Integrated multimode quantum optics is a promising platform for scalable continuous-variable quantum technologies leveraging multimode squeezing in both the spatial and spectral domains. However, on-chip measurement, routing and processing the relevant “supermodes” over which the squeezing resource is distributed still scales quadratically with the number of modes N , causing a rapid increase in photonic circuit size and number of required measurements. Here, we introduce a variational scheme, relying on self-configuring photonic networks (SCNs) that learn and extract the most-squeezed supermodes sequentially, reducing both the circuit size and the experimental overhead. Using homodyne measurement as a cost function, a sparse SCN discovers the l ≪ N most significant supermodes using O ( l N ) physical elements and optimization steps. We analyze and numerically simulate these architectures for both real-space and frequency-domain implementations, showing a fidelity close to unity between the learned circuit and the supermode decomposition, even in the presence of optical losses and detection noise. In the frequency domain, we show that circuit size can be further reduced by using inverse-designed surrogate networks, which emulate the layers learned thus far. Using two different frequency encoding schemes—uniformly and nonuniformly spaced frequency bins—we reduce an entire network (learning all N supermodes) to O ( N ) and even O ( 1 ) modulated cavities. Our results point toward chip-scale, resource-efficient quantum processing units and demultiplexers for continuous variable processing in multimode quantum optics, with applications ranging from quantum communication, metrology, and computation.
Integrated multimode quantum optics is a promising platform for scalable continuous-variable quantum technologies leveraging multimode squeezing in both the spatial and spectral domains. However, on-chip measurement, routing and processing the relevant “supermodes” over which the squeezing resource is distributed still scales quadratically with the number of modes N , causing a rapid increase in photonic circuit size and number of required measurements. Here, we introduce a variational scheme, relying on self-configuring photonic networks (SCNs) that learn and extract the most-squeezed supermodes sequentially, reducing both the circuit size and the experimental overhead. Using homodyne measurement as a cost function, a sparse SCN discovers the l ≪ N most significant supermodes using O ( l N ) physical elements and optimization steps. We analyze and numerically simulate these architectures for both real-space and frequency-domain implementations, showing a fidelity close to unity between the learned circuit and the supermode decomposition, even in the presence of optical losses and detection noise. In the frequency domain, we show that circuit size can be further reduced by using inverse-designed surrogate networks, which emulate the layers learned thus far. Using two different frequency encoding schemes—uniformly and nonuniformly spaced frequency bins—we reduce an entire network (learning all N supermodes) to O ( N ) and even O ( 1 ) modulated cavities. Our results point toward chip-scale, resource-efficient quantum processing units and demultiplexers for continuous variable processing in multimode quantum optics, with applications ranging from quantum communication, metrology, and computation.
Continuous-variable quantum networks constitute a valuable resource for a wide range of quantum communication and information protocols. While frequency- and fast time-multiplexing enable the implementation of scalable quantum architectures, a precise characterization of multimode squeezed-light sources is essential. In this work, we increase both the spectral resolution and the measured squeezing values. Both parameters are relevant for the improved generation of so-called cluster states, a key resource for measurement-based quantum computing. Our source is based on parametric down-conversion in a periodically poled KTP waveguide pumped by a pulsed laser. The source produces squeezed states over a specific set of optical spectra. Increased spectral resolution in spectrally resolved homodyne detection allowed us to enhance the squeezing per spectral mode, increasing it from 1 dB to more than 2.4 dB in the first mode when measuring with a homodyne detector with a bandwidth of a few MHz. Secondly, we implemented a pulse-by-pulse characterization of the resource using a fast homodyne detector with an electronic bandwidth on the order of the laser repetition rate (100 MHz). Using this approach, the fast measurements revealed squeezing values of up to 1.5 dB in the first few spectral modes. To fully access the multimode quantum resource and ultimately improve the amount of squeezing, a high quantum efficiency is required. To avoid limitations imposed by poor spatial mode matching between the quantum resource and the local oscillator in homodyne detection, we implemented a wavefront-shaping scheme to characterize and control both the intensity profile and phase of the local oscillator. In preliminary tests this approach increased the mode-matching between the reference beam and the quantum signal by more than 8% while simultaneously providing a detailed characterization of the beam shape and of the influence of waveguide transmission on the beam profile. To achieve a genuine advantage in quantum information processing over classical protocols, the generation of non-Gaussian states is necessary. We therefore present a complete scheme for the creation of non-Gaussian states in a multimode system via mode-selective single-photon addition and subtraction, implemented through nonlinear optical processes in second-order nonlinear materials. We introduce a simulation framework applied to our squeezing source, which can be adapted to other regimes as well. Based on this framework, we are able to predict specific waveguide configurations that enable full control over the generated quantum states while maintaining high purity, with each process exhibiting a Schmidt number close to K=1, corresponding to effective single-mode addressing. generated quantum states while maintaining high purity, with each process exhibiting a Schmidt number close to K=1, corresponding to effective single-mode addressing.
