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Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter
Authors:
M. Aamir,
G. Adamov,
T. Adams,
C. Adloff,
S. Afanasiev,
C. Agrawal,
C. Agrawal,
A. Ahmad,
H. A. Ahmed,
S. Akbar,
N. Akchurin,
B. Akgul,
B. Akgun,
R. O. Akpinar,
E. Aktas,
A. Al Kadhim,
V. Alexakhin,
J. Alimena,
J. Alison,
A. Alpana,
W. Alshehri,
P. Alvarez Dominguez,
M. Alyari,
C. Amendola,
R. B. Amir
, et al. (550 additional authors not shown)
Abstract:
A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transverse and longitudinal granularity. The active media are silicon sensors and scintillator tiles readout by SiPMs and the absorbers are a combination of lead and Cu/CuW in the electromagnetic section, and steel in the hadr…
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A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transverse and longitudinal granularity. The active media are silicon sensors and scintillator tiles readout by SiPMs and the absorbers are a combination of lead and Cu/CuW in the electromagnetic section, and steel in the hadronic section. The shower reconstruction method is based on graph neural networks and it makes use of a dynamic reduction network architecture. It is shown that the algorithm is able to capture and mitigate the main effects that normally hinder the reconstruction of hadronic showers using classical reconstruction methods, by compensating for fluctuations in the multiplicity, energy, and spatial distributions of the shower's constituents. The performance of the algorithm is evaluated using test beam data collected in 2018 prototype of the CMS HGCAL accompanied by a section of the CALICE AHCAL prototype. The capability of the method to mitigate the impact of energy leakage from the calorimeter is also demonstrated.
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Submitted 18 December, 2024; v1 submitted 17 June, 2024;
originally announced June 2024.
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Electron Energy Regression in the CMS High-Granularity Calorimeter Prototype
Authors:
Roger Rusack,
Bhargav Joshi,
Alpana Alpana,
Seema Sharma,
Thomas Vadnais
Abstract:
We present a new publicly available dataset that contains simulated data of a novel calorimeter to be installed at the CERN Large Hadron Collider. This detector will have more than six-million channels with each channel capable of position, ionisation and precision time measurement. Reconstructing these events in an efficient way poses an immense challenge which is being addressed with the latest…
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We present a new publicly available dataset that contains simulated data of a novel calorimeter to be installed at the CERN Large Hadron Collider. This detector will have more than six-million channels with each channel capable of position, ionisation and precision time measurement. Reconstructing these events in an efficient way poses an immense challenge which is being addressed with the latest machine learning techniques. As part of this development a large prototype with 12,000 channels was built and a beam of high-energy electrons incident on it. Using machine learning methods we have reconstructed the energy of incident electrons from the energies of three-dimensional hits, which is known to some precision. By releasing this data publicly we hope to encourage experts in the application of machine learning to develop efficient and accurate image reconstruction of these electrons.
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Submitted 12 September, 2023;
originally announced September 2023.
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Predicting the Future of the CMS Detector: Crystal Radiation Damage and Machine Learning at the LHC
Authors:
Bhargav Joshi,
Taihui Li,
Buyun Liang,
Roger Rusack,
Ju Sun
Abstract:
The 75,848 lead tungstate crystals in CMS experiment at the CERN Large Hadron Collider are used to measure the energy of electrons and photons produced in the proton-proton collisions. The optical transparency of the crystals degrades slowly with radiation dose due to the beam-beam collisions. The transparency of each crystal is monitored with a laser monitoring system that tracks changes in the o…
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The 75,848 lead tungstate crystals in CMS experiment at the CERN Large Hadron Collider are used to measure the energy of electrons and photons produced in the proton-proton collisions. The optical transparency of the crystals degrades slowly with radiation dose due to the beam-beam collisions. The transparency of each crystal is monitored with a laser monitoring system that tracks changes in the optical properties of the crystals due to radiation from the collision products. Predicting the optical transparency of the crystals, both in the short-term and in the long-term, is a critical task for the CMS experiment. We describe here the public data release, following FAIR principles, of the crystal monitoring data collected by the CMS Collaboration between 2016 and 2018. Besides describing the dataset and its access, the problems that can be addressed with it are described, as well as an example solution based on a Long Short-Term Memory neural network developed to predict future behavior of the crystals.
