Aleksey K. Fedorov

Denis Bokhan, Alena S. Mastiukova, Aleksey S. Boev et al.

Multiclass classification is of great interest for various applications, for example, it is a common task in computer vision, where one needs to categorize an image into three or more classes. Here we propose a quantum machine learning approach based on quantum convolutional neural networks for solving the multiclass classification problem. The corresponding learning procedure is implemented via TensorFlowQuantum as a hybrid quantum-classical (variational) model, where quantum output results are fed to the softmax activation function with the subsequent minimization of the cross entropy loss via optimizing the parameters of the quantum circuit. Our conceptional improvements here include a new model for a quantum perceptron and an optimized structure of the quantum circuit. We use the proposed approach to solve a 4-class classification problem for the case of the MNIST dataset using eight qubits for data encoding and four ancilla qubits; previous results have been obtained for 3-class classification problems. Our results show that accuracies of our solution are similar to classical convolutional neural networks with comparable numbers of trainable parameters. We expect that our finding provide a new step towards the use of quantum neural networks for solving relevant problems in the NISQ era and beyond.

M. A. Gavreev, A. S. Mastiukova, E. O. Kiktenko et al.

Quantum technologies require methods for preparing and manipulating entangled multiparticle states. However, the problem of determining whether a given quantum state is entangled or separable is known to be an NP-hard problem in general, and even the task of detecting entanglement breakdown for a given class of quantum states is difficult. In this work, we develop an approach for revealing entanglement breakdown using a machine learning technique, which is known as 'learning by confusion'. We consider a family of quantum states, which is parameterized such that there is a single critical value dividing states within this family into separate and entangled. We demonstrate the 'learning by confusion' scheme allows us to determine the critical value. Specifically, we study the performance of the method for the two-qubit, two-qutrit, and two-ququart entangled state. In addition, we investigate the properties of the local depolarization and the generalized amplitude damping channel in the framework of the confusion scheme. Within our approach and setting the parameterization of special trajectories, we obtain an entanglement-breakdown 'phase diagram' of a quantum channel, which indicates regions of entangled (separable) states and the entanglement-breakdown region. Then we extend the way of using the 'learning by confusion' scheme for recognizing whether an arbitrary given state is entangled or separable. We show that the developed method provides correct answers for a variety of states, including entangled states with positive partial transpose. We also present a more practical version of the method, which is suitable for studying entanglement breakdown in noisy intermediate-scale quantum devices. We demonstrate its performance using an available cloud-based IBM quantum processor.

A. I. Gircha, A. S. Boev, K. Avchaciov et al.

Deep generative chemistry models emerge as powerful tools to expedite drug discovery. However, the immense size and complexity of the structural space of all possible drug-like molecules pose significant obstacles, which could be overcome with hybrid architectures combining quantum computers with deep classical networks. As the first step toward this goal, we built a compact discrete variational autoencoder (DVAE) with a Restricted Boltzmann Machine (RBM) of reduced size in its latent layer. The size of the proposed model was small enough to fit on a state-of-the-art D-Wave quantum annealer and allowed training on a subset of the ChEMBL dataset of biologically active compounds. Finally, we generated 2331 novel chemical structures with medicinal chemistry and synthetic accessibility properties in the ranges typical for molecules from ChEMBL. The presented results demonstrate the feasibility of using already existing or soon-to-be-available quantum computing devices as testbeds for future drug discovery applications.

E. O. Kiktenko, A. S. Zelenetsky, A. K. Fedorov

Digital signatures are widely used for providing security of communications. At the same time, the security of currently deployed digital signature protocols is based on unproven computational assumptions. An efficient way to ensure an unconditional (information-theoretic) security of communication is to use quantum key distribution (QKD), whose security is based on laws of quantum mechanics. In this work, we develop an unconditionally secure signature scheme that guarantees authenticity and transferability of arbitrary length messages in a QKD network. In the proposed setup, the QKD network consists of two subnetworks: (i) an internal network that includes the signer and with limitation on the number of malicious nodes and (ii) an external network that has no assumptions on the number of malicious nodes. A consequence of the absence of the trust assumption in the external subnetwork is the necessity of assistance from internal subnetwork recipients for the verification of message-signature pairs by external subnetwork recipients. We provide a comprehensive security analysis of the developed scheme, perform an optimization of the scheme parameters with respect to the secret key consumption, and demonstrate that the developed scheme is compatible with the capabilities of currently available QKD devices.

S. E. Yunakovsky, M. Kot, N. O. Pozhar et al.

Quantum computing technologies pose a significant threat to the currently employed public-key cryptography protocols. In this paper, we discuss the impact of the quantum threat on public key infrastructures (PKIs), which are used as a part of security systems for protecting production environments. We analyze security issues of existing models with a focus on requirements for a fast transition to post-quantum solutions. Although our primary focus is on the attacks with quantum computing, we also discuss some security issues that are not directly related to the used cryptographic algorithms but are essential for the overall security of the PKI. We attempt to provide a set of security recommendations regarding the PKI from the viewpoints of attacks with quantum computers.

