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REVIEW 3 major objections 4 minor 248 references

Search for an Anomalous Excess of Single Photons in the MicroBooNE Neutrino Experiment

T0 review · 3 major / 4 minor · reviewed 2026-08-15 · deepseek-v4-flash

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Pith's one-line read MicroBooNE finds no excess of single photons from neutrino-induced Delta radiative decays, but cannot rule out photon sources with no visible proton.

desk verdict A solid, honest MicroBooNE doctoral thesis with a genuinely new single-photon selection and a null result whose visible-proton leg is robust and whose 0p leg is explicitly model-dependent. read the letter →

arxiv 2506.18956 v1 pith:ZTVFXSSR submitted 2025-06-23 hep-ex

Lee Hagaman This is my paper · ORCID
classification hep-ex
keywords singlephotonsearchMicroBooNEliquidargontimeprojectionchamberneutralcurrentDeltaradiativedecayMinilowenergyexcessphoton-likeneutrinoanomalyLEEhypothesis
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

MicroBooNE set out to test whether the anomalous low-energy excess seen by MiniBooNE could be made of photon showers rather than electron showers, and this thesis targets the largest expected source of single photons: neutral-current $\Delta$ radiative decays. Using a joint Wire-Cell and Pandora selection, the analysis observes data consistent with nominal expectations and finds no significant excess of single photons. Hypothesis tests that scale the NC $\Delta$ radiative decay rate to match MiniBooNE's LEE exclude large parts of the scaling plane when the photons come with a visible proton, but leave the no-visible-proton axis open. If the result holds, explanations of the MiniBooNE LEE that produce single photons with visible protons are disfavored at the tested energies; photon-like explanations with invisible protons remain viable.

What carries the argument

The load-bearing object is the $NC\Delta\to N\gamma$ single-photon selection, built by combining two independent LArTPC reconstructions: Wire-Cell 3D imaging and Pandora pattern recognition. The selection isolates events with one electromagnetic shower and uses electron-photon discrimination (a gap between vertex and shower, and the $dE/dx$ at the shower stem) to identify photons; the hypothesis tests then scan the scaling factor $x_\Delta$ (multiplying the nominal NC $\Delta$ radiative rate) and the fraction $x_{0p}$ of single photons with no visible proton, a parameter introduced because the data cannot constrain the true-0p efficiency. The machinery also includes the true-0p efficiency maps and the systematic covariance, which carry the analysis from reconstructed kinematics to the exclusion contours.

What would settle it

A dedicated re-analysis of the same data that tags single-photon events with no reconstructed proton—for example by using a control sample of $e^+e^-$ pairs to measure the true-0p efficiency—and finds a significant low-energy excess would directly contradict the paper's claim of consistency with expectation. Concretely, recomputing the one-bin count with the true-0p efficiency doubled and photonuclear absorption reduced by 30% would show whether the nominal prediction is robust.

Watch

Extended reading notes

Core claim

The central claim is that the joint Wire-Cell + Pandora selection for neutral-current $\Delta$ radiative decays ($NC\Delta\to N\gamma$) in MicroBooNE finds data consistent with the nominal background prediction, with no significant excess of single-photon events. The analysis quantifies this by testing the 'enhanced NC $\Delta$' version of the MiniBooNE LEE hypothesis, in which the NC $\Delta$ radiative decay rate is scaled by a factor $x_\Delta$, and a more general two-parameter hypothesis in which a fraction $x_{0p}$ of the photons have no visible proton. The data exclude large regions of the ($x_\Delta$, $x_{0p}$) plane, particularly where the photons are accompanied by visible protons, but cannot exclude the $x_{0p}$-only axis. In the author's words, the data are consistent with expectation but cannot rule out all potential sources of additional single photons, especially those with no visible proton activity.

Load-bearing premise

The null result rests on the simulation's prediction for single photons that leave no visible proton—the topology the thesis explicitly says it cannot constrain—so if GENIE's photon production or photonuclear absorption, or the 0p reconstruction efficiency, is wrong, the apparent consistency could hide a real photon excess.

Editorial extensions

If this is right

  • If the central claim is right, the enhanced NC Delta radiative decay explanation of the MiniBooNE LEE is disfavored whenever the photon is accompanied by a visible proton at MicroBooNE's energies.
  • The two-parameter exclusion in ($x_\Delta$, $x_{0p}$) means any NC Delta-like LEE model that requires a large visible-proton fraction is ruled out, while models living on the no-visible-proton axis survive.
  • The result demonstrates that joint Wire-Cell + Pandora single-photon selections can constrain photon-like LEE explanations and provides a reusable framework for such searches.
  • Data being consistent with nominal expectation implies no new single-photon source is needed to describe the current MicroBooNE sample, within the untested 0p region.
  • The 0p channel is the clear next target: the analysis's own efficiency maps show where future sensitivity must improve.

Reading between the lines

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

  • I read the 0p axis as the place where a photon-like LEE could still be hiding; a natural next step would be a selection that sacrifices visible-proton purity to recover low-energy 0p showers and uses the measured 0p efficiency as a fit parameter.
  • The same ($x_\Delta$, $x_{0p}$) scaling-plane technique could be applied to other single-photon searches, such as coherent or inclusive single photons, to map out which photon production mechanisms are compatible with the null result.
  • Because GENIE's photonuclear absorption is a leading modeling uncertainty, a data-driven measurement of photon survival in argon would strengthen or overturn the conclusion; the thesis's own Geant4 EM modifications show this modeling is not settled.
  • If a future liquid-argon experiment with lower proton thresholds finds a 0p single-photon excess, it would revive the photon interpretation of the MiniBooNE LEE that this result 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

3 major / 4 minor

Summary. The dissertation reports a search for an anomalous excess of single photons in MicroBooNE, targeting neutral-current Delta radiative decays (NC Delta to N gamma). It develops a joint Wire-Cell plus Pandora selection, evaluates backgrounds with GENIE simulation and a MicroBooNE tune, constrains systematic uncertainties with nu-mu-CC and NC-pi0 sidebands, and tests the MiniBooNE LEE under scaled NC Delta-like hypotheses characterized by parameters x_Delta and x_0p. The observed data are reported as consistent with the nominal prediction, and the analysis excludes parts of the (x_Delta, x_0p) plane while leaving the zero-visible-proton (0p) axis open, as stated in the abstract.

Significance. If the result holds, it disfavors photon-like explanations of the MiniBooNE LEE that would produce NC Delta radiative single photons accompanied by a visible proton, and it provides a detailed experimental template for single-photon searches in LArTPCs. The analysis has notable strengths: selection development on a small blinded subset (Sec. 3.3.3), nine detector systematic universes (Sec. 2.4), conditional constraints from nu-mu-CC and NC-pi0 sidebands (Sec. 4.5.3), fake-data closure tests (Appendix A), and a combination of two independent reconstruction chains. The external benchmark built from MiniBooNE's measured excess is not derived from MicroBooNE's own fit, so the exclusion test is not circular. The principal weakness is that the 0p topology, on which the thesis explicitly concedes no constraint, is also the place where the simulation-dependent prediction is least tested.

major comments (3)
  1. [Sec. 4.5.1, Fig. 4.35; Secs. 5.2.2-5.2.3; Secs. 4.39-4.43; Sec. 5.3.1] The central null statement 'data consistent with our nominal expectation' includes the 0p channel, but the true-0p efficiency and 0p shower efficiencies are presented as simulation-only quantities with no data closure test for that topology. The thesis itself documents a GENIE branching-ratio bugfix, material differences between GENIE FSI models for single photons (Figs. 4.39-4.43), and ad hoc Geant4 electromagnetic model modifications (Sec. 5.3.1). As written, the quoted consistency with expectation for the 0p component is therefore not robust: a genuine 0p photon excess could be absorbed into the simulated prediction if the true 0p efficiency or photonuclear absorption differs from the model. Please either add a data-driven 0p validation/sideband constraint or explicitly rescope the consistency claim to the visible-proton topology and quantify how large a 0p excess could be hidden within the quoted uncertainties.
  2. [Sec. 4.6.5, Figs. 4.73 and 4.75] Section 4.6.5 introduces x_0p precisely because data cannot pin down the zero-proton fraction, and the resulting exclusion leaves the x_0p axis open. The conclusions should therefore always carry the qualifier 'with visible proton activity' when describing excluded NC Delta-like LEE hypotheses. The abstract already states this caveat, but the chapter-level summary and the captions of Figs. 4.73-4.75 should be equally explicit so that a reader does not walk away with the impression that 0p-only models are tested.
  3. [Sec. 4.5.3, Table 4.4] The conditional constraint uses nu-mu-CC and NC-pi0 sidebands. These channels share flux and cross-section systematics with the single-photon signal, but they do not directly constrain the 0p single-photon reconstruction efficiency or the photonuclear-absorption model for 0p photons. The post-constraint uncertainties in Table 4.4 may therefore be underestimated for the 0p channel. The text should state this limitation explicitly and either provide an unconstrained 0p systematic or demonstrate a quantitative correlation between the sideband channels and the 0p acceptance.
minor comments (4)
  1. [Acknowledgments and throughout] Several typographical errors should be corrected, including 'instutitions', 'componentns', 'descripancy', and 'decomissioning'.
  2. [Fig. 2.7 caption] The caption reads 'tob, left, right, and bottom panels'; this should be 'top, left, right, and bottom panels'.
  3. [Sec. 2.4.4] The phrase 'We finished finished processing' contains a duplicated word and should be revised.
  4. [Chapters 4-5] The notation for the signal process is inconsistent (NC Delta, NC Delta radiative decay, NC Delta to N gamma). Define the notation once and use it consistently throughout.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the tested LEE hypotheses are fixed by external MiniBooNE data, the MicroBooNE null result is compared to an externally benchmarked prediction, and the 0p gap is a stated limitation rather than a self-referential input.

