First measurement of the total inelastic cross section of positively charged kaons on argon at energies between 5.0 and 7.5 GeV

Abstract

ProtoDUNE Single-Phase (ProtoDUNE-SP) is a 770-ton liquid argon time projection chamber that operated in a hadron test beam at the CERN Neutrino Platform in 2018. We present a measurement of the total inelastic cross section of charged kaons on argon as a function of kaon energy using 6 and 7 GeV / c beam momentum settings. The flux-weighted average of the extracted inelastic cross section at each beam momentum setting was measured to be 380 ± 26 mbarns for the 6 GeV / c setting and 379 ± 35 mbarns for the 7 GeV / c setting.

Published by the American Physical Society 2024

Full text

First measurement of the total inelastic cross section of positively charged
kaons on argon at energies between 5.0 and 7.5 GeV
A. Abed Abud et al.*
(DUNE Collaboration)
(Received 2 August 2024; accepted 20 September 2024; published 14 November 2024)
ProtoDUNE Single-Phase (ProtoDUNE-SP) is a 770-ton liquid argon time projection chamber that
operated in a hadron test beam at the CERN Neutrino Platform in 2018. We present a measurement of the
total inelastic cross section of charged kaons on argon as a function of kaon energy using 6 and 7GeV=c
beam momentum settings. The flux-weighted average of the extracted inelastic cross section at each beam
momentum setting was measured to be 380 26 mbarns for the 6GeV=c setting and 379 35 mbarns for
the 7GeV=c setting.
DOI: 10.1103/PhysRevD.110.092011
I. INTRODUCTION
Liquid argon time projection chambers (LArTPCs) may
be used to measure the trajectories of charged particles with
millimeter resolution. This capability makes the detectors,
like those of the Deep Underground Neutrino Experiment
(DUNE) far detector modules, sensitive to studying GeV-
scale and MeV-scale neutrinos and searching for physics
beyond the Standard Model [1]. An example of important
physics that can be done using the DUNE far detector
modules is a search for proton decay to a final state with a
neutrino and a charged kaon (p→νþKþ), which is
predicted to be dominant in a broad class of supersymmetric
grand unified theories [2–6]. Unlike searches in water
Cherenkov detectors [7], DUNE can detect the final-state
kaon, which has a momentum of 330 MeV=c absent final-
state interactions. The efficiency of observing this signature
is sensitive to modeling kaon transport in the LAr medium,
which is limited by the dearth of kaon-argon scattering
data. This search for nucleon decay requires a representa-
tive model of kaon transport and interactions in liquid
argon to ensure an accurate simulation of signal events.
Without reliable data and simulations, the relevant uncer-
tainties for the kaon cross section on argon cannot be
constrained. This can lead to large systematic uncertainties
in nucleon decay searches with a potentially biased cross-
section model.
As a first step toward collecting high-quality kaon-
argon interaction data, the ProtoDUNE Single-Phase
(ProtoDUNE-SP) large-scale prototype of a DUNE far
detector module was exposed to a test beam from the
H4-VLE beamline at CERN that included kaons at 6 and
7GeV=c [8,9]. ProtoDUNE-SP is a 770-ton LArTPC with
the same drift distance and full-scale engineering parts as a
DUNE Far Detector Horizontal Drift module. It measures
the tracking and calorimetry of charged particles by
detecting the ionization electrons that drift toward three
layers of wire planes. The H4-VLE beamline, a tertiary
beam from the CERN Super Proton Synchrotron, is
referred to as simply the “beam”in many places in this
paper. ProtoDUNE-SP collected data from the beam, using
many beamline momentum settings, over two months from
September 2018 to November 2018.
The data from ProtoDUNE-SP can be used by event
generators that simulate hadron-nucleus interactions, like
the neutrino event generator
GENIE
[10–14] and the trans-
port and interaction simulation program
GEANT
4[15–17],
to improve the modeling of kaon interactions on argon
nuclei. The kaon-argon cross section has never been
measured as a function of energy on argon. Therefore,
the purpose of this analysis is to provide the first meas-
urement of the total inelastic cross section of kaons on
argon at these high energies. Neither
GENIE
nor
GEANT
4has
recommended uncertainties for kaon-argon interactions,
providing a unique opportunity for ProtoDUNE-SP to
inform inputs on associated modeling uncertainties.
In this work, the kaon-argon total inelastic cross section
is reported as a function of kaon energy within the limits of
the detection threshold, described in Sec. IV. Figure 1
shows the total inelastic and the elastic cross section
predicted by the
GEANT
4Bertini cascade model [15–17].
Charged kaons produced by the beam with kinetic energies
of approximately 4.5 to 7 GeV are capable of reaching the
liquid argon of ProtoDUNE-SP. Using the
GEANT
4pre-
diction from Fig. 1, the simulated total inelastic cross
*Full author list given at the end of the article.
Published by the American Physical Society under the terms of
the Creative Commons Attribution 4.0 International license.
Further distribution of this work must maintain attribution to
the author(s) and the published article’s title, journal citation,
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PHYSICAL REVIEW D 110, 092011 (2024)
2470-0010=2024=110(9)=092011(22) 092011-1 Published by the American Physical Society

section at the relevant energies should be approximately
450 millibarns (mbarns).
Section II discusses ProtoDUNE-SP more broadly, and
Sec. III outlines the simulation and reconstruction of
ProtoDUNE-SP data. Section IV explains the thin slice
method used in this measurement. This method divides the
detector into thin targets, referred to as thin slices, using the
wires of the LArTPC to demarcate the slices. An incident
slice is counted if a particle reaches a particular wire.
Within that slice, it may also interact on the argon, which
means the slice contains both an incident and an interacting
slice. After an interacting slice is detected, the counting for
the event stops as the outgoing particles have unknown
identities and energies. The cross section is measured using
the counts of the incident and interacting slices as a
function of kinetic energy.
Section Vdescribes the selection of candidate kaon
interaction events, and Sec. VI shows energy-related
measurements using selected kaons. Section VII reports
the kaon-argon cross section with comparisons to models.
Section VIII discusses the evaluations of the statistical and
systematic uncertainties.
II. PROTODUNE-SP AND THE H4-VLE BEAMLINE
ProtoDUNE-SP is a 770-ton liquid argon detector that is
7.2 m wide, 6.1 m high, and 7 m long. It has two TPCs,
each with a drift distance of 3.6 m [9]. The detector
contains six readout wire planes called anode plane
assemblies (APAs), with three APAs for each drift volume.
Each APA contains three readout wire planes—the U, V,
and X wire planes—and are 6.2 m high, 2.3 m long, and
0.1 m thick [9]. The U and V wires are the first two planes
and detect drifting electrons via the currents induced on the
wires as the charges drift past them, creating bipolar
signals. The X wires, known as collection wires, have
unipolar signals where the drifting electrons collect on the
wires and stop drifting in the TPC [9]. The U, V, and X
wires are oriented 35.7°, −35.7°, and 0° relative to the
vertical direction, respectively. The pitch between wires is
0.467 cm for induction wires and 0.479 cm for collection
wires. Each APA has 960 X wires, 800 U wires, and
800 V wires.
Three APAs are installed in a 7 m line and sit in front of
one sidewall of the cryostat, and the other three APAs are
installed in a similar fashion in front of the opposite
sidewall of the cryostat. These APAs are 7.2 m away from
each other, and the cathode plane assembly (CPA) sits
midway between the two separate walls of APAs. The CPA
provides a high voltage of 180 kV, leading to a nominal
electric field strength of 500 V=cm across the 3.6 m
separating each APA from the CPA, which allows the
ionization electrons to drift to the APAs. The H4-VLE
beam pipe connects to the upstream face of LArTPC via a
low-density beam plug that allows the beam to enter
without scattering off the material in the cryostat [8,9].
The beam only enters one TPC of the detector. The beam
side of the detector has the vertical gap between APAs
instrumented with electron diverters that intend to improve
charge-collection efficiency for electrons drifting near the
gap between neighboring APAs. Unfortunately, these
electron diverters exhibited high-voltage shorts and were
left electrically grounded during operations, distorting the
track images and causing some loss of collected charge.
As a surface-based detector, ProtoDUNE-SP is exposed
to an intense flux of cosmic-ray muons, which create
electron-ion pairs in the detector. The argon ions drift
slower than the ionization electrons, leading to an excess of
ions around the surface of the detector. The excess of ions
creates a space charge effect that alters the local electric
field, leading to distorted calorimetry and tracking [19].
A calibration of the space charge effect is completed by
measuring the tracking distortions on the surfaces of the
detector, where the effect is maximal, with cosmic-ray
muon data [8]. The distortions measured are then used to
correct for local electric field fluctuations by using a
linearly interpolated three-dimensional map. An “inverted”
map using these data measurements is used to recreate the
space charge effect in simulation. The original three-
dimensional map is utilized to calibrate this effect in
simulation.
From September 2018 to early November 2018, the
H4-VLE beamline settings were adjusted to emit positively
charged particles at 0.3, 0.5, 1, 2, 3, 6, and 7GeV=c
beamline momentum settings. The beamline trigger oper-
ates at a rate of 25 Hz, which qualitatively translates to
beam particles being observed one at a time within
ProtoDUNE-SP. The beam consists of positively charged
protons, positrons, kaons, pions, and muons. The beam
particle species is identified using a time-of-flight system
and Cherenkov detectors. The beam particle momentum is
measured from the bend of the particle’s trajectory through
FIG. 1.
GEANT
4predicted total inelastic cross section and
elastic cross section of positively charged kaons on argon as a
function of kinetic energy [15–17]. Predictions made using
interfaces in Ref. [18].
A. ABED ABUD et al. PHYS. REV. D 110, 092011 (2024)
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a well-known magnetic field using data from tracking fibers
[8,20]. The 6GeV=c and 7GeV=c beam momentum
settings are the only settings that produce kaons that reach
ProtoDUNE-SP. The kaons are identified using only the
Cherenkov detectors, explicitly requiring a signal in the
high-pressure Cherenkov detector but no signal in the low-
pressure Cherenkov detector [8].
III. SIMULATION AND RECONSTRUCTION
A simulation of the beam, including its transport to and
through the LArTPC, is implemented using
GEANT
4
[15–17], with the entire CERN H4-VLE facility simulated
from the primary beam to the tertiary beam that reaches
ProtoDUNE-SP [20]. The selection of kaon inelastic
scattering events starts with the beamline instrumentation
discussed in Sec. II. A kaon event is defined as any time the
beamline instrumentation has a signal recorded by the high-
pressure Cherenkov detector and the absence of a signal
recorded by the low-pressure Cherenkov detector [8].
The rest of the selection steps rely on information from
the reconstruction of tracks and showers in the TPC to
select relevant events. Additionally, the beamline instru-
mentation also has tracking fibers to reconstruct a beam
track that can be extrapolated to the TPC [8,20]. These
steps will be described in Sec. V.
ProtoDUNE-SP uses the Pandora multialgorithm
reconstruction package to identify the beam particle,
reconstructing particle hierarchies using pattern recognition
[8,21,22]. It then employs a boosted decision tree to select
beam particle candidates that enter through the beam pipe
and beam plug into the liquid argon detector. A full
description of the software used in ProtoDUNE-SP is
given in Refs. [8,22].
