If you build or use quantum technologies - from quantum computers to quantum sensors - quantum control engineering empowers you to extract maximum performance from your quantum hardware.
Control engineering makes airplanes fly, robots walk, and cars drive themselves.
The team at Q-CTRL are experts in bringing this power to the quantum domain to solve the toughest challenges in the field.
Q-CTRL has assembled the world’s largest and most capable team of expert quantum control engineers. Our expertise spans the dominant quantum computing hardware platforms as well as near-term applications in sensing and metrology. We are theorists and experimentalists, physicists, engineers, and quantum computer scientists working at the cutting edge of quantum technology.
Our team understands the challenges faced by hardware R&D teams, software architects, and end-users, and has a sustained publication track record demonstrating an ability to drive progress across the field of quantum technology. We solve tough challenges from experimental hardware optimization through to quantum computer architecture analyses, sensor data fusion to improved clock stabilization using machine learning.
Just imagine how much our team can help you achieve.
Our experience includes cutting-edge custom engineering projects in:
Developing customized quantum control solutions to suppress errors like cross-talk and leakage, maximize gate speed, and identify sources of decoherence for novel device designs using superconducting circuits, semiconducting devices, neutral atoms, and trapped ions.
Designing advanced quantum sensors for defense, mining and space. Includes novel hardware designs and operating principles for atomic-physics units deployed in gravimetry, magnetometry, and inertial navigation. Application of robust and spectrally narrow control concepts to the operation of quantum sensors for platform-noise rejection.
Driving research in academia and industry. Application of advanced techniques in machine learning to improve quantum experiment operation, readout, and hardware characterization. Developed novel custom software packages for data fusion in quantum characterization, complete with ML hyperparameter autotuning routines. Novel reinforcement-learning algorithms for automated quantum device tuneup and optimization.
Our team members have led the development and operation of superconducting quantum processors, as well as the application of optimal control to these devices. We’ve leveraged these experiences to deliver totally new control solutions for superconducting qubits to our customers and partners.
The Q-CTRL team has extensive experience in trapped-ion quantum logic and experimental hardware. Through our IARPA and ARO sponsored collaborations with the University of Sydney we have demonstrated how Q-CTRL solutions can help identify noise sources and dramatically improve the robustness and speed of Molmer-Sorensen entangling gates.
The Q-CTRL Quantum Engineering team has built extraordinary proficiency from working in some of the world’s most advanced atomic devices groups. We have a demonstrated track record of the integration of machine-learning and optimal control into neutral atom experiments to drive major performance enhancement in hardware, and deploying robust control to mitigate noise and decoherence.
The validation of quantum hardware performance is a critical task in the development and integration of quantum firmware. Our team has focused on moving beyond simplified abstractions to understanding the practical impact of realistic hardware noise environments on the interpretation of QCVV protocols. Our emphasis on gaining actionable information about microscopic noise sources has led to new interpretations of hardware characterization routines.
The interface of quantum control with other layers of the quantum computing stack presents some of the most profound opportunities to advance quantum computing in the NISQ era. Our team has led the exploration of control in the development of quantum computer architectures, from the physical to the logical layers.
We are pioneers in the application of quantum control to clocks and sensors for applications in aerospace and defense. Our experiences tackle some of the toughest problems in developing high-performance devices in tight-SWAP settings. We’ve delivered control solutions to suppress the Dick effect in atomic clocks, narrowband controls to suppress clutter in magnetometers, and novel pulse sequences enabling nanoscale MRI. Moreover, members of our team have led ground-breaking hardware developments in novel quantum-enhanced sensors, including advanced atomic interferometers for magnetometry, gravimetry, and PNT.
Various members of our team have made foundational contributions to quantum control engineering as a discipline. This spans open-quantum-system dynamics, open-loop control and dynamic error suppression, feedback control, and input-output theory. We also possess deep expertise in machine learning applied to control engineering with experience spanning robotics and quantum coherent devices. Current interests include reinforcement learning and automated optimization of quantum hardware.
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