutations with the given law converges to uniform on Sn.

Cite (BibTeX)
@misc{OAI:From-partial-permutation-information-to-Fourier-bounds-September-26-2026,
  author = {{OpenAI}},
  title = {{From partial permutation information to Fourier bounds}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/From-partial-permutation-information-to-Fourier-bounds-September-26-2026/main.pdf}{OAI:From-partial-permutation-information-to-Fourier-bounds-September-26-2026}},
  year = {2026}
}

Conditional information under deterministic coordinate sweeps

September 26, 2026 81 pages

We bound the information remaining after paths of specified cards in the Thorp shuffle on n=2dn=2^d cards have been observed. After a fixed number of deterministic coordinate sweeps, the joint endpoint law of further cards is close to uniform on the available positions, on average over the observed paths, provided a fixed positive fraction of labels lies outside both lists. Combined with a Fourier transfer, these bounds give full-deck mixing after 2048d2048d physical shuffles.

Cite (BibTeX)
@misc{OAI:Conditional-information-under-deterministic-coordinate-sweeps-September-26-2026,
  author = {{OpenAI}},
  title = {{Conditional information under deterministic coordinate sweeps}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/Conditional-information-under-deterministic-coordinate-sweeps-September-26-2026/main.pdf}{OAI:Conditional-information-under-deterministic-coordinate-sweeps-September-26-2026}},
  year = {2026}
}

Conditional permutations in a revealed switching environment

September 26, 2026 32 pages

Fix half the labels in a Thorp shuffle on 2d2^d positions and reveal their complete trajectories. We prove that, after an explicit absolute number of coordinate sweeps, the conditional permutation of the remaining labels approaches uniform in expected total variation as d→∞d\to\infty, uniformly in the initial layout. The resulting constructions give full-deck mixing in a constant multiple of d physical shuffles.

Cite (BibTeX)
@misc{OAI:Conditional-permutations-in-a-revealed-switching-environment-September-26-2026,
  author = {{OpenAI}},
  title = {{Conditional permutations in a revealed switching environment}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/Conditional-permutations-in-a-revealed-switching-environment-September-26-2026/paper.pdf}{OAI:Conditional-permutations-in-a-revealed-switching-environment-September-26-2026}},
  year = {2026}
}

Routing densities and representation contraction for Thorp sweeps

September 26, 2026 86 pages Main result formalized in Lean

For N=2dN=2^d cards, we prove that an absolute number of coordinate sweeps of the Thorp shuffle brings the full permutation law to total-variation distance tending to zero from uniform. The mixing time therefore has optimal order Θ(log⁡N)\Theta(\log N) in physical shuffles.

Cite (BibTeX)
@misc{OAI:Routing-densities-and-representation-contraction-for-Thorp-sweeps-September-26-2026,
  author = {{OpenAI}},
  title = {{Routing densities and representation contraction for Thorp sweeps}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/Routing-densities-and-representation-contraction-for-Thorp-sweeps-September-26-2026/paper.pdf}{OAI:Routing-densities-and-representation-contraction-for-Thorp-sweeps-September-26-2026}},
  year = {2026}
}

Row–column symmetry and contraction of coordinate sweeps

September 26, 2026 38 pages

We prove that the Thorp shuffle on N=2dN=2^d labeled cards has full-permutation total-variation mixing time Θ(log⁡N)\Theta(\log N) in physical shuffles. An absolute number of coordinate sweeps suffices for the upper bound.

Cite (BibTeX)
@misc{OAI:Row-column-symmetry-and-contraction-of-coordinate-sweeps-September-26-2026,
  author = {{OpenAI}},
  title = {{Row--column symmetry and contraction of coordinate sweeps}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/Row-column-symmetry-and-contraction-of-coordinate-sweeps-September-26-2026/paper.pdf}{OAI:Row-column-symmetry-and-contraction-of-coordinate-sweeps-September-26-2026}},
  year = {2026}
}

Random-subspace tests and trace smoothing for coordinate sweeps

September 26, 2026 15 pages

We prove that an absolute number of coordinate sweeps of the Thorp shuffle on n=2dn=2^d positions brings the full permutation to total-variation distance at most 12n−5\frac12n^{-5} from uniform, uniformly over the initial deck. Thus O(d)O(d) physical shuffles suffice, which is optimal in order.