Figure 2shows the observed and simulated distributions
of the reconstructed track lengths for events with a beam
kaon, as determined by the beamline instrumentation, for
the 6GeV=c samples. The corresponding distributions
for the reconstructed track lengths and all other event
selection distributions for the 7GeV=c samples showed
similar agreement and are included in the Appendix. The
spikes in Fig. 2at around 230 cm and 460 cm correspond
to broken tracks caused by the electron diverters that sit in
the gaps between the APAs, as discussed in the previous
section, with the last spike at around 700 cm correspond-
ing to the end of the active volume. Most TPC tracks are
secondary particles without any TPC-related selection
steps. An excess of short reconstructed track lengths is
observedinthedata,likelydrivenbybackgroundsec-
ondary particles.
The interaction point—or track endpoint—is determined
using clustering and vertex-finding algorithms that are
almost identical to those from the MicroBooNE
reconstruction and are described in detail in Ref. [23].
The initial clustering aims to make small clusters that
contain energy depositions from a single particle and avoid
erroneously clustering energy from multiple particles into a
single cluster. Numerous algorithms then associate these
pure clusters together, aiming to produce a single cluster
containing all energy depositions from a single particle. In
addition, algorithms are applied to split clusters if kinks are
found or where the topology suggests that there may be
contributions from multiple particles. These clusters are
classified as either tracks or showers based on their
topologies. Candidate 3D interaction points are produced
by comparing pairs of clusters from two 2D views and
reconstructing their start and end points as candidate
interaction points. Pandora uses a boosted decision tree
to select the vertex candidate most likely to correspond to
the interaction point of the beam particle. The signal
process is an inelastic interaction of the incident kaon.
An inelastic interaction in this analysis is defined as any
process where either:
(i) the angle between the beam kaon and leading
outgoing particle is greater than 11 degrees
(ii) two or more particles emerge from the interac-
tion point.
The kinetic energy threshold for observing a final-state
proton or charged kaon in the detector is 40 MeV, and for a
charged pion it is 20 MeV. We apply these restrictions to
our signal definition.
IV. METHODOLOGY
The cross-section measurements presented in this
paper use the thin slice method pioneered by the LArIAT
experiment [24,25]. The approach treats the detector as a
series of thin argon targets (slices). The number of surviv-
ing particles (Nsurv) is:
FIG. 2. Reconstructed track length for simulation and data
without any TPC-related selection steps at the 6GeV=c beamline
setting. Events in simulation are classified by the true identities
and fates of the reconstructed TPC tracks, including secondary
particles (sec.) from kaon interactions that are misidentified as the
beam particle. Only statistical uncertainties from the statistics in
data are shown. The statistics of the simulation are scaled to
match the normalization of all data events, including those
without a reconstructed track in the TPC.
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NsurvðdÞ¼Ninc exp ð−d=lÞ¼Ninc exp ð−σdnÞ;ð1Þ
where Ninc is the number of incident particles, dis the
distance traveled, and l¼ðnσÞ−1is the interaction length
of a kaon in argon, where nis the number density and σis
the cross section.
AnaturalwaytodevelopslicesinaLArTPCwitha
wire readout is to use the individual wires to demarcate
thin target slices from one another. Therefore, a slice is a
three-dimensional box of argon between wires. For each
particle, the incident energy at each thin slice is esti-
mated. The total number of particles at each incident
energy (Ninc) is counted, as are the total number of
interactions (Nint). Regardless of whether or not there was
an interaction, if an energy deposit from the kaon is
registered in a thin target slice, then the slice is counted in
the bin corresponding to the kinetic energy of the kaon in
that slice (Ninc). The cross section, using Eq. (1),is:
σðEkinÞ¼ MAr
NArρlnNincðEkinÞ
NincðEkinÞ−NintðEkinÞ;ð2Þ
where Ekin is the kinetic energy of the particle, NAis the
Avogadro constant, MAr is the atomic mass of argon, ρis
the density of liquid argon, and ris the three-dimensional
distance the particle travels from one wire to the next
[24,25]. The value of ris 0.498 cm, given the wire
spacing between the collection plane wires of 0.479 cm
and that the beam travels at a 16-degree angle in the
detector.
The kinetic energy at a given slice (Ekin;j) is recon-
structed as:
Ekin;j¼Ekin;beam −X
j−1
i¼0
ΔEi;ð3Þ
where Ekin;beam is the initial beam particle kinetic energy
and ΔEiis the measured energy lost in slice i. The total ΔE
is summed from all slices up to slice j.
Background subtractions, unsmearing, and efficiency
corrections are required to convert the measured inter-
action and incident spectra into a cross section. These
corrections are applied via RooUnfold with unfolding
done using a Bayesianlike unfolding algorithm imple-
mented based on Richardson-Lucy deconvolution
[26–30]. The process includes background subtraction,
unsmearing, and efficiency corrections. These correc-
tions are applied on the incident and interacting slice
distributions separately, an approach similar to that
previously used by LArIAT [25]. These unfolded dis-
tributions of the incident and interacting slices are then
used in Eq. (2) to measure the cross section as a function
of kinetic energy.
V. EVENT SELECTION
There are three event selection steps to select candidate
kaons and an additional step to select a candidate kaon with
an inelastic interaction. They include the following selec-
tion steps for events where the beamline trigger reports a
kaon candidate:
(i) the event must have a reconstructed TPC track.
(ii) the endpoint of the TPC track must enter the
fiducial volume by being at least 30 cm down-
stream of the start of the active volume of
the detector. This selection step is motivated by
significant inefficiencies and impurities in cor-
rectly identifying and reconstructing the beam
particle with a TPC track in the first 30 cm of
the detector.
(iii) the TPC track must be matched to the trajectory of
the beam track from the beamline instrumentation. A
match requires that their positions and angles agree
within three times the standard deviations of the
distributions for these measurements at the start of
the fiducial volume.
Because the electron diverters tend to break tracks, as
discussed in Sec. II, only the interaction and incident
slices contained before the point of 220 cm across the
detector length, which corresponds to collection plane
wire 464, are considered in the cross section measure-
ment. This is the final step. At each collection wire, the
kaon energy is estimated per Eq. (3), and the kaon either
undergoes an interaction or does not. Thus, for each
incident particle, we observe many “slices”and record
the interaction as a function of energy. The interaction
point—or vertex—identification occurs through Pandora
as described in Sec. III. Event displays of some selected
kaon inelastic interaction candidates are shown in Fig. 3.
In these events, the beam enters the TPC at time tick 4750,
where a time tick represents the 500 ns sampling intervals
of the analog-to-digital converters for the wires, and then
it travels over 50 cm before interacting with the argon. The
beam particles, highlighted by the black ovals, travel in
approximately straight lines from the left to the right
before scattering, creating complicated final states with
many showers. The top two event displays show little
shower activity, indicating they may be candidate events
with a final state with one positively charged kaon and
other nonstrange hadrons. The third event display shows a
complex interaction with many showers and tracks in the
final state.
Figure 4shows the distributions of reconstructed track
lengths for selected TPC tracks that will form the incident
and interacting slice spectra from the 6GeV=c beamline
setting. Secondary kaons, which are byproducts of true
beam kaons interacting off the argon and traveling with
some unknown kinetic energies, are the most significant
background for the event selection. As these secondary
kaons will have similar characteristics to beam kaons, they
A. ABED ABUD et al. PHYS. REV. D 110, 092011 (2024)
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are an irreducible background. The breakdown of the data
andsimulationsamplesthrougheachselectionstepare
shown in Table I.
The selection efficiency and purity are evaluated as a
function of kinetic energy from simulation. An inefficiency
in measuring a slice of kinetic energy occurs when no TPC
track corresponds to the beam particle in the slice. A
background slice occurs when there is a TPC track in a slice
that the true kaon does not reach. The definition for a
background slice is used regardless of whether the TPC
track is from a true kaon or not, which allows the analysis to
fully recover the truth-level distributions when unfolding
reconstruction information taken from the nominal simu-
lation. Results are shown in Fig. 5. The purity is close to
95% for interacting slices and 85% for incident slices. The
lower purity is because a single background particle
entering the detector contributes to many noninteracting
slices, but only a single inelastic interaction can occur per
particle. The efficiency varies between 35 and 40% as a
function of energy. The inefficiencies are dominated by
events with a true kaon in the fiducial volume, but the event
did not have a TPC track identified as the beam particle.
VI. ENERGY MEASUREMENTS AND BINNING
As referenced in Eq. (3), the initial kinetic energy is
determined using measurements from the beamline
FIG. 3. Three candidate event displays of selected beam kaons,
highlighted in black, that inelastically interact on the argon from
data taken in early November 2018. The beam travels from the
left to the right at an angle of approximately 16 degrees. Cosmic-
ray muons can be seen in the foreground and background of the
beam event, and a nonfunctioning wire can be observed
near wire 370.
FIG. 4. Reconstructed track length for simulation and data of
the 6GeV=c beamline setting for selected kaons (top) and for
selected kaons that interact within the fiducial volume (bottom).
Only statistical uncertainties are shown for the data, and the
statistics from the simulation are scaled to match those from
the data.
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instrumentation. Figure 6displays the beamline kinetic
energy measurements of the selected beam kaons. The
impact of the systematic uncertainty is found by shifting the
data distribution by the 1.2% kinetic energy modeling
uncertainty of the beamline simulation, which will be
discussed in greater detail in Sec. VIII.
The TPC calorimetry is calibrated by applying corrections
to the electric field variations, corrections for the spatial
variations, and an overall charge scale using through-going
and stopping cosmic-ray muons [8]. The energy resolution
was evaluated and done by measuring the difference
between the true and reconstructed kinetic energies at the
interaction points in the simulation. The minimum resolu-
tion is measured to be 124 MeV, as seen in Fig. 7.
TABLE I. Information on the fractions of the samples remaining for data and simulation after each selection step from the left
(beamline reports a candidate kaon) to the right (candidate kaon has an interaction in the fiducial volume). In this table, a beam kaon with
an inelastic interaction in the fiducial volume is defined as a signal event.
Selection step Beam (%) TPC track (%) Fiducial (%) Beam-TPC match (%) Contained interaction (%)
6GeV=c data 100.0 58.0 46.0 25.4 18.6
7GeV=c data 100.0 55.6 44.8 27.3 19.5
6GeV=c sim total 100.0 55.0 44.7 29.1 23.2
6GeV=c sim signal 24.9 24.4 24.0 21.8 20.9
6GeV=c sim bkg 75.1 30.6 20.7 7.3 2.2
7GeV=c sim total 100.0 45.1 36.5 24.0 19.1
7GeV=c sim signal 20.9 20.4 20.0 18.3 17.5
7GeV=c sim bkg 79.1 24.7 16.5 5.6 1.5
FIG. 5. Purity (top) and efficiency (bottom) of the event
selection for each bin for the 6GeV=c simulation sample.
FIG. 6. Initial beam particle kinetic energy as measured by the
beamline instrumentation for selected kaon candidate tracks for
the 6GeV=c beamline setting. Both systematic and statistical
uncertainties are shown.
FIG. 7. Kinetic energy resolution at the interaction point of
beam particles that pass all selection criteria for interacting kaons
in the 6GeV=c simulation sample. The distribution has a mean
energy bias of 0.50 MeV. The distribution is not scaled to the
statistics in the data.
