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REVIEW 5 major objections 5 minor 26 references

Simulation and measurement of Black Body Radiation background in a Transition Edge Sensor

T0 review · 5 major / 5 minor · reviewed 2026-08-15 · deepseek-v4-flash

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Pith's one-line read Black-body radiation from the room-temperature laboratory is the primary background source for a fiber-coupled transition-edge sensor, and a modular simulation reproduces the measured spectrum within uncertainties.

desk verdict A genuinely useful BBR simulation framework for fiber-coupled TES detectors, but the claimed 'within uncertainties' agreement with the 72-hour background measurement is overstated and needs a quantitative test. read the letter →

arxiv 2505.08555 v1 pith:TQS454BJ submitted 2025-05-13 hep-ex physics.ins-det

José Alejandro Rubiera Gimeno , Katharina-Sophie Isleif , Friederike Januschek , Axel Lindner , Manuel Meyer , Gulden Othman , Elmeri Rivasto , Rikhav Shah
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Christina Schwemmbauer
This is my paper · ORCID
classification hep-exphysics.ins-det
keywords transitionedgesensorblackbodyradiationsinglephotondetectionbackgroundsimulationenergyresolutionfibercurlingaxion-likeparticleslightshiningthroughawall
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

The paper argues that the background seen by a fiber-coupled tungsten transition-edge sensor—a single-photon detector being developed for the photon-counting channel of a light-shining-through-a-wall experiment—is dominated by room-temperature black-body radiation coupling into the optical fiber, not by intrinsic sensor noise. It builds a modular simulation that follows black-body-distributed photons from the warm fiber end through fiber transmission, fiber curling, and the sensor's wavelength-dependent absorbance, then folds in the detector's energy resolution and pile-up. Against a 72-hour extrinsic background run, the simulation reproduces the measured spectral shape within uncertainties, and it predicts—and the improved analysis confirms—that improving the energy resolution from 11.3% to 5.3% reduces the background rate in the 1064 nm signal region by an order of magnitude, to about $10^{-4}$ counts per second. That is still above the $7.7\times10^{-6}$ counts per second the experiment needs, so the paper identifies black-body radiation as the target of the next background-reduction steps.

What carries the argument

The central object is a modular radiative-transfer simulation built on the black-body spectrum $B(E,T)=2E^2/(h^3c^2(\exp(E/kT)-1))$ for a body at temperature $T$. For each optical path, the flux entering the fiber is integrated over the core area and the acceptance cone set by the numerical aperture, then multiplied by the wavelength-dependent transmissions of the fiber, two fiber-curling sections, and the transition-edge sensor optical stack; the result is convolved with a Gaussian energy response of width $\sigma_{1064\,\mathrm{nm}}$ and supplemented by a pile-up term with minimum resolvable time separation $\Delta t_{\min}=0.75\,\mu\mathrm{s}$. The same machinery produces the predictions at 11.3% and 5.3% energy resolution, and its uncertainty bands are dominated by the assumed curling diameters and by a 2 K temperature variation of the warm fiber end.

What would settle it

Measure a 72-hour extrinsic background spectrum with the fiber's path inside the cryostat mapped to better than a centimeter and a thermometer at the fiber's covered warm end; if the simulated black-body spectrum with those inputs does not reproduce the measured shape between 0.95 eV and 1.2 eV, or if the unexplained excess around 1.165 eV is independent of the measured fiber-end temperature, the central claim is falsified.

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Extended reading notes

Core claim

The paper's central claim is that black-body radiation from the room-temperature laboratory, coupled through the optical fiber that guides light to the sensor, is the primary background source in the fiber-coupled setup, and that this source can be modeled quantitatively. The load-bearing mechanism is a black-body source spectrum $B(E,T)$, multiplied along every optical path by wavelength-dependent transmissions—fiber, fiber curling, and the sensor's band-pass absorbance—and finally convolved with the sensor's Gaussian energy resolution and a pile-up term. The simulated spectrum is consistent with the measured extrinsic background between roughly 0.95 eV and 1.2 eV, and the simulation correctly predicts the size of the improvement obtained when the analysis energy resolution is improved from 11.3% to 5.3%: the background rate in the 1064 nm signal window falls by an order of magnitude, to about $10^{-4}$ counts per second. The paper also notes an excess of events in the one-$\sigma$ region around 1.165 eV that the black-body model does not explain, which it attributes to non-black-body events surviving the analysis cuts.

