  Quantum computing (QC) offers a new computing paradigm that has the potential
to provide significant speedups over classical computing. Each additional qubit
doubles the size of the computational state space available to a quantum
algorithm. Such exponentially expanding reach underlies QC's power, but at the
same time puts demanding requirements on the quantum processing units (QPU)
hardware. On the other hand, purely classical simulations of quantum circuits
on either central processing unit (CPU) or graphics processing unit (GPU) scale
poorly as they quickly become bottlenecked by runtime and memory. This paper
introduces CutQC, a scalable hybrid computing approach that distributes a large
quantum circuit onto quantum (QPU) and classical platforms (CPU or GPU) for
co-processing. CutQC demonstrates evaluation of quantum circuits that are
larger than the limit of QPU or classical simulation, and achieves much higher
quantum circuit evaluation fidelity than the large NISQ devices achieve in
real-system runs.
