[table]capposition=top

# Performance of a prototype TORCH time-of-flight detector

S. Bhasina,b, T. Blakec, N. H. Brookb,, M. F. Cicalac, T. Conneelyd, D.
Cussansa,
M. W. U. van Dijke, R. Fortye, C. Freie, E. P. M. Gabrielf,, R. Gaog, T.
Gershonc,
T. Gyse, T. Hadavizadehg,, T. H. Hancockg, N. Harnewg, T. Jonesc, M. Krepsc,
J. Milnesd, D. Piedigrossie, J. Rademackera, J. C. Smallwoodg, Now at
Manchester Metropolitan University, Manchester, M15 6BH, UKNow at Nikhef
National Institute for Subatomic Physics, Amsterdam, NetherlandsNow at School
of Physics and Astronomy, Monash University, Melbourne, AustraliaCorresponding
author’s email<EMAIL_ADDRESS>
a H.H. Wills Physics Laboratory, University of Bristol, Tyndall Avenue,
Bristol BS8 1TL, UK
b University of Bath, Claverton Down, Bath BA2 7AY, UK
c Department of Physics, University of Warwick, Coventry, CV4 7AL, UK
d Photek Ltd., 26 Castleham Road, St Leonards on Sea, East Sussex, TN38 9NS,
UK
e CERN, CH 1211, Geneva 23, Switzerland
f School of Physics and Astronomy, University of Edinburgh, James Clerk
Maxwell Building, Edinburgh EH9 3FD, UK
g Denys Wilkinson Laboratory, University of Oxford, Keble Road, Oxford OX1
3RH, UK

TORCH is a novel time-of-flight detector, designed to provide charged particle
identification of pions, kaons and protons in the momentum range
2–20$\text{\,Ge\kern-1.00006ptV\\!/}c$ over a 9.5 m flight path. A detector
module, comprising a 10 mm thick quartz plate, provides a source of Cherenkov
photons which propagate via total internal reflection to one end of the plate.
Here, the photons are focused onto an array of custom-designed Micro-Channel
Plate Photo-Multiplier Tubes (MCP-PMTs) which measure their positions and
arrival times. The target time resolution per photon is 70 ps which, for 30
detected photons per charged particle, results in a $10-15\text{\,ps}$ time-
of-flight resolution. A 1.25 m length TORCH prototype module employing two
MCP-PMTs has been developed, and tested at the CERN PS using a charged hadron
beam of 8$\text{\,Ge\kern-1.00006ptV\\!/}c$ momentum. The construction of the
module, the properties of the MCP-PMTs and the readout electronics are
described. Measurements of the collected photon yields and single-photon time
resolutions have been performed as a function of particle entry points on the
plate and compared to expectations. These studies show that the performance of
the TORCH prototype approaches the design goals for the full-scale detector.

##  1 Introduction

The TORCH detector (Time Of internally Reflected CHerenkov light) is designed
to perform particle identification of low-momentum
(2-20$\text{\,Ge\kern-1.00006ptV\\!/}c$) charged hadrons using time-of-flight.
The TORCH detector uses prompt Cherenkov photons which are produced when
charged particles traverse a 10 mm thick quartz plate, combining DIRC-style
reconstruction with timing measurements [1, 2]. The method extends the
techniques which were pioneered by the BaBar DIRC [3] and Belle II iTOP [4, 5]
collaborations. Total internal reflection traps a fraction of the photons
within the plate, which propagate to focusing optics positioned at the
periphery of the plate. Inside the focusing optics, the photons are reflected
onto photo-sensitive detectors by a cylindrical mirrored surface. The geometry
allows for the Cherenkov angle of emission to be reconstructed and the time-
of-arrival recorded.

The principle of the TORCH time-of-flight (ToF) measurement is detailed in
Ref. [2]. From knowledge of the particle entry position in the radiator and
the photon hit coordinate, the Cherenkov emission angle $\theta_{c}$ and hence
the photon path length in the quartz $L$ can be calculated by unfolding the
multiple internal reflections of the photon. Due to chromatic dispersion in
the radiator, photons with different wavelengths propagate at different speeds
according to the group refractive index $n_{g}$ of quartz. The expression
$\cos\theta_{c}=1/(\beta n_{p})$ relates $\theta_{c}$ to the phase refractive
index $n_{p}$ which in turn yields $n_{g}$ via a known dispersion relation.
The time-of-propagation in the quartz and thence the ToF can then be
calculated from the inferred group velocity and $L$. The method also requires
knowledge of $\beta$, the speed of the charged particle, which can be
calculated from the known particle momentum and measured time for each
particle mass hypothesis in turn. This can be propagated through subsequent
reconstruction stages, allowing the preferred mass to be selected.

The design of a single full-sized TORCH module is shown in Fig. 1(a), with
radiator dimensions ${660\times 2500\times 10\text{\,mm}^{3}}$ (width $\times$
length $\times$ thickness). A modular design has been employed to allow
coverage across large areas with flexibility of geometries. The proposed
design for use in the Upgrade II of the LHCb experiment [6] is shown in Fig.
1(b). Here the TORCH detector is composed of eighteen modules covering an area
of $6\text{\,m}\times 5\text{\,m}$. Each module will be equipped with eleven
Micro-Channel Plate Photomultiplier Tubes (MCP-PMTs). When positioned at a
distance of $9.5\text{\,m}$ from the LHCb interaction point, the ToF
difference between $10\text{\,Ge\kern-1.00006ptV\\!/}c$ pions and kaons is
$35\text{\,ps}$, requiring a per-track time resolution of $17.5\text{\,ps}$
for two standard deviations ($\sigma$) and $11.7\text{\,ps}$ for $3\sigma$ of
separation between mass hypotheses. Given $\sim 30$ detected photons per
track, the requirement on the single-photon time resolution is chosen to be
$\sim 70\text{\,ps}$ [7]. In addition, the photons’ time-of-propagation within
the quartz increases the time separation between signals from the different
species due to the differing Cherenkov angles.

This paper builds upon the work presented in Refs. [2, 8], where a small-scale
($120\times 350\times 10\text{\,mm}^{3}$) TORCH demonstrator was tested with
both a circular MCP-PMT and a single square MCP-PMT. Both prototype MCP-PMTs
were produced by Photek, UK [9]. Here the work concerns the development of a
larger, half-length full-width, TORCH module instrumented with two customised
Photek MCP-PMTs and readout electronics, described in Section 2. This TORCH
demonstrator has been tested in a beam at the CERN PS. Section 3 reports the
modelling of the demonstrator. The test beam infrastructure is presented in
Section 4. Section 5 describes the data-driven calibrations made to the data.
In Section 6 the photon counting efficiency of the prototype is reported,
determined by comparing yields in data and simulation. In addition, the timing
resolutions of both single photons and hadron tracks are measured as a
function of track position in the radiator, after which a comparison is made
to the design goals. Finally, a summary and the outlook for future work is
presented in Section 7.

(a)

(b)

Figure 1: TORCH detector design for LHCb Upgrade II. (a) A single TORCH module
with the charged particle path (black line) and the Cherenkov photons (red
lines), (b) the full TORCH detector.

##  2 Design of the prototype

The tests described in this paper were undertaken with a TORCH prototype
module, hereafter referred to as Proto-TORCH. The prototype is constructed
from a $660\times 1250\times 10\text{\,mm}^{3}$ (width $\times$ length
$\times$ thickness) fused silica radiator plate. The plate, which has half the
length of a full TORCH module, is glued to a full-sized focusing block with
matching width at the top of the plate. In addition, specialised mechanics
were manufactured for mounting the MCP-PMTs and the accompanying electronics.
In this section the quartz radiator plate, the focusing block, and the
mechanical construction of the support structure holding the optical assembly
are reported, together with a description of the MCP-PMTs and readout
electronics.

(a)

(b)

Figure 2:  (a) The manufactured radiator plate. (b) The focusing block.

###  2.1 Quartz radiator plate and focusing block

Photographs of the manufactured radiator plate and focusing block are shown in
Fig. 2. All optical components were procured from Nikon Glass111Nikon
Corporation Glass Business Unit, Sagamihara-City, Kanagawa 252-0328 Japan..
The flat plate surfaces of the radiator plate were polished to a surface
roughness of $\sim 0.5\text{\,nm}$ to minimise surface scattering. With this
level of control, simulations show that $90-95\%$ of photons that undergo
$\sim 200$ internal reflections are retained[10]. All side faces of the plate
are also polished, including the bottom surface to allow upward reflections of
downward travelling photons. All edges of the plate are bevelled to 0.1 mm to
avoid sharp edges.

An illustration of the focusing block is shown in Fig. 3(a). The block has a
cylindrical mirrored (aluminised) surface with a focal point $5.5\text{\,mm}$
beyond the exit surface of the block, which is at an angle of $36^{\circ}$ to
the radiator face. The MCP-PMTs have 5.0mm-thick input windows which are
spaced 0.5mm from the focusing block with an air gap in between (to avoid
gluing), such that the focal point coincides with the photo-cathode plane.
Photons propagate at an angle $\theta_{z}$ relative to the radiator face and
upon entering the block are reflected before reaching the MCP-PMT plane. The
curvature of the mirror is such that photons emitted with the same angle
$\theta_{z}$ from any point of the radiator are reflected onto the same
vertical ($y^{\prime}$) coordinate on the MCP-PMT plane. The acceptance of
photons on the detector plane is limited to photons that enter the focusing
block at angles in the range $0.45<\theta_{z}<0.85$ rad. The reflectivity of
the mirrored surface has been measured to be above 85% over the photon energy
range of interest (and is further discussed in Sec. 3). The side faces are
also critical reflective surfaces and as such are polished. The top and bottom
faces are kept rough so light might be diffused outside the block. Whilst this
prevents correlated reflections, associated scattering does result in some
out-of-time background.

(a)

(b)

Figure 3:  (a) A schematic representation of the focusing block, not to scale,
which shows the translation of the photon’s angle of exit from the quartz
plate in the vertical plane into the vertical position on the MCP-PMT plane.
The charged particle path is shown by the black line with the Cherenkov
photons shown by the coloured lines. (b) A technical drawing for the design of
the Proto-TORCH mechanics. Detail is given of the focusing-block mounting
showing the groove in the block, the mounting plate, and aligning micrometer
screws.

The main structural support for the focusing block is via a mounting plate
which is located inside a groove in the block, and this holds the block onto
an outer frame, shown in Fig. 3(b). The groove can contribute towards multiple
reflections within the focusing block and, to mitigate this, the groove
surface is is kept rough and painted black. At each end, there is an
adjustable micrometric screw to hold the block laterally.

The focusing optics and radiator plate were produced separately, and were
bonded together at CERN with Pactan 8030 silicone-based adhesive which has
good transmission characteristics up to 6 eV in photon energy[11] (further
discussed in Sec. 3). The advantage of this adhesive is that it does not set
rigidly and is suited to disassembly if the need arises.

(a)

(b)

Figure 4:  (a) The optical support frame for the quartz radiator, lying
horizontally; the micrometer adjustments are visible at the bottom left, and
the support structure for the MCP-PMTs and electronics, on the right. (b) The
fully assembled prototype in its casing (left) the CAD model, and (right)
after construction.

###  2.2 Mechanical frame

The optical components are mounted in a rigid anodised aluminium mechanical
frame, as shown in Fig. 4(a). The focusing block and the quartz plate assembly
is finely located via micro-metric screws providing (almost) point contact to
the side surfaces of the plate. As these surfaces are reflective-critical, the
contact area is minimised by design. The radiator plate is supported from the
bottom by two micro-metric screws and two additional spring loaded stoppers.
These latter elements compensate for thermal expansion of the aluminium frame.
All point contacts are terminated with black bumpers of dimension $\sim$1.7
cm2, and made of polyoxymethylene (POM).

To bond the optical components, the frame acts as a jig for applying the
optical adhesive between the quartz plate and the focusing block. With the
implementation of micro-metric screws, the radiator plate is first translated
near to the focusing block. Then, by suitable fine-adjustment of the screws,
this allows a thin and carefully-controlled coating of glue of thickness 55
$\mu$m, which minimises transmission light-loss.

A mechanical structure that houses the MCP-PMTs and all the readout
electronics is attached to the optical assembly described above. This
structure implements so-called “comb plates”, which allow the accurate
location of the electronics boards to directly couple to the photo-detectors.
The readout boards are fitted with metallic plates, coupled with thermal
paste, to adequately transfer heat to the comb plates. Copper pipes (visible
in Fig. 4(a)) are embedded in these combs, to provide liquid cooling and to
evacuate the heat. Note that the liquid cooling was not used during this test
beam campaign as only two MCP-PMTs were used, but the mechanics are designed
to allow the system to be extended to the full complement of eleven MCP-PMTs
used in a full-scale module.

The complete assembly: optical components, aluminium frame, photodetectors and
electronics, shown in Fig. 4(b), is housed finally within a large and rigid
light-tight crate. The assembly is mounted at a rotating point which is
located at the top. This allows a tilt around the horizontal $x$-axis
(perpendicular to the beam direction) and hence a variation of the incident
particle angle through the radiator. A mechanism at the base ensures a smooth
and precise rotation of the assembly up to $10^{\circ}$.

