Study of a 200 ton Gadolinium-loaded Water
Cherenkov Detector for Super-KamiokaNDE
Gadolinium Project
Chenyuan Xu
Okayama University
Student Num 41426209

1

Abstract
Supernova Relic Neutrino (SRN) has not been observed yet because of
its low event rate and high background. By adding gadolinium into water
Cherenkov detector, inverse beta decay will have two signals, the prompt
one is positron signal and the delayed one is a ∼8 MeV gamma cascadefrom neutron capture on gadolinium. By this way, background for SRN
can be largely reduced by detecting prompt and delayed signals coincidently, and Super-K will also have the ability to distinguish neutrino andanti-neutrino. SK-Gd is a R&D project proposed to dissolve gadolinium
into Super-K. As a part of it, EGADS, a 200ton water Cherenkov detector
was built in Kamioka mine. 0.2% gadolinium water has been successfully
loaded into EGADS tank and the neutron capture efficiency of gadolinium
in EGADS was measured to be
Ef fGd (Data) = 84.36 ± 1.79%
Ef fGd (M C) = 84.51 ± 0.33%
Current status of SK-Gd project and the physics work being performedin EGADS as well as the details of EGADS detector calibration and data
analysis will be presented in this thesis.

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Contents
1 Supernova neutrino
1.1 Supernova explosion . . . . . . . . . . . . . . . . . . . . . . . . .
1.1.1 Time evolution of stellar . . . . . . . . . . . . . . . . . . .
1.1.2 Neutrino reaction in supernova process . . . . . . . . . . .
1.2 Supernova Relic Neutrino . . . . . . . . . . . . . . . . . . . . . .

4
4
4
5
7

2 Super-Kamiokande detector
2.1 Super-K Detector overview . . . . . . . . . . . . . . . . . . . . .
2.2 Cherenkov radiation . . . . . . . . . . . . . . . . . . . . . . . . .
2.3 Neutrino interaction in water Cerenkov detector . . . . . . . . .
2.4 Photomultiplier tube . . . . . . . . . . . . . . . . . . . . . . . . .
2.5 SRN detection in Super-Kamiokande . . . . . . . . . . . . . . . .

9
9
10
12
13
15

3 SK-Gd project and EGADS
17
3.1 EGADS Detector overview . . . . . . . . . . . . . . . . . . . . . . 17
3.1.1 200 tons water tank . . . . . . . . . . . . . . . . . . . . . 17
3.1.2 Water system . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.1.3 Electronics and Trigger . . . . . . . . . . . . . . . . . . . 18
3.1.4 Gadolinium concentration . . . . . . . . . . . . . . . . . . 19
3.2 Water transparency . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.2.1 Soak test . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.2.2 UDEAL system . . . . . . . . . . . . . . . . . . . . . . . . 22
3.3 Detector calibration . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.3.1 HV setting . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.3.2 Timing correction . . . . . . . . . . . . . . . . . . . . . . 26
3.3.3 Quantum efficiency measurement . . . . . . . . . . . . . . 27
3.3.4 Gain measurement . . . . . . . . . . . . . . . . . . . . . . 29
3.3.5 Long term stability . . . . . . . . . . . . . . . . . . . . . . 30
4 EGADS data analysis
32
4.1 Event reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . 32
4.1.1 Vertex reconstruction . . . . . . . . . . . . . . . . . . . . 32
4.1.2 Direction reconstruction . . . . . . . . . . . . . . . . . . . 33
4.1.3 Energy reconstruction . . . . . . . . . . . . . . . . . . . . 34
4.1.4 Monte Carlo tuning . . . . . . . . . . . . . . . . . . . . . 36
4.2 Estimation of neutron capture efficiency . . . . . . . . . . . . . . 38
4.2.1 Detection setup . . . . . . . . . . . . . . . . . . . . . . . . 38
4.2.2 Data reduction . . . . . . . . . . . . . . . . . . . . . . . . 38
4.2.3 Fake prompt event . . . . . . . . . . . . . . . . . . . . . . 41
4.2.4 Neutron capture efficiency . . . . . . . . . . . . . . . . . . 43
5 Summary and prospect

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1

Supernova neutrino

1.1

Supernova explosion

On February 23rd 1987, supernova burst of Large Magellanic Cloud wasobserved. It is a supernova from about 51.4kpc distance from the earth and it isnumbered with SN1987A. It is the first time that human detected the supernova
by neutrinos and that is the sign of the birth of Neutrino Astronomy. In SN
1987A, the neutrino detector KamiokaNDE observed 11 neutrinos [1], while
American detector IBM observed 8 neutrinos [2]. The detection of supernova
neutrino is not only a new page in the physics history but also proved that thefundamental model of core collapse supernova is correct. Study about supernova
was based on optical observation in the past and it is limited by a lot of reasons.
Neutrino has offered a new way to approach to the the mechanism of supernova
explosion and cosmic evolution. Now experiments of supernova neutrino searchare being carried out in the world wide.

Figure 1: Supernova 1987A
1.1.1

Time evolution of stellar

Supernova explosion is the last stage of the life of large stars. The lastprocess of the stellar evolution depends on its mass.
Protostar : M < 0.08M
The core of protostar is formed by the interstellar gases. The core will continue
to absorb the nearby gases and grow larger and larger. The kinetic energy of theabsorbed matter will be transferred to thermal energy and that is why protostar
is brighter than the main sequence star. The Hydrogen in the core will not start
to fuse until the core temperature reaches 107 K. If the core begins to cool down
before it reaches 107 K, the Hydrogen will never begin to burn and the star will

4

finally become a black dwarf.
Jupiter is an example for protostar.
Hydrogen burning : 0.08M < M < 0.46M
Hydrogen burning starts from 0.08M . The reactions of Hydrogen burning iscomplex but the most basic one is:
4p →4 He + 2e+ + 2ν(1)

Hydrogen supplies the energy and then the star could make balance from thetemperature and inner pressure of itself. Star with mass less than 0.46M willstop burning its energy in this phase and then become a white dwarf which
consists of Helium. The white dwarf will continue to emit light until it hascompletely cooled down and become a black dwarf. However, the life time ofwhite dwarf is so long that it is even longer than the age of our current cosmic.
So there is no black dwarf existing yet.
Helium burning : 0.46M < M < 4M
When the Hydrogen burning stops, the star will begin to contract because ofits gravitation. If the core temperature exceeds 108 K, Helium will start to burnand finally becomes a red giant with a core of Carbon and Oxygen. As the sizeof the star increases, the gravitation in the penumbra becomes weak and thestar begin to blast off the matter of its outside part. The core will remains andbecome a white dwarf. Our sun is an example for this.
Carbon deflagration : 4M < M < 8M
For the stars whose mass is between 4M and 8M , the Carbon-Oxygen coreproduced in the last process will begin to burn. The mass of the core is near the
Chandrasekhar Limit and the degenerate pressure of the electrons is stronger.
Thus, even though the core is burning, it could not expand and it is called
Carbon deflagration. This is the mechanism of one type of supernova. Whenthe core burns up, the total energy it gives out is even larger than the binding
energy of the star so nothing could remain after the burst.
Gravitational collapse : 8M < M
For the stars 8M < M < 12M , Ne-Mg cores could be made by carbon
burning under the degenerate pressure. And for the stars 12M < M , iron corecan be made and the core could not burn any more as iron is the most stableelement. The core loses the source of energy and the temperature and pressure
increase as the star contracts by gravitation. In the end, the star will die witha supernova explosion.
1.1.2

