论文标题
用于因果假设测试的可扩展量子门实现
A scalable quantum gate-based implementation for causal hypothesis testing
论文作者
论文摘要
在这项工作中，我们研究了用于加速因果推断的量子计算算法。具体来说，我们考虑了[\ textit {nat commun} 10，1472（2019）]中提出的因果假设检验的形式主义。我们开发一个量子电路实现，并使用它来证明先前工作中引入的错误概率需要修改。遵循理论描述的实用场景被构造为IBM Qiskit上的基于量子门的可扩展算法。我们介绍了嵌入因果假设的甲骨文的电路结构并评估相关的栅极复杂性。此外，我们在模拟器平台上的实验验证了预测的加速。我们讨论了该框架在生物信息学和人工通用智能中的因果推理用例中的应用。
In this work, we study quantum computing algorithms for accelerating causal inference. Specifically, we consider the formalism of causal hypothesis testing presented in [\textit{Nat Commun} 10, 1472 (2019)]. We develop a quantum circuit implementation and use it to demonstrate that the error probability introduced in the previous work requires modification. The practical scenario, which follows a theoretical description, is constructed as a scalable quantum gate-based algorithm on IBM Qiskit. We present the circuit construction of the oracle embedding the causal hypothesis and assess the associated gate complexities. Additionally, our experiments on a simulator platform validate the predicted speedup. We discuss applications of this framework for causal inference use cases in bioinformatics and artificial general intelligence.