Load-bearing premise

The analysis assumes that the pulse-shape cuts—fitted rise time, decay time, and reduced chi-squared, all calibrated on 1064 nm laser pulses—reject non-photon events without biasing the reconstructed photon energies; the paper itself reports an excess of events in the one-sigma signal region, indicating that this assumption is at least partially violated exactly where the signal would be.

Editorial extensions

If this is right

  • If black-body radiation is indeed the dominant background, then reducing the temperature of the fiber's warm end or shielding it inside the cryostat attacks the dominant background source; the simulation estimates a factor-of-five rate reduction when the lab temperature drops from 295 K to 283 K.
  • The factor-of-two improvement in energy resolution, from 11.3% to 5.3%, lowers the measured background rate in every one-sigma window around 1064 nm by an order of magnitude, in agreement with the simulation.
  • At 5.3% energy resolution the simulated upper-limit black-body rate in the [0, 3-sigma] window reaches $5\times10^{-6}$ counts per second, which would meet the experiment's target, while the measured value of $6.9\times10^{-5}$ counts per second shows the gap that remains.
  • Fiber curling suppresses both the low-energy tail of the black-body spectrum and pile-up pairs that could mimic 1064 nm photons, making the in-cryostat fiber geometry a controllable background-rejection handle.
  • The residual excess in the one-sigma signal region implies that even a perfect black-body background model will not suffice; those non-black-body events must be identified and suppressed separately.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A consequence the authors leave implicit: the unexplained events in the one-sigma signal region should be nearly independent of the fiber-end temperature, unlike the black-body component, so a temperature-sweep measurement would separate the two backgrounds without changing the analysis.
  • Beyond this specific detector, the same radiative-transfer machinery applies to other fiber-coupled cryogenic photon counters; the uncertainty analysis here suggests that precisely documenting the fiber path inside a cryostat is the cheapest way to sharpen any such background prediction.
  • Because the black-body rate at 1.165 eV falls steeply with temperature, actively cooling just the fiber feedthrough could push the black-body rate well below the factor-of-five gain the paper quotes, an engineering route the paper leaves open.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

5 major / 5 minor

Summary. The paper reports on a tungsten Transition Edge Sensor (TES) being developed for single-photon detection in the ALPS II light-shining-through-a-wall experiment. The main technical contribution is a simulation framework that computes the expected black-body radiation (BBR) background propagating through an optical fiber to the TES, including fiber transmission, fiber curling losses, TES absorbance, energy resolution, and pile-up. The framework is exercised for the specific geometry of an extrinsics background measurement (warm fiber end covered, fiber curled inside the cryostat, 72 h of data). The authors compare the simulated BBR spectrum with measured spectra from the extrinsics run and claim that the background is consistent with BBR as the primary contributor and that the simulation reproduces the spectral distribution within uncertainties. They also show that improving the energy resolution from 11.3% to 5.3% reduces the predicted background in the 1064 nm signal region by about an order of magnitude, although the measured rates in that region still exceed the ALPS II requirement of 7.7e-6 cps.

Significance. If the BBR simulation framework is validated, it would be a useful tool for designing background-reduction strategies for the ALPS II single-photon detector and for similar cryogenic single-photon experiments. The framework is modular, and most input parameters are taken from independent measurements (manufacturer fiber-loss data, spectrometer measurements of curling transmission, reflectance data from a thesis, and calibration-derived energy resolution), which is a strength. The paper also documents a concrete reduction in measured extrinsic background achieved through analysis improvements. However, the central claim of quantitative agreement between simulation and measurement is currently not supported by the quantitative comparison in the paper: in the most important 1064 nm signal region, the measured rates exceed the simulated upper limits by factors of 3 to 14, and the paper itself attributes part of the excess to non-BBR events. The manuscript therefore requires substantial revision of its claims and a more careful uncertainty treatment before the validation claim can be accepted.

