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Real-Time Wiener Deconvolution for feature reconstruction in JUNO
Authors:
L. Lastrucci,
M. Grassi,
A. Triossi,
J. Hu,
X. Jiang,
R. Brugnera,
A. Garfagnini,
V. Cerrone,
L. V. D'Auria,
A. Gavrikov,
R. M. Guizzetti,
A. Serafini,
G. Andronico,
V. Antonelli,
A. Barresi,
D. Basilico,
M. Beretta,
A. Bergnoli,
M. Borghesi,
A. Brigatti,
R. Bruno,
A. Budano,
B. Caccianiga,
A. Cammi,
R. Caruso
, et al. (52 additional authors not shown)
Abstract:
In particle physics, experiments generate substantial amounts of data that can be difficult to process without preliminary scaling. To avoid losing potentially crucial data, experimental collaborations are studying novel techniques for real-time data processing to extract features for further physics analysis. A common approach, especially in neutrino physics, is to use FPGAs for data acquisition…
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In particle physics, experiments generate substantial amounts of data that can be difficult to process without preliminary scaling. To avoid losing potentially crucial data, experimental collaborations are studying novel techniques for real-time data processing to extract features for further physics analysis. A common approach, especially in neutrino physics, is to use FPGAs for data acquisition and pre-processing. This paper presents an advanced Real-Time Wiener deconvolution algorithm designed to leverage the processing capabilities of the FPGA integrated into the readout boards of the Jiangmen Underground Neutrino Observatory (JUNO). The goal is to enable real-time reconstruction of the signal generated by photomultiplier tubes (PMTs) when neutrino interactions are detected. By exploiting online reconstruction of the signal generated by PMTs, we expect to improve the detection of low-energy depositions, such as those produced by transient astrophysical phenomena. These depositions are usually not saved because of the significant background that affects the low end of the energy spectrum, which would result in a large trigger rate, hence a large amount of data required for storage. This paper presents the features of the algorithm, including its ability to manage high-throughput data streams with minimal latency, adaptability, and resilience in discerning the characteristics of input data. Performance is evaluated on a JUNO electronic board. This study further demonstrates the potential of FPGA-based solutions for neutrino physics.
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Submitted 26 March, 2026;
originally announced March 2026.
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Slice hyperholomorphicity of the $S$-resolvent operators and boundary conditions
Authors:
Francesco Mantovani
Abstract:
The foundation of spectral theory on the $S$-spectrum can be traced back to the quaternionic framework of quantum mechanics. The concept of $S$-spectrum for quaternionic operators emerged as the natural spectrum in slice hyperholomorphic functional calculi, known as the $S$-functional calculus and also utilized in the quaternionic spectral theorem. This spectral theory extends to Clifford operator…
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The foundation of spectral theory on the $S$-spectrum can be traced back to the quaternionic framework of quantum mechanics. The concept of $S$-spectrum for quaternionic operators emerged as the natural spectrum in slice hyperholomorphic functional calculi, known as the $S$-functional calculus and also utilized in the quaternionic spectral theorem. This spectral theory extends to Clifford operators. A key distinction from classical complex spectral theory lies in the definition of the $S$-spectrum, which is second order in the operator $T$, and in the $S$-resolvent operators that turns out to be the product of two different operators. This study delves into the analyticity of the $S$-resolvent operators under specified boundary conditions for the $S$-spectral problem. The spectral theory on the $S$-spectrum also provides deeper insights into classical spectral theory.
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Submitted 4 February, 2026;
originally announced February 2026.
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The $ν$ EYE Neutrino Telescope: Conceptual Design Report
Authors:
Shaomin Chen,
YangHwan Ahn,
Davide Franco,
Fabio Mantovani,
Aldo Ianni,
Jiyong Choi,
S. Gwon,
K. K. Joo,
Chang Hyon Ha,
Kim Siyeon,
Jong-Chul Park,
M. Pac,
Pouya Bakhti,
Meshkat Rajaee,
Seodong Shin,
Young Ju Ko,
Bo-Young Han,
Jihoon Choi,
B. R. Ko,
HyangKyu Park,
Gihan Hong,
Jaebak Kim,
Minseo Kim,
Kyungmin Lee,
E. Won
, et al. (16 additional authors not shown)
Abstract:
The {$\bfνEYE$} (``new eye'', Neutrino Experiment at YEmilab, \href{https://sites.google.com/korea.ac.kr/the-nueye-telescope} {\tt nuEYE.korea.ac.kr}) neutrino project leverages the existing large pit at Yemilab located in South Korea, to reveal the existence of sterile neutrino, the up-turn of the neutrinos from the Sun, and the first minimum of the neutrino oscillation over distances on the orde…
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The {$\bfνEYE$} (``new eye'', Neutrino Experiment at YEmilab, \href{https://sites.google.com/korea.ac.kr/the-nueye-telescope} {\tt nuEYE.korea.ac.kr}) neutrino project leverages the existing large pit at Yemilab located in South Korea, to reveal the existence of sterile neutrino, the up-turn of the neutrinos from the Sun, and the first minimum of the neutrino oscillation over distances on the order of tens of kilometers for the first time. This initiative is expected to facilitate a wide range of significant scientific and technological advancements within both South Korean and international communities engaged in neutrino science and technology. The {$\bfνEYE$} aims to investigate the largely unexplored sector of almost-massless lepton in the elementary particle physics in detail. The emphasis will be placed on the study of real time nuclear processes and reactions involving possible sterile neutrinos on timescales down to nanoseconds in ultra-high intense or radioactive neutrino beams for the first time in the world; the {$\bfνEYE$} looks at to-be universal oscillation (``up-turn'' in the electron neutrino survival probability) of neutrinos predicted by the three neutrino oscillation paradigm. This will confirm or deny our current understanding on the particle interactions of the lepton sector; and measurement of the first oscillation minimum between the first and second neutrinos in mass.
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Submitted 18 January, 2026;
originally announced January 2026.
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Ultra-trace analysis of U and Th in organic liquid scintillators with high sensitivity
Authors:
A. Barresi,
D. Chiesa,
D. Merli,
M. Nastasi,
S. Nisi,
E. Previtali,
M. Sisti,
M. Borghesi,
A. Cammi,
C. Coletta,
G. Ferrante,
L. Loi,
G. Andronico,
V. Antonelli,
D. Basilico,
M. Beretta,
A. Bergnoli,
A. Brigatti,
R. Brugnera,
R. Bruno,
A. Budano,
B. Caccianiga,
V. Cerrone,
R. Caruso,
C. Clementi
, et al. (41 additional authors not shown)
Abstract:
Rare event searches demand extremely low background levels, necessitating ever-advancing screening techniques to enhance sensitivity. Liquid scintillators are highly attractive as detector media due to their inherent radiopurity and scalability in mass. In this work, we present a screening procedure to measure ultra-trace concentrations of natural contaminants -- $^{238}$U and $^{232}$Th -- with s…
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Rare event searches demand extremely low background levels, necessitating ever-advancing screening techniques to enhance sensitivity. Liquid scintillators are highly attractive as detector media due to their inherent radiopurity and scalability in mass. In this work, we present a screening procedure to measure ultra-trace concentrations of natural contaminants -- $^{238}$U and $^{232}$Th -- with sensitivities at the \qty{E-15}{g/g} level. Our method combines neutron activation analysis with radiochemical techniques, followed by \bg\ coincidence spectroscopy to minimize interference backgrounds. This approach achieves sensitivities of \qty{0.65E-15}{g/g} for $^{238}$U and \qty{2.3E-15}{g/g} for $^{232}$Th, among the best reported worldwide. Potential pathways for further sensitivity improvements are outlined in the conclusions.
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Submitted 6 December, 2025;
originally announced December 2025.
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First measurement of reactor neutrino oscillations at JUNO
Authors:
Angel Abusleme,
Thomas Adam,
Kai Adamowicz,
David Adey,
Shakeel Ahmad,
Rizwan Ahmed,
Timo Ahola,
Sebastiano Aiello,
Fengpeng An,
Guangpeng An,
Costas Andreopoulos,
Giuseppe Andronico,
João Pedro Athayde Marcondes de André,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Burin Asavapibhop,
Didier Auguste,
Margherita Buizza Avanzini,
Andrej Babic,
Jingzhi Bai,
Weidong Bai,
Nikita Balashov,
Roberto Barbera,
Andrea Barresi
, et al. (1114 additional authors not shown)
Abstract:
Neutrino oscillations, a quantum effect manifesting at macroscopic scales, are governed by lepton flavor mixing angles and neutrino mass-squared differences that are fundamental parameters of particle physics, representing phenomena beyond the Standard Model. Precision measurements of these parameters are essential for testing the completeness of the three-flavor framework, determining the mass or…
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Neutrino oscillations, a quantum effect manifesting at macroscopic scales, are governed by lepton flavor mixing angles and neutrino mass-squared differences that are fundamental parameters of particle physics, representing phenomena beyond the Standard Model. Precision measurements of these parameters are essential for testing the completeness of the three-flavor framework, determining the mass ordering of neutrinos, and probing possible new physics. The Jiangmen Underground Neutrino Observatory (JUNO) is a 20 kton liquid-scintillator detector located 52.5 km from multiple reactor cores, designed to resolve the interference pattern of reactor neutrinos with sub-percent precision. Here we report, using the first 59.1 days of data collected since detector completion in August 2025, the first simultaneous high-precision determination of two neutrino oscillation parameters, $\sin^2 θ_{12} = 0.3092\,\pm\,0.0087$ and $Δm^2_{21} = (7.50\,\pm\,0.12)\times10^{-5}\;{\rm eV}^2$ for the normal mass ordering scenario, improving the precision by a factor of 1.6 relative to the combination of all previous measurements. These results advance the basic understanding of neutrinos, validate the detector's design, and confirm JUNO's readiness for its primary goal of resolving the neutrino mass ordering with a larger dataset. The rapid achievement with a short exposure highlights JUNO's potential to push the frontiers of precision neutrino physics and paves the way for its broad scientific program.
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Submitted 18 November, 2025;
originally announced November 2025.
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Initial performance results of the JUNO detector
Authors:
Angel Abusleme,
Thomas Adam,
Kai Adamowicz,
David Adey,
Shakeel Ahmad,
Rizwan Ahmed,
Timo Ahola,
Sebastiano Aiello,
Fengpeng An,
Guangpeng An,
Costas Andreopoulos,
Giuseppe Andronico,
João Pedro Athayde Marcondes de André,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Burin Asavapibhop,
Didier Auguste,
Margherita Buizza Avanzini,
Andrej Babic,
Jingzhi Bai,
Weidong Bai,
Nikita Balashov,
Roberto Barbera,
Andrea Barresi
, et al. (1114 additional authors not shown)
Abstract:
The Jiangmen Underground Neutrino Observatory (JUNO) started physics data taking on 26 August 2025. JUNO consists of a 20-kton liquid scintillator central detector, surrounded by a 35 kton water pool serving as a Cherenkov veto, and almost 1000 m$^2$ of plastic scintillator veto on top. The detector is located in a shallow underground laboratory with an overburden of 1800 m.w.e. This paper present…
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The Jiangmen Underground Neutrino Observatory (JUNO) started physics data taking on 26 August 2025. JUNO consists of a 20-kton liquid scintillator central detector, surrounded by a 35 kton water pool serving as a Cherenkov veto, and almost 1000 m$^2$ of plastic scintillator veto on top. The detector is located in a shallow underground laboratory with an overburden of 1800 m.w.e. This paper presents the performance results of the detector, extensively studied during the commissioning of the water phase, the subsequent liquid scintillator filling phase, and the first physics runs. The liquid scintillator achieved an attenuation length of 20.6 m at 430 nm, while the high coverage PMT system and scintillator together yielded about 1785 photoelectrons per MeV of energy deposit at the detector centre, measured using the 2.223 MeV $γ$ from neutron captures on hydrogen with an Am-C calibration source. The reconstructed energy resolution is 3.4% for two 0.511 MeV $γ$ at the detector centre and 2.9% for the 0.93 MeV quenched Po-214 alpha decays from natural radioactive sources. The energy nonlinearity is calibrated to better than 1%. Intrinsic contaminations of U-238 and Th-232 in the liquid scintillator are below 10$^{-16}$ g/g, assuming secular equilibrium. The water Cherenkov detector achieves a muon detection efficiency better than 99.9% for muons traversing the liquid scintillator volume. During the initial science runs, the data acquisition duty cycle exceeded 97.8%, demonstrating the excellent stability and readiness of JUNO for high-precision neutrino physics.
