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As an important technology of the quantum detection, the quantum synchronization detection is always used in the detection or measurement of some quantum systems. A probing model is established to describe the probing of a qubit system in the cavity field and to reveal the effect of the environment (cavity) on the quantum synchronization occurrence, as well as the interactions among environment, a qubit system, and probing equipment. By adjusting the frequency of the probe, the in-phase, anti-phase, and out-of-phase synchronization can be achieved. Simultaneously, the effect ofγ  3${\gamma }_{3}$which describes the interaction strength between the probe and environments for quantum synchronization is discussed under different Ohmic dissipation index   s  . Finally, the machine learning method is applied to present an optimization for classification and regression of synchronization transition dependent on   s   andγ  3${\gamma }_{3}$.

Machine learning studies for the effects of probes and cavity on quantum synchronization