Quantum optical systems are poised to become integral components of technologies of the future. While there is growing commercial interest in these systems---for applications in information processing, secure communication and precision metrology---there remain significant technical challenges to overcome before widespread adoption is possible. In this thesis we consider the general problem of optimising quantum optical systems, with a focus on sensing and information processing applications. We investigate four different classes of system with varying degrees of generality and complexity, and demonstrate four corresponding optimisation techniques. At the most specific end of the spectrum---where behaviour is best understood---we consider the problem of interferometric sensitivity enhancement, specifically in the context of long-baseline gravitational wave detectors. We investigate the use of an auxiliary optomechanical system to generate squeezed light exhibiting frequency-dependent quadrature rotation. Such rotation is necessary to evade the effect of quantum back action and achieve broadband sensitivity beyond the standard quantum limit. We find that a cavity optomechanical system is generally unsuitable for this purpose, since the quadrature rotation occurs in the opposite direction to that required for broadband sensitivity improvement. Next we introduce a general technique to engineer arbitrary optical spring potentials in cavity optomechanical systems. This technique has the potential to optimise many types of sensors relying on the optical spring effect. As an example, we show that this technique could yield an enhancement in sensitivity by a factor of 5 when applied to a certain gravitational sensor based on a levitated cavity mirror. We then consider a particular nanowire-based optomechanical system with potential applications in force sensing. We demonstrate a variety of ways to improve its sensitivity to transient forces. We first apply a non-stationary feedback cooling protocol to the system, and achieve an improvement in peak signal-to-noise ratio by a factor of 3, corresponding to a force resolution of 0.2fN. We then implement two non-stationary estimation schemes, which involve post-processing data taken in the absence of physical feedback cooling, to achieve a comparable enhancement in performance without the need for additional experimental complexity. Finally, to address the most complex of systems, we present a general-purpose machine learning algorithm capable of automatically modelling and optimising arbitrary physical systems without human input. To demonstrate the potential of the algorithm we apply it to a magneto-optical trap used for a quantum memory, and achieve an improvement in optical depth from 138 to 448. The four techniques presented differ significantly in their style and the types of systems to which they are applicable. Successfully harnessing the full range of such optimisation procedures will be vital in unlocking the potential of quantum optical systems in the technologies of the future
Quantum optical systems are poised to become integral components of technologies of the future. While there is growing commercial interest in these systems---for applications in information processing, secure communication and precision metrology---there remain significant technical challenges to overcome before widespread adoption is possible. In this thesis we consider the general problem of optimising quantum optical systems, with a focus on sensing and information processing applications. We investigate four different classes of system with varying degrees of generality and complexity, and demonstrate four corresponding optimisation techniques. At the most specific end of the spectrum---where behaviour is best understood---we consider the problem of interferometric sensitivity enhancement, specifically in the context of long-baseline gravitational wave detectors. We investigate the use of an auxiliary optomechanical system to generate squeezed light exhibiting frequency-dependent quadrature rotation. Such rotation is necessary to evade the effect of quantum back action and achieve broadband sensitivity beyond the standard quantum limit. We find that a cavity optomechanical system is generally unsuitable for this purpose, since the quadrature rotation occurs in the opposite direction to that required for broadband sensitivity improvement. Next we introduce a general technique to engineer arbitrary optical spring potentials in cavity optomechanical systems. This technique has the potential to optimise many types of sensors relying on the optical spring effect. As an example, we show that this technique could yield an enhancement in sensitivity by a factor of 5 when applied to a certain gravitational sensor based on a levitated cavity mirror. We then consider a particular nanowire-based optomechanical system with potential applications in force sensing. We demonstrate a variety of ways to improve its sensitivity to transient forces. We first apply a non-stationary feedback cooling protocol to the system, and achieve an improvement in peak signal-to-noise ratio by a factor of 3, corresponding to a force resolution of 0.2fN. We then implement two non-stationary estimation schemes, which involve post-processing data taken in the absence of physical feedback cooling, to achieve a comparable enhancement in performance without the need for additional experimental complexity. Finally, to address the most complex of systems, we present a general-purpose machine learning algorithm capable of automatically modelling and optimising arbitrary physical systems without human input. To demonstrate the potential of the algorithm we apply it to a magneto-optical trap used for a quantum memory, and achieve an improvement in optical depth from 138 to 448. The four techniques presented differ significantly in their style and the types of systems to which they are applicable. Successfully harnessing the full range of such optimisation procedures will be vital in unlocking the potential of quantum optical systems in the technologies of the future