full rationale

The paper's central claim is a null result: data are consistent with the nominal expectation for NC Delta radiative single-photon events, with the explicit caveat that no-visible-proton (0p) sources cannot be ruled out (abstract). The hypotheses tested in Chapter 4 are defined from the MiniBooNE low-energy excess, an external dataset, not from a fit to MicroBooNE's own signal region; the eLEE model in Sec. 3.4.1 is explicitly an unfolding of the MiniBooNE LEE into true neutrino energy, and the NC Delta LEE scaling parameters are likewise external benchmarks whose values MicroBooNE data are used to constrain rather than to define. The conditional constraint procedure uses MicroBooNE sidebands for nuisance parameters, which is disclosed and standard practice, and it does not fit the signal-strength parameter being tested. The thesis's reliance on prior MicroBooNE/collaboration work for reconstruction and detector modeling is a normal use of shared experimental infrastructure, not a load-bearing self-citation that defines the physics result; the quoted model dependence of the 0p efficiency and GENIE photon modeling is an acknowledged uncertainty and a limitation, not a circular reduction. No step was found in which a prediction is equivalent by construction to an input, a fitted parameter is renamed as a prediction, or a uniqueness claim is imported from the authors' prior work.

Assumptions & free parameters 4 free parameters · 5 assumptions · 0 invented entities

The thesis pulls its central prediction from GENIE v3.0.6 with the MicroBooNE tune, Geant4-based detector simulation with nine variation universes, and the MiniBooNE LEE measurement. The genuinely paper-specific free parameters are the LEE test scalings x_Δ and x_0p in §4.6.4-4.6.5. No new entities are invented.

free parameters (4)
  • x_Δ (enhanced NC Delta LEE scaling) = not stated in available excerpt; exclusion ranges quoted in §4.6.4
    Fractional scaling of the NC Delta to N gamma component needed to reproduce the MiniBooNE LEE; used as the test parameter in §4.6.4 'Tests of the Enhanced NC Delta MiniBooNE LEE Hypothesis'.
  • x_0p (zero-proton fraction of LEE) = not stated in available excerpt; exclusion in (x_Δ, x_0p) plane in §4.6.5
    Parameterizes the fraction of LEE single-photon events with no visible proton, the topology the thesis cannot constrain; enters the 2D LEE exclusion tests (§4.6.5).
  • eLEE x strength = x=1 median unfolding; fractional scalings considered
    Chapter 3's νeCC analysis tests fractional scalings of the electron-LEE model unfolded from MiniBooNE data (§3.4.1).
  • BDT cut thresholds = νeCC BDT cut 7, νμCC BDT cut 0.9 (Chapter 3 selections)
    Selection thresholds chosen to maximize efficiency times purity on simulation (§3.3.3), with data blinded; analogous cuts are used for the Chapter 4 NC Delta selections.
assumptions (5)
  • domain assumption GENIE v3.0.6 with the MicroBooNE tune G18_10a_02_11a provides an adequate model of neutrino-argon interactions, including photon and π0 production rates.
    The nominal expectation in Chapters 3 and 4 is defined by this simulation; entered in §3.4.2 and used throughout §4.5 for the signal and background prediction.
  • domain assumption The nine detector-variation universes (space charge, recombination, wire response, light yield, etc.) span the true detector response uncertainty.
    Systematic covariance in §2.4 and §4.5.3 is built from differences between the central value and these nine variations; if the true response lies outside this envelope, the quoted errors are underestimated.
  • domain assumption NC Delta to N gamma is the largest expected source of single photons in MicroBooNE, so a search targeting it can bound photon-like LEE hypotheses.
    Motivates the whole search design in §4.2.
  • ad hoc to paper The MiniBooNE LEE can be represented as a scaled NC Delta-like signal, and the zero-proton fraction x_0p is a meaningful, transferable parameter.
    Phenomenological mapping used for the hypothesis tests in §4.6.4-4.6.5; its validity across detector technologies is assumed rather than demonstrated.
  • domain assumption Photonuclear absorption cross sections and the modified Geant4 electromagnetic model describe photon propagation in argon correctly.
    Photon background rates depend on this modeling (§5.3.1, Figs. 4.40-4.43); incorrect photonuclear rates would bias the single-photon background estimate.

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Cite this review

Pith. "Pith review of Search for an Anomalous Excess of Single Photons in the MicroBooNE Neutrino Experiment." pith.science (2026). https://pith.science/paper/ZTVFXSSR

@misc{pith2026250618956,
  author       = {Pith},
  title        = {Pith review of: Search for an Anomalous Excess of Single Photons in the MicroBooNE Neutrino Experiment},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/ZTVFXSSR}},
  note         = {Machine review of arXiv:2506.18956}
}
read the original abstract

Neutrinos are some of the most elusive particles in the standard model, being incredibly common throughout the universe, but interacting with detectors incredibly rarely. Certain properties of neutrinos remain difficult to measure, including their masses, their CP violation properties, and whether or not they are their own antiparticles. Additionally, there have been several anomalous results in neutrino experiments which remain unexplained. MicroBooNE was built in order to study these anomalous results using a more capable detector technology, the Liquid Argon Time Projection Chamber. Specifically, MicroBooNE is able to search for an anomalous excess of low energy electromagnetic showers, which was previously observed by the MiniBooNE experiment. In particular, MicroBooNE is able to study whether the excess could consist of electron showers or photon showers. In this thesis, I describe a search for this anomalous excess by targeting neutral current Delta radiative decays, the largest expected source of single photons in MicroBooNE. We observe data consistent with our nominal expectation, but cannot rule out all potential sources of additional single photon events, particularly those with no visible proton activity. There remains significant potential to probe this channel in even more detail using MicroBooNE and other experiments in the near future.

Figures

Figures reproduced from arXiv: 2506.18956 by the authors.

