Memristive devices are a class of physical systems with history-dependent dynamics characterized by signature hysteresis loops in their input–output relations. In the past few decades, memristive devices have attracted enormous interest in electronics. This is because memristive dynamics is very pervasive in nanoscale devices, and has potentially groundbreaking applications ranging from energy-efficient memories to physical neural networks and neuromorphic computing platforms. Recently, the concept of a quantum memristor was introduced by a few proposals, all of which face limited technological practicality. Here we propose and experimentally demonstrate a novel quantum-optical memristor (based on integrated photonics) that acts on single-photon states. We fully characterize the memristive dynamics of our device and tomographically reconstruct its quantum output state. Finally, we propose a possible application of our device in the framework of quantum machine learning through a scheme of quantum reservoir computing, which we apply to classical and quantum learning tasks. Our simulations show promising results, and may break new ground towards the use of quantum memristors in quantum neuromorphic architectures.

Femtosecond laser writing is a powerful technique that allows rapid and cost‐effective fabrication of photonic integrated circuits with unique 3D geometries. In particular, the possibility to reconfigure such devices by thermo‐optic phase shifters represents a paramount feature, exploited to produce adaptive and programmable circuits. However, the scalability is strongly limited by the flaws of current thermal phase shifters, which require hundreds of milliwatts to operate and exhibit large thermal crosstalk. In this work, thermally‐insulating 3D microstructures are exploited to decrease the power needed to induce a 2π phase shift down to 37 mW and to reduce the crosstalk to a few percent. Further improvement is demonstrated when operating in vacuum, with sub‐milliwatt power dissipation and negligible crosstalk. These results pave the way toward the demonstration of complex programmable integrated photonic circuits fabricated by femtosecond laser writing, thus opening exciting perspectives in integrated quantum photonics.

We report on a universal method to measure the genuine indistinguishability of $n$ photons—a crucial parameter that determines the accuracy of optical quantum computing. Our approach relies on a low-depth cyclic multiport interferometer with $N=2n$ modes, leading to a quantum interference fringe whose visibility is a direct measurement of the genuine $n$-photon indistinguishability. We experimentally demonstrate this technique for an eight-mode integrated interferometer fabricated using femtosecond laser micromachining and four photons from a quantum dot single-photon source. We measure a four-photon indistinguishability up to $0.81\pm 0.03$. This value decreases as we intentionally alter the photon pairwise indistinguishability. The low-depth and low-loss multiport interferometer design provides an original path to evaluate the genuine indistinguishability of resource states of increasing photon number.

Multiple parameter estimation is an essential task for both fundamental science and applications. For this reason, developing strategies and devices able to perform measurements with the smallest uncertainty has become a research branch of particular interest for various fields. It is known that the achievement of the ultimate precision bounds is possible only by exploiting quantum resources.¹ Indeed, nowadays, quantum sensors^2,3 represent one of the most promising applications of quantum-enhanced technologies, and they are already employed for different applications, from imaging⁴ and biological sensing⁵ to gravitational wave detection.^6,7 The highest measurement precision achievable depends on the available resources; therefore, the main focus of most quantum metrology investigations relies on the optimization of such probe states and, successively, of the performed measurements to attain such limits.^8,9 However, in a real scenario, the number of quantum resources is always limited and not all the desired probe states can be prepared. It follows that, in a limited-resource regime, operating the device at its optimal working point and employing optimized control strategies^{10 – 12} for achieving the highest estimation precision becomes crucial. The identification of such optimal feedbacks is far from being trivial in particular for quantum systems of increasing complexity and dimensions and for multiparameter estimation problems. Usually, the employed optimization algorithms are extremely time-consuming, since they have to be computed after each measurement outcome and, more importantly, they rely on the knowledge of the device’s physical model. One of the most employed methods, which assures the convergence to the ultimate precision bound, is to update the knowledge on the parameter posterior distribution through the Bayes rule after the use of each resource.^{13 – 17} Therefore, adaptive methods generally require a precise characterization of the operation of the employed system in order to update properly the knowledge on the investigated parameters at each step of the protocol. Such requirement is still the bottleneck for the application of optimal adaptive protocols in most quantum sensing applications. A practical model-free alternative to Bayesian update combined with a computationally feasible optimization algorithm for the identification of optimal feedback is thus desirable.

Mutually entangled multi-photon states are at the heart of all-optical quantum technologies. While impressive progresses have been reported in the generation of such quantum light states using free space apparatus, high-fidelity high-rate on-chip entanglement generation is crucial for future scalability. In this work, we use a bright quantum-dot based single-photon source to demonstrate the high fidelity generation of 4-photon Greenberg-Horne-Zeilinger (GHZ) states with a low-loss reconfigurable glass photonic circuit. We reconstruct the density matrix of the generated states using full quantum-state tomography reaching an experimental fidelity to the target state of $${{{{\mathcal{F}}}}}_{{{{{\rm{GHZ}}}}}_{4}}=(86.0\pm 0.4)\, \%$$ F GHZ 4 = ( 86.0 ± 0.4 ) % , and a purity of $${{{{\mathcal{P}}}}}_{{{{{\rm{GHZ}}}}}_{4}}=(76.3\pm 0.6)\, \%$$ P GHZ 4 = ( 76.3 ± 0.6 ) % . The entanglement of the generated states is certified with a semi device-independent approach through the violation of a Bell-like inequality by more than 39 standard deviations. Finally, we carry out a four-partite quantum secret sharing protocol on-chip where a regulator shares with three interlocutors a sifted key with up to 1978 bits, achieving a qubit-error rate of 10.87%. These results establish that the quantum-dot technology combined with glass photonic circuitry offers a viable path for entanglement generation and distribution.

Boson Sampling is a computational paradigm representing one of the most viable and pursued approaches to demonstrate the regime of quantum advantage. Recent results have shown significant technological leaps in single-photon generation and detection, leading to progressively larger instances of Boson Sampling experiments in different photonic systems. However, a crucial requirement for a fully-fledged platform solving this problem is the capability of implementing large-scale interferometers, that must simultaneously exhibit low losses, high degree of reconfigurability and the realization of arbitrary transformations. In this work, we move a step forward in this direction by demonstrating the adoption of a compact and reconfigurable 3D-integrated platform for photonic Boson Sampling. We perform 3- and 4-photon experiments by using such platform, showing the possibility of programming the circuit to implement a large number of unitary transformations. These results show that such compact and highly-reconfigurable layout can be scaled up to experiments with larger number of photons and modes, and can provide a viable direction for hybrid computing with photonic processors.