Neutrino reaction in supernova process

The process of supernova explosion can be divided as follows.
Beginning of core collapse
When the mass of the core exceed the Chandrasekhar Limit, the gravitational
collapse will start and the density of the core will get larger and larger. νe will5

be released by electron capture(2) by the nuclei and the photodisintegration ofiron nuclei(3) also occurs in this step.
e− + A(N, Z) → νe + A(N + 1, Z − 1)(2)

γ +56 F e → 13α + 4n − 124.4M eV(3)Both of the two interactions will reduce the degenerate pressure and become
the trigger of a rapid core collapse.
Neutrino trapping
When the density of the core exceeds 3 × 109 g/cm3 , the neutrinos will follows
the coherent scattering(4) with the nuclei and be unable to go outside. This iscalled neutrino trapping and the boundary is called neutrino sphere.
ν + A(N, Z) → ν + A(N, Z)(4)Core bounce
When core density continue to increase and finally reaches the level of nuclear
density(∼ 1014 g/cm3 ), the shock wave will be repulsed and driven towards
outside.
Neutrino cooling
After the shock wave passed through, the matter outside the core will drop to
the center and ∼ 1053 erg of gravitational energy will be converted into thermalenergy. All flavors of neutrinos will be produced by pair annihilation(5) andbremsstrahlung(6).
e− + e+ → ν + ν̄(5)
N + N → N + N + ν + ν̄(6)ν̄e and νe will also be produce by electron capture(7) and positron capture(8).
e− + p → νe + n(7)

e+ + n → ν̄e + p(8)Most of the energy are released by neutrinos and the star cools down in about
10s.
Supernova burst
The shock wave may takes several hours until it arrives the surface of the star.
The penumbra part will be blasted off and the remnant of the star will become
neutron star. Or if the mass of the core is heavy enough, it will finally becomea black hole.
Summarizing this session, only νe can be emitted in the very beginning of supernova explosion, and later after that neutrinos of all flavors will be produced.

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1.2

Supernova Relic Neutrino

As 99% of the energy is released by neutrino flux in supernova process, it
is an important way to study supernova models by neutrinos. It is consideredthat supernova occurs two or three times within one century in our galaxy [3].
Although there is no supernova observed from SN1987A, supernova is always
occurring in the 15 billion years history of the universe. These neutrinos frompast supernovae are called Supernova Relic Neutrinos (SRN), or known as another name as Diffuse Supernova Neutrino Background (DSNB). The first models
for SRN were founded even before SN1987A [4], while the studies about SRN
largely increased after SN1987A. Figure 2 shows the ν̄e fluxes predicted by thefollowing theoretical models:Constant SN rate model [5] (Totani et al. 1995)
The supernova rate was assumed as a constant in the whole universe in thismodel.
Population synthesis [6] (Totani et al. 1996)
It is founded by the same author by using a population synthesis of the stars in
the galaxy evolution.
Cosmic gas infall model [7] (Malaney et al. 1997)
This model uses the supernova rate which is obtained from the density distribution of interstellar gas as a function of red shift parameter.
Chemical evolution model [8] (Hartmann et al. 1997)
This model considered the history of the cosmic star formation which is obtained
from the chemical evolution.
Heavy metal model [9] (Kaplinghat et al. 2000)
In this model, the theoretical upper limit of SRN flux is predicted by using theabundance of heavy elements.
LMA neutrino oscillation [10] (Ando et al. 2002)
The parameter for neutrino oscillasion is considered in this model.

7Figure 2: Colour lines are the ν̄e flux predicted by each model. Black lines
represent other background neutrinos.
The reason why only ν̄e is considered is that the cross section of ν̄e reaction
in water Cherenkov detector is two orders larger than the others in the mainenergy range of SRN. Even though ν̄e reaction has large cross section, SRN flux
is still hidden in various background and has not been detected yet. As can been
seen from the Figure 2, Solar and reactor neutrinos are dominant below 10MeV,
and atmospheric neutrinos become dominant above 30MeV. A new R&D projectfocusing on SRN search in 10∼30MeV window is now being carried out. The
details will be stated later.

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2Super-Kamiokande detector

2.1Super-K Detector overview

Super-K, which is short for Super-KamaiokaNDE, is a neutrino detector
built in 1000m underground in Kamioka mine in Gifu Prefecture of Japan. The
last three letters NDE means neutrino detection experiment as well as nucleon
decay experiment. It is a water Cherenkov detector as a stainless cylinder of
39m radius and 42m height, with total volume of 50000 tons water. The rockaround the detector acts as a shield to stop the comic muons and other kinds ofbackgrounds from environment like gamma rays and neutrons. However, due tothe small cross section of neutrino reactions, neutrino can easily even go throughthe earth and it is also the reason for the large volume of water target.

Figure 3: View of Super-K tank and Kamioka mine
Super-K consists of an outer detector and an inner detector. Inner detector
has 32000 tons volume and 11129 20-inch photon-multiplier tubes (PMT) with
about 40% coverage, while outer detector has 1885 8-inch PMTs [11]. PMTs
are installed in the top, barrel and bottom of the tank by stainless frames. Rateof muon events in Super-K is about 1∼2Hz, outer detector is used to recognize
the muon events. For such purpose, the wall of outer detector is covered withwhite tyvek sheets of about 80% reflection to increase the photon collection
efficiency. And oppositely, to decrease the reflection and the possibility of misreconstruction, inner detector is covered with black sheets.

9Figure 4: Stainless frame of top, bottom and barrel PMTs. The surface of
the PMTs are covered with black sheet to reduce reflection.
The construction work of Super-K began in 1991 and be finished in 1996.
The purpose of the Super-K is various neutrinos physics and the measurement ofproton life time. It observed solar neutrinos [12], atmospheric neutrinos [13] aswell as accelerator neutrinos [14], and several evidences for neutrino oscillations
were found. Super-K detector started to take data from April 1996 and now it
is running as fourth phase. Super-K has been collecting data for nearly twenty
years and it is still the largest neutrino detector in the world.

2.2

Cherenkov radiation

The speed of light in medium is c/n, when the index of refraction is n. If
a charged particle passes through the medium with velocity larger than c/n,
the particle will emit a forward cone of light. This is named as Cherenkov
radiation, while P.A.Cherenkov is the person who discovered this effect in 1934.
To theoretically explain it, when a charged particle travels in the medium, it
10Particlee±µ±π±Threshold(MeV)
0.767
157.4
207.9

Table 1: Cherenkov threshold for charged particles in water.
will emit spherical wave by electric polarization. If the velocity of the particle
exceeds c/n, the spherical waves can interfere with each other and form radiation(Figure 6). Otherwise, they will never meet each other and stay independent(Figure 5).

Figure 5: when velocity of thecharged particle is smaller thanc/nFigure 6: when velocity of thecharged particle is larger thanc/nThus, the angle between Cherenkov light and the direction of the charged
particle can be calculated with the ratio of light velocity in the medium c/n andthe velocity of incident particle as follows:cos θ =1nβ(9)Here β = v/c. Considering the critical condition of Cherenkov radiation is
β > 1/n ,the energy threshold for incident particle to emit Cherenkov light is:
Ethr = √nmn2 − 1(10)

For water Cherenkov detector, the index of refraction is 1.33, so the thresholdof total energy for the main particles is shown below.
In most cases, the signals observed in Super-K are from electrons or muons
with β ≈ 1, so the Cherenkov angle is close to 42◦ . The number of photon (N)produced by Cherenkov radiation in unit length dL can be calculated as:
d2 N
2παZ 21=(1 − 2 2 )
2
dλdL
λ
n β
11

(11)

Here λ is the wavelength of Cerenkov radiation, Z is the charge of incident
particle, and α is fine-structure constant. By integrating it, the number ofphoton in specific wavelength range (λ1 , λ2 ) is:dN
2παZ 2 1
11=( − )(1 − 2 2 )
dL
n
λ1
λ2
n β

(12)

For example, when an electron travels 1cm in Super-K tank with β ≈ 1,
about 340 photons would be produced in Super-K PMT sensitive range of
280nm∼660nm. It can hardly be observed and that is why we need photonmultiplier tubes (PMT).

2.3

Neutrino interaction in water Cerenkov detector

Supernova emits neutrinos and anti-neutrinos in three flavors. These neutrinos react with water and finally charged particles are observed by Cerenkov
radiation. The main reactions of neutrinos in water Cerenkov detector is shown
below.

Figure 7: Cross section comparison of various neutrino interaction in
0∼60MeV range [15]Inverse Beta Decay:ν e + p → n + e+

(13)This is the most dominant interaction and it has the largest cross section in theenergy region of Supernova neutrinos. It occurs between the anti-neutrinos ofelectron type and the free protons in the water. Most of supernova neutrinos
will be detected via this interaction. However, the direction information will belost in this interaction.

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Photoelectronic Surface
Material
DynodeQuantum Efficiency
Dark Rate
Time Resolution

50cm
Sb-K-Cs
Venetian Blind type
22% at 390nm
3.5kHz3ns RMS at 1pe

Table 2: Properties of Super-K inner PMT

Neutral Current Interaction:
νx + 16 O → νx + γ + X(14)

ν + e− → ν + e−

(15)

Elastic Scattering:This is the elastic scattering between neutrinos and electrons in water. It
happens in all flavours, but the electron-neutrino has about 6 times larger crosssection than others because of charged current interaction. The cross sectionis two order smaller than inverse beta decay but it can conserve the direction
information of the incident neutrinos, which is very important for the early
announcement to the other measurement such as optical observation, gammaray and so on.

2.4

Photomultiplier tube

The PMTs being used in Super-K are produced by Hamamatsu Photonics
c.o, and the development work was done under the cooperation of Super-K
group. The inner detector PMTs are 20-inch Hamamatsu R3600 PMTs, andthe outer detector PMTs are 8-inch Hamamatsu R1408 PMTs. The designof inner detector PMTs are based on the PMTs being used in KamiokaNDE
experiment, with several improvements.
Figure 9 shows the structure of a PMT. The photo-cathode is made of bailkali(Sb-K-Cs) and it is sensitive to photons with wavelength in 300∼600 nm, which
covers the wavelength of Cherenkov light. Electron photons could be multipliedwith a gain of ∼10 7 by 11 chain dynodes. Super-K PMTs not only have better
time resolution than Kamiokannde PMTs, but also become able to identify
single photon signals. It is an improvement of great significance because mostof the signals in low energy events like supernova neutrinos are due to single
photon.

13

Figure 8: Photo of a bare PMT

Figure 9: Inner structure of PMT

14

Figure 10: The acrylic cover and FRP case used from 2001 to protect the
PMT from shock wave
The threshold is set to 1/4 pe and the rate of dark noise above this thresholdwas ∼3.5 kHz when in Super-K first phase. The magnetic field of the earth canlargely affect the photoelectrons so Helmholtz coils are used for compensation.
The residual geo-magnetic field is kept less than 100 mG in every position of
the tank.
In the accident happened in 2001, about half of the PMTs were broken as aresult of shock wave. Since that, PMTs in Super-K are all installed with acrylic
covers and FRP cases as shown in Figure 10. The transmittance of the acrylic
cover is about 96% and it doesn’t affect the event reconstruction.

2.5

SRN detection in Super-Kamiokande

The reason why SRN has not been observed is high background and low event
rate. As the largest water Cherenkov detector in the world, Super-K has thelargest volume and the best sensitivity for SRN flux. The event rate of SRN between 10MeV and 30MeV is expected to be about 1.3-6.7 events/year/22.5kton
in Super-K.
In SRN detection, inverse beta decay plays an important role, because its crosssection is two orders of magnitude larger than νe elastic scattering with electron, which is the second most visible interaction of SRN in Super-K. Currently,
IBD only has a Cherenkov signal emitted by positron. The neutron producedin IBD will be thermalized in water and then be captured by free protons, witha result of 2.2 MeV gamma ray emission. The coincidence detection of positronand neutron can effectively reduce the background. Neutron tagging will alsoenable Super-K to identify electron-neutrinos and anti-electron-neutrinos, which
is very important for the investigation of supernova explosion mechanism andwill also largely improve the precision of other neutrino physics.
However it is very difficult to detect 2.2MeV gamma rays as it is below the detection threshold and thus the method of tagging neutrons by 2.2MeV gamma
ray has a very low efficiency. Because of these, adding gadolinium into Super-K
was proposed [16]. The cross section of thermal neutron capture on natural

15

gadolinium is 49000 barn, while 0.3 barn on free protons. And neutron captureon 155 Gd and 157 Gd can emit 8.5MeV and 7.9MeV gamma rays respectively. It
will make neutron tagging much easier and more efficient than 2.2MeV gamma.
n + Gd → Gd + γ 0 s(8M eV )(16)

Figure 11: Detection principle of using gadolinium to produce delayed signal
By this way, inverse beta decay will have two signals, positron signal is
the prompt one and the ∼8 MeV gamma cascade from neutron capture on
gadolinium is the delayed one. Background for SRN can be largely reduced bydetecting prompt and delayed signals coincidently, and Super-K will also havethe ability to distinguish neutrino and anti-neutrino. As will be discussed later,
now a lot of R&D works are ongoing and the project of adding gadolinium into
SK is called SK-Gd project.

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3

SK-Gd project and EGADS

3.1

EGADS Detector overview

3.1.1

200 tons water tank

It is essential to understand what will happen after loading gadolinium waterand estimate all the potential effect. The most direct and efficient way is to build
a similar detector with the same conditions as Super-K. Such R&D project iscalled Evaluating Gadoliniums Action on Detector System (EGADS), which was
funded in 2009 and proposed to test gadolinium effect on Super-K. In gadolinium
loaded detector, most of the neutrons produced by inverse beta decay will be
captured in 2m distance. Thus, the size of EGADS detector does not need tobe so large. Finally the tank was designed as a 200m3 stainless steel tank andbuilt inside Kamioka mine in 2010, several tens of meters from SK tank. 240
20-inch PMTs were installed into EGADS tank and its own data acquisition
system has been developed. Within these 240 PMTs, 224 of them are the samewith Super-K and 16 of them are prototypes which will be tested for Hyper-K.
And also, 18 of the 224 Super-K PMTs are installed with FRP cases and 60
are installed with both FRP cases and acrylic vessels, while the remaining 146
are bare ones. Gadolinium sulfate (Gd2 (SO4 )3 ) was chosen for our candidate
as will be discussed later. The work of filling gadolinium into EGADS tankstarted from November 2014. The filling work was finished by April 2015 and
0.2% gadolinium sulfate has been dissolved. A 90% efficiency of neutron capture
is expected under this concentration.

Figure 12: Photo of EGADS underground lab inside Kamioka mine
3.1.2

Water system

To dissolve gadolinium into Super-K, an important thing is the upgradeof the current water system. The major importance is the stability of water

17

quality, so the system should have the ability to remove the impurities and keep
the water quality at a good level. What’s more, gadolinium should be gathered
and reloaded into the tank after purification when the water is passing throughthe system. A prototype of the circulation system for gadolinium loaded water
was developed at University of California, Irvine (UCI) long before EGADS
project started and now the system has already running for more than one year.
Gadolinium loaded water pumped out from EGADS tank will first go throughan ultra-filter, which removes the impurities larger than gadolinium. Then thewater will be filtered by two nano-filters, which filter out the particles of about
the same size of gadolinium, and the gadolinium concentrated water rejectedby the filters will be lead to a buffer tank. Then the water passed from thenano-filters will go through reverse osmosis membranes(RO) to remove smaller
impurities. Water is also treated with deionizers, UV lights and micro-filtersto ensure that anions of about the same size of gadolinium or organic carbons
are removed. Finally the purified water will go into the collection buffer tankand be mixed with the gadolinium concentrated water and then be injected into
EGADS tank again.

Figure 13: Structure of water circulation system of EGADSA pre-mix 15 ton tank has also been installed together with a pre-treatment
system. Gadolinium sulfate will be mixed in this 15 ton tank before being
injected into EGADS tank. The pre-treatment system has a stirrer to facilitate
the dissolution of gadolinium sulfate in water.
3.1.3

Electronics and Trigger

The signals from the PMTs are sent to front end modules called Analog
Timing Module(ATM). One ATM board can treat the signals from 12 PMTs
and 20 ATM modules are being used. If the input signal into the ATM exceeds
the threshold level, ATM will produce a 200 ns width and -15 mV height signal
called HITSUM. HITSUM generated from the front panels for all the ATM
modules are summed up and sent to a discriminator, which determines the18trigger threshold of DAQ system. For example, the threshold of prompt trigger
in normal run mode is -110mV, this is equal to about 45 PMT hits, which means
signals are outputted from 45 PMTs within 200ns. In ATM module, both signal
timing and integrated charge are digitalized. Such information is recorded andtransferred to a front-end Linux PC, as well as the trigger timing and trigger
type of each event.

Figure 14: Trigger system and HITSUM signal
Raw data in binary format is saved in the front end PC in the mine. A
program called real time process is checking the data and DAQ status. Every
8 hours, the real time process will sent the raw data to the online computersin computer building outside the mine. The raw data will be converted into
analysable format by online computers, and can be used in offline analysis later.
3.1.4

Gadolinium concentration

We are doing our best to make the gadolinium concentration to be uniform
in the tank and we expect the concentration to be as stable as possible. But
actually the gadolinium concentration is slightly different in different positionand changes with time. So it becomes necessary to monitor how uniformly
we could dissolve gadolinium as well as to check how well the water system
works. For such purpose, UDEAL is used to take samples from top, centre
and bottom of the tank. The samples are measured with an atomic absorption
spectrometer(AAS) with an measurement uncertainty of 3.5%.

19

Figure 15: Photo of the Zeeman atomic absorption spectrometer in EGADS
lab

Figure 16: Scheme of the Zeeman AAS machine
The scheme of the Zeeman AAS machine used for this measurement is shownin Figure 16. Since 0.2% gadolinium concentration is too high for the cuvetteof Zeeman AAS machine, the samples are diluted and compared with standard
solutions. Standard solutions are used for calibration of the machine every time
when it is switched on. The diluted sample is heated and atomized and then be
shined by the light from hollow cathode lamp. The light amount absorbed by
the sample is proportional to the gadolinium contained in the sample.

3.2

Water transparency

3.2.1

Soak test

Adding gadolinium may influence the material aging. We need to ensure that
adding a gadolinium solution will not corrode or easily age detector materials.
20

The materials used for the construction of EGADS and Super-K tank are tested
in Okayama University. The samples of these materials are soaked in gadolinium
water in 500ml or 250ml bottles and be kept in thermostats chambers at 15◦ .
They are tested under different conditions such as gadolinium concentration andtemperatures.

Figure 17: Sample of pure water and gadolinium dissolved water
The transparency of the water soaked with samples can be measured with
spectrometer. The wavelength range of the spectrometer are set as 200nm∼800nm,
while the sensitive range of PMT is about 280nm∼630nm. The transparency
comparison of pure water and 0.2% gadolinium water without any samples areshown below. Though the transparency decreases below 250nm, it doesn’t affectour detection because it is out of PMT sensitive range. GdCl3 was proposedin the past. However, a test with one kiloton water tank with 0.2% of GdCl3
showed that although GdCl3 did not decrease water transparency, chlorine lifted old rust already present in the one kiloton tank and it has been confirmed bysoak test. Now our new candidate is (Gd2 (SO4 )3 ). After we loaded gadolinium
sulfate, rust was once found in the tank. After soak test we found out thatthe rust was due to a kind of wire used to fix blacksheet in EGADS tank. It
is a newly used material and it is not being used in Super-K. Other materials
such as mine guard which is our candidate for leak fixing in the future, are also
carefully tested with promising results.

21

Figure 18: Transmittance comparison of pure water and gadolinium water.
Red line is distilled water and green line is gadolinium water.
3.2.2

UDEAL system

In order to monitor the water transparency change in the tank, a measurement device called Underground Device Evaluating Attenuation Length(UDEAL) was developed at UCI. This device consists of a beam injector, aintensity monitor (upper part), pipe (middle) and transmitted light instrument(below the pipe).

