CUDA-Q Circuit Simulation Backends

The simulators available in CUDA-Q are grouped in the figure below. The following sections follow the structure of the figure and provide additional technical details and code examples for using each circuit simulator.

Simulators In CUDA-Q

Simulator Name	Method	Purpose	Processor(s)	Precision(s)	N Qubits
qpp-cpu	State Vector	Testing and small applications	CPU	single	< 28
nvidia	State Vector	General purpose (default)	Single GPU	single / double	< 33 / 32 (64 GB)
nvidia, option=mgpu	State Vector	Large-scale simulation	multi-GPU multi-node	single / double	33+
tensornet	Tensor Network	Shallow-depth (low-entanglement) and high width circuits	multi-GPU multi-node	single / double	Thousands
tensornet-mps	Matrix Product State	Square-shaped circuits	Single GPU	single / double	Hundreds
fermioniq	Various	Various	Single GPU	Various	Various
nvidia, option=mqpu	State Vector	Asynchronous distribution across multiple simulated QPUs to speedup applications	multi-GPU multi-node	single / double	< 33 / 32 (64 GB)
remote-mqpu	State Vector / Tensor Network	Combine mqpu with other backend like tensornet and mgpu	varies	varies	varies
density-matrix-cpu	Density Matrix	Noisy simulations	CPU	single	< 14
stim	Stabilizer	QEC simulation	CPU	N/A	Thousands +
orca-photonics	State Vector	Photonics	CPU	double	Varies on qudit level

• State Vector Simulators
  • CPU
  • Single-GPU
  • Multi-node multi-GPU
• Tensor Network Simulators
  • Multi-node multi-GPU
  • Matrix product state
  • Fermioniq
• Multi-QPU Simulators
  • Simulate Multiple QPUs in Parallel
  • Multi-QPU + Other Backends
• Noisy Simulators
  • Density Matrix
  • Stim
• Photonics Simulators
  • orca-photonics