###  2.3 Micro-Channel Plate PMTs

During the beam tests, the Proto-TORCH module was instrumented with a pair of
Photek-developed MCP-PMTs, the final devices of a 3-stage R&D plan [9]. The
two MCP-PMTs were located adjacent to the upper corner of the radiator plate;
their associated electronics readout boards are visible in Fig. 4.

Both MCP-PMTs have an intrinsic pixelisation of $64\times 64$ pads over a
$53\times 53$ mm2 active area, within a $60\times 60$ mm2 physical footprint.
The MCP-PMT anode pads are connected directly to an external printed circuit
board (PCB) using anisotropic conductive film. The MCP-PMTs are read out with
a granularity of $8\times 64$ pixels, achieved by electronically grouping
channels on the PCB in the horizontal direction, and seen schematically in
Fig. 5(a). The front surface and back-plane connectors of the MCP-PMT are
shown in Fig. 5(b).

The MCP-PMTs are designed to withstand an integrated anode charge of $5\,{\rm
C}/{\rm cm}^{2}$ [12] by utilising an atomic layer deposition (ALD) coating on
the micro-channel plates. The electron avalanche within the MCP-PMT deposits
charge on a resistive layer inside the PMT, which is capacitively coupled to
the anode pads via an insulating layer. Since the avalanche of charge produced
by a single photon in the MCP typically causes hits on multiple channels, the
centroid of these hits allows the spatial and timing precision of the photon
arrival to be improved using a charge-weighting technique in the vertical
direction. This achieves an effective $8\times 128$ granularity, which
provides a sufficient angular precision on the reconstructed Cherenkov angle
to meet the TORCH single-photon timing requirements.

The single-photon timing resolution requirement can be realistically broken
down into 50 ps from the MCP-PMT and readout, and 50 ps from the time-of-
propagation resulting from the finite pixel size. The single-photon time
resolution of a 64 $\times$ 64 pixel Photek MCP-PMT has been measured to be
$(47.5\pm 0.7)\text{\,ps}$ in the laboratory [13], including the contribution
from the customised electronics-readout system, described in the section
below.

The two MCP-PMTs under test (hereafter labelled MCPs ‘A’ and ‘B’) are
characterised by their quantum efficiency (QE), multiplication factor and
charge avalanche point-spread function (PSF). The QEs of both MCP-PMTs were
measured in the laboratory prior to the beam tests in October 2018, and the
performance differs for MCPs A and B, as shown in Fig. 6(a). The higher QE of
MCP B resulted in a greater photon yield for that tube. The collection
efficiency of the MCP-PMTs, defined as the probability for a converted
photoelectron to be multiplied through the MCP chain, is quoted by Photek to
be around $65\%$. The gain in each MCP-PMT is estimated to be around
$1.25\times 10^{6}$ electrons for MCP A and $1.35\times 10^{6}$ electrons for
MCP B, based on the calibrated bleeder-chain HV settings. The gain was
measured in the laboratory and was found to vary over the MCP-PMT plane: up to
17% across MCP B, but as high as 50% across MCP A. The insulating layer has a
thickness of $0.3\text{\,mm}$ on MCP A which results in a PSF FWHM at the
anode pads of $1.30\pm 0.13\text{\,mm}$ [8]. MCP B has a $0.5\text{\,mm}$
thick insulating layer, with a PSF FWHM of $1.90\pm 0.06\text{\,mm}$.

(a)

(b)

Figure 5:  (a) The MCP-PMT pixel layout where the $64\times 64$ pixels are
grouped to form 8 columns and charge sharing is used to increase the effective
granularity to 128 rows. (b) The MCP-PMT front surface and the connectors on
the rear side.

(a)

(b)

Figure 6: (a) The measured quantum efficiencies as a function of wavelength of
the MCP-PMTs instrumented on Proto-TORCH, measured at CERN. (b) The absolute
efficiencies of glue transmission, mirror reflectivity and photo-electron
conversion (for MCP B) as a function of wavelength. The photon emission
spectrum and expected photon yield due to the efficiency sources are also
shown, both with arbitrary scaling.

###  2.4 Electronics and trigger

The signals from the MCP-PMTs are read out using customised electronics boards
[14] that use chip-sets developed for the ALICE TOF detector [15]. A modular
electronics system for a small-scale prototype providing up to 256 channels
per system in a 4-board $\times$ 64-channel arrangement has been reported
previously [16] and the Proto-TORCH electronics design evolves from this.

A set of four NINO ASIC chips [17] are located on the so-called NINO board.
Four NINO boards are connected to a single MCP-PMT, each through one of the
four connectors mounted on the MCP-PMT rear surface. Each NINO channel
amplifies the input signal and outputs a square pulse, for which the leading
edge corresponds to the time that the leading edge of the charge deposit
crosses the threshold; the length indicates the Time-Over-Threshold (TOT). The
NINO charge thresholds are estimated to be 20-30 fC over all channels. This is
based on a measurement of four channels from two NINO boards at a threshold
setting of 100 mV (1.65V/1.55V) made previously in Ref. [11]. A single NINO
chip comprises 32-channels, giving a total of 128 channels per NINO board.

The two edges of the NINO output pulse are then time-stamped by a High
Performance Time to Digital Convertor (HPTDC) ASIC [18], located on the HPTDC
board. A single HPTDC board comprises two 32-channel HPTDCs. The HPTDC time
digitisation was set throughout the beam tests close to 100 ps binning (256
bins in 25 ns), which provides a small contribution to the final measured
Proto-TORCH timing resolution of 100/$\sqrt{12}$ ps.

A Readout board collects digitised data from four HPTDC boards and formats
them into Ethernet packets to be sent to a DAQ PC. The data include the
leading edge time of the signal and the TOT. The TOT is correlated to the
charge deposited in the pixel and is used to correct for time-walk of the
signal. The non-linearities in the HPTDC binning are also corrected offline,
with details given in Sec. 5.

The footprint of the new printed circuit boards has conformed to IEC
standards, namely a 3U height of 100 mm with a total stack height of front and
rear boards to fit within the dimensions of a standard 9U crate. This ensures
no interference of the electronics with the siting of the radiator plate.

Figure 7 shows the data-flow of the electronics system and a photograph of the
system for a single NINO board, showing also the connector to an MCP-PMT. The
Proto-TORCH modularity has each 8 $\times$ 64-channel MCP-PMT served by four
NINO boards, eight HPTDC boards, and two Readout boards joined together by a
backplane, with the system read out by two 1 Gbps Ethernet links. The Ethernet
links are connected to a commercial switch with 10 Gbps uplink ports, where
the DAQ PC is connected. The switch controls the routing, traffic control and
buffering, which allows simultaneous readout of all readout boards within the
system.

The readout board communicates with an AIDA Trigger Logic Unit (TLU)[19] using
the EUDAQ2 framework [20], which provides a trigger and synchronisation with
additional beamline counters. The TLU distributes clock, trigger and enable
signals to the readout boards in the system. Once data-taking starts, the
HPTDC measures the photon arrival time and TOT when a trigger signal is
received. The readout boards raise a busy signal to the TLU if a maximum
trigger rate is reached.

(a)

(b)

Figure 7: (a) A schematic and (b) a photograph of the TORCH electronics
readout boards.

##  3 Efficiencies and simulation

Monte Carlo simulation is used to provide expectations of the single-photon
arrival-time distributions and of the photon yields. In addition, the external
contribution towards the time resolution due to the beam profile used in the
test beam (described in Sec. 4) is estimated using simulated events, where the
unknown event-by-event beam-particle entry points result in small deviations
in the path length of Cherenkov photons.

The simulation is generated using Geant4 [21, 22] and takes as input a charged
particle of known species, momentum, and entry position on the radiator. The
profile of the beam entry position is modelled as a 2D Gaussian with widths
$2.73\text{\,mm}$ in $x$ and $2.01\text{\,mm}$ in $y$, based on measurement in
Ref. [8]. The production of Cherenkov radiation is modelled according to the
Frank-Tamm relation [23], with the emission spectrum inversely proportional to
the wavelength squared. The photons are propagated through a modelled radiator
and focusing block, with refractive indices implemented from the
manufacturer’s specifications. The surfaces of the radiator and focusing block
are modelled as dielectric-dielectric boundaries, with properties to match the
surface types as described in Sec. 2.1. The transmission of photons through
the glue that is used to optically couple the radiator and focusing block is
accounted for, which imposes a sharp cut-off at low wavelengths around 220 nm.
The mirrored surface of the focusing block has a wavelength-dependent
reflectivity which plateaus in the middle of the range. The air-gap between
the focusing block exit surface and the MCP-PMT window is also included. The
photon emission spectrum, efficiencies from different sources, and the
resulting expected photon yields are shown as a function of photon wavelength
in Fig. 6(b).

Further, the response of the MCP-PMT and NINO chip is modelled. The
probability of photon conversion in the photocathode is modelled according to
the measured QE, which peaks in the wavelength range $250-300\text{\,nm}$. The
behaviour of the photo-electron through the Micro-Channel Plates is determined
by the collection efficiency and the probability of back-scattering, which can
lead to spatial displacement and time delay of the charge avalanche. A back-
scattering model has been determined based on data taken during laboratory
tests of the MCP-PMTs. The gain amplification of an individual photo-electron
is randomly sampled from a model developed from measurements of the gain made
in laboratory tests. The charge avalanche is spread according to the PSF of
each MCP-PMT, and a Gaussian integral of the charge-spread is performed to
determine which pixels receive sufficient depositions to be above the NINO
threshold, and thus have a hit recorded. The same clustering algorithm used in
the data analysis (described in Sec. 5) is used to cluster the hits into
reconstructed photons.

##  4 Test beam setup

The beam test was performed at the T9 area of the CERN PS using a nominal
8$\text{\,Ge\kern-1.00006ptV\\!/}c$ momentum beam composed of $(47.3\pm
1.5)\%$ pions and $(52.7\pm 1.5)\%$ protons [24]. The beam-line infrastructure
was similar to that of previous test beam campaigns with the smaller
module[8]. The beam-line components are illustrated and are visible in the
photograph of the beam test area in Fig. 8.

Two timing stations provided a time reference and were positioned 11 m apart,
with Proto-TORCH positioned 1.65 m upstream of the downstream station. Each
timing station comprises a $8\times 8\times 100$$\text{\,mm}^{3}$ borosilicate
bar, coupled to a single-channel MCP-PMT to provide accurate timing, and a
pair of crossed scintillators. The borosilicate bar was located relative to
the beam such that Cherenkov light produced by traversing particles was
oriented directly towards the MCP-PMT. The crossed scintillators, each
connected to a PMT, had an overlap of $8\times 8$$\text{\,mm}^{2}$
perpendicular to the beam. The trigger required a signal in both PMTs of the
downstream timing station, which served to narrow the beam spatial definition
and ensured the triggered particles passed through the borosilicate finger.
The timing signals from both timing stations were injected into the Proto-
TORCH readout electronics, eight channels per MCP-PMT, to allow
straightforward synchronisation of the data, which also meant that the timing
signals were digitised using the 100 ps binning of the HPTDC chips. This
scheme had the slight disadvantage that several pixels of the MCP-PMT were not
read out, to be replaced by data from the time-reference stations.

A pair of CO2-filled threshold Cherenkov counters were located upstream of the
first timing station to discriminate pions from protons in the beam. These
enabled a method of particle identification independent of the ToF provided by
the timing stations. In addition, a large scintillator coupled to a single-
channel PMT was used in conjunction with signals from both Cherenkov counters
to reduce random noise. An EUDET/AIDA pixel beam telescope [25] was used to
measure the beam profile [8], and some of its scintillating layers were used
in the trigger definition.

In the test beam, the TORCH light-tight crate was mounted on a translation
table, allowing free movement in both directions perpendicular to the beam
direction. The radiator was tilted to $5^{\circ}$ with respect to the vertical
in order to improve the light collection efficiency from incident charged
particles.

The performance of Proto-TORCH was studied at a total of six beam-entry
positions, as indicated in Fig. 10. The positions relative to the upper left
corner of the plate (nearest to the MCP-PMTs) are shown in Table 10. These
geometrical configurations were chosen such that the Cherenkov patterns were
well-contained within the instrumented region of the MCP-PMT detector plane.

(a)

(b)

Figure 8: (a) Views of the T9 test beam area along the beam direction. The
beam trajectory has been overlaid and travels from right to left. One of the
Cherenkov counters, the telescope and the downstream timing station are not
visible in the photograph. (b) The layout of the components of the test beam,
with the beam travelling from right to left.

Figure 9:  Proto-TORCH track positions, with coordinates given in Table 10.