22

Figure 19: Scheme of UDEAL device
UDEAL can take water samples automatically from three positions (top,centre, bottom) of the tank, and measure the samples with laser by seven different wavelengths (337nm, 375nm, 405nm, 445nm, 473nm, 532nm and 595nm).
These wavelengths cover the main range of Cherenkov light signals in Super-K.
By using the measurement results of UDEAL, water transparency is evaluatedas the intensity of Cherenkov light left at a distance of 15 m (LL15m ). Timerelated change of water transparency is shown in Figure 20. Gadolinium sulfate
was injected into the tank by four times, after the injection transparency got
down suddenly, and then recovered as a result of circulation. Measurement with
spectrophotometer and other studies are also being performed.

23

Figure 20: Water transparency change measured by UDEAL. It is estimatedby LL15m .

3.3

Detector calibration

3.3.1

HV setting

In PMT calibration, Quantum Efficiency (QE) and gain are two importantfactors. Here, QE also includes the collection efficiency of photoelectrons onto
the first dynode of the PMT. Gain is the conversion factor from the number ofcollected photoelectrons to output charge (in units of pC). Low energy events
like SRN signals usually consist of single photoelectron (pe) hits so their analysis
heavily depends on QE calibration, while high energy events depend more on
gain calibration. The output of the PMT depends on the voltage applied on it.
So first of all, we need to determine the high voltage value for all the PMTs.
PMTs with the same geometry are divided into one group and the target ofhigh voltage calibration is to make the PMTs in the same group to have a same
output value.

24

Figure 21: Setup of the measurement of Xe scintillation light
For this calibration, we use Xe flash lamp as a light source. Light from thelamp passes through a UV filter and then be injected into the tank throughoptical fiber, finally arrive at a scintillator ball placed in the center of the tank.
The other two fibers go to an avalanche photodiode(APD) module and a darkbox installed with a 2 inch PMT, which are both used to monitor the lightintensity of Xe lamp. The scintillator ball is an acrylic ball containing 15ppm
POPOP as a wavelength shifter and 2000ppm MgO as a diffuser to make thelight emission from the ball as uniform as possible.
After high voltage adjustment, a table of high-voltage setting for each PMT was
made and this table has been loaded into electronics system. Figure 22 showsthat the difference between every PMT and the average value of its group is lessthan 1%, with 0.003% RMS.

Figure 22: Distribution of charge difference of normal PMTs after HV adjustment25

3.3.2

Timing correction

Timing for each PMT has to be calibrated for precise reconstruction of event
vertices. However, the transmit time, cable length and processing time of readout electronics of each PMT are different, as a result the time response of each
PMT also varies. Besides, we have to consider a so-called timing-walk effect, itmeans the timing of discriminator output is related to the pulse height of PMT
signal. As shown in Figure 23, the rise time of a large pulse is faster than thatof a smaller one.

Figure 23: Time walk effectIncluding all these above, we propose to make a charge-timing correction
for each PMT to make relative timing difference as small as possible, suchcorrection constants is called TQmap. Every PMT has its own TQmap because
the character of each PMT is unique. Figure 24 shows an example of TQmap of
one PMT. As discussed before, higher charge hits have earlier timing and better
resolution.

Figure 24: TQ distribution of the PMT with ID 1
26

To calibrate PMT timing, we use a nitrogen laser as a light source. The
nitrogen laser(USHOKEC-100) can emit light of 0.4ns FWHM at a wavelengthof 337nm. A dye is used to shift the 337nm light to 398nm, where the lightabsorption spectrum and quantum efficiency of the PMTs are almost maximum.
The laser output is monitored by a fast response 2 inch PMT, which is also used
to produce timing trigger for DAQ system. The output light from laser is leaded
into the tank by optical fiber and then be emitted from a diffuser ball placedin the centre of the tank. Directional variations in the photon emission time ofthe diffuser ball were measured to be less than 0.2ns.
3.3.3

Quantum efficiency measurement

The absolute value of quantum efficiency (Q.E.) of PMTs is measured byHamamatsu Photonics when these PMTs were produced. QE depends on the
wavelength of photons, and their relationship is shown in Fig 25. As can beseen from this figure, the value of Q.E. at the typical wave length of Cherenkov
light (λ = 390nm) is 22%.

Figure 25: Absolute Q.E. values of PMT depending on wavelength27

Figure 26: Ni ball used for relative Q.E. measurement [17]However, the conditions of every PMT are not completely the same so thatthe relative QE slightly differs from each other. The Relative QE of each PMT
is measured by Ni-Cf source. This source is made by 58 Ni ball and a 252 Cf stickis inserted into the ball. Neutrons are provided by 252 Cf, and 9MeV gamma
rays are emitted isotropically by neutron capture on 58 Ni. More than 99% of
observed signals are due to single pe. The source is made like a ball as shownin the Figure 26. When measuring QE of PMTs, Ni-Cf source was placed at
the centre of the tank, and relative QE can be calculated by counting rateof each PMT. Of course, the distances from the source to PMTs in different
positions are different so the PMTs will detect different numbers of photons.
To take the position effect into consideration, MC simulation is used and theexperiment data is compared to MC results to cancel the geometry differences.
The dispersion of relative QE was measured to be 5.7% of RMS.

Figure 27: Relative Q.E. difference28

3.3.4Gain measurement

Similarly to QE measurement, we need to measure the absolute and relativevalue of PMT gains. As gain means the proportion of photoelectron numbers
and PMT output charge, absolute gain can be calculated from the charge distribution of single photon signals. LED was chosen to be the light source. LED
light is injected into the tank by optical fiber and finally emit from the diffuse
ball which is also used for timing calibration. Diffuser ball was placed in thecentre of the tank and the light output of LED was carefully controlled to ensure
the light arrived PMT surface is at single photon level. The charge distributionof single photon signals is shown in Figure 28 as green line.

Figure 28: Charge distribution for one pe signals. Left is linear scale and rightis the same figure in log scale.
The green line in the Figure decreases in low charge parts, it is due to thethreshold of ATM modules used in electronics. To extend this distribution to low
charge parts, we reduced the ATM threshold to half of normal values, and raise
the PMTs gain to double of normal values by high voltage setting. The resultis shown as blue line in the Figure. The distribution is better than the green
one but it still decreases in very low parts because the ATM threshold is notcompletely zero. However, the single photon distribution could be considered
to be linear below 0.5pC so we can extend this distribution to zero by fitting
it using linear function. The result is shown as red line and we integrated it toobtain the conversion factor from observed charge to photo-electron value. The
latest result is 2.502 from pC to pe.

29Figure 29: Relative gain difference
For relative gain, it is measured with laser diode. Here, we need two measurements using the same light source to reduce the geometrical effect. In thefirst one we emit high intensity flashed from the centre of the tank to makeeach PMT can get a suitable number of photons, and then calculate the average charge of each PMT. In the second measurement, we emit low intensity
flashed to make sure that every event only hit a few PMTs so that almost allof these signals are single pe. By taking the ratio of the average charge in thefirst measurement and the hit rate in the second measurement, relative gain ofeach PMT can be estimated. Figure 29 shows the relative gain distribution foreach PMT, and its dispersion was measured to be 6.8% of RMS.
All of these calibration works were carried out when EGADS tank was filledwith pure water. And other works such as Rayleigh scattering measurement
were also performed.
3.3.5

Long term stability

After basic calibration works described in the previous sections, it is also
important to monitor the long term performance of the PMTs. So we installed
the Xe flash lamp with scintillator ball into a side hole of the tank as a longterm monitor. The side hole is about 2m from the centre hole. The time-relatedchange of PMTs is termly checked.

