qiskit-documentation/docs/api/qiskit-addon-mpf/backends-quimb-circuit.mdx

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---
title: quimb_circuit (latest version)
description: API reference for qiskit_addon_mpf.backends.quimb_circuit in the latest version of qiskit-addon-mpf
in_page_toc_min_heading_level: 2
python_api_type: module
python_api_name: qiskit_addon_mpf.backends.quimb_circuit
---
<span id="module-qiskit_addon_mpf.backends.quimb_circuit" />
<span id="quimb-circuit-based-backend-qiskit-addon-mpf-backends-quimb-circuit" />
# Quimb circuit-based backend
`qiskit_addon_mpf.backends.quimb_circuit`
A circuit-based time-evolution backend using [`quimb`](https://quimb.readthedocs.io/en/latest/autoapi/quimb/index.html#module-quimb "(in quimb v1.10)").
<Admonition title="Warning" type="caution">
This backend is only available if the optional dependencies have been installed:
```python
pip install "qiskit-addon-mpf[quimb]"
```
</Admonition>
| | |
| ------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------- |
| [`CircuitEvolver`](backends-quimb-circuit-circuit-evolver "qiskit_addon_mpf.backends.quimb_circuit.CircuitEvolver") | A time-evolution engine based on quantum circuits. |
| [`CircuitState`](backends-quimb-circuit-circuit-state "qiskit_addon_mpf.backends.quimb_circuit.CircuitState") | An MPO-like representation of a time-evolution state based on quantum circuits. |
## Underlying method
Quimb boasts direct support for the simulation of quantum circuits in the form of its tensor-network based [`quimb.tensor.Circuit`](https://quimb.readthedocs.io/en/latest/autoapi/quimb/tensor/index.html#quimb.tensor.Circuit "(in quimb v1.10)") representation. We can leverage this, to bypass any explicit time-evolution algorithm and instead directly encode the time-evolution in a [`QuantumCircuit`](/api/qiskit/qiskit.circuit.QuantumCircuit "(in Qiskit v1.4)") and use [`quimb`](https://quimb.readthedocs.io/en/latest/autoapi/quimb/index.html#module-quimb "(in quimb v1.10)") to compute the overlap between two such circuits. For more information, check out their guide on [Quantum Circuits](https://quimb.readthedocs.io/en/latest/tensor-circuit.html "(in quimb v1.10)").
## Code example
This section shows a simple example to get you started with using this backend. The example shows how to create the three factory functions required for the [`setup_dynamic_lse()`](dynamic#setup_dynamic_lse "qiskit_addon_mpf.dynamic.setup_dynamic_lse").
The [`IdentityStateFactory`](dynamic#identitystatefactory "qiskit_addon_mpf.dynamic.IdentityStateFactory") protocol is already fulfilled by the [`CircuitState`](backends-quimb-circuit-circuit-state "qiskit_addon_mpf.backends.quimb_circuit.CircuitState") constructor, rendering the `identity_factory` argument trivial:
```python
>>> from qiskit_addon_mpf.backends.quimb_circuit import CircuitState
>>> identity_factory = CircuitState
```
The setup of the [`CircuitEvolver`](backends-quimb-circuit-circuit-evolver "qiskit_addon_mpf.backends.quimb_circuit.CircuitEvolver") is slightly more involved. It requires a **parameterized** [`QuantumCircuit`](/api/qiskit/qiskit.circuit.QuantumCircuit "(in Qiskit v1.4)") object as its input where the [`Parameter`](/api/qiskit/qiskit.circuit.Parameter "(in Qiskit v1.4)") should take the place of the Trotter methods time step (`dt`).
To show how such a parameterized Trotter circuit template is constructed, we reuse the same Hamiltonian and second-order Suzuki-Trotter formula as in [`quimb_layers`](backends-quimb-layers#module-qiskit_addon_mpf.backends.quimb_layers "qiskit_addon_mpf.backends.quimb_layers").
```python
>>> from qiskit.quantum_info import SparsePauliOp
>>> hamil = SparsePauliOp.from_sparse_list(
... [("ZZ", (i, i+1), 1.0) for i in range(0, 9, 2)] +
... [("Z", (i,), 0.5) for i in range(10)] +
... [("ZZ", (i, i+1), 1.0) for i in range(1, 9, 2)] +
... [("X", (i,), 0.25) for i in range(10)],
... num_qubits=10,
... )
```
But this time, we specify a [`Parameter`](/api/qiskit/qiskit.circuit.Parameter "(in Qiskit v1.4)") as the `time` argument when constructing the actual circuits.
```python
>>> from functools import partial
>>> from qiskit.circuit import Parameter
>>> from qiskit.synthesis import SuzukiTrotter
>>> from qiskit_addon_mpf.backends.quimb_circuit import CircuitEvolver
>>> from qiskit_addon_utils.problem_generators import generate_time_evolution_circuit
>>> dt = Parameter("dt")
>>> suzuki_2 = generate_time_evolution_circuit(hamil, time=dt, synthesis=SuzukiTrotter(order=2))
>>> approx_evolver_factory = partial(CircuitEvolver, circuit=suzuki_2)
```
<Admonition title="Caution" type="note">
It is **necessary** that the name of the [`Parameter`](/api/qiskit/qiskit.circuit.Parameter "(in Qiskit v1.4)") is `dt`!
</Admonition>
We can choose a higher order Trotter formula for the `exact_evolver_factory`. But note, that we must once again use a parameterized circuit, even if we immediately bind its parameter when constructing the `partial` function.
```python
>>> suzuki_4 = generate_time_evolution_circuit(hamil, time=dt, synthesis=SuzukiTrotter(order=4))
>>> exact_evolver_factory = partial(CircuitEvolver, circuit=suzuki_4, dt=0.05)
```
These factory functions may now be used to run the [`setup_dynamic_lse()`](dynamic#setup_dynamic_lse "qiskit_addon_mpf.dynamic.setup_dynamic_lse"). Refer to its documentation for more details on that.