Position |  $\Delta x$ (mm) |  $\Delta y$ (mm)
---|---|---
1 | 5 | 175
2 | 60 | 175
3 | 5 | 488.6
4 | 5 | 801.9
5 | 5 | 1115.4
6 | 330 | 1115.4

Figure 10:  Positions of tracks in Proto-TORCH with the origin taken at the
upper corner of the radiator closest to the MCP-PMTs.

##  5 Data processing

At the first stage of data analysis, various processing steps were undertaken
to calibrate the data. All calibrations were data-driven and performed on a
large, dedicated set of data, independent from the datasets used for TORCH
analysis. These calibrations included corrections for effects introduced by
the readout electronics: the time-walk of the NINO chip, time alignment of
pixels, and the integral non-linearity of the HPTDC chips. All algorithms are
described in Refs. [2, 8] and summarised below.

  * •

Pixel-to-pixel time alignment and time-walk calibration: Different routing-
line lengths on the NINO and HPTDC boards give small pixel-to-pixel time
offsets. These corrections were determined from the requirement that hits
within a photon cluster have the same arrival time. Using the same procedure,
a timing slew (time-walk) calibration was made for each pixel, and a
correction subsequently made to the arrival time of each photon hit according
to the width of its time-over-threshold.

  * •

HPTDC integral non-linearity (INL): The HPTDC ASICs which digitise the arrival
times and time-over-threshold from the NINO chip employ time-binning which is
not equally spaced in time (integral non-linearity). A calibration was adopted
to correct for the channel-to-channel non-linearity.

  * •

Clustering algorithm: The MCP-PMT is designed such that a single incident
photon will induce charge deposits over several neighbouring pixels, in order
to improve the effective granularity in the vertical direction. In the present
analysis, a simple average position is taken for the centroid of the pixel
hits within a cluster. Charge-to-TOT calibration of the NINO chip would allow
a more accurate cluster centroiding to be performed, and is being developed
for future test beams.

##  6 Test beam analysis

Analysis of the test beam data is categorised into three parts. First, the
single-photon time resolution is determined and compared to the target of 70
ps per photon. The contributions from the intrinsic MCP-PMT response,
electronics readout and photon reconstruction are inferred. Studies of the
resolution for paths of photons involving side reflections in the radiator are
then performed. Second, the yields of photons per charged track are determined
and compared to simulation. The relative yields of photons undergoing higher-
order reflections in the radiator are also assessed. Finally, the per-track
timing resolution is measured for tracks yielding multiple photon clusters,
verifying the improvement in performance when clusters are combined. All the
above analyses employ data taken at Positions 1, 3, 4, and 5 in the radiator;
the exception being for studies of variation of timing resolution and yield
with photon path, where the Position 6 dataset is used.

(a)

(b)

Figure 11: (a) The spatial distribution of reconstructed photon clusters on
MCPs A and B. Pixels marked with a red cross are those where the time
reference signals were injected. (b) The time projection of reconstructed
photon clusters on MCP-PMT column 16, with the photon trajectories that fall
within the MCP-PMT acceptance labelled, and the associated reflections on the
right.

During the beam test, Proto-TORCH was instrumented with two MCP-PMTs
corresponding to 1024 readout channels, 16 of which were allocated to time-
reference channels. Figure 11(a) shows the spatial distribution of
reconstructed photon clusters on the MCP-PMT plane for data taken with the
beam entering the plate at Position 6. The cones of Cherenkov radiation
emitted by the charged hadrons are focused into hyperbolic patterns, which are
folded in on themselves when the light is reflected from the sides of the
module. Signals from different paths in the radiator can be detected in the
same pixel but will arrive at different times. The different QEs of the two
MCP-PMTs is responsible for the lower level of light seen in MCP A. The empty
(dead) channels, represented by white entries in Fig. 11(a), reduces from MCP
A to MCP B as a result of improvements made in the wire bonding procedure of
the NINO chips when mounting on the boards during manufacture.

The time-projection plot (Fig. 11(b)) shows the reconstructed photon arrival
time (relative to the reference time) as a function of the clusters’ vertical
pixel position, for data collected on a typical single MCP-PMT column
(horizontal pixel). The red lines are predicted arrival patterns, simulated
from knowledge of the hadron track position and angle. In this projection, the
different orders of reflection (photon paths in the radiator) are well-
separated. The widths of each order are then measured to determine the single-
photon time resolution. The photon yields are determined by defining contained
regions around each order in this projection, where the regions are tuned to
minimise background counts and to avoid incorrect counting across neighbouring
orders.

###  6.1 Single-photon time resolution

The single-photon time resolution is determined using simultaneous unbinned
maximum-likelihood fits to the photon arrival times with respect to the time-
reference signal ($t_{0}$). A separate fit model is created for each vertical
pixel comprising:

  * •

Peaking structures to fit the signal distributions, modelled by Crystal Ball
functions [26] which fit asymmetric Gaussian distributions. This function
models the tails caused by late arriving back-scattered photoelectrons from
the MCP surface. Analytical reconstruction predictions are used to determine
how many peaking structures are expected for each pixel;

  * •

Peaking background shapes to account for structures observed in the data,
modelled by Gaussians. The structures are bands across all pixels that appear
at the same time, attributed to photons from secondary sources and/or
scattered signal light;

  * •

Polynomial background distributions to account for observed random background
levels.

A simultaneous fit to the photon time distribution is performed across all
vertical pixels of a column. In each vertical pixel the yields, mean times and
widths of the Crystal Ball probability distribution functions (PDFs) are free
to float, however the widths for individual reflection orders are shared in
the fit across all vertical pixels in the same MCP-PMT column. The parameters
of the background PDFs are also shared across all vertical pixels in a column.
The width of the Gaussian component of the fitted Crystal Ball function gives
the measured resolution per order of reflection per column,
$\sigma_{\text{meas}}$. An example fit to a single pixel is shown in Fig.
12(a) in which two peaking orders of reflection are observed, with one peaking
background structure and the polynomial background.

The measured resolution $\sigma_{\text{meas}}$ receives contributions from the
experimental setup that are external to TORCH, which need to be subtracted.
Here the start-time resolution is the primary contribution. During nominal
data taking, the rate of hits is maximised by requiring only the downstream
timing-reference scintillator stations to have fired. From a study of the time
difference between the two timing signals for different trigger
configurations, the $t_{0}$ resolution, $\sigma_{\text{time ref}}$, is
measured to be $53.2\pm 0.6\text{\,ps}$. The second contribution is due to the
finite size of the beam; the uncertainty in the particle entry position in the
quartz plate results in a variation of the photon path length and hence its
arrival time. From simulation and a knowledge of the beam profile, the
contribution to the time resolution, denoted by $\sigma_{\text{beam}}$, is
between 15.1 and 30.4 ps [24], dependent on the height at which the beam
enters the plate. The above contributions are subtracted in quadrature from
$\sigma_{\text{meas}}$ to obtain the TORCH single photon time resolution:

$\sigma_{\text{TORCH}}^{2}=\sigma_{\text{meas}}^{2}-\sigma_{\text{time
ref}}^{2}-\sigma_{\text{beam}}^{2}.$ (1)

The time resolution is measured for several beam entry positions, indicated by
Positions 1, 3, 4 and 5 in Fig. 10. Here the distance from the top of the
plate to the beam is varied from 175 mm to 1115.4 mm in four steps. The TORCH
time resolution for each MCP-PMT column and beam position is shown in Fig.
12(b), separately for the samples of pions and protons. It can be seen that
the time resolution of the prototype approaches the design goal of 70 ps but
there is some degradation for entry positions far from the MCP-PMTs, which is
to be expected. Due to the finite size of the pixels, the uncertainty on the
position and the Cherenkov angle introduces an uncertainty in the measurement
of the photon energy, hence the time resolution. This uncertainty scales
linearly with path length and propagation time. As a compensation for this
degradation, in any future PID reconstruction, there will be additional
information from the time-of-propagation measurement for the larger photon
path lengths, where the difference in Cherenkov angle of any two particle
species will result in a spatial and timing separation at the photodetector
plane.

(a)

(b)

Figure 12:  (a) An example of a fit to the time of arrival of photons on a
single vertical pixel (pixel 30 as shown in Fig. 11(b)), used to measure the
single photon time resolution. On this pixel there are two orders of
reflection, with times of arrival that peak at 8.9 ns and 9.8 ns. Their
respective measured widths are $124\pm 3$ ps and $134\pm 3$ ps. In addition to
the two signal peaks (blue / yellow), the background contributions (dotted)
comprise the total fit (cyan). (b) The single-photon time resolution
determined in different columns of MCP B and for different beam positions
(Positions 1 ($\times$), 3 ($\circ$), 4 ($\hbox to0.0pt{$\sqcap$\hss}\sqcup$),
5 ($\triangle$) as indicated in Fig. 10). The full (dotted) lines are the
results from the pion (proton) samples.  Figure 13: The TORCH time resolution
of the proton sample, displayed as a function of the propagation time and
number of hits per photon cluster. The overlaid surface is the result of the
2D fit described in the text.

To quantify the contributions to the TORCH time resolution from different
sources, a two-dimensional fit is performed as a function of the photon
propagation time (directly related to the beam entry position) and photon-
cluster size, shown for protons in Fig. 13. The time resolution is
parametrised by

$\sigma_{\text{TORCH}}^{2}=\sigma_{\text{prop}}(t_{p})^{2}+\sigma_{\text{MCP}}^{2}+\sigma_{\text{RO}}(N_{\text{Hits}})^{2},$
(2)

where the term $\sigma_{\text{prop}}(t_{p})$ characterises the contribution
that grows with photon propagation time, $t_{p}$; a constant term
$\sigma_{\text{MCP}}$ is associated to the resolution of the MCP-PMT; a term
$\sigma_{\text{RO}}(N_{\text{Hits}})$ describes effects from the charge-spread
and readout process which is a function of the number of hits in a cluster,
$N_{\text{Hits}}$. A linear dependence on $t_{p}$ and a
$1/\sqrt{N_{\text{Hits}}}$ dependence on ${N_{\text{Hits}}}$ are assumed in
$\sigma_{\text{prop}}$ and $\sigma_{\text{RO}}$, respectively. The results of
the fits are presented in Table 1, together with target values, which assume a
33 ps intrinsic MCP-PMT resolution added in quadrature with a
$60\,\text{ps}/\sqrt{N_{\text{Hits}}}$ readout resolution, giving 50 ps for
2.5 hits per cluster. The time-of-propagation resolution assumes a 50 ps
resolution based on a photon propagation time for a 2.5m quartz length. Whilst
the data do not entirely match expectations for the running of the
$\sigma_{\text{prop}}$ and $\sigma_{\text{RO}}$ terms, the MCP resolution term
is in agreement. The latter two resolutions are expected to improve with
future electronics calibrations, and the sources of these contributions will
be further studied in laboratory tests.

Table 1: The results of a 2D fit to the single photon time resolution as a function of propagation time, $t_{p}$ in  ps, and the number of hits per photon cluster. The results of analysis of both the pion and proton samples are shown separately and are consistent with each other. The target performance is also shown.  Contribution | Fitted values (ps) | Target values (ps)
---|---|---
Pion | Proton
$\sigma_{\text{prop}}(t_{p})$ | $(8.3\pm 0.7)\times 10^{-3}\times t_{p}$ | $(7.6\pm 0.5)\times 10^{-3}\times t_{p}$ | $(3.75\pm 0.8)\times 10^{-3}\times t_{p}$
$\sigma_{\text{MCP}}$ | $34.5\pm 8.6$ | $31.0\pm 7.6$ | $33$
$\sigma_{\text{RO}}(N_{\text{Hits}})$ | $(96.2\pm 6.7)/\sqrt{N_{\text{Hits}}}$ | $(95.0\pm 6.0)/\sqrt{N_{\text{Hits}}}$ | $60/\sqrt{N_{\text{Hits}}}$

Data taken with the beam entering the plate at Position 6, a location which is
centrally located towards the bottom of the plate, are used to study the time
resolutions of photons that have undergone multiple side and/or bottom
reflections in the plate, as shown in Fig. 11(b). Photons collected on MCP B
are studied, where there is good separation between different orders of
reflection across all columns.

The simultaneous fit, as described above, is used to determine the resolutions
of the six orders of reflection in each column. For each order, a weighted
average of the measured resolutions across all columns is calculated and is
shown in Fig. 14(a). Figure 14(b) shows the resolution as a function of the
total number of photon reflections in the quartz radiator, determined from
simulation. The number of reflections from the front and back surfaces as well
as those from the side and/or bottom faces are counted, although dominated by
reflections from the front/back. The vertical error bars indicate the
systematic uncertainties on the measurements associated with the column
averaging, whilst the horizontal error bars indicate the range of the number
of reflections.

The measured resolution for the direct photon path (path number 1) is
approximately 100 ps which is similar to the measured resolution of direct
photons from Position 5. Photon paths with side and bottom reflections have
slightly degraded resolutions, to be expected from the increased path length
and total numbers of reflections.

(a)

(b)

Figure 14: (a) Single-photon time resolution for different photon paths
originating from pions entering the plate at Position 6. (b) Single-photon
time resolution as a function of the total number of reflections made inside
the quartz radiator (taken from simulation) for different photon paths. The
colours indicate the paths as shown in Fig. 11(b).