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However, there are systematic uncertainties associated
with the simulation of the detector response and limited
statistics, making this not the definitive resolution. For
example, there is a 3% uncertainty on the calorimetry
calibration and a 1.2% uncertainty on the beam momentum
measurement, which corresponds to a maximum energy
discrepancy of approximately 80 MeV. The binning of the
analysis ensures equal statistics in each bin for the
reconstructed interacting slice distributions in the data
sample for both beam momentum settings. The minimum
bin size is then 260 MeV, which is greater than the
resolution measured in simulation and the uncertainties
from calorimetry.
The reconstructed slice distributions, highlighting
both the binning and slice distributions as a function of
energy, are shown for incident slices in Fig. 8and for
interacting slices in Fig. 9. Calorimetric-related uncer-
tainties, fully discussed in Sec. VIII, are applied to these
distributions.
VII. RESULTS
The kinetic energy distributions for all kaons—and for
interacting kaons—are separately unfolded using the
method of D’Agostini with four iterations [26–29]. The
smearing matrices are shown in Figs. 10 and 11. Studies
were done to test unfolding by altering the regularization,
not correcting for bin-to-bin smearing, and changing the
background subtraction and efficiency corrections. All had
an impact of less than a percent on the average cross section
compared to the nominal unfolding process described
above. The response matrix is obtained using only 66%
of the simulated data, which was done to use the remaining
33% as statistically independent fake data samples for
investigating systematic uncertainties.
The reconstructed slice spectra, shown in Figs. 8and 9,
are unfolded and then used to measure the cross section
with Eq. (2) with uncertainties that will be described in
Sec. VIII. Figure 12 displays the result for the data of the
FIG. 8. Reconstructed incident slice distributions between the
data and simulation for the 6GeV=c beamline setting (top) and
the 7GeV=c beamline setting (bottom). A calorimetric slice-by-
slice uncertainty of 3% and a beam kinetic energy scale
uncertainty of 1.2% are applied to the data. Statistics for the
simulation are scaled to match the normalization from the data.
FIG. 9. Reconstructed interacting slice distributions between
the data and simulation for the 6GeV=c sample (top) and the
7GeV=c sample (bottom). A calorimetric slice-by-slice uncer-
tainty of 3% and a beam kinetic energy scale uncertainty of 1.2%
are applied to the data. Statistics for the simulation are scaled to
match the normalization of incident slices from the data.
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6GeV=c sample with comparisons to predicted cross
sections from
GEANT
4,
GENIE
v3.2.0 hA2018, and
GENIE
v3.2.0
hN2018 [10–12,14–17,31].
GENIE
calculates the total cross
section using data and partial wave analysis [32].It
simulates interactions with either an empirical model
(hA2018) or a fully simulated cascade (hN2018) [11,14].
GEANT
4applies alterations of the base model cross section
using data sets included in the Particle Data Group
FIG. 10. Response matrices for the 6GeV=c simulation sample of the interacting (left) and incident (right) spectra. The entries in the
matrices are normalized so that the rows sum to one.
FIG. 11. Response matrices for the 7GeV=c simulation sample of the interacting (left) and incident (right) spectra. The entries in the
matrices are normalized so that the rows sum to one.
FIG. 12. Extracted total inelastic cross section from beam kaons at the momentum setting of 6GeV=c (left) with comparisons to
GENIE
v3.2.0 and
GEANT
4[10–12,14–17,31]. The relative uncertainties of the measurements are also shown (right). The hA2018 and
hN2018 cascade simulations of
GENIE
provide nearly the same prediction, and their distributions overlap.
A. ABED ABUD et al. PHYS. REV. D 110, 092011 (2024)
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summary cross-section measurements [33]. The reduced
chi-squared statistics between these models over four bins
are 11.26 for
GEANT
4and 13.33 for
GENIE
v3.2.0 hA2018. The
6GeV=c data sample flux-averaged cross section is mea-
sured at 380 26 mbarns. Table II shows the final results
with the breakdown of the uncertainties applied.
Figure 13 presents the cross section measured with data
at the 7GeV=c beam setting. The reduced chi-square
statistic measured divided by the number of bins is
2.64=2bins for
GEANT
4and 4.05=2bins for
GENIE
v3.2
hA2018.TableIII displays the final result with uncertainties
broken down by category. The flux-averaged cross
section is 379 35 mbarns for the 7GeV=c sample.
Encouragingly, the bin whose energy range overlaps with
the 6GeV=c sample has a similar measured cross section,
which is within uncertainties.
VIII. TREATMENT OF UNCERTAINTIES
Uncertainties are propagated by randomly sampling
statistical and systematic parameters 1000 times within
their a priori uncertainties [34]. The impact of the statistical
uncertainty on the individual kinetic energy bins of the
incident and interaction spectra is assessed by randomly
Poisson-fluctuating the number of entries in each bin
independently according to the measured counts. It is done
this way as the statistical uncertainty of the cross section is
not directly proportional to the statistical uncertainty of
interaction points given that the interaction and incident
distributions are inside a logarithm, as seen in Eq. (2).
However, there are enough statistics in the incident and
interacting distributions to assume both are Poisson-
distributed and uncorrelated; therefore, doing many inde-
pendent fluctuations of each bin can acquire the statistical
uncertainty on the cross section by remeasuring the cross
section with each Poisson-fluctuated sample. The resulting
uncertainty on the measured cross section is approximately
2.7%, as shown in Tables II and III.
The finite statistics of the simulation sample primarily
impact the analysis via the background subtraction,
unsmearing, and efficiency corrections. This effect is
propagated by varying the number of counts in each kinetic
energy bin for the backgrounds, inefficiencies, and within
the response matrix. Values from sampling a Poisson
distribution are used to regenerate the response matrices
TABLE II. Total inelastic positively charged kaon cross section
with uncertainties for data from the 6GeV=c momentum setting
beam. The total uncertainties (δtot) are broken down into the
systematic uncertainty (δsyst), statistical uncertainty from limited
data statistics (δData
stat ), and statistical uncertainty from limited
simulation statistics (δSim
stat ). All units for the cross section and
uncertainties are in millibarns.
Energy bin (MeV)
σinel
(mbarns) δtot δsyst δData
stat δSim
stat
4480–5080 369 47 44 13 10
5080–5340 435 63 60 16 12
5340–5610 368 51 48 13 10
5610–6170 366 54 50 15 10
FIG. 13. Extracted total inelastic cross section from beam kaons at the momentum setting of 7GeV=c (left) with comparisons to
GENIE
v3.2.0 and
GEANT
4[10–12,14–17,31]. The relative uncertainties of the measurements are also shown (right). The hA2018 and
hN2018 cascade simulations of
GENIE
provide nearly the same prediction, and their distributions overlap.
TABLE III. Total inelastic positively charged kaon cross
section with uncertainties for data from the 7GeV=c momentum
setting beam. The total uncertainties (δtot) are broken down into
the systematic uncertainty (δsyst), statistical uncertainty from
limited data statistics (δData
stat ), and statistical uncertainty from
limited simulation statistics (δSim
stat ). All units for the cross section
and uncertainties are in millibarns.
Energy bin (MeV)
σinel
(mbarns) δtot δsyst δData
stat δSim
stat
5520–6320 386 42 38 11 15
6320–7120 367 61 59 10 14
FIRST MEASUREMENT OF THE TOTAL INELASTIC CROSS …PHYS. REV. D 110, 092011 (2024)
092011-9

and affiliated corrections, with each bin treated as inde-
pendent from the others. As statistics in the incident slices
are significantly larger than those of the interacting slices,
by a factor of around 200 as shown in Fig. 8, this
uncertainty is only applied to the response matrix and
affiliated corrections for interacting slices.
The systematic uncertainties considered in this
analysis are related to the simulation of the beamline
and beamline instrumentation, the TPC response, the
hadron transport model, and instances in which modeling
and reconstruction of the TPC data are ill-posed. The
results from unfolding with the new response matrices are
used to address the total impact of the systematic effects
on the analysis.
The systematic term associated with the beamline
momentum scale arises from uncertainties in terms of
the position of the fiber monitors and the magnetic field
strength in the beamline instrumentation. This value was
calculated as 1.2% [35] of the beam particle energy.
Therefore, the energy of the beam kaon is fluctuated
according to a Gaussian distribution with width of 1.2%,
resulting in an approximately 2% uncertainty on the
measured cross section.
Furthermore, the particle itself can “scrape”against
material upon entering the liquid argon, losing energy in
the process. These beam “scrapers”should appear in
selections if their position is greater than 1.5 times the
radius of the beam away from the beam center (rbeam).
There are 3.15 times more selected events in data that
exceed this 1.5rbeam metric than in simulation. Therefore,
the systematic uncertainty treatment alters the frequency of
the beam “scrapers”with a central value weight of 3.15 and
a standard deviation of 2.15 to address the difference
between data and simulation. The weight upscales simu-
lation events whereby the beamline instrumentation system
momentum and truth information momentum at the TPC
differ by over 200 MeV, the estimated minimal energy lost
for a beam “scraper.”
A 3% calorimetric uncertainty from the TPC is assumed
in the energy determination. This value is taken from
evaluations of the calorimetry calibration uncertainty [36].
That study observed the spread in charge calibration results
from subsamples of cosmic-ray muons separated by their
trajectories in the detector, based on a similar analysis from
MicroBooNE [37]. Although the ProtoDUNE-SP study
measured 2% deviations in calibration values, a 3%
uncertainty is applied to address time-dependent fluctua-
tions in the spread of calibration results.
The space charge effect, as discussed in Sec. II, may alter
the reconstructed positions of particles. The fiducial vol-
ume is defined to reduce the impact of the space charge
effect on the track reconstruction efficiency. Mismodeling
of the space charge distribution in the TPC can be
effectively treated as shifts in the boundaries of the fiducial
volume. The impact of the uncertainty of the space charge
modeling is estimated using the spread in the mean
distortion at the surfaces of the detector over time. The
uncertainty on the spatial distortions from the space charge
effect was measured to be 8%.
The systematic uncertainty in this analysis arising from
mismodeling of charged kaon scattering is assessed by
using the
GEANT
4
REWEIGHT
package [18] to reweight
events based on the total signal cross section, which intends
to probe how the underlying simulated cross section
impacts the background subtraction and efficiency cor-
rections. The total inelastic cross section was varied by
20%. Additionally, differences in vertexing due to the
multiplicities and charges of kaons in the final state were
observed in the simulation. Therefore, the number of
interactions with one positively charged kaon and any
number of nonstrange hadrons in the final state, one of the
two dominant exclusive channels, is reweighted by 20%.
The weighting is done in a manner to hold the total cross
section constant. The other dominant channel, which
occurs as frequently, is a final state with a single neutral
kaon and any number of nonstrange hadrons. The impact
of all these modeling uncertainties is 2–6% on the cross
section per bin.
The impact of mismodeling the effect of the electron
diverter is determined by changing the frequency of
these events occurring in the incident response matrices.
The following uncertainty increases and decreases
the relative number of tracks broken by the electron
diverters. It only applies to tracks that do not end within
the fiducial volume, which means this weight only
impacts the incident slice spectrum. The uncertainty on
this effect is set to 100%, as the rate at which the electron
diverter breaks reconstructed tracks is not well simulated
and overpredicts the number of broken tracks, as seen
in Fig. 2.
