The efficient characterization of quantum systems, the verification of the operations of quantum devices and the validation of underpinning physical models are central challenges for quantum technologies and fundamental physics. The computational cost of such studies could be improved by machine learning enhanced by quantum simulators. Here researchers interface two different quantum systems through a classical channel—a silicon-photonics quantum simulator and an electron spin in a diamond nitrogen–vacancy centre—and use the former to learn the Hamiltonian of the latter via Bayesian inference. Researchers learn the salient Hamiltonian parameter with an uncertainty of approximately. Furthermore, an observed saturation in the learning algorithm suggests deficiencies in the underlying Hamiltonian model, which we exploit to further improve the model. They implement an interactive version of the protocol and experimentally show its ability to characterize the operation of the quantum photonic device.
Quantum photonic simulator and diamond nitrogen–vacancy centre
Nature Physics – Experimental quantum Hamiltonian learning
Wang is a prolific business-oriented writer of emerging and disruptive technologies. He is known for insightful articles that combine business and technical analysis that catches the attention of the general public and is also useful for those in the industries. He is the sole author and writer of nextbigfuture.com
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He gave the recent keynote presentation at Monte Jade event with a talk entitled the Future for You. He gave an annual update on molecular nanotechnology at Singularity University on nanotechnology, gave a TEDX talk on energy, and advises USC ASTE 527 (advanced space projects program). He has been interviewed for radio, professional organizations. podcasts and corporate events. He was recently interviewed by the radio program Steel on Steel on satellites and high altitude balloons that will track all movement in many parts of the USA.
He fundraises for various high impact technology companies and has worked in computer technology, insurance, healthcare and with corporate finance.
He has substantial familiarity with a broad range of breakthrough technologies like age reversal and antiaging, quantum computers, artificial intelligence, ocean tech, agtech, nuclear fission, advanced nuclear fission, space propulsion, satellites, imaging, molecular nanotechnology, biotechnology, medicine, blockchain, crypto and many other areas.