###  6.2 Photon yields

The number of photons collected in Proto-TORCH are counted and compared to
yields obtained from simulated samples. To exclude photons that are likely to
have originated from background sources, photons are only counted if they
arrive within $0.5\text{\,ns}$ of the peak time of arrival, and on pixels
close to expectation (determined from simulation).

For beam positions close to the side edge of the quartz, only photons that
travel directly or are reflected once off the nearest side edge are counted.
The yields of the number of photons detected per incident hadron in data,
$N_{\text{photons}}$, are compared to expectations from simulation in Fig. 15.
Some discrepancies between data and simulation are observed; in particular
there are more events in data where no photons are observed than in
simulation. This is attributed to two effects: firstly the likely occurrence
of a small number of false triggers, and secondly that small charge-shared
pulses can have amplitudes below the NINO thresholds which are not accurately
modelled in the simulation. The mean number of photons detected per hadron for
each beam position is shown in Table 2. Improved and consistent agreement is
seen when events with $N_{\text{photons}}=0$ are excluded, better than 80% at
all beam positions. The photon yield reduces when the beam is positioned
further from the MCP-PMTs because the angular acceptance of the detection
surface decreases. Note that the mean photon yield per hadron is significantly
reduced compared to future expectations of 30 photons per charged track for a
fully-instrumented module. This is primarily because only two (of the eleven)
MCP-PMTs are instrumented, and only two of the possible photon paths are
considered here. In addition, future MCP-PMTs are expected to have a much
improved quantum efficiency which will result in larger yields.

(a) Position 1

(b) Position 3

(c) Position 4

(d) Position 5

Figure 15: Photon counting yields for the four beam entry positions from data and simulation. Table 2: The mean number of photons detected originating from Positions 1, 3, 4 and 5 in data and simulation. The final column gives the ratio of the mean yields when the contributions from events with zero photons detected in data and simulation are excluded. Position | Mean $N_{\text{photons}}$ | Mean(Data)/Mean(Simulation)
---|---|---
Data | Simulation | All | Excluding $N_{\text{photons}}$=0
1 | 2.605 $\pm$ 0.007 | 3.586 $\pm$ 0.020 | 0.726 $\pm$ 0.004 | 0.843 $\pm$ 0.005
3 | 1.419 $\pm$ 0.005 | 2.016 $\pm$ 0.029 | 0.704 $\pm$ 0.010 | 0.824 $\pm$ 0.010
4 | 0.937 $\pm$ 0.004 | 1.454 $\pm$ 0.024 | 0.644 $\pm$ 0.011 | 0.823 $\pm$ 0.008
5 | 0.677 $\pm$ 0.002 | 1.127 $\pm$ 0.022 | 0.600 $\pm$ 0.012 | 0.820 $\pm$ 0.009

The yields of photons that have undergone multiple side reflections within the
quartz plate are also studied, using data taken with the beam at Position 6.
This central location towards the base of the plate allows for reflections
from both side surfaces and the bottom surface of the radiator to be observed.
As shown in Fig. 11(b), some orders of reflection arrive on the same pixel
close in time. To minimise double counting and mis-association, the boundaries
around each order are adapted from the nominal $\pm 0.5\text{\,ns}$ region for
each column individually. The yields from different photon paths are presented
in Table 3 and good agreement is generally seen in the photon yields when
compared to simulation. The deficiency in photon yields in data for photons
reflecting from the bottom surface is not completely understood, although we
note these photons undergo a significantly higher number of reflections
compared to the other paths within the radiator. Possible causes may be a
reduced-quality finish of this surface (which is not mirrored) and
interference with a mounting support bracket which is in close proximity.

Table 3: The yields of different photon paths originating from Position 6 in data and simulation. The path number corresponds to the paths shown in Fig. 11(b). The percentage is the fraction of the sum of yields from all paths.  Reflections (path number) | Data | Simulation
---|---|---
Yield | % | Yield | %
Direct (1) | 47533 | 27 | 23790 | 25
One side (left) (2) | 46300 | 26 | 21422 | 23
One side (right) (3) | 37383 | 21 | 16458 | 18
Two side (4) | 28936 | 16 | 13957 | 15
One bottom (5) | 9193 | 5 | 10624 | 11
One bottom, one side (6) | 9100 | 5 | 7574 | 8

###  6.3 Per-track time resolution

The final stage of the analysis involves measuring the so-called “per-track”
timing resolution, where the best estimate of the track time is determined
from a combination of arrival times of all photon clusters in the event. The
overall TORCH timing performance relies on there being a
$1/\sqrt{N_{\text{photons}}}$ dependence, assuming that the measurement
properties of individual photon hits are uncorrelated with others from the
same track. In what follows, the time-stamps of the individual photons from a
single incident track as identified in Sec. 6.1 are combined, and the
corresponding time resolution determined.

The analysis combines information from photons that arrive on different MCP
columns. In order to increase the yield of events that have several detected
photons, hits on both MCPs A and B are used. The per-track time resolution is
measured as a function of track entry position in the quartz radiator, and as
a function of $N_{\text{photons}}$.

The time of arrival of each photon, $t_{\text{meas}}$, is compared to the
expected time of arrival, $t_{\text{exp}}$, obtained from the peak position of
the relevant Crystal Ball function in the single photon analysis. A variable
$\Delta t$ is introduced to provide the best estimate of the average time
difference $<t_{\text{exp}}-t_{\text{meas}}>$ of all photons that originate
from the same hadron. The spread in $\Delta t$ then indicates the best
estimate of the per-track time resolution. The value of $\Delta t$ for each
event is found by constructing a $\chi^{2}$ variable,

$\chi^{2}=\sum\limits_{i}^{N_{\text{photons}}}\left(\frac{t^{i}_{\text{meas}}+\Delta
t-t^{i}_{\text{exp}}}{\sigma^{i}_{\text{meas}}}\right)^{2},$ (3)

minimisation of which with respect to $\Delta t$ allows the most probable
value of $\Delta t$, which is equivalent to the weighted mean.

The pion data (with direct photons paths only) are divided into separate
samples by the numbers of photons detected per event ($N_{\text{photons}}$),
and by track entry point. For each sample, the distribution of $\Delta t$ is
fit with a Crystal Ball function to characterise the signal. Examples of the
$\Delta t$ distribution and fitted PDFs for data taken at Position 1 are shown
in Fig. 16. The width of the Gaussian component of the Crystal Ball function
is taken as the measured per-track time resolution, which is then corrected by
subtracting contributions from the beam spread and time reference according to
Eqn. (1).

The per-track time resolution as a function of the number of photons per event
is shown in Fig. 17 for different beam entry positions. The measured
resolution decreases as the number of photons increases, but more slowly than
a $1/\sqrt{N_{\text{photons}}}$ dependence. The 1/$\sqrt{N_{\text{photons}}}$
dependence assumes that the underlying resolution is the same for all photons
however the greater effect of backscattered tails for low
$N_{\text{photons}}$, seen in Fig. 16, is a likely cause of a deviation from
the expected behaviour. A further systematic effect can be associated with the
clustering procedure, common across all hits. In addition, correlations are
possible within the electronics between closely-spaced multiple photon hits: a
common clock which defines the 100 ps TDC binning services 64 adjacent
channels of the HPTDC chips, which could contribute to deviations from an
uncorrelated 100/$\sqrt{12}$ ps bin resolution. A significantly finer time bin
designed into the next generation of TDCs will alleviate this issue. Such
features still need to be fully understood so that improvements in the
resolution can be made in the future.

(a)

(b)

Figure 16: The distribution of $\Delta t$ for events with beam entry at
Position 1, with (a) one photon detected per event and (b) three. The means
and widths specified refer to the means and sigmas respectively of the primary
Gaussians in the Crystal-Ball fits. The width quoted is not yet corrected for
external time resolution sources.  Figure 17: Proto-TORCH time resolution as a
function of the number of collected photons. The dotted lines indicate the
function $\sigma_{t}/\sqrt{N_{\text{photons}}}$, where $\sigma_{t}$ = 60, 80,
100, 120 ps from the bottom upwards.

##  7 Conclusions

Results have been reported from a half-height, full-width LHCb TORCH prototype
module, using samples of 8$\text{\,Ge\kern-1.00006ptV\\!/}c$ pions and protons
from the CERN T9 test beam. The prototype was instrumented with two custom-
built MCP-PMTs (out of a possible eleven). Photon yields from different track
locations are consistent with the expectations from simulation, indicating
that acceptance effects and sources of efficiency are largely understood.
Single-photon time resolutions of the prototype have been measured for
different beam entry positions in the quartz radiator plate. For entry
positions close to the MCP-PMTs, the desired 70 ps time resolution is
achieved. For positions further from the MCP-PMTs, and for photon paths that
undergo reflections from the side and/or bottom of the radiator, a dependence
on the path-length of the photons is expected, however the dependence seen in
data is worse than predicted by simulation. This performance should be
improved by future calibrations of the MCP-PMT readout electronics. The
measurement of the time resolution of the charged track as a function of
number of photon hits needs further study, and to understand the effect of
clustering and correlations of closely-spaced hits of photons within the MCP-
PMTs on the expected performance.

A test beam campaign is planned for the end of 2022, which will employ the
fully instrumented TORCH prototype (with up to eleven MCP-PMTs). This will be
used to further verify the photon yield and time resolution performance, and a
mixed charged-particle beam will be used to measure the time-of-flight PID
separation of different particle species over a range of momenta.

## Acknowledgements

The support is acknowledged of the Science and Technology Research Council,
UK, grant number ST/P002692/1, and of the European Research Council through an
FP7 Advanced Grant (ERC-2011-AdG299175-TORCH). We acknowledge the
contributions from the CERN T9 beam operators. We would like to thank Ankush
Mitra, Jeanette Chattaway of the University of Warwick, Keith Clark of the
University of Bristol, Mark Jones and Peter Hastings at the University of
Oxford, and the staff of the workshops at the Universities of Bristol,
Edinburgh, Oxford and Warwick Departments of Physics for their help in the
production of the Proto-TORCH mechanical frame and electronics. We also thank
Jon Lapington of the University of Leicester for his advice and insightful
discussions on the MCP-PMTs and Chris Slatter of Photek for his work on their
development. An individual author (TB) has received support from the Royal
Society (UK).

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F. Feindt, A. Fröhlich, C. Garbers, E. Garutti, P. Gunnellini, M. Hajheidari,
J. Haller, A. Hinzmann, G. Kasieczka, R. Klanner, R. Kogler, T. Kramer, V.
Kutzner, J. Lange, T. Lange, A. Lobanov, A. Malara, A. Nigamova, K.J. Pena
Rodriguez, O. Rieger, P. Schleper, M. Schröder, J. Schwandt, J. Sonneveld, H.
Stadie, G. Steinbrück, A. Tews, I. Zoi Karlsruher Institut fuer Technologie,
Karlsruhe, Germany
J. Bechtel, S. Brommer, E. Butz, R. Caspart, T. Chwalek, W. De
Boer${}^{\textrm{\textdagger}}$, A. Dierlamm, A. Droll, K. El Morabit, N.
Faltermann, M. Giffels, J.o. Gosewisch, A. Gottmann, F. Hartmann20, C.
Heidecker, U. Husemann, P. Keicher, R. Koppenhöfer, S. Maier, M. Metzler, S.
Mitra, Th. Müller, M. Neukum, A. Nürnberg, G. Quast, K. Rabbertz, J. Rauser,
D. Savoiu, M. Schnepf, D. Seith, I. Shvetsov, H.J. Simonis, R. Ulrich, J. Van
Der Linden, R.F. Von Cube, M. Wassmer, M. Weber, S. Wieland, R. Wolf, S.
Wozniewski, S. Wunsch Institute of Nuclear and Particle Physics (INPP), NCSR
Demokritos, Aghia Paraskevi, Greece
G. Anagnostou, G. Daskalakis, T. Geralis, A. Kyriakis, D. Loukas, A. Stakia
National and Kapodistrian University of Athens, Athens, Greece
M. Diamantopoulou, D. Karasavvas, G. Karathanasis, P. Kontaxakis, C.K. Koraka,
A. Manousakis-Katsikakis, A. Panagiotou, I. Papavergou, N. Saoulidou, K.
Theofilatos, E. Tziaferi, K. Vellidis, E. Vourliotis National Technical
University of Athens, Athens, Greece
G. Bakas, K. Kousouris, I. Papakrivopoulos, G. Tsipolitis, A. Zacharopoulou
University of Ioánnina, Ioánnina, Greece
K. Adamidis, I. Bestintzanos, I. Evangelou, C. Foudas, P. Gianneios, P.
Katsoulis, P. Kokkas, N. Manthos, I. Papadopoulos, J. Strologas MTA-ELTE
Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University
M. Csanad, K. Farkas, M.M.A. Gadallah26, S. Lökös27, P. Major, K. Mandal, A.
Mehta, G. Pasztor, A.J. Rádl, O. Surányi, G.I. Veres Wigner Research Centre
for Physics, Budapest, Hungary
M. Bartók28, G. Bencze, C. Hajdu, D. Horvath29, F. Sikler, V. Veszpremi, G.
Vesztergombi${}^{\textrm{\textdagger}}$ Institute of Nuclear Research ATOMKI,
Debrecen, Hungary
S. Czellar, J. Karancsi28, J. Molnar, Z. Szillasi, D. Teyssier Institute of
Physics, University of Debrecen
P. Raics, Z.L. Trocsanyi30, B. Ujvari Karoly Robert Campus, MATE Institute of
Technology
T. Csorgo31, F. Nemes31, T. Novak Indian Institute of Science (IISc),
Bangalore, India
J.R. Komaragiri, D. Kumar, L. Panwar, P.C. Tiwari National Institute of
Science Education and Research, HBNI, Bhubaneswar, India
S. Bahinipati32, C. Kar, P. Mal, T. Mishra, V.K. Muraleedharan Nair Bindhu33,
A. Nayak33, P. Saha, N. Sur, S.K. Swain, D. Vats33 Panjab University,
Chandigarh, India
S. Bansal, S.B. Beri, V. Bhatnagar, G. Chaudhary, S. Chauhan, N. Dhingra34, R.
Gupta, A. Kaur, M. Kaur, S. Kaur, P. Kumari, M. Meena, K. Sandeep, J.B. Singh,
A.K. Virdi University of Delhi, Delhi, India
A. Ahmed, A. Bhardwaj, B.C. Choudhary, M. Gola, S. Keshri, A. Kumar, M.
Naimuddin, P. Priyanka, K. Ranjan, A. Shah Saha Institute of Nuclear Physics,
HBNI, Kolkata, India
M. Bharti35, R. Bhattacharya, S. Bhattacharya, D. Bhowmik, S. Dutta, S. Dutta,
B. Gomber36, M. Maity37, P. Palit, P.K. Rout, G. Saha, B. Sahu, S. Sarkar, M.
Sharan, B. Singh35, S. Thakur35 Indian Institute of Technology Madras, Madras,
India
P.K. Behera, S.C. Behera, P. Kalbhor, A. Muhammad, R. Pradhan, P.R. Pujahari,
A. Sharma, A.K. Sikdar Bhabha Atomic Research Centre, Mumbai, India
D. Dutta, V. Jha, V. Kumar, D.K. Mishra, K. Naskar38, P.K. Netrakanti, L.M.
Pant, P. Shukla Tata Institute of Fundamental Research-A, Mumbai, India
T. Aziz, S. Dugad, M. Kumar Tata Institute of Fundamental Research-B, Mumbai,
India
S. Banerjee, R. Chudasama, M. Guchait, S. Karmakar, S. Kumar, G. Majumder, K.
Mazumdar, S. Mukherjee Indian Institute of Science Education and Research
(IISER), Pune, India
K. Alpana, S. Dube, B. Kansal, A. Laha, S. Pandey, A. Rane, A. Rastogi, S.
Sharma Isfahan University of Technology, Isfahan, Iran
H. Bakhshiansohi39, E. Khazaie, M. Zeinali40 Institute for Research in
Fundamental Sciences (IPM), Tehran, Iran
S. Chenarani41, S.M. Etesami, M. Khakzad, M. Mohammadi Najafabadi University
College Dublin, Dublin, Ireland
M. Grunewald INFN Sezione di Bari a, Università di Bari b, Politecnico di Bari
c, Bari, Italy
M. Abbresciaa,b, R. Alya,b,42, C. Arutaa,b, A. Colaleoa, D. Creanzaa,c, N. De
Filippisa,c, M. De Palmaa,b, A. Di Florioa,b, A. Di Pilatoa,b, W.
Elmetenaweea,b, L. Fiorea, A. Gelmia,b, M. Gula, G. Iasellia,c, M. Incea,b, S.
Lezkia,b, G. Maggia,c, M. Maggia, I. Margjekaa,b, V. Mastrapasquaa,b, J.A.
Merlina, S. Mya,b, S. Nuzzoa,b, A. Pellecchiaa,b, A. Pompilia,b, G.
Pugliesea,c, D. Ramos, A. Ranieria, G. Selvaggia,b, L. Silvestrisa, F.M.
Simonea,b, R. Vendittia, P. Verwilligena INFN Sezione di Bologna a, Università
di Bologna b, Bologna, Italy
G. Abbiendia, C. Battilanaa,b, D. Bonacorsia,b, L. Borgonovia, L.
Brigliadoria, R. Campaninia,b, P. Capiluppia,b, A. Castroa,b, F.R. Cavalloa,
M. Cuffiania,b, G.M. Dallavallea, T. Diotalevia,b, F. Fabbria, A. Fanfania,b,
P. Giacomellia, L. Giommia,b, C. Grandia, L. Guiduccia,b, S. Lo Meoa,43, L.
Lunertia,b, S. Marcellinia, G. Masettia, F.L. Navarriaa,b, A. Perrottaa, F.
Primaveraa,b, A.M. Rossia,b, T. Rovellia,b, G.P. Sirolia,b INFN Sezione di
Catania a, Università di Catania b, Catania, Italy
S. Albergoa,b,44, S. Costaa,b,44, A. Di Mattiaa, R. Potenzaa,b, A.
Tricomia,b,44, C. Tuvea,b INFN Sezione di Firenze a, Università di Firenze b,
Firenze, Italy
G. Barbaglia, A. Cassesea, R. Ceccarellia,b, V. Ciullia,b, C. Civininia, R.
D’Alessandroa,b, E. Focardia,b, G. Latinoa,b, P. Lenzia,b, M. Lizzoa,b, M.
Meschinia, S. Paolettia, R. Seiditaa,b, G. Sguazzonia, L. Viliania INFN
Laboratori Nazionali di Frascati, Frascati, Italy
L. Benussi, S. Bianco, D. Piccolo INFN Sezione di Genova a, Università di
Genova b, Genova, Italy
M. Bozzoa,b, F. Ferroa, R. Mulargiaa,b, E. Robuttia, S. Tosia,b INFN Sezione
di Milano-Bicocca a, Università di Milano-Bicocca b, Milano, Italy
A. Benagliaa, G. Boldrini, F. Brivioa,b, F. Cetorellia,b, F. De Guioa,b, M.E.
Dinardoa,b, P. Dinia, S. Gennaia, A. Ghezzia,b, P. Govonia,b, L. Guzzia,b,
M.T. Lucchinia,b, M. Malbertia, S. Malvezzia, A. Massironia, D. Menascea, L.
Moronia, M. Paganonia,b, D. Pedrinia, B.S. Pinolini, S. Ragazzia,b, N.
Redaellia, T. Tabarelli de Fatisa,b, D. Valsecchia,b,20, D. Zuoloa,b INFN
Sezione di Napoli a, Università di Napoli ’Federico II’ b, Napoli, Italy,
Università della Basilicata c, Potenza, Italy, Università G. Marconi d, Roma,
Italy
S. Buontempoa, F. Carnevalia,b, N. Cavalloa,c, A. De Iorioa,b, F. Fabozzia,c,
A.O.M. Iorioa,b, L. Listaa,b, S. Meolaa,d,20, P. Paoluccia,20, B. Rossia, C.
Sciaccaa,b INFN Sezione di Padova a, Università di Padova b, Padova, Italy,
Università di Trento c, Trento, Italy
P. Azzia, N. Bacchettaa, D. Biselloa,b, P. Bortignona, A. Bragagnoloa,b, R.
Carlina,b, P. Checchiaa, T. Dorigoa, U. Dossellia, F. Gasparinia,b, U.
Gasparinia,b, G. Grosso, S.Y. Hoha,b, L. Layera,45, E. Lusiani, M. Margonia,b,
A.T. Meneguzzoa,b, J. Pazzinia,b, M. Presillaa,b, P. Ronchesea,b, R.
Rossina,b, F. Simonettoa,b, G. Stronga, M. Tosia,b, H. Yarara,b, M.
Zanettia,b, P. Zottoa,b, A. Zucchettaa,b, G. Zumerlea,b INFN Sezione di Pavia
a, Università di Pavia b
C. Aime‘a,b, A. Braghieria, S. Calzaferria,b, D. Fiorinaa,b, P. Montagnaa,b,
S.P. Rattia,b, V. Rea, C. Riccardia,b, P. Salvinia, I. Vaia, P. Vituloa,b INFN
Sezione di Perugia a, Università di Perugia b, Perugia, Italy
P. Asenova,46, G.M. Bileia, D. Ciangottinia,b, L. Fanòa,b, P. Laricciaa,b, M.
Magherinib, G. Mantovania,b, V. Mariania,b, M. Menichellia, F. Moscatellia,46,
A. Piccinellia,b, A. Rossia,b, A. Santocchiaa,b, D. Spigaa, T. Tedeschia,b
INFN Sezione di Pisa a, Università di Pisa b, Scuola Normale Superiore di Pisa
c, Pisa Italy, Università di Siena d, Siena, Italy
P. Azzurria, G. Bagliesia, V. Bertacchia,c, L. Bianchinia, T. Boccalia, E.
Bossinia,b, R. Castaldia, M.A. Cioccia,b, V. D’Amantea,d, R. Dell’Orsoa, M.R.
Di Domenicoa,d, S. Donatoa, A. Giassia, F. Ligabuea,c, E. Mancaa,c, G.
Mandorlia,c, A. Messineoa,b, F. Pallaa, S. Paroliaa,b, G. Ramirez-Sancheza,c,
A. Rizzia,b, G. Rolandia,c, S. Roy Chowdhurya,c, A. Scribanoa, N. Shafieia,b,
P. Spagnoloa, R. Tenchinia, G. Tonellia,b, N. Turinia,d, A. Venturia, P.G.
Verdinia INFN Sezione di Roma a, Sapienza Università di Roma b, Rome, Italy
P. Barriaa, M. Campanaa,b, F. Cavallaria, D. Del Rea,b, E. Di Marcoa, M.
Diemoza, E. Longoa,b, P. Meridiania, G. Organtinia,b, F. Pandolfia, R.
Paramattia,b, C. Quarantaa,b, S. Rahatloua,b, C. Rovellia, F.
Santanastasioa,b, L. Soffia, R. Tramontanoa,b INFN Sezione di Torino a,
Università di Torino b, Torino, Italy, Università del Piemonte Orientale c,
Novara, Italy
N. Amapanea,b, R. Arcidiaconoa,c, S. Argiroa,b, M. Arneodoa,c, N. Bartosika,
R. Bellana,b, A. Belloraa,b, J. Berenguer Antequeraa,b, C. Biinoa, N.
Cartigliaa, S. Comettia, M. Costaa,b, R. Covarellia,b, N. Demariaa, B.
Kiania,b, F. Leggera, C. Mariottia, S. Masellia, E. Migliorea,b, E.
Monteila,b, M. Montenoa, M.M. Obertinoa,b, G. Ortonaa, L. Pachera,b, N.
Pastronea, M. Pelliccionia, G.L. Pinna Angionia,b, M. Ruspaa,c, K. Shchelinaa,
F. Sivieroa,b, V. Solaa, A. Solanoa,b, D. Soldia,b, A. Staianoa, M.
Tornagoa,b, D. Trocinoa, A. Vagnerinia,b INFN Sezione di Trieste a, Università
di Trieste b, Trieste, Italy
S. Belfortea, V. Candelisea,b, M. Casarsaa, F. Cossuttia, A. Da Rolda,b, G.
Della Riccaa,b, G. Sorrentinoa,b, F. Vazzolera,b Kyungpook National
University, Daegu, Korea
S. Dogra, C. Huh, B. Kim, D.H. Kim, G.N. Kim, J. Kim, J. Lee, S.W. Lee, C.S.
Moon, Y.D. Oh, S.I. Pak, B.C. Radburn-Smith, S. Sekmen, Y.C. Yang Chonnam
National University, Institute for Universe and Elementary Particles, Kwangju,
Korea
H. Kim, D.H. Moon Hanyang University, Seoul, Korea
B. Francois, T.J. Kim, J. Park Korea University, Seoul, Korea
S. Cho, S. Choi, Y. Go, B. Hong, K. Lee, K.S. Lee, J. Lim, J. Park, S.K. Park,
J. Yoo Kyung Hee University, Department of Physics, Seoul, Republic of Korea
J. Goh, A. Gurtu Sejong University, Seoul, Korea
H.S. Kim, Y. Kim Seoul National University, Seoul, Korea
J. Almond, J.H. Bhyun, J. Choi, S. Jeon, J. Kim, J.S. Kim, S. Ko, H. Kwon, H.
Lee, S. Lee, B.H. Oh, M. Oh, S.B. Oh, H. Seo, U.K. Yang, I. Yoon University of
Seoul, Seoul, Korea
W. Jang, D.Y. Kang, Y. Kang, S. Kim, B. Ko, J.S.H. Lee, Y. Lee, I.C. Park, Y.
Roh, M.S. Ryu, D. Song, I.J. Watson, S. Yang Yonsei University, Department of
Physics, Seoul, Korea
S. Ha, H.D. Yoo Sungkyunkwan University, Suwon, Korea
M. Choi, H. Lee, Y. Lee, I. Yu College of Engineering and Technology, American
University of the Middle East (AUM), Egaila, Kuwait
T. Beyrouthy, Y. Maghrbi Riga Technical University
T. Torims, V. Veckalns47 Vilnius University, Vilnius, Lithuania
M. Ambrozas, A. Carvalho Antunes De Oliveira, A. Juodagalvis, A. Rinkevicius,
G. Tamulaitis National Centre for Particle Physics, Universiti Malaya, Kuala
Lumpur, Malaysia
N. Bin Norjoharuddeen, W.A.T. Wan Abdullah, M.N. Yusli, Z. Zolkapli
Universidad de Sonora (UNISON), Hermosillo, Mexico
J.F. Benitez, A. Castaneda Hernandez, M. León Coello, J.A. Murillo Quijada, A.
Sehrawat, L. Valencia Palomo Centro de Investigacion y de Estudios Avanzados
del IPN, Mexico City, Mexico
G. Ayala, H. Castilla-Valdez, E. De La Cruz-Burelo, I. Heredia-De La Cruz48,
R. Lopez-Fernandez, C.A. Mondragon Herrera, D.A. Perez Navarro, A. Sanchez-
Hernandez Universidad Iberoamericana, Mexico City, Mexico
S. Carrillo Moreno, C. Oropeza Barrera, F. Vazquez Valencia Benemerita
Universidad Autonoma de Puebla, Puebla, Mexico
I. Pedraza, H.A. Salazar Ibarguen, C. Uribe Estrada University of Montenegro,
Podgorica, Montenegro
J. Mijuskovic49, N. Raicevic University of Auckland, Auckland, New Zealand
D. Krofcheck University of Canterbury, Christchurch, New Zealand
P.H. Butler National Centre for Physics, Quaid-I-Azam University, Islamabad,
Pakistan
A. Ahmad, M.I. Asghar, A. Awais, M.I.M. Awan, H.R. Hoorani, W.A. Khan, M.A.
Shah, M. Shoaib, M. Waqas AGH University of Science and Technology Faculty of
Computer Science, Electronics and Telecommunications, Krakow, Poland
V. Avati, L. Grzanka, M. Malawski National Centre for Nuclear Research,
Swierk, Poland
H. Bialkowska, M. Bluj, B. Boimska, M. Górski, M. Kazana, M. Szleper, P.
Zalewski Institute of Experimental Physics, Faculty of Physics, University of
Warsaw, Warsaw, Poland
K. Bunkowski, K. Doroba, A. Kalinowski, M. Konecki, J. Krolikowski, M. Walczak
Laboratório de Instrumentação e Física Experimental de Partículas, Lisboa,
Portugal
M. Araujo, P. Bargassa, D. Bastos, A. Boletti, P. Faccioli, M. Gallinaro, J.
Hollar, N. Leonardo, T. Niknejad, M. Pisano, J. Seixas, O. Toldaiev, J. Varela
Joint Institute for Nuclear Research, Dubna, Russia
S. Afanasiev, D. Budkouski, I. Golutvin, I. Gorbunov, V. Karjavine, V.
Korenkov, A. Lanev, A. Malakhov, V. Matveev50,51, V. Palichik, V. Perelygin,
M. Savina, D. Seitova, V. Shalaev, S. Shmatov, S. Shulha, V. Smirnov, O.
Teryaev, N. Voytishin, B.S. Yuldashev52, A. Zarubin, I. Zhizhin Petersburg
Nuclear Physics Institute, Gatchina (St. Petersburg), Russia
G. Gavrilov, V. Golovtcov, Y. Ivanov, V. Kim53, E. Kuznetsova54, V. Murzin, V.
Oreshkin, I. Smirnov, D. Sosnov, V. Sulimov, L. Uvarov, S. Volkov, A. Vorobyev
Institute for Nuclear Research, Moscow, Russia
Yu. Andreev, A. Dermenev, S. Gninenko, N. Golubev, A. Karneyeu, D.
Kirpichnikov, M. Kirsanov, N. Krasnikov, A. Pashenkov, G. Pivovarov, A.
Toropin Institute for Theoretical and Experimental Physics named by A.I.
Alikhanov of NRC ‘Kurchatov Institute’, Moscow, Russia
V. Epshteyn, V. Gavrilov, N. Lychkovskaya, A. Nikitenko55, V. Popov, A.
Stepennov, M. Toms, E. Vlasov, A. Zhokin Moscow Institute of Physics and
Technology, Moscow, Russia
T. Aushev National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
M. Chadeeva56, A. Oskin, P. Parygin, E. Popova, D. Selivanova, E. Zhemchugov56
P.N. Lebedev Physical Institute, Moscow, Russia
V. Andreev, M. Azarkin, I. Dremin, M. Kirakosyan, A. Terkulov Skobeltsyn
Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow,
Russia
A. Belyaev, E. Boos, V. Bunichev, M. Dubinin57, L. Dudko, A. Ershov, A.
Gribushin, V. Klyukhin, O. Kodolova, I. Lokhtin, S. Obraztsov, S. Petrushanko,
V. Savrin Novosibirsk State University (NSU), Novosibirsk, Russia
V. Blinov58, T. Dimova58, L. Kardapoltsev58, A. Kozyrev58, I. Ovtin58, Y.
Skovpen58 Institute for High Energy Physics of National Research Centre
‘Kurchatov Institute’, Protvino, Russia
I. Azhgirey, I. Bayshev, D. Elumakhov, V. Kachanov, D. Konstantinov, P.
Mandrik, V. Petrov, R. Ryutin, S. Slabospitskii, A. Sobol, S. Troshin, N.
Tyurin, A. Uzunian, A. Volkov National Research Tomsk Polytechnic University,
Tomsk, Russia
A. Babaev, V. Okhotnikov Tomsk State University, Tomsk, Russia
V. Borshch, V. Ivanchenko, E. Tcherniaev University of Belgrade: Faculty of
Physics and VINCA Institute of Nuclear Sciences, Belgrade, Serbia
P. Adzic59, M. Dordevic, P. Milenovic, J. Milosevic Centro de Investigaciones
Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain
M. Aguilar-Benitez, J. Alcaraz Maestre, A. Álvarez Fernández, I. Bachiller, M.
Barrio Luna, Cristina F. Bedoya, C.A. Carrillo Montoya, M. Cepeda, M. Cerrada,
N. Colino, B. De La Cruz, A. Delgado Peris, J.P. Fernández Ramos, J. Flix,
M.C. Fouz, O. Gonzalez Lopez, S. Goy Lopez, J.M. Hernandez, M.I. Josa, J. León
Holgado, D. Moran, Á. Navarro Tobar, C. Perez Dengra, A. Pérez-Calero
Yzquierdo, J. Puerta Pelayo, I. Redondo, L. Romero, S. Sánchez Navas, L. Urda
Gómez, C. Willmott Universidad Autónoma de Madrid, Madrid, Spain
J.F. de Trocóniz, R. Reyes-Almanza Universidad de Oviedo, Instituto
Universitario de Ciencias y Tecnologías Espaciales de Asturias (ICTEA),
Oviedo, Spain
B. Alvarez Gonzalez, J. Cuevas, C. Erice, J. Fernandez Menendez, S. Folgueras,
I. Gonzalez Caballero, J.R. González Fernández, E. Palencia Cortezon, C. Ramón
Álvarez, V. Rodríguez Bouza, A. Soto Rodríguez, A. Trapote, N. Trevisani, C.
Vico Villalba Instituto de Física de Cantabria (IFCA), CSIC-Universidad de
Cantabria, Santander, Spain
J.A. Brochero Cifuentes, I.J. Cabrillo, A. Calderon, J. Duarte Campderros, M.
Fernandez, C. Fernandez Madrazo, P.J. Fernández Manteca, A. García Alonso, G.
Gomez, C. Martinez Rivero, P. Martinez Ruiz del Arbol, F. Matorras, Pablo
Matorras-Cuevas, J. Piedra Gomez, C. Prieels, T. Rodrigo, A. Ruiz-Jimeno, L.
Scodellaro, I. Vila, J.M. Vizan Garcia University of Colombo, Colombo, Sri
Lanka
M.K. Jayananda, B. Kailasapathy60, D.U.J. Sonnadara, D.D.C. Wickramarathna
University of Ruhuna, Department of Physics, Matara, Sri Lanka
W.G.D. Dharmaratna, K. Liyanage, N. Perera, N. Wickramage CERN, European
Organization for Nuclear Research, Geneva, Switzerland
T.K. Aarrestad, D. Abbaneo, J. Alimena, E. Auffray, G. Auzinger, J. Baechler,
P. Baillon${}^{\textrm{\textdagger}}$, D. Barney, J. Bendavid, M. Bianco, A.
Bocci, T. Camporesi, M. Capeans Garrido, G. Cerminara, S.S. Chhibra, M.
Cipriani, L. Cristella, D. d’Enterria, A. Dabrowski, A. David, A. De Roeck,
M.M. Defranchis, M. Deile, M. Dobson, M. Dünser, N. Dupont, A. Elliott-
Peisert, N. Emriskova, F. Fallavollita61, D. Fasanella, A. Florent, G.
Franzoni, W. Funk, S. Giani, D. Gigi, K. Gill, F. Glege, L. Gouskos, M.
Haranko, J. Hegeman, V. Innocente, T. James, P. Janot, J. Kaspar, J. Kieseler,
M. Komm, N. Kratochwil, C. Lange, S. Laurila, P. Lecoq, A. Lintuluoto, K.
Long, C. Lourenço, B. Maier, L. Malgeri, S. Mallios, M. Mannelli, A.C. Marini,
F. Meijers, S. Mersi, E. Meschi, F. Moortgat, M. Mulders, S. Orfanelli, L.
Orsini, F. Pantaleo, L. Pape, E. Perez, M. Peruzzi, A. Petrilli, G.
Petrucciani, A. Pfeiffer, M. Pierini, D. Piparo, M. Pitt, H. Qu, T. Quast, D.
Rabady, A. Racz, G. Reales Gutiérrez, M. Rieger, M. Rovere, H. Sakulin, J.
Salfeld-Nebgen, S. Scarfi, C. Schäfer, C. Schwick, M. Selvaggi, A. Sharma, P.
Silva, W. Snoeys, P. Sphicas62, S. Summers, K. Tatar, V.R. Tavolaro, D.
Treille, P. Tropea, A. Tsirou, G.P. Van Onsem, J. Wanczyk63, K.A. Wozniak,
W.D. Zeuner Paul Scherrer Institut, Villigen, Switzerland
L. Caminada64, A. Ebrahimi, W. Erdmann, R. Horisberger, Q. Ingram, H.C.
Kaestli, D. Kotlinski, U. Langenegger, M. Missiroli64, L. Noehte64, T. Rohe
ETH Zurich - Institute for Particle Physics and Astrophysics (IPA), Zurich,
Switzerland
K. Androsov63, M. Backhaus, P. Berger, A. Calandri, N. Chernyavskaya, A. De
Cosa, G. Dissertori, M. Dittmar, M. Donegà, C. Dorfer, F. Eble, K. Gedia, F.
Glessgen, T.A. Gómez Espinosa, C. Grab, D. Hits, W. Lustermann, A.-M. Lyon,
R.A. Manzoni, L. Marchese, C. Martin Perez, M.T. Meinhard, F. Nessi-Tedaldi,
J. Niedziela, F. Pauss, V. Perovic, S. Pigazzini, M.G. Ratti, M. Reichmann, C.
Reissel, T. Reitenspiess, B. Ristic, D. Ruini, D.A. Sanz Becerra, V. Stampf,
J. Steggemann63, R. Wallny, D.H. Zhu Universität Zürich, Zurich, Switzerland
C. Amsler65, P. Bärtschi, C. Botta, D. Brzhechko, M.F. Canelli, K. Cormier, A.
De Wit, R. Del Burgo, J.K. Heikkilä, M. Huwiler, W. Jin, A. Jofrehei, B.
Kilminster, S. Leontsinis, S.P. Liechti, A. Macchiolo, P. Meiring, V.M.
Mikuni, U. Molinatti, I. Neutelings, A. Reimers, P. Robmann, S. Sanchez Cruz,
K. Schweiger, Y. Takahashi National Central University, Chung-Li, Taiwan
C. Adloff66, C.M. Kuo, W. Lin, A. Roy, T. Sarkar37, S.S. Yu National Taiwan
University (NTU), Taipei, Taiwan
