The Low Autocorrelation Binary Sequence problem with a tunable interaction range (or LABS problem for short) is the problem
of finding a sequence involving terms equal to only +1 and -1 such that an energy function called autocorrelation is minimized. The problem is inspired by an application in physics and has many other applications
in cryptography, for synchronization in digital communication systems, and in modulation of radar
pulses. Our contribution is twofold. First, we prove that for small values of the range, the problem is easy to solve. Second, we present a new mathematical programming formulation with some convexity properties that may offer promising improvements in the solution using a branch-and-bound or a branch-and-cut framework.