  A binary constant weight code is a type of error-correcting code with a wide
range of applications. The problem of finding a binary constant weight code has
long been studied as a combinatorial optimization problem in coding theory. In
this paper, we propose a quantum search algorithm for binary constant weight
codes. Specifically, the search problem is newly formulated as a quadratic
unconstrained binary optimization (QUBO) and Grover adaptive search (GAS) is
used for providing the quadratic speedup. Focusing on the inherent structure of
the problem, we derive an upper bound on the minimum of the objective function
value and a lower bound on the exact number of solutions. In our algebraic
analysis, it was found that this proposed algorithm is capable of reducing the
number of required qubits, thus enhancing the feasibility. Additionally, our
simulations demonstrated that it reduces the query complexities by 63% in the
classical domain and 31% in the quantum domain. The proposed approach may be
useful for other quantum search algorithms and optimization problems.
