Laszlo Gyongyosi

PhD in Quantum Information

Contact

Dr. Laszlo Gyongyosi
Quantum Technologies Laboratory
Department of Networked Systems and Services (BME-HIT)
Faculty of Electrical Engineering and Informatics (BME-VIK)

Budapest University of Technology and Economics (BME)

Hungarian Academy of Sciences (MTA)

School of Electronics and Computer Science (ECS)
Faculty of Physical Sciences and Engineering (FPSE)
University of Southampton (Soton)

BME-HIT, 2 Magyar tudosok krt., 1117 Budapest, Hungary
I.B.121., Phone: (+36) 1 463-3261, Fax: (+36) 1 463-3263
gyongyosi@hit.bme.hu
, l.gyongyosi@soton.ac.uk

Laszlo Gyongyosi

Curriculum Vitae

Download CV (PDF)
Research Summary (PDF)
Research Projects

Research Interests

Quantum Computation and Communication
Quantum Information
Quantum Networking
Quantum Cryptography

Education

PhD in Quantum Information with Highest Distinction (Mark: 3.0/3.0), (2013)
Doctoral School of Information Science and Technology
Faculty of Electrical Engineering and Informatics
Budapest University of Technology and Economics

PhD Thesis:
Information Geometric Superactivation of Asymptotic Quantum Capacity and Classical Zero-Error Capacity of Zero-Capacity Quantum Channels
PhD Thesis (PDF)

Advisor: Prof. Sandor Imre
Head of Department
Department of Networked Systems and Services, Budapest University of Technology and Economics

M.Sc. in Theoretical Computer Science with Honors (2008)
Department of Networked Systems and Services
Faculty of Electrical Engineering and Informatics
Budapest University of Technology and Economics

M.Sc Thesis: Quantum Copy-Protection Based on Holographic Data Storage
Diploma with Honors

Advisor: Prof. Sandor Imre
Head of Department
Department of Networked Systems and Services, Budapest University of Technology and Economics

Professional Experience

Research Associate in Quantum Information and Computation
Faculty of Electrical Engineering and Informatics
Budapest University of Technology and Economics

Research Group Leader, Quantum Internet
MTA Premium Postdoctoral Research Program
Hungarian Academy of Sciences

Researcher in Quantum Computation
School of Electronics and Computer Science, University of Southampton
Southampton SO17 1BJ, UK.

Researcher in Quantum Networking and Quantum Key Distribution
U.S. Army Research Laboratory (ARL)-BME
International collaboration in quantum networking and quantum communications

Researcher in Quantum Information
MTA-BME Information Systems Research Group
Mathematics and Natural Sciences
Hungarian Academy of Sciences

Lecturer in Quantum Information and Computation
Faculty of Electrical Engineering and Informatics
Budapest University of Technology and Economics

Selected Publications

L. Gyongyosi, S. Imre. Advances in the Quantum Internet, Communications of the ACM, DOI: 10.1145/3524455, 2022.

The quantum Internet utilizes the fundamental concepts of quantum mechanics for networking. The entangled network structure of the quantum Internet formulates a high-complexity network space with several advantages and challenges. The quantum supremacy of the quantum Internet refers to those advances and properties that are not available in any traditional Internet setting. Here, we review the attributes of quantum supremacy of the quantum Internet, addressing the requirements and proposals, the recent implementation basis, and the open problems.

Communications of the ACM, Volume 65 Issue 8

Article "Advances in the Quantum Internet" on the cover of Communications of the ACM, Volume 65 Issue 8, pp. 52-63, DOI: 10.1145/3524455, 2022.

L. Gyongyosi. Adaptive Problem Solving Dynamics in Gate-Model Quantum Computers, Entropy, DOI: 10.3390/e24091196, 2022.

Gate-model quantum computer architectures represent an implementable model used to realize quantum computations. The mathematical description of the dynamical attributes of adaptive problem solving and iterative objective function evaluation in a gate-model quantum computer is currently a challenge. Here, a mathematical model of adaptive problem solving dynamics in a gate-model quantum computer is defined. We characterize a canonical equation of adaptive objective function evaluation of computational problems. We study the stability of adaptive problem solving in gate-model quantum computers.

L. Gyongyosi, S. Imre. Scalable Distributed Gate-Model Quantum Computers, Scientific Reports, ‎Nature, DOI: 10.1038/s41598-020-76728-5, www.nature.com/articles/s41598-020-76728-5, 2021.

A scalable model for a distributed quantum computation is a challenging problem due to the complexity of the problem space provided by the diversity of possible quantum systems, from small-scale quantum devices to large-scale quantum computers. Here, we define a model of scalable distributed gate-model quantum computation in near-term quantum systems of the NISQ (noisy intermediate scale quantum) technology era. We prove that the proposed architecture can maximize an objective function of a computational problem in a distributed manner. We study the impacts of decoherence on distributed objective function evaluation.

L. Gyongyosi. Post-Processing Optimization for Continuous-Variable Quantum Key Distribution, Theoretical Computer Science, DOI: 10.1016/j.tcs.2021.08.023, 2021.

The performance of a continuous-variable quantum key distribution (CVQKD) protocol depends on the efficiency of the post-processing of measurement results. The post-processing methods extract statistical information from the raw data, establish the mutual knowledge between the parties, and produce a final key that provides absolute security. The post-processing phase is a bottleneck in CVQKD with crucial importance to the efficiency and protocol attributes. Post-processing uses the raw data of the parties generated by the quantum-level transmission and a classical authenticated channel to generate a secret key between the parties. The current reconciliation procedures require high-complexity coding with moderate resulting efficiency. Here we define an optimization method for post-processing in continuous-variable quantum key distribution. The reconciliation method achieves additive Gaussian noise on the random secret for arbitrarily low dimensional blocks. The model consumes all information from the raw data blocks to provide maximal efficiency and security via standard operations. The results can be realized by generic Gaussian coding schemes, allowing an easily implementation for experimental CVQKD protocols.

L. Gyongyosi. Energy Transfer and Thermodynamics of Quantum Gravity Computation, Chaos, Solitons & Fractals, DOI: 10.1016/j.csfx.2020.100050, 2020.

In a quantum gravity environment, the processes and events are causally non-separable because the term of time and the time-steps have no interpretable meaning in a non-fixed causality structure. Here, we study the energy transfer and thermodynamics of quantum gravity computations. We show that a non-fixed causality stimulates entropy transfer between the quantum gravity environment and the independent local systems of the quantum gravity space. We prove that the entropy transfer reduces the entropies of the contributing local systems and increases the entropy of the quantum gravity environment. We reveal on a smooth Cauchy slice that the space-time geometry of the quantum gravity environment dynamically adapts to the vanishing causality. We define the corresponding Hamiltonians and the causal development of the quantum gravity environment.

L. Gyongyosi, S. Imre. Resource Prioritization and Balancing for the Quantum Internet, Scientific Reports, ‎Nature, DOI: 10.1038/s41598-020-78960-5, www.nature.com/articles/s41598-020-78960-5, 2020.

The quantum Internet enables networking based on the fundamentals of quantum mechanics. Here, methods and procedures of resource prioritization and resource balancing are defined for the quantum Internet. We define a model for resource consumption optimization in quantum repeaters, and a strongly-entangled network structure for resource balancing. We study the resource-balancing efficiency of the strongly-entangled structure. We prove that a strongly-entangled quantum network is two times more efficient in a resource balancing problem than a full-mesh network of the traditional Internet.

L. Gyongyosi. Decoherence Dynamics Estimation for Superconducting Gate-Model Quantum Computers, Quantum Information Processing, Springer Nature, DOI: 10.1007/s11128-020-02863-7, 2020.

Superconducting gate-model quantum computer architectures provide an implementable model for practical quantum computations in the NISQ (noisy intermediate scale quantum) technology era. Due to hardware restrictions and decoherence, generating the physical layout of the quantum circuits of a gate-model quantum computer is a challenge. Here, we define a method for layout generation with a decoherence dynamics estimation in superconducting gate-model quantum computers. We propose an algorithm for the optimal placement of the quantum computational blocks of gate-model quantum circuits. We study the effects of capacitance interference on the distribution of the Gaussian noise in the Josephson energy.

