We develop a unified theoretical framework for the efficient description of multiphoton states generated and propagating in loop-based optical networks which contain nonlinear elements. These active optical components are modeled as nonlinear media, resembling a two-mode squeezer. First, such nonlinear components can be seeded to manipulate quantum states of light, as such enabling photon addition protocols. And, second, they can function as an amplifying medium for quantum light. To prove the practical importance of our approach, the impact of multiple round trips is analyzed for states propagating in experimentally relevant loop configurations of networks, such as time-multiplexed driven quantum walks and iterative photon-number state generation protocols. Our method not only enables us to model such complex systems but also allows us to propose alternative setups that overcome previous limitations. To characterize the systems under study, we provide exact expressions for fidelities with target states, success probabilities of heralding-type measurements, and correlations between optical modes, including many realistic imperfections. Moreover, we provide an easily implementable numerical approach by devising a vector-type representation of photonic states, measurement operators, and passive and active processes.
We develop a unified theoretical framework for the efficient description of multiphoton states generated and propagating in loop-based optical networks which contain nonlinear elements. These active optical components are modeled as nonlinear media, resembling a two-mode squeezer. First, such nonlinear components can be seeded to manipulate quantum states of light, as such enabling photon addition protocols. And, second, they can function as an amplifying medium for quantum light. To prove the practical importance of our approach, the impact of multiple round trips is analyzed for states propagating in experimentally relevant loop configurations of networks, such as time-multiplexed driven quantum walks and iterative photon-number state generation protocols. Our method not only enables us to model such complex systems but also allows us to propose alternative setups that overcome previous limitations. To characterize the systems under study, we provide exact expressions for fidelities with target states, success probabilities of heralding-type measurements, and correlations between optical modes, including many realistic imperfections. Moreover, we provide an easily implementable numerical approach by devising a vector-type representation of photonic states, measurement operators, and passive and active processes.
A scheme for the enhanced generation of higher photon-number states is realized, using an optical time-multiplexing setting that exploits a parametric down-conversion source for an iterative state generation. We use a quantum feedback mechanism for already generated photons to induce self-seeding of the consecutive nonlinear process, enabling us to coherently add photons to the light that propagates in the feedback loop. The addition can be carried out for any chosen number of round trips, resulting in a successive buildup of multiphoton states. Our system is only limited by loop losses. The looped design is rendered possible by a carefully engineered waveguide source that is compatible with and preserves the shape of the propagating mode. We compare the fidelities and success probabilities of our protocol with the common direct heralding of photon-number states. This comparison reveals that, for same the fidelity, our feedback-based setup significantly enhances success probabilities, being vital for an efficient utilization in quantum technologies. Moreover, quantum characteristics of the produced states are analyzed, and the flexibility of producing higher photon-number states with our setup beyond the common direct heralding is demonstrated.
Coherent manipulation of quantum states of light is key to photonic quantum information processing. In this Letter, we show that a passive two-level nonlinearity suffices to implement non-Gaussian quantum operations on propagating field modes. In particular, the collective light-matter interaction can efficiently extract a single photon from a multiphoton input wave packet to an orthogonal temporal mode. We accurately describe the single-photon subtraction process by elements of an intuitive quantum-trajectory model. By employing this process, quantum information protocols gain orders of magnitude improved efficiency over heralded schemes with linear optics. The reverse process can be used to add photons one by one to a single wave packet mode and compose arbitrarily large Fock states with a finite total success probability >96.7%.
Optical parametric processes underpin quantum photonics, while free-electron--photon interactions offer agile pathways to generate nontrivial quantum photonic states. These threads have so far largely progressed independently, whereas placing free electrons in a driven nonlinear system can potentially activate coherent parametric interaction channels for joint state engineering of both types of particles. Here we unify these paradigms by developing a general theoretical framework for parametric free-electron--photon interactions in a nonlinear optical system driven by degenerate parametric down-conversion. Unlike free electrons in a linear bath, here they can couple to Bogoliubov quasiparticles through two detuned phase-matching channels, where the parametric process and free-electron interactions can quantum amplify each other. Seeding the interaction with squeezed vacuum yields gain-only or loss-only electron energy spectra, and enables electron-heralded squeezed Fock states; with bare vacuum, postselecting electron energy sidebands generates high-fidelity Schrödinger cat states. Our results show how optical parametric interactions can quantum shape free electrons and photons, potentially enabling a quantum parametric dielectric laser accelerator that mitigates the need for temporal phase synchronization, thereby allowing acceleration probabilities to approach unity even for phase-random electrons.