major comments (5)
  1. [Abstract; Section V, Tables IV and V] The abstract and Section V state that the simulation reproduces the observed background 'within uncertainties', but the numbers in Tables IV and V do not support this for the signal region. For the [-1,1] sigma window, the measured pulse-height rate is 1.2e-4 cps while the simulated upper limit is 4.6e-5 cps; for the [0,3] sigma window the measured rate is 6.9e-5 cps versus a simulated upper limit of 5e-6 cps, a factor of about 14. The paper should quantify the level of agreement (or disagreement) explicitly, state which energy ranges the 'within uncertainties' claim applies to, and restrict the validation claim accordingly.
  2. [Section IV, Fig. 8; Section V, Figs. 10 and 11] The simulation uncertainty band is constructed from two ad hoc variations (a +/-2 K temperature change and an assumed extra half-loop with an estimated diameter), rather than from a measured or propagated uncertainty on the fiber path inside the cryostat. In addition, the measured data are presented without error bars and no chi-square, Kolmogorov-Smirnov, or similar quantitative comparison is reported. The authors should either provide a more principled uncertainty estimate (e.g., varying the curling parameters within independently measured ranges, including the 10 cm vs 11.2 cm approximation) or explicitly frame Fig. 11 as a qualitative comparison.
  3. [Section V, cuts on pulse-shape parameters] The pulse-shape cuts (rise time, decay time, reduced chi-squared) are defined from 1064 nm calibration pulses and are assumed to be energy independent, but this assumption is load-bearing for interpreting the measured spectrum as a photon energy spectrum. The paper itself notes an excess of events in the 1-sigma signal region that is attributed to non-BBR events, indicating that the cuts do not fully reject non-photon events in exactly the region relevant for ALPS II. The authors should test or justify the energy independence of the cuts (for example, by injecting known-energy sources across the measured range or by comparing the measured spectrum before and after cuts) and discuss how residual non-photon events affect the comparison with the BBR simulation.
  4. [Section V, Table V and Section IV, Tables III and IV] The simulated rates in Tables III and IV use an analysis efficiency that only includes the sigma-window acceptance, while the measured rates in Table V include an additional 98.4% cut acceptance and 90% system detection efficiency. The comparison between Tables IV and V is therefore not apples-to-apples. The authors should state explicitly whether the simulated rates should be multiplied by the same acceptance and efficiency factors before comparison, or provide a direct corrected comparison in the text.
  5. [Section III D, energy-resolution assumption] Equation 6 and the surrounding text assume a constant energy resolution sigma(E) = sigma_1064nm over the range [0 eV, 1.5 eV], citing previous measurements and other groups. Given that the low-energy part of the spectrum is not well described by the simulation and that the TES response may be nonlinear at low energies, the authors should provide quantitative evidence for this assumption in their own setup or explicitly discuss its impact on the comparison in Fig. 11.
minor comments (5)
  1. [Fig. 9 caption] The caption appears to have inconsistent labeling: subfigures (b), (c), and (d) are referenced, but the text seems to refer to (c) twice and (e) twice; please correct the panel labels and their descriptions.
  2. [Section IV, Fig. 8] The figure legend states that the upper limit is produced by varying the temperature by 2 K and the lower limit by adding a non-accounted bending, but the text in Section IV also mentions a sharper quarter-loop; please clarify in the legend which exact variations correspond to the band edges.
  3. [Figs. 10 and 11] The measured spectral points are plotted without error bars, which is especially problematic because the rates in Table V are derived from a single 72-hour run; adding Poisson error bars would help the reader judge the significance of the observed discrepancies.
  4. [Section III B, fiber transmission] The extrapolation of fiber loss outside the displayed wavelength range is described as 'linear', but the linearity is stated without further justification; a brief comment on the validity range would be useful.
  5. [Section IV, Eq. 11] The text says 'The accuracy of Eq. 11 is affected mainly by the fiber curling component and the temperature', but the actual contributions of the fiber-loss data, the TES reflectance approximation, and the numerical aperture are not quantified; a short sensitivity discussion would strengthen the uncertainty treatment.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the BBR simulation is a forward model built from independent measured and literature inputs, and it is not fitted to the extrinsics spectrum.

