Ansatz-Free Learning of Lindbladian Dynamics In Situ

• URL: http://arxiv.org/abs/2603.05492v1
• Date: Thu, 05 Mar 2026 18:57:25 GMT
• Title: Ansatz-Free Learning of Lindbladian Dynamics In Situ
• Authors: Petr Ivashkov, Nikita Romanov, Weiyuan Gong, Andi Gu, Hong-Ye Hu, Susanne F. Yelin,
• Abstract summary: We present the first sample-efficient protocol for learning sparse Lindbladians without assuming a priori structure or locality.<n>Our protocol is ancilla-free, uses only product-state preparations and Pauli-basis measurements, and achieves near-optimal time resolution.
• Score: 2.380854690607918
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Characterizing the dynamics of open quantum systems at the level of microscopic interactions and error mechanisms is essential for calibrating quantum hardware, designing robust simulation protocols, and developing tailored error-correction methods. Under Markovian noise/dissipation, a natural characterization approach is to identify the full Lindbladian generator that gives rise to both coherent (Hamiltonian) and dissipative dynamics. Prior protocols for learning Lindbladians from dynamical data assumed pre-specified interaction structure, which can be restrictive when the relevant noise channels or control imperfections are not known in advance. In this paper, we present the first sample-efficient protocol for learning sparse Lindbladians without assuming any a priori structure or locality. Our protocol is ancilla-free, uses only product-state preparations and Pauli-basis measurements, and achieves near-optimal time resolution, making it compatible with near-term experimental capabilities. The final sample complexity depends on linear-system conditioning, which we find empirically to be moderate for a broad class of physically motivated models. Together, this provides a systematic route to scalable characterization of open-system quantum dynamics, especially in settings where the error mechanisms of interest are unknown.

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