These algorithms combine the strengths of both quantum and classical computing to solve complex problems more effectively.
NVIDIA recently released a short film ‘Quantum Accelerated Supercomputing: Powering Tomorrow’s Breakthroughs’. In this film a panel of experts discussed advancements and challenges in quantum computing. These experts are leading the integration of quantum computing with classical supercomputing to address some of the most intricate problems in science and technology.
Dr. Jin-Sung Kim from NVIDIA highlighted that NVIDIA is collaborating with partners from industry, academia, and government laboratories to create an ecosystem that will facilitate this advancement. This cooperative approach is essential for the development and implementation of quantum computing technologies.
At the National Energy Research Scientific Computing Center (NERSC), Dr. Katie Klymko underscored the importance of simulation in quantum research. “GPU-powered supercomputers like Perlmutter empower the entire quantum community to develop improved algorithms and processors,” she remarked. Klymko’s work illustrates how classical computing resources can contribute to quantum computing research.
Dr. Nathan Gemelke from QuEra Computing discussed the innovative use of atoms as qubits. He implied that we can quantum compute by taking individual atoms, cooling them down, and trapping them in a focused laser beam known as an optical tweezer using laser cooling. This method shows promise for enhancing the scale and fidelity of quantum computing.
Addressing the challenge of error correction, Dr. Yonatan Cohen from Quantum Machines stated, “The main issue with quantum processors today is their noisiness and the high number of errors.” His collaboration with NVIDIA to develop the DGX Quantum system aims to tackle these errors by improving the interaction between quantum processors and classical computing power.
The film also highlighted the concept of hybrid algorithms, with Klymko noting that “there are many hybrid algorithms currently being developed and implemented.” These algorithms combine the strengths of both quantum and classical computing to solve complex problems more effectively.