Figure 1.1
Figure 1.1. Beta decay spectrum of radium and radium daughters, showing a continuous [PITH_FULL_IMAGE:figures/full_fig_p017_1_1.png] view at source ↗
Figure 1.2
Figure 1.2. Beta decay spectrum for different neutrino masses, predicted by Fermi in 1933 [PITH_FULL_IMAGE:figures/full_fig_p018_1_2.png] view at source ↗
Figure 1.3
Figure 1.3. Crossing symmetry between beta decay and inverse beta decay neutrino scatter [PITH_FULL_IMAGE:figures/full_fig_p018_1_3.png] view at source ↗
Figures from the paper (220 more)
Figure 1.4
Figure 1.4. Figure 1.4: Neutrino oscillation probabilities starting from the [PITH_FULL_IMAGE:figures/full_fig_p023_1_4.png]
Figure 1.5
Figure 1.5. Figure 1.5: Visualization of some neutrino oscillation experiment baselines and energies. [PITH_FULL_IMAGE:figures/full_fig_p023_1_5.png]
Figure 1.6
Figure 1.6. Figure 1.6: Neutrino oscillation parameter uncertainties over time. Figure taken from Ref. [PITH_FULL_IMAGE:figures/full_fig_p024_1_6.png]
Figure 1.7
Figure 1.7. Figure 1.7: Neutrino mass ordering possibilities, showing flavor fractions for each mass [PITH_FULL_IMAGE:figures/full_fig_p026_1_7.png]
Figure 1.8
Figure 1.8. Figure 1.8: Neutrino mass correlations. Code for this plot is available at [40]. [PITH_FULL_IMAGE:figures/full_fig_p028_1_8.png]
Figure 1.9
Figure 1.9. Figure 1.9: Neutrino oscillation probabilities starting from the [PITH_FULL_IMAGE:figures/full_fig_p032_1_9.png]
Figure 1.10
Figure 1.10. Figure 1.10: Visualization of some neutrino oscillation experiment baselines and energies, [PITH_FULL_IMAGE:figures/full_fig_p033_1_10.png]
Figure 1.11
Figure 1.11. Figure 1.11: Reactor Neutrino Anamaly as a function of distance, taken from Ref. [54]. [PITH_FULL_IMAGE:figures/full_fig_p034_1_11.png]
Figure 1.12
Figure 1.12. Figure 1.12: Reactor Antineutrino Anamaly allowed 3+1 sterile neutrino phase space, taken [PITH_FULL_IMAGE:figures/full_fig_p034_1_12.png]
Figure 1.13
Figure 1.13. Figure 1.13: Evidence for sterile neutrinos from Neutrino-4 [67]. Panel (a) shows the spec [PITH_FULL_IMAGE:figures/full_fig_p036_1_13.png]
Figure 1.14
Figure 1.14. Figure 1.14: Evidence for sterile neutrinos from GALLEX, SAGE, and BEST [72]. Panel [PITH_FULL_IMAGE:figures/full_fig_p037_1_14.png]
Figure 1.15
Figure 1.15. Figure 1.15: Evidence for sterile neutrinos from the LSND experiment [53]. Panel (a) shows [PITH_FULL_IMAGE:figures/full_fig_p038_1_15.png]
Figure 1.16
Figure 1.16. Figure 1.16: Illustration of MiniBooNE Cherenkov cone event reconstruction. Figure from [PITH_FULL_IMAGE:figures/full_fig_p039_1_16.png]
Figure 1.17
Figure 1.17. Figure 1.17: Panel (a) shows the MiniBooNE Low Energy Excess as a function of [PITH_FULL_IMAGE:figures/full_fig_p040_1_17.png]
Figure 1.19
Figure 1.19. Figure 1.19: 3+1 sterile neutrino summary from Ref. [80]. [PITH_FULL_IMAGE:figures/full_fig_p042_1_19.png]
Figure 1.20
Figure 1.20. Figure 1.20: Tension between νe and νµ disappearance searches and νe appearance searches. The red shows the region allowed by νe appearance searches, and the area to the left of the blue lines is the region allowed by νµ disappearance searches. From Ref. [83] To summarize, there…
Figure 1.21
Figure 1.21. Figure 1.21: Panel (a) shows the MiniBooNE νe-like cos θ distribution. The best-fit sterile oscillation parameters sin22θ = 0.807 and ∆m2 = 0.043 eV2/c4 are indicated with a dashed line. Panel (b) shows the MiniBooNE excess visible energy and cos θ distribution. From Ref. [73]. …
Figure 1.22
Figure 1.22. Figure 1.22: Illustration of the dark neutrino model from Ref. [84]. The top interaction [PITH_FULL_IMAGE:figures/full_fig_p045_1_22.png]
Figure 1.23
Figure 1.23. Figure 1.23: HNL e +e − production Feynman diagram, covering a wide range of models. The upscattering of a neutrino ν interacting with a nucleus to an HNL N can happen either before or after entering the MiniBooNE detector. The final neutrino ν could be an additional sterile sta…
Figure 2.1
Figure 2.1. Figure 2.1: LArTPC operation principle illustration. Figure from Ref. [112]. [PITH_FULL_IMAGE:figures/full_fig_p052_2_1.png]
Figure 2
Figure 2. Figure 2: shows a rendering of the MicroBooNE detector showing the field cage inside [PITH_FULL_IMAGE:figures/full_fig_p053_2.png]
Figure 8
Figure 8. Figure 8: The TPC inside the cryostat looking up the [PITH_FULL_IMAGE:figures/full_fig_p053_8.png]
Figure 2.3
Figure 2.3. Figure 2.3: MicroBooNE’s steel cryostat. Panel (a) shows the cryostat being lowered into [PITH_FULL_IMAGE:figures/full_fig_p054_2_3.png]
Figure 2.4
Figure 2.4. Figure 2.4: MicroBooNE’s TPC consisting of the cathode plane, field cage, and anode wires. [PITH_FULL_IMAGE:figures/full_fig_p056_2_4.png]
Figure 2.5
Figure 2.5. Figure 2.5: MicroBooNE’s PMTs. Panel (a) shows a diagram of a PMT assembly. Panel [PITH_FULL_IMAGE:figures/full_fig_p058_2_5.png]
Figure 2.6
Figure 2.6. Figure 2.6: MicroBooNE’s PMT wavelength response. This plot illustrates how the argon [PITH_FULL_IMAGE:figures/full_fig_p059_2_6.png]
Figure 2.7
Figure 2.7. Figure 2.7: Diagram of MicroBooNE’s cosmic ray tagger system, consisting of tob, left, right, [PITH_FULL_IMAGE:figures/full_fig_p060_2_7.png]
Figure 2.8
Figure 2.8. Figure 2.8: This steering mirror is then adjusted to aim through various parts of the TPC for [PITH_FULL_IMAGE:figures/full_fig_p060_2_8.png]
Figure 2.8
Figure 2.8. Figure 2.8: MicroBooNE’s laser. Panel (a) shows a diagram of the external laser optical [PITH_FULL_IMAGE:figures/full_fig_p061_2_8.png]
Figure 2.9
Figure 2.9. Figure 2.9: Purity monitors of the same design as those in MicroBooNE. Panel (a) shows [PITH_FULL_IMAGE:figures/full_fig_p062_2_9.png]
Figure 2.10
Figure 2.10. Figure 2.10: MicroBooNE dQ/dx vs residual range from data observations, with a clearly visible high dQ/dx band from protons, and lower dQ/dx band from muons, and a flat dQ/dx band from muons exiting the TPC. The increase in dQ/dx near the end of each tracks is known as the Bragg…
Figure 2.11
Figure 2.11. Figure 2.11: MicroBooNE wire modification hit charge and width ratios between data and [PITH_FULL_IMAGE:figures/full_fig_p066_2_11.png]
Figure 2.12
Figure 2.12. Figure 2.12: MicroBooNE light calibration over time. Updated relative to Ref. [131] with [PITH_FULL_IMAGE:figures/full_fig_p068_2_12.png]
Figure 2.13
Figure 2.13. Figure 2.13: Illustration of the Fermilab neutrino beams. The path of BNB protons acceler [PITH_FULL_IMAGE:figures/full_fig_p069_2_13.png]
Figure 2.14
Figure 2.14. Figure 2.14: 53 [PITH_FULL_IMAGE:figures/full_fig_p069_2_14.png]
Figure 2.14
Figure 2.14. Figure 2.14: Fermilab’s linear accelerators. Panel (a) shows the extraction cone electrode, [PITH_FULL_IMAGE:figures/full_fig_p070_2_14.png]
Figure 2.15
Figure 2.15. Figure 2.15: Fermilab’s Booster accelerator. Panel (a) shows an interior view of the Booster [PITH_FULL_IMAGE:figures/full_fig_p071_2_15.png]
Figure 2.16
Figure 2.16. Figure 2.16: Panel (a) shows the BNB beryllium air-cooled target. Panel (b) shows the BNB [PITH_FULL_IMAGE:figures/full_fig_p072_2_16.png]
Figure 2.17
Figure 2.17. Figure 2.17: BNB decay pipe and absorber, from Ref. [143]. [PITH_FULL_IMAGE:figures/full_fig_p073_2_17.png]
Figure 2.18
Figure 2.18. Figure 2.18: MicroBooNE BNB beam diagram. Adapted from Ref. [144]. [PITH_FULL_IMAGE:figures/full_fig_p073_2_18.png]
Figure 2.19
Figure 2.19. Figure 2.19: BNB flux spectrum, from Ref. [145]. In addition to the BNB, MicroBooNE sees 8 ◦ off-axis flux from the NuMI beam, illus￾trated as a simplified diagram in [PITH_FULL_IMAGE:figures/full_fig_p074_2_19.png]
Figure 2.20
Figure 2.20. Figure 2.20: MicroBooNE NuMI beam diagram. From Ref. [144]. [PITH_FULL_IMAGE:figures/full_fig_p074_2_20.png]
Figure 2.21
Figure 2.21. Figure 2.21: Panel (a) shows the NuMI flux spectrum in FHC mode for [PITH_FULL_IMAGE:figures/full_fig_p075_2_21.png]
Figure 2.22
Figure 2.22. Figure 2.22: NuMI Main Injector. From Ref. [152]. 60 [PITH_FULL_IMAGE:figures/full_fig_p076_2_22.png]