Cite (BibTeX)
@misc{OAI:Random-subspace-tests-and-trace-smoothing-for-coordinate-sweeps-September-26-2026,
  author = {{OpenAI}},
  title = {{Random-subspace tests and trace smoothing for coordinate sweeps}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/Random-subspace-tests-and-trace-smoothing-for-coordinate-sweeps-September-26-2026/paper.pdf}{OAI:Random-subspace-tests-and-trace-smoothing-for-coordinate-sweeps-September-26-2026}},
  year = {2026}
}

Compatibility entropy and the spectrum of a Thorp sweep

September 26, 2026 128 pages Main result formalized in Lean

We prove that the Thorp shuffle on n=2dn=2^d cards mixes in Θ(d)\Theta(d) physical shuffles. After a sufficiently large fixed number of coordinate sweeps, the total-variation distance of the full permutation from uniform tends to zero as d→∞d\to\infty.

Cite (BibTeX)
@misc{OAI:Compatibility-entropy-and-the-spectrum-of-a-Thorp-sweep-September-26-2026,
  author = {{OpenAI}},
  title = {{Compatibility entropy and the spectrum of a Thorp sweep}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/Compatibility-entropy-and-the-spectrum-of-a-Thorp-sweep-September-26-2026/paper.pdf}{OAI:Compatibility-entropy-and-the-spectrum-of-a-Thorp-sweep-September-26-2026}},
  year = {2026}
}

Signed tensor densities and diagram budgets for the Thorp shuffle

September 26, 2026 109 pages

We prove that a fixed number of coordinate sweeps of the Thorp shuffle on 2d2^d cards makes the squared L2 distance of the full permutation density from uniform tend to zero as d→∞d\to\infty. In particular, the total-variation mixing time is Θ(d)\Theta(d) physical shuffles.

Cite (BibTeX)
@misc{OAI:Signed-tensor-densities-and-diagram-budgets-for-coordinate-sweeps-September-26-2026,
  author = {{OpenAI}},
  title = {{Signed tensor densities and diagram budgets for the Thorp shuffle}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/Signed-tensor-densities-and-diagram-budgets-for-coordinate-sweeps-September-26-2026/paper.pdf}{OAI:Signed-tensor-densities-and-diagram-budgets-for-coordinate-sweeps-September-26-2026}},
  year = {2026}
}

Conditional coordinate sweeps and analytic transfer

September 26, 2026 23 pages Main result formalized in Lean

For coordinate sweeps with near-uniform line laws and line sizes among powers of two in a suitable fixed interval, we prove a Schatten-moment bound after conditioning on any feasible collection of prescribed card trajectories. An analytic transfer to binary sweeps then shows that a fixed number of sweeps mixes the Thorp shuffle on 2d2^d cards in O(d)O(d) physical steps, matching the order of the support lower bound.

Cite (BibTeX)
@misc{OAI:Conditional-coordinate-sweeps-and-analytic-transfer-September-26-2026,
  author = {{OpenAI}},
  title = {{Conditional coordinate sweeps and analytic transfer}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/Conditional-coordinate-sweeps-and-analytic-transfer-September-26-2026/main.pdf}{OAI:Conditional-coordinate-sweeps-and-analytic-transfer-September-26-2026}},
  year = {2026}
}

A strict four-row permanent inequality and permutation moments

September 26, 2026 19 pages

We prove a permanent inequality with exponent strictly below two for laws on S4 sufficiently close to uniform and with exactly uniform coordinate marginals. Applied to a four-row recursion, it shows that an absolute number of coordinate sweeps brings the full permutation of the Thorp shuffle on N=2dN=2^d cards to total-variation distance tending to zero from uniform as N→∞N\to\infty. Thus the mixing time has the optimal order O(log⁡N)O(\log N) in physical shuffles.

