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Quantum machine learning (QML) is a discipline that holds the promise of revolutionizing data processing and problem‐solving. However, dissipation and noise arising from the coupling with the environment are commonly perceived as major obstacles to its practical exploitation, as they impact the...
Nonlinear interferometry with entangled photons allows for characterizing a sample without detecting the photons interacting with it. This method enables highly sensitive optical sensing in the wavelength regions where efficient detectors are still under development. Recently, nonlinear...
In a world where Quantum Networks are rapidly becoming a reality, the development of the Quantum Internet is gaining increasing interest. Nevertheless, modern quantum networks are still in the early stages of development and have limited capacity to distribute resources among different users – a...
Quantum key distribution has emerged as a promising solution for constructing secure communication networks, with its information‐theoretic security rooted in quantum mechanics. One of the recent quantum key distribution protocols, the phase‐matching protocol, can have a quadratic key‐rate...
In classical machine learning (ML), “overfitting” is the phenomenon occurring when a given model learns the training data excessively well, and it thus performs poorly on unseen data. A commonly employed technique in ML is the so called “dropout,” which prevents computational units from becoming...
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