Normally forbidden emissions from graphene could expose quantum fluctuations in incoming light
Voltage fluctuations, light fluctuations, temperature fluctuations—any fluctuations are troublesome and thus undesirable. They don't just cause discomfort; in engineering and medical applications, they affect the accuracy of measurements or introduce errors in controls. Even at the minute level of quantum phenomena, fluctuations are considered undesirable.
Quantum fluctuations in light could be harnessed to detect and generate useful quantum optical signals, according to a theoretical study from the Indian Institute of Technology Bombay (IIT Bombay). The research suggests that graphene, a quantum material, could serve as an effective sensor to reveal information about the quantum nature of incoming light.
By carefully engineering the quantum fluctuations in the incident light, researchers were able to generate tailored high-frequency emissions in the extreme ultraviolet range. High-harmonic generation, an emerging technique, involves shining short, intense laser pulses on noble gases or specific solids to produce attosecond-duration pulses with frequencies that are integer multiples of the original laser frequency.
Quantum fluctuations, arising from Heisenberg's uncertainty principle, limit the precision of measurements at the quantum level. The IIT Bombay study discovered that when specially prepared quantum light with circularly polarized frequency components interacts with graphene, it generates high-frequency light and activates signals that would otherwise be forbidden.
The study reveals that the emitted light's polarization and forbidden frequency components carry distinct information about the quantum fluctuations in the incident light, providing a potential experimental method for detecting these fluctuations. The ultrafast nature of high-harmonic generation enables the exploration of quantum light-matter interactions on extremely short timescales.
While the study focuses on graphene, the researchers believe the underlying principles may be applicable to other quantum materials and nonlinear optical systems. Future work will involve exploring various quantum materials and generating datasets to train machine learning models for enhanced detection capabilities.
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