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2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)01:19

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Heteronuclear single-quantum correlation spectroscopy (HSQC) is a 2D NMR technique that reveals one-bond correlations between hydrogen and a heteronucleus. The HSQC experiment is similar to the heteronuclear correlation experiment (HETCOR) but is more sensitive. In the HSQC spectrum, the proton chemical shift is plotted on the horizontal F2 axis, while the 13C chemical shift is plotted on the vertical F1 axis. The corresponding proton and 13C spectra are also shown. The HSQC contour plot does...
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We demonstrate hybrid quantum machine learning (HQML) on real quantum devices, achieving 91.2% accuracy for cybersecurity analytics. This surpasses previous research using quantum simulators and enhances large-scale data streaming capabilities.

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Area of Science:

  • Quantum Computing
  • Machine Learning
  • Cybersecurity Analytics

Background:

  • Current research in hybrid quantum machine learning (HQML) is limited by data sample sizes and reliance on quantum simulators.
  • Previous studies, such as Suryotrisongko and Musashi (2022), were constrained to 1000 data samples using only software-based emulators.

Purpose of the Study:

  • To enable the execution of HQML methods on real quantum computers and real-device-based simulations.
  • To outperform existing research in terms of data samples processed and accuracy achieved.
  • To apply HQML to cybersecurity analytics for domain generation algorithm (DGA) botnet detection.

Main Methods:

  • Developed a stable quantum architecture for executing HQML algorithms on real quantum devices.
  • Introduced new hybrid quantum binary classifiers (HQBCs) utilizing Hoeffding decision tree algorithms.
  • Implemented batch-wise execution for accelerated processing and reduced quantum shot requirements.
  • Conducted experiments using Qiskit with Aer quantum simulator and real quantum devices (IonQ, Rigetti, Quantinuum) via Azure Quantum.

Main Results:

  • Successfully executed HQML with 100 data samples on real quantum computers and 5000 data samples on real-device-based simulations.
  • Achieved an average accuracy of 91.2%, significantly outperforming the previous state-of-the-art accuracy of 76.8%.
  • Completed all experiments within a total execution time of 1687 seconds.

Conclusions:

  • This study marks the first successful integration of HQML algorithms on real quantum hardware for cybersecurity applications.
  • The novel HQBCs and batch-wise execution strategy enable efficient processing of large-scale data streams.
  • The demonstrated approach significantly advances the practical application of quantum computing in cybersecurity analytics.