Cite (BibTeX)
@misc{OAI:A-strict-four-row-permanent-inequality-and-permutation-moments-September-26-2026,
  author = {{OpenAI}},
  title = {{A strict four-row permanent inequality and permutation moments}},
  howpublished = {OpenAI Math Release preprint
                  \href{https://github.com/openai/math/blob/main/preprints/A-strict-four-row-permanent-inequality-and-permutation-moments-September-26-2026/main.pdf}{OAI:A-strict-four-row-permanent-inequality-and-permutation-moments-September-26-2026}},
  year = {2026}
}

Lean formalization

OpenAI's note on what the formalization covers, from lean/docs/238.md.

Optimal logarithmic mixing of the Thorp shuffle

The following describes the scope of the Lean formalization related to the following accompanying paper(s):

Scope

The formalization proves optimal-order mixing of the Thorp shuffle on 2d2^d cards. After 1600d1600d complete shuffles, the full permutation law converges in total variation to uniform as d→∞d\to\infty, uniformly over initial decks. Together with the support lower bound of 2d−O(1)2d-O(1), this gives mixing time Θ(d)=Θ(log⁡(2d))\Theta(d)=\Theta(\log(2^d)).

The linked supporting results include frame and conditional-list estimates, regular trace and spectral bounds, signed moments, and full-density L2L^2 control. They also bound reciprocal Specht-dimension sums and give the eight-block Fourier estimate used in the mixing argument.

The formalized supporting result turns bounds on partial-permutation cosets into Fourier bounds. Partition a finite set into b≥1b\ge1 nonempty blocks, and let f≥0f\ge0 be a subprobability weight on its symmetric group whose left-coset masses for each block subgroup are at most BB. For every irreducible unitary representation of dimension DD and every u>0u>0, both the squared Hilbert–Schmidt norm and squared operator norm of its Fourier transform are at most bB C(u)D−1+(u+2)/bbB\,C(u)D^{-1+(u+2)/b}, where C(u)C(u) is the stated symmetric-group degree constant.

The paper's asymptotic conclusion about the product of two random permutations is outside this selected finite estimate.

The formalized results give averaged conditional mixing for half-permutations in the revealed-path model and full-deck mixing for the Thorp shuffle. In particular, the full-deck total-variation distance tends to zero after 16040400d16040400d steps on 2d2^d cards, uniformly over deterministic initial decks. The conditional estimate is averaged over the actual outside-path law, rather than asserted for each individual environment. The formalization also includes the associated overlay, reset minorization, and two-color conditional constructions.

The formalization covers nine routing and representation estimates for Thorp sweeps: adaptive operator and fourth-trace bounds, Casimir moments, dense truncation, sparse contact, harmonic-cycle contraction, smoothing, and three tail or sparse-saving estimates. They bound routing-density deviations and Fourier operators in dense and sparse regimes, including exponential savings in the level scale and representation dimension.

The conditional high-height estimate requires a sufficiently large cutoff height JJ that exceeds twice the number ss of coordinates in the fixed low block, so J>2sJ>2s. These are the earlier nine statements associated with the paper; its changed later statements and six other result blocks are outside this scope.

The formalization proves uniform representation bounds for one coordinate sweep of the Thorp shuffle. For each irreducible representation of dimension DD, it chooses a weight between D3/4D^{3/4} and DD and a Schatten exponent bounded by one absolute constant so that the weighted Schatten moment is at most one. The sweep's operator norm is consequently at most D−cD^{-c} for one absolute c>0c>0.

The supporting row–column estimate bounds the total squared overlap over all multiplicity copies on an occupied board, with explicit dependence on the row and column representation dimensions, the global dimension, the number of missing cells, and the number of rows or columns containing the global Young diagram. The paper's full physical-mixing conclusion is outside these selected representation estimates.

