---
title: IdentityFidelityModel (latest version)
description: API reference for qiskit_noise_learning.models.IdentityFidelityModel in the latest version of qiskit-noise-learning
source: https://quantum.cloud.ibm.com/docs/en/api/qiskit-noise-learning/generated/models-identity-fidelity-model
---

# qiskit\_noise\_learning.models.IdentityFidelityModel

*class* `qiskit_noise_learning.models.IdentityFidelityModel(gate_set: GateSet)`

[GitHub](https://github.com/Qiskit/qiskit-noise-learning/tree/stable/0.1/qiskit_noise_learning/models/identity_fidelity_model.py)

Bases: [`LinearMap`](/docs/api/qiskit-noise-learning/generated/math-linear-map "qiskit_noise_learning.math.linear_map.LinearMap")\[[`FidelityIndex`](/docs/api/qiskit-noise-learning/generated/sequences-fidelity-index "qiskit_noise_learning.sequences.fidelity_index.FidelityIndex"), [`FidelityIndex`](/docs/api/qiskit-noise-learning/generated/sequences-fidelity-index "qiskit_noise_learning.sequences.fidelity_index.FidelityIndex")]

A fidelity model whose parameters are the log fidelities themselves.

The parameterization matrix is the identity: the input and output spaces are the same [`LogFidelitySpace`](/docs/api/qiskit-noise-learning/generated/models-log-fidelity-space "qiskit_noise_learning.models.LogFidelitySpace"), and the row of a fidelity index is the unit vector on that index.

**Parameters**

**gate\_set** – The gate set whose fidelities are being modelled. To be converted to a [`ModelGateSet`](/docs/api/qiskit-noise-learning/generated/gate-sets-model-gate-set "qiskit_noise_learning.gate_sets.ModelGateSet").

### \_\_init\_\_

`__init__(gate_set: GateSet)`

## Methods

|                                                                                                                                                     |                                                                     |
| --------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------- |
| [`__init__`](#qiskit_noise_learning.models.IdentityFidelityModel.__init__ "qiskit_noise_learning.models.IdentityFidelityModel.__init__")(gate\_set) |                                                                     |
| `compose`(outer)                                                                                                                                    | Post-compose: self maps I->O, outer maps O->C, result maps I->C.    |
| `left_multiply`(matrix)                                                                                                                             | Multiply on the left by an explicit matrix.                         |
| `pre_compose`(inner)                                                                                                                                | Pre-compose: inner maps A->I, self maps I->O, result maps A->O.     |
| `projected_output`(output\_indices, vector)                                                                                                         | Compute a projection of the map applied to a vector.                |
| [`rows`](#qiskit_noise_learning.models.IdentityFidelityModel.rows "qiskit_noise_learning.models.IdentityFidelityModel.rows")(output\_indices)       | Construct the sub-matrix whose rows are the given fidelity indices. |

## Attributes

|                                                                                                                                          |                                                   |
| ---------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------- |
| [`gate_set`](#qiskit_noise_learning.models.IdentityFidelityModel.gate_set "qiskit_noise_learning.models.IdentityFidelityModel.gate_set") | The gate set whose fidelities are being modelled. |
| `input_space`                                                                                                                            | The input space.                                  |
| `output_space`                                                                                                                           | The output space.                                 |

### gate\_set

Type: [`ModelGateSet`](/docs/api/qiskit-noise-learning/generated/gate-sets-model-gate-set "qiskit_noise_learning.gate_sets.model_gate_set.ModelGateSet")

The gate set whose fidelities are being modelled.

### rows

`rows(output_indices: Iterable[FidelityIndex]) → IndexedMatrix[FidelityIndex, FidelityIndex]`

Construct the sub-matrix whose rows are the given fidelity indices.

Each row is the unit vector on its fidelity index (the identity parameterization).

**Parameters**

**output\_indices** – The fidelity indices labelling the desired rows.

**Returns**

An [`IndexedMatrix`](/docs/api/qiskit-noise-learning/generated/math-indexed-matrix "qiskit_noise_learning.math.IndexedMatrix") whose rows and columns are both the requested fidelity indices, with identity data.