30

Figure 30: Water transparency change monitored by Xe trigger. It is estimated by the ratio of the output charge of the most distant PMTs and thenearest PMTs.
This monitor can also be used to make a cross check for the water qualitychange in the tank. We choose the farest and nearest PMTs from the scintillatorball and take the ratio of their charges. The long term change of the ratio isshown in Figure 30, it has the same trend with the water transparency measurement of UDEALtransparency decreased suddenly when gadolinium sulfate
was injected, and then recovered after circulation system started running.

31

4

EGADS data analysis

4.1

Event reconstruction

The vertex of event is the position where the electron or muon exceeds
Cherenkov threshold and begin to produce Cherenkov light. By strict saying,
it is not a point but a track because the charged particle will continue to emit
Cherenkov light as long as its velocity is larger than light. However, in case of
low energy events like SRN, the scattered electrons can only go through several
cm in water, while the vertex resolution in Super-K is about 100cm. Thus, thetrack length is negligible and the vertex can be regarded as a point. In addition,
the number of photons produced in low energy events is so little that most of
the PMTs can only get a single photon signal. This means, reconstruction of
low energy events only need the timing information, while high energy events
also need to use charge information of the PMTs. Super-K has several software tools for the reconstruction of low energy events. The latest one is called
Branch Optimization Navigating Succesive Annealing Iterations (BONSAI). It
is developed on the base of Kai-fit, Clus-fit and Hayai, which were used in thepast. BONSAI has the best precision and resolution but it cost more time forcalculation than the others [18]. BONSAI fitter has been replanted to EGADS,
with the detector size and PMT position redefined. Other modifications arealso applied according to the conditions of EGADS.
4.1.1

Vertex reconstruction

The first thing of event reconstruction is to determine the vertex of the eventby using the timing signal and the positions of the PMTs. The real time when
the charged particle begin to produce Cherenkov light is obtained by subtracting
time of flight (TOF) from output timing information of each PMTs.
q
n
2
2
2
(x − xi ) + (y − yi ) + (z − zi )(17)tres,t = ti −cHere i means PMT number, n/c means velocity of light in water, ti and(xi , yi , zi ) are the position and timing signal of the PMTs. In ideal case we
expect the reconstruction position to make tres,i of all the hit PMTs to beequal. However there always exist background hits, which are caused by afterpulse, dark noise, reflection or else. To take them into consideration, BONSAI
calculates the likelihood of every event as:
L(~x, t0 ) =

N
hits
X

log(P (∆ti (~x)))

(18)

i=1

Here t0 is the average time of selected hits, and ti is the result of subtracting t0 from each tres,t . P (∆ti (~x)) is the possibility density function of typical
Cherenkov events. In Super-K, there is a calibration device called LINAC, it
can accelerate electrons and introduce them into the tank. The PDF used forevent reconstruction in Super-K is evaluated by LINAC, but EGADS doesn’t
have such device so the PDF of EGADS is made by Monte Carlo simulation.
After-pulse, dark noise and other parameters are well tuned by Cf-Ni source tomake sure MC and data have good agreement. Details are shown in 4.1.1.
32

Figure 31: The likelihood function which BONSAI uses for vertex reconstruction. The peaks around 40ns and 100ns are due to after pulse. [19]BONSAI will search the best vertex by maximizing the likelihood. The
fitting precision can also be estimated by the value named ”goodness”. It isdefined as:
N

hits
X
1
tres,t − tmean 2
1
exp(−
)
goodness = PNhits 1 ×
2
σ
2σ 2
2
i=1
i=1

(19)

σ

σ is the time resolution of the PMTs. Goodness ranges from 0 to 1, while
an ideal event will have a value of 1.
4.1.2

Direction reconstruction

After determining the vertex of the event, we should determine the incident
direction. Since the mass of electron is so little that in most of the cases thescattered electron has a velocity of β ≈ 1, even in low energy events like supernova neutrinos. Therefore, Cherenkov angle of the signal is expected to be closeto 42 degrees. However, the real signal does not perform to be a clear ring shapebecause of several effects like the multiple scattering of electron in water, thescattering and reflection of Cherenkov light, dark hits and so on. To determine
the direction with a better precision, firstly the tres,i of all the hit PMTs arecalculated and only the ones which are in the 50ns time window around thepeak are selected. The maximum number of hit PMTs in this 50ns window iscalled N50 . The direction is determined by the selected PMTs by maximizing
the likelihood as [20]
~ =
L(d)

N50
X

log(Pi (cosθdir )) ×

i=1

cosθi
a(θi )(20)

The function Pi (cosθdir ) is the possibility density function of the opening angle
between the incident direction and the vector from vertex point to hit PMT. The
PDF is made by Monte Carlo simulation. θi is the incident angle of Cherenkov
33

light to PMT surface, and the function a(θi ) describes the acceptance of thephoton by the photo-cathode of the PMT. The initial direction is calculated
as the sum of the vectors from the vertex point to all the PMTs selected by
N50 . Then the direction will searched with a spacing of 20 degrees, 9 degrees, 4
degrees and finally 1.6 degrees. In Super-K the direction resolution of 10MeV
electron is about 27 degrees according to LINAC calibration, so this searchspacing is small enough.
N50
Xd~init =
~vi
(21)
i=1

4.1.3

Energy reconstruction

Roughly, the energy of incident particle is in proportion to the number ofphotons produced by Cherenkov light. For low energy events, the number ofphoton is very little, for example, a 16MeV electron can only produce 2600
photons. In such events, PMTs could only get signals of one photon. So theenergy of incident particle can be calculated only by the number of hit PMTs,
instead of using their output charge. Another advantage of this method is, thecalculation will not be affected by PMT gain. The charge distribution of one
photon signal is shown in previous chapter. It is very difficult to recognize thenumber of photoelectrons when the signal is at a level of only several photons.
Because of all these above, N50 is used for energy reconstruction, and corrections
are applied to obtain the effective hits.
N50
X
ri
RcoverNall
× exp( ) × G(i)]×[(Xi + tail − dark ) ×
Nef f =
N
S(θ
,
ψ
)
λ
alive
i
i
i=1

(22)

Xi : correction for multi-photonelectron
When the event occurs near the wall of the tank, and the Cherenkov light goesforward to the wall, then the number of hit PMTs will be very little and each
PMT will have high possibility to get more than one photon. This effect iscorrected by taking the ratio xi of hit PMTs in the 3 × 3 area surrounding thei-th PMT and the total number of hit PMTs. Xi is defined as:((log xi1−1 )/xi xi < 1
(23)
3.0
xi =1
In this correction, it is assumed that the photons are uniform in the 3 × 3 area
and their distribution follows Poisson statistics.
εdark : correction for dark noise
εdark =

50ns × Nalive × Rdark
N50

(24)

Dark hits may occur in the 50ns window accidently so it should be subtracted
from the effective hits. Nalive is the number alive PMTs and Rdark is the rateof dark hits. In EGADS, dark rate is monitored by Laser Diode every day.

