A step toward practical photonic quantum neural networks, Featured News from SPIE!

Researchers from LIP6–Sorbonne Université, Quantum Lab–Sapienza University of Rome, Politecnico di Milano, and the Istituto di Fotonica e Nanotecnologie–Consiglio Nazionale delle Ricerche (IFN-CNR) have enabled the first demonstration of a photonic quantum convolutional neural network. Their study integrates an efficient photon-based neural network design with advanced hybrid photonic technologies. The work “Photonic quantum convolutional neural networks with … Leggi tutto

Photonic quantum convolutional neural networks with adaptive state injection

Recent photonic quantum machine learning proposals combined linear optics with adaptivity to enhance expressivity and improve algorithm performance and scalability. The particle-number-preserving property of linear optical platforms was recently employed to design a quantum convolutional neural network architecture with advantages in terms of resource complexity and the number of parameters needed. Here, we design and … Leggi tutto

Quantum memristor with vacuum–one-photon qubits

Quantum memristors offer a promising link between quantum and neuromorphic computing, merging the nonlinear, memory-dependent characteristics of classical memristors with the unique features of quantum states. An optical quantum memristor can be implemented using a vacuum–one-photon qubit that passes through a tunable beam splitter, where the reflectivity is adjusted according to the mean photon number … Leggi tutto

QuantumLab at the Italian Quantum Weeks

Quantum Lab is pleased to announce the 2025 edition of the Italian Quantum Weeks(https://quantumweeks.it) exhibition entitled “Quantum: a journey into quantum mechanics” to be held at the Museum of Classical Arts, Sapienza Università di Roma, from 12 to 16 May 2025. The event is organized in collaboration with the Department of Physics, the Museum of Physics, … Leggi tutto

Photonic Quantum Convolutional Neural Networks with Adaptive State Injection

Linear optical architectures have been extensively investigated for quantum computing and quantum machine learning applications. Recently, proposals for photonic quantum machine learning have combined linear optics with resource adaptivity, such as adaptive circuit reconfiguration, which promises to enhance expressivity and improve algorithm performances and scalability. Moreover, linear optical platforms preserve some subspaces due to the … Leggi tutto

The ERC Proof-of-Concept POQUB project just started!

he POQUB project, “PhOtonics QUantum Bernoulli Factory,” led by Fabio Sciarrino as Principal Investigator, started on 1 March 2025.POQUB is hosted by Quantum Lab, Department of Physics – Sapienza (https://www.quantumlab.it/), and will also involve the National Quantum Science and Technology Institute (NQSTI) (https://nqsti.it/) for the activities of technology transfer and for the interactions with the … Leggi tutto

“Quantum machine learning with Adaptive Boson Sampling via post-selection” published in Nature Communications

The implementation of large-scale universal quantum computation represents a challenging and ambitious task on the road to quantum processing of information. In recent years, an intermediate approach has been pursued to demonstrate quantum computational advantage via non-universal computational models. A relevant example for photonic platforms has been provided by the Boson Sampling paradigm and its … Leggi tutto