Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

fixed typo #2512

Closed
wants to merge 1 commit into from
Closed

fixed typo #2512

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion docs/api/qiskit-ibm-runtime/0.28/qiskit_ibm_runtime.options.ZneOptions.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ python_api_name: qiskit_ibm_runtime.options.ZneOptions

When this option is selected, gate twirling will always be used whether or not it has been enabled in the options.

In this technique, the twirled noise model of each each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.
In this technique, the twirled noise model of each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.

* **noise\_factors** – Noise factors to use for noise amplification. Default: (1, 1.5, 2) for PEA, and (1, 3, 5) otherwise.

Expand Down
2 changes: 1 addition & 1 deletion docs/api/qiskit-ibm-runtime/0.29/qiskit_ibm_runtime.options.ZneOptions.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ python_api_name: qiskit_ibm_runtime.options.ZneOptions

When this option is selected, gate twirling will always be used whether or not it has been enabled in the options.

In this technique, the twirled noise model of each each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.
In this technique, the twirled noise model of each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.

* **noise\_factors** – Noise factors to use for noise amplification. Default: `(1, 1.5, 2)` for PEA, and `(1, 3, 5)` otherwise.

Expand Down
2 changes: 1 addition & 1 deletion docs/api/qiskit-ibm-runtime/0.30/qiskit_ibm_runtime.options.ZneOptions.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ python_api_name: qiskit_ibm_runtime.options.ZneOptions

When this option is selected, gate twirling will always be used whether or not it has been enabled in the options.

In this technique, the twirled noise model of each each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.
In this technique, the twirled noise model of each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.

* **noise\_factors** – Noise factors to use for noise amplification. Default: `(1, 1.5, 2)` for PEA, and `(1, 3, 5)` otherwise.

Expand Down
2 changes: 1 addition & 1 deletion docs/api/qiskit-ibm-runtime/0.31/qiskit_ibm_runtime.options.ZneOptions.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ python_api_name: qiskit_ibm_runtime.options.ZneOptions

When this option is selected, gate twirling will always be used whether or not it has been enabled in the options.

In this technique, the twirled noise model of each each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.
In this technique, the twirled noise model of each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.

* **noise\_factors** – Noise factors to use for noise amplification. Default: `(1, 1.5, 2)` for PEA, and `(1, 3, 5)` otherwise.

Expand Down
2 changes: 1 addition & 1 deletion docs/api/qiskit-ibm-runtime/0.32/qiskit_ibm_runtime.options.ZneOptions.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ python_api_name: qiskit_ibm_runtime.options.ZneOptions

When this option is selected, gate twirling will always be used whether or not it has been enabled in the options.

In this technique, the twirled noise model of each each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.
In this technique, the twirled noise model of each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.

* **noise\_factors** – Noise factors to use for noise amplification. Default: `(1, 1.5, 2)` for PEA, and `(1, 3, 5)` otherwise.

Expand Down
2 changes: 1 addition & 1 deletion docs/api/qiskit-ibm-runtime/0.33/qiskit_ibm_runtime.options.ZneOptions.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ python_api_name: qiskit_ibm_runtime.options.ZneOptions

When this option is selected, gate twirling will always be used whether or not it has been enabled in the options.

In this technique, the twirled noise model of each each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.
In this technique, the twirled noise model of each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.

* **noise\_factors** (*UnsetType | Sequence\[float]*) – Noise factors to use for noise amplification. Default: `(1, 1.5, 2)` for PEA, and `(1, 3, 5)` otherwise.

Expand Down
2 changes: 1 addition & 1 deletion docs/api/qiskit-ibm-runtime/dev/qiskit_ibm_runtime.options.ZneOptions.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ python_api_name: qiskit_ibm_runtime.options.ZneOptions

When this option is selected, gate twirling will always be used whether or not it has been enabled in the options.

In this technique, the twirled noise model of each each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.
In this technique, the twirled noise model of each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.

* **noise\_factors** (*UnsetType | Sequence\[float]*) – Noise factors to use for noise amplification. Default: `(1, 1.5, 2)` for PEA, and `(1, 3, 5)` otherwise.

Expand Down
2 changes: 1 addition & 1 deletion docs/api/qiskit-ibm-runtime/qiskit_ibm_runtime.options.ZneOptions.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ python_api_name: qiskit_ibm_runtime.options.ZneOptions

When this option is selected, gate twirling will always be used whether or not it has been enabled in the options.