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Submitted 23 March, 2023;
originally announced March 2023.
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FAIR AI Models in High Energy Physics
Authors:
Javier Duarte,
Haoyang Li,
Avik Roy,
Ruike Zhu,
E. A. Huerta,
Daniel Diaz,
Philip Harris,
Raghav Kansal,
Daniel S. Katz,
Ishaan H. Kavoori,
Volodymyr V. Kindratenko,
Farouk Mokhtar,
Mark S. Neubauer,
Sang Eon Park,
Melissa Quinnan,
Roger Rusack,
Zhizhen Zhao
Abstract:
The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research software and other digital products is an active area of research. Machine learning (ML) models -- algorithms that have been trained on data without being explicitly…
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The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research software and other digital products is an active area of research. Machine learning (ML) models -- algorithms that have been trained on data without being explicitly programmed -- and more generally, artificial intelligence (AI) models, are an important target for this because of the ever-increasing pace with which AI is transforming scientific domains, such as experimental high energy physics (HEP). In this paper, we propose a practical definition of FAIR principles for AI models in HEP and describe a template for the application of these principles. We demonstrate the template's use with an example AI model applied to HEP, in which a graph neural network is used to identify Higgs bosons decaying to two bottom quarks. We report on the robustness of this FAIR AI model, its portability across hardware architectures and software frameworks, and its interpretability.
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Submitted 29 December, 2023; v1 submitted 9 December, 2022;
originally announced December 2022.
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Performance of the CMS High Granularity Calorimeter prototype to charged pion beams of 20$-$300 GeV/c
Authors:
B. Acar,
G. Adamov,
C. Adloff,
S. Afanasiev,
N. Akchurin,
B. Akgün,
M. Alhusseini,
J. Alison,
J. P. Figueiredo de sa Sousa de Almeida,
P. G. Dias de Almeida,
A. Alpana,
M. Alyari,
I. Andreev,
U. Aras,
P. Aspell,
I. O. Atakisi,
O. Bach,
A. Baden,
G. Bakas,
A. Bakshi,
S. Banerjee,
P. DeBarbaro,
P. Bargassa,
D. Barney,
F. Beaudette
, et al. (435 additional authors not shown)
Abstract:
The upgrade of the CMS experiment for the high luminosity operation of the LHC comprises the replacement of the current endcap calorimeter by a high granularity sampling calorimeter (HGCAL). The electromagnetic section of the HGCAL is based on silicon sensors interspersed between lead and copper (or copper tungsten) absorbers. The hadronic section uses layers of stainless steel as an absorbing med…
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The upgrade of the CMS experiment for the high luminosity operation of the LHC comprises the replacement of the current endcap calorimeter by a high granularity sampling calorimeter (HGCAL). The electromagnetic section of the HGCAL is based on silicon sensors interspersed between lead and copper (or copper tungsten) absorbers. The hadronic section uses layers of stainless steel as an absorbing medium and silicon sensors as an active medium in the regions of high radiation exposure, and scintillator tiles directly readout by silicon photomultipliers in the remaining regions. As part of the development of the detector and its readout electronic components, a section of a silicon-based HGCAL prototype detector along with a section of the CALICE AHCAL prototype was exposed to muons, electrons and charged pions in beam test experiments at the H2 beamline at the CERN SPS in October 2018. The AHCAL uses the same technology as foreseen for the HGCAL but with much finer longitudinal segmentation. The performance of the calorimeters in terms of energy response and resolution, longitudinal and transverse shower profiles is studied using negatively charged pions, and is compared to GEANT4 predictions. This is the first report summarizing results of hadronic showers measured by the HGCAL prototype using beam test data.
