We report unconditional lower bounds on k-OV circuits indicating complexity for randomised algorithms remains high.
The 2-Orthogonal Vectors (2-OV) problem is the following: given two tuples A and B of n Boolean vectors, each of dimension d , decide if there exist vectors u∈ A and v∈ B , such that u and v are orthogonal. This problem, and its generalization k -OV defined analogously for k tuples, are central problems in the area of fine-grained complexity. One of the major conjectures in fine-grained complexity is that k -OV cannot be solved by a randomised algorithm in nk-εpoly(d) time for any constant ε > 0 when d∈ ω (log n) . In this paper, we are interested in unconditional lower bounds against k -OV, but for weaker models of computation than the general Turing Machine. In particular, we are interested in circuit lower bounds for computing k -OV by Boolean circuit families of depth-3 of the form { OR}∘ { AND}∘ { OR} , or equivalently, a disjunction of CNFs . We show that for all k≤ d , any disjunction of t -CNFs computing k -OV requires size Ω ((n/t)^k) . In particular, when k is a constant, any disjunction of k -CNFs computing k -OV needs to use Ω (n^k) CNFs. This matches the brute-force construction, and for each k > 2 , this is the first tight unconditional Ω (n^k) lower bound against a class of circuits computing k -OV. Our results partially resolve a conjecture by Kane and Williams [26] (page 12, conjecture 10) about depth-3 { AC}^0 circuits computing 2-OV by showing that the conjecture is true for circuits having bounded bottom fan-in. As a secondary result, we show an exponential lower bound on the size of { AND}∘ { OR}∘ { AND} circuits computing 2-OV when d is very large. Since 2-OV reduces to k -OV by projections trivially, this lower bound works for k -OV as well.
No takes yet. Share an insight, caveat, or question.
Choudhury et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: