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Fix typo; update contributing guidelines (amazon-braket#76)
* Fix typo; update contributing guidelines * Update CONTRIBUTING.md * re-run notebook for output Co-authored-by: Cody Wang <speller26@gmail.com>
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‎CONTRIBUTING.md

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@@ -54,9 +54,7 @@ When you make a contribution please ensure that you
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1. Follow the existing flow of a notebook ([example](https://github.com/aws/amazon-braket-examples/blob/main/examples/getting_started/1_Running_quantum_circuits_on_simulators.ipynb)).
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1. Do not duplicate existing information but refer to other examples as relevant.
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1. Only have Open Source licensed dependencies in your example.
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1. Ensure that your example runs without issues on both a recent Braket Notebook Instance (create a new Braket Notebook Instance or restart one from Amazon Braket [in the console](https://docs.aws.amazon.com/braket/latest/developerguide/braket-get-started-create-notebook.html)) and locally, using our most [recently released Amazon Braket SDK version](https://github.com/aws/amazon-braket-sdk-python/blob/main/README.md#installing-the-amazon-braket-python-sdk).
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1. Ensure that your example runs without issues on both a recent Braket Notebook Instance (create a new Braket Notebook Instance or restart one from Amazon Braket [in the console](https://docs.aws.amazon.com/braket/latest/developerguide/braket-get-started-create-notebook.html)) and locally, using our most [recently released Amazon Braket SDK version](https://github.com/aws/amazon-braket-sdk-python/blob/main/README.md#installing-the-amazon-braket-python-sdk). Run the entire notebook by clicking `Cells > Run All`, either in the console or locally, and confirm that every cell completes without error.
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### Send a Pull Request
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GitHub provides additional documentation on [Creating a Pull Request](https://help.github.com/articles/creating-a-pull-request/).

‎examples/braket_features/Simulating_Noise_On_Amazon_Braket.ipynb

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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 2,
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"source": [
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"from braket.circuits import Circuit, Observable, Gate, Noise\n",
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"from braket.devices import LocalSimulator\n",
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 3,
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"source": [
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"# enter the S3 bucket you created during onboarding (or any other bucket starting with \"amazon-braket-\") \n",
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"my_bucket = \"amazon-braket-Your-Bucket-Name\" # the name of the bucket\n",
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 4,
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"source": [
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"# build a simple circuit\n",
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"circ = Circuit().h(0).cnot(0,1)\n",
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"measurement results: Counter({'00': 418, '11': 385, '01': 102, '10': 95})\n"
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"measurement results: Counter({'00': 431, '11': 410, '01': 88, '10': 71})\n"
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]
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}
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],
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 5,
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"source": [
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"def ghz_circuit(n_qubits: int) -> Circuit:\n",
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" \"\"\"\n",
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"measurement results: Counter({'0000000000000': 2, '0011000000001': 1, '0111110000000': 1, '1000010100000': 1, '1000001000000': 1, '1110111111110': 1, '1110000000011': 1, '0011001000000': 1, '0000001101011': 1})\n"
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"measurement results: Counter({'1111111111000': 1, '0000000000001': 1, '0000000011111': 1, '1111001000000': 1, '1011111111111': 1, '0000000000000': 1, '1111100000000': 1, '1110000001111': 1, '1111111000111': 1, '0010000000000': 1})\n"
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]
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}
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],
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 6,
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"source": [
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"# define a bit flip noise channel with probability = 0.1\n",
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"noise = Noise.BitFlip(probability=0.1)\n",
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 7,
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"source": [
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"# define a phase flip noise channel\n",
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"noise = Noise.PhaseFlip(probability=0.1)\n",
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 8,
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"source": [
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"# creat an arbitrary 2-qubit Kraus matrix\n",
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"E0 = unitary_group.rvs(4) * np.sqrt(0.2) \n",
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 9,
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"source": [
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"K_invalid = [np.random.randn(2,2), np.random.randn(2,2)] \n",
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"\n",
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 10,
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"source": [
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"# apply depolarizing noise\n",
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"circ = Circuit().x(0).x(1).cnot(0,1).depolarizing(1, probability=0.2).x(0).two_qubit_dephasing(target1=0, target2=1, probability=0.1)\n",
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 11,
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"source": [
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"noise = Noise.PhaseDamping(gamma=0.1)\n",
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"\n",
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"source": [
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"# the noise channel is applied to all the X gates in the circuit\n",
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"circ = Circuit().x(0).y(1).cnot(0,2).x(1).z(2)\n",
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 13,
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"source": [
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"U1=unitary_group.rvs(4)\n",
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"U2=unitary_group.rvs(4)\n",
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"source": [
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"# the noise channel is applied to every gate on qubits 0 and 2\n",
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"circ = Circuit().x(0).y(1).cnot(0,2).x(1).z(2)\n",
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": 15,
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"source": [
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"# the noise channel is applied to X gate on qubits 0\n",
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"circ = Circuit().x(0).y(1).cnot(0,2).x(0).x(1).z(2)\n",
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"source": [
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"# define two noise channels\n",
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"noise1 = Noise.Depolarizing(probability=0.1)\n",
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"source": [
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"# define a two-qubit noise channel\n",
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"noise = Noise.TwoQubitDephasing(probability=0.1)\n",
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},
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"cell_type": "code",
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"source": [
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"# define a noise channel\n",
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"noise = Noise.Depolarizing(probability=0.1)\n",
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{
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"cell_type": "code",
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"source": [
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"# define a two-qubit noise channel\n",
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"noise = Noise.TwoQubitDephasing(probability=0.1)\n",
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},
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{
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"cell_type": "code",
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"source": [
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"# define a noise channel\n",
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"noise = Noise.Depolarizing(probability=0.1)\n",
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"execution_count": 21,
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"source": [
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"# define a noise channel\n",
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"noise = Noise.PhaseFlip(probability=0.2)\n",
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"source": [
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"# define the noise channel\n",
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"noise = Noise.AmplitudeDamping(gamma=0.1)\n",
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"circ.density_matrix(target=[0,1])\n",
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"print(circ)\n",
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"\n",
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"# choose the noise simualtor, which is called \"braket_dm\"\n",
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"# choose the noise simulator, which is called \"braket_dm\"\n",
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"device = LocalSimulator(\"braket_dm\")\n",
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"# run the circuit\n",
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"task = device.run(circ, shots=0)\n",
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},
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{
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"cell_type": "code",
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"execution_count": 23,
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"source": [
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"# create a circuit\n",
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"circ = Circuit().x(0).y(1).cnot(0,2).x(1).z(2)\n",
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"\n",
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"T : | 0 | 1 | 2 | Result Types |\n",
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"- Probability is: \n",
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"[0.08 0.05 0. 0. 0.2 0.67 0. 0. ]\n",
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"[0.11 0.08 0. 0. 0.12 0.69 0. 0. ]\n",
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"- Expectation value <Z_0> is: \n",
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"-0.74\n"
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"-0.62\n"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3.7.6 64-bit ('base': conda)"
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"display_name": "Python 3.7.10 64-bit ('Braket': conda)"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.6"
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"version": "3.7.10"
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},
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"interpreter": {
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"hash": "0253d37730c9ef949b31486b4cff0d658c43b30ac02c14841de7d7631b67ad05"
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"hash": "16295940b2ad1780f80ab35486298f56b74905bdf7e3032c7f9c97990fe8396d"
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}
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},
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"nbformat": 4,

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