Quantum Computing Application: Simplifying NMR Spectroscopy
A speedier solution for molecular biomedical research
+ [R]esearchers from the Medical School enlisted a pair of quantum physicists from the Faculty of Arts and Sciences to help. Now, the combination of medical researchers and quantum scientists have published the results of their collaboration — a new algorithm for decoding signals from NMR readings that draws from both quantum computing and classical machine learning — in a new study in Nature Machine Intelligence.
They figured that since the basics of NMR, short for nuclear magnetic resonance, is grounded in quantum mechanics, then perhaps a quantum computer could help push the technique beyond the current limits set by using ordinary computer processors to interpret the data.
+ The hybrid algorithm does, in theory, just what the researchers hoped. It would reduce a process that can take days for classical computers days into just minutes by using quantum systems that run on only 50 to 100 quantum bits, or “qubits,” the fundamental building blocks on which these computers operate. In other words, the algorithm works on both quantum computers that already exist and the so-called “near-term” quantum computers now being developed. These machines would act as a bridge between the intermediate period of current error- (or “noise-”) prone machines and the error-correcting, perfected versions envisioned to become reality decades from now.
+ The researchers believe the new hybrid algorithm can be one of the first applications for the not-so-distant intermediate computers, helping fill a growing need in practical applications of quantum technology as the hardware catches up with the theory. Quantum computers use the mysterious properties of matter at extremely small scales to greatly advance processing power and perform calculations that are virtually impossible for ordinary computers to solve.
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