论文标题
部分可观测时空混沌系统的无模型预测
Automated error correction in superdense coding, with implementation on superconducting quantum computer
论文作者
论文摘要
由于量子状态中不可避免的噪声和量子纠缠的脆弱性,易耐断层量子计算机的构建仍然是一个具有挑战性的问题。但是,大多数误差校正代码都会增加算法的复杂性,从而降低任何量子优势。在这里,我们提出了一种特定于任务的错误纠正技术,该技术对限制的量子状态提供了完整的保护。具体而言,我们在利用N Qubit Permorized Bell状态的超密集编码算法中进行了自动误差校正。它的核心是基于贝尔状态的非破坏性歧视方法,该方法涉及对Ancilla Qubits(阶段和平均值)的测量。该算法显示为可分布,可以分配给共享正交状态的任何一组当事方。自动化是指实验在量子计算机中实现算法,通过利用单一操作员,没有介于两者之间的测量,因此无需外部干预。我们还通过实验意识到在7 QUITAIND的IBM量子计算机上以及在噪声存在下的27 QUITING量子模拟器上,在7 QUITAINCONDICTICT IBM量子计算机上使用三种不同类型的超密集编码算法的自动误差校正技术。生成概率直方图以显示我们实验结果的高忠诚度。量子层析成像还使用量子计算机进行,以阐明我们方法的功效。
Construction of a fault-tolerant quantum computer remains a challenging problem due to unavoidable noise in quantum states and the fragility of quantum entanglement. However, most of the error-correcting codes increases the complexity of the algorithms, thereby decreasing any quantum advantage. Here we present a task-specific error-correction technique that provides a complete protection over a restricted set of quantum states. Specifically, we give an automated error correction in Superdense Coding algorithms utilizing n-qubit generalized Bell states. At its core, it is based on non-destructive discrimination method of Bell states involving measurements on ancilla qubits (phase and parity ancilla). The algorithm is shown to be distributable and can be distributed to any set of parties sharing orthogonal states. Automated refers to experimentally implementing the algorithm in a quantum computer by utilizing unitary operators with no measurements in between and thus without the need for outside intervention. We also experimentally realize our automated error correction technique for three different types of superdense coding algorithm on a 7-qubit superconducting IBM quantum computer and also on a 27-qubit quantum simulator in the presence of noise. Probability histograms are generated to show the high fidelity of our experimental results. Quantum state tomography is also carried out with the quantum computer to explicate the efficacy of our method.