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arxiv: 2605.18863 · v1 · pith:SJHNDNQ2new · submitted 2026-05-15 · ⚛️ physics.ins-det · quant-ph

Enhanced Temperature Sensitivity in Ensemble NV Centers through Improved Optically Detected Magnetic Resonance Spectral Modeling

Yuki S. Kato , Shingo Sotoma , Keisuke Fujita , Masanori Fujiwara , Izuru Ohki , Yuichiro Matsuzaki , Norikazu Mizuochi , Yoshie Harada This is my paper

Pith reviewed 2026-05-20 16:35 UTC · model grok-4.3

classification ⚛️ physics.ins-det quant-ph
keywords NV centersODMR spectroscopytemperature sensingspectral fittingLorentzian modelnanodiamondsensemble defectszero-field splitting
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0 comments X

The pith

Ensemble NV ODMR spectra near resonance are well approximated by a single Lorentzian plus background term, improving temperature sensing.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper establishes a new way to model and fit the optically detected magnetic resonance spectra from groups of nitrogen-vacancy centers in diamond. It shows that when individual NV responses are averaged over variations in zero-field splitting and strain, the shape near the resonance can be captured by one Lorentzian curve with an added background. This dip-peak fitting method determines the resonance frequency more precisely than standard Lorentzian or Voigt fits, especially with low microwave power. More accurate frequencies lead to better temperature estimates from these sensors. The approach is validated in experiments with fluorescent nanodiamond samples.

Core claim

Starting from a physical model of ensemble cw-ODMR spectra as a convolution of single-NV responses with distributed zero-field splitting and strain, the spectral feature near resonance is accurately approximated by a single Lorentzian function with a background term. This approximation enables the dip-peak fitting method to extract the resonance frequency more faithfully than conventional models, allowing faster and more accurate temperature sensing under weaker microwave excitation, as confirmed by experiments on fluorescent nanodiamond ensembles.

What carries the argument

Dip-peak fitting, which uses a single Lorentzian with background term to model the near-resonance feature in ensemble cw-ODMR spectra derived from convolving distributed single-NV responses.

If this is right

  • Resonance frequency can be extracted more accurately from the spectra.
  • Temperature estimation precision increases for ensemble NV sensors.
  • Measurements can be performed with weaker microwave excitation.
  • Data acquisition can be faster while maintaining accuracy.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar modeling approaches could improve sensitivity in other distributed quantum sensor ensembles.
  • This fitting method might reduce the required microwave power, lowering heating effects in biological applications.
  • Extending the model to include more distributions could further refine fits for specific diamond samples.

Load-bearing premise

That the convolution of single-NV responses with distributions of zero-field splitting and strain results in a spectrum near resonance that is accurately captured by one Lorentzian plus a background term.

What would settle it

Compare the root-mean-square fitting residual or the standard deviation of extracted resonance frequencies between the proposed model and conventional Lorentzian/Voigt fits on the same set of experimental ensemble cw-ODMR spectra; if the new model does not yield lower errors, the approximation does not hold.

Figures

Figures reproduced from arXiv: 2605.18863 by Izuru Ohki, Keisuke Fujita, Masanori Fujiwara, Norikazu Mizuochi, Shingo Sotoma, Yoshie Harada, Yuichiro Matsuzaki, Yuki S. Kato.

Figure 1
Figure 1. Figure 1: FIG. 1. (a) Schematic illustration of a nitrogen–vacancy cen [PITH_FULL_IMAGE:figures/full_fig_p001_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2. (a) Optical setup for cw-ODMR measurements. [PITH_FULL_IMAGE:figures/full_fig_p002_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. Fitting results of cw-ODMR spectra. cw-ODMR [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4. Dependence of the resonance-frequency fluctuation [PITH_FULL_IMAGE:figures/full_fig_p005_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5. (a) cw-ODMR spectra measured at different mi [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: FIG. 6. (a, b) Temperature dependence of the cw-ODMR [PITH_FULL_IMAGE:figures/full_fig_p007_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: FIG. 7. Monte Carlo simulation results of cw-ODMR spectra [PITH_FULL_IMAGE:figures/full_fig_p008_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: FIG. 8. Graphical representation of the analysis results [PITH_FULL_IMAGE:figures/full_fig_p009_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: FIG. 9. Results of dip–peak fitting for 100 nm FNDs with electron irradiation doses of 4 [PITH_FULL_IMAGE:figures/full_fig_p010_9.png] view at source ↗
read the original abstract

Nitrogen-vacancy (NV) center ensembles provide a powerful platform for high-precision temperature sensing, with ongoing efforts to further enhance their measurement performance. In ensemble NV optically detected magnetic resonance (ODMR) spectra, commonly used Lorentzian and Voigt fitting models fail to accurately describe the spectral shape near the resonance frequency, leading to degraded precision in resonance-frequency determination and, consequently, temperature estimation. In this work, we analytically establish a new fitting method, termed dip-peak fitting, for extracting the resonance frequency from ensemble cw-ODMR spectra. Starting from a physical model that describes ensemble cw-ODMR spectra as a convolution of single-NV responses with distributed zero-field splitting and strain, we show that the spectral feature near resonance can be accurately approximated by a single Lorentzian function with a background term. The proposed fitting model reproduces the cw-ODMR spectrum around resonance more faithfully than conventional approaches, enabling faster and more accurate resonance-frequency determination under weaker microwave excitation. Experiments using fluorescent nanodiamond ensembles confirm the robustness and applicability of this method for high-precision temperature sensing.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript proposes a 'dip-peak fitting' method for extracting resonance frequencies from ensemble NV-center cw-ODMR spectra to improve temperature sensing precision. Starting from a physical convolution model of single-NV responses with distributed zero-field splitting and strain, the authors claim that the near-resonance spectral feature is accurately approximated by a single Lorentzian plus background term. This is asserted to outperform standard Lorentzian and Voigt fits, enabling better performance at weaker microwave excitation, with experimental confirmation reported on fluorescent nanodiamond ensembles.