The formalization proves a uniform trace-smoothing estimate for coordinate sweeps of the Thorp shuffle on 2d2^d cards. One absolute sweep parameter works for every d≥1d\ge1: the regular trace is at most 1+(2d)−101+(2^d)^{-10}, and the full permutation law after the corresponding fixed number of sweeps is within 12(2d)−5\tfrac12(2^d)^{-5} of uniform in total variation, for every initial deck. Thus the selected upper bound uses O(d)O(d) physical shuffles.

The formalized result is the weighted compatibility theorem for balanced A×DA\times D rectangles, with n=ADn=AD and n/2≤A,D≤2n\sqrt n/2\le A,D\le2\sqrt n. For arbitrary nonnegative weights on the row and column permutation groups, the normalized compatibility average is bounded by exp⁡(C0n54/100)\exp(C_0n^{54/100}) times the product of the marginal L1/θL^{1/\theta} factors, where θ=1−L/log⁡n>0\theta=1-L/\log\sqrt n>0 and the constants are absolute. Compatibility means injectivity in every original column. The bounded regular-moment and other moment/rank conclusions are not included.

The formalization gives signed representation estimates for coordinate sweeps of the Thorp shuffle. For every signed occurrence of a Young diagram of size 2d2^d, it bounds the logarithm of a fixed-order weighted sweep moment by a small multiple of the signed partition entropy plus an explicit remainder-size budget. The moment order is uniform over the diagrams and decompositions after the two small coefficients are fixed.

The linked supporting angle bound controls the overlap of row, column, and global signed-type projections on an occupied rectangle, with explicit entropy, dimension, and missing-cell factors. These selected estimates support the paper's full-density argument; the full L2L^2 and total-variation mixing conclusion is outside them.

The formalized binary-sweep theorem gives a universal power contraction in every irreducible representation: for sufficiently large dd, the averaged sweep on 2d2^d slots has operator norm at most D−gD^{-g} in representation dimension DD, for some g>0g>0. The sign expectation is zero, and a fixed number of independent sweeps approaches uniform in total variation from every initial deck. A separate conditional moment estimate covers allowed power-of-two grids and disjoint coordinate-respecting trajectories, with its stated feasibility premise. Physical-shuffle law identification is not included.

The formalization proves the paper's strict four-row permanent inequality. There are constants 4/3<p<24/3<p<2 and ε>0\varepsilon>0 such that every probability law on S4S_4 within total-variation distance ε\varepsilon of uniform, and with exactly uniform coordinate marginals, satisfies the permanent bound by the product of the four LpL^p row norms for every nonnegative matrix. The exponent and neighborhood are uniform over those laws. The Thorp mixing consequence is outside this selected statement.

Comparator links

Result Comparator statement
Reciprocal Specht degrees and eight-block Fourier bound ThorpFirstReciprocal.lean
Frame, spectral, and density estimates for Thorp mixing ThorpRemaining.lean
Fourier bounds from complementary coset caps PartialPermutation.lean
Nine routing-density and representation estimates ThorpRouting.lean
Row–column overlap on occupied boards OccupiedOverlap.lean
Weighted Schatten moments and operator contraction for coordinate sweeps WeightedSweepMoments.lean
Regular trace smoothing and full-permutation mixing CoordinateTrace.lean
Weighted row–column compatibility bound ThorpWeightedCompatibility.lean
One-sided angle bound for signed spin types SpinAngle.lean
Uniform signed-occurrence moment bound for coordinate sweeps SignedSweepMoment.lean
Binary sweep contraction and mixing BinarySweep.lean
Conditional coordinate-sweep moment estimate CoordinateSweeps.lean
Strict four-row permanent inequality near the uniform law FourRowPermanent.lean

Data from github.com/openai/math at commit adc7f12, committed October 6, 2026 at 21:58 UTC, last checked for changes about 7 hours ago. Titles, subjects, summaries, abstracts and Lean notes are OpenAI's; page counts are read from the PDFs. The map, related results, search, kinds of results and the named-problem index are Emergent Mind's, built with text embeddings and an LLM, and may contain errors.

An Emergent Mind Labs project. Emergent Mind is not affiliated with OpenAI. None of these results has been peer reviewed. Cite the manuscripts themselves, using the BibTeX on each result's page.