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Quantum Machines and Nvidia have partnered to advance quantum computing, focusing on error correction. Their collaboration utilizes Nvidia's DGX Quantum platform alongside Quantum Machines' control hardware to enhance qubit calibration. This partnership aims to improve the performance and fidelity of quantum computers, moving closer to the goal of error-corrected quantum systems.
The integration of reinforcement learning into the calibration process is a significant step forward. By continuously adjusting control pulses in real-time, the companies can address the challenges of quantum error correction more effectively. This collaboration is just the beginning, with plans for further optimization and the development of open-source libraries to support researchers.
• Nvidia and Quantum Machines enhance qubit calibration using reinforcement learning.
• Improved calibration can exponentially boost quantum error correction performance.
Reinforcement learning is applied to optimize the calibration of qubits in quantum processors.
Quantum error correction is essential for achieving fault-tolerant quantum computing.
Calibration involves adjusting control pulses to maintain high fidelity in quantum computing.
Quantum Machines specializes in quantum control hardware, crucial for enhancing quantum computing performance.
Nvidia develops powerful computing platforms that support advanced quantum computing applications.
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