
Universal discriminative quantum neural networks
Quantum mechanics fundamentally forbids deterministic discrimination of ...
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Basic protocols in quantum reinforcement learning with superconducting circuits
Superconducting circuit technologies have recently achieved quantum prot...
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Optimized Quantum Circuit Partitioning
The main objective of this paper is to improve the communication costs i...
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Quantum Physical Unclonable Functions: Possibilities and Impossibilities
Physical Unclonable Functions (PUFs) are physical devices with unique be...
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An endtoend trainable hybrid classicalquantum classifier
We introduce a hybrid model combining a quantuminspired tensor network ...
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FDivergences and Cost Function Locality in Generative Modelling with Quantum Circuits
Generative modelling is an important unsupervised task in machine learni...
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Universal Effectiveness of HighDepth Circuits in Variational Eigenproblems
We explore the effectiveness of highdepth, noiseless, parameteric quant...
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Variational Quantum Cloning: Improving Practicality for Quantum Cryptanalysis
Cryptanalysis on standard quantum cryptographic systems generally involves finding optimal adversarial attack strategies on the underlying protocols. The core principle of modelling quantum attacks in many cases reduces to the adversary's ability to clone unknown quantum states which facilitates the extraction of some meaningful secret information. Explicit optimal attack strategies typically require high computational resources due to large circuit depths or, in many cases, are unknown. 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 classicalquantum techniques. The algorithm contains operationally meaningful cost functions with theoretical guarantees, quantum circuit structure learning and gradient descent based optimisation. Our approach enables the endtoend discovery of hardware efficient quantum circuits to clone specific families of quantum states, which in turn leads to an improvement in cloning fidelites when implemented on quantum hardware: the Rigetti Aspen chip. Finally, we connect these results to quantum cryptographic primitives, in particular quantum coin flipping. We derive attacks on two protocols as examples, based on quantum cloning and facilitated by VQC. As a result, our algorithm can improve near term attacks on these protocols, using approximate quantum cloning as a resource.
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