Geometric programming for circuit optimization

Author(s):  
Stephen P. Boyd ◽  
Seung Jean Kim
2005 ◽  
Vol 53 (6) ◽  
pp. 899-932 ◽  
Author(s):  
Stephen P. Boyd ◽  
Seung-Jean Kim ◽  
Dinesh D. Patil ◽  
Mark A. Horowitz

2006 ◽  
Author(s):  
Daniel Lafond ◽  
Yves Lacouture ◽  
Guy Mineau

2017 ◽  
Vol E100.C (4) ◽  
pp. 407-415
Author(s):  
Minyoung YOON ◽  
Byungjoon KIM ◽  
Jintae KIM ◽  
Sangwook NAM

2021 ◽  
Vol 20 (7) ◽  
Author(s):  
Ismail Ghodsollahee ◽  
Zohreh Davarzani ◽  
Mariam Zomorodi ◽  
Paweł Pławiak ◽  
Monireh Houshmand ◽  
...  

AbstractAs quantum computation grows, the number of qubits involved in a given quantum computer increases. But due to the physical limitations in the number of qubits of a single quantum device, the computation should be performed in a distributed system. In this paper, a new model of quantum computation based on the matrix representation of quantum circuits is proposed. Then, using this model, we propose a novel approach for reducing the number of teleportations in a distributed quantum circuit. The proposed method consists of two phases: the pre-processing phase and the optimization phase. In the pre-processing phase, it considers the bi-partitioning of quantum circuits by Non-Dominated Sorting Genetic Algorithm (NSGA-III) to minimize the number of global gates and to distribute the quantum circuit into two balanced parts with equal number of qubits and minimum number of global gates. In the optimization phase, two heuristics named Heuristic I and Heuristic II are proposed to optimize the number of teleportations according to the partitioning obtained from the pre-processing phase. Finally, the proposed approach is evaluated on many benchmark quantum circuits. The results of these evaluations show an average of 22.16% improvement in the teleportation cost of the proposed approach compared to the existing works in the literature.


2013 ◽  
Vol 5 (3) ◽  
pp. 373-380
Author(s):  
Zeinab Kheiri ◽  
Faezeh Zahmatkesh ◽  
Bing-Yuan Cao

1980 ◽  
Vol 102 (3) ◽  
pp. 154-159 ◽  
Author(s):  
A. Lavi

A complex power system may be modeled by a system of inequalities representing the constraints imposed by the physical laws: heat transfer, energy balance, cycle efficiency and so forth. The nature of the resulting mathematical model is such that the terms contain complex expressions involving the design and operating variables of the process. With the addition of an objective function involving the cost of major system components, a multivariable nonlinear programming problem can be formulated. Seldom does the model lend itself to analytical treatment. This paper is concerned with a specific formulation and solution of nonlinear programming problems which arise in the design of ocean thermal energy conversion (OTEC) power plants. The technique used is geometric programming, GP. It is shown that GP serves as an excellent tool for system analysis because it provides sensitivity information essential to the designer.


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