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Submitted 18 November, 2025;
originally announced November 2025.
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Prospects for geoneutrino detection with JUNO
Authors:
Thomas Adam,
Shakeel Ahmad,
Rizwan Ahmed,
Fengpeng An,
João Pedro Athayde Marcondes de André,
Costas Andreopoulos,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Didier Auguste,
Marcel Büchner,
Weidong Bai,
Nikita Balashov,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Beretta,
Antonio Bergnoli,
Nikita Bessonov,
Daniel Bick,
Lukas Bieger,
Svetlana Biktemerova,
Thilo Birkenfeld,
Simon Blyth
, et al. (605 additional authors not shown)
Abstract:
Geoneutrinos, which are antineutrinos emitted during the decay of long-lived radioactive elements inside Earth, serve as a unique tool for studying the composition and heat budget of our planet. The Jiangmen Underground Neutrino Observatory (JUNO) experiment in China, which has recently completed construction, is expected to collect a sample comparable in size to the entire existing world geoneutr…
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Geoneutrinos, which are antineutrinos emitted during the decay of long-lived radioactive elements inside Earth, serve as a unique tool for studying the composition and heat budget of our planet. The Jiangmen Underground Neutrino Observatory (JUNO) experiment in China, which has recently completed construction, is expected to collect a sample comparable in size to the entire existing world geoneutrino dataset in less than a year. This paper presents an updated estimation of sensitivity to geoneutrinos of JUNO using the best knowledge available to date about the experimental site, the surrounding nuclear reactors, the detector response uncertainties, and the constraints expected from the TAO satellite detector. To facilitate comparison with present and future geological models, our results cover a wide range of predicted signal strengths. Despite the significant background from reactor antineutrinos, the experiment will measure the total geoneutrino flux with a precision comparable to that of existing experiments within its first few years, ultimately achieving a world-leading precision of about 8% over ten years. The large statistics of JUNO will also allow separation of the Uranium-238 and Thorium-232 contributions with unprecedented precision, providing crucial constraints on models of formation and composition of Earth. Observation of the mantle signal above the lithospheric flux will be possible but challenging. For models with the highest predicted mantle concentrations of heat-producing elements, a 3-sigma detection over six years requires knowledge of the lithospheric flux to within 15%. Together with complementary measurements from other locations, the geoneutrino results of JUNO will offer cutting-edge, high-precision insights into the interior of Earth, of fundamental importance to both the geoscience and neutrino physics communities.
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Submitted 10 November, 2025;
originally announced November 2025.
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Automatic Minds: Cognitive Parallels Between Hypnotic States and Large Language Model Processing
Authors:
Giuseppe Riva,
Brenda K. Wiederhold,
Fabrizia Mantovani
Abstract:
The cognitive processes of the hypnotized mind and the computational operations of large language models (LLMs) share deep functional parallels. Both systems generate sophisticated, contextually appropriate behavior through automatic pattern-completion mechanisms operating with limited or unreliable executive oversight. This review examines this convergence across three principles: automaticity, i…
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The cognitive processes of the hypnotized mind and the computational operations of large language models (LLMs) share deep functional parallels. Both systems generate sophisticated, contextually appropriate behavior through automatic pattern-completion mechanisms operating with limited or unreliable executive oversight. This review examines this convergence across three principles: automaticity, in which responses emerge from associative rather than deliberative processes; suppressed monitoring, leading to errors such as confabulation in hypnosis and hallucination in LLMs; and heightened contextual dependency, where immediate cues (for example, the suggestion of a therapist or the prompt of the user) override stable knowledge.
These mechanisms reveal an observer-relative meaning gap: both systems produce coherent but ungrounded outputs that require an external interpreter to supply meaning. Hypnosis and LLMs also exemplify functional agency - the capacity for complex, goal-directed, context-sensitive behavior - without subjective agency, the conscious awareness of intention and ownership that defines human action. This distinction clarifies how purposive behavior can emerge without self-reflective consciousness, governed instead by structural and contextual dynamics. Finally, both domains illuminate the phenomenon of scheming: automatic, goal-directed pattern generation that unfolds without reflective awareness. Hypnosis provides an experimental model for understanding how intention can become dissociated from conscious deliberation, offering insights into the hidden motivational dynamics of artificial systems. Recognizing these parallels suggests that the future of reliable AI lies in hybrid architectures that integrate generative fluency with mechanisms of executive monitoring, an approach inspired by the complex, self-regulating architecture of the human mind.
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Submitted 3 November, 2025;
originally announced November 2025.
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Design, waterproofing, and mass production of the 3-inch PMT frontend system of JUNO
Authors:
Jilei Xu,
Miao He,
Cédric Cerna,
Yongbo Huang,
Thomas Adam,
Shakeel Ahmad,
Rizwan Ahmed,
Fengpeng An,
Costas Andreopoulos,
Giuseppe Andronico,
João Pedro Athayde Marcondes de André,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Didier Auguste,
Weidong Bai,
Nikita Balashov,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Beretta,
Antonio Bergnoli,
Nikita Bessonov,
Daniel Bick,
Lukas Bieger
, et al. (609 additional authors not shown)
Abstract:
Over 25,600 3-inch photomultiplier tubes (PMTs) have been instrumented for the central detector of the Jiangmen Underground Neutrino Observatory. Each PMT is equipped with a high-voltage divider and a frontend cable with waterproof sealing. Groups of sixteen PMTs are connected to the underwater frontend readout electronics via specialized multi-channel waterproof connectors. This paper outlines th…
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Over 25,600 3-inch photomultiplier tubes (PMTs) have been instrumented for the central detector of the Jiangmen Underground Neutrino Observatory. Each PMT is equipped with a high-voltage divider and a frontend cable with waterproof sealing. Groups of sixteen PMTs are connected to the underwater frontend readout electronics via specialized multi-channel waterproof connectors. This paper outlines the design and mass production processes for the high-voltage divider, the cable and connector, as well as the waterproof potting of the PMT bases. The results of the acceptance tests of all the integrated PMTs are also presented.
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Submitted 22 January, 2026; v1 submitted 7 October, 2025;
originally announced October 2025.
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The S-functional calculus for the Clifford adjoint operator
Authors:
F. Colombo,
F. Mantovani,
P. Schlosser
Abstract:
In this paper, we work within the framework of modules over the Clifford algebra $\mathbb{R}_d$. Our investigation focuses on the S-spectrum and the S-functional calculus in its various forms for the adjoint T* of a Clifford operator T. One of the key results we present is that the bisectoriality of T can be transferred to T*. This is grounded in the fact that, for Clifford operators, the S-spectr…
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In this paper, we work within the framework of modules over the Clifford algebra $\mathbb{R}_d$. Our investigation focuses on the S-spectrum and the S-functional calculus in its various forms for the adjoint T* of a Clifford operator T. One of the key results we present is that the bisectoriality of T can be transferred to T*. This is grounded in the fact that, for Clifford operators, the S-spectrum of the adjoint operator T* is identical to that of T. Furthermore, we demonstrate that for the existing formulations of the S-functional calculus, including bounded, unbounded, $ω$, and $H^\infty$ versions, there is a clear connection between the left functional calculus of T and the right functional calculus of T*. This explicit link between the left functional calculus of T and the right functional calculus of T* and vice versa is obtained using the function $f^\#(s):=\overline{f(\overline{s})}$. Finally, we discuss the fact that the S-spectrum, related to the invertibility of the second-order operator T^2-2s_0T+|s|^2, can actually be characterized through the invertibility of the first-order $\mathbb{R}$-linear operator T-I^Rs.
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Submitted 18 August, 2025;
originally announced August 2025.
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Simulation-based inference for Precision Neutrino Physics through Neural Monte Carlo tuning
Authors:
A. Gavrikov,
A. Serafini,
D. Dolzhikov,
A. Garfagnini,
M. Gonchar,
M. Grassi,
R. Brugnera,
V. Cerrone,
L. V. D'Auria,
R. M. Guizzetti,
L. Lastrucci,
G. Andronico,
V. Antonelli,
A. Barresi,
D. Basilico,
M. Beretta,
A. Bergnoli,
M. Borghesi,
A. Brigatti,
R. Bruno,
A. Budano,
B. Caccianiga,
A. Cammi,
R. Caruso,
D. Chiesa
, et al. (41 additional authors not shown)
Abstract:
Precise modeling of detector energy response is crucial for next-generation neutrino experiments which present computational challenges due to lack of analytical likelihoods. We propose a solution using neural likelihood estimation within the simulation-based inference framework. We develop two complementary neural density estimators that model likelihoods of calibration data: conditional normaliz…
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Precise modeling of detector energy response is crucial for next-generation neutrino experiments which present computational challenges due to lack of analytical likelihoods. We propose a solution using neural likelihood estimation within the simulation-based inference framework. We develop two complementary neural density estimators that model likelihoods of calibration data: conditional normalizing flows and a transformer-based regressor. We adopt JUNO - a large neutrino experiment - as a case study. The energy response of JUNO depends on several parameters, all of which should be tuned, given their non-linear behavior and strong correlations in the calibration data. To this end, we integrate the modeled likelihoods with Bayesian nested sampling for parameter inference, achieving uncertainties limited only by statistics with near-zero systematic biases. The normalizing flows model enables unbinned likelihood analysis, while the transformer provides an efficient binned alternative. By providing both options, our framework offers flexibility to choose the most appropriate method for specific needs. Finally, our approach establishes a template for similar applications across experimental neutrino and broader particle physics.
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Submitted 31 July, 2025;
originally announced July 2025.
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Muon tracking in a LiquidO opaque scintillator detector
Authors:
LiquidO Collaboration,
J. Apilluelo,
L. Asquith,
E. F. Bannister,
N. P. Barradas,
C. L. Baylis,
J. L. Beney,
M. Berberan e Santos,
X. de la Bernardie,
T. J. C. Bezerra,
M. Bongrand,
C. Bourgeois,
D. Breton,
J. Busto,
A. Cabrera,
A. Cadiou,
E. Calvo,
M. de Carlos Generowicz,
E. Chauveau,
B. J. Cattermole,
M. Chen,
P. Chimenti,
D. F. Cowen,
S. Kr. Das,
S. Dusini
, et al. (67 additional authors not shown)
Abstract:
LiquidO is an innovative radiation detector concept. The core idea is to exploit stochastic light confinement in a highly scattering medium to self-segment the detector volume. In this paper, we demonstrate event-by-event muon tracking in a LiquidO opaque scintillator detector prototype. The detector consists of a 30 mm cubic scintillator volume instrumented with 64 wavelength-shifting fibres arra…
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LiquidO is an innovative radiation detector concept. The core idea is to exploit stochastic light confinement in a highly scattering medium to self-segment the detector volume. In this paper, we demonstrate event-by-event muon tracking in a LiquidO opaque scintillator detector prototype. The detector consists of a 30 mm cubic scintillator volume instrumented with 64 wavelength-shifting fibres arranged in an 8$\times$8 grid with a 3.2 mm pitch and read out by silicon photomultipliers. A wax-based opaque scintillator with a scattering length of approximately 0.5 mm is used. The tracking performance of this LiquidO detector is characterised with cosmic-ray muons and the position resolution is demonstrated to be 450 $μ$m per row of fibres. These results highlight the potential of LiquidO opaque scintillator detectors to achieve fine spatial resolution, enabling precise particle tracking and imaging.
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Submitted 14 January, 2026; v1 submitted 18 July, 2025;
originally announced July 2025.
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Quadratic estimates for the $H^\infty$-functional calculus of bisectorial Clifford operators
Authors:
Fabrizio Colombo,
Francesco Mantovani,
Peter Schlosser
Abstract:
The $H^\infty$-functional calculus is a two-step procedure, introduced by A. McIntosh, that allows the definition of functions of sectorial operators in Banach spaces. It plays a crucial role in the spectral theory of differential operators, as well as in their applications to evolution equations and various other fields of science. An extension of the $H^\infty$-functional calculus also exists in…
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The $H^\infty$-functional calculus is a two-step procedure, introduced by A. McIntosh, that allows the definition of functions of sectorial operators in Banach spaces. It plays a crucial role in the spectral theory of differential operators, as well as in their applications to evolution equations and various other fields of science. An extension of the $H^\infty$-functional calculus also exists in the hypercomplex setting, where it is based on the notion of $S$-spectrum. Originally this was done for sectorial quaternionic operators, but then also generalized all the way to bisectorial fully Clifford operators. In the latter setting and in Hilbert spaces, this paper now characterizes the boundedness of the $H^\infty$-functional calculus through certain quadratic estimates. Due to substantial differences in the definitions of the $S$-spectrum and the $S$-resolvent operators, the proofs of quadratic estimates in this setting face additional challenges compared to the classical theory of complex operators.
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Submitted 20 June, 2025;
originally announced June 2025.
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The $H^\infty$-functional calculus for right slice hyperholomorphic functions and right linear Clifford operators
Authors:
Fabrizio Colombo,
Francesco Mantovani,
Peter Schlosser
Abstract:
In 2016, the spectral theory on the $S$-spectrum was used to establish the $H^\infty$-functional calculus for quaternionic or Clifford operators. This calculus applies for example to sectorial or bisectorial right linear operators $T$ and left slice hyperholomorphic functions $f$ that can grow as polynomials. It relies on the product of the two operators $e(T)^{-1}$ and $(ef)(T)$, both defined via…
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In 2016, the spectral theory on the $S$-spectrum was used to establish the $H^\infty$-functional calculus for quaternionic or Clifford operators. This calculus applies for example to sectorial or bisectorial right linear operators $T$ and left slice hyperholomorphic functions $f$ that can grow as polynomials. It relies on the product of the two operators $e(T)^{-1}$ and $(ef)(T)$, both defined via some underlying $S$-functional calculus (also called $ω$-functional calculus). For left slice holomorphic functions $f$ this definition does not depend on the choice of the regularizer function $e$. However, due to the non-commutative multiplication of Clifford numbers, it was unclear how to extend this definition to right slice hyperholomorphic functions. This paper addresses this significant unresolved issue and shows how right linear operators can possess the $H^\infty$-functional calculus also for right slice hyperholomorphic functions.
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Submitted 5 May, 2025;
originally announced May 2025.
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Introducing MareNostrum5: A European pre-exascale energy-efficient system designed to serve a broad spectrum of scientific workloads
Authors:
Fabio Banchelli,
Marta Garcia-Gasulla,
Filippo Mantovani,
Joan Vinyals,
Josep Pocurull,
David Vicente,
Beatriz Eguzkitza,
Flavio C. C. Galeazzo,
Mario C. Acosta,
Sergi Girona
Abstract:
MareNostrum5 is a pre-exascale supercomputer at the Barcelona Supercomputing Center (BSC), part of the EuroHPC Joint Undertaking. With a peak performance of 314 petaflops, MareNostrum5 features a hybrid architecture comprising Intel Sapphire Rapids CPUs, NVIDIA Hopper GPUs, and DDR5 and high-bandwidth memory (HBM), organized into four partitions optimized for diverse workloads. This document evalu…
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MareNostrum5 is a pre-exascale supercomputer at the Barcelona Supercomputing Center (BSC), part of the EuroHPC Joint Undertaking. With a peak performance of 314 petaflops, MareNostrum5 features a hybrid architecture comprising Intel Sapphire Rapids CPUs, NVIDIA Hopper GPUs, and DDR5 and high-bandwidth memory (HBM), organized into four partitions optimized for diverse workloads. This document evaluates MareNostrum5 through micro-benchmarks (floating-point performance, memory bandwidth, interconnect throughput), HPC benchmarks (HPL and HPCG), and application studies using Alya, OpenFOAM, and IFS. It highlights MareNostrum5's scalability, efficiency, and energy performance, utilizing the EAR (Energy Aware Runtime) framework to assess power consumption and the effects of direct liquid cooling. Additionally, HBM and DDR5 configurations are compared to examine memory performance trade-offs. Designed to complement standard technical documentation, this study provides insights to guide both new and experienced users in optimizing their workloads and maximizing MareNostrum5's computational capabilities.
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Submitted 12 March, 2025;
originally announced March 2025.
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The Stochastic Light Confinement of LiquidO
Authors:
LiquidO Collaboration,
J. Apilluelo,
L. Asquith,
E. F. Bannister,
N. P. Barradas,
J. L. Beney,
M. Berberan e Santos,
X. de la Bernardie,
T. J. C. Bezerra,
M. Bongrand,
C. Bourgeois,
D. Breton,
C. Buck,
J. Busto,
K. Burns,
A. Cabrera,
A. Cadiou,
E. Calvo,
E. Chauveau,
B. J. Cattermole,
M. Chen,
P. Chimenti,
D. F. Cowen,
S. Dusini,
A. Earle
, et al. (72 additional authors not shown)
Abstract:
Light-based detectors have been widely used in fundamental research and industry since their inception in the 1930s. The energy particles deposit in these detectors is converted to optical signals via the Cherenkov and scintillation mechanisms that are then propagated through transparent media to photosensors placed typically on the detector's periphery, sometimes up to tens of metres away. Liquid…
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Light-based detectors have been widely used in fundamental research and industry since their inception in the 1930s. The energy particles deposit in these detectors is converted to optical signals via the Cherenkov and scintillation mechanisms that are then propagated through transparent media to photosensors placed typically on the detector's periphery, sometimes up to tens of metres away. LiquidO is a new technique pioneering the use of opaque media to stochastically confine light around each energy deposition while collecting it with an array of fibres that thread the medium. This approach preserves topological event information otherwise lost in the conventional approach, enabling real-time imaging down to the MeV scale. Our article demonstrates LiquidO's imaging principle with a ten-litre prototype, revealing successful light confinement of 90% of the detected light within a 5 cm radius sphere, using a custom opaque scintillator with a scattering length on the order of a few millimetres. These high-resolution imaging capabilities unlock opportunities in fundamental physics research and applications beyond. The absolute amount of light detected is also studied, including possible data-driven extrapolations to LiquidO-based detectors beyond prototyping limitations. Additionally, LiquidO's timing capabilities are explored through its ability to distinguish Cherenkov light from a slow scintillator.
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Submitted 12 March, 2025; v1 submitted 4 March, 2025;
originally announced March 2025.
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Simulation of the Background from $^{13}$C$(α, n)^{16}$O Reaction in the JUNO Scintillator
Authors:
JUNO Collaboration,
Thomas Adam,
Kai Adamowicz,
Shakeel Ahmad,
Rizwan Ahmed,
Sebastiano Aiello,
Fengpeng An,
Costas Andreopoulos,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
João Pedro Athayde Marcondes de André,
Didier Auguste,
Weidong Bai,
Nikita Balashov,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Beretta,
Antonio Bergnoli,
Nikita Bessonov,
Daniel Bick,
Lukas Bieger,
Svetlana Biktemerova
, et al. (608 additional authors not shown)
Abstract:
Large-scale organic liquid scintillator detectors are highly efficient in the detection of MeV-scale electron antineutrinos. These signal events can be detected through inverse beta decay on protons, which produce a positron accompanied by a neutron. A noteworthy background for antineutrinos coming from nuclear power reactors and from the depths of the Earth (geoneutrinos) is generated by ($α, n$)…
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Large-scale organic liquid scintillator detectors are highly efficient in the detection of MeV-scale electron antineutrinos. These signal events can be detected through inverse beta decay on protons, which produce a positron accompanied by a neutron. A noteworthy background for antineutrinos coming from nuclear power reactors and from the depths of the Earth (geoneutrinos) is generated by ($α, n$) reactions. In organic liquid scintillator detectors, $α$ particles emitted from intrinsic contaminants such as $^{238}$U, $^{232}$Th, and $^{210}$Pb/$^{210}$Po, can be captured on $^{13}$C nuclei, followed by the emission of a MeV-scale neutron. Three distinct interaction mechanisms can produce prompt energy depositions preceding the delayed neutron capture, leading to a pair of events correlated in space and time within the detector. Thus, ($α, n$) reactions represent an indistinguishable background in liquid scintillator-based antineutrino detectors, where their expected rate and energy spectrum are typically evaluated via Monte Carlo simulations. This work presents results from the open-source SaG4n software, used to calculate the expected energy depositions from the neutron and any associated de-excitation products. Also simulated is a detailed detector response to these interactions, using a dedicated Geant4-based simulation software from the JUNO experiment. An expected measurable $^{13}$C$(α, n)^{16}$O event rate and reconstructed prompt energy spectrum with associated uncertainties, are presented in the context of JUNO, however, the methods and results are applicable and relevant to other organic liquid scintillator neutrino detectors.
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Submitted 2 May, 2025; v1 submitted 2 March, 2025;
originally announced March 2025.
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COCOA: a compact Compton camera for astrophysical observation of MeV-scale gamma rays
Authors:
LiquidO Collaboration,
S. R. Soleti,
J. J. Gómez-Cadenas,
J. Apilluelo,
L. Asquith,
E. F. Bannister,
N. P. Barradas,
C. L. Baylis,
J. L. Beney,
M. Berberan e Santos,
X. de la Bernardie,
T. J. C. Bezerra,
M. Bongrand,
C. Bourgeois,
D. Breton,
J. Busto,
K. Burns,
A. Cabrera,
A. Cadiou,
E. Calvo,
M. de Carlos Generowicz,
E. Chauveau,
B. J. Cattermole,
M. Chen,
P. Chimenti
, et al. (67 additional authors not shown)
Abstract:
COCOA (COmpact COmpton cAmera) is a next-generation gamma-ray telescope designed for astrophysical observations in the MeV energy range. The detector comprises a scatterer volume employing the LiquidO detection technology and an array of scintillating crystals acting as absorber. Surrounding plastic scintillator panels serve as a veto system for charged particles. The detector's compact, scalable…
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COCOA (COmpact COmpton cAmera) is a next-generation gamma-ray telescope designed for astrophysical observations in the MeV energy range. The detector comprises a scatterer volume employing the LiquidO detection technology and an array of scintillating crystals acting as absorber. Surrounding plastic scintillator panels serve as a veto system for charged particles. The detector's compact, scalable design enables flexible deployment on microsatellites or high-altitude balloons. Gamma rays at MeV energies have not been well explored historically (the so-called "MeV gap") and COCOA has the potential to improve the sensitivity in this energy band.