Machine learning now plays a pivotal role in our society, providing solutions to problems that were previously thought intractable. The meteoric rise of this technology can no doubt be attributed to the information age that we now live in. As data is continually amassed, more efficient and scalable methods are required to yield functional models and accurate inferences. Simultaneously we have also seen quantum technology come to the forefront of research and next generation systems. These technologies promise secure information transfer, efficient computation and high precision sensing, at levels unattainable by their classical counterparts. Although these technologies are powerful, they are necessarily more complicated and difficult to control. The combination of these two advances yields an opportunity for study, namely leveraging the power of machine learning to control and optimise quantum (and more generally complex) systems. The work presented in thesis explores these avenues of investigation and demonstrates the potential success of machine learning methods in the domain of quantum and complex systems. One of the most crucial potential quantum technologies is the quantum memory. If we are to one day harness the true power of quantum key distribution for secure transimission of information, and more general quantum computating tasks, it will almost certainly involve the use of quantum memorys. We start by presenting the operation of the cold atom workhorse: the magneto-optical trap (MOT). To use a cold atomic ensemble as a quantum memory we are required to prepare the atoms using a specialised cooling sequence. During this we observe a stable, coherent optical emission exiting each end of the elongated ensemble. We characterise this behaviour and compare it to similar observations in previous work. Following this, we use the ensemble to implement a backward Raman memory. Using this scheme we are able to demonstrate an increased efficiency over that of previous forward recall implementations. While we are limited by the optical depth of the system, we observe an efficiency more than double that of previous implementations. The MOT provides an easily accessible test bed for the optimisation via some machine learning technique. As we require an efficient search method, we implement a new type of algorithm based on deep learning. We design this technique such that the artificial neural networks are placed in control of the online optimisation, rather than simply being used as surrogate models. We experimentally optimise the optical depth of the MOT using this method, by parametrising the time varying compression sequence. We identify a new and unintuitive method for cooling the atomic ensemble which surpasses current methods. Following this initial implementation we make substantial improvements to the deep learning approach. This extends the approach to be applicable to a far wider range of complex problems, which may contain extensive local minima and structure. We benchmark this algorithm against many of the conventional optimisation techniques and demonstrate superior capability to optimise problems with high dimensionality. Finally we apply this technique to a series of preliminary problems, namely the tuning of a single electron transistor and second-order correlations from a quantum dot source.
Optical and optomechanical systems are exploited for quantum technologies to perform highly precise measurements for fundamental physics as well as biological and engineering tasks. Theoretical studies using tools from statistics and quantum information can greatly aid studies of the sensing capabilities of quantum systems and experimental designs. These allow us to quantify the amount of information about a parameter encoded in a quantum state itself and examine how that can be extracted through measurements. In this thesis we show how mechanical squeezing and measurements beyond position can be utilised to improve the precision of wavepacket expansion measurements which can test collapse models of quantum mechanics. Particularly, that squeezing can compensate for the free-fall time which is often the most significant limiting factor in such experiments, and measurements of other quadratures can offer increased precision. We demonstrate that the use of additional optical fields to measure the displacement of a free mass in a radiation-pressure limited interferometer cannot surpass the ultimate precision of the single-mode interferometer. This work applies to the likes of laser-interferometric gravitational wave detectors. Finally, we venture into multi-parameter estimation: we calculate bounds for multi-mode Gaussian states used to estimate many phase shifts and optimise over the input states. In contrast to the—far less experimentally feasible—multi-mode generalisations of N00N states we see no significant improvement when using multi-mode Gaussian states for the task. Given their comparable performance in single-phase estimation this is a new limitation of Gaussian states appearing only at the multi-parameter level.
