Academia Sinica Integrates NVIDIA Model to Advance AI-Driven Quantum Processor Calibration
Academia Sinica partnered with NVIDIA to develop an AI-driven automated calibration technology for Quantum Processing Units (QPUs), accelerating quantum computing development.
📋 Article Processing Timeline
- 📰 Published: April 17, 2026 at 18:20
- 🔍 Collected: April 17, 2026 at 18:31 (11 min after Published)
- 🤖 AI Analyzed: April 18, 2026 at 21:57 (27h 25m after Collected)
Central News Agency
(CNA Reporter Wu Hsin-yun, Taipei, 17th) Academia Sinica announced today that it has recently partnered with NVIDIA to utilize the NVIDIA Ising series AI models to develop an AI-driven automated calibration technology. This improves testing efficiency and system scalability, laying the foundation for scaling up quantum chips.
The Quantum Processing Unit (QPU) is the core of a superconducting quantum computer. In the past, QPU calibration heavily relied on human experience and iterative correction programs, which had limited efficiency and struggled to meet large system demands.
Academia Sinica issued a press release today pointing out that to overcome the limitations of traditional QPU calibration, it collaborated with NVIDIA to use the Ising series AI models. By developing this AI-driven automated technology within an architecture integrating quantum computing and Graphics Processing Units (GPUs), the development process for QPU fabrication and testing is accelerated, effectively closing the gap between current hardware capabilities and practical quantum applications.
Chen Chi-Tung, Executive Director of the Quantum Computer Center at Academia Sinica's Key Issues Research Center, noted that this system has been integrated into their quantum computing platform. Through an automated multi-agent collaborative architecture, it provides key capabilities such as closed-loop parameter optimization. Through a continuous "execute-detect-adjust" cycle, it automatically fine-tunes parameters and detects qubit frequencies.
Chen stated that by simply inputting a single natural language command, read-out calibration can be completed on a quantum chip containing 5 qubits and 4 couplers, and an experimental workflow is automatically generated. This demonstrates its application potential on the center's recently unveiled 20-qubit chip.
Academia Sinica stated that through its collaboration with NVIDIA, it is establishing a highly reliable, efficient, and scalable quantum testing infrastructure. It will open this platform to domestic academic, research, and industrial sectors, promoting technical exchange and further strengthening Taiwan's overall quantum tech ecosystem. (Editor: Kuan Chung-wei) 1150417
Choose to stand with the facts, every sponsorship from you is the power to protect press freedom.
Download the CNA "First Hand News" APP to grasp the latest news instantly.
The text, images, and audio/video on this website may not be reproduced, publicly broadcast, or publicly transmitted and utilized without authorization.
(CNA Reporter Wu Hsin-yun, Taipei, 17th) Academia Sinica announced today that it has recently partnered with NVIDIA to utilize the NVIDIA Ising series AI models to develop an AI-driven automated calibration technology. This improves testing efficiency and system scalability, laying the foundation for scaling up quantum chips.
The Quantum Processing Unit (QPU) is the core of a superconducting quantum computer. In the past, QPU calibration heavily relied on human experience and iterative correction programs, which had limited efficiency and struggled to meet large system demands.
Academia Sinica issued a press release today pointing out that to overcome the limitations of traditional QPU calibration, it collaborated with NVIDIA to use the Ising series AI models. By developing this AI-driven automated technology within an architecture integrating quantum computing and Graphics Processing Units (GPUs), the development process for QPU fabrication and testing is accelerated, effectively closing the gap between current hardware capabilities and practical quantum applications.
Chen Chi-Tung, Executive Director of the Quantum Computer Center at Academia Sinica's Key Issues Research Center, noted that this system has been integrated into their quantum computing platform. Through an automated multi-agent collaborative architecture, it provides key capabilities such as closed-loop parameter optimization. Through a continuous "execute-detect-adjust" cycle, it automatically fine-tunes parameters and detects qubit frequencies.
Chen stated that by simply inputting a single natural language command, read-out calibration can be completed on a quantum chip containing 5 qubits and 4 couplers, and an experimental workflow is automatically generated. This demonstrates its application potential on the center's recently unveiled 20-qubit chip.
Academia Sinica stated that through its collaboration with NVIDIA, it is establishing a highly reliable, efficient, and scalable quantum testing infrastructure. It will open this platform to domestic academic, research, and industrial sectors, promoting technical exchange and further strengthening Taiwan's overall quantum tech ecosystem. (Editor: Kuan Chung-wei) 1150417
Choose to stand with the facts, every sponsorship from you is the power to protect press freedom.
Download the CNA "First Hand News" APP to grasp the latest news instantly.
The text, images, and audio/video on this website may not be reproduced, publicly broadcast, or publicly transmitted and utilized without authorization.