A quantum network comprises interconnected quantum servers capable of communication and collaboration for computational tasks. It is essential for quantum servers within this network to identify and authenticate one another. For instance, when a quantum server intends to execute a computational task on another machine, it becomes crucial for the quantum server to verify the authenticity of other quantum servers to maintain confidence in delegating computation. While several methods for fingerprinting these quantum computers have been proposed, many are resource-intensive and not currently practical. To address this, we introduce Q-ID, a lightweight fingerprinting method that accurately identifies quantum servers with negligible quantum computational demands. Q-ID operates by running a user’s task circuit at two different levels of noise, using the resulting performance gap as a unique identifier for quantum servers. Additionally, we have developed an error evolution algorithm that allows users to locally estimate this performance gap. By comparing the estimated gap with the actual one, users can effectively identify or differentiate between quantum servers in a network. Our experiments on the IBM quantum platform showcase the efficacy and benefits of our approach.

中文翻译：

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Q-ID：通过指纹识别的轻量级量子网络服务器


量子网络由互连的量子服务器组成，能够进行计算任务的通信和协作。该网络中的量子服务器相互识别和验证至关重要。例如，当量子服务器打算在另一台机器上执行计算任务时，验证其他量子服务器的真实性以保持委托计算的信心就变得至关重要。虽然已经提出了几种对这些量子计算机进行指纹识别的方法，但许多方法都是资源密集型的，目前并不实用。为了解决这个问题，我们引入了 Q-ID，这是一种轻量级指纹识别方法，可以准确识别量子服务器，而量子计算需求可以忽略不计。 Q-ID 的工作原理是在两种不同的噪声水平下运行用户的任务电路，并使用由此产生的性能差距作为量子服务器的唯一标识符。此外，我们还开发了一种误差演化算法，允许用户在本地估计这种性能差距。通过将估计的差距与实际的差距进行比较，用户可以有效地识别或区分网络中的量子服务器。我们在 IBM 量子平台上进行的实验展示了我们方法的功效和优势。