Advances in precision optomechanical measurement underpin a wide range of technologies, from inertial sensors to the detection of gravitational waves and the exploration of fundamental physics. For such applications, the ultimate sensitivity is limited by quantum noise: shot noise, which stems from the stochastic arrival of photons, dominates at high frequencies, while Quantum Back-Action (QBA) noise—arising from the random radiation-pressure force exerted by the light field—prevails at low frequencies. The interplay between these two contributions defines the Standard Quantum Limit (SQL) of interferometry, a power-dependent trade-off that constrains further performance improvements. Although several sub-SQL techniques have been demonstrated, they typically enhance narrow-band sensitivity or require long filter cavities. Coherent Quantum Noise Cancellation (CQNC), first proposed by Tsang and Caves, offers a broadband solution by introducing an Effective Negative-Mass Oscillator (ENMO) that destructively interferes with the QBA noise across the entire spectrum except at the mechanical resonance of the opto-mechanically coupled system. A mathematically equivalent scheme for broadband QBA evasion has been demonstrated—for example, using atomic ensembles. The operation of this scheme is restricted to specific atomic transition wavelengths and is therefore unsuitable for many optomechanical platforms. This thesis reports the first all-optical, table-top realisation of an ENMO capable of Coherent Quantum Noise Cancellation in quantum optomechanical sensors. The scheme employs an optical analogue of the optomechanical interaction, generated through a combination of parametric down-conversion and beam-splitting processes, yielding a tunable, wavelength-flexible, and compact system. The achieved parameters satisfy the CQNC targets established in earlier theoretical work, and the current system predicts a broadband quantum-noise reduction of 3.6 dB (77% suppression of QBA noise(in dB)) at the frequency of maximum suppression. With further reduction of intracavity losses, the projected cancellation improves to 11.9 dB (81% suppression (in dB)). The experimental realisation features two polarisation-coupled optical resonators that host a two-mode squeezing interaction; the optical resonators possess distinct detunings and linewidths. The interdependent nature of the ENMO system motivated the development of an in-situ characterisation method, which is essential for integrating the ENMO with an optomechanical system in practical applications. Adequately addressing the system’s complexity required the development of five specialised experimental techniques for parameter tuning and comprehensive characterisation. Beyond quantum-noise cancellation, this system lends itself to application in quantum-information and quantum-communication tasks, including an on-demand, high-purity single-photon source and a quantum memory. Owing to the optical platform’s immunity to thermal decoherence, it can be operated at room temperature, and the parametric down-conversion process affords flexibility in wavelength selection. The results presented here advance the state of the art in broadband quantum noise reduction in a broad class of optomechanical devices, with immediate relevance for emerging quantum-technology applications.
Quantum noise limits high-precision sensing, such as in gravitational wave detectors. Caves first proposed beating this shot-noise limit by injecting squeezed vacuum at the dark port of an interferometer. Frequency-dependent squeezing through a filter cavity now delivers broadband quantum noise reductions of up to 5.2 dB at Hanford and 6.1 dB at Livingston in the LIGO detectors' fourth observing run. Building on these advances, this thesis develops techniques for interferometric sensing under realistic loss and phase noise, spanning Gaussian state preparation, optomechanical readout and feedback control, and non-Gaussian state preparation. In Parts I and II, we work in the two-photon formalism, where states are Gaussian and dynamics are linear. In Part I, we present a waveguide squeezer as an alternative to the traditional bulk cavity-based source; it is single-pass, broadband, and compact, and its modularity opens a path to non-Gaussian state generation. We report the detection of squeezed light from waveguide sources at 1064 nm in the sub-MHz regime, and we phase-stabilize the squeezed vacuum with quantum noise locking. We also analyze the loss and phase-noise tolerance of Gaussian states. In Part II, we design a tabletop phase-sensitive optomechanical amplifier and analyze its performance in terms of cavity stability, control system, and noise budget. We then implement the locking scheme, including Pound-Drever-Hall locking of the cavity, and characterize the noise budget at the initial stage. We also propose using optomechanics for coherent feedback control, which could evade back-action and broaden the detection bandwidth of future gravitational wave detectors. In Part III, we turn to non-Gaussian states. Phase noise does not preserve Gaussianity, so the best input state under combined loss and phase noise need not be Gaussian. We numerically optimize the input state for displacement sensing over the (η,σϕ) landscape, integrating the Lindblad master equation in a truncated Fock basis and computing the quantum Fisher information. Within the Gaussian sub-family, the optimizer returns a displaced squeezed state once phase noise is appreciable, rather than pure squeezed vacuum. Without the Gaussian restriction, the optimized states sort roughly into four classes (Fock-like, cubic-phase-like, discrete-rotational, and squeezed), each dominant in a different region of the parameter space. In the experimentally relevant region of 1% loss and 100 mrad phase noise, cat states outperform squeezed vacuum even with balanced homodyne readout, an improvement implementable in the near term. We also show that the non-Gaussian advantage persists at higher photon budgets, well above Nˉ=5. Together, these results show how state preparation, readout, and feedback choices trade off against realistic loss and phase noise, and identify the regimes where non-Gaussian states perform better.
