Machine learning drives the self-discovery of pulses that stabilize quantum systems in the face of environmental noise. Controlling the trajectory of a basketball is relatively straightforward, as it only requires the application of mechanical force and human skill. However, controlling the movemen
Quantum systems refer to the study of systems that operate on the principles of quantum mechanics. These systems include atoms, molecules, and subatomic particles, and are known for their unique properties such as superposition, entanglement, and quantum interference.
Controlling the trajectory of a basketball is relatively straightforward, as it only requires the application of mechanical force and human skill. However, controlling the movement of quantum systems like atoms and electrons poses a much greater challenge. These tiny particles are prone to perturbations that can cause them to deviate from their intended path in unexpected ways.
“Technologies built from quantum systems offer immense possibilities,” said Dr. Bijita Sarma, the article’s lead author and a Postdoctoral Scholar at OIST Quantum Machines Unit in the lab of Professor Jason Twamley. “But to benefit from their promise for ultraprecise sensor design, high-speed quantum information processing, and, we must learn to design ways to achieve fast cooling and control of these systems.
Quantum computing has the potential to revolutionize the world by enabling high computing speeds and reformatting cryptographic techniques. That is why many research institutes and big-tech companies such as Google and IBM are investing a lot of resources in developing such technologies. But to enable this, researchers must achieve complete control over the operation of such quantum systems at very high speed, so that the effects of noise and damping can be eliminated.
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