Quantum computing has the potential to transform industries from drug discovery to logistics, but the major barrier between today’s quantum devices and useful applications is noise. These obstacles, introduced by environmental interactions and imperfect hardware, mean that today’s qubits can only perform a few hundred operations before quantum computation is irretrievably degraded.
Although seemingly unavoidable, noise in quantum hardware is a result of so-called logical qubits, the tens, hundreds, or even thousands of actual physical qubits that enable correction of errors caused by noise. This can be handled by a set of . Logical qubits are the holy grail of quantum computing, and quantum hardware builder Infleqtion today announced NVIDIA CUDA-Q Platform Design and demonstrate an experiment using two of them.
These logic qubits were used to perform a small-scale demonstration of the so-called single-impurity Anderson model, a high-precision approach needed for many important materials science applications.
This is the first time a demonstration of a materials science quantum algorithm has been performed on a logical qubit. Creating just one logical qubit is extremely difficult. Infleqtion was able to achieve this feat thanks to precise modeling of quantum computers using CUDA-Q’s unique GPU-accelerated simulation capabilities.
After developing and testing the entire experiment within CUDA-Q’s simulator with only a few modifications, Infleqtion uses CUDA-Q to perform a You can now orchestrate your experiments.
This research sets the stage for quantum computing to move toward large-scale error correction systems.
Many scaling challenges still exist between today’s large-scale systems of quantum devices and logical qubits. These can only be solved by integrating quantum hardware and AI supercomputers to form accelerated quantum supercomputers.
NVIDIA continues to work with partners like Infleqtion to enable this groundbreaking research needed to make accelerated quantum supercomputing a reality.
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