Polarization Entangled Lidar

The Polarization Entangled Lidar (PEL) is proposed to investigate new atmospheric science measurement capabilities enabled by polarization entangled photons. Today’s polarized lidars including Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and High Spectral Resolution Lidar (HSRL) depend on a few backscattered photons to measure the depolarization ratio allowing discrimination of cloud phase and the presence of non-spherical aerosols. With PEL nearly every transmitted photon can be sensed. In a PEL, nearly every photon transmitted in an outgoing lidar pulse has a polarization entangled photon traveling clockwise in a Polarization Maintaining Fiber (PMF) loop. Polarization changes in the transmitted pulses correspond to the local polarized entangled photons, which can be detected very rapidly after they occur whether or not the transmitted entangled photon is backscattered to the lidar receiver. A demonstration experiment is planned to establish the PEL concept. Design an experiment to demonstrate a Polarization Entangled Lidar (PEL). Create polarization entangled signal and idler photons through four-wave mixing. A dichroic mirror then splits the signal and idler photons onto to two paths. On one path the signal photons are transmitted into the atmosphere as outgoing lidar pulses. On the other path, the idler photons are coupled onto a PMF loop so that the polarized idler photons travel around the loop in a clockwise direction. As long as the initial polarized idler photons retain their polarization they pass through the loop in a clockwise direction. If their polarization changes they are reflected in a counter-clockwise direction and detected. Since the signal and idler photons are polarization entangled, changes in the polarization of the signal photons due to interactions with the atmosphere, dust particles, or ice crystals will change the polarization of the idler photons. The problem is to reduce uncertainty in cloud feedback and aerosol radiative forcing by a factor of 2 (Decadal Survey Report: https://www.nap.edu/catalog/24938, pp. 597-600). The problem is hard because lidar retrievals rely on a priori estimates of the aerosol type and properties and lidar retrievals near the surface, under conditions of low aerosol loadings, and in cloudy atmospheres lack the desired sensitivity.

The current state of practice, as evidenced in the CALIOP and HSRL lidars, uses the laser backscatter depolarization technique where the optical receiver uses a polarization beam splitter to create parallel and perpendicular polarization channels. The ratio of the returned signal powers of these two channels is the linear depolarization ratio allowing discrimination of cloud phase and the presence of non-spherical aerosols. These lidars measure the backscatter at two wavelengths to derive the aerosol and cloud profiles. The HSRL uses an iodine filter module to discriminate between aerosol and molecular backscatter coefficients. The maximum vertical resolution for is 30 m for CALIOP and 15 m for HSRL. The radiative forcing uncertainty by aerosols (about 1 W/m-2) is twice that of other factors of total forcing uncertainty (Decadal Survey Report: https://www.nap.edu/catalog/24938, p. 468). Current lidars only sense using backscattered photons. Using polarization entangled photons for atmospheric sensing is new and it could allow you to sense information from nearly every photon transmitted in a lidar pulse as the pulse travels through the atmosphere, in addition to just the few photons that are backscattered. We think we will be successful because highly efficient polarization entangled photon sources have been demonstrated (V.O. Lorenz et al., J. of Phys. 414, 2013) and polarization entanglement measurements have been made using polarizer reflected photons (A. Aspect et al., Opt. Comm. 34, 1980). If successful, it could provide a way to collect data between gated lidar return pulse samples and potentially provide additional information to reduce uncertainty in cloud feedback and aerosol radiative forcing.

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