Streaming algorithms for groups and semigroups
Pith reviewed 2026-05-24 12:26 UTC · model grok-4.3
The pith
Randomized streaming distinguishers decide word equality in linear semigroups and product constructions using logarithmic space.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
We construct such distinguishers with low error probability using logarithmic, and in some cases doubly logarithmic, space. For example, our results apply to linear semigroups and to semigroups obtained under suitable restrictions via standard constructions such as graph products, wreath products, and semilattice decompositions. In case of commutative semigroups and cancellative nilpotent semigroups, we achieve space complexity O(log log n). We complement these upper bounds with lower bounds demonstrating that certain well-known semigroups do not admit sublinear-space distinguishers. This includes, for example, free inverse monoids of rank at least two and Thompson's group F.
What carries the argument
A distinguisher is a randomized streaming algorithm that processes two input words in parallel and, with high probability, reaches identical memory states if the words represent the same element, and distinct states otherwise.
Load-bearing premise
The target semigroups must be finitely generated and satisfy the structural restrictions such as linearity or being obtainable via the listed standard constructions.
What would settle it
A counterexample would be a finitely generated linear semigroup for which no logarithmic-space distinguisher exists, or a proof that Thompson's group F admits a sublinear-space distinguisher.
read the original abstract
We investigate deterministic and randomized streaming algorithms for word problems in finitely generated groups and semigroups. For this we introduce the notion of a distinguisher: a randomized streaming algorithm that processes two input words in parallel and, with high probability, reaches identical memory states if the words represent the same element, and distinct states otherwise. We construct such distinguishers with low error probability using logarithmic, and in some cases doubly logarithmic, space. For example, our results apply to linear semigroups and to semigroups obtained (under suitable restrictions) via standard constructions such as graph products, wreath products, and semilattice decompositions. In case of commutative semigroups and cancellative nilpotent semigroups, we achieve space complexity $\mathcal{O}(\log \log n)$. We complement these upper bounds with lower bounds demonstrating that certain well-known semigroups do not admit sublinear-space distinguishers. This includes, for example, free inverse monoids of rank at least two and Thompson's group $F$. Finally, we study randomized streaming algorithms for subgroup membership problems in free groups and their direct products.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper introduces the notion of a distinguisher—a randomized streaming algorithm that processes two input words in parallel and, with high probability, reaches identical memory states if the words represent the same semigroup or group element and distinct states otherwise. It constructs such distinguishers using O(log n) or O(log log n) space for finitely generated linear semigroups and for semigroups obtained via graph products, wreath products, and semilattice decompositions (under suitable restrictions), as well as for commutative semigroups and cancellative nilpotent semigroups. The paper complements these upper bounds with lower bounds showing that free inverse monoids of rank at least two and Thompson's group F admit no sublinear-space distinguishers, and studies randomized streaming algorithms for subgroup membership in free groups and their direct products.
Significance. If the constructions and lower-bound arguments hold, the work advances the application of streaming algorithms to algebraic decision problems by supplying explicit low-space distinguishers for several natural classes of semigroups together with matching impossibility results for well-studied examples. The introduction of distinguishers supplies a clean framework for analyzing equality testing under the streaming model. The paper supplies explicit algorithmic constructions for the upper bounds and concrete lower-bound arguments for the impossibility results.
minor comments (2)
- [Abstract] The abstract refers to “suitable restrictions” on the standard constructions (graph products, wreath products, semilattice decompositions) without enumerating them; the introduction should list the precise hypotheses under which the logarithmic-space distinguishers are obtained.
- [Introduction] Notation for the input length n and for the error probability is used without an explicit global definition; a short preliminary section collecting all parameters would improve readability.
Simulated Author's Rebuttal
We thank the referee for the positive summary, significance assessment, and recommendation of minor revision. No major comments were raised in the report.
Circularity Check
No significant circularity
full rationale
The paper introduces the distinguisher concept and constructs explicit streaming algorithms achieving logarithmic or doubly-logarithmic space for word problems in finitely generated linear semigroups and those closed under graph/wreath/semilattice products, plus matching lower bounds for free inverse monoids and Thompson's group F. These are algorithmic upper/lower bounds derived from structural properties of the semigroups rather than any self-referential definition, fitted parameter renamed as prediction, or load-bearing self-citation chain. The derivation chain is self-contained against external benchmarks in streaming complexity and semigroup theory.
Axiom & Free-Parameter Ledger
axioms (1)
- standard math Finitely generated groups and semigroups are equipped with the standard word problem and the usual notions of generation and relations.
Lean theorems connected to this paper
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IndisputableMonolith/Cost/FunctionalEquation.leanwashburn_uniqueness_aczel unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
We construct such distinguishers with low error probability using logarithmic, and in some cases doubly logarithmic, space. For example, our results apply to linear semigroups...
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IndisputableMonolith/Foundation/AbsoluteFloorClosure.leanabsolute_floor_iff_bare_distinguishability unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
The deterministic streaming space complexity of WP(G, Σ) is directly linked to the growth function γG,Σ(n)
What do these tags mean?
- matches
- The paper's claim is directly supported by a theorem in the formal canon.
- supports
- The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
- extends
- The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
- uses
- The paper appears to rely on the theorem as machinery.
- contradicts
- The paper's claim conflicts with a theorem or certificate in the canon.
- unclear
- Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.
Reference graph
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