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Submitted 27 May, 2023; v1 submitted 9 November, 2022;
originally announced November 2022.
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A Sub-Picosecond Digital Clock Monitoring System
Authors:
Rohith Saradhy,
Erich Frahm,
Eduardo B. S. Mendes,
Roger Rusack
Abstract:
We describe a low-cost system designed to monitor wander in digital clocks with a precision of $\le$ 1 ps. With this system we have shown that it is possible to track phase variations at the sub-picosecond level by adding noise to a reference clock. As in many cases where a clock is part of a complex distribution network small changes in temperature and other effects can lead to small changes in t…
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We describe a low-cost system designed to monitor wander in digital clocks with a precision of $\le$ 1 ps. With this system we have shown that it is possible to track phase variations at the sub-picosecond level by adding noise to a reference clock. As in many cases where a clock is part of a complex distribution network small changes in temperature and other effects can lead to small changes in the a clock's phase. As a further demonstration of the system, we have used it to measure the phase changes induced in optical signals in fibers.
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Submitted 12 December, 2022; v1 submitted 11 October, 2022;
originally announced October 2022.
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A Sub-Picosecond Digitally-Controlled Phase Delay
Authors:
Diba Dehmeshki,
Erich Frahm,
Roger Rusack,
Rohith Saradhy,
Yahya Tousi
Abstract:
The use of precision timing measurements will be a major tool at the HL-LHC, where it will be used to suppress pile-up and to search for long-lived particles. To control a reference clock with sub-picosecond accuracy, we have fabricated in the TSMC 65 nm process a digitally controlled phase shifter. It is composed of a chain of 66 cells, each with a digitally controlled planar wave guide with eith…
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The use of precision timing measurements will be a major tool at the HL-LHC, where it will be used to suppress pile-up and to search for long-lived particles. To control a reference clock with sub-picosecond accuracy, we have fabricated in the TSMC 65 nm process a digitally controlled phase shifter. It is composed of a chain of 66 cells, each with a digitally controlled planar wave guide with either a short or long delay. With this a reference clock's phase can be controlled to a precision of 200 fs with dynamic range of 12 ps.
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Submitted 26 November, 2021;
originally announced November 2021.
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Response of a CMS HGCAL silicon-pad electromagnetic calorimeter prototype to 20-300 GeV positrons
Authors:
B. Acar,
G. Adamov,
C. Adloff,
S. Afanasiev,
N. Akchurin,
B. Akgün,
F. Alam Khan,
M. Alhusseini,
J. Alison,
A. Alpana,
G. Altopp,
M. Alyari,
S. An,
S. Anagul,
I. Andreev,
P. Aspell,
I. O. Atakisi,
O. Bach,
A. Baden,
G. Bakas,
A. Bakshi,
S. Bannerjee,
P. Bargassa,
D. Barney,
F. Beaudette
, et al. (364 additional authors not shown)
Abstract:
The Compact Muon Solenoid Collaboration is designing a new high-granularity endcap calorimeter, HGCAL, to be installed later this decade. As part of this development work, a prototype system was built, with an electromagnetic section consisting of 14 double-sided structures, providing 28 sampling layers. Each sampling layer has an hexagonal module, where a multipad large-area silicon sensor is glu…
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The Compact Muon Solenoid Collaboration is designing a new high-granularity endcap calorimeter, HGCAL, to be installed later this decade. As part of this development work, a prototype system was built, with an electromagnetic section consisting of 14 double-sided structures, providing 28 sampling layers. Each sampling layer has an hexagonal module, where a multipad large-area silicon sensor is glued between an electronics circuit board and a metal baseplate. The sensor pads of approximately 1 cm$^2$ are wire-bonded to the circuit board and are readout by custom integrated circuits. The prototype was extensively tested with beams at CERN's Super Proton Synchrotron in 2018. Based on the data collected with beams of positrons, with energies ranging from 20 to 300 GeV, measurements of the energy resolution and linearity, the position and angular resolutions, and the shower shapes are presented and compared to a detailed Geant4 simulation.
