Quantum key distribution (QKD) is a cornerstone of the secure quantum encryption. Building on the quantum irreversibility, we develop a technique reborning the existing QKDs into protocols that are unrestricted in distance and have unprecedented high rates enhanced up to the standard protocols communication speeds. The core of our method is the continuous end-to-end physical control of information leaks in the quantum channel. Contrary to the existing long-distance QKD offerings, our technique does not require any trust nodes.
We introduce a hybrid model combining a quantum-inspired tensor network and a variational quantum circuit to perform supervised learning tasks. This architecture allows for the classical and quantum parts of the model to be trained simultaneously, providing an end-to-end training framework. We show that compared to the principal component analysis, a tensor network based on the matrix product state with low bond dimensions performs better as a feature extractor for the input data of the variational quantum circuit in the binary and ternary classification of MNIST and Fashion-MNIST datasets. The architecture is highly adaptable and the classical-quantum boundary can be adjusted according the availability of the quantum resource by exploiting the correspondence between tensor networks and quantum circuits.
Toward quantum machine learning deployed on imperfect near-term intermediate-scale quantum (NISQ) processors, the entire physical implementation of should include as less as possible hand-designed modules with only a few ad-hoc parameters to be determined. This work presents such a hardware-friendly end-to-end quantum machine learning scheme that can be implemented with imperfect near-term intermediate-scale quantum (NISQ) processors. The proposal transforms the machine learning task to the optimization of controlled quantum dynamics, in which the learning model is parameterized by experimentally tunable control variables. Our design also enables automated feature selection by encoding the raw input to quantum states through agent control variables. Comparing with the gate-based parameterized quantum circuits, the proposed end-to-end quantum learning model is easy to implement as there are only few ad-hoc parameters to be determined. Numerical simulations on the benchmarking MNIST dataset demonstrate that the model can achieve high performance using only 3-5 qubits without downsizing the dataset, which shows great potential for accomplishing large-scale real-world learning tasks on NISQ processors.arning models. The scheme is promising for efficiently performing large-scale real-world learning tasks using intermediate-scale quantum processors.
In this paper we present the quantum control attack on quantum key distribution systems. The cornerstone of the attack is that Eve can use unitary (polar) decomposition of her positive-operator valued measure elements, which allows her to realize the feed-forward operation (quantum control), change the states in the channel after her measurement and impose them to Bob. Below we consider the general eavesdropping strategy and the conditions those should be satisfied to provide the attack successfully. Moreover we consider several types of the attack, each of them is based on a different type of discrimination. We also provide the example on two non-orthogonal states and discuss different strategies in this case.
In this work, we explore the feasibility of performing satellite-to-Earth quantum key distribution (QKD) using the orbital angular momentum (OAM) of light. Due to the fragility of OAM states the conventional wisdom is that turbulence would render OAM-QKD non-viable in a satellite-to-Earth channel. However, based on detailed phase screen simulations of the anticipated atmospheric turbulence we find that OAM-QKD is viable in some system configurations, especially if quantum channel information is utilized in the processing of post-selected states. More specifically, using classically entangled light as a probe of the quantum channel, and reasonably-sized transmitter-receiver apertures, we find that non-zero QKD rates are achievable on sea-level ground stations. Without using classical light probes, OAM-QKD is relegated to high-altitude ground stations with large receiver apertures. Our work represents the first quantitative assessment of the performance of OAM-QKD from satellites, showing under what circumstances the much-touted higher dimensionality of OAM can be utilized in the context of secure communications.
Quantum key distribution (QKD) involving polarized photons could be vulnerable to a jamming (or denial-of-service) attack, in which a third party applies an external magnetic field to rotate the plane of polarization of photons headed toward one of the two intended recipients. Sufficiently large Faraday rotation of one of the polarized beams would prevent Alice and Bob from establishing a secure quantum channel. We investigate requirements to induce such rotation both for free-space transmission and for transmission via optical fiber, and find reasonable ranges of parameters in which a jamming attack could be successful against fiber-based QKD, even for systems that implement automated recalibration for polarization-frame alignment. The jamming attack could be applied selectively and indefinitely by an adversary without revealing her presence, and could be further combined with various eavesdropping attacks to yield unauthorized information.
A. D. Kodukhov
,V. A. Pastushenko
,N. S. Kirsanov
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(2021)
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"Boosting quantum key distribution via the end-to-end physical control"
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Valeria Pastushenko
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