Recently, Göös et al. [Göös et al., 2024] showed that Res ⋏ uSA = RevRes in the following sense: if a formula φ has refutations of size at most s and width/degree at most w in both Res and uSA, then there is a refutation for φ of size at most poly(s ⋅ 2^w) in RevRes. Their proof relies on the TFNP characterization of the aforementioned proof systems. In our work, we give a direct and simplified proof of this result, simultaneously achieving better bounds: we show that if for a formula φ there are refutations of size at most s in both Res and uSA, then there is a refutation of φ of size at most poly(s) in RevRes. This potentially allows us to "lift" size lower bounds from RevRes to Res for the formulas for which there are upper bounds in uSA. This kind of lifting was not possible before because of the exponential blow-up in size from the width. Similarly, we improve the bounds in another intersection theorem from [Göös et al., 2024] by giving a direct proof of Res ⋏ uNS = RevResT. Finally, we generalize those intersection theorems to some proof systems for which we currently do not have a TFNP characterization. For example, we show that Res(⊕) ⋏ u-wRes(⊕) = RevRes(⊕), which effectively allows us to reduce the problem of proving Pigeonhole Principle lower bounds in Res(⊕) to proving Pigeonhole Principle lower bounds in RevRes(⊕), a potentially weaker proof system.

Resolution with symmetries is a natural extension of the Resolution proof system that allows to use symmetries of the formula to simplify the proof. Symmetries can be global (applied to the whole input formula), local (applied to a subformula), or dynamic (applied to newly derived clauses as well). The framework of Resolution with (global) symmetries was introduced by [Krishnamurthy, 1985] and further extended by [Arai and Urquhart, 2000] to local symmetries. Later, [Szeider, 2005] generalized this approach to homomorphisms and introduced the notion of Resolution with dynamic symmetries. While proving superpolynomial proof-size lower bounds for Resolution with dynamic symmetries remains an open problem already for two decades, the power of proof systems with global and local symmetries is well studied: exponential lower bounds have been proven for these proof systems, as well as exponential separations between all of them. However, these systems are too general to reflect practical applications since it is computationally too hard to find and efficiently exploit arbitrary symmetries. In this work, we introduce the notion of small symmetries: symmetries that can operate on a limited number of variables at the same time. Resolution with small symmetries gives hopes both for practical applications and for theoretical study of dynamic symmetries. We show that proof systems with both local and global small symmetries form strict hierarchies w.r.t. the size of symmetries. We prove exponential separations between proof systems with symmetries of different sizes and types. It turns out that even lower levels of these hierarchies are exponentially separated from Resolution and stronger proof systems, such as constant-depth Frege. As a byproduct of our constructions, we obtain an exponential separation between the classical systems SRCI and SRII that was not known before.

The longest common subsequence (LCS) problem is a fundamental algorithmic problem. Given a pair of strings, the problem asks for the length of the longest string that is a subsequence in both input strings. Among the many relatives of this problem, there is its natural version where one or both of input strings have periodic structure. The case where only one of the input strings is periodic has been considered before; in this work, we develop an efficient algorithm for the more difficult case where both input strings are periodic. The algorithm is based on the existing algebraic framework for the LCS problem, developed by the third author; in particular, we extend this framework to dealing with affine (i.e. doubly-infinite periodic) permutations instead of finite ones. Given input strings that are a k-repeat of a period of length m and an 𝓁-repeat of a period of length n, the resulting algorithm runs in time O(mn+n log n log k), which is a substantial improvement over existing approaches. The algorithm has been implemented by the first author; by running his code, one can process pairs of periodic input strings with lengths far beyond the reach of all known alternative algorithms.