L. Gyongyosi. Objective Function Estimation for Solving Optimization Problems in Gate-Model Quantum Computers, Scientific Reports, ‎Nature, DOI: 10.1038/s41598-020-71007-9, www.nature.com/articles/s41598-020-71007-9, 2020.

Quantum computers provide a valuable resource to solve computational problems. The maximization of the objective function of a computational problem is a crucial problem in gate-model quantum computers. The objective function estimation is a high-cost procedure that requires several rounds of quantum computations and measurements. Here, we define a method for objective function estimation of arbitrary computational problems in gate-model quantum computers. The proposed solution significantly reduces the costs of the objective function estimation and provides an optimized estimate of the state of the quantum computer for solving optimization problems.

L. Gyongyosi. Unsupervised Quantum Gate Control for Gate-Model Quantum Computers, Scientific Reports, ‎Nature, DOI: 10.1038/s41598-020-67018-1, www.nature.com/articles/s41598-020-67018-1, 2020.

In near-term quantum computers, the operations are realized by unitary quantum gates. The precise and stable working mechanism of quantum gates is essential for the implementation of any complex quantum computations. Here, we define a method for the unsupervised control of quantum gates in near-term quantum computers. We model a scenario in which a tensor product structure of non-stable quantum gates is not controllable in terms of control theory. We prove that the non-stable quantum gate becomes controllable via a machine learning method if the quantum gates formulate an entangled gate structure.

L. Gyongyosi, S. Imre. Circuit Depth Reduction for Gate-Model Quantum Computers, Scientific Reports, ‎Nature, DOI: 10.1038/s41598-020-67014-5, www.nature.com/articles/s41598-020-67014-5, 2020.

Quantum computers utilize the fundamentals of quantum mechanics to solve computational problems more efficiently than traditional computers. Gate-model quantum computers are fundamental to implement near-term quantum computer architectures and quantum devices. Here, a quantum algorithm is defined for the circuit depth reduction of gate-model quantum computers. The proposed solution evaluates the reduced time complexity equivalent of a reference quantum circuit. We prove the complexity of the quantum algorithm and the achievable reduction in circuit depth. The method provides a tractable solution to reduce the time complexity and physical layer costs of quantum computers.

L. Gyongyosi. Dynamics of Entangled Networks of the Quantum Internet, Scientific Reports, ‎Nature, DOI: 10.1038/s41598-020-68498-x, www.nature.com/articles/s41598-020-68498-x, 2020.

Entangled quantum networks are a fundamental of any global-scale quantum Internet. Here, a mathematical model is developed to quantify the dynamics of entangled network structures and entanglement flow in the quantum Internet. The analytical solutions of the model determine the equilibrium states of the entangled quantum networks and characterize the stability, fluctuation attributes, and dynamics of entanglement flow in entangled network structures. We demonstrate the results of the model through various entangled structures and quantify the dynamics.

L. Gyongyosi, S. Imre. Routing Space Exploration for Scalable Routing in the Quantum Internet, Scientific Reports, ‎Nature, DOI: 10.1038/s41598-020-68354-y, www.nature.com/articles/s41598-020-68354-y, 2020.

The entangled network structure of the quantum Internet formulates a high complexity routing space that is hard to explore. Scalable routing is a routing method that can determine an optimal routing at particular subnetwork conditions in the quantum Internet to perform a high-performance and low-complexity routing in the entangled structure. Here, we define a method for routing space exploration and scalable routing in the quantum Internet. We prove that scalable routing allows a compact and efficient routing in the entangled networks of the quantum Internet.

L. Gyongyosi. Quantum State Optimization and Computational Pathway Evaluation for Gate-Model Quantum Computers, Scientific Reports, ‎Nature, DOI: 10.1038/s41598-020-61316-4, www.nature.com/articles/s41598-020-61316-4, 2020.

A computational problem fed into a gate-model quantum computer identifies an objective function with a particular computational pathway (objective function connectivity). The solution of the computational problem involves identifying a target objective function value that is the subject to be reached. A bottleneck in a gate-model quantum computer is the requirement of several rounds of quantum state preparations, high-cost run sequences, and multiple rounds of measurements to determine a target (optimal) state of the quantum computer that achieves the target objective function value. Here, we define a method for optimal quantum state determination and computational path evaluation for gate-model quantum computers. We prove a state determination method that finds a target system state for a quantum computer at a given target objective function value. The computational pathway evaluation procedure sets the connectivity of the objective function in the target system state on a fixed hardware architecture of the quantum computer. The proposed solution evolves the target system state without requiring the preparation of intermediate states between the initial and target states of the quantum computer. Our method avoids high-cost system state preparations and expensive running procedures and measurement apparatuses in gate-model quantum computers. The results are convenient for gate-model quantum computations and the near-term quantum devices of the quantum Internet.

L. Gyongyosi, S. Imre. Theory of Noise-Scaled Stability Bounds and Entanglement Rate Maximization in the Quantum Internet, Scientific Reports, ‎Nature, DOI: 10.1038/s41598-020-58200-6, www.nature.com/articles/s41598-020-58200-6, 2020.

Crucial problems of the quantum Internet are the derivation of stability properties of quantum repeaters and theory of entanglement rate maximization in an entangled network structure. The stability property of a quantum repeater entails that all incoming density matrices can be swapped with a target density matrix. The strong stability of a quantum repeater implies stable entanglement swapping with the boundness of stored density matrices in the quantum memory and the boundness of delays. Here, a theoretical framework of noise-scaled stability analysis and entanglement rate maximization is conceived for the quantum Internet. We define the term of entanglement swapping set that models the status of quantum memory of a quantum repeater with the stored density matrices. We determine the optimal entanglement swapping method that maximizes the entanglement rate of the quantum repeaters at the different entanglement swapping sets as function of the noise of the local memory and local operations. We prove the stability properties for non-complete entanglement swapping sets, complete entanglement swapping sets and perfect entanglement swapping sets. We prove the entanglement rates for the different entanglement swapping sets and noise levels. The results can be applied to the experimental quantum Internet.

L. Gyongyosi, S. Imre. Subcarrier Domain of Multicarrier Continuous-Variable Quantum Key Distribution, Journal of Statistical Physics, Springer Nature, DOI: 10.1007/s10955-019-02404-2, 2019.

The subcarrier domain of multicarrier continuous-variable quantum key distribution (CVQKD) is defined. In a multicarrier CVQKD scheme, the information is granulated into Gaussian subcarrier CVs and the physical Gaussian link is divided into Gaussian subchannels. The subcarrier domain injects physical attributes to the description of the subcarrier transmission.We prove that the subcarrier domain is a natural representation of the subcarrierlevel transmission in a multicarrier CVQKD scheme. We also extend the subcarrier domain to a multiple-access multicarrier CVQKD setting. We demonstrate the results through the adaptive multicarrier quadrature-division (AMQD) CVQKD scheme and the AMQD-MQA (multiuser quadrature allocation) multiple-access multicarrier scheme. The subcarrier domain representation provides a general apparatus that can be utilized for an arbitrary multicarrier CVQKD scenario.

Journal of Statistical Physics

Journal of Statistical Physics, Vol. 177, pp. 960-983, DOI: 10.1007/s10955-019-02404-2, 2019.

L. Gyongyosi, S. Imre. Optimizing High-Efficiency Quantum Memory with Quantum Machine Learning for Near-Term Quantum Devices, Scientific Reports, ‎Nature, DOI: 10.1038/s41598-019-56689-0, www.nature.com/articles/s41598-019-56689-0, 2019.