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Submitted 12 May, 2025; v1 submitted 28 February, 2025;
originally announced February 2025.
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Fluorescence emission of the JUNO liquid scintillator
Authors:
M. Beretta,
F. Houria,
F. Ferraro,
D. Basilico,
A. Brigatti,
B. Caccianiga,
A. Caslini,
C. Landini,
P. Lombardi,
L. Pelicci,
E. Percalli,
G. Ranucci,
A. C. Re,
C. Clementi,
F. Ortica,
A. Romani,
V. Antonelli,
M. G. Giammarchi,
L. Miramonti,
P. Saggese,
M. D. C. Torri,
S. Aiello,
G. Andronico,
A. Barresi,
A. Bergnoli
, et al. (43 additional authors not shown)
Abstract:
JUNO is a huge neutrino detector that will use 20 kton of organic liquid scintillator as its detection medium. The scintillator is a mixture of linear alkyl benzene (LAB), 2.5 g/L of 2,5-diphenyloxazole (PPO) and 3 mg/L of 1,4-Bis(2-methylstyryl)benzene (Bis-MSB). The main goal of JUNO is to determine the Neutrino Mass Ordering [1, 2, 3]. In order to achieve this purpose, good energy and position…
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JUNO is a huge neutrino detector that will use 20 kton of organic liquid scintillator as its detection medium. The scintillator is a mixture of linear alkyl benzene (LAB), 2.5 g/L of 2,5-diphenyloxazole (PPO) and 3 mg/L of 1,4-Bis(2-methylstyryl)benzene (Bis-MSB). The main goal of JUNO is to determine the Neutrino Mass Ordering [1, 2, 3]. In order to achieve this purpose, good energy and position reconstruction is required, hence a complete understanding of the optical characteristics of the liquid scintillator is mandatory. In this paper we present the measurements on the JUNO scintillator emission spectrum, absorption length and fluorescence time distribution performed respectively with a spectrofluorimeter, a spectrophotometer and a custom made setup
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Submitted 9 March, 2025; v1 submitted 17 January, 2025;
originally announced January 2025.
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Batched DGEMMs for scientific codes running on long vector architectures
Authors:
Fabio Banchelli,
Marta Garcia-Gasulla,
Filippo Mantovani
Abstract:
In this work, we evaluate the performance of SeisSol, a simulator of seismic wave phenomena and earthquake dynamics, on a RISC-V-based system utilizing a vector processing unit. We focus on GEMM libraries and address their limited ability to leverage long vector architectures by developing a batched DGEMM library in plain C. This library achieves speedups ranging from approximately 3.5x to 32.6x c…
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In this work, we evaluate the performance of SeisSol, a simulator of seismic wave phenomena and earthquake dynamics, on a RISC-V-based system utilizing a vector processing unit. We focus on GEMM libraries and address their limited ability to leverage long vector architectures by developing a batched DGEMM library in plain C. This library achieves speedups ranging from approximately 3.5x to 32.6x compared to the reference implementation. We then integrate the batched approach into the SeisSol application, ensuring portability across different CPU architectures. Lastly, we demonstrate that our implementation is portable to an Intel CPU, resulting in improved execution times in most cases.
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Submitted 10 January, 2025;
originally announced January 2025.
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Superoscillations in the hypercomplex setting
Authors:
F. Colombo,
F. Mantovani,
S. Pinton,
P. Schlosser
Abstract:
Superoscillatory functions represent a counterintuitive phenomenon in physics but also in mathematics, where a band-limited function oscillates faster than its highest Fourier component. They appear in various contexts, including quantum mechanics, as a result of a weak measurement introduced by Y. Aharonov and collaborators. These functions can be extended to the complex variable and are a specif…
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Superoscillatory functions represent a counterintuitive phenomenon in physics but also in mathematics, where a band-limited function oscillates faster than its highest Fourier component. They appear in various contexts, including quantum mechanics, as a result of a weak measurement introduced by Y. Aharonov and collaborators. These functions can be extended to the complex variable and are a specific instance of the more general notion of supershift. The aim of this paper is to extend the notion of superoscillatory functions to the hypercomplex setting. This extension is richer than the complex case since the Fueter-Sce extension theorem for Clifford-valued functions provides two notions of hyperholomorphic functions. We will explore these notions and address the corresponding superoscillating theories.
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Submitted 22 December, 2024;
originally announced December 2024.
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Exploiting long vectors with a CFD code: a co-design show case
Authors:
Marc Blancafort,
Roger Ferrer,
Guillaume Houzeaux,
Marta Garcia-Gasulla,
Filippo Mantovani
Abstract:
A current trend in HPC systems is the utilization of architectures with SIMD or vector extensions to exploit data parallelism. There are several ways to take advantage of such modern vector architectures, each with a different impact on the code and its portability. For example, the use of intrinsics, guided vectorization via pragmas, or compiler autovectorization. Our objectives are to maximize v…
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A current trend in HPC systems is the utilization of architectures with SIMD or vector extensions to exploit data parallelism. There are several ways to take advantage of such modern vector architectures, each with a different impact on the code and its portability. For example, the use of intrinsics, guided vectorization via pragmas, or compiler autovectorization. Our objectives are to maximize vectorization efficiency and minimize code specialization. To achieve these objectives, we rely on compiler autovectorization. We leverage a set of hardware and software tools that allow us to analyze in detail where autovectorization is suboptimal. Thus, we apply an iterative methodology that allows us to incrementally improve the efficient use of the underlying hardware. In this paper, we apply this methodology to a CFD production code. We evaluate the performance on an innovative configurable platform powered by a RISC-V core coupled with a wide vector unit capable of operating with up to 256 double precision elements. Following the vectorization process, we demonstrate a single-core speedup of 7.6$\times$ compared to its scalar implementation. Furthermore, we show that code portability is not compromised, as our solution continues to exhibit performance benefits, or at the very least, no drawbacks, on other HPC architectures such as Intel x86 and NEC SX-Aurora.
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Submitted 27 October, 2024;
originally announced November 2024.
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RAVE: RISC-V Analyzer of Vector Executions, a QEMU tracing plugin
Authors:
Pablo Vizcaino,
Filippo Mantovani,
Jesus Labarta,
Roger Ferrer
Abstract:
Simulators are crucial during the development of a chip, like the RISC-V accelerator designed in the European Processor Initiative project. In this paper, we showcase the limitations of the current simulation solutions in the project and propose using QEMU with RAVE, a plugin we implement and describe in this document. This methodology can rapidly simulate and analyze applications running on the v…
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Simulators are crucial during the development of a chip, like the RISC-V accelerator designed in the European Processor Initiative project. In this paper, we showcase the limitations of the current simulation solutions in the project and propose using QEMU with RAVE, a plugin we implement and describe in this document. This methodology can rapidly simulate and analyze applications running on the v1.0 and v0.7.1 RISC-V V-extension. Our plugin reports the vector and scalar instructions alongside useful information such as the vector-length being used, the single-element-width, and the register usage, among other vectorization metrics. We provide an API used from the simulated Application to control the RAVE plugin and the capability to generate vectorization traces that can be analyzed using Paraver. Finally, we demonstrate the efficiency of our solution between different evaluated machines and against other simulation methods used in the European Processor Accelerator (EPAC) project.
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Submitted 20 September, 2024;
originally announced September 2024.
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The $H^\infty$-functional calculus for bisectorial Clifford operators
Authors:
Francesco Mantovani,
Peter Schlosser
Abstract:
The aim of this article is to introduce the H-infinity functional calculus for unbounded bisectorial operators in a Clifford module over the algebra R_n. While recent studies have focused on bounded operators or unbounded paravector operators, we now investigate unbounded fully Clifford operators and define polynomially growing functions of them. We first generate the omega-functional calculus for…
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The aim of this article is to introduce the H-infinity functional calculus for unbounded bisectorial operators in a Clifford module over the algebra R_n. While recent studies have focused on bounded operators or unbounded paravector operators, we now investigate unbounded fully Clifford operators and define polynomially growing functions of them. We first generate the omega-functional calculus for functions that exhibit an appropriate decay at zero and at infinity. We then extend to functions with a finite value at zero and at infinity. Finally, using a subsequent regularization procedure, we can define the H-infinity functional calculus for the class of regularizable functions, which in particular include functions with polynomial growth at infinity and, if T is injective, also functions with polynomial growth at zero.
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Submitted 14 February, 2025; v1 submitted 11 September, 2024;
originally announced September 2024.
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Psychomatics -- A Multidisciplinary Framework for Understanding Artificial Minds
Authors:
Giuseppe Riva,
Fabrizia Mantovani,
Brenda K. Wiederhold,
Antonella Marchetti,
Andrea Gaggioli
Abstract:
Although LLMs and other artificial intelligence systems demonstrate cognitive skills similar to humans, like concept learning and language acquisition, the way they process information fundamentally differs from biological cognition. To better understand these differences this paper introduces Psychomatics, a multidisciplinary framework bridging cognitive science, linguistics, and computer science…
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Although LLMs and other artificial intelligence systems demonstrate cognitive skills similar to humans, like concept learning and language acquisition, the way they process information fundamentally differs from biological cognition. To better understand these differences this paper introduces Psychomatics, a multidisciplinary framework bridging cognitive science, linguistics, and computer science. It aims to better understand the high-level functioning of LLMs, focusing specifically on how LLMs acquire, learn, remember, and use information to produce their outputs. To achieve this goal, Psychomatics will rely on a comparative methodology, starting from a theory-driven research question - is the process of language development and use different in humans and LLMs? - drawing parallels between LLMs and biological systems. Our analysis shows how LLMs can map and manipulate complex linguistic patterns in their training data. Moreover, LLMs can follow Grice's Cooperative Principle to provide relevant and informative responses. However, human cognition draws from multiple sources of meaning, including experiential, emotional, and imaginative facets, which transcend mere language processing and are rooted in our social and developmental trajectories. Moreover, current LLMs lack physical embodiment, reducing their ability to make sense of the intricate interplay between perception, action, and cognition that shapes human understanding and expression. Ultimately, Psychomatics holds the potential to yield transformative insights into the nature of language, cognition, and intelligence, both artificial and biological. Moreover, by drawing parallels between LLMs and human cognitive processes, Psychomatics can inform the development of more robust and human-like AI systems.
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Submitted 23 July, 2024;
originally announced July 2024.
