Zero Noise Extrapolation with FiQCI EMS#
What is Zero Noise Extrapolation?#
Zero Noise Extrapolation (ZNE) is an error mitigation technique that estimates the ideal (zero-noise) expectation value of a quantum circuit by intentionally amplifying the noise at several known levels and then extrapolating back to the zero-noise limit.
The core idea is:
Run the original circuit to obtain an expectation value at the base noise level.
Amplify the noise by creating scaled versions of the circuit (e.g., at scale factors 1, 3, 5).
Extrapolate the measured expectation values to the zero-noise point using a fitted model.
Because noise grows predictably with circuit depth, measuring at multiple noise levels reveals the trend, and extrapolation removes the noise contribution.
Circuit Folding Methods#
FiQCI EMS supports two methods for amplifying noise by increasing the effective circuit depth.
Local folding: Local folding replaces individual two-qubit gates \(G\) with \(G G G\) (for scale factor 3), \(G G G G G\) (for scale factor 5), and so on. Each gate is repeated
scale_factortimes in place.Only two-qubit gates are folded (single-qubit gate errors are typically negligible).
The
fold_gatesparameter can restrict folding to specific gate names. IfNone, all two-qubit gates are folded.
Global folding: Global folding appends the entire circuit and its inverse in alternating sequence. For a circuit \(C\) with scale factor 3, the result is \(C C^\dagger C\), and for scale factor 5: \(C C^\dagger C C^\dagger C\).
This uniformly amplifies noise across all gates.
The
fold_gatesparameter is not applicable and will be ignored if set.
Extrapolation Methods#
After running circuits at each scale factor, the expectation values are extrapolated to zero noise. FiQCI EMS provides four extrapolation methods:
Exponential: Fits an exponential decay model and works well when noise causes exponential decay of expectation values, which is common for depolarizing noise.
Richardson: Uses Lagrange interpolation to compute exact coefficients that combine the measured values into a zero-noise estimate. This is a model-free method that makes no assumptions about the noise shape.
Polynomial: Fits a polynomial of a given degree to the data. The degree defaults to
min(n_scales - 1, 2)and can be set with theextrapolation_degreeparameter.Linear: A special case of polynomial extrapolation with degree 1. Fits a straight line through the data points.
Usage#
Via Mitigation Level#
Setting mitigation_level=3 enables ZNE with default settings (local folding, scale factors [1, 3, 5], exponential extrapolation):
from fiqci.ems import FiQCIEstimator
estimator = FiQCIEstimator(backend=backend, mitigation_level=3)
Manual Configuration#
For fine-grained control, enable ZNE explicitly via the zne() method:
estimator = FiQCIEstimator(backend=backend, mitigation_level=1)
estimator.zne(
enabled=True,
scale_factors=[1, 3, 5],
folding_method="global",
extrapolation_method="richardson",
)
Parameters#
Parameter |
Type |
Default |
Description |
|---|---|---|---|
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— |
Enable or disable ZNE. |
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Gate names to fold (local folding only). |
|
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Positive odd integers specifying the noise scale levels. At least two are required. |
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Polynomial degree (only for |
Examples#
Zero Noise Extrapolation Example — runnable notebook demonstrating ZNE with default and custom settings.
References#
Temme, K., Bravyi, S., Gambetta, J. M., “Error Mitigation for Short-Depth Quantum Circuits”, https://arxiv.org/abs/1612.02058
Li, Y., Benjamin, S. C., “Efficient Variational Quantum Simulator Incorporating Active Error Minimization”, https://arxiv.org/abs/1611.09301
Pegah Mohammadipour, Xiantao Li., “Direct Analysis of Zero-Noise Extrapolation: Polynomial Methods, Error Bounds, and Simultaneous Physical-Algorithmic Error Mitigation” https://arxiv.org/abs/2502.20673