While Pandora employs various algorithms to find the
end point of the beam particle, they may miss the vertex, as
Fig. 14 shows that the endpoint of the reconstructed track
may not exactly be the true endpoint. These events may still
have kaon inelastic scatters in the fiducial volume.
However, these events may underestimate or overestimate
the number of incident slices of the beam particle, biasing
the results. These tracks are called either broken or
extended tracks. An additional uncertainty term was
introduced to address the miscounting of incident slices
from inaccurate vertex positions, changing the “flux”in a
thin slice measurement. The uncertainty changes the
relative frequency of kaons in simulation with recon-
structed vertices that are more than 5 cm away from the
true interaction vertices. A 100% uncertainty on their
frequencies in simulation is assumed for both broken
and extended tracks, as data-driven constraints cannot be
provided on vertexing.
The fiducial volume is chosen to minimize the impact
of the tracking inefficiency. However, the TPC track
A. ABED ABUD et al. PHYS. REV. D 110, 092011 (2024)
092011-10

reconstruction may still have discrepancies in perfor-
mance between data and simulation not covered by the
space charge effect systematic uncertainty. Therefore, an
uncertainty of 6% is applied to events without a TPC
track, which is a conservative value from the measure-
ments of the efficiency for selecting a beam particle
in Ref. [22].
Table IV shows the 1σshifts for data from the
6GeV=c beamline setting. Table Vreveals the same shifts
for data from the 7GeV=c beamline setting. The dominant
uncertainties are the vertex identification uncertainty and
the uncertainties on the
GEANT
4model used in the
simulation. The former can be improved with in-depth
vertexing studies on how the reconstruction delineates
vertices and how much energy is required to create a
vertex or to stitch the parent and secondary. The latter
could be improved with the reduction of the background
of secondary kaons reconstructed as the beam particle as
the uncertainty alters the frequency of all kaons in
simulation, even those in events where the background
is selected by the TPC track reconstruction. There is
currently no known way to reduce the TPC track selection
choosing a secondary kaons, as the dE=dx would be
nearly identical to that of beam kaons.
IX. CONCLUSIONS
This paper describes a measurement of the total inelastic
cross section of positively charged kaons on argon with the
FIG. 14. Difference in the endpoint along the detector length
(Z) between the truth-level information and the calibrated
reconstructed information for the 6GeV=c simulation sample.
The mean offset measured in the 6GeV=c simulation sample is
0.539 cm with a standard deviation of 1.231 cm using a
Gaussian fit.
TABLE IV. Percent deviations from central-value data results by throwing positive one and negative one standard deviation shifts of
the uncertainty parameters for the 6GeV=c sample.
Uncertainty source (þ1σ
−1σ) 4480–5080 MeV (%) 5080–5340 MeV (%) 5340–5610 MeV (%) 5610–6170 MeV (%)
Beam modeling −1.79
1.58
2.50
−3.89
−0.74
1.71
4.01
0.51
dE=dx calibration 0.94
1.59
−0.71
−0.76
−0.96
−1.69
1.92
1.66
Space charge effect 1.28
1.92
−1.18
0.76
−2.04
0.28
2.05
4.42
GEANT
4modeling 6.84
−4.60
3.72
−5.60
1.98
−5.16
4.32
−0.64
Electron diverter effect 6.54
−1.24
3.11
−2.68
1.64
−2.73
2.42
3.43
Vertex identification 8.55
−6.25
9.37
−10.57
7.93
−10.18
13.44
−8.28
Events without a track 1.61
1.22
−0.29
−1.40
−1.05
−1.83
2.70
1.27
Simulation statistics −0.90
0.89
−1.81
2.12
−1.54
1.76
−2.27
2.48
Data statistics 2.65
−2.27
−4.80
−9.77
5.35
−0.06
6.58
−0.56
All uncertainties 13.38
8.82
12.08
16.38
10.35
12.25
16.88
10.56
TABLE V. Percent deviations from central-valuedata results by
throwing positive one and negative one standard deviation shifts
of the uncertainty parameters for the 7GeV=c sample.
Uncertainty
source (þ1σ
−1σ)
5520–6320 MeV
(%)
6320–7120 MeV
(%)
Beam modeling −2.38
−3.44
2.16
−0.10
dE=dx calibration 0.69
−0.61
0.18
1.41
Space charge effect −0.06
0.85
0.07
2.76
GEANT
4modeling 4.12
−4.23
2.57
−1.05
Electron diverter effect 3.77
−3.46
−1.69
3.46
Vertex identification 5.94
−7.24
14.76
−12.00
Events without a track 0.45
−0.56
1.50
−0.20
Simulation statistics −1.87
2.04
−2.59
3.05
Data statistics −0.79
−5.03
3.57
−1.46
All uncertainties 8.78
11.18
15.93
13.34
FIRST MEASUREMENT OF THE TOTAL INELASTIC CROSS …PHYS. REV. D 110, 092011 (2024)
092011-11

ProtoDUNE-SP detector using the thin slice method [25].
This measurement was done with data taken at the H4-
VLE at the CERN Neutrino Platform. A simple event
selection achieved a purity of approximately 85-90%
between kinetic energies of 4.5 and 7.0 GeV (Table I).
The results, at around 380 mbarns, have a precision of
approximately 14%, according to Tables II and III.The
total uncertainty almost entirely comes from systematic
uncertainties addressing the detector model and uncer-
tainties regarding the kaon cross-section model used in
GEANT
4. The measurements translate to
GEANT
4overesti-
mating the cross section by 16% and
GENIE
overestimating
the cross section by 19%. For the 6GeV=c data sample,
the reduced chi-square statistic measured is 11.26=4bins
with
GEANT
4and 13.33=4bins with
GENIE
hA2018,sug-
gesting tension with both models.
Future studies can utilize the results for tuning
kaon reaction scattering models incorporated in various
hadron interaction event generators. The upcoming
ProtoDUNE Horizontal Drift detector will also exist in
the same detector hall with a wire-based readout and can
measure similar cross sections with nearly identical
methods. It may also run with the beam polarity reversed,
allowing for a cross section analysis of negatively
charged kaons.
ACKNOWLEDGMENTS
The ProtoDUNE-SP detector was constructed and oper-
ated on the CERN Neutrino Platform. We gratefully
acknowledge the support of the CERN management and
the CERN EP, BE, TE, EN, and IT Departments for NP04/
ProtoDUNE-SP. This document was prepared by the
DUNE collaboration using the resources of the Fermi
National Accelerator Laboratory (Fermilab), a U.S.
Department of Energy, Office of Science, HEP User
Facility. Fermilab is managed by Fermi Research
Alliance, LLC (FRA), acting under Contract No. DE-
AC02-07CH11359. This work was supported by CNPq,
FAPERJ, FAPEG, and FAPESP, Brazil; CFI, IPP, and
NSERC, Canada; CERN; MŠMT, Czech Republic;
ERDF, H2020-EU, and MSCA, European Union;
CNRS/IN2P3 and CEA, France; INFN, Italy; FCT,
Portugal; NRF, South Korea; CAM, Fundación “La
Caixa,”Junta de Andalucía-FEDER, MICINN, and
Xunta de Galicia, Spain; SERI and SNSF, Switzerland;
TÜBİTAK, Turkey; The Royal Society and UKRI/STFC,
United Kingdom; DOE and NSF, United States of America.
APPENDIX: DISTRIBUTIONS OF THE 7 GeV =c
BEAM EVENT SELECTION
This appendix contains the distributions for the 7GeV=c
samples for the event selection in simulation and data. The
distribution of tracks without the event selection are shown
in Fig. 15. The distribution for all selected kaons and
FIG. 15. Reconstructed track length for simulation and data
without any selection steps for the 7GeV=c samples. The
statistics are scaled to match the statistics of the data, regardless
of if the event had a TPC track. Only statistical uncertainties from
the data are shown.
FIG. 16. Reconstructed track length for simulation and data for
the 7GeV=c samples both for all selected kaons (top) and only
selected kaons with interacting slices in the fiducial volume
(bottom). The statistics are scaled to match the statistics of the
data. Only statistical uncertainties from the data are shown.
A. ABED ABUD et al. PHYS. REV. D 110, 092011 (2024)
092011-12

selected kaons with interactions in the fiducial volume are
shown in Fig. 16. The initial beamline kinetic energy
distributions for all selected beam kaons at this beamline
setting, as measured by the beamline instrumentation, are
shown in Fig. 17.
All distributions show agreements with similar distribu-
tions in the 6GeV=c sample, as seen in Fig. 4.
Furthermore, similar purities and slightly lower efficiencies
in incident and interacting slice distributions can be
observed in Fig. 18.