Significance. If the claimed approximation holds over the relevant parameter range and demonstrably improves resonance-frequency precision, the work could meaningfully advance practical ensemble NV temperature sensors by reducing required microwave power while maintaining or increasing sensitivity. The experimental component on nanodiamonds provides a useful test bed, but the absence of explicit equations, validity bounds, and quantitative error analysis in the presented material limits the immediate assessed impact.

major comments (2)
  1. [Abstract] Abstract (paragraph on derivation): The central claim that the convolution of single-NV responses with ZFS/strain distributions yields a near-resonance feature accurately fit by one Lorentzian plus background is load-bearing, yet the text provides neither the explicit functional forms of the distributions nor the integration steps that produce the claimed Lorentzian approximation. Without these, it is impossible to verify the regime of validity (e.g., rms strain ≪ linewidth) or to confirm that the result remains single-peaked and symmetric inside the fitting window.
  2. [Abstract] Abstract and experimental section: No quantitative comparison of resonance-frequency extraction errors, temperature sensitivity figures of merit, or statistical uncertainties is supplied between the proposed dip-peak fit and conventional Lorentzian/Voigt models. This omission prevents assessment of whether the reported improvement is statistically significant or merely visual.
minor comments (2)
  1. The term 'dip-peak fitting' is introduced without a clear definition of the background functional form or how the peak and dip components are parameterized; a short equation or diagram would remove ambiguity.
  2. The manuscript would benefit from a brief statement of the microwave power levels used in the 'weaker excitation' regime and the corresponding ODMR contrast values.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful and constructive review of our manuscript. We have addressed each major comment below and will revise the manuscript accordingly to improve clarity, provide missing details, and strengthen the quantitative analysis.

read point-by-point responses

  1. Referee: [Abstract] Abstract (paragraph on derivation): The central claim that the convolution of single-NV responses with ZFS/strain distributions yields a near-resonance feature accurately fit by one Lorentzian plus background is load-bearing, yet the text provides neither the explicit functional forms of the distributions nor the integration steps that produce the claimed Lorentzian approximation. Without these, it is impossible to verify the regime of validity (e.g., rms strain ≪ linewidth) or to confirm that the result remains single-peaked and symmetric inside the fitting window.

    Authors: We agree that the abstract does not contain the explicit functional forms or integration steps. The full manuscript derives the approximation from a convolution of single-NV Lorentzian responses with Gaussian distributions for zero-field splitting and strain; the near-resonance feature reduces to a Lorentzian plus linear background when the rms strain is much smaller than the linewidth. To make this self-contained, we will revise the abstract to include a concise statement of the assumed distributions (Gaussian with given rms values), the key steps of the integration, and the validity condition (rms strain ≪ linewidth) that preserves single-peaked symmetry within the fitting window. revision: yes

  2. Referee: [Abstract] Abstract and experimental section: No quantitative comparison of resonance-frequency extraction errors, temperature sensitivity figures of merit, or statistical uncertainties is supplied between the proposed dip-peak fit and conventional Lorentzian/Voigt models. This omission prevents assessment of whether the reported improvement is statistically significant or merely visual.

    Authors: We acknowledge that quantitative metrics are required to substantiate the claimed improvement. In the revised manuscript we will add a dedicated comparison subsection (or supplementary figure) reporting root-mean-square errors in extracted resonance frequencies, temperature sensitivity figures of merit (e.g., in mK/√Hz), and statistical uncertainties obtained from repeated measurements for the dip-peak, Lorentzian, and Voigt models. These data will allow direct evaluation of statistical significance. revision: yes

Circularity Check

0 steps flagged

No circularity: derivation proceeds from external physical convolution model to analytical approximation

full rationale

The paper starts from a stated physical model of ensemble cw-ODMR spectra as the convolution of single-NV responses with distributed zero-field splitting and strain, then analytically shows that the near-resonance feature can be approximated by a single Lorentzian plus background. This is a forward mathematical reduction from an independent physical description rather than a self-definitional loop, a fitted parameter renamed as prediction, or a load-bearing self-citation. No equations or steps in the provided abstract reduce the claimed approximation to the target temperature or resonance data by construction; the fitting form is presented as derived rather than tuned directly to the spectra being analyzed. The derivation is therefore self-contained against the external physical model and receives the default non-circularity finding.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the physical convolution model of ensemble spectra and the validity of the Lorentzian-plus-background approximation; no free parameters or new entities are introduced in the abstract.

axioms (1)
  • domain assumption Ensemble cw-ODMR spectra can be modeled as a convolution of single-NV responses with distributed zero-field splitting and strain
    This is explicitly stated as the starting physical model from which the dip-peak approximation is derived.

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Reference graph

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