Machine-Learning Based Quantum Noise Decoder

An apparatus comprising at least one non-transitory memory storing computer-executable instructions and a processing device, the computer-executable instructions, when executed by the processing device, configured to cause the apparatus to at least:

• train a quantum noise decoder comprising a machine-learning trained quantum error determination model using training data comprising operational data captured based at least in part on operation of a particular quantum processor;
• generate a noise model for the particular quantum processor based on the machine-learning trained quantum error determination model;
• and
• provide the noise model, wherein providing the noise model comprises at least one of (a) causing a graphical representation of at least a portion of the noise model to be provided via a display of a computing entity such that at least one component or parameter of the particular quantum processor is modified or changed based thereon or (b) providing at least a portion of the noise model as input associated with executable instructions for execution by a controller of the particular quantum processor or a computing entity in communication with the controller of the particular quantum processor such that at least one component or parameter of the particular quantum processor is modified or changed based thereon.