In the realm of quantum technologies and energy-efficient communications, a team of researchers from the University of Basel, Ruhr University Bochum, and the University of Sheffield has made significant strides. The team, led by Timon L. Baltisberger and Richard J. Warburton, has demonstrated a method to improve the coherence of photon pairs generated from semiconductor quantum dots, a finding that could have practical applications in the energy sector, particularly in quantum communication and computing.
The researchers focused on a phenomenon known as a two-photon cascade, where a quantum dot emits two photons in quick succession. Previous studies have shown that these photon pairs can be entangled, a property crucial for quantum technologies. However, the photons generated in this process often lack coherence, which is essential for many applications. The team addressed this issue by using a technique called Purcell enhancement, which increases the rate of photon emission, and by operating in a low-noise environment.
By implementing these improvements, the researchers achieved high interference visibility for both photons in the cascade. Interference visibility is a measure of photon coherence, with higher values indicating better coherence. The team reported visibilities of 94% for the first photon (XX) and 82% for the second photon (X), which are among the highest reported for this type of system. The researchers also demonstrated that the coherence of the photon pairs followed theoretical predictions, providing a solid foundation for future work.
This research, published in the journal Nature Communications, highlights the potential of semiconductor quantum dots as a source of coherent photon pairs. In the energy sector, coherent photon pairs could be used to develop more secure and efficient quantum communication networks, which could revolutionize the way energy data is transmitted and managed. Additionally, the ability to generate coherent photons on-demand could have applications in quantum computing, which could lead to more energy-efficient algorithms for solving complex problems in the energy industry.
This article is based on research available at arXiv.