Quantum memories are a fundamental of any global-scale quantum Internet, high-performance quantum networking and near-term quantum computers. A main problem of quantum memories is the low retrieval efficiency of the quantum systems from the quantum registers of the quantum memory. Here, we define a novel quantum memory called high-retrieval-efficiency (HRE) quantum memory for near-term quantum devices. An HRE quantum memory unit integrates local unitary operations on its hardware level for the optimization of the readout procedure and utilizes the advanced techniques of quantum machine learning. We define the integrated unitary operations of an HRE quantum memory, prove the learning procedure, and evaluate the achievable output signal-to-noise ratio values. We prove that the local unitaries of an HRE quantum memory achieve the optimization of the readout procedure in an unsupervised manner without the use of any labeled data or training sequences. We show that the readout procedure of an HRE quantum memory is realized in a completely blind manner without any information about the input quantum system or about the unknown quantum operation of the quantum register. We evaluate the retrieval efficiency of an HRE quantum memory and the output SNR (signal-to-noise ratio). The results are particularly convenient for gate-model quantum computers and the near-term quantum devices of the quantum Internet.

L. Gyongyosi, S. Imre. Training Optimization for Gate-Model Quantum Neural Networks, Scientific Reports, ‎Nature, DOI: 10.1038/s41598-019-48892-w, www.nature.com/articles/s41598-019-48892-w, 2019.

Gate-based quantum computations represent an essential to realize near-term quantum computer architectures. A gate-model quantum neural network (QNN) is a QNN implemented on a gate-model quantum computer, realized via a set of unitaries with associated gate parameters. Here, we define a training optimization procedure for gate-model QNNs. By deriving the environmental attributes of the gate-model quantum network, we prove the constraint-based learning models. We show that the optimal learning procedures are different if side information is available in different directions, and if side information is accessible about the previous running sequences of the gate-model QNN. The results are particularly convenient for gate-model quantum computer implementations.

L. Gyongyosi, S. Imre. A Survey on Quantum Computing Technology, Computer Science Review, Elsevier, DOI: 10.1016/j.cosrev.2018.11.002, 2019.

The power of quantum computing technologies is based on the fundamentals of quantum mechanics, such as quantum superposition, quantum entanglement, or the no-cloning theorem. Since these phenomena have no classical analogue, similar results cannot be achieved within the framework of traditional computing. The experimental insights of quantum computing technologies have already been demonstrated, and several studies are in progress. Here we review the most recent results of quantum computation technology and address the open problems of the field.

Computer Science Review

Computer Science Review, Vol. 31, pp. 51-71, DOI: 10.1016/j.cosrev.2018.11.002, 2019.

L. Gyongyosi, S. Imre. State Stabilization for Gate-Model Quantum Computers, ‎Quantum Information Processing, Springer Nature, DOI: 10.1007/s11128-019-2397-0, 2019.

Gate-model quantum computers can allow quantum computations in near-term implementations. The stabilization of an optimal quantum state of a quantum computer is a challenge, since it requires stable quantum evolutions via a precise calibration of the unitaries. Here, we propose a method for the stabilization of an optimal quantum state of a quantum computer through an arbitrary number of running sequences. The optimal state of the quantum computer is set to maximize an objective function of an arbitrary problem fed into the quantum computer. We also propose a procedure to classify the stabilized quantum states of the quantum computer into stability classes. The results are convenient for gate-model quantum computations and near-term quantum computers.

L. Gyongyosi, S. Imre. Multiple Access Multicarrier Continuous-Variable Quantum Key Distribution, Chaos, Solitons & Fractals, DOI: 10.1016/j.chaos.2018.07.006, 2018.

One of the most important practical realizations of the fundamentals of quantum mechanics is continuous-variable quantum key distribution (CVQKD). Here we propose the adaptive multicarrier quadrature division-multiuser quadrature allocation (AMQD-MQA) multiple access technique for continuous-variable quantum key distribution. The MQA scheme is based on the AMQD modulation, which granulates the inputs of the users into Gaussian subcarrier continuous-variables (CVs). In an AMQD-MQA multiple access scenario, the simultaneous reliable transmission of the users is handled by the dynamic allocation of the Gaussian subcarrier CVs. We propose two different settings of AMQD-MQA for multiple input-multiple output communication. We introduce a rate-selection strategy that tunes the modulation variances and allocates adaptively the quadratures of the users over the sub-channels. We also prove the rate formulas if only partial channel side information is available for the users of the sub-channel conditions. We show a technique for the compensation of a nonideal Gaussian input modulation, which allows the users to overwhelm the modulation imperfections to reach optimal capacity-achieving communication over the Gaussian sub-channels. We investigate the diversity amplification of the sub-channel transmittance coefficients and reveal that a strong diversity can be exploited by opportunistic Gaussian modulation.

Chaos, Solitons & Fractals

Chaos, Solitons & Fractals, Vol. 114, pp. 491-505, DOI: 10.1016/j.chaos.2018.07.006, 2018.

L. Gyongyosi. Multicarrier Continuous-Variable Quantum Key Distribution, Theoretical Computer Science, Elsevier, DOI: 10.1016/j.tcs.2019.11.026, 2019.

The multicarrier continuous-variable quantum key distribution (CVQKD) protocol is defined. In a CVQKD protocol, the information is conveyed by coherent quantum states. The quantum continuous variables are sent through a noisy quantum channel. For a quantum channel with additive-multiplicative noise both additive and multiplicative disturbances are present in the transmission. The multiplicative disturbance is an inherent attribute of diverse physical environments. Physical links with additive and multiplicative disturbances can represent a more general approach than purely additive noise links in several practical scenarios. In a standard CVQKD setting, the noise is modeled as an additive white Gaussian noise caused by an eavesdropper (Gaussian quantum link). As a corollary, standard CVQKD protocols are not optimal for arbitrary Gaussian quantum channels if multiplicative disturbances are also present in the physical link. Here, we define the adaptive multicarrier quadrature division (AMQD) modulation technique for CVQKD. The AMQD method is optimal for arbitrary Gaussian quantum channels with arbitrary multiplicative disturbances. The protocol granulates the Gaussian random input into Gaussian subcarrier continuous variables in the encoding phase, which are then decoded by a continuous unitary transformation. The subcarrier coherent variables formulate sub-channels from the physical link which leads to improved transmission efficiency, higher tolerable loss, and excess noise in comparison to standard CVQKD protocols. We also derive the security proof of multicarrier CVQKD at optimal Gaussian attacks in the finite-size and asymptotic regimes.

Theoretical Computer Science

Theoretical Computer Science, Vol. 816, pp. 67-95, DOI: 10.1016/j.tcs.2019.11.026, 2019.

L. Gyongyosi, S. Imre. Quantum Circuit Design for Objective Function Maximization in Gate-Model Quantum Computers, ‎Quantum Information Processing, Springer Nature, DOI: 10.1007/s11128-019-2326-2, 2019.

Gate-model quantum computers provide an experimentally implementable architecture for near-term quantum computations. To design a reduced quantum circuit that can simulate a high-complexity reference quantum circuit, an optimization should be taken on the number of input quantum states, on the unitary operations of the quantum circuit, and on the number of output measurement rounds. Besides the optimization of the physical layout of the hardware layer, the quantum computer should also solve difficult computational problems very efficiently. To yield a desired output system, a particular objective function associated with the computational problem fed into the quantum computer should be maximized. The reduced gate structure should be able to produce the maximized value of the objective function. These parallel requirements must be satisfied simultaneously, which makes the optimization difficult. Here, we demonstrate a method for designing quantum circuits for gate-model quantum computers and define the Quantum Triple Annealing Minimization (QTAM) algorithm. The aim of QTAM is to determine an optimal reduced topology for the quantum circuits in the hardware layer at the maximization of the objective function of an arbitrary computational problem.

L. Gyongyosi, S. Imre. Dense Quantum Measurement Theory, Scientific Reports, ‎Nature, DOI: 10.1038/s41598-019-43250-2, www.nature.com/articles/s41598-019-43250-2, 2019.

