Optimal cloning of an undisclosed quantum algorithm

Weigang Wang

In order to solve the questions of the traditional quantum evolution algorithm, which are easy to fall into precocity and the slow convergence rate in the complex function optimizing, clone operator is introduced into the quantum evolution algorithm. The quantum clone algorithm which is a kind of new evolution algorithm is proposed. This algorithm both has drawn lessons from the highly effective parallelism of quantum evolution algorithm and has used the multiplicity of clone operator increasing population. It has enhanced the overall situation optimization ability in solving function optimization question. The simulation result indicates that the algorithm is superior to the traditional quantum evolution algorithm and has solved the optimization problem of complex function.

Dagmar Bruß, ARTUR K. EKERT, Chiara Macchiavello

Ting Gao, Fengli Yan, Zhi‐Xi Wang +1 more

Essam Halim Houssein, Mohamed A. Mahdy, Manal G. Eldin +3 more

Introduction: Quantum cloning operation, started with no-go theorem which proved that there is no capability to perform a cloning operation on an unknown quantum state, however, a number of trials proved that we can make approximate quantum state cloning that is still with some errors. Objectives: To the best of our knowledge, this paper is the first of its kind to attempt using meta-heuristic algorithm such as Adaptive Guided Differential Evolution (AGDE), to tackle the problem of quantum cloning circuit parameters to enhance the cloning fidelity. Methods: To investigate the effectiveness of the AGDE, the extensive experiments have demonstrated that the AGDE can achieve outstanding performance compared to other well-known meta-heuristics including; Enhanced LSHADE-SPACMA Algorithm (ELSHADE-SPACMA), Enhanced Differential Evolution algorithm with novel control parameter adaptation (PaDE), Improved Multi-operator Differential Evolution Algorithm (IMODE), Parameters with adaptive learning mechanism (PALM), QUasi-Affine TRansformation Evolutionary algorithm (QUATRE), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Cuckoo Search (CS), Bat-inspired Algorithm (BA), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA). Results: . Conclusion: Accordingly, the qualitative and quantitative measurements including average, standard deviation, convergence curves of the competitive algorithms over 30 independent runs, proved the superiority of AGDE to enhance the cloning fidelity.

Nicolau Orell, Sebastià

The Variational Quantum Cloning algorithm uses machine learning to obtain through optimization a circuit capable of generating approximate clones from unknown input quantum states. We adapt this algorithm to a boson sampling photonic platform formed exclusively by phase-shifters and beam-splitters, which is not universal but it still allows us to achieve quantum advantage. We have been able to obtain results through simulations reaching optimal fidelities for 1 to 2 universal cloning and also 1 to 2 and 1 to 3 phase-covariant cloning. This project demonstrates the capabilities of this type of photonic platforms and it can be used as a reference to adapt other variational algorithms to them.

Duong Bui, Kimmo Halunen, Nhan Nguyen +1 more