Quantum Metrology with Bright Squeezed Light

Abstract

The noise of any measurement is fundamentally constrained by the laws of quantum mechanics, and this has significant implications for the development of sensors and measuring devices which are essential tools in science and engineering. In quantum metrology, the properties of quantum states of light are used to reduce measurement noise below the limit allowed by classical physics. In this thesis, we explore the application of squeezed states of light for improving precision and sensitivity in optical measurements.

Squeezed states are particularly versatile quantum states because they may be produced with high optical power, which makes them suitable for a range of optical applications. We begin by describing the development of a source of high power squeezed light, which utilised the Kerr effect in photonic crystal fibre. This approach allows us to generate quantum noise reduction at visible wavelengths.

We then investigate the precision improvement that may be attained by using squeezed light to reduce the noise of measurements in the frequency domain. We develop theory which shows that an improvement in the measured signal-to-noise ratio by applying squeezing does not necessarily correspond to a precision improvement, due to the effect of classical noise on the variance of the signal. Our theoretical model is used to identify the conditions required for squeezing to provide a precision improvement for the detection of amplitude modulation, and this is experimentally verified using our squeezed light source.

Finally, we develop a new method of optical loss estimation which provides enhanced precision by using squeezed light. This approach employs a novel technique for the cancellation of classical noise, which enables an experimental demonstration 8 orders of magnitude above the power limitations of previous demonstrations of quantum enhanced loss estimation. We anticipate that this approach will find application in imaging and spectroscopy.

Date of Award	2 Dec 2021
Original language	English
Awarding Institution	University of Bristol
Supervisor	Jonathan Matthews (Supervisor) & Dylan Mahler (Supervisor)