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The data samples which have been used in this analysis are described in this section. A summary of the POT of the datasets used in this analysis is found in Table 7.1.

7.2.1

Run 1 Data

The data used in this analysis represents5 × 1019 protons on target of collected beam data from

MicroBooNE Run 1. This represents less than 5% of the full13 × 1020POT which MicroBooNE is

expected to collect over its lifetime, and is the data which is currently open for the purposes of developing analyses.

In addition to this, all of the Run 1 off-beam data is used.

7.2.2

Simulated Data

The nominal simulation sample used in this analysis corresponds to around 2,000,000 events, or 1.86e+21 POT. These events are generated within the MicroBooNE TPC according to the simula- tion chain outlined in Chapter 4.

7.2.3

Out-of-TPC Simulation

The nominal simulated dataset contains neutrino interactions which have been simulated within the MicroBooNE TPC. Particles from interactions which take place outside of the TPC may enter and be selected as neutrino candidates. These are referred to asOut-of-TPC ordirtbackgrounds.

This happens primarily because the MicroBooNE TPC is contained within a cylindrical cryo- stat which is filled with liquid argon. Approximately half of the total mass of liquid argon is not contained within the TPC, and this means that approximately half of the interactions in Micro- BooNE occur inside of the cryostat but outside of the TPC. These interactions are able to have a flash in-time with the beam which may be detected by the light collection system, meaning they may be selected as a neutrino candidate. Due to processing constraints, these events are not contained in the nominal simulation, and so a separate simulation of these events is produced.

This dataset corresponds to 1.69e+21 POT.

7.2.4

Detector Variation Samples

In order to assess the impact of the detector-related systematic uncertainties in MicroBooNE, severaldetector variationdatasets are leveraged. These are simulated samples where parameters

thought to have some systematic effect on analyses are varied by their ±1𝜎 bound, or where

specific models are turned on or off in order to gauge the magnitude of their effect. Each detector variation dataset uses the same underlying events from the GENIE generator in order to remove statistical uncertainty as a factor.

One drawback of separating the out-of-TPC events from the simulation is that the detector variation samples described below do not affect the dirt backgrounds, however the out-of-TPC contamination in neutrino selections is generally small due to fiducial volume constraints, and so the effect of this is estimated to be small.

The variation samples presented here are intended to be a conservative treatment, and work is ongoing within the collaboration to constrain many of these through in-situ measurements. Many of the effects listed here are described in greater detail in Chapter 3.

Central Value (CV) The nominal MicroBooNE simulation with no additions or modifications.

Note that this is the same simulation as presented in Section 7.2.2, but it contains the same underlying events as the other detector variation samples such that they are not statistically independent.

Space Charge Effect (SCE) A data-driven correction is applied to the nominal simulation of

the SCE. This dataset is then generated using the data-driven SCE model which moves the simulation to better match what is measured in the data. This data-driven correction is applied to both the spatial migration map and the electric field modification map.

Light Yield (LY) In the central value simulation, there were a number of bugs contained in the

simulation of scintillation light. The primary bug here is that the simulation assumed that every particle produced light assuming it was a true electron meaning the number of pho- tons/cm is constant for all particle species. This has been corrected in this variation sample.

Longitudinal Diffusion (LD Up and LD Down) There are two variations here: one turns down

the longitudinal diffusion coefficient and the other turns the coefficient up. Currently this is estimated from world data to be 6.2 cm2/s+57%

−47%. In future iterations of the systematic un-

certainty treatment, the result obtained in Chapter 5 will supersede these values.

Transverse Diffusion (TD Up and TD Down) Both transverse and longitudinal diffusion are

simulated assuming MicroBooNE’s design voltage, 500 V/cm. In the case of longitudinal diffusion the uncertainties easily cover the difference between this (6.2 cm2/s) and the cor-

rect value from a fit to world data (6.36cm2/s), however in the case of transverse diffusion

this is not the case, and so both variations fall below the nominal 𝐷𝑇 value and the ±1𝜎

is 16.3 cm2/s−24.5%

−49.6%. The world data for transverse diffusion does not cover the MicroBooNE

electric field, and so the uncertainties here were chosen from theoretical models.

Wire Noise (WN Up and WN Down) The nominal simulation uses a data-driven model of wire

PMT Noise (PMTN Up and PMTN Down) The main noise on the MicroBooNE PMTs issingle PE noise, which is seen at a rate of 250 Hz. The systematic variations here use a±1𝜎 of ±50𝐻 𝑧, which is an approximate±1 𝜎 variation on measurements taken from the data.

Induced Charge (DIC) Induced charge has been widely discussed within this work. There is no

induced charge simulation in the nominal MicroBooNE simulation. This detector variation introduces a preliminary simulation of this effect, and is referred to as theDynamic Induced Chargesimulation.

Wire Response Function (SQUEEZE RF and STRETCH RF) The wire response function is

measured from the data, however studies on simulation have shown that there is some bias on this measurement. This is a roughly 20% bias, and so these detector variation samples modify the width of the response function by±this amount.

Removing Channels Prone To Saturation (SAT) A number of channels in the MicroBooNE

TPC will occasionally have charge build up on the capacitors in the ASICs, and this results in an amount of dead time on wires connected to these ASICs. This detector variation simulation simulates these channels as being non-responsive in order to understand the effect on the reconstruction.

Removing Misconfigured Channels (MIS) This variation simulates misconfigured channels

as being non-responsive in order to place an upper bound on their effect on reconstruction.

Light Outside of the TPC (EXTTPCVIS) The light production from charged particles outside

of the TPC is thought to be incorrectly simulated because effects such as the reflectance of the cryostat are not present, and so this variation increases the light yield in this region by 50%.

Electron Lifetime (LT) The electron lifetime in MicroBooNE has been measured to be very

estimates a lower bound on the effect of electron lifetime by simulating the lifetime to be 10 ms.

Recombination Model (BIRKS) The nominal MicroBooNE simulation uses the Modified Box

model tuned to ArgoNeuT data. This substitutes the Birks recombination model [92], tuned to ICARUS data [103], in the MicroBooNE reconstruction (note that the Modified Box model is still used in simulation).

Sample Number of Triggers POT Scale Factor

On-beam data 10905211 4.89e+19 -

Off-beam data 77329137 - 0.141 BNB+Cosmic - 1.86e+21 0.026 Out-of-TPC - 1.69e+21 0.029 CV - 1.94e+20 0.253 SCE - 3.92e+20 0.125 LY - 1.97e+20 0.248 LD Up - 1.95e+20 0.251 LD Down - 1.97e+20 0.248 TD Up - 1.95e+20 0.250 TD Down - 1.98e+20 0.248 WN Up - 1.94e+20 0.252 WN Down - 1.96e+20 0.250 PMTN Up - 1.96e+20 0.250 PMTN Down - 1.98e+20 0.247 DIC - 1.96e+20 0.250 STRETCH RF - 1.94e+20 0.252 SQUEEZE RF - 1.94e+20 0.252 SAT - 1.97e+20 0.248 MIS - 1.93e+20 0.252 EXTTPCVIS - 1.97e+20 0.249 LT - 1.97e+20 0.249 BIRKS - 1.97e+20 0.248

Table 7.1: Datasets used in the development of the𝜈𝜇 CC 0𝜋N𝑝selection, and understanding of