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Submitted 31 March, 2022; v1 submitted 12 November, 2021;
originally announced November 2021.
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Construction and commissioning of CMS CE prototype silicon modules
Authors:
B. Acar,
G. Adamov,
C. Adloff,
S. Afanasiev,
N. Akchurin,
B. Akgün,
M. Alhusseini,
J. Alison,
G. Altopp,
M. Alyari,
S. An,
S. Anagul,
I. Andreev,
M. Andrews,
P. Aspell,
I. A. Atakisi,
O. Bach,
A. Baden,
G. Bakas,
A. Bakshi,
P. Bargassa,
D. Barney,
E. Becheva,
P. Behera,
A. Belloni
, et al. (307 additional authors not shown)
Abstract:
As part of its HL-LHC upgrade program, the CMS Collaboration is developing a High Granularity Calorimeter (CE) to replace the existing endcap calorimeters. The CE is a sampling calorimeter with unprecedented transverse and longitudinal readout for both electromagnetic (CE-E) and hadronic (CE-H) compartments. The calorimeter will be built with $\sim$30,000 hexagonal silicon modules. Prototype modul…
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As part of its HL-LHC upgrade program, the CMS Collaboration is developing a High Granularity Calorimeter (CE) to replace the existing endcap calorimeters. The CE is a sampling calorimeter with unprecedented transverse and longitudinal readout for both electromagnetic (CE-E) and hadronic (CE-H) compartments. The calorimeter will be built with $\sim$30,000 hexagonal silicon modules. Prototype modules have been constructed with 6-inch hexagonal silicon sensors with cell areas of 1.1~$cm^2$, and the SKIROC2-CMS readout ASIC. Beam tests of different sampling configurations were conducted with the prototype modules at DESY and CERN in 2017 and 2018. This paper describes the construction and commissioning of the CE calorimeter prototype, the silicon modules used in the construction, their basic performance, and the methods used for their calibration.
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Submitted 10 December, 2020;
originally announced December 2020.
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The DAQ system of the 12,000 Channel CMS High Granularity Calorimeter Prototype
Authors:
B. Acar,
G. Adamov,
C. Adloff,
S. Afanasiev,
N. Akchurin,
B. Akgün,
M. Alhusseini,
J. Alison,
G. Altopp,
M. Alyari,
S. An,
S. Anagul,
I. Andreev,
M. Andrews,
P. Aspell,
I. A. Atakisi,
O. Bach,
A. Baden,
G. Bakas,
A. Bakshi,
P. Bargassa,
D. Barney,
E. Becheva,
P. Behera,
A. Belloni
, et al. (307 additional authors not shown)
Abstract:
The CMS experiment at the CERN LHC will be upgraded to accommodate the 5-fold increase in the instantaneous luminosity expected at the High-Luminosity LHC (HL-LHC). Concomitant with this increase will be an increase in the number of interactions in each bunch crossing and a significant increase in the total ionising dose and fluence. One part of this upgrade is the replacement of the current endca…
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The CMS experiment at the CERN LHC will be upgraded to accommodate the 5-fold increase in the instantaneous luminosity expected at the High-Luminosity LHC (HL-LHC). Concomitant with this increase will be an increase in the number of interactions in each bunch crossing and a significant increase in the total ionising dose and fluence. One part of this upgrade is the replacement of the current endcap calorimeters with a high granularity sampling calorimeter equipped with silicon sensors, designed to manage the high collision rates. As part of the development of this calorimeter, a series of beam tests have been conducted with different sampling configurations using prototype segmented silicon detectors. In the most recent of these tests, conducted in late 2018 at the CERN SPS, the performance of a prototype calorimeter equipped with ${\approx}12,000\rm{~channels}$ of silicon sensors was studied with beams of high-energy electrons, pions and muons. This paper describes the custom-built scalable data acquisition system that was built with readily available FPGA mezzanines and low-cost Raspberry PI computers.