In this technique, the twirled noise model of each each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.
In this technique, the twirled noise model of each unique layer of entangling gates in your ISA circuits is learned beforehand, see [`LayerNoiseLearningOptions`](qiskit_ibm_runtime.options.LayerNoiseLearningOptions "qiskit_ibm_runtime.options.LayerNoiseLearningOptions") for relevant learning options. Once complete, your circuits are executed at each noise factor, where every entangling layer of your circuits is amplified by probabilistically injecting single-qubit noise proportional to the corresponding learned noise model.

* **noise\_factors** (*UnsetType | Sequence\[float]*) – Noise factors to use for noise amplification. Default: `(1, 1.5, 2)` for PEA, and `(1, 3, 5)` otherwise.

Expand Down
2 changes: 1 addition & 1 deletion docs/api/qiskit/0.19/qiskit.aqua.operators.evolutions.QDrift.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@ python_api_name: qiskit.aqua.operators.evolutions.QDrift
# QDrift

<Class id="qiskit.aqua.operators.evolutions.QDrift" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-aqua/tree/stable/0.7/qiskit/aqua/operators/evolutions/trotterizations/qdrift.py" signature="QDrift(reps=1)" modifiers="class">
The QDrift Trotterization method, which selects each each term in the Trotterization randomly, with a probability proportional to its weight. Based on the work of Earl Campbell in [https://arxiv.org/abs/1811.08017](https://arxiv.org/abs/1811.08017).
The QDrift Trotterization method, which selects each term in the Trotterization randomly, with a probability proportional to its weight. Based on the work of Earl Campbell in [https://arxiv.org/abs/1811.08017](https://arxiv.org/abs/1811.08017).

**Parameters**

Expand Down
2 changes: 1 addition & 1 deletion docs/api/qiskit/0.19/qiskit.aqua.operators.evolutions.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -49,5 +49,5 @@ The EvolutionBase class gives an interface for algorithms to ask for Evolutions
| [`TrotterizationFactory`](qiskit.aqua.operators.evolutions.TrotterizationFactory "qiskit.aqua.operators.evolutions.TrotterizationFactory") | A factory for conveniently creating TrotterizationBase instances. |
| [`Trotter`](qiskit.aqua.operators.evolutions.Trotter "qiskit.aqua.operators.evolutions.Trotter") | Simple Trotter expansion, composing the evolution circuits of each Operator in the sum together `reps` times and dividing the evolution time of each by `reps`. |
| [`Suzuki`](qiskit.aqua.operators.evolutions.Suzuki "qiskit.aqua.operators.evolutions.Suzuki") | Suzuki Trotter expansion, composing the evolution circuits of each Operator in the sum together by a recursive “bookends” strategy, repeating the whole composed circuit `reps` times. |
| [`QDrift`](qiskit.aqua.operators.evolutions.QDrift "qiskit.aqua.operators.evolutions.QDrift") | The QDrift Trotterization method, which selects each each term in the Trotterization randomly, with a probability proportional to its weight. |
| [`QDrift`](qiskit.aqua.operators.evolutions.QDrift "qiskit.aqua.operators.evolutions.QDrift") | The QDrift Trotterization method, which selects each term in the Trotterization randomly, with a probability proportional to its weight. |

2 changes: 1 addition & 1 deletion docs/api/qiskit/0.24/qiskit.aqua.operators.evolutions.QDrift.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@ python_api_name: qiskit.aqua.operators.evolutions.QDrift
# qiskit.aqua.operators.evolutions.QDrift

<Class id="qiskit.aqua.operators.evolutions.QDrift" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-aqua/tree/stable/0.8/qiskit/aqua/operators/evolutions/trotterizations/qdrift.py" signature="QDrift(reps=1)" modifiers="class">
The QDrift Trotterization method, which selects each each term in the Trotterization randomly, with a probability proportional to its weight. Based on the work of Earl Campbell in [https://arxiv.org/abs/1811.08017](https://arxiv.org/abs/1811.08017).
The QDrift Trotterization method, which selects each term in the Trotterization randomly, with a probability proportional to its weight. Based on the work of Earl Campbell in [https://arxiv.org/abs/1811.08017](https://arxiv.org/abs/1811.08017).

