Multifrequency sources of quantum correlated photon pairs on-chip: a path toward integrated Quantum Frequency Combs

By L. Caspani, C. Reimer, M. Kues, P. Roztocki, M. Clerici, B. Wetzel, Y. Jestin, M. Ferrera, Marco Peccianti, Alessia Pasquazi and 5 more. 2016

144 citations recorded by the source corpus.

Abstract Recent developments in quantum photonics have initiated the process of bringing photonic-quantumbased systems out-of-the-lab and into real-world applications. As an example, devices to enable the exchange of a cryptographic key secured by the laws of quantum mechanics are already commercially available. In order to further boost this process, the next step is to transfer the results achieved by means of bulky and expensive setups into miniaturized and affordable devices. Integrated quantum photonics is exactly addressing this issue. In this paper, we briefly review the most recent advancements in the generation of quantum states of light on-chip. In particular, we focus on optical microcavities, as they can offer a solution to the problem of low efficiency that is characteristic of the materials typically used in integrated platforms. In addition, we show that specifically designed microcavities can also offer further advantages, such as compatibility with telecom standards (for exploiting existing fibre networks) and quantum memories (necessary to extend the communication distance), as well as giving a longitudinal multimode character for larger information transfer and processing. This last property (i.e., the increased dimensionality of the photon quantum state) is achieved through the ability to generate multiple photon pairs on a frequency comb, corresponding to the microcavity resonances. Further achievements include the possibility of fully exploiting the polarization degree of freedom, even for integrated devices. These results pave the way for the generation of integrated quantum frequency combs that, in turn, may find important applications toward the realization of a compact quantum-computing platform.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/7702e80e2cbb4ad69c86a8f6341c6a0bfc72cc60

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In Atomic and Molecular Physics, and Optics

  1. Xingyuan Xu
  2. Arnan Mitchell
  3. Mengxi Tan
  4. Jiayang Wu
  5. David J. Moss
  6. Roberto Morandotti
  7. Brent E. Little
  8. Sai T. Chu

In Electrical and Electronic Engineering

  1. Xingyuan Xu
  2. Arnan Mitchell
  3. Mengxi Tan
  4. Jiayang Wu
  5. David J. Moss
  6. Roberto Morandotti
  7. Brent E. Little
  8. Sai T. Chu

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