Quantum measurement is a fundamental cornerstone of experimental quantum computations. The main issues in current quantum measurement strategies are the high number of measurement rounds to determine a global optimal measurement output and the low success probability of finding a global optimal measurement output. Each measurement round requires preparing the quantum system and applying quantum operations and measurements with high-precision control in the physical layer. These issues result in extremely high-cost measurements with a low probability of success at the end of the measurement rounds. Here, we define a novel measurement for quantum computations called dense quantum measurement. The dense measurement strategy aims at fixing the main drawbacks of standard quantum measurements by achieving a significant reduction in the number of necessary measurement rounds and by radically improving the success probabilities of finding global optimal outputs. We provide application scenarios for quantum circuits with arbitrary unitary sequences, and prove that dense measurement theory provides an experimentally implementable solution for gate-model quantum computer architectures.

L. Gyongyosi, S. Imre. Opportunistic Entanglement Distribution for the Quantum Internet, Scientific Reports, ‎Nature, DOI: 10.1038/s41598-019-38495-w, www.nature.com/articles/s41598-019-38495-w, 2019.

Quantum entanglement is a building block of the entangled quantum networks of the quantum Internet. A fundamental problem of the quantum Internet is entanglement distribution. Since quantum entanglement will be fundamental to any future quantum networking scenarios, the distribution mechanism of quantum entanglement is a critical and emerging issue in quantum networks. Here we define the method of opportunistic entanglement distribution for the quantum Internet. The opportunistic model defines distribution sets that are aimed to select those quantum nodes for which the cost function picks up a local minimum. The cost function utilizes the error patterns of the local quantum memories and the predictability of the evolution of the entanglement fidelities. Our method provides efficient entanglement distributing with respect to the actual statuses of the local quantum memories of the node pairs. The model provides an easily-applicable, moderate-complexity solution for high-fidelity entanglement distribution in experimental quantum Internet scenarios.

L. Gyongyosi, S. Imre. Multilayer Optimization for the Quantum Internet, Scientific Reports, ‎Nature, DOI:10.1038/s41598-018-30957-x, www.nature.com/articles/s41598-018-30957-x, 2018.

We define a multilayer optimization method for the quantum Internet. Multilayer optimization integrates separate procedures for the optimization of the quantum layer and the classical layer of the quantum Internet. The multilayer optimization procedure defines advanced techniques for the optimization of the layers. The optimization of the quantum layer covers the minimization of total usage time of quantum memories in the quantum nodes, the maximization of the entanglement throughput over the entangled links, and the reduction of the number of entangled links between the arbitrary source and target quantum nodes. The objective of the optimization of the classical layer is the cost minimization of any auxiliary classical communications. The multilayer optimization framework provides a practically implementable tool for quantum network communications, or long-distance quantum communications.

L. Gyongyosi, S. Imre. Decentralized Base-Graph Routing for the Quantum Internet, Physical Review A, American Physical Society, DOI: 10.1103/PhysRevA.98.022310, 2018.

Quantum repeater networks are a fundamental of any future quantum internet and long-distance quantum communications. The entangled quantum nodes can communicate through several different levels of entanglement, leading to a heterogeneous, multilevel network structure. The level of entanglement between the quantum nodes determines the hop distance and the probability of the existence of an entangled link in the network. Here, we define a decentralized routing for entangled quantum networks. The proposed method allows an efficient routing to find the shortest paths in entangled quantum networks by using only local knowledge of the quantum nodes. We give bounds on the maximum value of the total number of entangled links of a path. The proposed scheme can be directly applied in practical quantum communications and quantum networking scenarios.

L. Gyongyosi, S. Imre, H. V. Nguyen. A Survey on Quantum Channel Capacities, IEEE Communications Surveys and Tutorials, IEEE, 10.1109/COMST.2017.2786748, 2018.

Quantum information processing exploits the quantum nature of information. It offers fundamentally new solutions in the field of computer science and extends the possibilities to a level that cannot be imagined in classical communication systems. For quantum communication channels, many new capacity definitions were developed in comparison to classical counterparts. A quantum channel can be used to realize classical information transmission or to deliver quantum information, such as quantum entanglement. Here we review the properties of the quantum communication channel, the various capacity measures and the fundamental differences between the classical and quantum channels.

IEEE Communications Surveys and Tutorials, IEEE

IEEE Communications Surveys and Tutorials, Vol 20, Issue 2, pp. 1149-1205, ISSN 1553-877X, IEEE, DOI: 10.1109/COMST.2017.2786748, 2018.

L. Gyongyosi, S. Imre. Entanglement-Gradient Routing for Quantum Networks, Scientific Reports, ‎Nature, www.nature.com/articles/s41598-017-14394-w, 2017.

We define the entanglement-gradient routing scheme for quantum repeater networks. The routing framework fuses the fundamentals of swarm intelligence and quantum Shannon theory. Swarm intelligence provides nature-inspired solutions for problem solving. Motivated by models of social insect behavior, the routing is performed using parallel threads to determine the shortest path via the entanglement gradient coefficient, which describes the feasibility of the entangled links and paths of the network. The routing metrics are derived from the characteristics of entanglement transmission and relevant measures of entanglement distribution in quantum networks. The method allows a moderate complexity decentralized routing in quantum repeater networks. The results can be applied in experimental quantum networking, future quantum Internet, and long-distance quantum communications.

L Gyongyosi. Quantum Imaging of High-Dimensional Hilbert Spaces with Radon Transform, International Journal of Circuit Theory and Applications (IJCTA), Special Issue on Quantum Circuits (Wiley), DOI: 10.1002/cta.2332, 2017.

High-dimensional Hilbert spaces possess large information encoding and transmission capabilities. Characterizing exactly the real potential of high-dimensional entangled systems is a cornerstone of tomography and quantum imaging. The accuracy of the measurement apparatus and devices used in quantum imaging is physically limited, which allows no further improvements to be made. To extend the possibilities, we introduce a post-processing method for quantum imaging that is based on the Radon transform and the projection-slice theorem. The proposed solution leads to an enhanced precision and a deeper parameterization of the information conveying capabilities of high-dimensional Hilbert spaces. We demonstrate the method for the analysis of high-dimensional position-momentum photonic entanglement. We show that the entropic separability bound in terms of standard deviations is violated considerably more strongly in comparison to the standard setting and current data processing. The results indicate that the possibilities of the quantum imaging of high-dimensional Hilbert spaces can be extended by applying appropriate calculations in the post-processing phase.

International Journal of Circuit Theory and Applications

International Journal of Circuit Theory and Applications, Special Issue: Quantum Circuits, Vol. 45, Issue 7, pp. 1029-1046, DOI: 10.1002/cta.2332, 2017.

L. Gyongyosi, S. Imre. Gaussian Quadrature Inference for Continuous-Variable Quantum Key Distribution, Proceedings of SPIE Quantum Information and Computation IX, DOI: 10.1117/12.2223482, 2016.

We propose the Gaussian quadrature inference (GQI) method for multicarrier continuous-variable quantum key distribution (CVQKD). A multicarrier CVQKD protocol utilizes Gaussian subcarrier quantum continuous variables (CV) for information transmission. The GQI framework provides a minimal error estimate of the quadratures of the CV quantum states from the discrete, measured noisy subcarrier variables. GQI utilizes the fundamentals of regularization theory and statistical information processing. We characterize GQI for multicarrier CVQKD, and define a method for the statistical modeling and processing of noisy Gaussian subcarrier quadratures. We demonstrate the results through the adaptive multicarrier quadrature division (AMQD) scheme. We introduce the terms statistical secret key rate and statistical private classical information, which quantities are derived purely by the statistical functions of GQI. We prove the secret key rate formulas for a multiple access multicarrier CVQKD via the AMQD-MQA (multiuser quadrature allocation) scheme. The framework can be established in an arbitrary CVQKD protocol and measurement setting, and are implementable by standard low-complexity statistical functions, which is particularly convenient for an experimental CVQKD scenario.

L. Gyongyosi, S. Imre. Eigenchannel Decomposition for Continuous-Variable Quantum Key Distribution, Proceedings of SPIE Advances in Photonics of Quantum Computing, Memory, and Communication VIII, DOI: 10.1117/12.2076532, 2015.

