Mathematical models Archives - IEEE Transactions on Quantum Engineering

Quantum Wavelength-Division Multiplexing and Multiple-Access Communication Systems and Networks: Advanced Applications

May 12, 2025Marzieh Bathaee; Mohammad Rezai; Jawad A. SalehiQuantum Networking & Communications, UncategorizedCommunication systems, Mathematical models, Network topology, Optical fiber amplifiers, Optical fiber networks, Quantum networks, Receivers, Stars, Topology, WDM networks

Abstract: A cost-effective global quantum Internet may be developed using the existing communication infrastructure. This article examines the quantum version of three conventional wavelength-division-multiplexing and multiple-access (WDM) communication systems and networks. They are Lambdanet-based broadcast WDM networks, quantum routers based on a waveguide grating router, and fiber-to-the-quantum nodes that are fed by two opposing and […]

Modeling and Performance Evaluation of Hybrid Classical–Quantum Serverless Computing Platforms

May 6, 2025Claudio CicconettiQuantum ComputingComputational modeling, Containers, Delays, Logic gates, Mathematical models, Numerical models, Optimization, Quantum circuit, Quantum computing, Serverless computing

Abstract: While quantum computing technologies are evolving toward achieving full maturity, hybrid algorithms, such as variational quantum computing, are already emerging as valid candidates to solve practical problems in fields, such as chemistry and operations research. This situation calls for a tighter and better integration of classical and quantum computing infrastructures to improve efficiency and […]

Emulation of Density Matrix Dynamics With Classical Analog Circuits

March 19, 2025Anthony J. Cressman, Rahul SarpeshkarQuantum ComputingAnalog circuits, Capacitors, Emulation, Mathematical models, Noise, Noise measurement, Quantum computing, Quantum system, Vectors, Voltage

Abstract: Analog circuits have emerged as a valuable quantum emulation and simulation platform. Specifically, they have been experimentally shown to excel in emulating coherent state vector dynamics and motifs of quantum circuits, such as the quantum Fourier transform, tensor product superpositions, two-level systems such as Josephson junctions, and nuclear magnetic resonance state dynamics, all on […]

Explicit Quantum Circuit for Simulating the Advection–Diffusion–Reaction Dynamics

February 21, 2025Claudio Sanavio, Enea Mauri, Sauro SucciQuantum ComputingComputational fluid dynamics, Convergence, Encoding, Logic gates, Logistics, Mathematical models, Polynomials, Quantum algorithm, Quantum circuit, Qubit

We assess the convergence of the Carleman linearization of advection–diffusion–reaction (ADR) equations with a logistic nonlinearity. It is shown that five Carleman iterates provide a satisfactory approximation of the original ADR across a broad range of parameters and strength of nonlinearity. To assess the feasibility of a quantum algorithm based on this linearization, we analyze […]

Improving Urban Traffic Mobility via a Versatile Quantum Annealing Model

September 5, 2023Andrea MarchesinQuantum EngineeringAnnealing, Computational modeling, Mathematical models, Optimization, Quantum annealing, Quantum mechanics, Roads

The growth of cities and the resulting increase in vehicular traffic pose significant challenges to the environment and citizens’ quality of life. To address these challenges, a new algorithm has been proposed that leverages the quantum annealing paradigm and D-wave’s machines to optimize the control of traffic lights in cities. The algorithm considers traffic information […]

Analysis of the Vehicle Routing Problem Solved via Hybrid Quantum Algorithms in the Presence of Noisy Channels

August 10, 2023Nishikanta MohantyQuantum ComputingApproximation algorithms, Mathematical models, Minimization, Optimization, Quantum computing, Software, Stationary state

The vehicle routing problem (VRP) is an NP-hard optimization problem that has been an interest of research for decades in science and industry. The objective is to plan routes of vehicles to deliver goods to a fixed number of customers with optimal efficiency. Classical tools and methods provide good approximations to reach the optimal global […]

Extensible Gauge-Invariant FDM With Spin–Orbit Coupling for Quantum Devices

June 14, 2023John E. TiessenEnabling TechnologiesFinite difference methods, HEMTs, Magnetic confinement, Mathematical models, MODFETs, Quantum system, Qubit

We present a novel derivation and implementation of the finite-difference method (FDM) that is gauge invariant and incorporates spin–orbit coupling for the study of quantum systems. This version of FDM is meant to assist in the design and simulation of quantum devices that utilize multiple internal degrees of freedom (e.g., spin) by providing a way […]

Prediction of Solar Irradiance One Hour Ahead Based on Quantum Long Short-Term Memory Network

June 14, 2023Yunjun YuQuantum ComputingAtmospheric modeling, Computational modeling, Data models, Feature extraction, Forecasting, Mathematical models, Predictive models

The short-term forecasting of photovoltaic (PV) power generation ensures the scheduling and dispatching of electrical power, helps design a PV-integrated energy management system, and enhances the security of grid operation. However, due to the randomness of solar energy, the output of the PV system will fluctuate, which will affect the safe operation of the grid. […]

Efficient Quantum State Preparation for the Cauchy Distribution Based on Piecewise Arithmetic

November 2, 2022Ethan T. WangOpen Access, Quantum ComputingApproximation algorithms, Distribution functions, Logic gates, Mathematical models, Monte Carlo methods, Qubit, Registers

The benefits of the quantum Monte Carlo algorithm heavily rely on the efficiency of the superposition state preparation. So far, most reported Monte Carlo algorithms use the Grover–Rudolph state preparation method, which is suitable for efficiently integrable distribution functions. Consequently, most reported works are based on log-concave distributions, such as normal distributions. However, non-log-concave distributions […]