M. A. Kudinov, E. O. Kiktenko, A. K. Fedorov

In this work, we discuss in detail a flaw in the original security proof of the W-OTS${^+}$ variant of the Winternitz one-time signature scheme, which is an important component for various stateless and stateful many-time hash-based digital signature schemes. We update the security proof for the W-OTS${^+}$ scheme and derive the corresponding security level. Our result is of importance for the security analysis of hash-based digital signature schemes.

E. O. Kiktenko, M. A. Kudinov, A. A. Bulychev et al.

In the present work, a peculiar property of hash-based signatures allowing detection of their forgery event is explored. This property relies on the fact that a successful forgery of a hash-based signature most likely results in a collision with respect to the employed hash function, while the demonstration of this collision could serve as convincing evidence of the forgery. Here we prove that with properly adjusted parameters Lamport and Winternitz one-time signatures schemes could exhibit a forgery detection availability property. This property is of significant importance in the framework of crypto-agility paradigm since the considered forgery detection serves as an alarm that the employed cryptographic hash function becomes insecure to use and the corresponding scheme has to be replaced.

E. O. Kiktenko, A. O. Malyshev, M. A. Gavreev et al.

Quantum key distribution (QKD) enables unconditionally secure communication between distinct parties using a quantum channel and an authentic public channel. Reducing the portion of quantum-generated secret keys, that is consumed during the authentication procedure, is of significant importance for improving the performance of QKD systems. In the present work, we develop a lightweight authentication protocol for QKD based on a `ping-pong' scheme of authenticity check for QKD. An important feature of this scheme is that the only one authentication tag is generated and transmitted during each of the QKD post-processing rounds. For the tag generation purpose, we design an unconditionally secure procedure based on the concept of key recycling. The procedure is based on the combination of almost universal$_2$ polynomial hashing, XOR universal$_2$ Toeplitz hashing, and one-time pad (OTP) encryption. We demonstrate how to minimize both the length of the recycled key and the size of the authentication key, that is required for OTP encryption. As a result, in real case scenarios, the portion of quantum-generated secret keys that is consumed for the authentication purposes is below 1\%. Finally, we provide a security analysis of the full quantum key growing process in the framework of universally composable security.

Y. A. Kharkov, V. E. Sotskov, A. A. Karazeev et al.

Understanding properties of quantum matter is an outstanding challenge in science. In this paper, we demonstrate how machine-learning methods can be successfully applied for the classification of various regimes in single-particle and many-body systems. We realize neural network algorithms that perform a classification between regular and chaotic behavior in quantum billiard models with remarkably high accuracy. We use the variational autoencoder for autosupervised classification of regular/chaotic wave functions, as well as demonstrating that variational autoencoders could be used as a tool for detection of anomalous quantum states, such as quantum scars. By taking this method further, we show that machine learning techniques allow us to pin down the transition from integrability to many-body quantum chaos in Heisenberg XXZ spin chains. For both cases, we confirm the existence of universal W shapes that characterize the transition. Our results pave the way for exploring the power of machine learning tools for revealing exotic phenomena in quantum many-body systems.

A. S. Trushechkin, P. A. Tregubov, E. O. Kiktenko et al.

Quantum key distribution (QKD) offers a way for establishing information-theoretically secure communications. An important part of QKD technology is a high-quality random number generator (RNG) for quantum states preparation and for post-processing procedures. In the present work, we consider a novel class of prepare-and-measure QKD protocols, utilizing additional pseudorandomness in the preparation of quantum states. We study one of such protocols and analyze its security against the intercept-resend attack. We demonstrate that, for single-photon sources, the considered protocol gives better secret key rates than the BB84 and the asymmetric BB84 protocol. However, the protocol strongly requires single-photon sources.

E. O. Kiktenko, N. O. Pozhar, A. V. Duplinskiy et al.

We report the results of the implementation of a quantum key distribution (QKD) network using standard fibre communication lines in Moscow. The developed QKD network is based on the paradigm of trusted repeaters and allows a common secret key to be generated between users via an intermediate trusted node. The main feature of the network is the integration of the setups using two types of encoding, i.e. polarisation encoding and phase encoding. One of the possible applications of the developed QKD network is the continuous key renewal in existing symmetric encryption devices with a key refresh time of up to 14 s.

I. S. Kabanov, R. R. Yunusov, Y. V. Kurochkin et al.

We review new frontiers in information security technologies in communications and distributed storage technologies with the use of classical, quantum, hybrid classical-quantum, and post-quantum cryptography. We analyze the current state-of-the-art, critical characteristics, development trends, and limitations of these techniques for application in enterprise information protection systems. An approach concerning the selection of practical encryption technologies for enterprises with branched communication networks is introduced.