26、Quantum Software Development with QuantumPath®:Unleashing the Power of Quantum Computing

Quantum Software Development with QuantumPath®:Unleashing the Power of Quantum Computing

1. Introduction

Quantum theory is a revolutionary physics theory that describes the behavior of matter at sub - atomic levels. Quantum computers, based on principles like superposition and entanglement, aim to exponentially boost computational power. This has led to interesting developments in various fields such as cryptography, artificial intelligence, and communications.

However, developing quantum software currently faces numerous challenges. There is a wide variety of quantum programming languages, development environments, simulators, and hardware. Moreover, there is no established methodology for high - quality quantum software development.

QuantumPath® (QPath®) is a quantum software development platform designed to support the design, implementation, and execution of quantum software applications.

2. QPath® Principles and Functionalities

QPath® is built on several key principles:
- Agnosticism : Supports both quantum gate - based and annealing technology.
- Extensibility : Can adapt to the continuous research and evolution of quantum technologies through a well - designed extension model.
- Integration : Enables the integration of quantum/classical (hybrid) information systems.
- Independency : Follows the “write once, run everywhere” principle, masking the complexities of different environments.
- Optimization : Collects and analyzes stored telemetry.
- Scalability : Can be deployed on multiple servers to accommodate user and process growth.
- Security : Provides secure access to service layers and protects system assets.
- Software engineering : Supports the quantum software life cycle and its engineering.
- Usability : Helps visually design quantum assets, define requirements, and explore results without worrying about quantum computer languages.

QPath® is composed of two large functional units:
- CORE Modules : The core of the QuantumPath platform, which can manage solutions independent of quantum technology with the help of general - purpose tools.
- The APPs platform : Integrates with the CORE modules and simplifies the management of hybrid software project life cycles for development teams.

2.1 Management of Solutions and Their Assets

QPath® includes all the necessary elements for a “quantum application,” such as the application solution and its relationship to the quantum execution context, quantum circuits, direct code units, intermediate language treatment of assets, and main flows for algorithm coordination and execution control. All data in the cloud system is encrypted from origin to storage.

2.2 Tools for the Design of Quantum Assets
  • Circuit Editor : Allows the graphical design of quantum gate circuits through a web UI based on the Quirk Quantum Circuit Simulator. It supports drag - and - drop and generates an intermediate QpIL language for running algorithms on any quantum gate hardware.
  • Annealer Compositor : A high - level tool for graphically modeling optimization problems. The design is simplified to four elements:
    • Parameters : Variables with constant values for parameterizing problem properties.
    • Auxiliary data : Arrays of data used in problem rules.
    • Classes : Define different types of real variables in the problem.
    • Rules : Model the objective function and constraints of the problem.
      After editing, it compiles the circuit and generates code in annealing meta - language.
  • Flow Editor : Coordinates the execution of circuits and other elements in an application.
  • Direct Code Editor : Allows users to create code for specific hardware. It simplifies the process by letting users write code inside a module abstraction and provides managed items for integration into the QPath® pipeline. The defined code can be encapsulated as a standard circuit.
2.3 Connection Points and qSOA

QPath® enables the interconnection of quantum applications in a classic solution ecosystem. It provides a REST API service layer, allowing classic applications to easily consume quantum algorithms stored in the system or create new ones using QPath® IL. For example, the following Connection Point checks the completion status and outcome of a job token:

(/api/connectionPoint/GetQuantumExecutionResponse/jobtoken/idSolution/idFlow)
HTTP GET HEADERS
content - type: application/json
Authorization: Bearer tokenJWT
RESPONSE
{
    "ExitCode": "OK",
    "ExitMessage": null,
    "ExecutionData": {
        "Solution": "WEBINARAnneal",
        "Flow": "BoxFlows",
        "Device": "dwave_ExactSolver_simulator",
        "Histogram": "histogram struct ",
        "Duration": 157226789
    }
}

QPath® supports the qSOA (Quantum Service Oriented Architecture) based on connection points, which simplifies the integration of quantum services into classical systems.