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Submitted 8 December, 2020; v1 submitted 7 December, 2020;
originally announced December 2020.
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New Technologies for Discovery
Authors:
Z. Ahmed,
A. Apresyan,
M. Artuso,
P. Barry,
E. Bielejec,
F. Blaszczyk,
T. Bose,
D. Braga,
S. A. Charlebois,
A. Chatterjee,
A. Chavarria,
H. -M. Cho,
S. Dalla Torre,
M. Demarteau,
D. Denisov,
M. Diefenthaler,
A. Dragone,
F. Fahim,
C. Gee,
S. Habib,
G. Haller,
J. Hogan,
B. J. P. Jones,
M. Garcia-Sciveres,
G. Giacomini
, et al. (58 additional authors not shown)
Abstract:
For the field of high energy physics to continue to have a bright future, priority within the field must be given to investments in the development of both evolutionary and transformational detector development that is coordinated across the national laboratories and with the university community, international partners and other disciplines. While the fundamental science questions addressed by hi…
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For the field of high energy physics to continue to have a bright future, priority within the field must be given to investments in the development of both evolutionary and transformational detector development that is coordinated across the national laboratories and with the university community, international partners and other disciplines. While the fundamental science questions addressed by high energy physics have never been more compelling, there is acute awareness of the challenging budgetary and technical constraints when scaling current technologies. Furthermore, many technologies are reaching their sensitivity limit and new approaches need to be developed to overcome the currently irreducible technological challenges. This situation is unfolding against a backdrop of declining funding for instrumentation, both at the national laboratories and in particular at the universities. This trend has to be reversed for the country to continue to play a leadership role in particle physics, especially in this most promising era of imminent new discoveries that could finally break the hugely successful, but limited, Standard Model of fundamental particle interactions. In this challenging environment it is essential that the community invest anew in instrumentation and optimize the use of the available resources to develop new innovative, cost-effective instrumentation, as this is our best hope to successfully accomplish the mission of high energy physics. This report summarizes the current status of instrumentation for high energy physics, the challenges and needs of future experiments and indicates high priority research areas.
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Submitted 10 August, 2019; v1 submitted 31 July, 2019;
originally announced August 2019.
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Quantum Sensing for High Energy Physics
Authors:
Zeeshan Ahmed,
Yuri Alexeev,
Giorgio Apollinari,
Asimina Arvanitaki,
David Awschalom,
Karl K. Berggren,
Karl Van Bibber,
Przemyslaw Bienias,
Geoffrey Bodwin,
Malcolm Boshier,
Daniel Bowring,
Davide Braga,
Karen Byrum,
Gustavo Cancelo,
Gianpaolo Carosi,
Tom Cecil,
Clarence Chang,
Mattia Checchin,
Sergei Chekanov,
Aaron Chou,
Aashish Clerk,
Ian Cloet,
Michael Crisler,
Marcel Demarteau,
Ranjan Dharmapalan
, et al. (91 additional authors not shown)
Abstract:
Report of the first workshop to identify approaches and techniques in the domain of quantum sensing that can be utilized by future High Energy Physics applications to further the scientific goals of High Energy Physics.
Report of the first workshop to identify approaches and techniques in the domain of quantum sensing that can be utilized by future High Energy Physics applications to further the scientific goals of High Energy Physics.
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Submitted 29 March, 2018;
originally announced March 2018.
