Mitigating sloppiness in joint estimation of successive squeezing parameters

Abstract When two successive squeezing operations with the same phase are applied to a field mode, reliably estimating the amplitude of each is impossible because the output state depends solely on their sum. In this case, the quantum statistical model becomes sloppy, and the quantum Fisher information matrix turns singular. However, estimation of both parameters becomes feasible if the quantum state is subjected to an appropriate scrambling operation between the two squeezing operations. In this work, we analyze in detail the effects of a phase-shift scrambling transformation, optimized to reduce sloppiness and maximize the overall estimation precision using only classical probes. We also compare the optimized precision bounds of joint estimation with those of stepwise estimation methods, finding that joint estimation retains an advantage despite the quantum noise induced by the residual parameter incompatibility. Finally, we analyze the precision achievable by general-dyne detection and find that it approaches the optimal precision when one of the two squeezing amplitudes is large enough.

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Publication Details

Journal
New Journal of Physics
Published
2025-10-01
DOI
https://doi.org/10.1088/1367-2630/ae1250
Citations
3
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
4.29
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article

Mitigating sloppiness in joint estimation of successive squeezing parameters

Matteo G. A. Paris, Devendra Kumar Mishra, Stefano Olivares, Priyanka Sharma
3 citations
New Journal of Physics
Neural dynamics and brain function
4.29
article

Mitigating sloppiness in joint estimation of successive squeezing parameters

Matteo G. A. Paris, Devendra Kumar Mishra, Stefano Olivares, Priyanka Sharma
article en
3 citations

Abstract

Abstract When two successive squeezing operations with the same phase are applied to a field mode, reliably estimating the amplitude of each is impossible because the output state depends solely on their sum. In this case, the quantum statistical model becomes sloppy, and the quantum Fisher information matrix turns singular. However, estimation of both parameters becomes feasible if the quantum state is subjected to an appropriate scrambling operation between the two squeezing operations. In this work, we analyze in detail the effects of a phase-shift scrambling transformation, optimized to reduce sloppiness and maximize the overall estimation precision using only classical probes. We also compare the optimized precision bounds of joint estimation with those of stepwise estimation methods, finding that joint estimation retains an advantage despite the quantum noise induced by the residual parameter incompatibility. Finally, we analyze the precision achievable by general-dyne detection and find that it approaches the optimal precision when one of the two squeezing amplitudes is large enough.

New Journal of PhysicsVol. 27(10)
University of Milan (IT), Banaras Hindu University (IN)
Openalex Percentile: Top 5%
Neural dynamics and brain function
4.29
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Mitigating sloppiness in joint estimation of successive squeezing parameters — Matteo G. A. Paris, Devendra Kumar Mishra, et al. · New Journal of Physics (2025) | TGRS Research Map | TGRS