The quantum hybrid algorithm has recently become a very promising and speedy method for solving larger-scale optimization problems in the noisy intermediate-scale quantum(NISQ)era.The unit commitment(UC)problem is a f...The quantum hybrid algorithm has recently become a very promising and speedy method for solving larger-scale optimization problems in the noisy intermediate-scale quantum(NISQ)era.The unit commitment(UC)problem is a fundamental problem in the field of power systems that aims to satisfy the power balance constraint with minimal cost.In this paper,we focus on the implementation of the UC solution using exact quantum algorithms based on the quantum neural network(QNN).This method is tested with a ten-unit system under the power balance constraint.In order to improve computing precision and reduce network complexity,we propose a knowledge-based partially connected quantum neural network(PCQNN).The results show that exact solutions can be obtained by the improved algorithm and that the depth of the quantum circuit can be reduced simultaneously.展开更多
Distributed quantum computation has gained extensive attention.In this paper,we consider a search problem that includes only one target item in the unordered database.After that,we propose a distributed exact Grover’...Distributed quantum computation has gained extensive attention.In this paper,we consider a search problem that includes only one target item in the unordered database.After that,we propose a distributed exact Grover’s algorithm(DEGA),which decomposes the original search problem into■n/2■parts.Specifically,(i)our algorithm is as exact as the modified version of Grover’s algorithm by Long,which means the theoretical probability of finding the objective state is 100%;(ii)the actual depth of our circuit is 8(n mod 2)+9,which is less than the circuit depths of the original and modified Grover’s algorithms,1+8■π/4√2^(n)■and 9+8■π/4√2^(n)-1/2■,respectively.It only depends on the parity of n,and it is not deepened as n increases;(iii)we provide particular situations of the DEGA on MindQuantum(a quantum software)to demonstrate the practicality and validity of our method.Since our circuit is shallower,it will be more resistant to the depolarization channel noise.展开更多
基金supported in part by the China Postdoctoral Science Foundation(Grant No.2023M740874)。
文摘The quantum hybrid algorithm has recently become a very promising and speedy method for solving larger-scale optimization problems in the noisy intermediate-scale quantum(NISQ)era.The unit commitment(UC)problem is a fundamental problem in the field of power systems that aims to satisfy the power balance constraint with minimal cost.In this paper,we focus on the implementation of the UC solution using exact quantum algorithms based on the quantum neural network(QNN).This method is tested with a ten-unit system under the power balance constraint.In order to improve computing precision and reduce network complexity,we propose a knowledge-based partially connected quantum neural network(PCQNN).The results show that exact solutions can be obtained by the improved algorithm and that the depth of the quantum circuit can be reduced simultaneously.
基金supported in part by the National Natural Science Foundation of China(Nos.61572532 and 61876195)the Natural Science Foundation of Guangdong Province of China(No.2017B030311011).
文摘Distributed quantum computation has gained extensive attention.In this paper,we consider a search problem that includes only one target item in the unordered database.After that,we propose a distributed exact Grover’s algorithm(DEGA),which decomposes the original search problem into■n/2■parts.Specifically,(i)our algorithm is as exact as the modified version of Grover’s algorithm by Long,which means the theoretical probability of finding the objective state is 100%;(ii)the actual depth of our circuit is 8(n mod 2)+9,which is less than the circuit depths of the original and modified Grover’s algorithms,1+8■π/4√2^(n)■and 9+8■π/4√2^(n)-1/2■,respectively.It only depends on the parity of n,and it is not deepened as n increases;(iii)we provide particular situations of the DEGA on MindQuantum(a quantum software)to demonstrate the practicality and validity of our method.Since our circuit is shallower,it will be more resistant to the depolarization channel noise.