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First measurement of muon-neutrino disappearance in NOvA
Authors:
P. Adamson,
C. Ader,
M. Andrews,
N. Anfimov,
I. Anghel,
K. Arms,
E. Arrieta-Diaz,
A. Aurisano,
D. Ayres,
C. Backhouse,
M. Baird,
B. A. Bambah,
K. Bays,
R. Bernstein,
M. Betancourt,
V. Bhatnagar,
B. Bhuyan,
J. Bian,
K. Biery,
T. Blackburn,
V. Bocean,
D. Bogert,
A. Bolshakova,
M. Bowden,
C. Bower
, et al. (235 additional authors not shown)
Abstract:
This paper reports the first measurement using the NOvA detectors of $ν_μ$ disappearance in a $ν_μ$ beam. The analysis uses a 14 kton-equivalent exposure of $2.74 \times 10^{20}$ protons-on-target from the Fermilab NuMI beam. Assuming the normal neutrino mass hierarchy, we measure $Δm^{2}_{32}=(2.52^{+0.20}_{-0.18})\times 10^{-3}$ eV$^{2}$ and $\sin^2θ_{23}$ in the range 0.38-0.65, both at the 68%…
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This paper reports the first measurement using the NOvA detectors of $ν_μ$ disappearance in a $ν_μ$ beam. The analysis uses a 14 kton-equivalent exposure of $2.74 \times 10^{20}$ protons-on-target from the Fermilab NuMI beam. Assuming the normal neutrino mass hierarchy, we measure $Δm^{2}_{32}=(2.52^{+0.20}_{-0.18})\times 10^{-3}$ eV$^{2}$ and $\sin^2θ_{23}$ in the range 0.38-0.65, both at the 68% confidence level, with two statistically-degenerate best fit points at $\sin^2θ_{23} = $ 0.43 and 0.60. Results for the inverted mass hierarchy are also presented.
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Submitted 20 January, 2016; v1 submitted 19 January, 2016;
originally announced January 2016.
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First measurement of electron neutrino appearance in NOvA
Authors:
P. Adamson,
C. Ader,
M. Andrews,
N. Anfimov,
I. Anghel,
K. Arms,
E. Arrieta-Diaz,
A. Aurisano,
D. S. Ayres,
C. Backhouse,
M. Baird,
B. A. Bambah,
K. Bays,
R. Bernstein,
M. Betancourt,
V. Bhatnagar,
B. Bhuyan,
J. Bian,
K. Biery,
T. Blackburn,
V. Bocean,
D. Bogert,
A. Bolshakova,
M. Bowden,
C. Bower
, et al. (235 additional authors not shown)
Abstract:
We report results from the first search for $ν_μ\toν_e$ transitions by the NOvA experiment. In an exposure equivalent to $2.74\times10^{20}$ protons-on-target in the upgraded NuMI beam at Fermilab, we observe 6 events in the Far Detector, compared to a background expectation of $0.99\pm0.11$ (syst.) events based on the Near Detector measurement. A secondary analysis observes 11 events with a backg…
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We report results from the first search for $ν_μ\toν_e$ transitions by the NOvA experiment. In an exposure equivalent to $2.74\times10^{20}$ protons-on-target in the upgraded NuMI beam at Fermilab, we observe 6 events in the Far Detector, compared to a background expectation of $0.99\pm0.11$ (syst.) events based on the Near Detector measurement. A secondary analysis observes 11 events with a background of $1.07\pm0.14$ (syst.). The $3.3σ$ excess of events observed in the primary analysis disfavors $0.1π< δ_{CP} < 0.5π$ in the inverted mass hierarchy at the 90% C.L.
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Submitted 2 May, 2016; v1 submitted 19 January, 2016;
originally announced January 2016.
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Planning the Future of U.S. Particle Physics (Snowmass 2013): Chapter 8: Instrumentation Frontier
Authors:
M. Demarteau,
R. Lipton,
H. Nicholson,
I. Shipsey,
D. Akerib,
A. Albayrak-Yetkin,
J. Alexander,
J. Anderson,
M. Artuso,
D. Asner,
R. Ball,
M. Battaglia,
C. Bebek,
J. Beene,
Y. Benhammou,
E. Bentefour,
M. Bergevin,
A. Bernstein,
B. Bilki,
E. Blucher,
G. Bolla,
D. Bortoletto,
N. Bowden,
G. Brooijmans,
K. Byrum
, et al. (189 additional authors not shown)
Abstract:
These reports present the results of the 2013 Community Summer Study of the APS Division of Particles and Fields ("Snowmass 2013") on the future program of particle physics in the U.S. Chapter 8, on the Instrumentation Frontier, discusses the instrumentation needs of future experiments in the Energy, Intensity, and Cosmic Frontiers, promising new technologies for particle physics research, and iss…
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These reports present the results of the 2013 Community Summer Study of the APS Division of Particles and Fields ("Snowmass 2013") on the future program of particle physics in the U.S. Chapter 8, on the Instrumentation Frontier, discusses the instrumentation needs of future experiments in the Energy, Intensity, and Cosmic Frontiers, promising new technologies for particle physics research, and issues of gathering resources for long-term research in this area.