Figure 2.23
Figure 2.23. Figure 2.23: NuMI target and horns. Panel (a) shows the NuMI target, appearing as a series [PITH_FULL_IMAGE:figures/full_fig_p077_2_23.png]
Figure 2.24
Figure 2.24. Figure 2.24: Panel (a) shows the NuMI decay pipe, and panel (b) shows the NuMI absorber. [PITH_FULL_IMAGE:figures/full_fig_p078_2_24.png]
Figure 2.25
Figure 2.25. Figure 2.25: MicroBooNE purity over time, as indicated by a metric from our purity mon [PITH_FULL_IMAGE:figures/full_fig_p079_2_25.png]
Figure 2.26
Figure 2.26. Figure 2.26: Mean νµCC muon median dQ/dx discrepancy between runs 1-3 and run 4b, before and after the predicted attenuation ratio fix. Panel (a) shows the discrepancy for simulation, and Panel (b) shows the descripancy for data. Runs 4a and 4b refer do different sub-periods of …
Figure 2.27
Figure 2.27. Figure 2.27: Electron attenuation ratio modeling for a 1.1 ms drift time (the mean drift time [PITH_FULL_IMAGE:figures/full_fig_p081_2_27.png]
Figure 2.28
Figure 2.28. Figure 2.28: Investigations of the run dependent light yield. The left panels (a), (c), and (e) [PITH_FULL_IMAGE:figures/full_fig_p083_2_28.png]
Figure 2.29
Figure 2.29. Figure 2.29: MicroBooNE single photoelectron waveforms. Figure from Ref. [155]. [PITH_FULL_IMAGE:figures/full_fig_p084_2_29.png]
Figure 2.30
Figure 2.30. Figure 2.30: MicroBooNE PMT gains over time. Each color shows a different PMT. There [PITH_FULL_IMAGE:figures/full_fig_p085_2_30.png]
Figure 2.31
Figure 2.31. Figure 2.31: PMT gains over time near run 4. Panel (a) shows the older [PITH_FULL_IMAGE:figures/full_fig_p086_2_31.png]
Figure 2.32
Figure 2.32. Figure 2.32: Neutrinos per POT over time, showing a notable decrease in run 4a. [PITH_FULL_IMAGE:figures/full_fig_p087_2_32.png]
Figure 2.33
Figure 2.33. Figure 2.33: BNB target scans. Panel (a) shows the horizontal scan, centered on the vertical [PITH_FULL_IMAGE:figures/full_fig_p088_2_33.png]
Figure 2.34
Figure 2.34. Figure 2.34: BNB beam monitor diagram. The proton beam starts at the top and passes [PITH_FULL_IMAGE:figures/full_fig_p088_2_34.png]
Figure 2.35
Figure 2.35. Figure 2.35: BNB measured position over time. The vertical dashed lines indicate the [PITH_FULL_IMAGE:figures/full_fig_p089_2_35.png]
Figure 2.36
Figure 2.36. Figure 2.36: VPTG unreliable behavior starting June 18, 2018. [PITH_FULL_IMAGE:figures/full_fig_p090_2_36.png]
Figure 2.37
Figure 2.37. Figure 2.37: Mistargeted beam simulation. So, now that we know that the deficit can be explained by reduced neutrino flux from this position offset, we run a full beam flux simulation, including all hadron productions and decays to investigate potential energy dependence due to …
Figure 2.38
Figure 2.38. Figure 2.38: Run 4a simulated beam position, shown via the density of simulated interac [PITH_FULL_IMAGE:figures/full_fig_p092_2_38.png]
Figure 2.39
Figure 2.39. Figure 2.39: Run 4a updated flux simulation. Panel (a) shows the on-center simulated flux in [PITH_FULL_IMAGE:figures/full_fig_p092_2_39.png]
Figure 3.1
Figure 3.1. Figure 3.1: MicroBooNE wire response for tracks with [PITH_FULL_IMAGE:figures/full_fig_p094_3_1.png]
Figure 3
Figure 3. Figure 3: shows the best case scenario, and there are a variety of factors that can make [PITH_FULL_IMAGE:figures/full_fig_p094_3.png]
Figure 3.2
Figure 3.2. Figure 3.2: Panel (a) shows the shorted U region in red, and the shorted Y region in blue. [PITH_FULL_IMAGE:figures/full_fig_p095_3_2.png]
Figure 3.3
Figure 3.3. Figure 3.3: MicroBooNE signal processing for an example U plane image, with the left [PITH_FULL_IMAGE:figures/full_fig_p097_3_3.png]
Figure 3.4
Figure 3.4. Figure 3.4: MicroBooNE signal processing for the V and Y planes, with the left showing the [PITH_FULL_IMAGE:figures/full_fig_p097_3_4.png]
Figure 3.5
Figure 3.5. Figure 3.5: Wire-Cell tiling. Panel (a) shows all wires which see charge at the same time [PITH_FULL_IMAGE:figures/full_fig_p099_3_5.png]
Figure 3.6
Figure 3.6. Figure 3.6: MicroBooNE dead wires. Panel (a) indicates the regions where at least one wire [PITH_FULL_IMAGE:figures/full_fig_p099_3_6.png]
Figure 3.7
Figure 3.7. Figure 3.7: Wire-Cell deghosting. Figure from Ref. [162]. [PITH_FULL_IMAGE:figures/full_fig_p101_3_7.png]
Figure 3.8
Figure 3.8. Figure 3.8: Wire-Cell 3D event display after all imaging steps. This corresponds to run 3493 [PITH_FULL_IMAGE:figures/full_fig_p102_3_8.png]
Figure 3.9
Figure 3.9. Figure 3.9: Wire-Cell 3D event display after clustering. The TPC boundary is outlined as [PITH_FULL_IMAGE:figures/full_fig_p104_3_9.png]
Figure 3.10
Figure 3.10. Figure 3.10: Wire-Cell charge-light matching for a simulated electron neutrino cluster. The [PITH_FULL_IMAGE:figures/full_fig_p106_3_10.png]
Figure 3.11
Figure 3.11. Figure 3.11: Wire-Cell pattern recognition stages for an example [PITH_FULL_IMAGE:figures/full_fig_p107_3_11.png]
Figure 3.12
Figure 3.12. Figure 3.12: A diagram of the important processes contributing to an electromagnetic shower. [PITH_FULL_IMAGE:figures/full_fig_p108_3_12.png]
Figure 3.13
Figure 3.13. Figure 3.13: Diagram of a sparse convolutional neural network of the type used for Wire-Cell [PITH_FULL_IMAGE:figures/full_fig_p110_3_13.png]
Figure 3.14
Figure 3.14. Figure 3.14: Panel (a) shows the charge information, and panel (b) shows the truth labeling. [PITH_FULL_IMAGE:figures/full_fig_p110_3_14.png]
Figure 3.15
Figure 3.15. Figure 3.15: MicroBooNE’s effective space charge boundary, determined by reconstructions [PITH_FULL_IMAGE:figures/full_fig_p113_3_15.png]
Figure 3.16
Figure 3.16. Figure 3.16: Panel (a) shows an example through-going muon cosmic event. Panel (b) shows [PITH_FULL_IMAGE:figures/full_fig_p115_3_16.png]
Figure 3.17
Figure 3.17. Figure 3.17: MicroBooNE Wire-Cell generic selected neutrino events as a function of recon [PITH_FULL_IMAGE:figures/full_fig_p116_3_17.png]
Figure 3.18
Figure 3.18. Figure 3.18: An example νeCC 1p candidate event. The candidate vertex is indicated with a sphere, with a candidate proton exiting to the bottom right and a candidate electron shower exiting to the top right. From NuMI Run 6365 subrun 0 event 21, with the 3D Wire-Cell display vie…
Figure 3.19
Figure 3.19. Figure 3.19: An example νµCC 0p candidate event. The candidate vertex is indicated with a sphere, and the candidate muon exits to the right, and experiences some distortion from multiple coulomb scattering before forming a Bragg peak and coming to rest. From BNB Run 5127 subrun …
Figure 3.20
Figure 3.20. Figure 3.20: An example NC π 0 1p candidate event. The candidate vertex is indicated with a sphere, with a candidate proton exiting upward, and two photons from a candidate π 0 exiting to the bottom left and bottom right. From BNB Run 5051 Subrun 31 Event 1573, with the 3D Wire-…
Figure 3.21
Figure 3.21. Figure 3.21: MicroBooNE event displays illustrating the features which allow electron-photon [PITH_FULL_IMAGE:figures/full_fig_p120_3_21.png]
Figure 3.22
Figure 3.22. Figure 3.22: Cut-based νeCC selection prediction for 5.3 · 1019 POT. In pink, we show the prediction from the LEE model, described in Sec. 3.4.1. Figure from Ref. [168]. Next, I will describe our inclusive νµCC selection. As shown in [PITH_FULL_IMAGE:figures/full_fig_p122_3_22.png]
Figure 3.23
Figure 3.23. Figure 3.23: Cut-based νµCC selection for fully contained events and 5.3 · 1019 POT of open data. Figure from Ref. [168]. Finally, I will describe our NCπ 0 and νµCCπ 0 selections. If an event contains at least two reconstructed showers, we create a π 0 candidate by choosing the…
Figure 3.24
Figure 3.24. Figure 3.24: Figures from Ref. [163]. 3.3.3 BDT-based Selections In the process of developing the cut-based selections, we identified many key variables with the power to discriminate between signal and background events. The key advantage of this human-designed cut-based proced…
Figure 3.25
