initial commit

.github/workflows/ci.yml

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+name: Python Code Quality Checks
+
+on:
+  push:
+    branches: [ "main" ]
+  pull_request:
+    branches: [ "main" ]
+
+jobs:
+  code-quality:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.9", "3.10", "3.11"]
+
+    steps:
+    - uses: actions/checkout@v3
+
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v4
+      with:
+        python-version: ${{ matrix.python-version }}
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install black pylint pytest
+        pip install .
+    
+    - name: Check code formatting with Black
+      run: |
+        black --check --diff .
+    
+    - name: Run Pylint
+      run: |
+        pylint $(git ls-files '*.py') --disable=C0301,R0913,R0914
+    
+    - name: Run tests
+      run: |
+        python -m pytest tests/ -v
+
+  build-success:
+    needs: code-quality
+    runs-on: ubuntu-latest
+    steps:
+    - name: Build success
+      run: echo "All code quality checks passed!"

.gitignore

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+# editor files
+.vscode/
+.idea/
+
+#standard python ignores follow
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+.pytest_cache/
+*.py[cod]
+*$py.class
+
+# Distribution / packaging
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# dotenv
+.env
+
+# virtualenv
+.venv
+venv/
+ENV/
+
+.DS_Store

README.md

@@ -1 +1,42 @@
-# gadd
+# Genetic Algorithm-based optimization of Dynamical Decoupling (GADD)
+
+This is the companion repository to the paper [Empirical learning of dynamical decoupling on quantum processors](https://arxiv.org/abs/2403.02294). You can use this code to train on physical processors then run target circuits with sequences found via GADD.
+
+## Installation
+
+The package can be installed by running `pip install .` in the root directory of the package. If you would like to make changes to the package, you should run `pip install -e .` instead to install it in editable mode.
+
+## Usage
+
+This package is designed to be used on top of [Qiskit](https://github.com/Qiskit/qiskit) and the [Qiskit Runtime IBM Client](https://github.com/Qiskit/qiskit-ibm-runtime).
+
+The core class `GADD` runs the genetic algorithm training process
+on training circuits, outputting the best sequence and intermediate training data, if desired, which can be then used to run on a target circuit:
+
+```
+service = QiskitRuntimeService()
+backend = service.least_busy(operational=True, simulator=False, min_num_qubits=n_qubits)
+
+with Batch(backend=backend):
+    sampler = SamplerV2()
+    gadd = GADD(backend=backend)
+
+    # train
+    [seq, data] = gadd.train(backend=backend,
+        sampler=sampler,
+        training_circuit=training_circuit,
+        utility_function=utility_function,
+        save_iterations=True,
+        comparison_seqs=["baseline", "xy4", "cpmg","edd"])
+
+    # visualize the training progression
+    gadd.plot(seq, data)
+
+    # run on target circuit (can run on a different backend)
+    gadd.run(
+        seq = seq,
+        target_circuit=target_circuit,
+        sampler=sampler
+    )
+```
+

gadd/VERSION.txt

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+0.1

gadd/__init__.py

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+from .gadd import GADD
+from .sequences import DDSequence, StandardSequences, DDStrategy
+from .library import SequenceUtility
+from .utility_functions import UtilityFunction