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Submitted 23 January, 2014;
originally announced January 2014.
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Sensor Compendium
Authors:
M. Artuso,
M. Battaglia,
G. Bolla,
D. Bortoletto,
B. Cabrera,
J. E. Carlstrom,
C. L. Chang,
W. Cooper,
C. Da Via,
M. Demarteau,
J. Fast,
H. Frisch,
M. Garcia-Sciveres,
S. Golwala,
C. Haber,
J. Hall,
E. Hoppe,
K. D. Irwin,
H. Kagan,
C. Kenney,
A. T. Lee,
D. Lynn,
J. Orrell,
M. Pyle,
R. Rusack
, et al. (7 additional authors not shown)
Abstract:
Sensors play a key role in detecting both charged particles and photons for all three frontiers in Particle Physics. The signals from an individual sensor that can be used include ionization deposited, phonons created, or light emitted from excitations of the material. The individual sensors are then typically arrayed for detection of individual particles or groups of particles. Mounting of new, e…
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Sensors play a key role in detecting both charged particles and photons for all three frontiers in Particle Physics. The signals from an individual sensor that can be used include ionization deposited, phonons created, or light emitted from excitations of the material. The individual sensors are then typically arrayed for detection of individual particles or groups of particles. Mounting of new, ever higher performance experiments, often depend on advances in sensors in a range of performance characteristics. These performance metrics can include position resolution for passing particles, time resolution on particles impacting the sensor, and overall rate capabilities. In addition the feasible detector area and cost frequently provides a limit to what can be built and therefore is often another area where improvements are important. Finally, radiation tolerance is becoming a requirement in a broad array of devices. We present a status report on a broad category of sensors, including challenges for the future and work in progress to solve those challenges
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Submitted 25 October, 2013; v1 submitted 18 October, 2013;
originally announced October 2013.
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Radiation hardness qualification of PbWO4 scintillation crystals for the CMS Electromagnetic Calorimeter
Authors:
The CMS Electromagnetic Calorimeter Group,
P. Adzic,
N. Almeida,
D. Andelin,
I. Anicin,
Z. Antunovic,
R. Arcidiacono,
M. W. Arenton,
E. Auffray,
S. Argiro,
A. Askew,
S. Baccaro,
S. Baffioni,
M. Balazs,
D. Bandurin,
D. Barney,
L. M. Barone,
A. Bartoloni,
C. Baty,
S. Beauceron,
K. W. Bell,
C. Bernet,
M. Besancon,
B. Betev,
R. Beuselinck
, et al. (245 additional authors not shown)
Abstract:
Ensuring the radiation hardness of PbWO4 crystals was one of the main priorities during the construction of the electromagnetic calorimeter of the CMS experiment at CERN. The production on an industrial scale of radiation hard crystals and their certification over a period of several years represented a difficult challenge both for CMS and for the crystal suppliers. The present article reviews t…
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Ensuring the radiation hardness of PbWO4 crystals was one of the main priorities during the construction of the electromagnetic calorimeter of the CMS experiment at CERN. The production on an industrial scale of radiation hard crystals and their certification over a period of several years represented a difficult challenge both for CMS and for the crystal suppliers. The present article reviews the related scientific and technological problems encountered.
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Submitted 21 December, 2009;
originally announced December 2009.