full rationale

The paper's central derivation chain is not circular. The simulated BBR spectrum is computed from Planck's law (Eq. 1), the fiber numerical aperture and core area (Eq. 10), manufacturer fiber loss data [18], a spectrometer-measured fiber-curling transmission fitted to an error-function form (Eq. 4 and Table II), a TES reflectance curve approximated from the independent thesis data of [17], and an energy resolution taken from prior data analyses [13,25]. None of these parameters is adjusted to match the 72-hour extrinsics histogram of Section V, so the simulation is a genuine forward prediction rather than a fit renamed as a prediction. The qualitative comparison in Fig. 11 and the abstract's 'reproduces, within uncertainties' claim are quantitatively under-supported (no chi-square or KS statistic is reported), and the authors themselves concede that the low-energy part is not described and that the excess in the 1-sigma signal region 'indicates that these events are not due to BBR.' However, an overstated agreement claim is a validation and presentation concern, not circularity. The energy-resolution reduction result is also not a fitted-input-called-prediction: reducing sigma_1064nm in Eq. 6 narrows the Gaussian detector response, and because the BBR spectrum rises steeply toward low energies, the rate in sigma-scaled windows around 1064 nm decreases by roughly an order of magnitude. This is a consequence of the model, not an input relabeled as an output. The self-citations used in the paper, e.g., [13] and [25] for energy resolution and system detection efficiency, supply independently measured detector parameters that do not assume the BBR hypothesis and are not used to enforce agreement with the background data. No equation in the paper reduces to another by construction, and no load-bearing claim is justified solely by a self-citation chain. Therefore no circularity is identified.

Assumptions & free parameters 7 free parameters · 8 assumptions · 0 invented entities

The model rests on standard physics and several hand-assigned geometric and environmental parameters. The most consequential free choices are the unmonitored fiber bending geometry used to set the lower uncertainty bound and the measured energy resolution used both in the simulation and in the rate comparison. No new physical entities are introduced.

free parameters (7)
  • TES reflectance model parameters (lambda1, b1, a1, lambda2, b2, a2) = 700 nm, 0.55, 0.01/nm, 2100 nm, 0.2, 0.002/nm
    Chosen by hand in Eq. 3 and Table I to approximate reflection data from [17]; used in eta_TES(E) in Eq. 11.
  • Fiber one-loop curling fit parameters (a, lambda0 per diameter) = d=12.0 mm: a=9.71e-3/nm, lambda0=1231 nm; d=112 mm: a=1.75e-2/nm, lambda0=1768 nm (Table II)
    Fit to measured white-light transmission of curled fiber (Fig. 4) using Eq. 4; exponent alpha counts number of loops.
  • Room temperature T = 295 K with +2 K upper variation
    Assumed lab temperature for B(E,T) in Eq. 11; not monitored at the fiber end during the measurement, as acknowledged in Section V.
  • Fiber length inside cryostat = 4 m
    Estimated length used in eta_fiber(E, 4 m); affects attenuation of low-energy photons.
  • Fiber bending geometry inside cryostat = 4 loops of 11.2 cm diameter plus 1/4 loop of 2.5 cm; lower bound adds 1/2 loop of 4.2 cm and 1/4 loop of 1.2 cm
    Hand-assigned from photographs and the undocumented fiber path; the lower-bound additions dominate the uncertainty band and are explicitly introduced to cover possible unmonitored bending (Section IV, Fig. 8).
  • Energy resolution sigma_1064nm = 0.13 eV (11.3%) and 0.061 eV (5.3%)
    Measured from Gaussian fits to 1064 nm calibration pulses in [13] and [25]; used to fold BBR spectra and define sigma regions. Not ad hoc.
  • Pile-up time window Delta_t_min = 0.75 microseconds
    Assumed minimum distinguishable time between pulses in the current analysis; only affects the pile-up term Eq. 7, which is suppressed by fiber curling.
assumptions (8)
  • domain assumption Black-body emission follows Planck's law and Lambert's cosine law (Eq. 1)
    Used as the production model for BBR from room-temperature fiber and surroundings.
  • domain assumption Fiber at room temperature re-emits absorbed BBR inside the fiber, equivalent to BBR production at the cryostat feedthrough
    Section IV states that absorbed photons are compensated by photons produced by the optical fiber, justifying the single-source model.
  • domain assumption Fiber accepts all photons with incidence angle below theta_max set by NA and rejects all others; component transmission is angle-independent
    Introduced by the Heaviside step function H(theta_max - theta) in Eq. 5 and the text below it.
  • domain assumption TES energy response is a Gaussian with constant sigma(E) = sigma_1064nm over 0 to 1.5 eV
    Section III D; motivated by previous measurements [21-23] but used without propagating uncertainty.
  • domain assumption Pulse-shape parameters (rise time, decay time, reduced chi-squared) are independent of photon energy, so 1064 nm calibration cuts apply to all background events
    Section V and Fig. 9; if false, the background spectrum after cuts is biased, and the paper reports an excess consistent with such bias.
  • domain assumption TES response is linear: pulse integral and pulse height are proportional to photon energy
    Section V calibration paragraph establishes the energy scale from the 1064 nm line.
  • domain assumption BBR coupling at fiber junctions inside the cryostat is negligible because of the lower temperature
    Fig. 5 caption states that contributions at internal boundaries are neglected given the lower temperature.
  • domain assumption Measured extrinsics environment is a black body at 295 K with the fiber end covered by black cloth
    Section V measurement description; temperature was not continuously monitored.

