arXiv subjects

C. Clementi

Publications and source records attributed to C. Clementi.

15 recordsLinked to original sources

arXiv2026

Ultra-trace analysis of 40K in organic liquid scintillators

Rare-event searches require exceptionally low background levels, motivating the development of increasingly sophisticated screening methods to push sensitivity limits. Liquid scintillators are particularly attractive detector media due to their intrinsic radiopurity and the ability to scale to large target masses. In this work, we present a screening strategy capable of measuring ultra-trace concentrations of $^{40}\text{K}$ with sensitivities below $10^{-15}$g/g. The method combines neutron activation analysis with a dedicated radiochemical treatment, followed by low-background HPGe gamma spectroscopy. Using this approach, we achieved a minimum detectable concentration of $2.9\cdot10^{-16}$g/g for $^{40}\text{K}$, placing this technique among the most sensitive currently available.

physics.ins-det↗

arXiv2026

Real-Time Wiener Deconvolution for feature reconstruction in JUNO

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.

physics.ins-det↗

arXiv2025

Ultra-trace analysis of U and Th in organic liquid scintillators with high sensitivity

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.

physics.ins-det↗

arXiv2025

Simulation-based inference for Precision Neutrino Physics through Neural Monte Carlo tuning

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.

physics.data-an↗

arXiv2025

Fluorescence emission of the JUNO liquid scintillator

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

physics.ins-det↗

arXiv2024

Interpretable machine learning approach for electron antineutrino selection in a large liquid scintillator detector

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.

physics.ins-det↗

arXiv2024

Distillation and Stripping purification plants for JUNO liquid scintillator

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.

physics.ins-det↗

arXiv2024

Refractive index in the JUNO liquid scintillator

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.

physics.ins-det↗

arXiv2023

Analysis of reactor burnup simulation uncertainties for antineutrino spectrum prediction

Nuclear reactors are a source of electron antineutrinos due to the presence of unstable fission products that undergo $\beta^-$ 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.

physics.ins-det↗

arXiv2020

Embedded Readout Electronics R&D for the Large PMTs in the JUNO Experiment

Jiangmen Underground neutrino Observatory (JUNO) is a next generation liquid scintillator neutrino experiment under construction phase in South China. Thanks to the anti-neutrinos produced by the nearby nuclear power plants, JUNO will primarily study the neutrino mass hierarchy, one of the open key questions in neutrino physics. One key ingredient for the success of the measurement is to use high speed, high resolution sampling electronics located very close to the detector signal. Linearity in the response of the electronics in another important ingredient for the success of the experiment. During the initial design phase of the electronics, a custom design, with the Front-End and Read-Out electronics located very close to the detector analog signal has been developed and successfully tested. The present paper describes the electronics structure and the first tests performed on the prototypes. The electronics prototypes have been tested and they show good linearity response, with a maximum deviation of 1.3% over the full dynamic range (1-1000 p.e.), fulfilling the JUNO experiment requirements.

physics.ins-det↗

arXiv2019

$^{222}$Rn contamination mechanisms on acrylic surfaces

In this work, the $^{222}$Rn contamination mechanisms on acrylic surfaces have been investigated. $^{222}$Rn can represent a significant background source for low-background experiments, and acrylic is a suitable material for detector design thanks to its purity and transparency. Four acrylic samples have been exposed to a $^{222}$Rn rich environment for different time periods, being contaminated by $^{222}$Rn and its progenies. Subsequently, the time evolution of radiocontaminants activity on the samples has been evaluated with $α$ and $γ$ measurements, highlighting the role of different decay modes in the contamination process. A detailed analysis of the alpha spectra allowed to quantify the implantation depth of the contaminants. Moreover, a study of both $α$ and $γ$ measurements pointed out the $^{222}$Rn diffusion inside the samples.

physics.ins-det↗

arXiv2019

Distillation and stripping pilot plants for the JUNO neutrino detector: design, operations and reliability

