collaborators

8 papers

quant-ph2026

Classical simulation and model concentration in passive linear optics

Léo Monbroussou, Hugo Thomas, Hela Mhiri +2

Passive linear optics is a restricted model of quantum computation, with complexity-theoretic evidence of quantum advantage for sampling tasks and low losses that make it attractiv…

quant-ph2026

Private training in quantum machine learning

Tigran Sedrakyan, Frédéric Grosshans, Elham Kashefi

With the emergence of machine learning (ML) models trained on large datasets containing potentially sensitive data, a major question in AI safety is how to make learning private wi…

quant-ph2026

Authentication in Quantum Networks

Christopher Battarbee, Suchetana Goswami, Elham Kashefi +1

In this review, we survey the cryptographic task of authentication from the perspective of quantum communication. We review three main flavours of authentication that are often con…

quant-ph2026

Boson sampling beyond the dilute regime: second moments and anti-concentration

Hela Mhiri, Hugo Thomas, Léo Monbroussou +3

Boson sampling is a leading candidate for demonstrating quantum advantage in photonic systems. Despite significant experimental and theoretical progress, a characterization of its…

quant-ph2026

Hybrid Authentication Protocols for Advanced Quantum Networks

Suchetana Goswami, Mina Doosti, Elham Kashefi

Authentication is a fundamental building block of secure quantum networks, essential for quantum cryptographic protocols and often debated as a key limitation of quantum key distri…

quant-ph2026

Information-Theoretic Limits of Quantum Learning via Data Compression

Armando Angrisani, Brian Coyle, Elham Kashefi

Understanding the power of quantum data in machine learning is central to many proposed applications of quantum technologies. While access to quantum data can offer exponential adv…