One-tape time simulation in two-fifths-power space

A one-tape machine's run can be replayed with far less memory than the old square-root rule allowed.

1 paper September 25, 2026 Explained by AI

A one-tape machine is a simple computer that reads and writes a single strip of cells. The classical way to replay T of its steps uses memory of about the square root of T. This paper proves that about the two-fifths power of T is enough, up to log factors. It answers a question Ryan Williams asked in 2025 for this model. The replay may take far longer than the original run.

First step
—
Significance
Major
It answers an open question from Williams's 2025 square-root paper, though only for one writable tape.
Trust
Formal proof listed
Field
Theoretical computer science
1 paper

The explanation

Picture a simple machine that runs for ten billion steps, so T = 10^10. It works on one long strip of cells, called a tape. A head reads and writes one cell, then moves at most one cell left or right. A fixed rule table decides each step. This is a one-tape Turing machine. Now ask a second program, the simulator, to work out how the run ends. The simulator may take as long as it likes. The question is how little memory it needs.

The classical answer is memory of about the square root of the step count. For ten billion steps that is about 100,000 units. This paper brings it down to about the two-fifths power of T. For ten billion steps that is about 10,000, ten times less. The gap widens as T grows. At T = 10^20 it is 10^10 against 10^8, a factor of 100. Both figures leave out a factor that grows like a fixed power of log T. Here log₂ T is about 33, and the paper does not state that power. So these numbers show the trend, not exact memory sizes.

The square-root simulation for one-tape machines is old. Williams's account attributes it to Hopcroft and Ullman. In 2025, Ryan Williams showed that any multitape machine running t steps fits in about √(t log t) memory. His proof builds on a 2024 method of Cook and Mertz. That method lets nested calculations share one pool of memory and restore it afterward. In his full paper, Williams asked whether the one-tape square-root exponent could drop by a fixed amount. This paper proves that it can. Any exponent above 2/5 works, and 2/5 sits a full tenth below 1/2.

The first idea is to cut the tape into blocks of equal width b. Then shift the cut points and count how often the head crosses a block edge. Each head move crosses an edge for exactly one of the b possible shifts. So across all b shifts there are at most T crossings in total. Some shift therefore has at most T/b crossings. With T = 10^10 and b = 10,000, that is at most a million. Each stay inside one block is a visit. Between visits only a short summary passes along: the state, head positions, elapsed time and end flags.

That short summary makes checking cheap. Suppose someone hands over the full list of summaries. Then each block can be replayed on its own, from its starting contents. Whether the list is right splits into separate checks, one per block. The hard part is that the simulator must guess these summaries. A nested calculation has to hold its guess while deeper calls run. If every level held one, the memory would pile up. The paper groups b visits into an epoch and guesses them in rounds of √b visits. It arranges the calls so any chain of nested calls holds at most one round guess per epoch. In the example, that means rounds of 100 visits and 101 epochs. Balancing block size against these held guesses gives the two-fifths exponent.

This splitting is also why the result needs a single writable tape. With two writable tapes, one step can depend on two blocks at once, and the checks no longer split. For several writable tapes the paper gives only a separate square-root bound. The machine may still have extra heads that only read the input. The paper also needs the starting tape contents to be readable with very little memory. Ordinary inputs meet that condition by rescanning.

The saving is in memory only. The simulator may run far longer than the machine it copies, so this cannot be turned into a speed-up. No time cap is needed either. The simulator can try caps 2, 4, 8 and so on until the machine actually halts. The paper does not claim that two-fifths is the best possible. Its own count shows only that tuning this method's three sizes cannot do better.

How sure is this? A computer proof checker called Lean has checked formal versions of both main statements. One has a supplied time cap, and one has an unknown halting time. The multitape comparison and the paper's consequences for time and memory classes are outside that check. No specialist review of the paper has been published.

What it doesn't show. This does not speed up any computation, and it gives no two-fifths bound for machines with several writable tapes.

Where it came from

This result comes from an unreleased OpenAI model, published in the openai/math release on 6 October 2026.

Hype check

Major within its model. Lean has checked both main statements. The result saves memory, not time, covers one writable tape only, and has no published specialist review.

Words used

Turing machine
A simple model computer: a head moves along a tape of cells, following a fixed rule table.
Tape
The machine's strip of memory cells, each holding one symbol.
Simulation
A program that works out what another machine would do, step by step or by cleverer means.
Space
The number of memory bits a program uses while it runs.
Exponent
The power in a bound like T to the 1/2 or T to the 2/5; smaller means less growth.
Read-only head
An extra head that can read the input but never write.
Polylogarithmic factor
An extra factor that grows like a fixed power of log T, slowly compared with any power of T.

The original paper

All quoted lines (16)

  1. We write O~(f(T))\softO(f(T)) for O(f(T)log⁡C(T+2))O(f(T)\log^C(T+2)), with a fixed constant CC.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  2. In particular, every fixed exponent ϵ>2/5\epsilon>2/5 suffices.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  3. Every unit head move crosses a boundary for exactly one offset; a stationary move crosses none.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  4. A visit accesses one long block and exchanges only a short controller, consisting of the state, head positions, time and terminal flags.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  5. Once a proposed controller transcript is fixed, all visits to a particular block can be replayed using that block's initial contents. Consistency of the transcript therefore factors over the blocks.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  6. Group bb visits into an epoch and append their controllers in rounds of k=bk=\sqrt b visits.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  7. Such a call immediately leads to earlier epochs, so a recursion path pays for at most one retained round guess per epoch.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  8. The resulting space bound is O~ ⁣(b+(1+T/b2)b),\softO\!\left(b+(1+T/b^2)\sqrt b\right), balanced at b≍T2/5b\asymp T^{2/5}.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  9. The single selected block in Lemma … is essential to the factored round rule.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  10. Section … gives a separate O~(T)\softO(\sqrt T) simulation for every fixed number of writable tapes.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  11. The result applies to one writable head, even when additional read-only input heads are present; it is not a two-fifths bound for arbitrary multitape machines.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  12. A fixed number of additional read-only input heads may move by at most one position per step.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  13. Ordinary input access satisfies it for every cap by storing the requested coordinate and rescanning to that position or an endmarker.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  14. Theorem … concerns space, with no useful bound on simulation time. It cannot be iterated as a time improvement.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  15. Continue after a timeout and return only on an actual halt.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text
  16. The parameter calculation in Section … explains why changing the three scales in this construction alone does not lower its exponent. It is not a lower bound on other simulations, an optimality claim, or a claim of a general multitape improvement.
    Simulating One-Tape Time in Two-Fifths-Power Space Back to text

Other sources

  1. R. R. Williams, “Simulating Time with Square-Root Space”, STOC ’25 (2025), 13–23; full version arXiv:2502.17779
  2. J. Cook and I. Mertz, “Tree Evaluation Is in Space O(log n · log log n)”, STOC ’24 (2024), 1268–1278
  3. openai/math release notes (2026): model provenance and review status manuscripts and supporting proof artifacts produced by an internal OpenAI model