We develop a singular layer transmission model for continuous-variable quantum key distribution (CVQKD). In CVQKD, the transmit information is carried by continuous-variable (CV) quantum states, particularly by Gaussian random distributed position and momentum quadratures. The reliable transmission of the quadrature components over a noisy link is a cornerstone of CVQKD protocols. The proposed singular layer uses the singular value decomposition of the Gaussian quantum channel, which yields an additional degree of freedom for the phase space transmission. This additional degree of freedom can further be exploited in a multiple-access scenario. The singular layer defines the eigenchannels of the Gaussian physical link, which can be used for the simultaneous reliable transmission of multiple user data streams. We demonstrate the results through the adaptive multicarrier quadrature division-multiuser quadrature allocation (AMQD-MQA) CVQKD multiple-access scheme. We define the singular model of AMQD-MQA and characterize the properties of the eigenchannel interference. The singular layer transmission provides improved simultaneous transmission rates for the users with unconditional security in a multiple-access scenario, particularly in crucial low signal-to-noise ratio regimes.

L. Gyongyosi. A Statistical Model of Information Evaporation of Perfectly Reflecting Black Holes, International Journal of Quantum Information (IJQI), ISSN 0219-7499, 1793-6918, DOI: 10.1142/S0219749915600254, 2014.

We provide a statistical communication model for the phenomenon of quantum information evaporation from black holes (BHs). A BH behaves as a reflecting quantum channel in a very special regime, which allows for a receiver to perfectly recover the absorbed quantum information. The quantum channel of a perfectly reflecting (PR) BH is the probabilistically weighted sum of infinitely many qubit cloning channels. In this work, we reveal the statistical communication background of the information evaporation process of PR BHs. We show that the density of the cloned quantum particles in function of the PR BH's mass approximates a Chi-square distribution, while the stimulated emission process is characterized by zero-mean, circular symmetric complex Gaussian random variables. The results lead to the existence of Rayleigh random distributed coefficients in the probability density evolution, which confirms the presence of Rayleigh fading (a special type of random fluctuation) in the statistical communication model of BH information evaporation.

International Journal of Circuit Theory and Applications

International Journal of Quantum Information, Vol. 12, No. 07n08, 1560025, DOI: 10.1142/S0219749915600254, 2014.

L. Gyongyosi, S. Imre. Geometrical Analysis of Physically Allowed Quantum Cloning Transformations for Quantum Cryptography, Information Sciences, Elsevier, ISSN: 0020-0255; http://dx.doi.org/10.1016/j.ins.2014.07.010, 2014.

The security of quantum key distribution (QKD) relies on the no-cloning theorem, which allows no to copy perfectly a quantum system. An eavesdropping activity on the quantum channel perturbs the state of the quantum states, which results in noise at the receiver. The physical layer detection of the eavesdropping activity of the quantum channel requires tomography, which is intractable in experiment. An adequate and equivalent answer for the problem can be proposed through the logical layer. We propose an efficient algorithmical tool to study the eavesdropping activity on the quantum channel and characterize the properties of a quantum cloning-based attack for DV and CVQKD protocols. The physically allowed quantum cloning transformations on a quantum system can be described in terms of information geometry. We propose a computational geometrical method to analyze the cloning activity on the quantum channel and to characterize the noise properties. The security analysis studies the DV (discrete variable) and CV (continuous variable) QKD schemes through the four-state (BB84) and six-state DVQKD protocols and the two-way CVQKD protocol. The proposed geometrical method provides a useful tool to analyze the most powerful attacks against quantum cryptography and the effects of the physically allowed quantum cloning transformations.

S. Imre, L. Gyongyosi. Advanced Quantum Communications - An Engineering Approach, Publisher: Wiley-IEEE Press (New Jersey, USA), John Wiley & Sons, Inc., The Institute of Electrical and Electronics Engineers, ISBN-10: 1118002369, ISBN-13: 978-11180023, 488 pages, 2013.

In this book, we present the fundamental results of quantum information theory and the details of advanced quantum communication protocols with clear mathematical and information theoretical background.

Advanced Quantum Communications, Laszlo Gyongyosi

Advanced Quantum Communications - An Engineering Approach, Publisher: Wiley-IEEE Press (New Jersey, USA), John Wiley and Sons, Inc., The Institute of Electrical and Electronics Engineers, ISBN-10: 1118002369, ISBN-13: 978-11180023, 488 pages, Hardcover, 2013.

L. Gyongyosi. The Correlation Conversion Property of Quantum Channels, Quantum Information Processing, Springer, ISSN: 1570-0755, ISSN: 1573-1332, DOI: 10.1007/s11128-013-0663-0, 2013.

Transmission of quantum entanglement will play a crucial role in future networks and long-distance quantum communications. Quantum Key Distribution, the working mechanism of quantum repeaters and the various quantum communication protocols are all based on quantum entanglement. On the other hand, quantum entanglement is extremely fragile and sensitive to the noise of the communication channel over which it has been transmitted. To share entanglement between distant points, high fidelity quantum channels are needed. In practice, these communication links are noisy, which makes it impossible or extremely difficult and expensive to distribute entanglement. In this work we first show that quantum entanglement can be generated by a new idea, exploiting the most natural effect of the communication channels: the noise itself of the link. We prove that the noise transformation of quantum channels that are not able to transmit quantum entanglement can be used to generate distillable (useable) entanglement from classically correlated input. We call this new phenomenon the Correlation Conversion property (CC-property) of quantum channels. The proposed solution does not require any non-local operation or local measurement by the parties, only the use of standard quantum channels.

L. Gyongyosi, S. Imre. Superactivation of Quantum Channels is Limited by the Quantum Relative Entropy Function, Quantum Information Processing, Springer, ISSN: 1570-0755, ISSN: 1573-1332, DOI: 10.1007/s11128-012-0446-z, 2012.

In this work we prove that the possibility of superactivation of quantum channel capacities is determined by the mathematical properties of the quantum relative entropy function. Before our work this fundamental and purely mathematical connection between the quantum relative entropy function and the superactivation effect was completely unrevealed. We demonstrate the results for the quantum capacity; however the proposed theorems and connections hold for all other channel capacities of quantum channels for which the superactivation is possible.

Quantum Information Processing

Quantum Information Processing, Vol. 12, pp. 1011-1021, DOI: 10.1007/s11128-012-0446-z, 2012.

L. Gyongyosi, S. Imre. Algorithmic Superactivation of Asymptotic Quantum Capacity of Zero-Capacity Quantum Channels, Information Sciences, Elsevier, ISSN: 0020-0255; DOI: 10.1016/j.ins.2012.08.008, 2012.

The superactivation of zero-capacity quantum channels makes it possible to use two zero-capacity quantum channels with a positive joint capacity for their output. Currently, we have no theoretical background to describe all possible combinations of superactive zero-capacity channels; hence, there may be many other possible combinations. In practice, to discover such superactive zero-capacity channel-pairs, we must analyze an extremely large set of possible quantum states, channel models, and channel probabilities. There is still no extremely efficient algorithmic tool for this purpose. This paper shows an efficient algorithmical method of finding such combinations. Our method can be a very valuable tool for improving the results of fault-tolerant quantum computation and possible communication techniques over very noisy quantum channels.

Information Sciences

Information Sciences, Vol. 222, pp. 737-753, DOI: 10.1016/j.ins.2012.08.008, 2012.

L. Gyongyosi, with S. Imre et al. Quantum-assisted and Quantum-based Solutions in Wireless Systems, in: ,,Wireless Myths, Realities and Futures: From 3G/4G to Optical and Quantum Wireless'', Proceedings of the IEEE, 100th Year Anniversary Celebration Volume of the Proceedings of the IEEE, ISSN: 0018-9219, DOI: 10.1109/JPROC.2012.2189788, 2012.

In wireless systems there is always a trade-off between reducing the transmit power and mitigating the resultant signal-degradation imposed by the transmit-power reduction with the aid of sophisticated receiver algorithms, when considering the total energy consumption. Quantum-assisted wireless communications exploits the extra computing power offered by quantum mechanics based architectures. This paper summarizes some recent results in quantum computing and the corresponding application areas in wireless communications.

