There has been significant work recently on integer programs (IPs) min{c x : Ax ≤ b, x ∈ Z n } with a constraint marix A with bounded subdeterminants. This is motivated by a well-known conjecture claiming that, for any constant ∆ ∈ Z >0 , ∆-modular IPs are efficiently solvable, which are IPs where the constraint matrix A ∈ Z m×n has full column rank and all n × n minors of A are within {−∆, . . . , ∆}. Previous progress on this question, in particular for ∆ = 2, relies on algorithms that solve an important special case, namely strictly ∆-modular IPs, which further restrict the n × n minors of A to be within {−∆, 0, ∆}. Even for ∆ = 2, such problems include well-known combinatorial optimization problems like the minimum odd/even cut problem. The conjecture remains open even for strictly ∆-modular IPs. Prior advances were restricted to prime ∆, which allows for employing strong number-theoretic results.In this work, we make first progress beyond the prime case by presenting techniques not relying on such strong number-theoretic prime results. In particular, our approach implies that there is a randomized algorithm to check feasibility of strictly ∆-modular IPs in strongly polynomial time if ∆ ≤ 4.
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