Condensed Matter Seminar
Quantum Matched Filtering – Global vs. Local Detection of Entanglement with SU(1,1) interference
Prof. Avi Peer
BIU
Abstract
Active SU(1,1) interferometers exploit parametric amplification rather than linear beam splitting, enabling phase‑sensitive gain and multi‑mode quantum correlations that are inaccessible to standard passive interferometers. These properties make them natural candidates for quantum‑enhanced sensing. I will present our recent advances in using SU(1,1) interferometry to implement optimal quantum receivers and to surpass classical time–energy and sensitivity limits.
The major part of the talk will focus on Quantum Matched Filtering [arXiv:2503.03583]. We show that an SU(1,1) interferometer, operated with appropriately engineered gain and pump phase, implements the optimal quantum measurement for detecting a known weak waveform embedded in broadband noise. Unlike classical matched filtering, which relies on classical correlation and is limited by the separability criterion, a quantum matched filter relies on inseparable entanglement. We demonstrate a quantum matched filter that breaks the classical separability limit by more than twelve orders of magnitude. I will then connect these ideas to our broader program in quantum sensing and nonlinear‑interferometric parameter estimation
The major part of the talk will focus on Quantum Matched Filtering [arXiv:2503.03583]. We show that an SU(1,1) interferometer, operated with appropriately engineered gain and pump phase, implements the optimal quantum measurement for detecting a known weak waveform embedded in broadband noise. Unlike classical matched filtering, which relies on classical correlation and is limited by the separability criterion, a quantum matched filter relies on inseparable entanglement. We demonstrate a quantum matched filter that breaks the classical separability limit by more than twelve orders of magnitude. I will then connect these ideas to our broader program in quantum sensing and nonlinear‑interferometric parameter estimation