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.

Related papers

• Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [63.733312560668274]
  Given a quantum circuit containing d tunable RZ gates and G-d Clifford gates, can a learner perform purely classical inference to efficiently predict its linear properties? We prove that the sample complexity scaling linearly in d is necessary and sufficient to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d. We devise a kernel-based learning model capable of trading off prediction error and computational complexity, transitioning from exponential to scaling in many practical settings.
  arXiv  Detail & Related papers  (2024-08-22T08:21:28Z)
• Realistic Runtime Analysis for Quantum Simplex Computation [0.4407851469168588]
  We present a quantum analog for classical runtime analysis when solving real-world instances of important optimization problems. We show that a practical quantum advantage for realistic problem sizes would require quantum gate operation times that are considerably below current physical limitations.
  arXiv  Detail & Related papers  (2023-11-16T16:11:44Z)
• Quantum data learning for quantum simulations in high-energy physics [55.41644538483948]
  We explore the applicability of quantum-data learning to practical problems in high-energy physics. We make use of ansatz based on quantum convolutional neural networks and numerically show that it is capable of recognizing quantum phases of ground states. The observation of non-trivial learning properties demonstrated in these benchmarks will motivate further exploration of the quantum-data learning architecture in high-energy physics.
  arXiv  Detail & Related papers  (2023-06-29T18:00:01Z)
• Robustness of quantum algorithms against coherent control errors [0.5407319151576265]
  We present a framework for analyzing the robustness of quantum algorithms against coherent control errors using Lipschitz bounds. We derive worst-case fidelity bounds which show that the resilience against coherent control errors is mainly influenced by the norms of the Hamiltonians generating the individual gates.
  arXiv  Detail & Related papers  (2023-03-01T16:18:38Z)
• Theory and Implementation of the Quantum Approximate Optimization Algorithm: A Comprehensible Introduction and Case Study Using Qiskit and IBM Quantum Computers [0.0]
  We lay our focus on practical aspects and step-by-step guide through the realization of a proof of concept quantum application. In every step we first explain the underlying theory and subsequently provide the implementation using IBM's Qiskit. As another central aspect of this tutorial we provide extensive experiments on the 27 qubits state-of-the-art quantum computer ibmq_ehningen.
  arXiv  Detail & Related papers  (2023-01-23T16:38:06Z)
• A Quantum Algorithm for Computing All Diagnoses of a Switching Circuit [73.70667578066775]
  Faults are by nature while most man-made systems, and especially computers, work deterministically. This paper provides such a connecting via quantum information theory which is an intuitive approach as quantum physics obeys probability laws.
  arXiv  Detail & Related papers  (2022-09-08T17:55:30Z)
• Automatic Test Pattern Generation for Robust Quantum Circuit Testing [8.860149267706221]
  We introduce the stabilizer projector decomposition (SPD) for representing the quantum test pattern. We construct the test application (i.e., state preparation and measurement) using Clifford-only circuits. We develop an SPD generation algorithm, as well as several acceleration techniques which can exploit both locality and sparsity in generating SPDs.
  arXiv  Detail & Related papers  (2022-02-22T07:06:10Z)
• Circuit Symmetry Verification Mitigates Quantum-Domain Impairments [69.33243249411113]
  We propose circuit-oriented symmetry verification that are capable of verifying the commutativity of quantum circuits without the knowledge of the quantum state. In particular, we propose the Fourier-temporal stabilizer (STS) technique, which generalizes the conventional quantum-domain formalism to circuit-oriented stabilizers.
  arXiv  Detail & Related papers  (2021-12-27T21:15:35Z)
• Realization of arbitrary doubly-controlled quantum phase gates [62.997667081978825]
  We introduce a high-fidelity gate set inspired by a proposal for near-term quantum advantage in optimization problems. By orchestrating coherent, multi-level control over three transmon qutrits, we synthesize a family of deterministic, continuous-angle quantum phase gates acting in the natural three-qubit computational basis.
  arXiv  Detail & Related papers  (2021-08-03T17:49:09Z)
• Error mitigation and quantum-assisted simulation in the error corrected regime [77.34726150561087]
  A standard approach to quantum computing is based on the idea of promoting a classically simulable and fault-tolerant set of operations. We show how the addition of noisy magic resources allows one to boost classical quasiprobability simulations of a quantum circuit.
  arXiv  Detail & Related papers  (2021-03-12T20:58:41Z)
• Quantum Simulation of Light-Front Parton Correlators [0.0]
  The physics of high-energy colliders relies on the knowledge of non-perturbative parton correlators. We propose a quantum algorithm to perform a quantum simulation of these type of correlators.
  arXiv  Detail & Related papers  (2020-11-02T19:38:33Z)
• An Application of Quantum Annealing Computing to Seismic Inversion [55.41644538483948]
  We apply a quantum algorithm to a D-Wave quantum annealer to solve a small scale seismic inversions problem. The accuracy achieved by the quantum computer is at least as good as that of the classical computer.
  arXiv  Detail & Related papers  (2020-05-06T14:18:44Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.