Figure 3.25. Figure 3.25: AdaBoost diagram. Figure from Ref. [170]. [PITH_FULL_IMAGE:figures/full_fig_p125_3_25.png]
Figure 3.26
Figure 3.26. Figure 3.26: νeCC selection prediction for fully contained events using ROOT TMVA Ad￾aBoost BDTs, for 5.3 · 1019 POT. In pink, we show the prediction from the LEE model, described in Sec. 3.4.1. Figure from Ref. [168]. One of my first contributions in the Wire-Cell team was stud…
Figure 3.27
Figure 3.27. Figure 3.27: XGBoost diagram. Figure from Ref. [172]. [PITH_FULL_IMAGE:figures/full_fig_p126_3_27.png]
Figure 3.28
Figure 3.28. Figure 3.28: νeCC selection prediction for fully contained events using the XGBoost BDT, for 5.3 · 1019 POT. In pink, we show the prediction from the LEE model, described in Sec. 3.4.1. Figure from Ref. [168]. Figs. 3.29 and 3.30 show the efficiency and purity, prediction, and d…
Figure 3.29
Figure 3.29. Figure 3.29: Panel (a) shows the efficiency and purity of our [PITH_FULL_IMAGE:figures/full_fig_p129_3_29.png]
Figure 3.30
Figure 3.30. Figure 3.30: Panel (a) shows the efficiency and purity of our [PITH_FULL_IMAGE:figures/full_fig_p129_3_30.png]
Figure 3.31
Figure 3.31. Figure 3.31: Panel (a) shows the νeCC selection efficiency as a function of the neutrino energy. Panel (b) shows the νeCC selection efficiency as a function of the electron shower angle relative to the beam direction. Figures from Ref. [163]. 500 1000 1500 2000 2500 (MeV) True E…
Figure 3.32
Figure 3.32. Figure 3.32: Panel (a) shows the νµCC selection efficiency as a function of the neutrino energy. Panel (b) shows the νµCC selection efficiency as a function of the muon angle relative to the beam direction. Figures from Ref. [163]. 114 [PITH_FULL_IMAGE:figures/full_fig_p130_3_32.png]
Figure 3
Figure 3. Figure 3: shows the MiniBooNE LEE in reconstructed space, as well as the response [PITH_FULL_IMAGE:figures/full_fig_p131_3.png]
Figure 3.33
Figure 3.33. Figure 3.33: Panel (a) shows the MiniBooNE LEE as a function of reconstructed neutrino [PITH_FULL_IMAGE:figures/full_fig_p132_3_33.png]
Figure 3.34
Figure 3.34. Figure 3.34: Median unfolded νeCC LEE model. Panel (a) shows the unfolded result in MiniBooNE. Panel (b) shows the median unfolded result in MicroBooNE, with no selection applied. Figures from Ref. [174] and [163]. We label this median unfolded model as LEE (x=1), but in order t…
Figure 3.35
Figure 3.35. Figure 3.35: Out-cryostat simulated neutrino vertex positions, showing the effect of simulated [PITH_FULL_IMAGE:figures/full_fig_p134_3_35.png]
Figure 3.36
Figure 3.36. Figure 3.36: νeCC LEE systematic uncertainty breakdown. Panel (a) shows the fractional uncertainty from each type of systematic uncertainty, as well as the sum from all systematic uncertainties in quadrature in black. Panel (b) shows the relative contributions to each bin Figure…
Figure 3.37
Figure 3.37. Figure 3.37: νeCC LEE systematic uncertainty correlation matrix. Figure from Ref. [163]. 120 [PITH_FULL_IMAGE:figures/full_fig_p136_3_37.png]
Figure 3.38
Figure 3.38. Figure 3.38: Conditional constraint diagram [PITH_FULL_IMAGE:figures/full_fig_p138_3_38.png]
Figure 3.39
Figure 3.39. Figure 3.39: Panel (a) shows the reconstructed neutrino energy distribution for [PITH_FULL_IMAGE:figures/full_fig_p139_3_39.png]
Figure 3.40
Figure 3.40. Figure 3.40: Panel (a) shows the reconstructed neutrino energy distribution for [PITH_FULL_IMAGE:figures/full_fig_p141_3_40.png]
Figure 3.41
Figure 3.41. Figure 3.41: Panel (a) shows the νeCC FC reconstructed neutrino energy distribution after constraints from νµCC and π 0 channels. Panel (b) compares the distribution before and after constraints. Figures from Ref. [163]. From these spectra, we can pretty much immediately tell by…
Figure 3.42
Figure 3.42. Figure 3.42: Figures from Ref. [163]. We also assess what scaling factors of the median unfolded MiniBooNE LEE model are consistent with our data. We do this by calculating χ 2 nested = χ 2 null − χ 2 min, the difference between the χ 2 at the null hypothesis and the χ 2 at the …
Figure 3.43
Figure 3.43. Figure 3.43: νeCC LEEx exclusion. Figure from Ref. [163]. In [PITH_FULL_IMAGE:figures/full_fig_p144_3_43.png]
Figure 3.44
Figure 3.44. Figure 3.44: νeCC nested likelihood ratio test. Figure from Ref. [163]. 128 [PITH_FULL_IMAGE:figures/full_fig_p144_3_44.png]
Figure 1.21
Figure 1.21. Figure 1.21: Looking at our data in Fig. 3.45, we again see no sign of an excess at forward [PITH_FULL_IMAGE:figures/full_fig_p145_1_21.png]
Figure 3.45
Figure 3.45. Figure 3.45: Panel (a) shows the reconstructed shower angle distribution for [PITH_FULL_IMAGE:figures/full_fig_p145_3_45.png]
Figure 3.46
Figure 3.46. Figure 3.46: Reconstructed neutrino energy distributions for [PITH_FULL_IMAGE:figures/full_fig_p146_3_46.png]
Figure 3.47
Figure 3.47. Figure 3.47: Reconstructed neutrino energy distributions for [PITH_FULL_IMAGE:figures/full_fig_p147_3_47.png]
Figure 3.48
Figure 3.48. Figure 3.48: νeCC nested likelihood ratio test with and without selections split by proton multiplicity. Figure from Ref. [163]. I synthesized the results from this Wire-Cell νeCC search into the data release available at https://www.hepdata.net/record/ins1953539. 3.4.5 Other νe…
Figure 3.49
Figure 3.49. Figure 3.49: νeCC 0π results from Pandora reconstruction. Panel (a) shows events with one or more reconstructed protons, and panel (b) shows events without reconstructed protons. Figures from Ref. [184]. There was also an analysis which used deep learning based reconstruction te…
Figure 3.50
Figure 3.50. Figure 3.50: νeCC 1e1p QE-like results from DL reconstruction. Figure from Ref. [184]. We summarize the statistical tests from all of these analyses in [PITH_FULL_IMAGE:figures/full_fig_p150_3_50.png]
Figure 3.51
Figure 3.51. Figure 3.51: νeCC results from different reconstructions. Figures from Ref. [184]. More recently, we have updated the Pandora pionless analysis. We expanded the median unfolding MiniBooNE LEE model described in Sec. 3.4.1 in order to account for the electron shower energy and an…
Figure 3.52
Figure 3.52. Figure 3.52: νeCC 0π results from Pandora reconstruction. Figure from Ref. [188]. 3.5 3+1 Sterile Neutrino Results In the previous section, we carefully searched for a νe flux increase that matches the Mini￾BooNE LEE. We used a median unfolding of the MiniBooNE excess, which doe…
Figure 3.53
Figure 3.53. Figure 3.53: νeCC reconstructed energy distribution compared to the 3+1 sterile neutrino best fit parameters. Figure from Ref. [189]. For this analysis, there is an important degeneracy to consider: for certain parameters, 136 [PITH_FULL_IMAGE:figures/full_fig_p152_3_53.png]
Figure 3.54
Figure 3.54. Figure 3.54: BNB νe appearance and disappearance cancellation. Figure modified from from Ref. [189]. We form exclusion limits using the frequentist-motivated CLs method [190]. For each 3+1 sterile neutrino hypothesis point, we generate pseudo-experiments for both the standard th…
Figure 3.55
Figure 3.55. Figure 3.55: MicroBooNE BNB 3+1 sterile exclusions. Panel (a) shows the exclusion for [PITH_FULL_IMAGE:figures/full_fig_p154_3_55.png]
Figure 3.56
Figure 3.56. Figure 3.56: MicroBooNE BNB 3+1 sterile exclusions compared with the MiniBooNE LEE [PITH_FULL_IMAGE:figures/full_fig_p155_3_56.png]
Figure 3.57
Figure 3.57. Figure 3.57: νeCC appearance and disappearance cancellation. Figures from Ref. [192]. This leads to a significantly improved sensitivity when we include both the BNB and NuMI beams, as shown in [PITH_FULL_IMAGE:figures/full_fig_p156_3_57.png]
Figure 3.58
Figure 3.58. Figure 3.58: BNB+NuMI 3+1 sterile neutrino exclusion sensitivities. Figures from Ref. [PITH_FULL_IMAGE:figures/full_fig_p157_3_58.png]
Figure 4.1
Figure 4.1. Figure 4.1: Examples of how π 0 → γγ events can be mistaken for single photons in neutrino detectors. This means that for the single photon search described in this chapter, we should not have such high expectations as we had for the νeCC searches. In this more difficult topolog…