L. Ceard, Y. Chao, K.F. Chen, P.H. Chen, W.-S. Hou, Y.y. Li, R.-S. Lu, E.
Paganis, A. Psallidas, A. Steen, H.y. Wu, E. Yazgan, P.r. Yu Chulalongkorn
University, Faculty of Science, Department of Physics, Bangkok, Thailand
B. Asavapibhop, C. Asawatangtrakuldee, N. Srimanobhas Çukurova University,
Physics Department, Science and Art Faculty, Adana, Turkey
F. Boran, S. Damarseckin67, Z.S. Demiroglu, F. Dolek, I. Dumanoglu68, E.
Eskut, Y. Guler69, E. Gurpinar Guler69, I. Hos70, C. Isik, O. Kara, A. Kayis
Topaksu, U. Kiminsu, G. Onengut, K. Ozdemir71, A. Polatoz, A.E. Simsek, B.
Tali72, U.G. Tok, S. Turkcapar, I.S. Zorbakir, C. Zorbilmez Middle East
Technical University, Physics Department, Ankara, Turkey
B. Isildak73, G. Karapinar74, K. Ocalan75, M. Yalvac76 Bogazici University,
Istanbul, Turkey
B. Akgun, I.O. Atakisi, E. Gülmez, M. Kaya77, O. Kaya78, Ö. Özçelik, S.
Tekten79, E.A. Yetkin80 Istanbul Technical University, Istanbul, Turkey
A. Cakir, K. Cankocak68, Y. Komurcu, S. Sen81 Istanbul University, Istanbul,
Turkey
S. Cerci72, B. Kaynak, S. Ozkorucuklu, D. Sunar Cerci72 Institute for
Scintillation Materials of National Academy of Science of Ukraine, Kharkov,
Ukraine
B. Grynyov National Scientific Center, Kharkov Institute of Physics and
Technology, Kharkov, Ukraine
L. Levchuk University of Bristol, Bristol, United Kingdom
D. Anthony, E. Bhal, S. Bologna, J.J. Brooke, A. Bundock, E. Clement, D.
Cussans, H. Flacher, J. Goldstein, G.P. Heath, H.F. Heath, L. Kreczko, B.
Krikler, S. Paramesvaran, S. Seif El Nasr-Storey, V.J. Smith, N. Stylianou82,
K. Walkingshaw Pass, R. White Rutherford Appleton Laboratory, Didcot, United
Kingdom
K.W. Bell, A. Belyaev83, C. Brew, R.M. Brown, D.J.A. Cockerill, C. Cooke, K.V.
Ellis, K. Harder, S. Harper, M.l. Holmberg84, J. Linacre, K. Manolopoulos,
D.M. Newbold, E. Olaiya, D. Petyt, T. Reis, T. Schuh, C.H. Shepherd-
Themistocleous, I.R. Tomalin, T. Williams Imperial College, London, United
Kingdom
R. Bainbridge, P. Bloch, S. Bonomally, J. Borg, S. Breeze, O. Buchmuller, V.
Cepaitis, G.S. Chahal85, D. Colling, P. Dauncey, G. Davies, M. Della Negra, A.
Dow, S. Fayer, G. Fedi, G. Hall, M.H. Hassanshahi, G. Iles, J. Langford, L.
Lyons, A.-M. Magnan, S. Malik, A. Martelli, D.G. Monk, J. Nash86, M. Pesaresi,
D.M. Raymond, A. Richards, A. Rose, E. Scott, C. Seez, A. Shtipliyski, A.
Tapper, K. Uchida, T. Virdee20, M. Vojinovic, N. Wardle, S.N. Webb, D.
Winterbottom Brunel University, Uxbridge, United Kingdom
K. Coldham, J.E. Cole, A. Khan, P. Kyberd, I.D. Reid, L. Teodorescu, S. Zahid
Baylor University, Waco, USA
S. Abdullin, A. Brinkerhoff, B. Caraway, J. Dittmann, K. Hatakeyama, A.R.
Kanuganti, B. McMaster, N. Pastika, M. Saunders, S. Sawant, C. Sutantawibul,
J. Wilson Catholic University of America, Washington, DC, USA
R. Bartek, A. Dominguez, R. Uniyal, A.M. Vargas Hernandez The University of
Alabama, Tuscaloosa, USA
A. Buccilli, S.I. Cooper, D. Di Croce, S.V. Gleyzer, C. Henderson, C.U. Perez,
P. Rumerio87, C. West Boston University, Boston, USA
A. Akpinar, A. Albert, D. Arcaro, C. Cosby, Z. Demiragli, E. Fontanesi, D.
Gastler, S. May, J. Rohlf, K. Salyer, D. Sperka, D. Spitzbart, I. Suarez, A.
Tsatsos, S. Yuan, D. Zou Brown University, Providence, USA
G. Benelli, B. Burkle, X. Coubez21, D. Cutts, M. Hadley, U. Heintz, J.M.
Hogan88, G. Landsberg, K.T. Lau, M. Lukasik, J. Luo, M. Narain, S. Sagir89, E.
Usai, W.Y. Wong, X. Yan, D. Yu, W. Zhang University of California, Davis,
Davis, USA
J. Bonilla, C. Brainerd, R. Breedon, M. Calderon De La Barca Sanchez, M.
Chertok, J. Conway, P.T. Cox, R. Erbacher, G. Haza, F. Jensen, O. Kukral, R.
Lander, M. Mulhearn, D. Pellett, B. Regnery, D. Taylor, Y. Yao, F. Zhang
University of California, Los Angeles, USA
M. Bachtis, R. Cousins, A. Datta, D. Hamilton, J. Hauser, M. Ignatenko, M.A.
Iqbal, T. Lam, W.A. Nash, S. Regnard, D. Saltzberg, B. Stone, V. Valuev
University of California, Riverside, Riverside, USA
K. Burt, Y. Chen, R. Clare, J.W. Gary, M. Gordon, G. Hanson, G. Karapostoli,
O.R. Long, N. Manganelli, M. Olmedo Negrete, W. Si, S. Wimpenny, Y. Zhang
University of California, San Diego, La Jolla, USA
J.G. Branson, P. Chang, S. Cittolin, S. Cooperstein, N. Deelen, D. Diaz, J.
Duarte, R. Gerosa, L. Giannini, D. Gilbert, J. Guiang, R. Kansal, V.
Krutelyov, R. Lee, J. Letts, M. Masciovecchio, M. Pieri, B.V. Sathia
Narayanan, V. Sharma, M. Tadel, A. Vartak, F. Würthwein, Y. Xiang, A. Yagil
University of California, Santa Barbara - Department of Physics, Santa
Barbara, USA
N. Amin, C. Campagnari, M. Citron, A. Dorsett, V. Dutta, J. Incandela, M.
Kilpatrick, J. Kim, B. Marsh, H. Mei, M. Oshiro, M. Quinnan, J. Richman, U.
Sarica, F. Setti, J. Sheplock, D. Stuart, S. Wang California Institute of
Technology, Pasadena, USA
A. Bornheim, O. Cerri, I. Dutta, J.M. Lawhorn, N. Lu, J. Mao, H.B. Newman,
T.Q. Nguyen, M. Spiropulu, J.R. Vlimant, C. Wang, S. Xie, Z. Zhang, R.Y. Zhu
Carnegie Mellon University, Pittsburgh, USA
J. Alison, S. An, M.B. Andrews, P. Bryant, T. Ferguson, A. Harilal, C. Liu, T.
Mudholkar, M. Paulini, A. Sanchez, W. Terrill University of Colorado Boulder,
Boulder, USA
J.P. Cumalat, W.T. Ford, A. Hassani, E. MacDonald, R. Patel, A. Perloff, C.
Savard, K. Stenson, K.A. Ulmer, S.R. Wagner Cornell University, Ithaca, USA
J. Alexander, S. Bright-thonney, Y. Cheng, D.J. Cranshaw, S. Hogan, J. Monroy,
J.R. Patterson, D. Quach, J. Reichert, M. Reid, A. Ryd, W. Sun, J. Thom, P.
Wittich, R. Zou Fermi National Accelerator Laboratory, Batavia, USA
M. Albrow, M. Alyari, G. Apollinari, A. Apresyan, A. Apyan, S. Banerjee,
L.A.T. Bauerdick, D. Berry, J. Berryhill, P.C. Bhat, K. Burkett, J.N. Butler,
A. Canepa, G.B. Cerati, H.W.K. Cheung, F. Chlebana, M. Cremonesi, K.F. Di
Petrillo, V.D. Elvira, Y. Feng, J. Freeman, Z. Gecse, L. Gray, D. Green, S.
Grünendahl, O. Gutsche, R.M. Harris, R. Heller, T.C. Herwig, J. Hirschauer, B.
Jayatilaka, S. Jindariani, M. Johnson, U. Joshi, T. Klijnsma, B. Klima, K.H.M.
Kwok, S. Lammel, D. Lincoln, R. Lipton, T. Liu, C. Madrid, K. Maeshima, C.
Mantilla, D. Mason, P. McBride, P. Merkel, S. Mrenna, S. Nahn, J. Ngadiuba, V.
O’Dell, V. Papadimitriou, K. Pedro, C. Pena57, O. Prokofyev, F. Ravera, A.
Reinsvold Hall, L. Ristori, E. Sexton-Kennedy, N. Smith, A. Soha, W.J.
Spalding, L. Spiegel, S. Stoynev, J. Strait, L. Taylor, S. Tkaczyk, N.V. Tran,
L. Uplegger, E.W. Vaandering, H.A. Weber University of Florida, Gainesville,
USA
D. Acosta, P. Avery, D. Bourilkov, L. Cadamuro, V. Cherepanov, F. Errico, R.D.
Field, D. Guerrero, B.M. Joshi, M. Kim, E. Koenig, J. Konigsberg, A. Korytov,
K.H. Lo, K. Matchev, N. Menendez, G. Mitselmakher, A. Muthirakalayil Madhu, N.
Rawal, D. Rosenzweig, S. Rosenzweig, J. Rotter, K. Shi, J. Sturdy, J. Wang, E.
Yigitbasi, X. Zuo Florida State University, Tallahassee, USA
T. Adams, A. Askew, R. Habibullah, V. Hagopian, K.F. Johnson, R. Khurana, T.
Kolberg, G. Martinez, H. Prosper, C. Schiber, O. Viazlo, R. Yohay, J. Zhang
Florida Institute of Technology, Melbourne, USA
M.M. Baarmand, S. Butalla, T. Elkafrawy15, M. Hohlmann, R. Kumar Verma, D.
Noonan, M. Rahmani, F. Yumiceva University of Illinois at Chicago (UIC),
Chicago, USA
M.R. Adams, H. Becerril Gonzalez, R. Cavanaugh, X. Chen, S. Dittmer, O.
Evdokimov, C.E. Gerber, D.A. Hangal, D.J. Hofman, A.H. Merrit, C. Mills, G.
Oh, T. Roy, S. Rudrabhatla, M.B. Tonjes, N. Varelas, J. Viinikainen, X. Wang,
Z. Wu, Z. Ye The University of Iowa, Iowa City, USA
M. Alhusseini, K. Dilsiz90, R.P. Gandrajula, O.K. Köseyan, J.-P. Merlo, A.
Mestvirishvili91, J. Nachtman, H. Ogul92, Y. Onel, A. Penzo, C. Snyder, E.
Tiras93 Johns Hopkins University, Baltimore, USA
O. Amram, B. Blumenfeld, L. Corcodilos, J. Davis, M. Eminizer, A.V. Gritsan,
S. Kyriacou, P. Maksimovic, J. Roskes, M. Swartz, T.Á. Vámi The University of
Kansas, Lawrence, USA
A. Abreu, J. Anguiano, C. Baldenegro Barrera, P. Baringer, A. Bean, A.
Bylinkin, Z. Flowers, T. Isidori, S. Khalil, J. King, G. Krintiras, A.
Kropivnitskaya, M. Lazarovits, C. Lindsey, J. Marquez, N. Minafra, M. Murray,
M. Nickel, C. Rogan, C. Royon, R. Salvatico, S. Sanders, E. Schmitz, C. Smith,
J.D. Tapia Takaki, Q. Wang, Z. Warner, J. Williams, G. Wilson Kansas State
University, Manhattan, USA
S. Duric, A. Ivanov, K. Kaadze, D. Kim, Y. Maravin, T. Mitchell, A. Modak, K.
Nam Lawrence Livermore National Laboratory, Livermore, USA
F. Rebassoo, D. Wright University of Maryland, College Park, USA
E. Adams, A. Baden, O. Baron, A. Belloni, S.C. Eno, N.J. Hadley, S. Jabeen,
R.G. Kellogg, T. Koeth, A.C. Mignerey, S. Nabili, C. Palmer, M. Seidel, A.
Skuja, L. Wang, K. Wong Massachusetts Institute of Technology, Cambridge, USA
D. Abercrombie, G. Andreassi, R. Bi, S. Brandt, W. Busza, I.A. Cali, Y. Chen,
M. D’Alfonso, J. Eysermans, C. Freer, G. Gomez Ceballos, M. Goncharov, P.
Harris, M. Hu, M. Klute, D. Kovalskyi, J. Krupa, Y.-J. Lee, C. Mironov, C.
Paus, D. Rankin, C. Roland, G. Roland, Z. Shi, G.S.F. Stephans, J. Wang, Z.
Wang, B. Wyslouch University of Minnesota, Minneapolis, USA
R.M. Chatterjee, A. Evans, P. Hansen, J. Hiltbrand, Sh. Jain, M. Krohn, Y.
Kubota, J. Mans, M. Revering, R. Rusack, R. Saradhy, N. Schroeder, N. Strobbe,
M.A. Wadud University of Nebraska-Lincoln, Lincoln, USA
K. Bloom, M. Bryson, S. Chauhan, D.R. Claes, C. Fangmeier, L. Finco, F. Golf,
C. Joo, I. Kravchenko, M. Musich, I. Reed, J.E. Siado, G.R.
Snow${}^{\textrm{\textdagger}}$, W. Tabb, F. Yan, A.G. Zecchinelli State
University of New York at Buffalo, Buffalo, USA
G. Agarwal, H. Bandyopadhyay, L. Hay, I. Iashvili, A. Kharchilava, C. McLean,
D. Nguyen, J. Pekkanen, S. Rappoccio, A. Williams Northeastern University,
Boston, USA
G. Alverson, E. Barberis, Y. Haddad, A. Hortiangtham, J. Li, G. Madigan, B.
