Function dem_from_kernel

python/cudaq/runtime/dem.py:25–53

Generate a detector error model (DEM) from a CUDA-Q kernel. Runs `kernel` under the internal `"dem"` execution context, captures the recorded circuit from the backend, and returns Stim's standard `.dem` text via `stim::DetectorErrorModel::str()`. The active CUDA-Q target is unaffect

(kernel, *args, noise_model=None)

@trace.traced
def dem_from_kernel(kernel, *args, noise_model=None):
    """Generate a detector error model (DEM) from a CUDA-Q kernel.

    Runs `kernel` under the internal `"dem"` execution context, captures
    the recorded circuit from the backend, and returns Stim's standard
    `.dem` text via `stim::DetectorErrorModel::str()`. The active CUDA-Q
    target is unaffected; the analysis simulator is an internal,
    thread-local override.

    Args:
      kernel (:class:`Kernel`): The :class:`Kernel` to analyze.
      *arguments: Concrete argument values forwarded to the kernel invocation.
      noise_model (:class:`NoiseModel`, optional): Noise model layered on
          top of any `apply_noise` ops already present in the kernel.

    Returns:
      UTF-8 string in Stim's standard `.dem` file format. Consumers
      that need a structured DEM can parse it with
      `stim.DetectorErrorModel(text)`.
    """
    _detail_check_conditionals_on_measure(kernel)

    if isa_kernel_decorator(kernel):
        decorator = kernel
    else:
        decorator = mk_decorator(kernel)
    processedArgs, module = decorator.prepare_call(*args)
    return cudaq_runtime.dem_from_kernel_impl(decorator.uniqName, module,
                                              noise_model, *processedArgs)