Figure 4.2
Figure 4.2. Figure 4.2: Photon radiation length in argon. Panel (a) shows the predicted mean free [PITH_FULL_IMAGE:figures/full_fig_p160_4_2.png]
Figure 4.3
Figure 4.3. Figure 4.3: NC ∆ → N γ Feynman diagrams. Panel (a) shows a neutrino exciting a proton to a ∆+ resonance which radiatively decays to a proton and photon, and panel (b) shows a neutrino exciting a neutron to a ∆0 resonance which radiatively decays to a neutron and photon. Accordin…
Figure 4.4
Figure 4.4. Figure 4.4: NC ∆ → N γ effective branching fraction in MicroBooNE. Figure from Ref. [200]. 4.2.1 NC ∆ Radiative Decay in MiniBooNE The majority of the photon background in MiniBooNE’s νeCC search is mis-reconstructed NC π 0 events where one photon is not properly identified, but…
Figure 4.5
Figure 4.5. Figure 4.5: MiniBooNE radial fit to NC ∆ scaling. Panel (a) shows the LEE radial distri￾bution, and panel (b) shows the radial distribution after scaling up NC ∆ radiative events by a factor of 3.18. Figures from Ref. [73]. 4.2.2 Previous Searches For NC ∆ Radiative Decay Inspir…
Figure 4.6
Figure 4.6. Figure 4.6: NOMAD single photon search. Panel (a) shows a single photon event, with [PITH_FULL_IMAGE:figures/full_fig_p164_4_6.png]
Figure 4.7
Figure 4.7. Figure 4.7: T2K NC ∆ → N γ search results. Panel (a) shows the energy distribution, and panel (b) shows the angle distribution. Figures from Ref. [202]. Both the NOMAD and T2K results can be interpreted as limits on the total NC 1γ cross section, as shown in [PITH_FULL_IMAGE:fi…
Figure 4.8
Figure 4.8. Figure 4.8: T2K and NOMAD NC ∆ exclusions, considering their neutrino energy ranges. Figures from Ref. [202]. 4.3 Pandora NC ∆ Radiative Decay Search in MicroBooNE Now, I will describe the first MicroBooNE search for single photons, specifically for the NC ∆ → N γ process using …
Figure 4.9
Figure 4.9. Figure 4.9: NC ∆ → N γ cross section predictions. Figure from Ref. [200]. This first single photon search in MicroBooNE used Pandora reconstruction [160]. Un￾like the Wire-Cell reconstruction method described in Sec. 3.2, Pandora performs particle clustering in each 2D view befo…
Figure 4.10
Figure 4.10. Figure 4.10: NC ∆ → N γ event displays. Panel (a) shows a candidate 1γ1p event, where one photon points back to the neutrino vertex which also produced a proton track, in run 9524 subrun 127 event 6375. Panel (b) shows a simulated 1γ0p event, where the neutrino interaction happe…
Figure 4.11
Figure 4.11. Figure 4.11: Constraining NC π 0 distributions used to constrain the Pandora NC ∆ radiative decay selections. Panel (a) shows events with reconstructed protons, and panel (b) shows events without reconstructed protons. Figures from Ref. [204] [PITH_FULL_IMAGE:figures/full_fig_p…
Figure 4.12
Figure 4.12. Figure 4.12: Correlation matrix between the Pandora NC [PITH_FULL_IMAGE:figures/full_fig_p170_4_12.png]
Figure 4.13
Figure 4.13. Figure 4.13: Pandora NC ∆ radiative decay results in one bin. The left of each panel shows the result before constraints, and the right of each panel shows the result after constraints. Panel (a) shows events with reconstructed protons, and panel (b) shows events without reconst…
Figure 4
Figure 4. Figure 4: , and in terms of the NC [PITH_FULL_IMAGE:figures/full_fig_p172_4.png]
Figure 4.14
Figure 4.14. Figure 4.14: Pandora NC ∆ radiative decay exclusion for x∆ scaling. Figure from Ref. [204]. In addition to the one-bin distributions, we also consider kinematic distributions, as shown in [PITH_FULL_IMAGE:figures/full_fig_p172_4_14.png]
Figure 4.15
Figure 4.15. Figure 4.15: Pandora NC ∆ radiative decay shower energy distributions. Each top panel shows the result before constraints, and the bottom panel shows the result both before and after constraints. Panel (a) shows events with reconstructed protons, and panel (b) shows events witho…
Figure 4.16
Figure 4.16. Figure 4.16: NC ∆ → N γ topologies predicted by GENIE. We break multiplicities down to 0, 1, M for multiple (greater than or equal to two), and X for any number (zero or greater than zero). Panel (a) shows the breakdown of initial state particles, just after the ∆ → N γ decay. P…
Figure 4.17
Figure 4.17. Figure 4.17: Flowchart of the Wire-Cell NC ∆ → N γ selection. We train the BDT to select simulated NC ∆ → N γ events from simulated backgrounds, including a high-statistics sample of NC π 0 events, and measured beam-off cosmic ray back￾grounds. This training consisted of 157,967…
Figure 4.18
Figure 4.18. Figure 4.18: Wire-Cell NC ∆ → N γ BDT training curves. Panel (a) shows the classification error, which functions as the loss being minimized. Panel (b) shows the area under the ROC curve. The performance on the validation set after the BDT training is shown in [PITH_FULL_IMAGE:…
Figure 4.19
Figure 4.19. Figure 4.19: Wire-Cell NC ∆ training results. Panel (a) shows the ROC curve, showing all possible efficiency vs purity values. Panel (b) shows the distribution of background and signal events as a function of BDT scores. Note that this only displays the small amount of training …
Figure 4.20
Figure 4.20. Figure 4.20: Wire-Cell NC ∆ → N γ BDT important variables. A final cut value was chosen at a BDT score of 2.61. As shown in [PITH_FULL_IMAGE:figures/full_fig_p179_4_20.png]
Figure 4.21
Figure 4.21. Figure 4.21: Wire-Cell NC ∆ → N γ BDT efficiency, purity, and efficiency times purity vs BDT score. Panels (a) and (c) show the performance for events with one or more recon￾structed protons, and panels (b) and (d) show the performance for events without recon￾structed protons. …
Figure 4.22
Figure 4.22. Figure 4.22: Wire-Cell NC ∆ → N γ neutrino energy resolution. Panel (a) shows the resolu￾tion for all NC ∆ → N γ events, and panel (b) shows the resolution for only Wire-Cell NC ∆ → N γ selected events. 165 [PITH_FULL_IMAGE:figures/full_fig_p181_4_22.png]
Figure 4.23
Figure 4.23. Figure 4.23: Wire-Cell NC ∆ → N γ resolution for deposited energy inside the TPC fiducial volume. Panel (a) shows the resolution for all NC ∆ → N γ events, and panel (b) shows the resolution for only Wire-Cell NC ∆ → N γ selected events. (a) (b) [PITH_FULL_IMAGE:figures/full_fi…
Figure 4.24
Figure 4.24. Figure 4.24: Wire-Cell NC ∆ → N γ shower resolution. Panel (a) shows the resolution for all NC ∆ → N γ events, and panel (b) shows the resolution for only Wire-Cell NC ∆ → N γ selected events. 166 [PITH_FULL_IMAGE:figures/full_fig_p182_4_24.png]
Figure 4.25
Figure 4.25. Figure 4.25: Wire-Cell NC ∆ → N γ shower angle resolution. Panel (a) shows the resolution for all NC ∆ → N γ events, and panel (b) shows the resolution for only Wire-Cell NC ∆ → N γ selected events. Before unblinding, a number of validations were performed to make sure that the …
Figure 4.26
Figure 4.26. Figure 4.26: One-bin Wire-Cell NC ∆ → N γ selection with NuMI data. Panel (a) shows 1γNp events, and panel (b) shows 1γ0p events. Detector systematics have not been included. 168 [PITH_FULL_IMAGE:figures/full_fig_p184_4_26.png]
Figure 4.27
Figure 4.27. Figure 4.27: Reconstructed neutrino energy for the Wire-Cell NC [PITH_FULL_IMAGE:figures/full_fig_p185_4_27.png]
Figure 4.28
Figure 4.28. Figure 4.28: Reconstructed primary shower energy for the Wire-Cell NC [PITH_FULL_IMAGE:figures/full_fig_p185_4_28.png]
Figure 4.29
Figure 4.29. Figure 4.29: Reconstructed shower cos(θ) for the Wire-Cell NC ∆ → N γ selection with NuMI data. Panel (a) shows 1γNp events, and panel (b) shows 1γ0p events. Events reconstructed with default values have been removed. Detector systematics have not been included. −3 10 −2 10 −1 1…
Figure 4.30
Figure 4.30. Figure 4.30: Reconstructed Wire-Cell NC ∆ → N γ BDT scores for generic neutrino selected events with a reconstructed shower in NuMI data. Panel (a) shows all Np events, and panel (b) shows all 1γ0p events. Events with a score above 2.61 (dashed line) are included in the selectio…
