This paper demonstrates the integration of Reinforcement Learning (RL) into quantum transpiling workflows, significantly enhancing the synthesis and routing of quantum circuits. By employing RL, we achieve near-optimal synthesis of Linear Function, …
Published systematic literature review on quantum machine learning and its applications in Computer Science Review journal. Analyzed 94 studies from 2017-2023, identifying two primary algorithm categories and highlighting image classification as a key application area, while noting that quantum hardware improvements are necessary for QML full potential.
Quantum physics has changed the way we understand our environment, and one of its branches, quantum mechanics, has demonstrated accurate and consistent theoretical results. Quantum computing is the process of performing calculations using quantum …
Honored by major announcements from IBM Quantum Summit 2023, including IBM Heron chip with 3-5x performance improvement, 1,121-processor Condor system, operational Quantum System Two, Qiskit 1.0 release, Quantum Serverless beta, and AI integration for automated code development and enhanced transpiler tools.
Quantum Computing is envisioned as one of the scientific areas with greater transformative potential. Already there exist applications running in quantum devices for different areas, like cybersecurity, chemistry, or machine learning. One subarea …
The advent of quantum computers makes it possible to perform quantum computations in different areas like machine learning, finance, or chemistry. This paper showcases one of the emerging areas under quantum machine learning, quantum natural language …
To achieve faster computational speeds than classical computing, quantum computing is rapidly evolving to become one of the most popular areas of computer engineering. The advent of Noisy Intermediate Scale Quantum (NISQ) devices has made it possible …