**Parameters**

Expand Down
2 changes: 1 addition & 1 deletion docs/api/qiskit/0.24/qiskit.aqua.operators.evolutions.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -49,5 +49,5 @@ The EvolutionBase class gives an interface for algorithms to ask for Evolutions
| [`TrotterizationFactory`](qiskit.aqua.operators.evolutions.TrotterizationFactory "qiskit.aqua.operators.evolutions.TrotterizationFactory") | A factory for conveniently creating TrotterizationBase instances. |
| [`Trotter`](qiskit.aqua.operators.evolutions.Trotter "qiskit.aqua.operators.evolutions.Trotter") | Simple Trotter expansion, composing the evolution circuits of each Operator in the sum together `reps` times and dividing the evolution time of each by `reps`. |
| [`Suzuki`](qiskit.aqua.operators.evolutions.Suzuki "qiskit.aqua.operators.evolutions.Suzuki") | Suzuki Trotter expansion, composing the evolution circuits of each Operator in the sum together by a recursive “bookends” strategy, repeating the whole composed circuit `reps` times. |
| [`QDrift`](qiskit.aqua.operators.evolutions.QDrift "qiskit.aqua.operators.evolutions.QDrift") | The QDrift Trotterization method, which selects each each term in the Trotterization randomly, with a probability proportional to its weight. |
| [`QDrift`](qiskit.aqua.operators.evolutions.QDrift "qiskit.aqua.operators.evolutions.QDrift") | The QDrift Trotterization method, which selects each term in the Trotterization randomly, with a probability proportional to its weight. |

2 changes: 1 addition & 1 deletion docs/api/qiskit/0.25/qiskit.aqua.operators.evolutions.QDrift.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@ python_api_name: qiskit.aqua.operators.evolutions.QDrift
# qiskit.aqua.operators.evolutions.QDrift

<Class id="qiskit.aqua.operators.evolutions.QDrift" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-aqua/tree/stable/0.9/qiskit/aqua/operators/evolutions/trotterizations/qdrift.py" signature="QDrift(reps=1)" modifiers="class">
The QDrift Trotterization method, which selects each each term in the Trotterization randomly, with a probability proportional to its weight. Based on the work of Earl Campbell in [https://arxiv.org/abs/1811.08017](https://arxiv.org/abs/1811.08017).
The QDrift Trotterization method, which selects each term in the Trotterization randomly, with a probability proportional to its weight. Based on the work of Earl Campbell in [https://arxiv.org/abs/1811.08017](https://arxiv.org/abs/1811.08017).

**Parameters**

Expand Down
2 changes: 1 addition & 1 deletion docs/api/qiskit/0.25/qiskit.aqua.operators.evolutions.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -49,5 +49,5 @@ The EvolutionBase class gives an interface for algorithms to ask for Evolutions
| [`TrotterizationFactory`](qiskit.aqua.operators.evolutions.TrotterizationFactory "qiskit.aqua.operators.evolutions.TrotterizationFactory") | A factory for conveniently creating TrotterizationBase instances. |
| [`Trotter`](qiskit.aqua.operators.evolutions.Trotter "qiskit.aqua.operators.evolutions.Trotter") | Simple Trotter expansion, composing the evolution circuits of each Operator in the sum together `reps` times and dividing the evolution time of each by `reps`. |
| [`Suzuki`](qiskit.aqua.operators.evolutions.Suzuki "qiskit.aqua.operators.evolutions.Suzuki") | Suzuki Trotter expansion, composing the evolution circuits of each Operator in the sum together by a recursive “bookends” strategy, repeating the whole composed circuit `reps` times. |
| [`QDrift`](qiskit.aqua.operators.evolutions.QDrift "qiskit.aqua.operators.evolutions.QDrift") | The QDrift Trotterization method, which selects each each term in the Trotterization randomly, with a probability proportional to its weight. |
| [`QDrift`](qiskit.aqua.operators.evolutions.QDrift "qiskit.aqua.operators.evolutions.QDrift") | The QDrift Trotterization method, which selects each term in the Trotterization randomly, with a probability proportional to its weight. |

2 changes: 1 addition & 1 deletion docs/api/qiskit/0.25/qiskit.opflow.evolutions.QDrift.mdx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@ python_api_name: qiskit.opflow.evolutions.QDrift
# qiskit.opflow\.evolutions.QDrift

<Class id="qiskit.opflow.evolutions.QDrift" isDedicatedPage={true} github="https://github.com/qiskit/qiskit/tree/stable/0.17/qiskit/opflow/evolutions/trotterizations/qdrift.py" signature="QDrift(reps=1)" modifiers="class">
The QDrift Trotterization method, which selects each each term in the Trotterization randomly, with a probability proportional to its weight. Based on the work of Earl Campbell in [https://arxiv.org/abs/1811.08017](https://arxiv.org/abs/1811.08017).
The QDrift Trotterization method, which selects each term in the Trotterization randomly, with a probability proportional to its weight. Based on the work of Earl Campbell in [https://arxiv.org/abs/1811.08017](https://arxiv.org/abs/1811.08017).

**Parameters**

Expand Down
Loading