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Interpretable machine learning approach for electron antineutrino selection in a large liquid scintillator detector
Authors:
A. Gavrikov,
V. Cerrone,
A. Serafini,
R. Brugnera,
A. Garfagnini,
M. Grassi,
B. Jelmini,
L. Lastrucci,
S. Aiello,
G. Andronico,
V. Antonelli,
A. Barresi,
D. Basilico,
M. Beretta,
A. Bergnoli,
M. Borghesi,
A. Brigatti,
R. Bruno,
A. Budano,
B. Caccianiga,
A. Cammi,
R. Caruso,
D. Chiesa,
C. Clementi,
S. Dusini
, et al. (43 additional authors not shown)
Abstract:
Several neutrino detectors, KamLAND, Daya Bay, Double Chooz, RENO, and the forthcoming large-scale JUNO, rely on liquid scintillator to detect reactor antineutrino interactions. In this context, inverse beta decay represents the golden channel for antineutrino detection, providing a pair of correlated events, thus a strong experimental signature to distinguish the signal from a variety of backgrou…
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Several neutrino detectors, KamLAND, Daya Bay, Double Chooz, RENO, and the forthcoming large-scale JUNO, rely on liquid scintillator to detect reactor antineutrino interactions. In this context, inverse beta decay represents the golden channel for antineutrino detection, providing a pair of correlated events, thus a strong experimental signature to distinguish the signal from a variety of backgrounds. However, given the low cross-section of antineutrino interactions, the development of a powerful event selection algorithm becomes imperative to achieve effective discrimination between signal and backgrounds. In this study, we introduce a machine learning (ML) model to achieve this goal: a fully connected neural network as a powerful signal-background discriminator for a large liquid scintillator detector. We demonstrate, using the JUNO detector as an example, that, despite the already high efficiency of a cut-based approach, the presented ML model can further improve the overall event selection efficiency. Moreover, it allows for the retention of signal events at the detector edges that would otherwise be rejected because of the overwhelming amount of background events in that region. We also present the first interpretable analysis of the ML approach for event selection in reactor neutrino experiments. This method provides insights into the decision-making process of the model and offers valuable information for improving and updating traditional event selection approaches.
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Submitted 25 November, 2024; v1 submitted 9 June, 2024;
originally announced June 2024.
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Distillation and Stripping purification plants for JUNO liquid scintillator
Authors:
C. Landini,
M. Beretta,
P. Lombardi,
A. Brigatti,
M. Montuschi,
S. Parmeggiano,
G. Ranucci,
V. Antonelli,
D. Basilico,
B. Caccianiga,
M. G. Giammarchi,
L. Miramonti,
E. Percalli,
A. C. Re,
P. Saggese,
M. D. C. Torri,
S. Aiello,
G. Andronico,
A. Barresi,
A. Bergnoli,
M. Borghesi,
R. Brugnera,
R. Bruno,
A. Budano,
A. Cammi
, et al. (42 additional authors not shown)
Abstract:
The optical and radiochemical purification of the scintillating liquid, which will fill the central detector of the JUNO experiment, plays a crucial role in achieving its scientific goals. Given its gigantic mass and dimensions and an unprecedented target value of about 3% @ 1 MeV in energy resolution, JUNO has set severe requirements on the parameters of its scintillator, such as attenuation leng…
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The optical and radiochemical purification of the scintillating liquid, which will fill the central detector of the JUNO experiment, plays a crucial role in achieving its scientific goals. Given its gigantic mass and dimensions and an unprecedented target value of about 3% @ 1 MeV in energy resolution, JUNO has set severe requirements on the parameters of its scintillator, such as attenuation length (Lat>20 m at 430 nm), transparency, light yield, and content of radioactive contaminants (238U,232Th<10-15 g/g). To accomplish these needs, the scintillator will be processed using several purification methods, including distillation in partial vacuum and gas stripping, which are performed in two large scale plants installed at the JUNO site. In this paper, layout, operating principles, and technical aspects which have driven the design and construction of the distil- lation and gas stripping plants are reviewed. The distillation is effective in enhancing the optical properties and removing heavy radio-impurities (238U,232Th, 40K), while the stripping process exploits pure water steam and high-purity nitrogen to extract gaseous contaminants (222Rn, 39Ar, 85Kr, O2) from the scintillator. The plant operating parameters have been tuned during the recent com- missioning phase at the JUNO site and several QA/QC measurements and tests have been performed to evaluate the performances of the plants. Some preliminary results on the efficiency of these purification processes will be shown.
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Submitted 3 June, 2024;
originally announced June 2024.
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Refractive index in the JUNO liquid scintillator
Authors:
H. S. Zhang,
M. Beretta,
S. Cialdi,
C. X. Yang,
J. H. Huang,
F. Ferraro,
G. F. Cao,
G. Reina,
Z. Y. Deng,
E. Suerra,
S. Altilia,
V. Antonelli,
D. Basilico,
A. Brigatti,
B. Caccianiga,
M. G. Giammarchi,
C. Landini,
P. Lombardi,
L. Miramonti,
E. Percalli,
G. Ranucci,
A. C. Re,
P. Saggese,
M. D. C. Torri,
S. Aiello
, et al. (51 additional authors not shown)
Abstract:
In the field of rare event physics, it is common to have huge masses of organic liquid scintillator as detection medium. In particular, they are widely used to study neutrino properties or astrophysical neutrinos. Thanks to its safety properties (such as low toxicity and high flash point) and easy scalability, linear alkyl benzene is the most common solvent used to produce liquid scintillators for…
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In the field of rare event physics, it is common to have huge masses of organic liquid scintillator as detection medium. In particular, they are widely used to study neutrino properties or astrophysical neutrinos. Thanks to its safety properties (such as low toxicity and high flash point) and easy scalability, linear alkyl benzene is the most common solvent used to produce liquid scintillators for large mass experiments. The knowledge of the refractive index is a pivotal point to understand the detector response, as this quantity (and its wavelength dependence) affects the Cherenkov radiation and photon propagation in the medium. In this paper, we report the measurement of the refractive index of the JUNO liquid scintillator between 260-1064 nm performed with two different methods (an ellipsometer and a refractometer), with a sub percent level precision. In addition, we used an interferometer to measure the group velocity in the JUNO liquid scintillator and verify the expected value derived from the refractive index measurements.
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Submitted 30 May, 2024;
originally announced May 2024.
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Potential to identify neutrino mass ordering with reactor antineutrinos at JUNO
Authors:
JUNO Collaboration,
Angel Abusleme,
Thomas Adam,
Shakeel Ahmad,
Rizwan Ahmed,
Sebastiano Aiello,
Muhammad Akram,
Abid Aleem,
Fengpeng An,
Qi An,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Burin Asavapibhop,
João Pedro Athayde Marcondes de André,
Didier Auguste,
Weidong Bai,
Nikita Balashov,
Wander Baldini,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Bellato,
Marco Beretta
, et al. (605 additional authors not shown)
Abstract:
The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose neutrino experiment under construction in South China. This paper presents an updated estimate of JUNO's sensitivity to neutrino mass ordering using the reactor antineutrinos emitted from eight nuclear reactor cores in the Taishan and Yangjiang nuclear power plants. This measurement is planned by studying the fine interference…
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The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose neutrino experiment under construction in South China. This paper presents an updated estimate of JUNO's sensitivity to neutrino mass ordering using the reactor antineutrinos emitted from eight nuclear reactor cores in the Taishan and Yangjiang nuclear power plants. This measurement is planned by studying the fine interference pattern caused by quasi-vacuum oscillations in the oscillated antineutrino spectrum at a baseline of 52.5~km and is completely independent of the CP violating phase and neutrino mixing angle $θ_{23}$. The sensitivity is obtained through a joint analysis of JUNO and Taishan Antineutrino Observatory (TAO) detectors utilizing the best available knowledge to date about the location and overburden of the JUNO experimental site, local and global nuclear reactors, JUNO and TAO detector responses, expected event rates and spectra of signals and backgrounds, and systematic uncertainties of analysis inputs. We find that a 3$σ$ median sensitivity to reject the wrong mass ordering hypothesis can be reached with an exposure to approximately 6.5 years $\times$ 26.6 GW thermal power.
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Submitted 11 February, 2025; v1 submitted 28 May, 2024;
originally announced May 2024.
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Prediction of Energy Resolution in the JUNO Experiment
Authors:
JUNO Collaboration,
Angel Abusleme,
Thomas Adam,
Kai Adamowicz,
Shakeel Ahmad,
Rizwan Ahmed,
Sebastiano Aiello,
Fengpeng An,
Qi An,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
João Pedro Athayde Marcondes de André,
Didier Auguste,
Weidong Bai,
Nikita Balashov,
Wander Baldini,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Bellato,
Marco Beretta,
Antonio Bergnoli,
Daniel Bick
, et al. (629 additional authors not shown)
Abstract:
This paper presents an energy resolution study of the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3\% at 1~MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components o…
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This paper presents an energy resolution study of the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3\% at 1~MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components of the JUNO detector. Various factors affecting the detection of inverse beta decay signals have an impact on the energy resolution, extending beyond the statistical fluctuations of the detected number of photons, such as the properties of the liquid scintillator, performance of photomultiplier tubes, and the energy reconstruction algorithm. To account for these effects, a full JUNO simulation and reconstruction approach is employed. This enables the modeling of all relevant effects and the evaluation of associated inputs to accurately estimate the energy resolution. The results of study reveal an energy resolution of 2.95\% at 1~MeV. Furthermore, this study assesses the contribution of major effects to the overall energy resolution budget. This analysis serves as a reference for interpreting future measurements of energy resolution during JUNO data collection. Moreover, it provides a guideline for comprehending the energy resolution characteristics of liquid scintillator-based detectors.
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Submitted 9 January, 2025; v1 submitted 28 May, 2024;
originally announced May 2024.
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JUNO Sensitivity to Invisible Decay Modes of Neutrons
Authors:
JUNO Collaboration,
Angel Abusleme,
Thomas Adam,
Kai Adamowicz,
Shakeel Ahmad,
Rizwan Ahmed,
Sebastiano Aiello,
Fengpeng An,
Qi An,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
João Pedro Athayde Marcondes de André,
Didier Auguste,
Weidong Bai,
Nikita Balashov,
Wander Baldini,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Bellato,
Marco Beretta,
Antonio Bergnoli,
Daniel Bick
, et al. (635 additional authors not shown)
Abstract:
We explore the decay of bound neutrons into invisible particles (e.g., $n\rightarrow 3 ν$ or $nn \rightarrow 2 ν$) in the JUNO liquid scintillator detector, which do not produce an observable signal. The invisible decay includes two decay modes: $ n \rightarrow { inv} $ and $ nn \rightarrow { inv} $. The invisible decays of $s$-shell neutrons in $^{12}{\rm C}$ will leave a highly excited residual…
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We explore the decay of bound neutrons into invisible particles (e.g., $n\rightarrow 3 ν$ or $nn \rightarrow 2 ν$) in the JUNO liquid scintillator detector, which do not produce an observable signal. The invisible decay includes two decay modes: $ n \rightarrow { inv} $ and $ nn \rightarrow { inv} $. The invisible decays of $s$-shell neutrons in $^{12}{\rm C}$ will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino $\barν_e$, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are $τ/B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, {\rm yr}$ and $τ/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}$.
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Submitted 26 February, 2025; v1 submitted 27 May, 2024;
originally announced May 2024.