Figure 4.31
Figure 4.31. Figure 4.31: Panel (a) shows efficiencies as a function of true neutrino energy. Panel (b) [PITH_FULL_IMAGE:figures/full_fig_p187_4_31.png]
Figure 4.32
Figure 4.32. Figure 4.32: NC ∆ → N γ proton energy efficiencies. Error bars show binomial statistical uncertainties on each efficiency calculation. The gray histogram shows the shape of all true NC ∆ → N γ events [PITH_FULL_IMAGE:figures/full_fig_p188_4_32.png]
Figure 4.33
Figure 4.33. Figure 4.33: NC ∆ → N γ 1D shower kinematic efficiencies. Panel (a) shows efficiencies as a function of true primary photon shower energy. Panel (b) shows efficiencies as a function of true primary photon angle with respect to the beam. Error bars show binomial statistical uncer…
Figure 4.34
Figure 4.34. Figure 4.34: 2D shower kinematic efficiencies for all NC [PITH_FULL_IMAGE:figures/full_fig_p190_4_34.png]
Figure 4.35
Figure 4.35. Figure 4.35: 2D shower kinematic efficiencies for NC ∆ → N γ with zero true primary protons of any energy as functions of true primary shower energy and angle with respect to the beam. Panel (a) shows the Wire-Cell 1γ0p selection, and panel (b) shows the Pandora 1γ0p selection. …
Figure 4
Figure 4. Figure 4: shows efficiencies as functions of variables that involve both the proton and the [PITH_FULL_IMAGE:figures/full_fig_p191_4.png]
Figure 4.36
Figure 4.36. Figure 4.36: 1γ1p NC ∆ → N γ proton kinematic efficiencies. Panel (a) shows efficiencies as a function of the true primary proton kinetic energy. Panel (b) shows efficiencies as a function of the true primary proton angle with respect to the beam. Error bars show binomial statis…
Figure 4.37
Figure 4.37. Figure 4.37: True 1γ1p NC ∆ → N γ efficiencies involving both the proton and photon. Panel (a) shows efficiencies as a function of the proton-photon opening angle. Panel (b) shows efficiencies as a function of the proton-photon invariant mass. The gray histogram shows the shape …
Figure 4.38
Figure 4.38. Figure 4.38: Wire-Cell and Pandora overlap Venn diagram. [PITH_FULL_IMAGE:figures/full_fig_p194_4_38.png]
Figure 4.39
Figure 4.39. Figure 4.39: GENIE branching ratio bugfix. We then carefully tested our GENIE uncertainty code to try to understand why this 181 [PITH_FULL_IMAGE:figures/full_fig_p197_4_39.png]
Figure 4.40
Figure 4.40. Figure 4.40: Photonuclear absorption in argon. Panel (a) shows a measurement of the pho [PITH_FULL_IMAGE:figures/full_fig_p201_4_40.png]
Figure 4.41
Figure 4.41. Figure 4.41: A diagram illustrating the fact that π 0 and η particles will produce photons outside of the nuclear medium, while ∆ particles will produce photons inside of the nucleus, and therefore those photons could undergo final state interactions with the nuclear medium. Our…
Figure 4.42
Figure 4.42. Figure 4.42: Photon energies and parent particles from 1,000,000 [PITH_FULL_IMAGE:figures/full_fig_p204_4_42.png]
Figure 4.43
Figure 4.43. Figure 4.43: Single photons from different GENIE FSI models. Panel (a) shows the energy [PITH_FULL_IMAGE:figures/full_fig_p205_4_43.png]
Figure 4.44
Figure 4.44. Figure 4.44: NC [PITH_FULL_IMAGE:figures/full_fig_p206_4_44.png]
Figure 4.45
Figure 4.45. Figure 4.45: NC ∆ → N γ detector response systematic uncertainty breakdown. In order to constrain our systematic uncertainties, we use NC π 0 and νµCC observa￾tions, both with and without reconstructed protons. Our NC π 0 constraining sidebands are updated relative to those desc…
Figure 4.46
Figure 4.46. Figure 4.46: NC ∆ → N γ constraining channels. These uncertainties are highly correlated with our predictions in the signal channels, as shown in [PITH_FULL_IMAGE:figures/full_fig_p208_4_46.png]
Figure 4.47
Figure 4.47. Figure 4.47: Correlation matrix between NC ∆ → N γ signal channels and constraining sideband channels. This correlation matrix R is constructed from the covariance matrix Σ by Σij/ p ΣiiΣjj . The resulting reduction in systematic uncertainties is shown in [PITH_FULL_IMAGE:figur…
Figure 4.48
Figure 4.48. Figure 4.48: NC ∆ → N γ constrained systematic uncertainties. 4.6 Joint Wire-Cell+Pandora NC ∆ Radiative Decay Results With our selection finalized and careful checks of small BNB data samples, NuMI data samples, and fake data studies, and careful consideration of all systematic…
Figure 4.49
Figure 4.49. Figure 4.49: Wire-Cell NC ∆ → N γ overlaid event displays. The color corresponds to the amount of ionization energy per unit length. Panel (a) shows the x-z view, and Panel (b) shows the y-z view, with dead wires indicated by gray shading. 195 [PITH_FULL_IMAGE:figures/full_fig_…
Figure 4.50
Figure 4.50. Figure 4.50: Wire-Cell NC ∆ → N γ overlaid event displays. The color corresponds to the reconstructed event for each 3D space point. Panel (a) shows the x-z view, and Panel (b) shows the y-z view, with dead wires indicated by gray shading [PITH_FULL_IMAGE:figures/full_fig_p212_…
Figure 4.51
Figure 4.51. Figure 4.51: NC ∆ → N γ BDT score distributions. We show only events passing the preselection, which consists of Wire-Cell generic neutrino selection plus the existence of a reconstructed shower. Panels (a) and (c) shows events with one or more reconstructed protons, and panels …
Figure 4.52
Figure 4.52. Figure 4.52: NC ∆ → N γ one bin observations. We performed a series of goodness of fit χ 2/ndf tests, both before and after the conditional constraint, as shown in [PITH_FULL_IMAGE:figures/full_fig_p214_4_52.png]
Figure 4
Figure 4. Figure 4: shows distributions of reconstructed protons and charged pions. We see that [PITH_FULL_IMAGE:figures/full_fig_p215_4.png]
Figure 4.53
Figure 4.53. Figure 4.53: Wire-Cell NC ∆ → N γ reconstructed particle multiplicities. Panel (a) shows the reconstructed number of protons, and panel (b) shows the reconstructed number of charged pions. No systematic uncertainties are considered, and no conditional constraint has been applied…
Figure 4.54
Figure 4.54. Figure 4.54: Wire-Cell NC ∆ → N γ selections with simpler required reconstructed topolo￾gies. Panel (a) shows the 1γ1p0π ± selection and panel (b) shows the 1γ0p0π ± selection. No systematic uncertainties are considered, and no conditional constraint has been applied. 200 [PITH…
Figure 4.55
Figure 4.55. Figure 4.55: Wire-Cell and Pandora NC ∆ → N γ overlapping selection. No systematic uncertainties are considered, and no conditional constraint has been applied. 201 [PITH_FULL_IMAGE:figures/full_fig_p217_4_55.png]
Figure 4.56
Figure 4.56. Figure 4.56: Wire-Cell and Pandora NC ∆ → N γ partially overlapping selections. Panel (a) shows events which have a reconstructed proton in both reconstructions, panel (b) shows events which have no reconstructed protons in either reconstructions, panel (c) shows events which ha…
Figure 4
Figure 4. Figure 4: shows reconstructed shower energy distributions for Wire-Cell selected events. [PITH_FULL_IMAGE:figures/full_fig_p219_4.png]
Figure 4.57
Figure 4.57. Figure 4.57: shows reconstructed shower energy distributions for Pandora selected events [PITH_FULL_IMAGE:figures/full_fig_p219_4_57.png]
Figure 4.58
Figure 4.58. Figure 4.58: Wire-Cell NC ∆ → N γ shower energy distributions. Panels (a) and (c) shows events with one or more reconstructed protons, and panels (b) and (d) show events with zero reconstructed protons. Panels (a) and (b) show the distributions with a breakdown of different pred…
Figure 4
Figure 4. Figure 4: summarizes all four reconstructed shower energy distributions after con [PITH_FULL_IMAGE:figures/full_fig_p220_4.png]
Figure 4.59
Figure 4.59. Figure 4.59: NC ∆ → N γ shower energy summary. The Pandora and Wire-Cell data samples correspond to 6.80 × 1020 and 6.37 × 1020 POT, respectively [PITH_FULL_IMAGE:figures/full_fig_p221_4_59.png]
Figure 4.60
Figure 4.60. Figure 4.60: Pandora NC ∆ → N γ shower angle distributions. The x-axis shows the cosine of the angle between the reconstructed shower direction and the neutrino beam direction. Panels (a) and (c) shows events with one reconstructed proton, and panels (b) and (d) show events with…
