Extracting Hidden Quantum Information From a Light Source
MrPlow writes:
Submitted via IRC for soylent_red
Researchers report on a technique to extract the quantum information hidden in an image that carries both classical and quantum information. This technique opens a new pathway for quantum enhance microscopes that aim to observe ultra-sensitive samples.
Current super-resolution microscopes or microarray laser scanning technology are known because of their high sensitivities and very good resolutions. However, they implement high light power to study samples, samples that can be light sensitive and thus become damaged or perturbed when illuminated by these devices.
Imaging techniques that employ quantum light are becoming of major importance nowadays, since their capabilities in terms of resolution and sensitivity can surpass classical limitations and, in addition, they do not damage the sample. This is possible because quantum light is emitted in single photons and that uses the property of entanglement to reach lower light intensity regimes.
Now, even though the use of quantum light and quantum detectors has been experimenting a steady development over these last years, there is still a few caveats that need to be solved. Quantum detectors are themselves sensitive to classical noise, noise which may end up being so significant that it can reduce or even cancel out any kind of quantum advantage over the images obtained.
Thus, launched a year ago, the European project Q-MIC has gathered an international team of researchers with different expertise who have come together to develop and implement quantum imaging technologies to create a quantum enhanced microscope that will be able to go beyond capabilities of current microscopy technologies.
In a study recently published in Sciences Advances, researchers Hugo Defienne and Daniele Faccio from the University of Glasgow and partners of the Q-MIC project, have reported on a new technique that uses image distillation to extract quantum information from an illuminated source that contains both quantum and classical information.
Source: https://www.sciencedaily.com/releases/2019/10/191024115010.htm
Journal Reference:
Hugo Defienne, Matthew Reichert, Jason W. Fleischer, Daniele Faccio. Quantum image distillation. Science Advances, 2019; 5 (10): eaax0307 DOI: 10.1126/sciadv.aax0307
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