EU: Exponentially Improved Quantum Memory (ExIQ)
We plan to demonstrate a new approach towards quantum memories based on a theoretical proposal which is centred around the phenomenon of selective radiance. Selective radiance occurs when the distance between emitters around a waveguide is smaller than the wavelength of the emitters. In this case destructive interference suppresses light scattering into all modes except the forward propagating target mode. This drastically reduces photon losses and increases the efficiency of the quantum memory operation. The error rate of such a new type of quantum memory scales with the optical depth (OD) as exp(-OD) in contrast to the previously established 1/OD. We plan to implement this new scheme with atomic emitters coupled to a nanofiber. Nanofiber based atom-light interfaces are versatile and scalable platforms which allow to precisely study these fundamental quantum effects and at the same time allow for easy integration into fibre based applications. The effect of selective radiance depends upon a lattice with a period smaller than the emitter wavelength. This will be achieved through an appropriate new choice of the laser wavelengths used in the optical trapping scheme. For best memory performance all lattice sites need to be filled. To realize this we use a collisional blockade effect in a Lambda enhanced grey molasses cooling which ejects one atom every time two or more atoms are present at a lattice site. To optimize the quantum memory performance we will perform an in-depth study of the phenomenon of selective radiance by analysing the transmission spectrum, the scattering into free space and by ring-down measurements. In the last step we will demonstrate the quantum memory performance and the exponential scaling with OD. The successful demonstration of this type of quantum memory is an important step towards large distance distribution of quantum information and paves the way for future quantum networks.
Financer
Duration of project
Start date: 06/2020
End date: 06/2022
Research Areas
Research Areas