A scalable quantum gate-based implementation for causal hypothesis
testing
- URL: http://arxiv.org/abs/2209.02016v4
- Date: Mon, 2 Oct 2023 14:32:10 GMT
- Title: A scalable quantum gate-based implementation for causal hypothesis
testing
- Authors: Akash Kundu, Tamal Acharya, Aritra Sarkar
- Abstract summary: We study quantum computing algorithms for accelerating causal inference.
We develop a quantum circuit implementation and use it to demonstrate that the error probability introduced in the previous work requires modification.
We discuss applications of this framework for causal inference use cases in bioinformatics and artificial general intelligence.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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.
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