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Spectral properties of the gradient operator with nonconstant coefficients
Authors:
Fabrizio Colombo,
Francesco Mantovani,
Peter Schlosser
Abstract:
In mathematical physics, the gradient operator with nonconstant coefficients encompasses various models, including Fourier's law for heat propagation and Fick's first law, that relates the diffusive flux to the gradient of the concentration. Specifically, consider $n\geq 3$ orthogonal unit vectors $e_1,\dots,e_n\in\mathbb{R}^n$, and let $Ω\subseteq\mathbb{R}^n$ be some (in general unbounded) Lipsc…
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In mathematical physics, the gradient operator with nonconstant coefficients encompasses various models, including Fourier's law for heat propagation and Fick's first law, that relates the diffusive flux to the gradient of the concentration. Specifically, consider $n\geq 3$ orthogonal unit vectors $e_1,\dots,e_n\in\mathbb{R}^n$, and let $Ω\subseteq\mathbb{R}^n$ be some (in general unbounded) Lipschitz domain. This paper investigates the spectral properties of the gradient operator $T=\sum_{i=1}^ne_ia_i(x)\frac{\partial}{\partial x_i}$ with nonconstant positive coefficients $a_i:\overlineΩ\to(0,\infty)$. Under certain regularity and growth conditions on the $a_i$, we identify bisectorial or strip-type regions that belong to the $S$-resolvent set of $T$. Moreover, we obtain suitable estimates of the associated resolvent operator. Our focus lies in the spectral theory on the $S$-spectrum, designed to study the operators acting in Clifford modules $V$ over the Clifford algebra $\mathbb{R}_n$, with vector operators being a specific crucial subclass. The spectral properties related to the $S$-spectrum of $T$ are linked to the inversion of the operator $Q_s(T):=T^2-2s_0T+|s|^2$, where $s\in\mathbb{R}^{n+1}$ is a paravector, i.e., it is of the form $s=s_0+s_1e_1+\dots+s_ne_n$. This spectral problem is substantially different from the complex one, since it allows to associate general boundary conditions to $Q_s(T)$, i.e., to the squared operator $T^2$.
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Submitted 21 August, 2024; v1 submitted 27 April, 2024;
originally announced April 2024.
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Analysis of reactor burnup simulation uncertainties for antineutrino spectrum prediction
Authors:
A. Barresi,
M. Borghesi,
A. Cammi,
D. Chiesa,
L. Loi,
M. Nastasi,
E. Previtali,
M. Sisti,
S. Aiello,
G. Andronico,
V. Antonelli,
D. Basilico,
M. Beretta,
A. Bergnoli,
A. Brigatti,
R. Brugnera,
R. Bruno,
A. Budano,
B. Caccianiga,
V. Cerrone,
R. Caruso,
C. Clementi,
S. Dusini,
A. Fabbri,
G. Felici
, et al. (42 additional authors not shown)
Abstract:
Nuclear reactors are a source of electron antineutrinos due to the presence of unstable fission products that undergo $β^-$ decay. They will be exploited by the JUNO experiment to determine the neutrino mass ordering and to get very precise measurements of the neutrino oscillation parameters. This requires the reactor antineutrino spectrum to be characterized as precisely as possible both through…
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Nuclear reactors are a source of electron antineutrinos due to the presence of unstable fission products that undergo $β^-$ decay. They will be exploited by the JUNO experiment to determine the neutrino mass ordering and to get very precise measurements of the neutrino oscillation parameters. This requires the reactor antineutrino spectrum to be characterized as precisely as possible both through high resolution measurements, as foreseen by the TAO experiment, and detailed simulation models. In this paper we present a benchmark analysis utilizing Serpent Monte Carlo simulations in comparison with real pressurized water reactor spent fuel data. Our objective is to study the accuracy of fission fraction predictions as a function of different reactor simulation approximations. Then, utilizing the BetaShape software, we construct fissile antineutrino spectra using the summation method, thereby assessing the influence of simulation uncertainties on reactor antineutrino spectrum.
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Submitted 30 October, 2024; v1 submitted 21 November, 2023;
originally announced November 2023.
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Compressed Real Numbers for AI: a case-study using a RISC-V CPU
Authors:
Federico Rossi,
Marco Cococcioni,
Roger Ferrer Ibàñez,
Jesùs Labarta,
Filippo Mantovani,
Marc Casas,
Emanuele Ruffaldi,
Sergio Saponara
Abstract:
As recently demonstrated, Deep Neural Networks (DNN), usually trained using single precision IEEE 754 floating point numbers (binary32), can also work using lower precision. Therefore, 16-bit and 8-bit compressed format have attracted considerable attention. In this paper, we focused on two families of formats that have already achieved interesting results in compressing binary32 numbers in machin…
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As recently demonstrated, Deep Neural Networks (DNN), usually trained using single precision IEEE 754 floating point numbers (binary32), can also work using lower precision. Therefore, 16-bit and 8-bit compressed format have attracted considerable attention. In this paper, we focused on two families of formats that have already achieved interesting results in compressing binary32 numbers in machine learning applications, without sensible degradation of the accuracy: bfloat and posit. Even if 16-bit and 8-bit bfloat/posit are routinely used for reducing the storage of the weights/biases of trained DNNs, the inference still often happens on the 32-bit FPU of the CPU (especially if GPUs are not available). In this paper we propose a way to decompress a tensor of bfloat/posits just before computations, i.e., after the compressed operands have been loaded within the vector registers of a vector capable CPU, in order to save bandwidth usage and increase cache efficiency. Finally, we show the architectural parameters and considerations under which this solution is advantageous with respect to the uncompressed one.
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Submitted 11 September, 2023;
originally announced September 2023.
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Real-time Monitoring for the Next Core-Collapse Supernova in JUNO
Authors:
Angel Abusleme,
Thomas Adam,
Shakeel Ahmad,
Rizwan Ahmed,
Sebastiano Aiello,
Muhammad Akram,
Abid Aleem,
Fengpeng An,
Qi An,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Burin Asavapibhop,
João Pedro Athayde Marcondes de André,
Didier Auguste,
Weidong Bai,
Nikita Balashov,
Wander Baldini,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Bellato,
Marco Beretta,
Antonio Bergnoli
, et al. (606 additional authors not shown)
Abstract:
The core-collapse supernova (CCSN) is considered one of the most energetic astrophysical events in the universe. The early and prompt detection of neutrinos before (pre-SN) and during the supernova (SN) burst presents a unique opportunity for multi-messenger observations of CCSN events. In this study, we describe the monitoring concept and present the sensitivity of the system to pre-SN and SN neu…
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The core-collapse supernova (CCSN) is considered one of the most energetic astrophysical events in the universe. The early and prompt detection of neutrinos before (pre-SN) and during the supernova (SN) burst presents a unique opportunity for multi-messenger observations of CCSN events. In this study, we describe the monitoring concept and present the sensitivity of the system to pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton liquid scintillator detector currently under construction in South China. The real-time monitoring system is designed to ensure both prompt alert speed and comprehensive coverage of progenitor stars. It incorporates prompt monitors on the electronic board as well as online monitors at the data acquisition stage. Assuming a false alert rate of 1 per year, this monitoring system exhibits sensitivity to pre-SN neutrinos up to a distance of approximately 1.6 (0.9) kiloparsecs and SN neutrinos up to about 370 (360) kiloparsecs for a progenitor mass of 30 solar masses, considering both normal and inverted mass ordering scenarios. The pointing ability of the CCSN is evaluated by analyzing the accumulated event anisotropy of inverse beta decay interactions from pre-SN or SN neutrinos. This, along with the early alert, can play a crucial role in facilitating follow-up multi-messenger observations of the next galactic or nearby extragalactic CCSN.
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Submitted 4 December, 2023; v1 submitted 13 September, 2023;
originally announced September 2023.
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Short reasons for long vectors in HPC CPUs: a study based on RISC-V
Authors:
Pablo Vizcaino,
Georgios Ieronymakis,
Nikolaos Dimou,
Vassilis Papaefstathiou,
Jesus Labarta,
Filippo Mantovani
Abstract:
For years, SIMD/vector units have enhanced the capabilities of modern CPUs in High-Performance Computing (HPC) and mobile technology. Typical commercially-available SIMD units process up to 8 double-precision elements with one instruction. The optimal vector width and its impact on CPU throughput due to memory latency and bandwidth remain challenging research areas. This study examines the behavio…
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For years, SIMD/vector units have enhanced the capabilities of modern CPUs in High-Performance Computing (HPC) and mobile technology. Typical commercially-available SIMD units process up to 8 double-precision elements with one instruction. The optimal vector width and its impact on CPU throughput due to memory latency and bandwidth remain challenging research areas. This study examines the behavior of four computational kernels on a RISC-V core connected to a customizable vector unit, capable of operating up to 256 double precision elements per instruction. The four codes have been purposefully selected to represent non-dense workloads: SpMV, BFS, PageRank, FFT. The experimental setup allows us to measure their performance while varying the vector length, the memory latency, and bandwidth. Our results not only show that larger vector lengths allow for better tolerance of limitations in the memory subsystem but also offer hope to code developers beyond dense linear algebra.
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Submitted 11 November, 2023; v1 submitted 13 September, 2023;
originally announced September 2023.
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Probing Earth's Missing Potassium using the Unique Antimatter Signature of Geoneutrinos
Authors:
LiquidO Consortium,
:,
A. Cabrera,
M. Chen,
F. Mantovani,
A. Serafini,
V. Strati,
J. Apilluelo,
L. Asquith,
J. L. Beney,
T. J. C. Bezerra,
M. Bongrand,
C. Bourgeois,
D. Breton,
M. Briere,
J. Busto,
A. Cadiou,
E. Calvo,
V. Chaumat,
E. Chauveau,
B. J. Cattermole,
P. Chimenti,
C. Delafosse,
H. de Kerret,
S. Dusini
, et al. (55 additional authors not shown)
Abstract:
The formation of the Earth remains an epoch with mysterious puzzles extending to our still incomplete understanding of the planet's potential origin and bulk composition. Direct confirmation of the Earth's internal heat engine was accomplished by the successful observation of geoneutrinos originating from uranium (U) and thorium (Th) progenies, manifestations of the planet's natural radioactivity…
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The formation of the Earth remains an epoch with mysterious puzzles extending to our still incomplete understanding of the planet's potential origin and bulk composition. Direct confirmation of the Earth's internal heat engine was accomplished by the successful observation of geoneutrinos originating from uranium (U) and thorium (Th) progenies, manifestations of the planet's natural radioactivity dominated by potassium (40K) and the decay chains of uranium (238U) and thorium (232Th). This radiogenic energy output is critical to planetary dynamics and must be accurately measured for a complete understanding of the overall heat budget and thermal history of the Earth. Detecting geoneutrinos remains the only direct probe to do so and constitutes a challenging objective in modern neutrino physics. In particular, the intriguing potassium geoneutrinos have never been observed and thus far have been considered impractical to measure. We propose here a novel approach for potassium geoneutrino detection using the unique antimatter signature of antineutrinos to reduce the otherwise overwhelming backgrounds to observing this rarest signal. The proposed detection framework relies on the innovative LiquidO detection technique to enable positron (e+) identification and antineutrino interactions with ideal isotope targets identified here for the first time. We also provide the complete experimental methodology to yield the first potassium geoneutrino discovery.
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Submitted 23 August, 2023; v1 submitted 8 August, 2023;
originally announced August 2023.
