Scientists Exchanged Quantum Data In A Free-Space QKD

Scientists Exchanged Quantum Data In A Free-Space QKD

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The ETRI (Electronics and Telecommunications Research Institute) has stated a free-space successful QKD (quantum key distribution) in daylight with the self-designed polarization encoding processor for the first time. QKD is one of the most capable secure communication techs that encode data into a single-photon—the tinniest calculable unit of light. By employing the quantum mechanical characteristics of the single-photon, quantum cryptography promises safe data exchange among the remote parties.

The free-space QKD system by ETRI operates successfully even at the time of daylight whereas most other systems have been unsuccessful to work properly owing to considerable amount of sunlight’s noise photons. By adopting and developing elaborate noise filtering techs, the QKD system by ETRI attained the 142.94 kbps of secure key rate with 4.26 of quantum bit error rate. The QKD system by ETRI is developed with the self-designed polarization encoding processor, which dramatically lowers the size of the system in comparison to traditional QKD systems.

On a related note, some computational calculations are so intrinsically tricky that traditional computers, comprising huge supercomputers, can take years to get through them. One such calculation has been met by scientist at Case Western Reserve University (CWRU). These scientists have designed a method to enhance and accelerate the discovery of tumors on MRI scans. In addition to this, the method improves MRIs in many other approaches.

Their method, dubbed as magnetic resonance fingerprinting, which was posted in Nature a couple of years back, can considerably elevate the amount of helpful data that MRI scans offer. But, to take complete benefit of this tech, every scan has to be tuned to the separate patient and the target that is being hunted for.

This needs huge computing capability, but now Microsoft is joining hands with Case Western to apply its technology for quantum computing to convert this magnetic resonance fingerprinting clinically applicable. Although actual quantum devices will not be employed, algorithms based on them will have a lion’s share.