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A. Bross ,66 G. Brunetti ,98,140 M. Brunetti ,209 N. Buchanan ,44 H. Budd ,175 J. Buergi,14 A. Bundock ,19
D. Burgardt,211 S. Butchart,191 V. G. Caceres,23 I. Cagnoli,92,17 T. Cai ,216 R. Calabrese ,100 R. Calabrese ,94,67
J. Calcutt ,155 L. Calivers ,14 E. Calvo ,39 A. Caminata ,96 A. F. Camino,168 W. Campanelli ,127 A. Campani ,96,71
A. Campos Benitez,207 N. Canci ,100 J. Capó,84 I. Caracas,134 D. Caratelli ,27 D. Carber ,44 J. M. Carceller,35 G. Carini,20
B. Carlus,110 M. F. Carneiro ,20 P. Carniti ,98 I. Caro Terrazas,44 H. Carranza,197 N. Carrara,23 L. Carroll,119 T. Carroll ,213
A. Carter,176 E. Casarejos ,206 D. Casazza ,94 J. F. Castaño Forero,7F. A. Castaño,6A. Castillo ,182 C. Castromonte ,106
E. Catano-Mur ,212 C. Cattadori ,98 F. Cavalier ,160 F. Cavanna ,66 S. Centro ,158 G. Cerati ,66 C. Cerna,131
A. Cervelli ,92 A. Cervera Villanueva,84 K. Chakraborty ,166 S. Chakraborty ,86 M. Chalifour ,35 A. Chappell ,209
N. Charitonidis ,35 A. Chatterjee ,166 H. Chen ,20 M. Chen ,24 W. C. Chen,199 Y. Chen ,184 Z. Chen-Wishart,176
D. Cherdack ,81 C. Chi,45 F. Chiapponi,92 R. Chirco ,87 N. Chitirasreemadam,103,167 K. Cho ,122 S. Choate ,108
D. Chokheli ,72 P. S. Chong,164 B. Chowdhury,8D. Christian ,66 A. Chukanov ,†M. Chung,202 E. Church ,157
M. F. Cicala,203 M. Cicerchia,158 V. Cicero,92,17 R. Ciolini ,103 P. Clarke ,57 G. Cline,126 T. E. Coan ,188 A. G. Cocco ,100
J. A. B. Coelho,161 A. Cohen,161 J. Collazo,206 J. Collot ,76 E. Conley ,55 J. M. Conrad,136 M. Convery ,184 S. Copello ,96
P. Cova ,99,162 C. Cox,176 L. Cremaldi ,144 L. Cremonesi ,172 J. I. Crespo-Anadón,39 M. Crisler ,66 E. Cristaldo ,98,10
J. Crnkovic ,66 G. Crone,203 R. Cross ,209 A. Cudd ,43 C. Cuesta ,39 Y. Cu i , 26 F. Curciarello ,95 D. Cussans ,19
J. Dai,76 O. Dalager,66 R. Dallavalle,161 W. Dallaway ,199 R. D’Amico,94,67 H. da Motta ,33 Z. A. Dar,212 R. Darby,191
L. Da Silva Peres,65 Q. David,110 G. S. Davies ,144 S. Davini ,96 J. Dawson ,161 R. De Aguiar,30 P. De Almeida,30
P. Debbins ,108 I. De Bonis,51 M. P. Decowski,146,3 A. de Gouvêa,150 P. C. De Holanda,30 I. L. De Icaza Astiz,191
P. De Jong ,146,3 P. Del Amo Sanchez,51 A. De la Torre,39 G. De Lauretis,110 A. Delbart,34 D. Delepine ,77
M. Delgado ,98,140 A. Dell’Acqua,35 G. Delle Monache,95 N. Delmonte ,99,162 P. De Lurgio,8R. Demario,139
G. De Matteis,97 J. R. T. de Mello Neto,65 D. M. DeMuth ,205 S. Dennis ,29 C. Densham ,178 P. Denton ,20
G. W. Deptuch ,20 A. De Roeck ,35 V. De Romeri ,84 J. P. Detje ,29 J. Devine ,35 R. Dharmapalan ,79 M. Dias ,201
A. Diaz ,28 J. S. Díaz,91 F. Díaz,169 F. Di Capua ,100,145 A. Di Domenico ,181,104 S. Di Domizio ,96,71 S. Di Falco ,103
L. Di Giulio,35 P. Ding ,66 L. Di Noto ,96,71 E. Diociaiuti ,95 C. Distefano ,105 R. Diurba ,14 M. Diwan ,20 Z. Djurcic ,8
D. Doering,184 S. Dolan ,35 F. Dolek ,207 M. J. Dolinski,54 D. Domenici ,95 L. Domine ,184 S. Donati ,103,167
Y. Donon,35 S. Doran,109 D. Douglas ,184 T. A. Doyle,189 A. Dragone ,184 F. Drielsma ,184 L. Duarte ,201
D. Duchesneau ,51 K. Duffy ,156 K. Dugas,24 P. Dunne ,88 B. Dutta ,195 H. Duyang ,185 D. A. Dwyer,126
A. S. Dyshkant,149 S. Dytman ,168 M. Eads,149 A. Earle,191 S. Edayath,109 D. Edmunds ,139 J. Eisch ,66 P. Englezos,177
A. Ereditato ,37 T. Erjavec,23 C. O. Escobar,66 J. J. Evans ,135 E. Ewart ,91 A. C. Ezeribe ,183 K. Fahey,66 L. Fajt,35
A. Falcone,98,140 M. Fani’,143,129 C. Farnese ,101 S. Farrell,174 Y. Farzan ,111 D. Fedoseev ,†J. Felix ,77 Y. Feng ,109
E. Fernandez-Martinez ,133 G. Ferry,160 E. Fialova,50 L. Fields ,151 P. Filip ,49 A. Filkins ,192 F. Filthaut ,146,173
R. Fine ,129 G. Fiorillo ,100,145 M. Fiorini ,94,67 S. Fogarty,44 W. Foreman ,87 J. Fowler,55 J. Franc ,50 K. Francis ,149
D. Franco ,37 J. Franklin ,56 J. Freeman ,66 J. Fried,20 A. Friedland ,184 S. Fuess ,66 I. K. Furic,68 K. Furman,172
A. P. Furmanski ,143 R. Gaba,159 A. Gabrielli ,92,17 A. M. Gago,169 F. Galizzi,98 H. Gallagher,200 N. Gallice ,20
V. Galymov ,110 E. Gamberini ,35 T. Gamble,183 F. Ganacim,193 R. Gandhi ,78 S. Ganguly ,66 F. Gao ,27 S. Gao ,20
D. Garcia-Gamez ,73 M. Á. García-Peris,84 F. Gardim,62 S. Gardiner ,66 D. Gastler,18 A. Gauch,14 J. Gauvreau,153
P. Gauzzi ,181,104 S. Gazzana ,95 G. Ge,45 N. Geffroy,51 B. Gelli ,30 S. Gent,187 L. Gerlach,20
Z. Ghorbani-Moghaddam ,96 T. Giammaria,94,67 D. Gibin ,158,101 I. Gil-Botella ,39 S. Gilligan ,155 A. Gioiosa ,103
S. Giovannella ,95 C. Girerd,110 A. K. Giri,90 C. Giugliano ,94 V. Giusti ,103 D. Gnani,126 O. Gogota ,124
S. Gollapinni ,129 K. Gollwitzer,66 R. A. Gomes ,63 L. V. Gomez Bermeo,182 L. S. Gomez Fajardo,182 F. Gonnella ,16
D. Gonzalez-Diaz ,85 M. Gonzalez-Lopez ,133 M. C. Goodman ,8S. Goswami,166 C. Gotti ,98 J. Goudeau,130
E. Goudzovski ,16 C. Grace ,126 E. Gramellini ,135 R. Gran ,142 E. Granados,77 P. Granger ,161 C. Grant,18
D. R. Gratieri ,70,30 G. Grauso,100 P. Green ,156 S. Greenberg,126,22 J. Greer ,19 W. C. Griffith,191 F. T. Groetschla,35
FIRST MEASUREMENT OF THE TOTAL INELASTIC CROSS …PHYS. REV. D 110, 092011 (2024)
092011-15

K. Grzelak ,208 L. Gu,125 W. Gu ,20 V. Guarino,8M. Guarise ,94,67 R. Guenette ,135 M. Guerzoni ,92 D. Guffanti ,98,140
A. Guglielmi ,101 B. Guo ,185 F. Y. Guo ,189 A. Gupta,184 V. Gupta,146,3 G. Gurung,197 D. Gutierrez,170 P. Guzowski ,135
M. M. Guzzo ,30 S. Gwon,38 A. Habig ,142 H. Hadavand ,197 L. Haegel ,110 R. Haenni ,14 L. Hagaman ,214 A. Hahn,66
J. Haiston,186 J. Hakenmüller,55 T. Hamernik ,66 P. Hamilton ,88 J. Hancock ,16 F. Happacher ,95 D. A. Harris ,216,66
A. Hart ,172 J. Hartnell ,191 T. Hartnett,178 J. Harton ,44 T. Hasegawa ,121 C. M. Hasnip ,35 R. Hatcher ,66
K. Hayrapetyan,172 J. Hays ,172 E. Hazen,18 M. He,81 A. Heavey ,66 K. M. Heeger ,214 J. Heise ,190 P. Hellmuth,131
S. Henry,175 K. Herner ,66 V. Hewes ,40 A. Higuera Pichardo ,174 C. Hilgenberg ,143 S. J. Hillier ,16 A. Himmel ,66
E. Hinkle,37 L. R. Hirsch,193 J. Ho ,53 J. Hoff,66 A. Holin ,178 T. Holvey ,156 E. Hoppe ,157 S. Horiuchi ,207
G. A. Horton-Smith ,119 T. Houdy,160 B. Howard,216 R. Howell,175 I. Hristova ,178 M. S. Hronek,66 J. Huang,23
R. G. Huang,126 Z. Hulcher,184 M. Ibrahim,59 G. Iles ,88 N. Ilic ,199 A. M. Iliescu ,95 R. Illingworth ,66 G. Ingratta ,92,17
A. Ioannisian ,215 B. Irwin,143 L. Isenhower ,1M. Ismerio Oliveira,65 R. Itay ,184 C. M. Jackson ,157 V. Jain ,2
E. James,66 W. Jang,197 B. Jargowsky ,24 D. Jena ,66 I. Jentz,213 X. Ji ,20 C. Jiang,115 J. Jiang,189 L. Jiang ,207 A. Jipa,21
J. H. Jo,20 F. R. Joaquim,127,112 W. Johnson,186 C. Jollet ,131 B. Jones ,197 R. Jones ,183 N. Jovancevic,152 M. Judah ,168
C. K. Jung,189 T. Junk ,66 Y. Jw a ,184,45 M. Kabirnezhad ,88 A. C. Kaboth,176,178 I. Kadenko ,124 I. Kakorin ,†
A. Kalitkina ,†D. Kalra,45 M. Kandemir,60 D. M. Kaplan ,87 G. Karagiorgi ,45 G. Karaman ,108 A. Karcher,126
Y. Karyotakis,51 S. Kasai,123 S. P. Kasetti,130 L. Kashur ,44 I. Katsioulas ,16 A. Kauther,149 N. Kazaryan ,215 L. Ke,20
E. Kearns ,18 P. T. Keener,164 K. J. Kelly ,195 E. Kemp ,30 O. Kemularia ,72 Y. Kermaidic,160 W. Ketchum,66
S. H. Kettell ,20 M. Khabibullin ,†N. Khan,88 A. Khvedelidze ,72 D. Kim ,195 J. Kim,175 M. J. Kim,66 B. King ,66
B. Kirby ,45 M. Kirby ,20 A. Kish ,66 J. Klein ,164 J. Kleykamp ,144 A. Klustova ,88 T. Kobilarcik ,66 L. Koch ,134
K. Koehler,213 L. W. Koerner ,81 D. H. Koh,184 L. Kolupaeva ,†D. Korablev ,†M. Kordosky ,212 T. Kosc ,76
U. Kose ,35 V. A. Kostelecký,91 K. Kothekar ,19 I. Kotler,54 M. Kovalcuk,49 V. Kozhukalov ,†W. Krah ,146 R. Kralik,191
M. Kramer ,126 L. Kreczko ,19 F. Krennrich,109 I. Kreslo ,14 T. Kroupova ,164 S. Kubota,135 M. Kubu,35 Y. Kudenko ,†
V. A. Kudryavtsev ,183 G. Kufatty,69 S. Kuhlmann ,8S. Kulagin ,†J. Kumar,79 P. Kum ar ,183 S. Kumaran ,24
J. Kunzmann ,14 R. Kuravi,126 N. Kurita ,184 C. Kuruppu ,185 V. Ku s , 50 T. Kutter,130 J. Kvasnicka,49 T. Labree,149
T. Lackey,66 I. Lalău,21 A. Lambert,126 B. J. Land,164 C. E. Lane ,54 N. Lane,135 K. Lang ,198 T. Langford ,214
M. Langstaff,135 F. Lanni ,35 O. Lantwin ,51 J. Larkin,20 P. Lasorak ,88 D. Last,164 A. Laudrain ,134 A. Laundrie,213
G. Laurenti ,92 E. Lavaut,160 P. Laycock ,20 I. Lazanu ,21 R. LaZur ,44 M. Lazzaroni ,99,141 T. Le,200 S. Leardini,85
J. Learned ,79 T. LeCompte ,184 V. Legin,124 G. Lehmann Miotto,35 R. Lehnert,91 M. A. Leigui de Oliveira,64
M. Leitner ,126 D. Leon Silverio,186 L. M. Lepin,69 J.-Y Li,57 S. W. Li,24 Y. Li ,20 H. Liao ,119 C. S. Lin,126
