We enable the characterization and analysis of arbitrary fundamental quantum logic operations, complex modulation protocols, distorted control waveforms, and even quantum circuits using a framework based on engineering-inspired transfer functions. This provides an intuitive approach to perform error budgeting using realistic laboratory noise sources rather than theoretical idealizations.
Open-loop control techniques can be optimized to both user needs and system constraints for the mitigation of hardware error. We provide an efficient toolkit to enable teams to choose relevant control waveforms tailored to their needs through machine learning. In addition we specialize in high efficiency closed-loop stabilization routines that minimize the need for destructive qubit measurements
Error probabilities aren't enough in building real quantum hardware. Error budgets must be informed by information about the underlying noise spectra and correlations in various quadratures (e.g. amplitude noise in control systems vs. ambient dephasing). We provide a complete, deployable package permitting our customers to detect and reconstruct the characteristics of hardware noise from measurement through to data fusion.
Qubit-based sensors provide tremendous sensitivity but typically rely upon measurement protocols that suffer from non-idealities which can contaminate the sensor's output. We provide optimal control protocols and data fusion procedures which enable computationally efficient reconstruction of sensor features even in a cluttered environment. Our techniques are deployable for a wide variety of defense and industrial sensing and standoff detection applications including gravitational and magnetic anomaly detection.
Passive frequency standards are often limited by their local oscillators. In tight-SWAP applications where LO hardware performance is constrained, this can provide a major performance limitation. We provide advanced control algorithms enabling real performance enhancements in slaved frequency standards without a need to change the underlying hardware. We help extract maximum performance from a hardware platform by deploying quantum control and optimal estimation.