A collaboration of over 30 researchers from Terra Quantum, JPMorganChase, NVIDIA, Google, NASA, Quantinuum, and academic institutions has co-authored a review on tensor networks, a mathematical framework in quantum computing. The paper, titled “Tensor networks for quantum computing,” was published in Nature Reviews Physics. The review presents a strategic roadmap for the use of tensor networks to unlock practical quantum capabilities and foster innovation.
Tensor networks are an efficient method for representing quantum states in high-dimensional many-body systems. The paper outlines how these networks can be applied to simulate quantum systems, design quantum circuits, and reduce noise to improve quantum error correction. The framework is also discussed for its use in enhancing the efficiency and interpretability of quantum machine learning models.
The review details a strategic path forward for how tensor networks can contribute to scaling quantum systems, enabling fault tolerance, and facilitating the combination of classical AI with quantum devices. Terra Quantum CEO Markus Pflitsch commented that collaborative work between academia, industry, and policymakers is necessary to address complex scientific challenges. The collaboration included contributions from researchers at institutions such as Caltech, Université de Sherbrooke, University of Jyväskylä, and the University of British Columbia.
Read the full announcement here and the paper in Nature Reviews Physics here.
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