D. Lindebaum,19 S. Linden,20 R. A. Lineros ,32 A. Lister ,213 B. R. Littlejohn ,87 H. Liu,20 J. Liu ,24 Y. Liu ,37
S. Lockwitz ,66 M. Lokajicek ,49 I. Lomidze,72 K. Long,88 T. V. Lopes,62 J. H. Lopez Botero ,6I. López de Rego,39
N. López-March,84 T. Lord ,209 J. M. LoSecco,151 W. C. Louis ,129 A. Lozano Sanchez,54 X.-G. Lu,209 K. B. Luk,80,126,22
B. Lunday,164 X. Luo ,27 E. Luppi ,94,67 D. MacFarlane ,184 A. A. Machado,30 P. Machado ,66 C. T. Macias,91
J. R. Macier,66 M. MacMahon,203 A. Maddalena ,75 A. Madera,35 P. Madigan ,22,126 S. Magill ,8C. Magueur,160
K. Mahn ,139 A. Maio ,127,61 A. Major ,55 K. Majumdar,128 S. Mameli,103 M. Man,199 R. C. Mandujano,24 J. Maneira,127,61
S. Manly ,175 A. Mann ,200 K. Manolopoulos,178 M. Manrique Plata,91 S. Manthey Corchado,39 V. N. Manyam ,20
M. Marchan,66 A. Marchionni ,66 W. Marciano ,20 D. Marfatia,79 C. Mariani ,207 J. Maricic ,79 F. Marinho ,113
A. D. Marino ,43 T. Markiewicz ,184 F. Das Chagas Marques,30 C. Marquet,131 M. Marshak ,143 C. M. Marshall,175
J. Marshall ,209 L. Martina ,97 J. Martín-Albo,84 N. Martinez,119 D. A. Martinez Caicedo,186 F. Martínez López,172
P. Martínez Mirav´e,84 S. Martynenko ,20 V. Mascagna ,98 C. Massari,98 A. Mastbaum ,177 F. Matichard,126 S. Matsuno,79
G. Matteucci ,100,145 J. Matthews ,130 C. Mauger ,164 N. Mauri ,92,17 K. Mavrokoridis ,128 I. Mawby ,125 R. Mazza,98
T. McAskill,210 N. McConkey,172,203 K. S. McFarland ,175 C. McGrew ,189 A. McNab ,135 L. Meazza ,98
V. C. N. Meddage,68 A. Mefodiev ,†B. Mehta ,159 P. Mehta ,116 P. Melas,11 O. Mena ,84 H. Mendez ,170 P. Mendez,35
D. P. M´endez,20 A. Menegolli ,102,163 G. Meng ,101 A. C. E. A. Mercuri,193 A. Meregaglia ,131 M. D. Messier,91
S. Metallo,143 W. Metcalf,130 M. Mewes ,91 H. Meyer ,211 T. Miao,66 J. Micallef,200,136 A. Miccoli ,97 G. Michna,187
R. Milincic,79 F. Miller ,213 G. Miller,135 W. Miller ,143 O. Mineev ,†A. Minotti ,98,140 L. Miralles Verge,35
O. G. Miranda ,41 C. Mironov ,161 S. Miryala ,20 S. Miscetti ,95 C. S. Mishra,66 P. Mishra,82 S. R. Mishra,185
A. Mislivec ,143 M. Mitchell,130 D. Mladenov,35 I. Mocioiu,165 A. Mogan ,66 N. Moggi ,92,17 R. Mohanta ,82
T. A. Mohayai ,91 N. Mokhov ,66 J. Molina,10 L. Molina Bueno,84 E. Montagna,92,17 A. Montanari ,92
A. ABED ABUD et al. PHYS. REV. D 110, 092011 (2024)
092011-16

C. Montanari ,102,66,163 D. Montanari ,66 D. Montanino ,97,179 L. M. Montaño Zetina,41 M. Mooney ,44 A. F. Moor ,183
Z. Moore ,192 D. Moreno ,7O. Moreno-Palacios,212 L. Morescalchi ,103 D. Moretti,98 R. Moretti,98 C. Morris,81
C. Mossey ,66 C. A. Moura ,64 G. Mouster ,125 W. M u , 66 L. Mualem ,28 J. Mueller ,44 M. Muether ,211
F. Muheim ,57 A. Muir ,52 M. Mulhearn ,23 D. Munford,81 L. J. Munteanu ,35 H. Muramatsu ,143 J. Muraz ,76
M. Murphy,207 T. Murphy,192 J. Muse ,143 A. Mytilinaki,178 J. Nachtman ,108 Y. Nagai ,59 S. Nagu ,132
R. Nandakumar ,178 D. Naples,168 S. Narita ,114 A. Navrer-Agasson ,88,135 N. Nayak ,20 M. Nebot-Guinot ,57
A. Nehm ,134 J. K. Nelson ,212 O. Neogi,108 J. Nesbit,213 M. Nessi ,66,35 D. Newbold ,178 M. Newcomer ,164
R. Nichol ,203 F. Nicolas-Arnaldos,73 A. Nikolica,164 J. Nikolov,152 E. Niner ,66 K. Nishimura ,79 A. Norman ,66
A. Norrick ,66 P. Novella ,84 A. Nowak,125 J. A. Nowak ,125 M. Oberling,8J. P. Ochoa-Ricoux,24 S. Oh ,55 S. B. Oh,66
A. Olivier ,151 A. Olshevskiy ,†T. Olson ,81 Y. Onel ,108 Y. Onishchuk ,124 A. Oranday,91 M. Osbiston,209
J. A. Osorio V´elez,6L. O’Sullivan,134 L. Otiniano Ormachea,46,106 J. Ott,24 L. Pagani ,23 G. Palacio ,58 O. Palamara ,66
S. Palestini ,35 J. M. Paley ,66 M. Pallavicini ,96,71 C. Palomares ,39 S. Pan,166 P. Panda,82 W. Panduro Vazquez,176
E. Pantic,23 V. Paolone ,168 R. Papaleo ,105 A. Papanestis ,178 D. Papoulias ,11 S. Paramesvaran ,19 A. Paris,170
S. Parke ,66 E. Parozzi,98,140 S. Parsa,14 Z. Parsa,20 S. Parveen,116 M. Parvu ,21 D. Pasciuto ,103 S. Pascoli ,92,17
L. Pasqualini ,92,17 J. Pasternak,88 C. Patrick ,57,203 L. Patrizii ,92 R. B. Patterson ,28 T. Patzak ,161 A. Paudel ,66
L. Paulucci ,64 Z. Pavlovic ,66 G. Pawloski ,143 D. Payne ,128 V. Pec ,49 E. Pedreschi ,103 S. J. M. Peeters,191
W. Pellico,66 A. Pena Perez,184 E. Pennacchio ,110 A. Penzo ,108 O. L. G. Peres,30 Y. F. Perez Gonzalez,56
L. P´erez-Molina,39 C. Pernas,212 J. Perry,57 D. Pershey ,69 G. Pessina ,98 G. Petrillo ,184 C. Petta ,93,31 R. Petti,185
M. Pfaff,88 V. Pia,92,17 L. Pickering ,178,176 F. Pietropaolo ,35,101 V. L. Pimentel ,47,30 G. Pinaroli,20 S. Pincha,89
J. Pinchault,51 K. Pitts ,207 K. Plows,156 C. Pollack,170 T. Pollman,146,3 F. Pompa ,84 X. Pons,35 N. Poonthottathil ,86,109
V. Popov,194 F. Poppi,92,17 J. Porter,191 L. G. Porto Paixão,30 M. Potekhin,20 R. Potenza,93,31 J. Pozimski,88 M. Pozzato ,92,17
T. Prakash,126 C. Pratt,23 M. Prest ,98 F. Psihas ,66 D. Pugnere ,110 X. Qian ,20 J. Queen,55 J. L. Raaf,66 V. Radeka,20
J. Rademacker ,19 B. Radics ,216 F. Raffaelli ,103 A. Rafique ,8E. Raguzin ,20 M. Rai,209 S. Rajagopalan ,20
M. Rajaoalisoa ,40 I. Rakhno,66 L. Rakotondravohitra ,5L. Ralte ,90 M. A. Ramirez Delgado,164 B. Ramson ,66
A. Rappoldi ,102,163 G. Raselli ,102,163 P. Ratoff ,125 R. Ray,66 H. Razafinime ,40 E. M. Rea,143 J. S. Real ,76
B. Rebel ,213,66 R. Rechenmacher,66 J. Reichenbacher ,186 S. D. Reitzner,66 H. Rejeb Sfar,35 E. Renner ,129
A. Renshaw ,81 S. Rescia,20 F. Resnati,35 Diego Restrepo,6C. Reynolds,172 M. Ribas,193 S. Riboldi ,99 C. Riccio ,189
G. Riccobene,105 J. S. Ricol,76 M. Rigan ,191 E. V. Rincón,58 A. Ritchie-Yates,176 S. Ritter,134 D. Rivera ,129 R. Rivera ,66
A. Robert,76 J. L. Rocabado Rocha,84 L. Rochester ,184 M. Roda ,128 P. Rodrigues ,156 M. J. Rodriguez Alonso,35
J. Rodriguez Rondon,186 S. Rosauro-Alcaraz ,160 P. Rosier,160 D. Ross,139 M. Rossella ,102,163 M. Rossi ,35
M. Ross-Lonergan ,129 N. Roy ,216 P. Roy ,211 C. Rubbia,74 A. Ruggeri,92 G. Ruiz Ferreira,135 B. Russell ,136
D. Ruterbories ,175 A. Rybnikov ,†S. Sacerdoti ,161 S. Saha,168 S. K. Sahoo ,90 N. Sahu ,90 P. Sala ,66 N. Samios,20
O. Samoylov ,†M. C. Sanchez,69 A. Sánchez Bravo,84 A. Sánchez-Castillo,73 P. Sánchez-Lucas,73 V. Sandberg,129
D. A. Sanders ,144 S. Sanfilippo ,105 D. Sankey ,178 D. Santoro,99,162 N. Saoulidou ,11 P. Sapienza ,105 C. Sarasty ,40
I. Sarcevic,9I. Sarra ,95 G. Savage,66 V. Savinov ,168 G. Scanavini ,214 A. Scaramelli,102 A. Scarff ,183 T. Schefke,130
H. Schellman ,155,66 S. Schifano ,94,67 P. Schlabach,66 D. Schmitz ,37 A. W. Schneider ,136 K. Scholberg ,55
A. Schukraft ,66 B. Schuld ,43 A. Segade,206 E. Segreto ,30 A. Selyunin ,†D. Senadheera,168 C. R. Senise Jr.,201
J. Sensenig ,164 M. H. Shaevitz,45 P. Shanahan ,66 P. Sharma,159 R. Kumar,171 S. Sharma Poudel,186 K. Shaw ,191
T. Shaw ,66 K. Shchablo,110 J. Shen,164 C. Shepherd-Themistocleous ,178 A. Sheshukov ,†J. Shi,29 W. Shi ,189
S. Shin ,117 S. Shivakoti,211 I. Shoemaker ,207 D. Shooltz,139 R. Shrock ,189 B. Siddi ,94 M. Siden,44 J. Silber ,126
L. Simard ,160 J. Sinclair ,184 G. Sinev,186 Jaydip Singh,23 J. Singh ,132 L. Singh,48 P. Singh ,172 V. Singh ,48
S. Singh Chauhan,159 R. Sipos ,35 C. Sironneau,161 G. Sirri ,92 K. Siyeon ,38 K. Skarpaas,184 J. Smedley,175 E. Smith ,91
J. Smith ,189 P. Smith,91 J. Smolik,50,49 M. Smy,24 M. Snape,209 E. L. Snider,66 P. Snopok ,87 D. Snowden-Ifft,153
M. Soares Nunes,66 H. Sobel ,24 M. Soderberg ,192 S. Sokolov ,†C. J. Solano Salinas,204,106 S. Söldner-Rembold,88,135
N. Solomey ,211 V. Solovov ,127 W. E. Sondheim,129 M. Sorel ,84 A. Sotnikov ,†J. Soto-Oton ,84 A. Sousa ,40
K. Soustruznik,36 F. Spinella ,103 J. Spitz ,138 N. J. C. Spooner,183 K. Spurgeon ,192 D. Stalder ,10 M. Stancari,66
L. Stanco ,158,101 J. Steenis,23 R. Stein ,19 H. M. Steiner,126 A. F. Steklain Lisbôa,193 A. Stepanova ,†J. Stewart,20
B. Stillwell ,37 J. Stock ,186 F. Stocker ,35 T. Stokes ,130 M. Strait ,143 T. Strauss ,66 L. Strigari ,195 A. Stuart ,42
J. G. Suarez,58 J. Subash,16 A. Surdo ,97 L. Suter ,66 C. M. Sutera,93,31 K. Sutton ,28 Y. Suvorov,100,145 R. Svoboda ,23
FIRST MEASUREMENT OF THE TOTAL INELASTIC CROSS …PHYS. REV. D 110, 092011 (2024)
092011-17

S. K. Swain,147 B. Szczerbinska,196 A. M. Szelc ,57 A. Sztuc ,203 A. Taffara,103 N. Talukdar ,185 J. Tamara,7
H. A. Tanaka,184 S. Tang ,20 N. Taniuchi,29 A. M. Tapia Casanova,137 B. Tapia Oregui,198 A. Tapper ,88 S. Tariq ,66
E. Tarpara,20 E. Tatar,83 R. Tayloe ,91 D. Tedeschi,185 A. M. Teklu,189 J. Tena Vidal,194 P. Tennessen,126,4 M. Tenti ,92
K. Terao ,184 F. Terranova ,98,140 G. Testera ,96 T. Thakore ,40 A. Thea ,178 S. Thomas,192 A. Thompson ,195
