Sparsity

In quantum computing, sparsity refers to how many elements in a matrix or operator (such as a Hamiltonian or unitary) are nonzero compared to the total possible elements. A sparse matrix has relatively few nonzero entries, which makes certain quantum algorithms (like Hamiltonian simulation or linear systems solvers) more efficient because only those entries need to be processed. Exploiting sparsity reduces computational complexity and resource requirements.