This paper describes the design, construction principles and operations of the distillation and stripping pilot plants tested at the Daya Bay Neutrino Laboratory, with the perspective to adapt this processes, system cleanliness and leak-tightness to the final full scale plants that will be used for the purification of the liquid scintillator used in the JUNO neutrino detector. The main goal of these plants is to remove radio impurities from the liquid scintillator while increasing its optical attenuation length. Purification of liquid scintillator will be performed with a system combining alumina oxide, distillation, water extraction and steam (or N2 gas) stripping. Such a combined system will aim at obtaining a total attenuation length greater than 20 m at 430 nm, and a bulk radiopurity for 238U and 232Th in the 10-15 to 10-17 g/g range. The pilot plants commissioning and operation have also provided valuable information on the degree of reliability of their main components, which will be particularly useful for the design of the final full scale purification equipment for the JUNO liquid scintillator. This paper describe two of the five pilot plants since the Alumina Column, Fluor mixing and the Water Extraction plants are in charge of the Chinese part of the collaboration.

physics.ins-det↗

arXiv2018

Nanoseconds Timing System Based on IEEE 1588 FPGA Implementation

Clock synchronization procedures are mandatory in most physical experiments where event fragments are readout by spatially dislocated sensors and must be glued together to reconstruct key parameters (e.g. energy, interaction vertex etc.) of the process under investigation. These distributed data readout topologies rely on an accurate time information available at the frontend, where raw data are acquired and tagged with a precise timestamp prior to data buffering and central data collecting. This makes the network complexity and latency, between frontend and backend electronics, negligible within upper bounds imposed by the frontend data buffer capability. The proposed research work describes an FPGA implementation of IEEE 1588 Precision Time Protocol (PTP) that exploits the CERN Timing, Trigger and Control (TTC) system as a multicast messaging physical and data link layer. The hardware implementation extends the clock synchronization to the nanoseconds range, overcoming the typical accuracy limitations inferred by computers Ethernet based Local Area Network (LAN). Establishing a reliable communication between master and timing receiver nodes is essential in a message-based synchronization system. In the backend electronics, the serial data streams synchronization with the global clock domain is guaranteed by an hardware-based finite state machine that scans the bit period using a variable delay chain and finds the optimal sampling point. The validity of the proposed timing system has been proved in point-to-point data links as well as in star topology configurations over standard CAT-5e cables. The results achieved together with weaknesses and possible improvements are hereby detailed.

cs.NI↗

arXiv2004

The effects of non-native interactions on protein folding rates: Theory and simulation

Proteins are minimally frustrated polymers. However, for realistic protein models non-native interactions must be taken into account. In this paper we analyze the effect of non-native interactions on the folding rate and on the folding free energy barrier. We present an analytic theory to account for the modification on the free energy landscape upon introduction of non-native contacts, added as a perturbation to the strong native interactions driving folding. Our theory predicts a rate-enhancement regime at fixed temperature, under the introduction of weak, non-native interactions. We have thoroughly tested this theoretical prediction with simulations of a coarse-grained protein model, by employing an off-lattice $C_α$ model of the src-SH3 domain. The strong agreement between results from simulations and theory confirm the non trivial result that a relatively small amount of non-native interaction energy can actually assist the folding to the native structure.

q-bio.BM↗

arXiv2000

Hamiltonian dynamics and geometry of phase transitions in classical XY models

The Hamiltonian dynamics associated to classical, planar, Heisenberg XY models is investigated for two- and three-dimensional lattices. Besides the conventional signatures of phase transitions, here obtained through time averages of thermodynamical observables in place of ensemble averages, qualitatively new information is derived from the temperature dependence of Lyapunov exponents. A Riemannian geometrization of newtonian dynamics suggests to consider other observables of geometric meaning tightly related with the largest Lyapunov exponent. The numerical computation of these observables - unusual in the study of phase transitions - sheds a new light on the microscopic dynamical counterpart of thermodynamics also pointing to the existence of some major change in the geometry of the mechanical manifolds at the thermodynamical transition. Through the microcanonical definition of the entropy, a relationship between thermodynamics and the extrinsic geometry of the constant energy surfaces $Σ_E$ of phase space can be naturally established. In this framework, an approximate formula is worked out, determining a highly non-trivial relationship between temperature and topology of the $Σ_E$. Whence it can be understood that the appearance of a phase transition must be tightly related to a suitable major topology change of the $Σ_E$. This contributes to the understanding of the origin of phase transitions in the microcanonical ensemble.

cond-mat.stat-mech↗