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Quantum Experiment Design Methodology
Information-Theoretic Gaps in Solar and Reactor Neutrino Oscillation Measurements
arXiv
Authors: Neetu Raj Singh Chundawat, Yu-Feng Li
Year
2026
Paper ID
2679
Status
Preprint
Abstract Read
~2 min
Abstract Words
206
Citations
N/A
Abstract
Quantum estimation theory provides a fundamental framework for analyzing how precisely physical parameters can be estimated from measurements. Neutrino oscillations are characterized by a set of parameters inferred from experiments conducted in different production and detection environments. The two solar oscillation parameters, Δm221 and θ12, can be estimated using both solar neutrino experiments and reactor neutrino experiments. In reactor experiments, neutrinos are detected after coherent vacuum evolution, while solar neutrinos arrive at the detector as incoherent mixtures. In this work, we use Quantum Fisher Information (QFI) to quantify and compare the information content accessible in these two experimental setups. We find that for reactor neutrinos, flavor measurements saturate the QFI bound for both parameters over specific energy ranges, demonstrating their optimality and explaining the high precision achieved by these experiments. In contrast, for solar neutrinos the phase-based contribution to the QFI, originating from the quantum coherence, is absent, rendering the estimation of Δm212 purely population-based and effectively classical, while the QFI for θ12 is dominated by basis rotation at high energies and is nearly saturated by flavor measurements. Consequently, solar neutrino experiments are intrinsically more sensitive to θ12 than to Δm212. This analysis highlights a fundamental distinction between the two estimation problems and accounts for their differing achievable precisions.
Why This Paper Matters
- This paper contributes to the Quantum Experiment Design & Methodology research area in the Quantum Articles archive.
- It adds a 2026 reference point for readers tracking recent quantum research.
- Quantum estimation theory provides a fundamental framework for analyzing how precisely physical parameters can be estimated from measurements.
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