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Research PaperResearchia:202605.16044

Scalable self-testing of generic multipartite quantum states

Jinchang Liu

Abstract

Characterizing large quantum systems with minimal assumptions is a central challenge in quantum information science. Self-testing provides the strongest form of certification by identifying the underlying quantum state solely from observed measurement statistics. However, existing self-testing methods for generic $n$-partite states face a scalability barrier, requiring exponentially many samples in the system size. In this work, we overcome this barrier by introducing a protocol that robustly se...

Submitted: May 16, 2026Subjects: Quantum Physics; Quantum Computing

Description / Details

Characterizing large quantum systems with minimal assumptions is a central challenge in quantum information science. Self-testing provides the strongest form of certification by identifying the underlying quantum state solely from observed measurement statistics. However, existing self-testing methods for generic nn-partite states face a scalability barrier, requiring exponentially many samples in the system size. In this work, we overcome this barrier by introducing a protocol that robustly self-tests almost all nn-qubit states with only polynomial sample complexity. The key ingredient is an efficient scheme for device-independently evaluating multipartite Pauli measurements, which can be implemented using only a linear number of ancillary Bell pairs together with standard projective and Bell measurements, well within the reach of current quantum technology. Beyond self-testing states, our scheme provides a general framework for implementing a wide range of learning and certification protocols in the device-independent setting, thereby opening a scalable route to device-independent quantum information processing in large-scale quantum networks.


Source: arXiv:2605.15106v1 - http://arxiv.org/abs/2605.15106v1 PDF: https://arxiv.org/pdf/2605.15106v1 Original Link: http://arxiv.org/abs/2605.15106v1

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Date:
May 16, 2026
Topic:
Quantum Computing
Area:
Quantum Physics
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