The work in this thesis is embedded in the framework of quantum metrology and explores quantum effects in solid state emitters and optical sensing. Specifically, the thesis comprises studies on silicon vacancy centres in nanodiamonds, phase measurements and cavity optomechanics utilising optical squeezed states, and a theoretical study on quantum amplifiers. Due to its similarity to single atoms, colour centres in diamond are ideal objects for exploring and exploiting quantum effects, because they are comparably easy to produce, probe and maintain. While nitrogen vacancy centres are the most renowned colour centres, we studied the silicon vacancy (SiV−) centre. In bulk diamond it features strong zero-phonon-line emission and, at cryogenic temperatures, a linewidth of hundreds of MHz, but it displays a weak spin coherence in the order of ns. To suppress the relaxation process which limits the coherence time, we utilised SiV− centres in nanodiamond. By means of confocal microscopy and resonant excitation at cryogenic temperatures, we measured linewidths in recently developed nanodiamond which were an order of magnitude smaller compared to previous studies on SiV− nanodiamonds. Furthermore, we identified spectral diffusion as the main hindrance in extending spin coherence times. Overcoming this issue will provide a promising candidate as an emitter for quantum information. Next, the question of how squeezed states of light can improve optical sensing was addressed. For this purpose, a squeezed light source was designed and built from scratch, which achieved a noise suppression of −8 dB at an optical pump power of 40mW. The generated squeezed light was first used to demonstrate how Gaussian states and detection can beat the shot noise limit and Rayleigh criterion in phase measurements simultaneously. Compared to quantum phase measurements based on single photon states, this approach is inherently deterministic. In addition, the applied homodyne detection enables close-to-unity detection efficiencies and thereby outperforms single photon state strategies which rely on comparably inefficient or demanding detection techniques. A second experiment combined squeezed light and feedback control to cool an optomechanical system. This proof-of-principle study is the first reported squeezing enhanced optomechanical cooling experiment. Despite losses of more than 50% (a resulting noise suppression of −2 dB), the mechanical resonator was cooled from room temperature to 130K. This represents a 12% improvement compared to the use of a coherent state protocol. Finally, we theoretically investigated the fundamental properties of quantum amplifiers. Such devices can be used in information and sensing technology to amplify signals to overcome e.g. technical detection limitations. Amplified communication channels were characterised by applying the measure of mutual information I, as it offers strict bounds on the maximum achievable performance, which enabled a fair comparison between different applications scenarios. As a result, we identified two peculiar configurations: A configuration where amplification does not affect I, and a configuration where quantum correlations do not always lead to an enhanced I.
Cavity optomechanical (COM) sensors, enhanced by quantum squeezing or entanglement, have become powerful tools for measuring ultra-weak forces with high precision and sensitivity. However, these sensors usually rely on linear COM couplings, a fundamental limitation when measurements of the mechanical energy are desired. Very recently, a giant enhancement of the signal-to-noise ratio was predicted in a quadratic COM system. Here we show that the performance of such a system can be further improved surpassing the standard quantum limit by using quantum squeezed light. Our approach is compatible with available engineering techniques of advanced COM sensors and provides new opportunities for using COM sensors in tests of fundamental laws of physics and quantum metrology applications.