Multimode squeezed light is a key resource for high-dimensional quantum technologies, enhancing metrological sensitivity, boosting communication security, and enabling parallel processing in computation. Its practical potential, however, remains constrained by the inherent single-mode operation of homodyne detection, necessitating post-processing for multimode characterization. Here, we overcome this long-standing challenge by employing multimode optical parametric amplification, enabling loss-tolerant direct detection of squeezing in each mode, which in turn permits mode sorting after amplification. As a result, we demonstrate, for the first time to the best of our knowledge, the real-time monitoring of multimode squeezing. With a spatial light modulator sorting the modes, we simultaneously measure squeezing in nine spatial modes co-propagating within one beam. Although mode sorting and filtering reduce the detection efficiency to less than 0.3%, we observe high-purity squeezing of up to - 7.9 ± 0.6 dB - to the best of our knowledge, the highest squeezing recorded for pulsed light. Furthermore, we demonstrate real-time, loss-tolerant characterization of continuous-variable entanglement and extend it to the detection of cluster states. Similar methods can be applied in the frequency domain, facilitating a crucial capability for scalable quantum technologies.
Scalable interferometers lie at the heart of photonic quantum technologies, but their expansion has been fundamentally limited by optical losses that grow with circuit depth. Here, we introduce and experimentally demonstrate a measurement-induced architecture for multimode squeezed-light interferometers that overcomes this barrier. By shifting complexity from deep optical networks to programmable homodyne measurements, we realize effective transformations within a shallow, low-loss platform. We validate the principle with a six-mode device and extend it to a 400-mode interferometer, marking a leap in scale beyond conventional designs. Crucially, this strategy not only enables scalable squeezed light interferometry but also provides a powerful route to the generation of large-scale entangled states-a key requirement for quantum computing, simulation, and communication. Our results establish measurement-induced circuits as a practical pathway toward noisy intermediate-scale quantum (NISQ) applications and future demonstrations of quantum advantage.
Continuous-variable (CV) multipartite entangled states, particularly Greenberger–Horne–Zeilinger (GHZ) states, are an indispensable resource for quantum networks and quantum information processing. Conventional approaches to generating CV GHZ states rely on combining multiple independently prepared squeezed lights through complex interferometric networks, which impose significant challenges in scalability and stability. Here, we experimentally demonstrate a compact and resource-efficient scheme for generating a tripartite CV GHZ state from a single quantum frequency comb produced by a synchronously pumped optical parametric oscillator. By employing multipixel homodyne detection, we simultaneously measure quadrature fluctuations across multiple frequency bands and reconstruct the full multimode covariance matrix in a single measurement. Through eigenmode decomposition, we extract a set of independent squeezed supermodes, which are subsequently transformed via a tailored linear unitary operation implemented in post-processing. Using this approach, we deterministically construct a tripartite GHZ state from three supermodes and verify its entanglement via the van Loock–Furusawa criteria, with the corresponding correlation variances measured to be 0.57, 0.75, and 0.57, all below the shot noise limit. This method effectively realizes a scalable entanglement generation scheme within a single optical beam, eliminating the need for complex interferometric networks. Our results provide a scalable and versatile platform for multimode quantum information processing.
Squeezed light underpins quantum-enhanced sensing and continuous-variable quantum information processing, and integrated photonics offers a route to producing it at scale. Universal to these applications are squeezed-light generation and measurement. Importantly, quantum measurements serve not only as readout but also as active operations in quantum-state evolution. However, integrating squeezed-light generation and photodetection on the same photonic chip has remained challenging because they impose fundamentally conflicting material requirements: low optical loss to preserve quantum correlations, but efficient photon absorption for photodetection. Here, we demonstrate squeezed-light generation, routing, and balanced homodyne detection integrated on a single photonic chip through heterogeneous integration. A two-mode squeezed quantum microcomb comprising 34 quantum modes is measured with approximately 3 dB squeezing. Our work establishes a scalable architecture for fully integrated squeezed-light quantum photonic systems, unifying quantum-state generation, processing, and detection on a single chip.
We introduce a new class of self-configuring photonic architectures called variational optical processors (VOPs). These devices tackle the problem of decomposing and measuring multimode light fields, both partially coherent and quantum, without requiring prior knowledge of the modes involved. Classical strategies for modal decomposition—such as Karhunen-Loève expansions [1] for partially coherent beams or Schmidt decompositions [2] for bipartite quantum states—often rely on comprehensive tomography and complex data processing. By contrast, VOPs discover the relevant modes in situ through a simple optimization of detection signals at their outputs (e.g., measured optical power or coincidence counts), eliminating the overhead usually associated with scanning and reconstruction. Prior demonstrations of self-configuring photonic networks have proven the feasibility of such approaches for analyzing and generating multimode coherent optical fields [3].