Noisy-intermediate-scale quantum power system state estimation

Quantum power system state estimation(QPSSE)offers an inspiring direction for tackling the challenge of state estimation through quantum computing.Nevertheless,the current bottlenecks originate from the scarcity of practical and scalable QPSSE methodologies in the noisy intermediate-scale quantum(NISQ)era.This paper devises a NISQ−QPSSE algorithm that facilitates state estimation on real NISQ devices.Our new contributions include:(1)A variational quantum circuit(VQC)-based QPSSE formulation that empowers QPSSE analysis utilizing shallow-depth quantum circuits;(2)A variational quantum linear solver(VQLS)-based QPSSE solver integrating QPSSE iterations with VQC optimization;(3)An advanced NISQ-compatible QPSSE methodology for tackling the measurement and coefficient matrix issues on real quantum computers;(4)A noise-resilient method to alleviate the detrimental effects of noise disturbances.The encouraging test results on the simulator and real-scale systems affirm the precision,universal-ity,and scalability of our QPSSE algorithm and demonstrate the vast potential of QPSSE in the thriving NISQ era.

Noise-resilient quantum power flow

Quantum power flow(QPF)offers an inspiring direction for overcoming the computation challenge of power flow through quantum computing.However,the practical implementation of existing QPF algorithms in today’s noisy-intermediate-scale quantum(NISQ)era remains limited because of their sensitivity to noise.This paper establishes an NISQ-QPF algorithm that enables power flow computation on noisy quantum devices.The main contributions include:(1)a variational quantum circuit(VQC)-based alternating current(AC)power flow formulation,which enables QPF using short-depth quantum circuits;(2)NISQ-compatible QPF solvers based on the variational quantum linear solver(VQLS)and modified fast decoupled power flow;and(3)an error-resilient QPF scheme to relieve the QPF iteration deviations caused by noise;(3)a practical NISQ-QPF framework for implementable and reliable power flow analysis on noisy quantum machines.Extensive simulation tests validate the accuracy and generality of NISQ-QPF for solving practical power flow on IBM’s real,noisy quantum computers.

Algorithm for simulating ocean circulation on a quantum computer

The accurate and efficient simulation of ocean circulation is a fundamental topic in marine science;however,it is also a well-known and dauntingly difficult problem that requires solving nonlinear partial differential equations with multiple variables.In this paper,we present for the first time an algorithm for simulating ocean circulation on a quantum computer to achieve a computational speedup.Our approach begins with using primitive equations describing the ocean dynamics and then discretizing these equations in time and space.It results in several linear system of equations(LSE)with sparse coefficient matrices.We solve these sparse LSE using the variational quantum linear solver that enables the present algorithm to run easily on near-term quantum computers.Additionally,we develop a scheme for manipulating the data flow in the algorithm based on the quantum random access memory and l∞norm tomography technique.The efficiency of our algorithm is verified using multiple platforms,including MATLAB,a quantum virtual simulator,and a real quantum computer.The impact of the number of shots and the noise of quantum gates on the solution accuracy is also discussed.Our findings demonstrate that error mitigation techniques can efficiently improve the solution accuracy.With the rapid advancements in quantum computing,this work represents an important first step toward solving the challenging problem of simulating ocean circulation using quantum computers.