2.4 Enterprise Backend

The backend is responsible for the overall operation of the platform. It is designed with security, high availability, load balancing, and asynchronous customer processing in mind. It manages connections to quantum simulators and computers, collects telemetry, and provides knowledge and automatic assistance. QPath® allows users to work with various quantum technologies from different providers and third - party simulators.

3. QPath® Advantages

QPath® offers several advantages:
- Facilitates Quantum Workforce Development : The shortage of specialized workforce is a major obstacle in the quantum computing industry. QPath® simplifies the development of quantum software, enabling engineers and programmers without “universal” skills to work on quantum projects. It supports multidisciplinary teams and focuses on the functional knowledge required for quantum solutions in different fields. Additionally, QPath® developers have access to aQuantum Knowledge, a portal with useful resources.
- Solves the Quality Problems of Quantum Computing Platforms :
| Quality Problem | How QPath® Solves It |
| — | — |
| Lower level of programming abstractions | QPath® is agnostic about quantum programming languages and supports visual designers and the Annealer Compositor. |
| Platform heterogeneity | Provides tools for development teams to focus on solutions without worrying about platform specificities. |
| Remote software development and deployment | Offers a complete set of tools for asset design, construction, testing, and execution. |
| Dependency on known quantum algorithms | Supports the creation, testing, implementation, and reuse of quantum algorithms, and has extensibility for new connectors. |
| Limited portability of software | Allows automatic lifecycle management from model to results, following the “write once, run everywhere” principle. |
| Lack of native quantum operating system | The enterprise backend is designed with security, high availability, load balancing, and asynchronous processing. |
| Fundamentally different programming model | Supports the integration of hybrid software and simplifies the management of hybrid project life cycles. |

4. Example of Quantum Development with QPath®

Let’s take the example of adding a simple QRNG (Quantum Random Number Generator) into a Navision data form using a pre - configured quantum provider in the NAV environment.
The steps are as follows:
1. Define the solution and assets in QPath® .
2. Define the QNRG using the circuit editor .
3. Compose the corresponding flow .
4. Execute the QNRG and select different quantum machines to explore the results .
5. Extend Navision using the qSOA REST API .
6. Use the Navision QPath Setup Dialog (custom NAV extensions developed) .
7. Validate and seal customer data with hash using the QRNG numbers obtained. Generate a hash for validated and sealed customers using a developed protocol .

In this example, all executions are recorded with telemetry, and the results are applied to the NAV data. If the QRNG improves over time, Navision can execute the call more accurately without code modification.

The following mermaid flowchart shows the process:

graph LR
    A[Define solution and assets in QPath®] --> B[Define QNRG using circuit editor]
    B --> C[Compose corresponding flow]
    C --> D[Execute QNRG and explore results]
    D --> E[Extend Navision using qSOA REST API]
    E --> F[Use Navision QPath Setup Dialog]
    F --> G[Validate and seal customer data with hash]
    G --> H[Generate hash for validated customers with QRNG]

This example demonstrates how QPath® can be used in a practical scenario to integrate quantum computing into existing software systems.

Quantum Software Development with QuantumPath®:Unleashing the Power of Quantum Computing

5. In - depth Analysis of QPath®’s Impact on Quantum Software Development
5.1 Impact on Industry Adoption

The challenges in quantum software development have been a significant roadblock to the widespread adoption of quantum computing in industries. QPath® addresses these challenges head - on, making it more accessible for businesses to integrate quantum solutions into their existing workflows.

For example, in the finance industry, where complex risk analysis and portfolio optimization problems can benefit from quantum computing’s power, QPath® allows financial analysts and developers to work together more effectively. The platform’s agnosticism means that they can use different quantum technologies without having to learn multiple programming languages and platforms from scratch.

The following table shows some industries and the potential quantum applications that QPath® can facilitate:
| Industry | Quantum Application |
| — | — |
| Finance | Risk analysis, portfolio optimization |
| Healthcare | Drug discovery, genetic analysis |
| Logistics | Route optimization, supply chain management |
| Energy | Power grid optimization, resource allocation |

5.2 Impact on Research and Development

In the research community, QPath® provides a valuable tool for exploring new quantum algorithms and applications. The platform’s extensibility allows researchers to attach new connectors and experiment with emerging quantum technologies.

