Quafu-Qcover:Explore combinatorial optimization problems on cloud-based quantum computers

We introduce Quafu-Qcover,an open-source cloud-based software package developed for solving combinatorial optimization problems using quantum simulators and hardware backends.Quafu-Qcover provides a standardized and comprehensive workflow that utilizes the quantum approximate optimization algorithm(QAOA).It facilitates the automatic conversion of the original problem into a quadratic unconstrained binary optimization(QUBO)model and its corresponding Ising model,which can be subsequently transformed into a weight graph.The core of Qcover relies on a graph decomposition-based classical algorithm,which efficiently derives the optimal parameters for the shallow QAOA circuit.Quafu-Qcover incorporates a dedicated compiler capable of translating QAOA circuits into physical quantum circuits that can be executed on Quafu cloud quantum computers.Compared to a general-purpose compiler,our compiler demonstrates the ability to generate shorter circuit depths,while also exhibiting superior speed performance.Additionally,the Qcover compiler has the capability to dynamically create a library of qubits coupling substructures in real-time,utilizing the most recent calibration data from the superconducting quantum devices.This ensures that computational tasks can be assigned to connected physical qubits with the highest fidelity.The Quafu-Qcover allows us to retrieve quantum computing sampling results using a task ID at any time,enabling asynchronous processing.Moreover,it incorporates modules for results preprocessing and visualization,facilitating an intuitive display of solutions for combinatorial optimization problems.We hope that Quafu-Qcover can serve as an instructive illustration for how to explore application problems on the Quafu cloud quantum computers.

Quantum software framework： a tentative study

In this paper we conduct a tentative study on the requirements and the structure for a quantum computer at the software level. From the software point of view, we describe the methodology used to minimize the decoherence. We con- struct the quantum instruction set for the higher-level computation. We also study the criteria for designing the quantum programming languages.

Quantum Algorithm of Imperfect KB Self-organization. Pt II: Robotic Control with Remote Knowledge Base Exchange

The technology of knowledge base remote design of the smart fuzzy con­trollers with the application of the"Soft/quantum computing optimizer"toolkit software developed.The possibility of the transmission and commu­nication the knowledge base using remote connection to the control object considered.Transmission and communication of the fuzzy controller’s knowledge bases implemented through the remote connection with the control object in the online mode apply the Bluetooth or WiFi technologies.Remote transmission of knowledge bases allows designing many different built-in intelligent controllers to implement a variety of control strategies under conditions of uncertainty and risk.As examples,two different models of robots described(mobile manipulator and(“cart-pole”system)inverted pendulum).A comparison of the control quality between fuzzy controllers and quantum fuzzy controller in various control modes is presented.The ability to connect and work with a physical model of control object without using than mathematical model demonstrated.The implemented technol­ogy of knowledge base design sharing in a swarm of intelligent robots with quantum controllers.It allows to achieve the goal of control and to gain additional knowledge by creating a new quantum hidden information source based on the synergetic effect of combining knowledge.Develop­ment and implementation of intelligent robust controller’s prototype for the intelligent quantum control system of mega-science project NICA(at the first stage for the cooling system of superconducted magnets)is discussed.The results of the experiments demonstrate the possibility of the ensured achievement of the control goal of a group of robots using soft/quantum computing technologies in the design of knowledge bases of smart fuzzy controllers in quantum intelligent control systems.The developed software toolkit allows to design and setup complex ill-defined and weakly formal­ized technical systems on line.

A New Path to Create Solutions for Quantum Annealing Problems

Quantum computing has already become a technology to be used by large companies in finance, distribution, health care, chemistry, etc. Among the different approaches, quantum annealing is one of the most promising in the short term. However, software development platforms do not offer user-friendly interfaces for the definition of annealing problems. In this paper we present a solution to this problem: QPath®’s Annealer Compositor that facilitates the definition and execution of annealing algorithms in either quantum annealing or digital annealing computers. An example based on a nurse work schedule is used for illustrating this special interface.