34

εtail : correction for reflection
If Cherenkov light is reflected, it will acts as a late hit outside the 50ns window.
This is corrected as:
εtail =

N100 − N50 − Nalive × Rdark × 50ns
N50

(25)

Similarly to the definition of N50 , N100 is the maximum number of hit PMTs
in 100ns time window.
Nall
Nalive: correction for dead PMTs
A correction for PMTs which are not working well.
1
S(θi ,ψi ): correction for the coverage of photo-cathodeThe effective coverage of photo-cathode depends on the incident angle of photons. Details about it can be found in reference.
exp( rλi ) : correction for water transparency
This is a correction for the photons lost by the reason of scattering or absorption
in the water. Here ri is the distance from vertex to i-th PMT, and λ is themeasured transparency.
Gi : correction for gain difference
It is a correction for the relative gain difference of the PMTs.
As discussed before, the energy of charged particle is roughly in linear proportion to the effective hit number. In Super-K the function to scale the energy
is calibrated by LINAC, while in EGADS we use MC simulation. Electrons withenergy of 2∼15MeV are generated in simulation and the relationship between
Nef f and energy is fit by polynomial function.

Figure 32: Nef f comparison of incident electrons with various energy. It is
made by MC simulation.
35

Figure 33: Fitting the relationship of Nef f and energy by polynomial function
4.1.4

Monte Carlo tuning

Monte Carlo simulation program of EGADS detector is based on Geant4.9.6p02. Geant4 is a scientific toolkit developed by CERN, it offers a framework for high energy physics simulation. The simulation program of EGADS iscalled EGSIM, while the official version of Super-K simulation program is called
SKDETSIM. EGSIM was developed on the base of SKDETSIM, it redefines thedetector and PMTs, and simulates the neutron capture process by gadolinium
and protons in 0.2% gadolinium water. The performance of Cherenkov photon in water depends on its wavelength. There are three processes: Rayleighscattering, Mie scattering, and absorption. The water transparency of 0.2%
gadolinium water is measured by spectrometer and has already be inputted into EGSIM. However, it is hard to know how much of the undetected photons
are due to absorption and how much of them are due to scattering. We have designed a laser for Rayleigh scattering measurement and the experiment is still inprogress. Currently, we determine the parameters by assuming 90% absorption
and 10% scattering.

36

Figure 34: Timing comparison of Data& MC in pure water

Figure 35: Reconstruction energy of
Data& MC in pure water

Figure 36: N50 of data&MC

Figure 37: Goodness of Data&MC inpure water. The definition of goodness
can be found in previous session.

Figure 38: Dirks of Data&MC in purewater. Dirks is a value used to estimate
the fitting precision of event direction.

Other calibration results, such as charge distribution of single photon, QE
and gain of PMTs, are also inputted. Dark rate and after-pulse of PMTs are
finally tuned by Ni-Cf source which is also used for relative QE measurement,37

because the signals from Ni-Cf source have a comparatively simple performancein water. Figure above shows the comparison of Ni-Cf data and EGSIM simulation results. After MC tuning, now data and MC have good agreement.

4.2

Estimation of neutron capture efficiency

4.2.1

Detection setup

The most important point of SK-Gd project is the detection of ∼8MeV
gamma from neutron capture on gadolinium. In order to estimate the neutron
capture efficiency of gadolinium in EGADS, Am/Be are chosen as a neutron
source. 241 Am decays to 237 Np by giving out a 4 He, then 9 Be reacts with
4
He and finally a neutron and a 4.4MeV gamma ray are produced. As mentioned
before, in SRN detection events are expected to have two signals, the prompt
one is the Cherenkov light made by positron, and the delayed one is the gamma
ray made by neutron capture. To make similar events as SRN, Am/Be source isplaced on the top of BGO crystal, and the 4.4MeV gamma from Am/Be source
can hit on BGO and make scintillation light. The scintillation light made by
4.4MeV gamma has a large number of PMT hits and can be easily separated
from neutron capture gamma. By such setting, the scintillation events can beconsidered as the prompt signal while the neutron capture gamma is the delayed
signal, and neutron capture efficiency can be estimated by coincidence detectionof these two.

Figure 39: Measurement setup of Am/Be experiment
4.2.2

Data reduction

Before comparing data to Monte Carlo simulation, we should first consider
how to remove the background events in data. Scintillation light produced by
BGO was found to be too bright that almost all of 240 EGADS PMTs will be hit
and it may cause a lot of afterglow events. To reduce the intensity of scintillation
light, we cover a kind of black polyethylene terephthalate sheets. The black
sheet is opened with several holes to make the scintillation light hit a proper
number of PMTs. Figure 40 shows the PMT hit timing distribution of prompt
events. As can be seen, there are two peaks in this distribution. First we must38

ensure all of these events are all real prompt events produced by 4.4MeV gamma
rays and BGO. Figure 40 shows the different performance of Cherenkov lightand scintillation light in PMT timing distribution. As can be seen, obviously
Cherenkov signal has a much sharper shape than scintillation signal. The N30
and N400 distribution of prompt events is also in Figure 40. The points around(N30 = 20,N400 = 80) are from scintillation light, and the points around (N30 =40,N400 = 40) can be considered to be Cherenkov background events. Therefore,
to check if these events are scintillation light emitted by BGO, we calculated
the ratio of N30 and N400 of all the prompt events. A cut of N30 /N400 >2.0 is applied to remove the Cherenkov background in prompt events. These
Cherenkov prompt events are from cosmic muon or gamma backgrounds.

Figure 41: N30 and N400 of prompt events. Horizontal axis is N30 andvertical axis the N400 .

Figure 40: Timing distribution of typical Cherenkov event and typical scintillation event

Delayed events are applied with reduction. The events with low reconstruction precision(goodness < 0.4, dirks < 0.1, dirks > 0.4) are removed. And weselect the events which are reconstructed in 2m distance from the tank centre,
because the events near the PMT surface have high possibility to be background.
After these so-called ”precut”, the time difference between the delayed eventsand their corresponding prompt events in 0.2% Gd concentration are shown in
Figure 44. The distribution of neutron capture events by Gd follows exponentialfunction and the flat component after 300ns is due to background because thebackground events do not have relationship with the parent prompt event sothey perform to be random.

Figure 42:
goodness.

Event cutting for

Figure 43: Event cutting for dirks.

39

The background in delayed events can be considered to be from the environment and the Am/Be source itself. The former one includes both neutrons andgamma rays from environment, and the latter one means the 4.4MeV gamma
rays and neutron capture events from the source come into the 1ms gate, eventhough they are not related to the prompt event which produced the 1ms gate.
An efficient method can be used to remove all these backgrounds in delayed
events. First we define the events in 0∼500ns in Figure 44 to be on-time events,
and relatively define the events in 500∼1000ns to be off-time events. Then background free distribution could be obtained by subtracting off-time events fromon-time events.

