# Cirq

## Notice

We only document what is different from Google's `qsimcirq`. For more information, please review [Google's Documentation](https://quantumai.google/reference/python/qsimcirq/QSimOptions). For information on using qsim, refer to [its documentation](https://quantumai.google/qsim). For getting started using the NVIDIA cuQuantum Appliance with Cirq, visit the [overview on NGC](./index.rst).

## API Reference

### `qsimcirq.QSimOptions`

```python
qsimcirq.QSimOptions(
    max_fused_gate_size: int = 4,
    cpu_threads: int = 1,
    ev_noisy_repetitions: int = 1,
    disable_gpu: bool = False,
    gpu_mode: Union[int, Sequence[int]] = (0,),
    gpu_sim_threads: int = 256,
    gpu_state_threads: int = 512,
    gpu_data_blocks: int = 16,
    verbosity: int = 0,
    denormals_are_zeros: bool = False,
    n_subsvs: int = -1,
    use_sampler Union[bool, None] = None,
)
```

---

|  Keyword   | Description |
|------------|-------------|
| `gpu_mode` | The GPU simulator backend to use. If `1`, the simulator backend will use cuStateVec. If `n`, an integer greater than 1, the simulator will use the multi-GPU backend with the first `n` devices. If a sequence of integers, the simulator will use the multi-GPU backend with devices whose ordinals match the values in the list. Default is to use the multi-GPU backend with device 0 |
| `n_subsvs` | The number of state-vector partitions. This option is ignored unless the multi-GPU backend is in use. If `-1`, the number of partitions equals the number of GPUs. For optimal performance, ensure that the number of partitions equals the number of GPUs, and that both are a power of two |
| `use_sampler`| If `None`, the multi-GPU backend will use its sampler, and all other backends will use their default sampler. If `True`, use the multi-GPU backend's sampler. If `False`, the multi-GPU backend's sampler is disabled |
| `disable_gpu` | Whether or not to disable the GPU simulator backend. All GPU options are only considered when this is `False` (default). Note the difference from `qsimcirq`'s `use_gpu` keyword |

---

**Some examples**

```python
options = qsimcirq.QSimOptions(gpu_mode=1)  # use cuStateVec (single-GPU) backend
options = qsimcirq.QSimOptions(gpu_mode=(0,))  # use multi-GPU backend with GPU #0
options = qsimcirq.QSimOptions(gpu_mode=2)  # use multi-GPU backend with the first 2 devices
options = qsimcirq.QSimOptions(gpu_mode=(0,2))  # use multi-GPU backend with GPU #0 & #2
```