A generalized echo squeezing protocol with near-Heisenberg limit sensitivity and strong robustness against excess noise and variation in squeezing parameter
Jinyang Li, Greg\'orio R. M. da Silva, Schuyler Kain, Selim M., Shahriar

TL;DR
This paper introduces a generalized echo squeezing protocol (GESP) that achieves near-Heisenberg limit sensitivity over a broad range of squeezing parameters, with enhanced robustness against excess noise and parameter variations, surpassing conventional protocols.
Contribution
The paper develops GESP, extending the Schrödinger cat state protocol to arbitrary squeezing parameters, and demonstrates its near-Heisenberg limit sensitivity and robustness over a wide parameter range.
Findings
GESP maintains near-Heisenberg limit sensitivity across a broad squeezing range.
GESP is robust against excess noise and parameter variations.
Sensitivity approaches the quantum Cramér-Rao bound over the entire squeezing interval.
Abstract
We present a generalized echo squeezing protocol (GESP) as a generalization of the Schr\"odinger cat state protocol (SCSP) with the value of the squeezing parameter being an arbitrary number rather than pi/2. We show analytically that over a broad range of the squeezing parameter the sensitivity reaches the Heisenberg limit (HL) within a factor of root-2. For a large number of particles, N, this plateau interval is almost the whole range from zero to pi/2, and the sensitivity is independent of the parity of N. Therefore, it is possible to operate a sensor over a wide interval of the squeezing parameter without changing the sensitivity. This is to be contrasted with the conventional echo squeezing protocol (CESP) which only works for a very small interval. In contrast to the CESP, the sensitivity of the GESP is close to the quantum Cram\'er-Rao bound over the whole range of the squeezing…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSparse and Compressive Sensing Techniques · Distributed Sensor Networks and Detection Algorithms · Target Tracking and Data Fusion in Sensor Networks
