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20212026
most citedSolving Rubik's Cube via Quantum Mechanics and Deep Reinforcement Learning

10 citations · 12 across the 7 of their papers we have counts for

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7 papers · 1 filter

quant-ph2025

Transpiling quantum circuits by a transformers-based algorithm

Michele Banfi, Paolo Zentilini, Sebastiano Corli +1

Transformers have gained popularity in machine learning due to their application in the field of natural language processing. They manipulate and process text efficiently, capturin…

quant-ph2025

Generation and detection of squeezed states via a synchronously pumped optical parametric oscillator

Edoardo Suerra, Samuele Altilia, Stefano Olivares +7

A synchronously pumped optical parametric oscillator (SPOPO) operating at 93 MHz is used to generate squeezed states at 1035 nm. The system features a counter-propagating beam at t…

quant-ph2025

A minimalist self-differencing gating scheme for dead-time-free single-photon avalanche diodes at high repetition rate

Samuele Altilia, Edoardo Suerra, Stefano Capra +6

Gated quenched SPAD detectors are widely used in quantum communication and quantum computing setups employing high-repetition-rate lasers. Here, we present a novel scheme for high-…

quant-ph20251 cited

Quantum physics informed neural networks for multi-variable partial differential equations

Giorgio Panichi, Sebastiano Corli, Enrico Prati

Quantum Physics-Informed Neural Networks (QPINNs) integrate quantum computing and machine learning to impose physical biases on the output of a quantum neural network, aiming to ei…

quant-ph20241 cited

Measurement-Based Quantum Compiling via Gauge Invariance

Sebastiano Corli, Enrico Prati

The measurement-based architecture is a paradigm of quantum computing, relying on the entanglement of a cluster of qubits and the measurements of a subset of it, conditioning the s…

quant-ph20243 cited

Quantum machine learning algorithms for anomaly detection: A review

Sebastiano Corli, Lorenzo Moro, Daniele Dragoni +2

The advent of quantum computers has justified the development of quantum machine learning algorithms , based on the adaptation of the principles of machine learning to the formalis…