---
title: PecOptions (latest version)
description: API reference for qiskit_ibm_runtime.options_models.PecOptions in the latest version of qiskit-ibm-runtime
source: https://eu-de.quantum.cloud.ibm.com/docs/en/api/qiskit-ibm-runtime/options-models-pec-options
---

# qiskit\_ibm\_runtime.options\_models.PecOptions

*pydantic model* `PecOptions`

[GitHub](https://github.com/Qiskit/qiskit-ibm-runtime/tree/stable/0.50/qiskit_ibm_runtime/options_models/pec.py#L24-L48)

Bases: `BaseOptionsModel`

Probabalistic error cancellation mitigation options. This is only used by V2 Estimator.

**Config**

- **validate\_assignment**: *bool = True*
- **extra**: *str = forbid*

### max\_overhead

*field*

Type: `Annotated`\[`float`, `Field`(`gt``=``0`)] | `None`

Default value: `100`

The maximum circuit sampling overhead allowed, or `None` for no maximum.

In order to remove the full learned noise, the number of randomizations should be multiplied by the sampling overhead, which is `gamma^2`.

The maximum overhead limits the sampling overhead allowed.

### noise\_gain

*field*

Type: `Annotated`\[`float`, `Field`(`ge``=``0`)] | `Literal`\[`'auto'`]

Default value: `'auto'`

The amount by which to scale the noise.

The amount by which to scale the noise, where:

- A value of `0` corresponds to removing the full learned noise.
- A value of `1` corresponds to no removal of the learned noise.
- A value between `0` and `1` corresponds to partially removing the learned noise.
- A value greater than one corresponds to amplifying the learned noise.

If `"auto"`, the value in the range `[0, 1]` will be chosen automatically for each input PUB by the formula `1 - log(max_overhead) / log(gamma^2)`.

### update

`update(**kwargs)`

[GitHub](https://github.com/Qiskit/qiskit-ibm-runtime/tree/stable/0.50/qiskit_ibm_runtime/options_models/base.py#L46-L54)

Update the options.

**Parameters**

**kwargs** (*Any*)

**Return type**

None