C. Thorn,20 S. C. Timm,66 E. Tiras ,60,108 V. Tishchenko ,20 N. Todorović,152 L. Tomassetti ,94,67 A. Tonazzo ,161
D. Torbunov ,20 M. Torti,98,140 M. Tortola ,84 F. Tortorici ,93,31 N. Tosi ,92 D. Totani,27 M. Toups ,66 C. Touramanis ,128
D. Tran,81 R. Travaglini ,92 J. Trevor,28 E. Triller,139 S. Trilov ,19 J. Truchon,213 D. Truncali,181,104 W. H. Trzaska ,118
Y. Tsai ,24 Y.-T. Tsai,184 Z. Tsamalaidze ,72 K. V. Tsang,184 N. Tsverava ,72 S. Z. Tu,115 S. Tufanli,35 C. Tunnell ,174
S. Turnberg,87 J. Turner ,56 M. Tuzi,84 J. Tyler,119 E. Tyley ,183 M. Tzanov,130 M. A. Uchida ,29 J. Ureña González,84
J. Urheim ,91 T. Usher ,184 H. Utaegbulam ,175 S. Uzunyan,149 M. R. Vagins ,120,24 P. Vahle ,212 S. Valder ,191
G. A. Valdiviesso,62 E. Valencia ,77 R. Valentim ,201 Z. Vallari ,28 E. Vallazza ,98 J. W. F. Valle,84 R. Van Berg ,164
R. G. Van de Water ,129 D. V. Forero,137 A. Vannozzi,95 M. Van Nuland-Troost,146 F. Varanini ,101 D. Vargas Oliva,199
S. Vasina ,†N. Vaughan ,155 K. Vaziri,66 A. Vázquez-Ramos,73 J. Vega ,46 S. Ventura ,101 A. Verdugo ,39
S. Vergani ,203 M. Verzocchi ,66 K. Vetter,66 M. Vicenzi ,20 H. Vieira de Souza,161 C. Vignoli ,75 C. Vilela ,127
E. Villa ,35 S. Viola ,105 B. Viren,20 A. P. Vizcaya Hernandez,44 Q. Vuong,175 A. V. Waldron ,172 M. Wallbank ,40
J. Walsh,139 T. Walton,66 H. Wang,25 J. Wang,186 L. Wang,126 M. H. L. S. Wang,66 X. Wang,66 Y. Wang ,25
K. Warburton ,109 D. Warner,44 L. Warsame ,88 M. O. Wascko,156,178 D. Waters ,203 A. Watson ,16 K. Wawrowska,178,191
A. Weber ,134,66 C. M. Weber,143 M. Weber ,14 H. Wei ,130 A. Weinstein ,109 S. Westerdale ,26 M. Wetstein,109
K. Whalen ,178 A. White ,197 A. White,214 L. H. Whitehead ,29 D. Whittington ,192 J. Wilhlemi,214 M. J. Wilking ,143
A. Wilkinson,203 C. Wilkinson ,126 F. Wilson ,178 R. J. Wilson ,44 P. Winter ,8W. Wisniewski ,184 J. Wolcott ,200
J. Wolfs ,175 T. Wongjirad,200 A. Wood,81 K. Wood,126 E. Worcester ,20 M. Worcester ,20 M. Wospakrik ,66 K. Wresilo,29
C. Wret ,175 S. Wu ,143 W. Wu ,66 W. Wu ,24 M. Wurm ,134 J. Wyenberg,53 Y. Xiao,24 I. Xiotidis,88 B. Yaeggy ,40
N. Yahlali,84 E. Yandel ,27 J. Yang,80 K. Yang ,156 T. Yang ,66 A. Yankelevich ,24 N. Yershov ,†K. Yonehara ,66
T. Young ,148 B. Yu ,20 H. Yu ,20 J. Yu ,197 Y. Yu , 87 W. Yuan ,57 R. Zaki,216 J. Zalesak ,49 L. Zambelli ,51
B. Zamorano ,73 A. Zani ,99 O. Zapata,6L. Zazueta ,192 G. P. Zeller,66 J. Zennamo,66 K. Zeug ,213 C. Zhang ,20
S. Zhang ,91 M. Zhao ,20 E. Zhivun,20 E. D. Zimmerman ,43 S. Zucchelli ,92,17 J. Zuklin ,49 V. Zutshi,149 and
R. Zwaska 66
(DUNE Collaboration)
1Abilene Christian University, Abilene, Texas 79601, USA
2University of Albany, SUNY, Albany, New York 12222, USA
3University of Amsterdam, NL-1098 XG Amsterdam, The Netherlands
4Antalya Bilim University, 07190 Döşemealtı/Antalya, Turkey
5University of Antananarivo, Antananarivo 101, Madagascar
6University of Antioquia, Medellín, Colombia
7Universidad Antonio Nariño, Bogotá, Colombia
8Argonne National Laboratory, Argonne, Illinois 60439, USA
9University of Arizona, Tucson, Arizona 85721, USA
10Universidad Nacional de Asunción, San Lorenzo, Paraguay
11University of Athens, Zografou GR 157 84, Greece
12Universidad del Atlántico, Puerto Colombia, Atlántico, Colombia
13Augustana University, Sioux Falls, South Dakota 57197, USA
14University of Bern, CH-3012 Bern, Switzerland
15Beykent University, Istanbul, Turkey
16University of Birmingham, Birmingham B15 2TT, United Kingdom
17Universit`a di Bologna, 40127 Bologna, Italy
18Boston University, Boston, Massachusetts 02215, USA
19University of Bristol, Bristol BS8 1TL, United Kingdom
20Brookhaven National Laboratory, Upton, New York 11973, USA
21University of Bucharest, Bucharest, Romania
22University of California Berkeley, Berkeley, California 94720, USA
23University of California Davis, Davis, California 95616, USA
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24University of California Irvine, Irvine, California 92697, USA
25University of California Los Angeles, Los Angeles, California 90095, USA
26University of California Riverside, Riverside California 92521, USA
27University of California Santa Barbara, Santa Barbara, California 93106, USA
28California Institute of Technology, Pasadena, California 91125, USA
29University of Cambridge, Cambridge CB3 0HE, United Kingdom
30Universidade Estadual de Campinas, Campinas-SP, 13083-970, Brazil
31Universit`a di Catania, 2-95131 Catania, Italy
32Universidad Católica del Norte, Antofagasta, Chile
33Centro Brasileiro de Pesquisas Físicas, Rio de Janeiro, RJ 22290-180, Brazil
34IRFU, CEA, Universit´e Paris-Saclay, F-91191 Gif-sur-Yvette, France
35CERN, The European Organization for Nuclear Research, 1211 Meyrin, Switzerland
36Institute of Particle and Nuclear Physics of the Faculty of Mathematics and Physics of the Charles
University, 180 00 Prague 8, Czech Republic
37University of Chicago, Chicago, Illinois 60637, USA
38Chung-Ang University, Seoul 06974, South Korea
39CIEMAT, Centro de Investigaciones Energ´eticas, Medioambientales y Tecnológicas,
E-28040 Madrid, Spain
40University of Cincinnati, Cincinnati, Ohio 45221, USA
41Centro de Investigación y de Estudios Avanzados del Instituto Polit´ecnico Nacional (Cinvestav),
Mexico City, Mexico
42Universidad de Colima, Colima, Mexico
43University of Colorado Boulder, Boulder, Colorado 80309, USA
44Colorado State University, Fort Collins, Colorado 80523, USA
45Columbia University, New York, New York 10027, USA
46Comisión Nacional de Investigación y Desarrollo Aeroespacial, Lima, Peru
47Centro de Tecnologia da Informacao Renato Archer, Amarais-Campinas, SP-CEP 13069-901
48Central University of South Bihar, Gaya, 824236, India
49Institute of Physics, Czech Academy of Sciences, 182 00 Prague 8, Czech Republic
50Czech Technical University, 115 19 Prague 1, Czech Republic
51Laboratoire d’Annecy de Physique des Particules, Universit´e Savoie Mont Blanc,
CNRS, LAPP-IN2P3, 74000 Annecy, France
52Daresbury Laboratory, Cheshire WA4 4AD, United Kingdom
53Dordt University, Sioux Center, Iowa 51250, USA
54Drexel University, Philadelphia, Pennsylvania 19104, USA
55Duke University, Durham, North Carolina 27708, USA
56Durham University, Durham DH1 3LE, United Kingdom
57University of Edinburgh, Edinburgh EH8 9YL, United Kingdom
58Universidad EIA, Envigado, Antioquia, Colombia
59Eötvös Loránd University, 1053 Budapest, Hungary
60Erciyes University, Kayseri, Turkey
61Faculdade de Ciências da Universidade de Lisboa-FCUL, 1749-016 Lisboa, Portugal
62Universidade Federal de Alfenas, Poços de Caldas-MG, 37715-400, Brazil
63Universidade Federal de Goias, Goiania, GO 74690-900, Brazil
64Universidade Federal do ABC, Santo Andr´e-SP, 09210-580, Brazil
65Universidade Federal do Rio de Janeiro, Rio de Janeiro-RJ, 21941-901, Brazil
66Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
67University of Ferrara, Ferrara, Italy
68University of Florida, Gainesville, Florida 32611-8440, USA
69Florida State University, Tallahassee, Florida, 32306 USA
70Fluminense Federal University, 9 Icaraí Niterói-RJ, 24220-900, Brazil
71Universit`a degli Studi di Genova, Genova, Italy
72Georgian Technical University, Tbilisi, Georgia
73University of Granada & CAFPE, 18002 Granada, Spain
74Gran Sasso Science Institute, L’Aquila, Italy
75Laboratori Nazionali del Gran Sasso, L’Aquila AQ, Italy
76University Grenoble Alpes, CNRS, Grenoble INP, LPSC-IN2P3, 38000 Grenoble, France
77Universidad de Guanajuato, Guanajuato, C.P. 37000, Mexico
78Harish-Chandra Research Institute, Jhunsi, Allahabad 211 019, India
79University of Hawaii, Honolulu, Hawaii 96822, USA
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80Hong Kong University of Science and Technology, Kowloon, Hong Kong, China
81University of Houston, Houston, Texas 77204, USA
82University of Hyderabad, Gachibowli, Hyderabad-500 046, India
83Idaho State University, Pocatello, Idaho 83209, USA
84Instituto de Física Corpuscular, CSIC and Universitat de Val `encia, 46980 Paterna, Valencia, Spain
85Instituto Galego de Física de Altas Enerxías, University of Santiago de Compostela,
Santiago de Compostela, 15782, Spain
86Indian Institute of Technology Kanpur, Uttar Pradesh 208016, India
87Illinois Institute of Technology, Chicago, Illinois 60616, USA
88Imperial College of Science, Technology and Medicine, London SW7 2BZ, United Kingdom
89Indian Institute of Technology Guwahati, Guwahati, 781 039, India
90Indian Institute of Technology Hyderabad, Hyderabad 502285, India
