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Found 5 papers, 1 papers with code
Learning Quantum Processes with Quantum Statistical Queries
Learning complex quantum processes is a central challenge in many areas of quantum computing and quantum machine learning, with applications in quantum benchmarking, cryptanalysis, and variational quantum algorithms.
A unifying framework for differentially private quantum algorithms
In this paper, we propose a novel and general definition of neighbouring quantum states.
Unclonability and Quantum Cryptanalysis: From Foundations to Applications
The impossibility of creating perfect identical copies of unknown quantum systems is a fundamental concept in quantum theory and one of the main non-classical properties of quantum information.
Differential Privacy Amplification in Quantum and Quantum-inspired Algorithms
Differential privacy provides a theoretical framework for processing a dataset about $n$ users, in a way that the output reveals a minimal information about any single user.
Variational Quantum Cloning: Improving Practicality for Quantum Cryptanalysis
In this work, we propose variational quantum cloning (VQC), a quantum machine learning based cryptanalysis algorithm which allows an adversary to obtain optimal (approximate) cloning strategies with short depth quantum circuits, trained using hybrid classical-quantum techniques.
