54 lines
3.1 KiB
Plaintext
54 lines
3.1 KiB
Plaintext
---
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title: qaoa_ansatz (latest version)
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description: API reference for qiskit.circuit.library.qaoa_ansatz in the latest version of qiskit
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in_page_toc_min_heading_level: 1
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python_api_type: class
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python_api_name: qiskit.circuit.library.qaoa_ansatz
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---
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<span id="qaoa-ansatz" />
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# qaoa\_ansatz
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<Class id="qiskit.circuit.library.qaoa_ansatz" isDedicatedPage={true} github="https://github.com/Qiskit/qiskit/tree/stable/1.3/qiskit/circuit/library/n_local/qaoa_ansatz.py#L33-L105" signature="qiskit.circuit.library.qaoa_ansatz(cost_operator, reps=1, initial_state=None, mixer_operator=None, insert_barriers=False, name='QAOA', flatten=True)" modifiers="class">
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Bases:
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A generalized QAOA quantum circuit with a support of custom initial states and mixers.
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**Examples**
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To define the QAOA ansatz we require a cost Hamiltonian, encoding the classical optimization problem:
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```python
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from qiskit.quantum_info import SparsePauliOp
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from qiskit.circuit.library import qaoa_ansatz
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cost_operator = SparsePauliOp(["ZZII", "IIZZ", "ZIIZ"])
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ansatz = qaoa_ansatz(cost_operator, reps=3, insert_barriers=True)
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ansatz.draw("mpl")
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```
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**Parameters**
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* **cost\_operator** (*BaseOperator*) – The operator representing the cost of the optimization problem, denoted as $U(C, \gamma)$ in \[1].
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* **reps** ([*int*](https://docs.python.org/3/library/functions.html#int "(in Python v3.13)")) – The integer determining the depth of the circuit, called $p$ in \[1].
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* **initial\_state** ([*QuantumCircuit*](qiskit.circuit.QuantumCircuit "qiskit.circuit.QuantumCircuit") *| None*) – An optional initial state to use, which defaults to a layer of Hadamard gates preparing the $|+\rangle^{\otimes n}$ state. If a custom mixer is chosen, this circuit should be set to prepare its ground state, to appropriately fulfill the annealing conditions.
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* **mixer\_operator** (*BaseOperator | None*) – An optional custom mixer, which defaults to global Pauli-$X$ rotations. This is denoted as $U(B, \beta)$ in \[1]. If this is set, the `initial_state` might also require modification.
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* **insert\_barriers** ([*bool*](https://docs.python.org/3/library/functions.html#bool "(in Python v3.13)")) – Whether to insert barriers in-between the cost and mixer operators.
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* **name** ([*str*](https://docs.python.org/3/library/stdtypes.html#str "(in Python v3.13)")) – The name of the circuit.
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* **flatten** ([*bool*](https://docs.python.org/3/library/functions.html#bool "(in Python v3.13)")) – If `True`, a flat circuit is returned instead of nesting it inside multiple layers of gate objects. Setting this to `False` is significantly less performant, especially for parameter binding, but can be desirable for a cleaner visualization.
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**Return type**
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[QuantumCircuit](qiskit.circuit.QuantumCircuit "qiskit.circuit.QuantumCircuit")
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**References**
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**\[1]: Farhi et al., A Quantum Approximate Optimization Algorithm.**
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[arXiv:1411.4028](https://arxiv.org/pdf/1411.4028)
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</Class>
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