Quantum data generation and simulation have several key applications:

• Chemical simulation: Extracting information about chemical structures and dynamics with potential applications to materials science, computational chemistry, computational biology, and drug discovery.
• Quantum matter simulation: Modeling and designing high-temperature superconductivity or other exotic states of matter which exhibit many-body quantum effects.
• Quantum control: Training hybrid quantum-classical models to perform optimal open- or closed-loop control, calibration, error mitigation, and error correction strategies for quantum devices.
• Quantum communication networks: Using machine learning to discriminate among non-orthogonal quantum states to design and construct structured quantum repeaters, receivers, and purification units.
• Quantum metrology: Improving high-precision measurements (such as quantum sensing and imaging) inherently done on small-scale quantum probes using variational quantum models.