In addition to the errors already considered in the error-aware fidelity evaluation, several other sources of error could be integrated to enhance the noise resilience of the generated approximate quantum circuits. One significant source is decoherence, which arises from the interaction of qubits with their environment, leading to loss of quantum information. Incorporating models that simulate decoherence effects, such as T1 and T2 relaxation times, could provide a more accurate representation of circuit performance under realistic conditions.
Another important source of error is crosstalk, which occurs when operations on one qubit inadvertently affect neighboring qubits. This can be particularly problematic in densely connected qubit architectures. Developing methods to quantify and mitigate crosstalk during the optimization process could lead to more reliable circuit designs.
Readout errors are also critical to consider, as they can significantly impact the final measurement outcomes of quantum circuits. Implementing error correction techniques or post-processing methods that account for readout fidelity could improve the accuracy of the results.
Lastly, thermal noise and control errors (such as imprecise gate operations due to calibration issues) should be included in the error models. By simulating these additional error sources, the optimization techniques can be better tailored to produce circuits that are resilient to a wider range of noise characteristics, ultimately enhancing their performance on NISQ devices.