arXiv:2508.14831v1 Announce Type: cross
Abstract: We prove a square-root space simulation for deterministic multitape Turing machines, showing $TIME[t] subseteq SPACE[O(sqrt{t})]$. The key step is a Height Compression Theorem that uniformly (and in logspace) reshapes the canonical left-deep succinct computation tree for a block-respecting run into a binary tree whose evaluation-stack depth along any DFS path is $O(log T)$ for $T = lceil t/b rceil$, while preserving $O(b)$ work at leaves, $O(1)$ at internal nodes, and edges that are logspace-checkable; semantic correctness across merges is witnessed by an exact $O(b)$ window replay at the unique interface. The proof uses midpoint (balanced) recursion, a per-path potential that bounds simultaneously active interfaces by $O(log T)$, and an indegree-capping replacement of multiway merges by balanced binary combiners. Algorithmically, an Algebraic Replay Engine with constant-degree maps over a constant-size field, together with pointerless DFS and index-free streaming, ensures constant-size per-level tokens and eliminates wide counters, yielding the additive tradeoff $S(b)=O(b + log(t/b))$ for block sizes $b ge b_0$ with $b_0 = Theta(log t)$, which at the canonical choice $b = Theta(sqrt{t})$ gives $O(sqrt{t})$ space; the $b_0$ threshold rules out degenerate blocks where addressing scratch would dominate the window footprint. The construction is uniform, relativizes, and is robust to standard model choices. Consequences include branching-program upper bounds $2^{O(sqrt{s})}$ for size-$s$ bounded-fan-in circuits, tightened quadratic-time lower bounds for $SPACE[n]$-complete problems via the standard hierarchy argument, and $O(sqrt{t})$-space certifying interpreters; under explicit locality assumptions, the framework extends to geometric $d$-dimensional models.