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https://github.com/Pitt-JonesLab/mirror-gates
mirror-decomposition integrated routing for algorithm gate efficiency
https://github.com/Pitt-JonesLab/mirror-gates
qiskit quantum-computing quantum-gates transpilation
Last synced: 17 days ago
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mirror-decomposition integrated routing for algorithm gate efficiency
- Host: GitHub
- URL: https://github.com/Pitt-JonesLab/mirror-gates
- Owner: Pitt-JonesLab
- License: mit
- Created: 2023-04-19T20:26:32.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2023-11-26T22:49:49.000Z (7 months ago)
- Last Synced: 2023-11-26T23:23:10.952Z (7 months ago)
- Topics: qiskit, quantum-computing, quantum-gates, transpilation
- Language: Jupyter Notebook
- Homepage:
- Size: 65.2 MB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
Lists
- awesome-qiskit - mirror-gates - Mirage is a transpilation plugin for quantum circuits that minimizes the use of swap gates while optimizing native basis gate decomposition through mirror gates. specifically designed for iswap-based quantum systems, mirage improves circuit depth, making quantum algorithms more practical and efficient. (Community)
README
# MIRAGE
[Quantum Circuit Decomposition and Routing Collaborative Design using Mirror Gates](https://arxiv.org/abs/2308.03874)
[](https://github.com/qiskit-community/ecosystem)
[](https://zenodo.org/doi/10.5281/zenodo.10208066)
## 📌 Project Overview
- **Objective**: Optimize quantum transpilation by unifying the layout and routing stages with gate decomposition.
- **Strategy**: Employ the mirror gate of $\texttt{U}$, represented as $\texttt{U} \cdot \texttt{SWAP}$, to achieve more cost-efficient routing without altering decomposition costs. In certain cases, it can even reduce decomposition expenses.
## 🌟 Key Features
- **Mirage Algorithm**: Defined in `src/mirror_gates/mirage.py`
## 📊 Results & Comparisons
- **Experiments**: Detailed in `src/notebooks/results`
- **Findings**: Our methodology considerably reduces circuit depth and swap count when compared with conventional techniques across multiple topologies.
## 🚀 Getting Started
To use as a standalone [transpiler plugin](https://qiskit.org/documentation/apidoc/transpiler_plugins.html), install using
```
pip install -e git+https://github.com/Pitt-JonesLab/mirror-gates#egg=mirror-gates[core]
```
Then get started by exploring the main demo located at `src/mirror_gates/notebooks/bench.ipynb`.
### 💻🐒 Usage
```python
from qiskit.transpiler import CouplingMap
coupling_map = CouplingMap.from_grid(6, 6)
```
#### 1. Use as a Qiskit-Plugin
Integrate MIRAGE into your existing transpilation pipeline:
```python
from qiskit import transpile
mirage_qc = transpile(
qc, # input circuit
optimization_level = 3, # default: Qiskit's highest level
coupling_map=coupling_map,
basis_gates= ["u", "xx_plus_yy", "id"],
routing_method="mirage",
layout_method="sabre_layout_v2",
)
```
#### 2. Use Mirage as a complete pass manager.
Handles all pre-, post-processing stages described in our paper:
```python
from mirror_gates.pass_managers import Mirage
mirage = Mirage(
coupling_map, # coupling map
name="Mirage-$\sqrt{\texttt{iSWAP}}$", # transpile_benchy and figure labels)
parallel=True, # run trials in parallel or serial
cx_basis=False, # turning on sets CNOT as the basis gate,
# (can take arbitrary basis but parameters are not configured that way yet)
cost_function="depth", # switch to "basic" for counting SWAPs
fixed_aggression=None, # force aggression level on all iterations
layout_trials=None, # how many independent layout trials to run (20)
fb_iters=None, # how many forward-backward iterations to run (4)
swap_trials=None, # how many independent routing trials to run (20)
no_vf2=False, # keep False to use VF2 for finding complete layouts
logger=None, # from logging moduel
)
mirage_qc = mirage.run(circuit=qc)
```
[!WARNING]
[!WARNING]
In the current version of Qiskit, there's no direct support for \( \sqrt{iSWAP} \) as a basis gate. As a workaround, I've been using `XX+YY`, which provides a partial solution but isn't fully optimized.
However, there's an ongoing [pull request](https://github.com/Qiskit/qiskit-terra/pull/9375) in Qiskit that introduces a new gate, `SiSwapGate`, which represents \( \sqrt{iSWAP} \). This PR also brings in optimized decomposition methods for the gate. I've previously [implemented a similar logic](https://github.com/Pitt-JonesLab/slam_decomposition/blob/main/src/slam/utils/transpiler_pass/weyl_decompose.py), but the PR suggests there might have been some inaccuracies in the paper I referenced.
To benefit from the advancements in the PR, I'm temporarily using a [fork of the PR](https://github.com/evmckinney9/qiskit-evmckinney9/tree/sqisw-gate) in this project. By leveraging the fork, when you use the `SiSwapGate`, you'll notice a more efficient decomposition compared to the `XX+YY` workaround.
Please note that this is a provisional solution. I'll transition back to the main Qiskit repository once the PR is merged and the `SiSwapGate` with its decomposition methods becomes officially available.
### 📋 Prerequisites
- **Monodromy Dependency**: This needs lrs. To install:
- `sudo apt install lrslib`
- **Package Dependencies**: By default, two other packages are dependencies:
- [transpile_benchy](https://github.com/evmckinney9/transpile_benchy): Manages circuit benchmarks, data analytics, and plotting.
- [monodromy (fork)](https://github.com/evmckinney9/monodromy): modified for Qiskit AnalysisPass integration.
- ⚠️ **Setup**: Running `make init` sets up the required environment and tools. It also clones required repositories.
- **Optional**: If you want to leverage the additional features from transpile_benchy, especially its submodules for circuit benchmarking, run `make dev-init`. This will clone and set up transpile_benchy with its complete functionalities.
### Dive Deeper into the Code 💻🐒
- **Please report any issues**. (Currently the most unstable part is related to the parallel processing. 😺)
- The main logic of the MIRAGE pass is in `src/mirror_gates/mirage.py` which includes `ParallelMirage`, and the class `Mirage`, a subclass of `qiskit.transpiler.passes.SabreSwap` to handle serial passes.
- The main pass manager is defined in `src/mirror_gates/pass_managers.py`.
- Circuit benchmarks are defined as `.txt` files in `src/mirror_gates/circuits/`. These are loaded into a `transpile_benchy.Library` object.
- For more details, see code documentation or contact me.
Additional utility commands available in the Makefile:
- **make format**: Formats the codebase.
- **make clean**: Cleans up temporary and unnecessary files.
- **make test**: Runs tests to ensure code functionality.
- For more information about the repository structure, visit my [python-template](https://github.com/evmckinney9/python-template).
## 📚 Reference
```bibtex
@article{McKinney_MIRAGE_Quantum_Circuit_2023,
author = {McKinney, Evan and Hatridge, Michael and Jones, Alex K},
doi = {10.48550/arXiv.2308.03874},
journal = {arXiv preprint arXiv:2308.03874},
title = {{MIRAGE: Quantum Circuit Decomposition and Routing Collaborative Design using Mirror Gates}},
year = {2023}
}
```