Proceedings of the IEEE, Laszlo Gyongyosi

Proceedings of the IEEE, 100th Year Anniversary Celebration Volume, Special Centennial Celebration Issue, DOI: 10.1109/JPROC.2012.2189788, 2012

L. Gyongyosi, S. Imre. Quantum Singular Value Decomposition Based Approximation Algorithm, Journal of Circuits, Systems, and Computers (JCSC), World Scientific, DOI: 10.1142/S0218126610006797; 2010.

Singular Value Decomposition (SVD) is one of the most useful techniques for analyzing data in linear algebra. SVD decomposes a rectangular real or complex matrix into two orthogonal matrices and one diagonal matrix. The proposed Quantum-SVD algorithm interpolates the non-uniform angles in the Fourier domain. The error of the Quantum-SVD approach is some orders lower than the error given by ordinary Quantum Fourier Transformation. Our Quantum-SVD algorithm is a fundamentally novel approach for the computation of the Quantum Fourier Transformation (QFT) of non-uniform states. The presented Quantum-SVD algorithm is based on the singular value decomposition mechanism, and the computation of Quantum Fourier Transformation of non-uniform angles of a quantum system. The Quantum-SVD approach provides advantages in terms of computational structure, being based on QFT and multiplications.

Journal Papers

Books

Advanced Quantum Communications, Laszlo Gyongyosi

Advanced Quantum Communications - An Engineering Approach, Publisher: Wiley-IEEE Press (New Jersey, USA), John Wiley and Sons, Inc., The Institute of Electrical and Electronics Engineers, ISBN-10: 1118002369, ISBN-13: 978-11180023, 488 pages, Hardcover, 2013.

 

Book Chapters

PhD Dissertation

Algorithmic Superactivation of Zero-Capacity Quantum Channels, PhD Dissertation, ISBN-13: 978-3-659-18584-7, 2013.

 

Conference Papers

arXiv

My papers on the arXiv.

L. Gyongyosi. Quantum State Optimization and Computational Pathway Evaluation for Gate-Model Quantum Computers
2020, Subjects: Quantum Physics (quant-ph)
Download: arXiv:2003.05255

L. Gyongyosi, S. Imre. Theory of Noise-Scaled Stability Bounds and Entanglement Rate Maximization in the Quantum Internet
2020, Subjects: Quantum Physics (quant-ph); Networking and Internet Architecture (cs.NI)
Download: arXiv:2003.05245

L. Gyongyosi, S. Imre. Optimizing High-Efficiency Quantum Memory with Quantum Machine Learning for Near-Term Quantum Devices
2020, Subjects: Quantum Physics (quant-ph); Networking and Internet Architecture (cs.NI)
Download: arXiv:2003.05244

L. Gyongyosi, S. Imre. Entanglement Accessibility Measures for the Quantum Internet
2020, Subjects: Quantum Physics (quant-ph); Networking and Internet Architecture (cs.NI)
Download: arXiv:2003.05239

L. Gyongyosi, S. Imre. Training Optimization for Gate-Model Quantum Neural Networks
2019, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1909.01048

L. Gyongyosi, S. Imre. State Stabilization for Gate-Model Quantum Computers
2019, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1909.01044

L. Gyongyosi, S. Imre. Dense Quantum Measurement Theory
2019, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1905.00260

L. Gyongyosi, S. Imre. Opportunistic Entanglement Distribution for the Quantum Internet
2019, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1905.00258

L. Gyongyosi, S. Imre. Entanglement Access Control for the Quantum Internet
2019, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1905.00256

L. Gyongyosi, S. Imre. Adaptive Routing for Quantum Memory Failures in the Quantum Internet
2019, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1905.00254

L. Gyongyosi, S. Imre. Topology Adaption for the Quantum Internet
2018, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1809.02928

L. Gyongyosi, S. Imre. Multilayer Optimization for the Quantum Internet
2018, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1808.07860

L. Gyongyosi, S. Imre. Entanglement Availability Differentiation Service for the Quantum Internet
2018, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1808.07859

L. Gyongyosi, S. Imre. A Poisson Model for Entanglement Optimization in the Quantum Internet
2018, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1803.02469

L. Gyongyosi, S. Imre. Quantum Circuit Design for Objective Function Maximization in Gate-Model Quantum Computers
2018, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1803.02460

L. Gyongyosi, S. Imre. Decentralized Base-Graph Routing for the Quantum Internet
2018, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1801.02020

L. Gyongyosi, S. Imre, Hung Viet Nguyen: A Survey on Quantum Channel Capacities
2018, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1801.02019

L. Gyongyosi, S. Imre. Entanglement-Gradient Routing for Quantum Networks
2017, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1710.02779

L. Gyongyosi. Iterative Secret Key Rate Adapting with Error Minimization for Continuous-Variable Quantum Key Distribution
2016, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1610.02823

L. Gyongyosi. Diversity Extraction for Multicarrier Continuous-Variable Quantum Key Distribution
2016, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1610.02822

L. Gyongyosi. Statistical Quadrature Evolution by Inference for Continuous-Variable Quantum Key Distribution
2016, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1603.09247

L. Gyongyosi. Correlation Measure Equivalence in Dynamic Causal Structures of Quantum Gravity
2016, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT); General Relativity and Quantum Cosmology (gr-qc); High Energy Physics - Theory (hep-th)
Download: arXiv:1603.02416

L. Gyongyosi. Gaussian Quadrature Inference for Multicarrier Continuous-Variable Quantum Key Distribution
2015, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1504.05574

L. Gyongyosi. Distribution Statistics and Random Matrix Formalism of Multicarrier Continuous-Variable Quantum Key Distribution
2014, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1410.8273

L. Gyongyosi. Adaptive Quadrature Detection for Multicarrier Continuous-Variable Quantum Key Distribution
2014, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1408.6493

L. Gyongyosi. Subcarrier Domain of Multicarrier Continuous-Variable Quantum Key Distribution
2014, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1406.6949

L. Gyongyosi. Multidimensional Manifold Extraction for Multicarrier Continuous-Variable Quantum Key Distribution
2014, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1405.6948

L. Gyongyosi. Security Thresholds of Multicarrier Continuous-Variable Quantum Key Distribution
2014, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1404.7109

L. Gyongyosi. Smooth Entropy Transfer of Quantum Gravity Information Processing
2014, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT); General Relativity and Quantum Cosmology (gr-qc); High Energy Physics - Theory (hep-th)
Download: arXiv:1403.6717

L. Gyongyosi. Singular Layer Transmission for Continuous-Variable Quantum Key Distribution
2014, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1402.5110

L. Gyongyosi, S. Imre. Theory of Quantum Gravity Information Processing
2014, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT); General Relativity and Quantum Cosmology (gr-qc); High Energy Physics - Theory (hep-th)
Download: arXiv:1401.6706

L. Gyongyosi, S. Imre. Multiple Access Multicarrier Continuous-Variable Quantum Key Distribution
2013, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1312.3614

L. Gyongyosi. A Statistical Model of Information Evaporation of Perfectly Reflecting Black Holes
2013, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT); General Relativity and Quantum Cosmology (gr-qc); High Energy Physics - Theory (hep-th)
Download: arXiv:1311.3598

L. Gyongyosi. Quantum Imaging of High-Dimensional Hilbert Spaces with Radon Transform
2013, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1310.8347

L. Gyongyosi. Adaptive Multicarrier Quadrature Division Modulation for Continuous-Variable Quantum Key Distribution
2013, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1310.1608

L. Gyongyosi. Low-Dimensional Reconciliation for Continuous-Variable Quantum Key Distribution
2013, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1308.1391

L. Gyongyosi. The Private Classical Capacity of a Partially Degradable Quantum Channel
2013, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download:  arXiv:1305.5970

L. Gyongyosi. The Structure and Quantum Capacity of a Partially Degradable Quantum Channel
2013, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1304.5666

L. Gyongyosi. Quantum Information Transmission over a Partially Degradable Channel
2013, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1303.0606

