arXiv subjects

Alexander Smal

Publications and source records attributed to Alexander Smal.

5 recordsLinked to original sources

arXiv2026

The Greedy Superstring Algorithm Achieves Ratio 2 for Strings of Length 6 Already

In the Shortest Common Superstring (SCS) problem, one is given a set of strings and is asked to find a string of minimum length containing each of the input strings as a substring. The greedy superstring conjecture states that the following natural greedy algorithm has approximation ratio $2$: while there is more than one string, select the pair of strings with the maximum overlap, merge them, and add the merged string back to the set. The greedy algorithm works in linear time and is probably the simplest possible approximation algorithm for SCS. If the conjecture holds, then the greedy algorithm also surpasses the approximation guarantees of the best known approximation algorithms. The conjecture is open for $40$ years already and even the approximation ratio $\rho_k$ in the special case in which input strings have length $k$ has not yet been found: for all $k \ge 3$, $2-1/k \le \rho_k \le \min\{(k+1)/2, 3.396\}$. We prove that already for strings of length $6$, the approximation ratio of the greedy algorithm is at least $2$: $\rho_k \ge 2$ for all $k \ge 6$. We also show that $\rho_3=9/5$, thus completely characterizing the worst-case behavior of the greedy algorithm for strings of length $3$.

cs.DS↗

arXiv2025

Catalytic Computing and Register Programs Beyond Log-Depth

In a seminal work, Buhrman et al. (STOC 2014) defined the class $CSPACE(s,c)$ of problems solvable in space $s$ with an additional catalytic tape of size $c$, which is a tape whose initial content must be restored at the end of the computation. They showed that uniform $TC^1$ circuits are computable in catalytic logspace, i.e., $CL=CSPACE(O(\log{n}), 2^{O(\log{n})})$, thus giving strong evidence that catalytic space gives $L$ strict additional power. Their study focuses on an arithmetic model called register programs, which has been a focal point in development since then. Understanding $CL$ remains a major open problem, as $TC^1$ remains the most powerful containment to date. In this work, we study the power of catalytic space and register programs to compute circuits of larger depth. Using register programs, we show that for every $\epsilon > 0$, $SAC^2 \subseteq CSPACE\left(O\left(\frac{\log^2{n}}{\log\log{n}}\right), 2^{O(\log^{1+\epsilon} n)}\right)$ This is an $O(\log \log n)$ factor improvement on the free space needed to compute $SAC^2$, which can be accomplished with near-polynomial catalytic space. We also exhibit non-trivial register programs for matrix powering, which is a further step towards showing $NC^2 \subseteq CL$.

cs.CC↗

arXiv2025

Simplifier: A New Tool for Boolean Circuit Simplification

The Boolean circuit simplification problem involves finding a smaller circuit that computes the same function as a given Boolean circuit. This problem is closely related to several key areas with both theoretical and practical applications, such as logic synthesis, satisfiability, and verification. In this paper, we present Simplifier, a new open source tool for simplifying Boolean circuits. The tool optimizes subcircuits with three inputs and at most three outputs, seeking to improve each one. It is designed as a low-effort method that runs in just a few seconds for circuits of reasonable size. This efficiency is achieved by combining two key strategies. First, the tool utilizes a precomputed database of optimized circuits, generated with SAT solvers after carefully clustering Boolean functions with three inputs and up to three outputs. Second, we demonstrate that it is sufficient to check a linear number of subcircuits, relative to the size of the original circuit. This allows a single iteration of the tool to be executed in linear time. We evaluated the tool on a wide range of Boolean circuits, including both industrial and hand-crafted examples, in two popular formats: AIG and BENCH. For AIG circuits, after applying the state-of-the-art ABC framework, our tool achieved an additional 4% average reduction in size. For BENCH circuits, the tool reduced their size by an average of 30%.

cs.LO↗

arXiv2023

Proving Unsatisfiability with Hitting Formulas

Hitting formulas have been studied in many different contexts at least since [Iwama,89]. A hitting formula is a set of Boolean clauses such that any two of them cannot be simultaneously falsified. [Peitl,Szeider,05] conjectured that hitting formulas should contain the hardest formulas for resolution. They supported their conjecture with experimental findings. Using the fact that hitting formulas are easy to check for satisfiability we use them to build a static proof system Hitting: a refutation of a CNF in Hitting is an unsatisfiable hitting formula such that each of its clauses is a weakening of a clause of the refuted CNF. Comparing this system to resolution and other proof systems is equivalent to studying the hardness of hitting formulas. We show that tree-like resolution and Hitting are quasi-polynomially separated. We prove that Hitting is quasi-polynomially simulated by tree-like resolution, thus hitting formulas cannot be exponentially hard for resolution, so Peitl-Szeider's conjecture is partially refuted. Nevertheless Hitting is surprisingly difficult to polynomially simulate. Using the ideas of PIT for noncommutative circuits [Raz-Shpilka,05] we show that Hitting is simulated by Extended Frege. As a byproduct, we show that a number of static (semi)algebraic systems are verifiable in a deterministic polynomial time. We consider multiple extensions of Hitting. Hitting(+) formulas are conjunctions of clauses containing affine equations instead of just literals, and every assignment falsifies at most one clause. The resulting system is related to Res(+) proof system for which no superpolynomial lower bounds are known: Hitting(+) simulates the tree-like version of Res(+) and is at least quasi-polynomially stronger. We show an exponential lower bound for Hitting(+).

cs.CC↗

arXiv2022

Irreducible subcube partitions

A \emph{subcube partition} is a partition of the Boolean cube $\{0,1\}^n$ into subcubes. A subcube partition is irreducible if the only sub-partitions whose union is a subcube are singletons and the entire partition. A subcube partition is tight if it "mentions" all coordinates. We study extremal properties of tight irreducible subcube partitions: minimal size, minimal weight, maximal number of points, maximal size, and maximal minimum dimension. We also consider the existence of homogeneous tight irreducible subcube partitions, in which all subcubes have the same dimensions. We additionally study subcube partitions of $\{0,\dots,q-1\}^n$, and partitions of $\mathbb{F}_2^n$ into affine subspaces, in both cases focusing on the minimal size. Our constructions and computer experiments lead to several conjectures on the extremal values of the aforementioned properties.

math.CO↗