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JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo
Authors:
JUNO Collaboration,
Angel Abusleme,
Thomas Adam,
Shakeel Ahmad,
Rizwan Ahmed,
Sebastiano Aiello,
Muhammad Akram,
Abid Aleem,
Tsagkarakis Alexandros,
Fengpeng An,
Qi An,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Burin Asavapibhop,
João Pedro Athayde Marcondes de André,
Didier Auguste,
Weidong Bai,
Nikita Balashov,
Wander Baldini,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Bellato
, et al. (581 additional authors not shown)
Abstract:
We discuss JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo via detecting inverse beta decay reactions of electron anti-neutrinos resulting from the annihilation. We study possible backgrounds to the signature, including the reactor neutrinos, diffuse supernova neutrino background, charged- and neutral-current interactions of atmospheric neutrinos, backgrounds from muon…
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We discuss JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo via detecting inverse beta decay reactions of electron anti-neutrinos resulting from the annihilation. We study possible backgrounds to the signature, including the reactor neutrinos, diffuse supernova neutrino background, charged- and neutral-current interactions of atmospheric neutrinos, backgrounds from muon-induced fast neutrons and cosmogenic isotopes. A fiducial volume cut, as well as the pulse shape discrimination and the muon veto are applied to suppress the above backgrounds. It is shown that JUNO sensitivity to the thermally averaged dark matter annihilation rate in 10 years of exposure would be significantly better than the present-day best limit set by Super-Kamiokande and would be comparable to that expected by Hyper-Kamiokande.
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Submitted 13 September, 2023; v1 submitted 15 June, 2023;
originally announced June 2023.
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Software Development Vehicles to enable extended and early co-design: a RISC-V and HPC case of study
Authors:
Filippo Mantovani,
Pablo Vizcaino,
Fabio Banchelli,
Marta Garcia-Gasulla,
Roger Ferrer,
Giorgos Ieronymakis,
Nikos Dimou,
Vassilis Papaefstathiou,
Jesus Labarta
Abstract:
Prototyping HPC systems with low-to-mid technology readiness level (TRL) systems is critical for providing feedback to hardware designers, the system software team (e.g., compiler developers), and early adopters from the scientific community. The typical approach to hardware design and HPC system prototyping often limits feedback or only allows it at a late stage. In this paper, we present a set o…
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Prototyping HPC systems with low-to-mid technology readiness level (TRL) systems is critical for providing feedback to hardware designers, the system software team (e.g., compiler developers), and early adopters from the scientific community. The typical approach to hardware design and HPC system prototyping often limits feedback or only allows it at a late stage. In this paper, we present a set of tools for co-designing HPC systems, called software development vehicles (SDV). We use an innovative RISC-V design as a demonstrator, which includes a scalar CPU and a vector processing unit capable of operating large vectors up to 16 kbits. We provide an incremental methodology and early tangible evidence of the co-design process that provide feedback to improve both architecture and system software at a very early stage of system development.
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Submitted 1 June, 2023;
originally announced June 2023.
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The JUNO experiment Top Tracker
Authors:
JUNO Collaboration,
Angel Abusleme,
Thomas Adam,
Shakeel Ahmad,
Rizwan Ahmed,
Sebastiano Aiello,
Muhammad Akram,
Abid Aleem,
Tsagkarakis Alexandros,
Fengpeng An,
Qi An,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Burin Asavapibhop,
João Pedro Athayde Marcondes de André,
Didier Auguste,
Weidong Bai,
Nikita Balashov,
Wander Baldini,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Bellato
, et al. (592 additional authors not shown)
Abstract:
The main task of the Top Tracker detector of the neutrino reactor experiment Jiangmen Underground Neutrino Observatory (JUNO) is to reconstruct and extrapolate atmospheric muon tracks down to the central detector. This muon tracker will help to evaluate the contribution of the cosmogenic background to the signal. The Top Tracker is located above JUNO's water Cherenkov Detector and Central Detector…
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The main task of the Top Tracker detector of the neutrino reactor experiment Jiangmen Underground Neutrino Observatory (JUNO) is to reconstruct and extrapolate atmospheric muon tracks down to the central detector. This muon tracker will help to evaluate the contribution of the cosmogenic background to the signal. The Top Tracker is located above JUNO's water Cherenkov Detector and Central Detector, covering about 60% of the surface above them. The JUNO Top Tracker is constituted by the decommissioned OPERA experiment Target Tracker modules. The technology used consists in walls of two planes of plastic scintillator strips, one per transverse direction. Wavelength shifting fibres collect the light signal emitted by the scintillator strips and guide it to both ends where it is read by multianode photomultiplier tubes. Compared to the OPERA Target Tracker, the JUNO Top Tracker uses new electronics able to cope with the high rate produced by the high rock radioactivity compared to the one in Gran Sasso underground laboratory. This paper will present the new electronics and mechanical structure developed for the Top Tracker of JUNO along with its expected performance based on the current detector simulation.
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Submitted 9 March, 2023;
originally announced March 2023.
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JUNO sensitivity to $^7$Be, $pep$, and CNO solar neutrinos
Authors:
Angel Abusleme,
Thomas Adam,
Shakeel Ahmad,
Rizwan Ahmed,
Sebastiano Aiello,
Muhammad Akram,
Abid Aleem,
Tsagkarakis Alexandros,
Fengpeng An,
Qi An,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Burin Asavapibhop,
João Pedro Athayde Marcondes de André,
Didier Auguste,
Weidong Bai,
Nikita Balashov,
Wander Baldini,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Bellato,
Marco Beretta
, et al. (592 additional authors not shown)
Abstract:
The Jiangmen Underground Neutrino Observatory (JUNO), the first multi-kton liquid scintillator detector, which is under construction in China, will have a unique potential to perform a real-time measurement of solar neutrinos well below the few MeV threshold typical for Water Cherenkov detectors. JUNO's large target mass and excellent energy resolution are prerequisites for reaching unprecedented…
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The Jiangmen Underground Neutrino Observatory (JUNO), the first multi-kton liquid scintillator detector, which is under construction in China, will have a unique potential to perform a real-time measurement of solar neutrinos well below the few MeV threshold typical for Water Cherenkov detectors. JUNO's large target mass and excellent energy resolution are prerequisites for reaching unprecedented levels of precision. In this paper, we provide estimation of the JUNO sensitivity to 7Be, pep, and CNO solar neutrinos that can be obtained via a spectral analysis above the 0.45 MeV threshold. This study is performed assuming different scenarios of the liquid scintillator radiopurity, ranging from the most opti mistic one corresponding to the radiopurity levels obtained by the Borexino experiment, up to the minimum requirements needed to perform the neutrino mass ordering determination with reactor antineutrinos - the main goal of JUNO. Our study shows that in most scenarios, JUNO will be able to improve the current best measurements on 7Be, pep, and CNO solar neutrino fluxes. We also perform a study on the JUNO capability to detect periodical time variations in the solar neutrino flux, such as the day-night modulation induced by neutrino flavor regeneration in Earth, and the modulations induced by temperature changes driven by helioseismic waves.
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Submitted 7 March, 2023;
originally announced March 2023.
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Implementation and performances of the IPbus protocol for the JUNO Large-PMT readout electronics
Authors:
Riccardo Triozzi,
Andrea Serafini,
Marco Bellato,
Antonio Bergnoli,
Matteo Bolognesi,
Riccardo Brugnera,
Vanessa Cerrone,
Chao Chen,
Barbara Clerbaux,
Alberto Coppi,
Daniele Corti,
Flavio dal Corso,
Jianmeng Dong,
Wei Dou,
Lei Fan,
Alberto Garfagnini,
Arsenii Gavrikov,
Guanghua Gong,
Marco Grassi,
Rosa Maria Guizzetti,
Shuang Hang,
Cong He,
Jun Hu,
Roberto Isocrate,
Beatrice Jelmini
, et al. (107 additional authors not shown)
Abstract:
The Jiangmen Underground Neutrino Observatory (JUNO) is a large neutrino detector currently under construction in China. Thanks to the tight requirements on its optical and radio-purity properties, it will be able to perform leading measurements detecting terrestrial and astrophysical neutrinos in a wide energy range from tens of keV to hundreds of MeV. A key requirement for the success of the exp…
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The Jiangmen Underground Neutrino Observatory (JUNO) is a large neutrino detector currently under construction in China. Thanks to the tight requirements on its optical and radio-purity properties, it will be able to perform leading measurements detecting terrestrial and astrophysical neutrinos in a wide energy range from tens of keV to hundreds of MeV. A key requirement for the success of the experiment is an unprecedented 3% energy resolution, guaranteed by its large active mass (20 kton) and the use of more than 20,000 20-inch photo-multiplier tubes (PMTs) acquired by high-speed, high-resolution sampling electronics located very close to the PMTs. As the Front-End and Read-Out electronics is expected to continuously run underwater for 30 years, a reliable readout acquisition system capable of handling the timestamped data stream coming from the Large-PMTs and permitting to simultaneously monitor and operate remotely the inaccessible electronics had to be developed. In this contribution, the firmware and hardware implementation of the IPbus based readout protocol will be presented, together with the performances measured on final modules during the mass production of the electronics.
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Submitted 20 February, 2023;
originally announced February 2023.
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Mass testing of the JUNO experiment 20-inch PMTs readout electronics
Authors:
Alberto Coppi,
Beatrice Jelmini,
Marco Bellato,
Antonio Bergnoli,
Matteo Bolognesi,
Riccardo Brugnera,
Vanessa Cerrone,
Chao Chen,
Barbara Clerbaux,
Daniele Corti,
Flavio dal Corso,
Jianmeng Dong,
Wei Dou,
Lei Fan,
Alberto Garfagnini,
Arsenii Gavrikov,
Guanghua Gong,
Marco Grassi,
Rosa Maria Guizzetti,
Shuang Hang,
Cong He,
Jun Hu,
Roberto Isocrate,
Xiaolu Ji,
Xiaoshan Jiang
, et al. (107 additional authors not shown)
Abstract:
The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose, large size, liquid scintillator experiment under construction in China. JUNO will perform leading measurements detecting neutrinos from different sources (reactor, terrestrial and astrophysical neutrinos) covering a wide energy range (from 200 keV to several GeV). This paper focuses on the design and development of a test pro…
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The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose, large size, liquid scintillator experiment under construction in China. JUNO will perform leading measurements detecting neutrinos from different sources (reactor, terrestrial and astrophysical neutrinos) covering a wide energy range (from 200 keV to several GeV). This paper focuses on the design and development of a test protocol for the 20-inch PMT underwater readout electronics, performed in parallel to the mass production line. In a time period of about ten months, a total number of 6950 electronic boards were tested with an acceptance yield of 99.1%.
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Submitted 11 January, 2023;
originally announced January 2023.
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JUNO Sensitivity on Proton Decay $p\to \barνK^+$ Searches
Authors:
JUNO Collaboration,
Angel Abusleme,
Thomas Adam,
Shakeel Ahmad,
Rizwan Ahmed,
Sebastiano Aiello,
Muhammad Akram,
Fengpeng An,
Qi An,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Burin Asavapibhop,
João Pedro Athayde Marcondes de André,
Didier Auguste,
Nikita Balashov,
Wander Baldini,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Bellato,
Antonio Bergnoli,
Thilo Birkenfeld,
Sylvie Blin
, et al. (586 additional authors not shown)
Abstract:
The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \barνK^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreov…
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The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \barνK^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \barνK^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel.
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Submitted 26 October, 2023; v1 submitted 16 December, 2022;
originally announced December 2022.