Figure 4.61
Figure 4.61. Figure 4.61: Wire-Cell NC ∆ → N γ shower angle distributions. The x-axis shows the cosine of the angle between the reconstructed shower direction and the neutrino beam direction. Panels (a) and (c) shows events with one or more reconstructed protons, and panels (b) and (d) show …
Figure 4.62
Figure 4.62. Figure 4.62: Wire-Cell NC ∆ → N γ 2D shower kinematics, with no conditional constrained applied. Panel (a) shows the predicted events, panel (b) shows the observed data events, and panel (c) shows data minus prediction. Events with and without reconstructed final state protons h…
Figure 4.63
Figure 4.63. Figure 4.63: Wire-Cell NC ∆ → N γ 2D shower kinematics, with the conditional constrained applied. Panel (a) shows the predicted events, panel (b) shows the observed data events, and panel (c) shows data minus prediction. Events with and without reconstructed final state protons …
Figure 4.64
Figure 4.64. Figure 4.64: MiniBooNE LEE 2D shower kinematics. Panel (a) shows the predicted events, [PITH_FULL_IMAGE:figures/full_fig_p225_4_64.png]
Figure 4.66
Figure 4.66. Figure 4.66: We see no notable data/prediction differences in any of these distributions. [PITH_FULL_IMAGE:figures/full_fig_p225_4_66.png]
Figure 4.65
Figure 4.65. Figure 4.65: Wire-Cell NC ∆ → N γ distance to the nearest TPC boundary. Panel (a) shows events with reconstructed protons, and panel (b) shows events without reconstructed protons. No systematic uncertainties are considered, and no conditional constraint has been applied. 0 200 …
Figure 4.66
Figure 4.66. Figure 4.66: Wire-Cell NC ∆ → N γ backwards projected distance to the nearest TPC boundary. Panel (a) shows events with reconstructed protons, and panel (b) shows events without reconstructed protons. No systematic uncertainties are considered, and no condi￾tional constraint has…
Figure 4
Figure 4. Figure 4: shows our data compared to this [PITH_FULL_IMAGE:figures/full_fig_p227_4.png]
Figure 4.67
Figure 4.67. Figure 4.67: NC ∆ → N γ one bin results with the x∆ = 3.18 LEE prediction. The Pandora and Wire-Cell data samples correspond to 6.80 × 1020 and 6.37 × 1020 POT, respectively. 0.0 0.5 1.0 1.5 2.0 2.5 Events Observed / Nominal Prediction WC 1γNp Pandora 1γ1p WC 1γ0p Pandora 1γ0p B…
Figure 4.68
Figure 4.68. Figure 4.68: NC ∆ → N γ one bin ratio results. The Pandora and Wire-Cell data samples correspond to 6.80 × 1020 and 6.37 × 1020 POT, respectively. 212 [PITH_FULL_IMAGE:figures/full_fig_p228_4_68.png]
Figure 4.69
Figure 4.69. Figure 4.69: NC ∆ → N γ two-hypothesis tests. The Pandora and Wire-Cell data samples correspond to 6.80 × 1020 and 6.37 × 1020 POT, respectively. Next, we consider expanded LEE hypotheses consisting of a wide range of possible x∆ values beyond just x∆ = 1 and x∆ = 3.18. This is …
Figure 4.70
Figure 4.70. Figure 4.70: NC ∆ → N γ 1D x∆ LEE sensitivity and data exclusion. We show the ∆χ 2 values and CL values as functions of x∆, for Wire-Cell, Pandora, and Wire-Cell+Pandora. We then show resulting error bars based on the 68% and 90% CL values. Panel (a) shows the sensitivity, calcu…
Figure 4.71
Figure 4.71. Figure 4.71: NC ∆ → N γ 1D x∆ LEE sensitivity and data exclusion by topology. We show the ∆χ 2 values and CL values as functions of x∆ for each of our four signal channels. We then show resulting error bars based on the 68% and 90% CL values. Panel (a) shows the sensitivity, cal…
Figure 4.72
Figure 4.72. Figure 4.72: NC ∆ → N γ 2D LEE exclusion CL values. Panels (a), (b), and (c) show Wire-Cell, Pandora, and Wire-Cell+Pandora sensitivities via an Asimov data set. Panels (d), (e), and (f) show Wire-Cell, Pandora, and Wire-Cell+Pandora real data results. To visualize these results…
Figure 4.73
Figure 4.73. Figure 4.73: NC ∆ → N γ 2D (xN p, x0p) LEE sensitivity and data exclusion. We show 90% CL contours for Wire-Cell, Pandora, and Wire-Cell+Pandora. Panel (a) shows the sensitivity, calculated with an Asimov data set which exactly matches the prediction. Panel (b) shows the real da…
Figure 4.74
Figure 4.74. Figure 4.74: NC ∆ → N γ comparison with 0p-only LEE model, corresponding to the (xN p, x0p) = (1, 6) point in our 2D LEE model phase space, which is consistent with a total 3.18 times enhancement matching the MiniBooNE prediction for an NC ∆ → N γ enhancement. Naively, we would …
Figure 4.75
Figure 4.75. Figure 4.75: NC ∆ → N γ 2D (x∆, x0p)LEE exclusion sensitivity and data result A data release from the combined Wire-Cell+Pandora NC ∆ → N γ analysis is available at https://www.hepdata.net/record/158531. 223 [PITH_FULL_IMAGE:figures/full_fig_p239_4_75.png]
Figure 5.1
Figure 5.1. Figure 5.1: NC coherent single photon results. From Ref. [208]. [PITH_FULL_IMAGE:figures/full_fig_p241_5_1.png]
Figure 5.2
Figure 5.2. Figure 5.2: 225 [PITH_FULL_IMAGE:figures/full_fig_p241_5_2.png]
Figure 5.2
Figure 5.2. Figure 5.2: Panel (a) shows a candidate inclusive single photon event from BNB data, Run [PITH_FULL_IMAGE:figures/full_fig_p242_5_2.png]
Figure 5.4
Figure 5.4. Figure 5.4: Super-Venn diagram example from Ref. [219]. [PITH_FULL_IMAGE:figures/full_fig_p243_5_4.png]
Figure 5.5
Figure 5.5. Figure 5.5: Overlapping data events. Panel (a) shows overlaps between each of the five [PITH_FULL_IMAGE:figures/full_fig_p244_5_5.png]
Figure 5.6
Figure 5.6. Figure 5.6: 2D shower kinematic efficiencies for NC ∆ → N γ events with no true primary proton with kinetic energy greater than 35 MeV. Panel (a) shows the Wire-Cell NC ∆ → N γ 1γ0p selection, panel (b) shows the Pandora NC ∆ → N γ 1γ0p selection, panel (c) shows the Pandora e +…
Figure 5.7
Figure 5.7. Figure 5.7: 2D shower kinematic efficiencies for NC ∆ → N γ events with no true primary proton with any kinetic energy. Panel (a) shows the Wire-Cell NC ∆ → N γ 1γ0p selection, panel (b) shows the Pandora NC ∆ → N γ 1γ0p selection, panel (c) shows the Pandora e +e − selection, p…
Figure 5.8
Figure 5.8. Figure 5.8: Proton energy efficiencies. 5.2.4 Photon Conversion Distance Efficiencies Lastly, we consider the efficiency as functions of the photon conversion distance, as shown in [PITH_FULL_IMAGE:figures/full_fig_p249_5_8.png]
Figure 5.9
Figure 5.9. Figure 5.9: Photon conversion distance efficiencies. [PITH_FULL_IMAGE:figures/full_fig_p250_5_9.png]
Figure 5.10
Figure 5.10. Figure 5.10: Geant4 EM modeling modifications. Panel (a) shows the Wire-Cell NC [PITH_FULL_IMAGE:figures/full_fig_p251_5_10.png]
Figure 5.11
Figure 5.11. Figure 5.11: PMT photon libraries. Panels (a), (b), and (c) show the nominal light maps, [PITH_FULL_IMAGE:figures/full_fig_p252_5_11.png]
Figure 5.12
Figure 5.12. Figure 5.12: Reconstructed light modification by position. The exact same events are sim [PITH_FULL_IMAGE:figures/full_fig_p253_5_12.png]
Figure 5.13
Figure 5.13. Figure 5.13: Reconstructed light modification BDT scores. Panel (a) shows NC [PITH_FULL_IMAGE:figures/full_fig_p254_5_13.png]
Figure 5.14
Figure 5.14. Figure 5.14: Geometric in-fiducial-volume BDT. We show correlations between each input [PITH_FULL_IMAGE:figures/full_fig_p256_5_14.png]
Figure 5.15
Figure 5.15. Figure 5.15: Deep learning e +e − opening angle identification. 5.4.3 3D Second Shower Veto For Misclustered π 0 s Another important background category for all of these single-photon-like selections is mis￾clustered π 0 events. In these events, both photon showers are visible i…
Figure 5.16
Figure 5.16. Figure 5.16: 3D spacepoints in a mis-clustered π 0 event. Reconstructed cosmic and neutrino points have been downsampled using furthest-point-sampling, and then have been identified as true neutrino or true cosmic using proximity to simulated Geant4 energy depositions. 5.4.4 Oth…

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Reviewed August 15, 2026 · model on record in the stance chip above.