Quantum reservoir computing (QRC) and quantum extreme learning machines (QELM) are two emerging approaches that have demonstrated their potential both in classical and quantum machine learning tasks. They exploit the quantumness of physical systems combined with an easy training strategy, achieving an ...
Quantum generative models provide inherently efficient sampling strategies and thus show promise for achieving an advantage using quantum hardware. In this work, we investigate the barriers to the trainability of quantum generative models posed by barren plateaus and exponential loss concentration. We explo...
At the intersection of machine learning and quantum computing, quantum machine learning has the potential of accelerating data analysis, especially for quantum data, with applications for quantum materials, biochemistry and high-energy physics. Neverthel
Materials challenges and opportunities for quantum computing hardware for Science by Nathalie P. de Leon et al.
Cybersecurity attorney Mark Francis and intellectual property attorneys Robert Hill and Jacob Schneider co-hosted a webinar about progress in quantum computing, a phenomenon that appears to be approaching a leap from science fiction to reality.
China’s Institute of High Energy Physics (IHEP) in Beijing is pioneering innovative approaches in quantum computing and quantum machine learning to open up new research pathways within its particle physics programme, as Hideki Okawa, Weidong Li and Jun Cao explain Simulate to accumulate The IHEP ...
Quantum Computing: The advent of quantum computing poses both challenges and opportunities for cloud mining. While it may enhance cryptographic security, it also has the potential to break existing encryption algorithms. Cloud mining services will need to adapt and invest in quantum-resistant technologie...
Quantum computing could potentially offer faster solutions for some of today's classically intractable problems using quantum processors as computational support for quantum algorithms [1]. Quantum processors, in the most frequent embodiment, comprise an array of quantum bits (qubits), the fundamental co...
Additionally, quantum computing will bring revolutionary development opportunities for AI. The number of quantum bits increases exponentially. Miniaturized quantum chips make possible the rapid and real-time processing. China's AI achieves major breakthroughs in basic theories, technologies, and ...
Quantum machine learning may provide powerful tools for data analysis in high-energy physics. Sau Lan Wu and Shinjae Yoo describe how the potential of these tools is starting to be tested and what has been understood thus far.