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Validation and integration tests of the JUNO 20-inch PMTs readout electronics
Authors:
Vanessa Cerrone,
Katharina von Sturm,
Marco Bellato,
Antonio Bergnoli,
Matteo Bolognesi,
Riccardo Brugnera,
Chao Chen,
Barbara Clerbaux,
Alberto Coppi,
Flavio dal Corso,
Daniele Corti,
Jianmeng Dong,
Wei Dou,
Lei Fan,
Alberto Garfagnini,
Guanghua Gong,
Marco Grassi,
Shuang Hang,
Rosa Maria Guizzetti,
Cong He,
Jun Hu,
Roberto Isocrate,
Beatrice Jelmini,
Xiaolu Ji,
Xiaoshan Jiang
, et al. (105 additional authors not shown)
Abstract:
The Jiangmen Underground Neutrino Observatory (JUNO) is a large neutrino detector currently under construction in China. JUNO will be able to study the neutrino mass ordering and to perform leading measurements detecting terrestrial and astrophysical neutrinos in a wide energy range, spanning from 200 keV to several GeV. Given the ambitious physics goals of JUNO, the electronic system has to meet…
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The Jiangmen Underground Neutrino Observatory (JUNO) is a large neutrino detector currently under construction in China. JUNO will be able to study the neutrino mass ordering and to perform leading measurements detecting terrestrial and astrophysical neutrinos in a wide energy range, spanning from 200 keV to several GeV. Given the ambitious physics goals of JUNO, the electronic system has to meet specific tight requirements, and a thorough characterization is required. The present paper describes the tests performed on the readout modules to measure their performances.
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Submitted 16 December, 2022;
originally announced December 2022.
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A portable coding strategy to exploit vectorization on combustion simulations
Authors:
Fabio Banchelli,
Guillermo Oyarzun,
Marta Garcia-Gasulla,
Filippo Mantovani,
Ambrus Both,
Guillaume Houzeaux,
Daniel Mira
Abstract:
The complexity of combustion simulations demands the latest high-performance computing tools to accelerate its time-to-solution results. A current trend on HPC systems is the utilization of CPUs with SIMD or vector extensions to exploit data parallelism. Our work proposes a strategy to improve the automatic vectorization of finite element-based scientific codes. The approach applies a parametric c…
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The complexity of combustion simulations demands the latest high-performance computing tools to accelerate its time-to-solution results. A current trend on HPC systems is the utilization of CPUs with SIMD or vector extensions to exploit data parallelism. Our work proposes a strategy to improve the automatic vectorization of finite element-based scientific codes. The approach applies a parametric configuration to the data structures to help the compiler detect the block of codes that can take advantage of vector computation while maintaining the code portable. A detailed analysis of the computational impact of this methodology on the different stages of a CFD solver is studied on the PRECCINSTA burner simulation. Our parametric implementation has proven to help the compiler generate more vector instructions in the assembly operation: this results in a reduction of up to 9.3 times of the total executed instruction maintaining constant the Instructions Per Cycle and the CPU frequency. The proposed strategy improves the performance of the CFD case under study up to 4.67 times on the MareNostrum 4 supercomputer.
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Submitted 21 October, 2022;
originally announced October 2022.
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Model Independent Approach of the JUNO $^8$B Solar Neutrino Program
Authors:
JUNO Collaboration,
Jie Zhao,
Baobiao Yue,
Haoqi Lu,
Yufeng Li,
Jiajie Ling,
Zeyuan Yu,
Angel Abusleme,
Thomas Adam,
Shakeel Ahmad,
Rizwan Ahmed,
Sebastiano Aiello,
Muhammad Akram,
Abid Aleem,
Tsagkarakis Alexandros,
Fengpeng An,
Qi An,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Burin Asavapibhop,
João Pedro Athayde Marcondes de André,
Didier Auguste,
Weidong Bai
, et al. (579 additional authors not shown)
Abstract:
The physics potential of detecting $^8$B solar neutrinos will be exploited at the Jiangmen Underground Neutrino Observatory (JUNO), in a model independent manner by using three distinct channels of the charged-current (CC), neutral-current (NC) and elastic scattering (ES) interactions. Due to the largest-ever mass of $^{13}$C nuclei in the liquid-scintillator detectors and the {expected} low backg…
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The physics potential of detecting $^8$B solar neutrinos will be exploited at the Jiangmen Underground Neutrino Observatory (JUNO), in a model independent manner by using three distinct channels of the charged-current (CC), neutral-current (NC) and elastic scattering (ES) interactions. Due to the largest-ever mass of $^{13}$C nuclei in the liquid-scintillator detectors and the {expected} low background level, $^8$B solar neutrinos would be observable in the CC and NC interactions on $^{13}$C for the first time. By virtue of optimized event selections and muon veto strategies, backgrounds from the accidental coincidence, muon-induced isotopes, and external backgrounds can be greatly suppressed. Excellent signal-to-background ratios can be achieved in the CC, NC and ES channels to guarantee the $^8$B solar neutrino observation. From the sensitivity studies performed in this work, we show that JUNO, with ten years of data, can reach the {1$σ$} precision levels of 5%, 8% and 20% for the $^8$B neutrino flux, $\sin^2θ_{12}$, and $Δm^2_{21}$, respectively. It would be unique and helpful to probe the details of both solar physics and neutrino physics. In addition, when combined with SNO, the world-best precision of 3% is expected for the $^8$B neutrino flux measurement.
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Submitted 6 March, 2024; v1 submitted 15 October, 2022;
originally announced October 2022.
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Airborne Radiometric Surveys and Machine Learning Algorithms for Revealing Soil Texture
Authors:
Andrea Maino,
Matteo Alberi,
Emiliano Anceschi,
Enrico Chiarelli,
Luca Cicala,
Tommaso Colonna,
Mario De Cesare,
Enrico Guastaldi,
Nicola Lopane,
Fabio Mantovani,
Maurizio Marcialis,
Nicola Martini,
Michele Montuschi,
Silvia Piccioli,
Kassandra Giulia Cristina Raptis,
Antonio Russo,
Filippo Semenza,
Virginia Strati
Abstract:
Soil texture is key information in agriculture for improving soil knowledge and crop performance, so the accurate mapping of this crucial feature is imperative for rationally planning cultivations and for targeting interventions. We studied the relationship between radioelements and soil texture in the Mezzano Lowland (Italy), a 189 $km^2$ agricultural plain investigated through a ded-icated airbo…
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Soil texture is key information in agriculture for improving soil knowledge and crop performance, so the accurate mapping of this crucial feature is imperative for rationally planning cultivations and for targeting interventions. We studied the relationship between radioelements and soil texture in the Mezzano Lowland (Italy), a 189 $km^2$ agricultural plain investigated through a ded-icated airborne gamma-ray spectroscopy survey. The K and Th abundances were used to retrieve the clay and sand content by means of a multi-approach method. Linear (simple and multiple) and non-linear (machine learning algorithms with deep neural networks) predictive models were trained and tested adopting a 1:50,000 scale soil texture map. The comparison of these approaches highlighted that the non-linear model introduces significant improvements in the prediction of soil texture fractions. The predicted maps of the clay and of the sand content were compared with the regional soil maps. Although the macro-structures were equally present, the airborne gam-ma-ray data permits us shedding light on finer features. Map areas with higher clay content were coincident with paleo-channels crossing the Mezzano Lowland in Etruscan and Roman periods, confirmed by the hydrographic setting of historical maps and by the geo-morphological features of the study area.
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Submitted 13 August, 2022;
originally announced August 2022.
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Prospects for Detecting the Diffuse Supernova Neutrino Background with JUNO
Authors:
JUNO Collaboration,
Angel Abusleme,
Thomas Adam,
Shakeel Ahmad,
Rizwan Ahmed,
Sebastiano Aiello,
Muhammad Akram,
Fengpeng An,
Qi An,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Burin Asavapibhop,
João Pedro Athayde Marcondes de André,
Didier Auguste,
Nikita Balashov,
Wander Baldini,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Bellato,
Antonio Bergnoli,
Thilo Birkenfeld,
Sylvie Blin
, et al. (577 additional authors not shown)
Abstract:
We present the detection potential for the diffuse supernova neutrino background (DSNB) at the Jiangmen Underground Neutrino Observatory (JUNO), using the inverse-beta-decay (IBD) detection channel on free protons. We employ the latest information on the DSNB flux predictions, and investigate in detail the background and its reduction for the DSNB search at JUNO. The atmospheric neutrino induced n…
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We present the detection potential for the diffuse supernova neutrino background (DSNB) at the Jiangmen Underground Neutrino Observatory (JUNO), using the inverse-beta-decay (IBD) detection channel on free protons. We employ the latest information on the DSNB flux predictions, and investigate in detail the background and its reduction for the DSNB search at JUNO. The atmospheric neutrino induced neutral current (NC) background turns out to be the most critical background, whose uncertainty is carefully evaluated from both the spread of model predictions and an envisaged \textit{in situ} measurement. We also make a careful study on the background suppression with the pulse shape discrimination (PSD) and triple coincidence (TC) cuts. With latest DSNB signal predictions, more realistic background evaluation and PSD efficiency optimization, and additional TC cut, JUNO can reach the significance of 3$σ$ for 3 years of data taking, and achieve better than 5$σ$ after 10 years for a reference DSNB model. In the pessimistic scenario of non-observation, JUNO would strongly improve the limits and exclude a significant region of the model parameter space.
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Submitted 13 October, 2022; v1 submitted 18 May, 2022;
originally announced May 2022.
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Mass Testing and Characterization of 20-inch PMTs for JUNO
Authors:
Angel Abusleme,
Thomas Adam,
Shakeel Ahmad,
Rizwan Ahmed,
Sebastiano Aiello,
Muhammad Akram,
Abid Aleem,
Tsagkarakis Alexandros,
Fengpeng An,
Qi An,
Giuseppe Andronico,
Nikolay Anfimov,
Vito Antonelli,
Tatiana Antoshkina,
Burin Asavapibhop,
Joao Pedro Athayde Marcondes de Andre,
Didier Auguste,
Weidong Bai,
Nikita Balashov,
Wander Baldini,
Andrea Barresi,
Davide Basilico,
Eric Baussan,
Marco Bellato,
Antonio Bergnoli
, et al. (541 additional authors not shown)
Abstract:
Main goal of the JUNO experiment is to determine the neutrino mass ordering using a 20kt liquid-scintillator detector. Its key feature is an excellent energy resolution of at least 3 % at 1 MeV, for which its instruments need to meet a certain quality and thus have to be fully characterized. More than 20,000 20-inch PMTs have been received and assessed by JUNO after a detailed testing program whic…
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Main goal of the JUNO experiment is to determine the neutrino mass ordering using a 20kt liquid-scintillator detector. Its key feature is an excellent energy resolution of at least 3 % at 1 MeV, for which its instruments need to meet a certain quality and thus have to be fully characterized. More than 20,000 20-inch PMTs have been received and assessed by JUNO after a detailed testing program which began in 2017 and elapsed for about four years. Based on this mass characterization and a set of specific requirements, a good quality of all accepted PMTs could be ascertained. This paper presents the performed testing procedure with the designed testing systems as well as the statistical characteristics of all 20-inch PMTs intended to be used in the JUNO experiment, covering more than fifteen performance parameters including the photocathode uniformity. This constitutes the largest sample of 20-inch PMTs ever produced and studied in detail to date, i.e. 15,000 of the newly developed 20-inch MCP-PMTs from Northern Night Vision Technology Co. (NNVT) and 5,000 of dynode PMTs from Hamamatsu Photonics K. K.(HPK).
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Submitted 17 September, 2022; v1 submitted 17 May, 2022;
originally announced May 2022.