The flow editor in QPath® enables researchers to design complex quantum circuits and algorithms, which can then be executed on different quantum machines. This flexibility promotes innovation in quantum research, as researchers can quickly prototype and test new ideas without being limited by the specificities of a single quantum platform.

The following mermaid flowchart shows the research and development process using QPath®:

graph LR
    A[Define research problem] --> B[Design quantum algorithm in QPath®]
    B --> C[Select appropriate quantum technology]
    C --> D[Execute algorithm on QPath®]
    D --> E[Analyze results]
    E --> F{Is the result satisfactory?}
    F -- Yes --> G[Publish findings]
    F -- No --> B
6. Future - Proofing with QPath®
6.1 Adapting to Technological Advancements

Quantum technologies are evolving at a rapid pace. New quantum algorithms are being developed, and quantum hardware is becoming more powerful. QPath®’s design principles, such as extensibility and agnosticism, make it well - positioned to adapt to these changes.

As new quantum programming languages and platforms emerge, QPath® can incorporate them through its extension model. This ensures that users of QPath® can take advantage of the latest technological advancements without having to rewrite their existing quantum software.

6.2 Scaling for Growth

As the demand for quantum computing increases, QPath®’s scalability feature becomes crucial. The platform can be deployed on multiple servers to handle a growing number of users and processes. This means that businesses and research institutions can scale their quantum operations as needed, without experiencing performance bottlenecks.

The enterprise backend of QPath® is designed to manage this growth efficiently. It provides security, high availability, and load balancing, ensuring that the platform remains reliable even under heavy usage.

7. Conclusion

QuantumPath® (QPath®) is a powerful quantum software development platform that addresses the major challenges in quantum software development. Its design principles, such as agnosticism, extensibility, and integration, make it a versatile tool for both industry and research.

By facilitating quantum workforce development and solving the quality problems of quantum computing platforms, QPath® paves the way for the widespread adoption of quantum computing. The example of adding a QRNG to a Navision data form demonstrates how QPath® can be used in a practical scenario to integrate quantum computing into existing software systems.

As quantum technologies continue to evolve, QPath®’s ability to adapt and scale will ensure that it remains a valuable asset in the field of quantum software development. Whether you are a business looking to leverage quantum computing for competitive advantage or a researcher exploring new frontiers in quantum science, QPath® offers a comprehensive solution.

【无人车路径跟踪】基于神经网络的数据驱动迭代学习控制(ILC)算法,用于具有未知模型和重复任务的非线性单输入单输出(SISO)离散时间系统的无人车的路径跟踪(Matlab代码实现)内容概要:本文介绍了一种基于神经网络的数据驱动迭代学习控制(ILC)算法,用于解决具有未知模型和重复任务的非线性单输入单输出(SISO)离散时间系统的无人车路径跟踪问题,并提供了完整的Matlab代码实现。该方法无需精确系统模型,通过数据驱动方式结合神经网络逼近系统动态,利用迭代学习机制不断提升控制性能,从而实现高精度的路径跟踪控制。文档还列举了大量相关科研方向和技术应用案例,涵盖智能优化算法、机器学习、路径规划、电力系统等多个领域,展示了该技术在科研仿真中的广泛应用前景。; 适合人群:具备一定自动控制理论基础和Matlab编程能力的研究生、科研人员及从事无人车控制、智能算法开发的工程技术人员。; 使用场景及目标:①应用于无人车在重复任务下的高精度路径跟踪控制;②为缺乏精确数学模型的非线性系统提供有效的控制策略设计思路;③作为科研复现与算法验证的学习资源,推动数据驱动控制方法的研究与应用。; 阅读建议:建议读者结合Matlab代码深入理解算法实现细节,重点关注神经网络与ILC的结合机制,并尝试在不同仿真环境中进行参数调优与性能对比,以掌握数据驱动控制的核心思想与工程应用技巧。
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