Nonclassical states of light are an essential resource for many emerging quantum technologies and applications ranging from information processing, encrypted communications, and networking to sensing, metrology, and imaging. Nonlinear optical processes in solid-state materials are widely used for generating quantum light, including single photons, entangled-photon pairs, and quadrature-squeezed states. Recent advances in nonlinear photonics have enabled the functionality of benchtop nonlinear instruments to be scaled down to a single chip without sacrificing efficiency or degrading the key performance metrics. The dramatic improvement in the size, weight, power, cost, and stability enabled by photonic integrated circuits has been essential for enabling the chip-scale generation, manipulation, and detection of quantum light at a steadily increasing degree of complexity and scale. Within the last decade, the authors have seen the progression from few-component photonic circuits operating on two photons to arrays of 18 identical heralded single-photon sources and reconfigurable devices operating with more than 650 components for multidimensional entanglement and arbitrary two-photon quantum gates. In this review, the authors summarize the history and recent key technological developments of chip-scale nonlinear quantum light generation based on integrated nonlinear photonics, recent advances in heterogeneous integrated methods, and approaches for system-level integration and demonstrated applications.
[eng] Quantum photonic technologies have achieved considerable success across a range of disciplines, including quantum computing, quantum communications, and quantum metrology. Conversely, in the current era of information, the ability to discern patterns within voluminous data sets is highly sought after, with Machine Learning (ML) having emerged as a powerful solution to address this challenge. The processing speed of photonic hardware, in conjunction with the potential for computation enhancement resulting from quantum properties, positions quantum photonics as a promising platform for the implementation of ML algorithms. In this thesis, we focus on reservoir computing (RC) as an ML framework that is suitable for time series processing. It provides fast and energy-efficient training in comparison to more conventional methods and is also appropriate for physical implementations. In this thesis, we explore the possibilities brought by quantum photonic setups in the field of quantum RC. Specifically, we propose and study different platform designs that are able to perform different temporal benchmark tasks by providing tunable memory and nonlinearity. Furthermore, we leverage the capabilities of state-of-the-art quantum photonic hardware and identify novel strategies to address key challenges in RC in quantum substrates, as well as expand the potential of quantum machine learning. Firstly, an approach is provided to overcome some of the limitations of quantum projective measurements, thereby enabling information processing in real time. This is achieved by generating a physical ensemble of quantum reservoirs that recirculate through an optical fiber inside a feedback loop. We investigate the detrimental effects of sampling noise due to finite ensembles and provide a strategy to mitigate them. Secondly, the consequences of increasing quantum squeezing in the dynamics of such setups were studied, and it was found that it monotonically improves the noise robustness of the platforms in realistic scenarios. Finally, we propose a novel design in which photonic cluster states, a specific kind of highly entangled quantum network, are used as resources to implement quantum RC. In this configuration, external input information is encoded into the quantum network via quantum teleportation by engineering the measurement basis of the protocol. Furthermore, the platform has the capacity to implement global quantum gates through local operations (single-mode measurements), thus establishing the foundation for distributed quantum ML.
Quantum walks function as essential means to implement quantum simulators, allowing one to study complex and often directly inaccessible quantum processes in controllable systems. In this contribution, the notion of a driven Gaussian quantum walk is introduced. In contrast to typically considered quantum walks in optical settings, we describe the operation of the walk in terms of a nonlinear map rather than a unitary operation, e.g., by replacing a beam-splitter-type coin with a two-mode squeezer, being a process that is controlled and driven by a pump field. This opens previously unattainable possibilities for quantum walks that include nonlinear elements as core components of their operation, vastly extending their range of applications. A full framework for driven Gaussian quantum walks is developed, including methods to dynamically characterize nonlinear, quantum, and quantum-nonlinear effects. Moreover, driven Gaussian quantum walks are compared with their classically interfering and linear counterparts, which are based on classical coherence of light rather than quantum superpositions. In particular, the generation and boost of highly multimode entanglement, squeezing, and other quantum effects are studied over the duration of the nonlinear walk. Importantly, we prove the quantumness of the evolution itself, regardless of the input state. A scheme for an experimental realization is proposed. Furthermore, nonlinear properties of driven Gaussian quantum walks are explored, such as amplification that leads to an ever increasing number of correlated quantum particles, constituting a source of new walkers during the walk. Therefore, a concept for quantum walks is proposed that leads to---and even produces---directly accessible quantum phenomena, and that renders the quantum simulation of nonlinear processes possible.