91Indiana University, Bloomington, Indiana 47405, USA
92Istituto Nazionale di Fisica Nucleare Sezione di Bologna, 40127 Bologna BO, Italy
93Istituto Nazionale di Fisica Nucleare Sezione di Catania, I-95123 Catania, Italy
94Istituto Nazionale di Fisica Nucleare Sezione di Ferrara, I-44122 Ferrara, Italy
95Istituto Nazionale di Fisica Nucleare Laboratori Nazionali di Frascati, Frascati, Roma, Italy
96Istituto Nazionale di Fisica Nucleare Sezione di Genova, 16146 Genova GE, Italy
97Istituto Nazionale di Fisica Nucleare Sezione di Lecce, 73100-Lecce, Italy
98Istituto Nazionale di Fisica Nucleare Sezione di Milano Bicocca, 3-I-20126 Milano, Italy
99Istituto Nazionale di Fisica Nucleare Sezione di Milano, 20133 Milano, Italy
100Istituto Nazionale di Fisica Nucleare Sezione di Napoli, I-80126 Napoli, Italy
101Istituto Nazionale di Fisica Nucleare Sezione di Padova, 35131 Padova, Italy
102Istituto Nazionale di Fisica Nucleare Sezione di Pavia, I-27100 Pavia, Italy
103Istituto Nazionale di Fisica Nucleare Laboratori Nazionali di Pisa, Pisa PI, Italy
104Istituto Nazionale di Fisica Nucleare Sezione di Roma, 00185 Roma RM, Italy
105Istituto Nazionale di Fisica Nucleare Laboratori Nazionali del Sud, 95123 Catania, Italy
106Universidad Nacional de Ingeniería, Lima 25, Perú
107University of Insubria, Via Ravasi, 2, 21100 Varese VA, Italy
108University of Iowa, Iowa City, Iowa 52242, USA
109Iowa State University, Ames, Iowa 50011, USA
110Institut de Physique des 2 Infinis de Lyon, 69622 Villeurbanne, France
111Institute for Research in Fundamental Sciences, Tehran, Iran
112Instituto Superior T´ecnico-IST, Universidade de Lisboa, 1049-001 Lisboa, Portugal
113Instituto Tecnológico de Aeronáutica, Sao Jose dos Campos, Brazil
114Iwate University, Morioka, Iwate 020-8551, Japan
115Jackson State University, Jackson, Mississippi 39217, USA
116Jawaharlal Nehru University, New Delhi 110067, India
117Jeonbuk National University, Jeonrabuk-do 54896, South Korea
118Jyväskylä University, FI-40014 Jyväskylä, Finland
119Kansas State University, Manhattan, Kansas 66506, USA
120Kavli Institute for the Physics and Mathematics of the Universe, Kashiwa, Chiba 277-8583, Japan
121High Energy Accelerator Research Organization (KEK), Ibaraki, 305-0801, Japan
122Korea Institute of Science and Technology Information, Daejeon, 34141, South Korea
123National Institute of Technology, Kure College, Hiroshima, 737-8506, Japan
124Taras Shevchenko National University of Kyiv, 01601 Kyiv, Ukraine
125Lancaster University, Lancaster LA1 4YB, United Kingdom
126Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
127Laboratório de Instrumentação e Física Experimental de Partículas,
1649-003 Lisboa and 3004-516 Coimbra, Portugal
128University of Liverpool, L69 7ZE, Liverpool, United Kingdom
129Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
130Louisiana State University, Baton Rouge, Louisiana 70803, USA
131Laboratoire de Physique des Deux Infinis Bordeaux-IN2P3, F-33175 Gradignan, Bordeaux, France
132University of Lucknow, Uttar Pradesh 226007, India
133Madrid Autonoma University and IFT UAM/CSIC, 28049 Madrid, Spain
134Johannes Gutenberg-Universität Mainz, 55122 Mainz, Germany
135University of Manchester, Manchester M13 9PL, United Kingdom
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136Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
137University of Medellín, Medellín, 050026 Colombia
138University of Michigan, Ann Arbor, Michigan 48109, USA
139Michigan State University, East Lansing, Michigan 48824, USA
140Universit`a di Milano Bicocca, 20126 Milano, Italy
141Universit`a degli Studi di Milano, I-20133 Milano, Italy
142University of Minnesota Duluth, Duluth, Minnesota 55812, USA
143University of Minnesota Twin Cities, Minneapolis, Minnesota 55455, USA
144University of Mississippi, University, Mississippi 38677 USA
145Universit`a degli Studi di Napoli Federico II , 80138 Napoli NA, Italy
146Nikhef National Institute of Subatomic Physics, 1098 XG Amsterdam, Netherlands
147National Institute of Science Education and Research (NISER), Odisha 752050, India
148University of North Dakota, Grand Forks, North Dakota 58202-8357, USA
149Northern Illinois University, DeKalb, Illinois 60115, USA
150Northwestern University, Evanston, Illinois 60208, USA
151University of Notre Dame, Notre Dame, Indiana 46556, USA
152University of Novi Sad, 21102 Novi Sad, Serbia
153Occidental College, Los Angeles, California 90041
154Ohio State University, Columbus, Ohio 43210, USA
155Oregon State University, Corvallis, Oregon 97331, USA
156University of Oxford, Oxford, OX1 3RH, United Kingdom
157Pacific Northwest National Laboratory, Richland, Washington 99352, USA
158Universt`a degli Studi di Padova, I-35131 Padova, Italy
159Panjab University, Chandigarh, 160014, India
160Universit´e Paris-Saclay, CNRS/IN2P3, IJCLab, 91405 Orsay, France
161Universit´e Paris Cit´e, CNRS, Astroparticule et Cosmologie, Paris, France
162University of Parma, 43121 Parma PR, Italy
163Universit`a degli Studi di Pavia, 27100 Pavia PV, Italy
164University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
165Pennsylvania State University, University Park, Pennsylvania 16802, USA
166Physical Research Laboratory, Ahmedabad 380 009, India
167Universit`a di Pisa, I-56127 Pisa, Italy
168University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
169Pontificia Universidad Católica del Perú, Lima, Perú
170University of Puerto Rico, Mayaguez 00681, Puerto Rico, USA
171Punjab Agricultural University, Ludhiana 141004, India
172Queen Mary University of London, London E1 4NS, United Kingdom
173Radboud University, NL-6525 AJ Nijmegen, Netherlands
174Rice University, Houston, Texas 77005
175University of Rochester, Rochester, New York 14627, USA
176Royal Holloway College London, London, TW20 0EX, United Kingdom
177Rutgers University, Piscataway, New Jersey, 08854, USA
178STFC Rutherford Appleton Laboratory, Didcot OX11 0QX, United Kingdom
179Universit`a del Salento, 73100 Lecce, Italy
180Universidad del Magdalena, Santa Marta, Colombia
181Sapienza University of Rome, 00185 Roma RM, Italy
182Universidad Sergio Arboleda, 11022 Bogotá, Colombia
183University of Sheffield, Sheffield S3 7RH, United Kingdom
184SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
185University of South Carolina, Columbia, South Carolina 29208, USA
186South Dakota School of Mines and Technology, Rapid City, South Dakota 57701, USA
187South Dakota State University, Brookings, South Dakota 57007, USA
188Southern Methodist University, Dallas, Texas 75275, USA
189Stony Brook University, SUNY, Stony Brook, New York 11794, USA
190Sanford Underground Research Facility, Lead, South Dakota 57754, USA
191University of Sussex, Brighton, BN1 9RH, United Kingdom
192Syracuse University, Syracuse, New York 13244, USA
193Universidade Tecnológica Federal do Paraná, Curitiba, Brazil
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194Tel Aviv University, Tel Aviv-Yafo, Israel
195Texas A&M University, College Station, Texas 77840
196Texas A&M University-Corpus Christi, Corpus Christi, Texas 78412, USA
197University of Texas at Arlington, Arlington, Texas 76019, USA
198University of Texas at Austin, Austin, Texas 78712, USA
199University of Toronto, Toronto, Ontario M5S 1A1, Canada
200Tufts University, Medford, Massachusetts 02155, USA
201Universidade Federal de São Paulo, 09913-030, São Paulo, Brazil
202Ulsan National Institute of Science and Technology, Ulsan 689-798, South Korea
203University College London, London, WC1E 6BT, United Kingdom
204Universidad Nacional Mayor de San Marcos, Lima, Peru
205Valley City State University, Valley City, North Dakota 58072, USA
206University of Vigo, E- 36310 Vigo, Spain
207Virginia Tech, Blacksburg, Virginia 24060, USA
208University of Warsaw, 02-093 Warsaw, Poland
209University of Warwick, Coventry CV4 7AL, United Kingdom
210Wellesley College, Wellesley, Massachusetts 02481, USA
211Wichita State University, Wichita, Kansas 67260, USA
212William and Mary, Williamsburg, Virginia 23187, USA
213University of Wisconsin Madison, Madison, Wisconsin 53706, USA
214Yale University, New Haven, Connecticut 06520, USA
215Yerevan Institute for Theoretical Physics and Modeling, Yerevan 0036, Armenia
216York University, Toronto M3J 1P3, Canada
†Affiliated with an Institute or an International Laboratory Participating within the DUNE Collaboration.
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