Figure 44: Time difference between prompt event and deleyed events. The
blue line is the expect number of the background from the source itself.
When the backgrounds are removed, data is compared with the results ofMonte Carlo simulation. As mentioned before, the parameters in Monte Carlosimulation are tuned by Ni-Cf source in pure water. As shown in Figure 45 andFigure 46, the time difference and reconstructed energy of data and Monte Carlosimulation have good agreement. If we fit the distribution of time difference by
exponential function as shown in Equation (18), we can obtain the average life
time of the neutron in Gd water. Table 3 shows the neutron life time in different
Gd concentration, the results are also in anticipation.
−xf (x) = p0 × e p1 + p2

40

(26)

Data
MC

2178 ± 44ppm
29.89 ± 0.33µs
30.03 ± 0.77µs

1055 ± 21ppm
51.48 ± 0.52µs
53.45 ± 1.19µs

225 ± 5ppm
130.1 ± 1.7µs
126.2 ± 2.0µs

Table 3: Cherenkov threshold for charged particles in water.

Figure 45: Time difference between prompt and delayed signals.

4.2.3

Figure 46: Reconstrued energy ofdelayed signals.

Fake prompt event

If we count the number of prompt events and delayed events, we found thatparts of the prompt events are not followed with its daughter event. When we
estimate the neutron capture efficiency and detection efficiency of our detector,
we should take such fake prompt events into consideration. The reason for fakeprompt has been understood. Very little of them are from environment, whilemost of them are due to Gd(n,γ). Neutron captured by Gd will produce gamma
rays with a total energy of ∼8MeV, these gamma rays may hit on the BGO andmake scintillation light. If the parent 4.4MeV failed to make prompt trigger,then the scintillation light made by Gd(n,γ) will be recorded as prompt event.
This is the main component of fake prompt events. The effect from environmentis also measured by the same experiment setup except that the Am/Be source
was taken away. The result shows that the fake prompt from environment isabout 8 events per hour and it is quite less when compared to the number
produced by Gd(n,γ).

41

Figure 47: Explanation of the reason of fake prompt events
Since fake prompt events are almost caused by Gd(n,γ), we can estimate
it from the Gd(n,γ) events which we already have. Here we select the events
which are tagged with both prompt and delayed trigger. That means, these
events are inside the 1ms gate which is generated by the parent prompt events,
but they exceed the threshold of prompt trigger. Figure 48 shows the timedifference between double triggered event and its parent prompt event. Fitting
the distribution with exponential function, the average time turns to be 30.11 ±0.74µs and it is consistent with the neutron life time in 0.2% Gd water which isshown in the previous section. To remove the flat part in this distribution, we
can use the on-off method stated before and then we can got the double triggered
events which are really caused by Gd(n,γ) and they are free of backgrounds.

Figure 48: Time difference between the prompt&delayed double triggered
events and their parent prompt events.
Figure 47 shows the comparison of prompt events and the prompt&delayed
double triggered events which are made from on-off method. Prompt event has
two peaks in its distribution, and the distribution of double triggered event is
consistent with one of them. Double triggered event has a low ratio of N400 overN30 , because even if one of the Gd(n,γ) hit on BGO the others will still perform42

Neutron in 0.2% Gd
Fake prompt

lif etime(µs)
29.89 ± 0.33µs
30.11 ± 0.74µs

Table 4: Cherenkov threshold for charged particles in water.
as Cherenkov light. Normalize the distributions with areas between 0∼60hits,
then apply the prompt cut as the last section did, and the proportion of fakeprompt events after reduction is 10.02%.

Figure 49: Applying Nhit cut ontoFigure 50: Applying N400 /N30
the prompt&delayed double triggeredcut onto the prompt&delayed
double triggered events
events4.2.4

Neutron capture efficiency

The purpose of Am/Be experiment is to calculate the neutron capture efficiency and to make sure it is consistent with our expectation. However, when we
detect a neutron signal, we do not know whether it is from neutron capture on
Gd, or neutron capture on proton or something else. The only to estimate it is
to use MC simulation because in simulation program we can know which event
is from Gd(n,γ) and which one is not. The Figure 51 shows the N50 distributionof MC simulation.

43

Ef fGdcaptureData
84.36 ± 1.79%

MC84.51 ± 0.33%

Table 5: Cherenkov threshold for charged particles in water.

Figure 51: N50 of the simulation result. Different colour shows the different
component
As can be seen from the Figure, the proton capture component decreases tozero around 4MeV. Here we cut the energy by 4.5MeV and the remaining events
are all Gd(n,γ). We can calculate the neutron capture efficiency as follows:
Nprompt × Ef fGdcapture × Ef fcut(Gd) = Non−of f(27)

Here Nprompt is the number of prompt trigger. If we consider that one
prompt event should be followed by a corresponding neutron event, then Nprompt
represents the number of neutrons generated from the source. Ef fGdcaptureis the neutron capture efficiency which we want to obtain, and Ef fcut(Gd) isthe analysis efficiency by applying 4.5MeV cut as well as the precut onto theGd(n,γ) events in MC simulation. Non−of f is the number of delayed events after
cutting. And finally after considering 10.02% fake prompt, the neutron capture
efficiency by Gd is shown in Table 5. The result from real data is consistent
with expectation.

44

5

Summary and prospect

In this thesis, basic overview of Super-K detector and details about SK-Gd
project were demonstrated.
To test the Gd effect to Super-K tank, EGADS detector and its own system
has been built. 0.2% gadolinium sulfate has already been successfully dissolved
into EGADS tank. Water system and transparency measurement device andDAQ electronics are running as expected. Basic calibration work was finishedin pure water condition. The measurement of Gd(n,γ) was conducted with
Am/Be source, and neutron capture efficiency of gadolinium in EGADS has
been estimated.
Based on the success of EGADS, SK-Gd project has already been approved by
SK collaboration, with the precise timeline yet to be determined as there arestill some remaining works in EGADS.
One thing is Ra/Rn removing. Ra is the impurity in water and Rn is the daughter nuclear produced in the chain decay of Ra. Both of them have radioactivity
and will be a neutron background for SRN detection. Now Ra/Rn removing
system is being developed in EGADS lab.
Another thing is the update work of electronics. Now the electronics in EGADS
is using Analog Timing Module (ATM), which was also used in Super-K first,
second and third phase. Super-K fourth phase is using a different one called
QTC-Based Electronics with Ethernet (QBEE) because nearby supernova burst
will have a extremely high data rate and high performance computing modules
are needed. EGADS electronics will be replaced with QBEE in the future tohave a completely same condition with Super-K.
In parallel, a GPS timing module and a real-time intelligent trigger system comprised of custom hardware and software will be added, and they are designed to
extract the most detailed, accurate supernova neutrino data possible as rapidly
as possible.
Once the remaining works in EGADS is finished, we will be prepared to add
gadolinium into Super-K.

45

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