Error mitigation refers to techniques that reduce the effect of noise and imperfect measurements in quantum experiments. Quantum devices are prone to errors from interactions with their environment and limitations in control, so measured outputs may differ from the results an ideal computation would produce. Mitigation aims to make results more reliable without necessarily correcting every error at the hardware level.
Common approaches include repeating measurements, calibrating readout errors, and running related circuits at different noise levels to estimate what a less noisy result might be. In practice, researchers use these methods to assess whether a quantum computation supports a scientific conclusion or a claimed advantage over classical methods. Mitigation does not guarantee accuracy: its assumptions, extra computational cost, and uncertainty should be reported, and results should be validated against appropriate benchmarks.