Marzocchi, D.M. Morse, V. Nguyen, T. Orimoto, A. Parker, L. Skinnari, A.
Tishelman-Charny, T. Wamorkar, B. Wang, A. Wisecarver, D. Wood Northwestern
University, Evanston, USA
S. Bhattacharya, J. Bueghly, Z. Chen, A. Gilbert, T. Gunter, K.A. Hahn, Y.
Liu, N. Odell, M.H. Schmitt, M. Velasco University of Notre Dame, Notre Dame,
USA
R. Band, R. Bucci, A. Das, N. Dev, R. Goldouzian, M. Hildreth, K. Hurtado
Anampa, C. Jessop, K. Lannon, J. Lawrence, N. Loukas, D. Lutton, N. Marinelli,
I. Mcalister, T. McCauley, C. Mcgrady, K. Mohrman, Y. Musienko50, R. Ruchti,
P. Siddireddy, A. Townsend, M. Wayne, A. Wightman, M. Zarucki, L. Zygala The
Ohio State University, Columbus, USA
B. Bylsma, B. Cardwell, L.S. Durkin, B. Francis, C. Hill, M. Nunez Ornelas, K.
Wei, B.L. Winer, B.R. Yates Princeton University, Princeton, USA
F.M. Addesa, B. Bonham, P. Das, G. Dezoort, P. Elmer, A. Frankenthal, B.
Greenberg, N. Haubrich, S. Higginbotham, A. Kalogeropoulos, G. Kopp, S. Kwan,
D. Lange, D. Marlow, K. Mei, I. Ojalvo, J. Olsen, D. Stickland, C. Tully
University of Puerto Rico, Mayaguez, USA
S. Malik, S. Norberg Purdue University, West Lafayette, USA
A.S. Bakshi, V.E. Barnes, R. Chawla, S. Das, L. Gutay, M. Jones, A.W. Jung, S.
Karmarkar, D. Kondratyev, M. Liu, G. Negro, N. Neumeister, G. Paspalaki, C.C.
Peng, S. Piperov, A. Purohit, J.F. Schulte, M. Stojanovic16, J. Thieman, F.
Wang, R. Xiao, W. Xie Purdue University Northwest, Hammond, USA
J. Dolen, N. Parashar Rice University, Houston, USA
A. Baty, M. Decaro, S. Dildick, K.M. Ecklund, S. Freed, P. Gardner, F.J.M.
Geurts, A. Kumar, W. Li, B.P. Padley, R. Redjimi, W. Shi, A.G. Stahl Leiton,
S. Yang, L. Zhang, Y. Zhang University of Rochester, Rochester, USA
A. Bodek, P. de Barbaro, R. Demina, J.L. Dulemba, C. Fallon, T. Ferbel, M.
Galanti, A. Garcia-Bellido, O. Hindrichs, A. Khukhunaishvili, E. Ranken, R.
Taus Rutgers, The State University of New Jersey, Piscataway, USA
B. Chiarito, J.P. Chou, A. Gandrakota, Y. Gershtein, E. Halkiadakis, A. Hart,
M. Heindl, O. Karacheban24, I. Laflotte, A. Lath, R. Montalvo, K. Nash, M.
Osherson, S. Salur, S. Schnetzer, S. Somalwar, R. Stone, S.A. Thayil, S.
Thomas, H. Wang University of Tennessee, Knoxville, USA
H. Acharya, A.G. Delannoy, S. Fiorendi, S. Spanier Texas A&M University,
College Station, USA
O. Bouhali94, M. Dalchenko, A. Delgado, R. Eusebi, J. Gilmore, T. Huang, T.
Kamon95, H. Kim, S. Luo, S. Malhotra, R. Mueller, D. Overton, D. Rathjens, A.
Safonov Texas Tech University, Lubbock, USA
N. Akchurin, J. Damgov, V. Hegde, S. Kunori, K. Lamichhane, S.W. Lee, T.
Mengke, S. Muthumuni, T. Peltola, I. Volobouev, Z. Wang, A. Whitbeck
Vanderbilt University, Nashville, USA
E. Appelt, S. Greene, A. Gurrola, W. Johns, A. Melo, H. Ni, K. Padeken, F.
Romeo, P. Sheldon, S. Tuo, J. Velkovska University of Virginia,
Charlottesville, USA
M.W. Arenton, B. Cox, G. Cummings, J. Hakala, R. Hirosky, M. Joyce, A.
Ledovskoy, A. Li, C. Neu, B. Tannenwald, S. White, E. Wolfe Wayne State
University, Detroit, USA
N. Poudyal University of Wisconsin - Madison, Madison, WI, USA
K. Black, T. Bose, C. Caillol, S. Dasu, I. De Bruyn, P. Everaerts, F. Fienga,
C. Galloni, H. He, M. Herndon, A. Hervé, U. Hussain, A. Lanaro, A. Loeliger,
R. Loveless, J. Madhusudanan Sreekala, A. Mallampalli, A. Mohammadi, D. Pinna,
A. Savin, V. Shang, V. Sharma, W.H. Smith, D. Teague, S. Trembath-Reichert, W.
Vetens †: Deceased
1: Also at TU Wien, Wien, Austria
2: Also at Institute of Basic and Applied Sciences, Faculty of Engineering,
Arab Academy for Science, Technology and Maritime Transport, Alexandria, Egypt
3: Also at Université Libre de Bruxelles, Bruxelles, Belgium
4: Also at Universidade Estadual de Campinas, Campinas, Brazil
5: Also at Federal University of Rio Grande do Sul, Porto Alegre, Brazil
6: Also at University of Chinese Academy of Sciences, Beijing, China
7: Also at Department of Physics, Tsinghua University, Beijing, China
8: Also at UFMS, Nova Andradina, Brazil
9: Also at Nanjing Normal University Department of Physics, Nanjing, China
10: Now at The University of Iowa, Iowa City, USA
11: Also at Institute for Theoretical and Experimental Physics named by A.I.
Alikhanov of NRC ‘Kurchatov Institute’, Moscow, Russia
12: Also at Joint Institute for Nuclear Research, Dubna, Russia
13: Now at Cairo University, Cairo, Egypt
14: Also at British University in Egypt, Cairo, Egypt
15: Now at Ain Shams University, Cairo, Egypt
16: Also at Purdue University, West Lafayette, USA
17: Also at Université de Haute Alsace, Mulhouse, France
18: Also at Ilia State University, Tbilisi, Georgia
19: Also at Erzincan Binali Yildirim University, Erzincan, Turkey
20: Also at CERN, European Organization for Nuclear Research, Geneva,
Switzerland
21: Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen,
Germany
22: Also at University of Hamburg, Hamburg, Germany
23: Also at Isfahan University of Technology, Isfahan, Iran, Isfahan, Iran
24: Also at Brandenburg University of Technology, Cottbus, Germany
25: Also at Forschungszentrum Jülich, Juelich, Germany
26: Also at Physics Department, Faculty of Science, Assiut University, Assiut,
Egypt
27: Also at Karoly Robert Campus, MATE Institute of Technology, Gyongyos,
Hungary
28: Also at Institute of Physics, University of Debrecen, Debrecen, Hungary
29: Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary
30: Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös
Loránd University, Budapest, Hungary
31: Also at Wigner Research Centre for Physics, Budapest, Hungary
32: Also at IIT Bhubaneswar, Bhubaneswar, India
33: Also at Institute of Physics, Bhubaneswar, India
34: Also at G.H.G. Khalsa College, Punjab, India
35: Also at Shoolini University, Solan, India
36: Also at University of Hyderabad, Hyderabad, India
37: Also at University of Visva-Bharati, Santiniketan, India
38: Also at Indian Institute of Technology (IIT), Mumbai, India
39: Also at Deutsches Elektronen-Synchrotron, Hamburg, Germany
40: Also at Sharif University of Technology, Tehran, Iran
41: Also at Department of Physics, University of Science and Technology of
Mazandaran, Behshahr, Iran
42: Now at INFN Sezione di Bari a, Università di Bari b, Politecnico di Bari
c, Bari, Italy
43: Also at Italian National Agency for New Technologies, Energy and
Sustainable Economic Development, Bologna, Italy
44: Also at Centro Siciliano di Fisica Nucleare e di Struttura Della Materia,
Catania, Italy
45: Also at Università di Napoli ’Federico II’, Napoli, Italy
46: Also at Consiglio Nazionale delle Ricerche - Istituto Officina dei
Materiali, PERUGIA, Italy
47: Also at Riga Technical University, Riga, Latvia
48: Also at Consejo Nacional de Ciencia y Tecnología, Mexico City, Mexico
49: Also at IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
50: Also at Institute for Nuclear Research, Moscow, Russia
51: Now at National Research Nuclear University ’Moscow Engineering Physics
Institute’ (MEPhI), Moscow, Russia
52: Also at Institute of Nuclear Physics of the Uzbekistan Academy of
Sciences, Tashkent, Uzbekistan
53: Also at St. Petersburg State Polytechnical University, St. Petersburg,
Russia
54: Also at University of Florida, Gainesville, USA
55: Also at Imperial College, London, United Kingdom
56: Also at P.N. Lebedev Physical Institute, Moscow, Russia
57: Also at California Institute of Technology, Pasadena, USA
58: Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia
59: Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia
60: Also at Trincomalee Campus, Eastern University, Sri Lanka, Nilaveli, Sri
Lanka
61: Also at INFN Sezione di Pavia a, Università di Pavia b, Pavia, Italy
62: Also at National and Kapodistrian University of Athens, Athens, Greece
63: Also at Ecole Polytechnique Fédérale Lausanne, Lausanne, Switzerland
64: Also at Universität Zürich, Zurich, Switzerland
65: Also at Stefan Meyer Institute for Subatomic Physics, Vienna, Austria
66: Also at Laboratoire d’Annecy-le-Vieux de Physique des Particules,
IN2P3-CNRS, Annecy-le-Vieux, France
67: Also at Şırnak University, Sirnak, Turkey
68: Also at Near East University, Research Center of Experimental Health
Science, Nicosia, Turkey
69: Also at Konya Technical University, Konya, Turkey
70: Also at Istanbul University - Cerrahpasa, Faculty of Engineering,
Istanbul, Turkey
71: Also at Piri Reis University, Istanbul, Turkey
72: Also at Adiyaman University, Adiyaman, Turkey
73: Also at Ozyegin University, Istanbul, Turkey
74: Also at Izmir Institute of Technology, Izmir, Turkey
75: Also at Necmettin Erbakan University, Konya, Turkey
76: Also at Bozok Universitetesi Rektörlügü, Yozgat, Turkey
77: Also at Marmara University, Istanbul, Turkey
78: Also at Milli Savunma University, Istanbul, Turkey
79: Also at Kafkas University, Kars, Turkey
80: Also at Istanbul Bilgi University, Istanbul, Turkey
81: Also at Hacettepe University, Ankara, Turkey
82: Also at Vrije Universiteit Brussel, Brussel, Belgium
83: Also at School of Physics and Astronomy, University of Southampton,
Southampton, United Kingdom
84: Also at Rutherford Appleton Laboratory, Didcot, United Kingdom
85: Also at IPPP Durham University, Durham, United Kingdom
86: Also at Monash University, Faculty of Science, Clayton, Australia
87: Also at Università di Torino, TORINO, Italy
88: Also at Bethel University, St. Paul, Minneapolis, USA, St. Paul, USA
89: Also at Karamanoğlu Mehmetbey University, Karaman, Turkey
90: Also at Bingol University, Bingol, Turkey
91: Also at Georgian Technical University, Tbilisi, Georgia
92: Also at Sinop University, Sinop, Turkey
93: Also at Erciyes University, KAYSERI, Turkey
94: Also at Texas A&M University at Qatar, Doha, Qatar
95: Also at Kyungpook National University, Daegu, Korea, Daegu, Korea