LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Entanglement-enhanced lidars for simultaneous range and velocity measurements

Photo from wikipedia

Lidar is a well known optical technology for measuring a target's range and radial velocity. We describe two lidar systems that use entanglement between transmitted signals and retained idlers to… Click to show full abstract

Lidar is a well known optical technology for measuring a target's range and radial velocity. We describe two lidar systems that use entanglement between transmitted signals and retained idlers to obtain significant quantum enhancements in simultaneous measurement of these parameters. The first entanglement-enhanced lidar circumvents the Arthurs-Kelly uncertainty relation for simultaneous measurement of range and radial velocity from detection of a single photon returned from the target. This performance presumes there is no extraneous (background) light, but is robust to the roundtrip loss incurred by the signal photons. The second entanglement-enhanced lidar---which requires a lossless, noiseless environment---realizes Heisenberg-limited accuracies for both its range and radial-velocity measurements, i.e., their root-mean-square estimation errors are both proportional to $1/M$ when $M$ signal photons are transmitted. These two lidars derive their entanglement-based enhancements from use of a unitary transformation that takes a signal-idler photon pair with frequencies $\omega_S$ and $\omega_I$ and converts it to a signal-idler photon pair whose frequencies are $(\omega_S + \omega_I)/2$ and $\omega_S-\omega_I$. Insight into how this transformation provides its benefits is provided through an analogy to superdense coding.

Keywords: entanglement enhanced; omega omega; velocity; velocity measurements; range radial

Journal Title: Physical Review Letters
Year Published: 2017

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.