Quantum Art Achieves 10X Circuit Depth Compression and 30% Error Reduction Using Multi-Qubit Gates and NVIDIA CUDA-Q Platform

Quantum Art's integration with NVIDIA CUDA-Q achieves 10x circuit depth compression and 30% error reduction using multi-qubit gates, accelerating the path to practical quantum computing.

Bay Area Metrowire Staff
Technology
Quantum Art Achieves 10X Circuit Depth Compression and 30% Error Reduction Using Multi-Qubit Gates and NVIDIA CUDA-Q Platform

Quantum Art, a developer of full-stack quantum computers based on trapped-ion qubits, announced today that it has achieved a 10-fold compression in circuit depth and a 30% reduction in error rates by compiling circuits with its all-to-all connected multi-qubit gates on NVIDIA accelerated computing using the NVIDIA CUDA-Q platform. This breakthrough, verified in simulation on the CUDA-Q quantum-classical integration framework, demonstrates the potential of combining Quantum Art's hardware-aware compilation with NVIDIA's accelerated computing ecosystem.

The improvements build on the CUDA-Q integration announced earlier this year. Quantum Art's fully programmable, all-to-all connected multi-qubit gates and advanced compiler serve as a critical resource for implementing circuits at smaller depth, enabling faster runtime and higher performance. The general-purpose compiler automatically optimizes input circuits and substitutes standard operations with efficient multi-qubit gates, consistently delivering order-of-magnitude compression and substantial performance gains.

“We designed our architecture to deliver real performance gains,” said Dr. Tal David, CEO of Quantum Art. “Programmable all-to-all multi-qubit gates are a critical advancement that supports our long-term goal of fault tolerant, commercially viable quantum computing.” Dr. Amit Ben-Kish, CTO and co-founder of Quantum Art, added, “Our compilation technique demonstrates how our multi-qubit gates and optimized compilers can compress quantum circuits by an order of magnitude while simultaneously improving performance by 30%. This compilation is verified by using the NVIDIA CUDA-Q platform to operate NVIDIA AI infrastructure.”

“By allowing researchers to draw on accelerated computing for their work, NVIDIA CUDA-Q is enabling next-generation breakthroughs in quantum computing,” said Sam Stanwyck, Group Product Manager for quantum computing at NVIDIA. “Quantum Art’s use of CUDA-Q to achieve circuit depth compression and error reduction is a clear example of how meaningful performance improvements are being realized by drawing on the latest advances in AI supercomputing.”

This breakthrough further validates and aligns with Quantum Art’s broader roadmap, which centers on scaling multi-qubit gates and reconfigurable multi-core architectures to deliver increasingly powerful quantum systems. The company's innovative architecture enables multi-core quantum processors with unparalleled performance and efficiency, shortening the path to commercial applications at scale.

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