L. Gyongyosi. The Correlation Conversion Property of Quantum Channels
2013, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1302.3118

L. Gyongyosi. Polaractivation of Hidden Private Classical Capacity Region of Quantum Channels
2013, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1302.3114

L. Gyongyosi, S. Imre. Concatenated Capacity-Achieving Polar Codes for Optical Quantum Channels
2012, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1302.3110

L. Gyongyosi, S. Imre. Properties of the Quantum Channel
2012, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1208.1270

L. Gyongyosi, S. Imre. Private Quantum Coding for Quantum Relay Networks
2012, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1208.0661

L. Gyongyosi, S. Imre. Pilot Quantum Error Correction for Global-Scale Quantum Communications
2012, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1207.4502

L. Gyongyosi, S. Imre. Algorithmic Superactivation of Asymptotic Quantum Capacity of Zero-Capacity Quantum Channels
2012, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1207.4491

L. Gyongyosi, S. Imre. Information Geometric Security Analysis of Differential Phase Shift Quantum Key Distribution Protocol
2012, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1207.4467

L. Gyongyosi, S. Imre. An Improvement in Quantum Fourier Transform
2012, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1207.4464

L. Gyongyosi, S. Imre. A Quantum Copy-Protection Scheme with Authentication
2012, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download:  arXiv:1207.4462

S. Imre, L. Gyongyosi. Quantum-assisted and Quantum-based Solutions in Wireless Systems
2012, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1206.5996

L. Gyongyosi. Information Geometric Superactivation of Asymptotic Quantum Capacity and Classical Zero-Error Capacity of Zero-Capacity Quantum Channels
PhD. Thesis, Budapest University of Technology and Economics, 2013, 392 pages, 4 tables, 128 figures, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1206.5980

L. Gyongyosi, S. Imre. Quasi-Superactivation of Classical Capacity of Zero-Capacity Quantum Channels
2012, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1206.5693

L. Gyongyosi, S. Imre. Superactivation of Quantum Channels is Limited by the Quantum Relative Entropy Function
2012, Subjects: Quantum Physics (quant-ph); Information Theory (cs.IT)
Download: arXiv:1206.5691

Professional Service

Program committee, IEEE International Conference on Communications 2025, Selected Areas in Communications: Quantum Communications and Information Technology (IEEE ICC'25 - SAC-11 QCIT), IEEE, 2025.

Program committee, IEEE International Conference on Communications 2024, Selected Areas in Communications: Quantum Communications and Information Technology (IEEE ICC'24 - SAC-11 QCIT), IEEE, 2024.

Program committee, IEEE Global Communications Conference (IEEE Globecom) 2023, Selected Areas in Communications: Quantum Communications and Computing, IEEE, 2023.

Program committee, IEEE International Conference on Communications 2023; Selected Areas in Communications: Quantum Communications and Information Technology (IEEE ICC'23 - SAC-11 QCIT), IEEE, 2023.

Program committee, IEEE Global Communications Conference (IEEE Globecom) 2022, Quantum Communications and Information Technology (QCIT), IEEE, 2022.

Program committee, IEEE International Conference on Communications (IEEE ICC) 2022, Quantum Communications and Computing, IEEE, 2022.

Program committee, IEEE International Conference on Communications (IEEE ICC) 2021, Quantum Communications and Computing, IEEE, 2021.

Program committee, IEEE Global Communications Conference (IEEE Globecom) 2020, Quantum Communications and Information Technology (QCIT), IEEE, 2020.

Program committee, IEEE Global Communications Conference (IEEE Globecom) 2019, Quantum Communications and Information Technology (QCIT), IEEE, 2019.

Program committee, IEEE Global Communications Conference (IEEE Globecom) 2018, Quantum Communications and Information Technology (QCIT), IEEE, 2018.

Program committee, QuantumComm - The Improving Quantum World, 2nd International ICST Conference on Quantum Communication and Quantum Networking, 2012.

Editor

Associate Editor, Quantum Communication, Frontiers in Quantum Science and Technology, Frontiers, 2021-Present.

Editor, Quantum Internet, Internet Technology Letters, Wiley, ISSN:2476-1508, 2019-Present.

Referee

IEEE Communications Magazine, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Communications Surveys and Tutorials, Institute of Electrical and Electronics Engineers (IEEE)

IEEE/OSA Journal of Lightwave Technology, ISSN: 0733-8724 (IEEE)

IEEE Photonics Technology Letters, ISSN: 1041-1135, (IEEE)

IEEE Network, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Communications Letters, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Transactions on Communications, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Transactions on Network and Service Management, Institute of Electrical and Electronics Engineers (IEEE)

IEEE/ACM Transactions on Networking, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Transactions on Control of Network Systems, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Transactions on Neural Networks and Learning Systems, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Transactions on Information Forensics & Security, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Transactions on Computers, IEEE Computer Society, ISSN 0018-9340.

IEEE Transactions on Vehicular Technology, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Transactions on Evolutionary Computation, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Transactions on Cybernetics, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Transactions on Quantum Engineering, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Transactions on Network Science and Engineering, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Transactions on VLSI Systems, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Journal on Selected Areas in Communications, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Photonics Journal, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Access, Institute of Electrical and Electronics Engineers (IEEE)

IEEE IET Networks, ISSN: 2047-4954, Institute of Electrical and Electronics Engineers (IEEE)

IEEE Sensors Letters, ISSN: 2475-1472, Institute of Electrical and Electronics Engineers (IEEE)

IEEE International Symposium on Information Theory (IEEE ISIT)

IEEE Workshops on Information Theory (IEEE)

IEEE International Workshop on Quantum Communications for Future Networks (IEEE QCFN)

IEEE Workshops on Quantum Communications and Information Technology, IEEE Global Communications Conference, (IEEE)

ACM Computing Surveys, ACM, ISSN: 0360-0300 (print); 1557-7341 (web)

Nature Communications, Nature

npj Quantum Information, Nature, ISSN 2056-6387

Communications Physics, Nature

Science Advances, American Association for the Advancement of Science, (AAAS), ISSN 2375-2548

Scientific Reports, Nature Publishing Group (NPG)

Quantum Information Processing, Springer Nature, ISSN: 1570-0755, ISSN: 1573-1332

Proceedings of the Royal Society A: Mathematical, Physical & Engineering Sciences, Royal Society, ISSN 1364-5021 (print), 1471-2946 (web)

Advanced Quantum Technologies, ISSN: 2511-9044, Wiley

EPJ Quantum Technology, ISSN: 2196-0763, Springer

Journal of Optics, IOP, ISSN: 2040-8978, Online ISSN: 2040-8986

Frontiers of Physics, Springer, ISSN: 2095-0462, 2095-0470

Optical and Quantum Electronics, Springer, ISSN: 1572-817X, 0030-4077

Quantum Science and Technology, IOP, Online ISSN: 2058-9565

IET Quantum Communication, ISSN 2632-8925

Measurement, Elsevier, ISSN: 0263-2241 (print); 1873-412X (web)

Chaos, Solitons and Fractals, Elsevier, ISSN: 0960-0779.

International Journal of Theoretical Physics, Springer, ISSN: 0020-7748; 1572-9575

Results in Physics, Elsevier, ISSN: 2211-3797

Applied Physics B, Springer, ISSN: 0946-2171 (print); 1432-0649 (web)

Annalen der Physik, Wiley-VCH, ISSN: 0003-3804 (print); 1521-3889 (web)

The European Physical Journal Plus, Springer, ISSN: 2190-5444

AIMS Mathematics, AIMS, ISSN: 2473-6988

Mathematical Reviews, AMS, ISSN: 0025-5629

Soft Computing, Springer, ISSN: 1432-7643 (print version), ISSN: 1433-7479 (electronic version)

Quantum Machine Intelligence, Springer, ISSN 2524-4914

The Journal of Supercomputing, Springer, ISSN: 0920-8542 (print); 1573-0484 (web)

Evolutionary Intelligence, Springer, ISSN 1864-5909, 1864-5917

Physica Scripta, Institute of Physics (IOP), Online ISSN: 1402-4896 Print ISSN: 0031-8949

Entropy, MDPI, ISSN 1099-4300

Universe, MDPI, ISSN: 2218-1997

Symmetry, MDPI, ISSN: 2073-8994

Information, MDPI, ISSN 2078-2489

Patterns, Cell Press, ISSN 2666-3899

Natural Computing, Springer Nature, ISSN: 1567-7818, ISSN: 1572-9796.

