devqubit adapter for CUDA-Q
Project description
devqubit-cudaq
NVIDIA CUDA-Q adapter for devqubit — automatic kernel capture, target snapshots, and result logging for CUDA-Q sample and observe workflows.
[!IMPORTANT] This is an internal adapter package. Install via
pip install "devqubit[cudaq]"and use thedevqubitpublic API.
Installation
pip install "devqubit[cudaq]"
Usage
Sampling
import cudaq
from devqubit import track
@cudaq.kernel
def bell():
q = cudaq.qvector(2)
h(q[0])
x.ctrl(q[0], q[1])
mz(q)
with track(project="cudaq-experiment") as run:
executor = run.wrap(cudaq)
result = executor.sample(bell, shots_count=1000)
Observe (Expectation Values)
from cudaq import spin
hamiltonian = spin.z(0)
with track(project="cudaq-vqe") as run:
executor = run.wrap(cudaq)
result = executor.observe(bell, hamiltonian)
print(result.expectation())
What's Captured
| Artifact | Kind | Role |
|---|---|---|
| Kernel JSON | cudaq.kernel.json |
program |
| Kernel diagram | cudaq.kernel.diagram |
program |
| MLIR (Quake) | cudaq.kernel.mlir |
program |
| QIR | cudaq.kernel.qir |
program |
| Counts / expectation | result.cudaq.output.json |
result |
| Execution envelope | devqubit.envelope.json |
envelope |
Documentation
See the Adapters guide for details on observe workflows, performance tuning, and spin operator capture.
License
Apache 2.0
Project details
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