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4 changes: 2 additions & 2 deletions docs/_book.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -178,10 +178,10 @@ upper_tabs:
path: /cirq/noise/calibration_faq
- title: "Floquet Calibration"
path: /cirq/noise/floquet_calibration_example
- title: "Cross Entropy Benchmarking (XEB)"
- title: "Cross-Entropy Benchmarking (XEB)"
style: accordion
section:
- title: "Cross Entropy Benchmarking Theory"
- title: "Cross-Entropy Benchmarking Theory"
path: /cirq/noise/qcvv/xeb_theory
- title: "Coherent vs incoherent noise with XEB"
path: /cirq/noise/qcvv/coherent_vs_incoherent_xeb
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2 changes: 1 addition & 1 deletion docs/noise/_index.yaml
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Expand Up @@ -20,7 +20,7 @@ landing_page:
options:
- cards
items:
- heading: Cross Entropy Benchmarking (XEB)
- heading: Cross-Entropy Benchmarking (XEB)
description: A characterization benchmarking method using cross entropy.
path: /cirq/noise/qcvv/xeb_theory
- heading: Visualizing noise
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4 changes: 2 additions & 2 deletions docs/noise/qcvv/coherent_vs_incoherent_xeb.ipynb
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Expand Up @@ -68,7 +68,7 @@
"id": "dd95be2a71eb"
},
"source": [
"This notebook demonstrates how to use Cross Entropy Benchmarking (XEB) end-to-end to compare coherent gate parameter error and incoherent depolarization error. It will mimic a small device graph of `cirq.GridQubit` pairs and simulate two-qubit XEB benchmarking circuits on them with noise models that introduce coherent and incoherent error before visualizing and comparing the results.\n",
"This notebook demonstrates how to use Cross-Entropy Benchmarking (XEB) end-to-end to compare coherent gate parameter error and incoherent depolarization error. It will mimic a small device graph of `cirq.GridQubit` pairs and simulate two-qubit XEB benchmarking circuits on them with noise models that introduce coherent and incoherent error before visualizing and comparing the results.\n",
"\n",
"For more information on types of error, see [Average, Pauli and Incoherent Error](../../google/calibration.md#average-pauli-and-incoherent_error). \n",
"\n",
Expand Down Expand Up @@ -877,7 +877,7 @@
"source": [
"## Conclusion\n",
"\n",
"Cross Entropy Benchmarking and optimizer refitting has been shown here to effectively characterize patterns of coherent error, to find the (parameters of the) true unitary operation used on individual qubit pairs. Importantly, this is effective even in the case where incoherent error is also acting on the system, but with noticeably reduced accuracy. In a real hardware system, with many interacting sources of error, XEB can still be useful to identify consistent coherent error, but it's important to remember that other error can confound these results. "
"Cross-Entropy Benchmarking and optimizer refitting has been shown here to effectively characterize patterns of coherent error, to find the (parameters of the) true unitary operation used on individual qubit pairs. Importantly, this is effective even in the case where incoherent error is also acting on the system, but with noticeably reduced accuracy. In a real hardware system, with many interacting sources of error, XEB can still be useful to identify consistent coherent error, but it's important to remember that other error can confound these results. "
]
},
{
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6 changes: 3 additions & 3 deletions docs/noise/qcvv/xeb_theory.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -68,9 +68,9 @@
"id": "07034e5e3982"
},
"source": [
"# Cross Entropy Benchmarking Theory\n",
"# Cross-Entropy Benchmarking Theory\n",
"\n",
"Cross entropy benchmarking uses the properties of random quantum programs to determine the fidelity of a wide variety of circuits. When applied to circuits with many qubits, XEB can characterize the performance of a large device. When applied to deep, two-qubit circuits it can be used to accurately characterize a two-qubit interaction potentially leading to better calibration."
"Cross-Entropy Benchmarking (XEB) uses the properties of random quantum programs to determine the fidelity of a wide variety of circuits. When applied to circuits with many qubits, XEB can characterize the performance of a large device. When applied to deep, two-qubit circuits it can be used to accurately characterize a two-qubit interaction potentially leading to better calibration."
]
},
{
Expand Down Expand Up @@ -252,7 +252,7 @@
},
"source": [
"### Execute circuits\n",
"Cross entropy benchmarking requires sampled bitstrings from the device being benchmarked *as well as* the true probabilities from a noiseless simulation. We find these quantities for all `(cycle_depth, circuit)` permutations."
"Cross-Entropy Benchmarking (XEB) requires sampled bitstrings from the device being benchmarked *as well as* the true probabilities from a noiseless simulation. We find these quantities for all `(cycle_depth, circuit)` permutations."
]
},
{
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2 changes: 1 addition & 1 deletion docs/tutorials/google/identifying_hardware_changes.ipynb
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Expand Up @@ -105,7 +105,7 @@
"\n",
"There are many [Calibration Metrics](../../google/calibration.md#individual-metrics) available to measure gate and readout error rates and see if they have changed. The [Visualizing Calibration Metrics](./visualizing_calibration_metrics.ipynb) tutorial demonstrates how to collect and visualize each of these available metrics. You can apply the comparison methods presented in this tutorial to any such metric, but the examples below focus on the two following metrics:\n",
"\n",
"* [`two_qubit_parallel_sqrt_iswap_gate_xeb_pauli_error_per_cycle`](../../google/calibration.md): This metric captures the estimated probability for the quantum state on two neighboring qubits to depolarize (as if a Pauli gate was applied to either or both qubits) after applying an $\\sqrt{i\\mathrm{SWAP}}$ gate. This metric includes some coherent error like the error introduced by control hardware. This metric is computed using [Cross Entropy Benchmarking (XEB)](../../noise/qcvv/xeb_theory.ipynb) during maintenance calibration and in this tutorial.\n",
"* [`two_qubit_parallel_sqrt_iswap_gate_xeb_pauli_error_per_cycle`](../../google/calibration.md): This metric captures the estimated probability for the quantum state on two neighboring qubits to depolarize (as if a Pauli gate was applied to either or both qubits) after applying an $\\sqrt{i\\mathrm{SWAP}}$ gate. This metric includes some coherent error like the error introduced by control hardware. This metric is computed using [Cross-Entropy Benchmarking (XEB)](../../noise/qcvv/xeb_theory.ipynb) during maintenance calibration and in this tutorial.\n",
"* [`parallel_p11_error`](../../google/calibration.md): This metric estimates the probability for a readout register to correctly measure a $|1\\rangle$ state on a qubit that was prepared to be in the $|1\\rangle$ state. The Simultaneous Readout experiment used to collect this metric evaluates all of the qubits in parallel/simultaneously.\n",
"\n",
"Note: The two-qubit metric uses Pauli error, which has two other multiplicatively-related variants: [Average error and Incoherent error](../../google/calibration.md#average-pauli-and-incoherent-error).\n"
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