Journal of Computational Electronics, Springer, ISSN 1572-8137, 1569-8025

Information Sciences, Elsevier, ISSN: 0020-0255

Journal of Symbolic Computation, Elsevier, ISSN: 0747-7171

Computers & Electrical Engineering, Elsevier Ltd., ISSN: 0045-7906.

SN Applied Sciences, Springer, ISSN: 2523-3971

Computer Methods and Programs in Biomedicine, Elsevier, ISSN: 0169-2607

Connection Science, Taylor and Francis

Vehicular Communications, Elsevier, ISSN: 2214-2096

International Journal of Communication Systems, ISSN: 1099-1131, John Wiley & Sons, Ltd.

Security and Communication Networks, John Wiley & Sons, Ltd.

Cybernetics and Systems, Taylor and Francis, ISSN: 0196-9722 (print); 1087-6553 (web)

Canadian Journal of Physics, ISSN: 1208-6045; 0008-4204

Discover Computing, Springer

SPIE Optical Engineering, ISSN: 0091-3286, E-ISSN: 1560-2303; USA

Springer Book Projects in Quantum Information, Springer, New York, NY 10013, USA

Applied Sciences Book Series in Quantum Information, Springer, New York, NY 10013, USA

Elsevier Book Projects in Quantum Information, Elsevier, USA

Infocommunications Journal, HTE

European Research Council (ERC), Research Projects in Quantum Information

European Science Foundation (ESF), Quantum Networking

Einstein Foundation, Berlin, Research Projects in Quantum Information

Swiss National Science Foundation (SNSF), Bern, Research Projects in Quantum Information

Research Projects in Quantum Technology, National Growth Fund, Dutch Research Council (NWO)

OTKA Scientific Research Fund, NKFI

Membership

Institute of Electrical and Electronics Engineers (IEEE)

American Physical Society (APS)

APS Division of Quantum Information (DQI), American Physical Society

Institute of Physics (IOP)

Optical Society of America (OSA)

Society of Photo-Optical Instrumentation Engineers (SPIE)

Lecturer

Quantum Infocommunications and Applications (BME-VIHIAV13), BME-HIT, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics

Quantum Computing and Communications (BME-VIHIMA14), BME-HIT, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics

Introduction to Quantum Computing and Communications (BME-VIHIAV06), BME-HIT, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics

Awards

BME-TOP100 Best Researcher Award, 1st place (awarded every five years), Top 1 researcher in the 5-year period of 2018-2023, Budapest University of Technology and Economics, 2023.

Research in Quantum Information and Communication, Ericsson, Pro Progressio, Hungary, 2022.

MTA Premium Postdoctoral Research Program 2019, Hungarian Academy of Sciences, 2019.

OSA Jean Bennett Memorial Award 2013, The Optical Society of America, Orlando, Florida, USA, 2013.

SPIE 2013 Quantum Information and Computation Award, SPIE Defense, Security, and Sensing 2013, USA, 2013.

APS PhD Student Grant Award 2013, The American Physical Society (APS), The University of North Carolina at Charlotte (UNCC), USA, 2013.

SPIE Photonics West OPTO 2013 Award, Advances in Photonics of Quantum Computing, Memory, and Communication, San Francisco, California, USA, 2013.

Incubic/Milton Chang Award, The Optical Society of America, Rochester, New York, USA, 2012.

BME PhD Researcher Fellowship 2012, Budapest University of Technology and Economics, 2012.

PhD Student Grant Award of Columbia University, New York, USA, 2012.

PhD Student Grant Award of QCRYPT 2012, The 2nd Annual Conference on Quantum Cryptography (Centre for Quantum Technologies), National University of Singapore, Singapore, 2012.

PhD Student Grant Award of APS DAMOP 2012 (DAMOP12), APS Division of Atomic, Molecular, and Optical Physics, American Physical Society (APS), California, USA, 2012.

PhD Student Grant Award of Quantum Information Processing 2012 (QIP2012), University of Montreal, Canada, 2012.

PhD Student Grant Award of The Second International Conference on Quantum Error Correction (QEC2011), University of Southern California (USC), USA, 2011.

PhD Student Grant Award of Stanford University, Stanford Optical Society, USA, 2011.

PhD Candidate Scholarship 2011, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, 2011.

BME PhD Researcher Fellowship 2011, Budapest University of Technology and Economics, 2011.

PhD Student Grant Award of University of Arizona, Optical Society of America (OSA), USA, 2010.

BME PhD Researcher Fellowship 2010, Budapest University of Technology and Economics, 2010.

"SANDOR CSIBI" PhD Researcher Scholarship 2010, Pro Progressio, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, 2010.

BEST PAPER AWARD 2010 from Harvard University, Cambridge, USA, 2010.

BEST PAPER AWARD 2009, FUTURE COMPUTING, The First International Conference on Future Computational Technologies and Applications, 2009.

BEST PAPER AWARD 2009 - "POLLAK-VIRAG" - from the Scientific Association for Infocommunication (Hungary), 2009.

Republican Scholarship, Budapest University of Technology and Economics, 2008.

Professional Scholarship, Faculty of Electrical Engineering and Informatics, BME (Level A, highest category), 2008.

University Professional Scholarship, BME (Level A, highest category), 2007.

Links

Prof. Sandor Imre, Head of Department, Department of Networked Systems and Services
Dr. Laszlo Bacsardi, Department of Networked Systems and Services, BME
Quantum Computing and Communications, Department of Networked Systems and Services, BME
Fundamental Problems in Quantum Physics

Quantum A.I. - Research at Google
Quantum computing at IBM
Quantum computing at Microsoft
Quantum computing at Intel
Bell Labs, USA
Oak Ridge National Laboratory, USA
Gordon Research Seminar, USA
Center for Distributed Quantum Information, U.S. Army Research Laboratory (ARL)

Center for Optoelectronics and Optical Communications, The University of North Carolina at Charlotte, USA
Laboratory for Quantum Photonics, Columbia University, USA
Quantum Information Science Group, National University of Singapore, Singapore
Vienna Center for Quantum Science and Technology, Vienna University of Technology, Vienna, Austria
School of Computer Science, Physics and Mathematics, Linnaeus University, Växjö, Sweden
Quantum Information Group, University of Tokyo, Tokyo, Japan
Quantum Information Science Theory Group, National Institute of Informatics, Tokyo, Japan
National Institute of Informatics, Tokyo, Japan
Department of Applied Physics, Fukui University, Fukui, Japan
NASA Ames Quantum Laboratory, Moffett Field, California, USA
Quantum Information Science & Technology Center, University of Southern California, USA
Quantum Information Lab., University of Montreal, Quebec, Canada
Stanford Photonics Research Center, Stanford University, USA
Department of Mathematics, Massachusetts Institute of Technology, USA
Department of Physics, Massachusetts Institute of Technology, USA
Clarendon Laboratory, University of Oxford, Oxford, UK
Centre for Quantum Computation, Oxford and Cambridge, UK
College of Optical Science, University of Arizona, Arizona, USA
Department of Physics at Harvard University, Harvard University, USA
Quantum Computing Technology Centre, University of Queensland, Australia
Quantum Computing at University of Ottawa, Ottawa, Canada
Quantum Computation at UC Berkeley, University of California at Berkeley, USA
Princeton Center for Theoretical Science, University of Princeton, Princeton, USA
Quantum Control Group, University of Southampton, Southampton, UK
Quantum Technology at Nanyang Technological University, Singapore
Stonehill College, USA
Quantum Information Center, The University of Texas at Austin, USA

Computational Information Geometry
Information Geometry Blog
Frank Nielsen's Channel