Classical simulation of quantum circuits is critical for the development of implementations of quantum algorithms: it does not require access to specialized hardware, facilitates debugging by allowing direct access to the quantum state, and is the only way to test on inputs that are too big for current NISQ computers.

Many quantum algorithms rely on invariants that result in sparsity in the state vector. A sparse state vector simulator only computes with non-zero amplitudes. For important classes of algorithms, this results in an asymptotic improvement in simulation time. While promising prior work has investigated ways to exploit sparsity, the challenge of scaling the sparse simulation via parallelization has remained completely open.

In this work, we address this challenge and present qblaze, a highly optimized sparse state vector simulator based on (i) a compact sorted array representation, and (ii) new, easily parallelizable and highly-scalable algorithms for all quantum operations.

Our extensive experimental evaluation of qblaze shows that it is often orders-of-magnitude more efficient than existing sparse state vector simulators even on a single thread, and scales to a large number of CPU cores. Overall, qblaze enables testing quantum algorithms on input sizes that were previously out of reach.