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Cite this review

Pith. "Pith review of Simulation and measurement of Black Body Radiation background in a Transition Edge Sensor." pith.science (2026). https://pith.science/paper/TQS454BJ

@misc{pith2026250508555,
  author       = {Pith},
  title        = {Pith review of: Simulation and measurement of Black Body Radiation background in a Transition Edge Sensor},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/TQS454BJ}},
  note         = {Machine review of arXiv:2505.08555}
}
abstract

The Any Light Particle Search II (ALPS II) experiment at DESY, Hamburg, is a Light-Shining-through-a-Wall (LSW) experiment aiming to probe the existence of axions and axion-like particles (ALPs), which are candidates for dark matter. Data collection in ALPS II is underway utilizing a heterodyne-based detection scheme. A complementary run for confirmation or as an alternative method is planned using single photon detection, requiring a sensor capable of measuring low-energy photons ($1064\,\mathrm{nm}$, $1.165\,\mathrm{eV}$) with high efficiency (higher than $50\,\%$) and a low background rate (below $7.7\cdot10^{-6}\,\mathrm{cps}$). To meet these requirements, we are investigating a tungsten Transition Edge Sensor (TES) provided by NIST, which operates in its superconducting transition region at millikelvin temperatures. This sensor exploits the drastic change in resistance caused by the absorption of a single photon. We find that the background observed in the setup with a fiber-coupled TES is consistent with Black Body Radiation (BBR) as the primary background contributor. A framework was developed to simulate BBR propagation to the TES under realistic conditions. The framework not only allows the exploration of background reduction strategies, such as improving the TES energy resolution, but also reproduces, within uncertainties, the spectral distribution of the observed background. These simulations have been validated with experimental data, in agreement with the modeled background distribution, and show that the improved energy resolution reduces the background rate in the $1064\,\mathrm{nm}$ signal region by one order of magnitude, to approximately $10^{-4}\,\mathrm{cps}$. However, this rate must be reduced further to meet the ALPS II requirements.

Figures

Figures reproduced from arXiv: 2505.08555 by the authors.

Figure 1
Figure 1. Model of the TES reflectance as a function of the [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. (a) Loss per kilometer of a HI-1060 optical fiber [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 4
Figure 4. Example of the transmission as a function of [PITH_FULL_IMAGE:figures/full_fig_p004_4.png] view at source ↗
Figures from the paper (8 more)
Figure 3
Figure 3. Figure 3: Transmission data as a function of energy from the [PITH_FULL_IMAGE:figures/full_fig_p004_3.png]
Figure 5
Figure 5. Figure 5: Scheme of the simulated path in the BBR simula [PITH_FULL_IMAGE:figures/full_fig_p006_5.png]
Figure 6
Figure 6. Figure 6: (a) Fiber curled inside the cryostat approximated [PITH_FULL_IMAGE:figures/full_fig_p006_6.png]
Figure 7
Figure 7. Figure 7: BBR spectrum computed from Eq. 11, at a tem [PITH_FULL_IMAGE:figures/full_fig_p007_7.png]
Figure 8
Figure 8. Figure 8: The dashed curves represent the BBR spectra simulated at a temperature of 295 K, as explained in section IV, [PITH_FULL_IMAGE:figures/full_fig_p008_8.png]
Figure 9
Figure 9. Figure 9: Distribution of parameters obtained by fitting the phenomenological model in a, c and e, and the frequency domain [PITH_FULL_IMAGE:figures/full_fig_p009_9.png]
Figure 10
Figure 10. Figure 10: Measured extrinsics energy spectrum computed using the pulse integral from the time domain analysis (blue) and [PITH_FULL_IMAGE:figures/full_fig_p010_10.png]
Figure 11
Figure 11. Figure 11: Simulated spectrum in Fig. 8, folded with an energy resolution of 5.3 %, compared to the measured rates from [PITH_FULL_IMAGE:figures/full_fig_p011_11.png]

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