Coincidence Events Research Articles

Pushing the limit of BGO-based dual-ended Cherenkov PET detectors through photon transit time correction

Objective. The high production cost of commonly used lutetium-based fast scintillators and the development of silicon photomultipliers technology have made bismuth germanate (BGO) a promising candidate for time-of-flight positron emission tomography (TOF PET) detectors owing to its generation of prompt Cherenkov photons. However, using BGO as a hybrid scintillator is disadvantageous owing to its low photon statistics and distribution that does not conform well to a single Gaussian. To mitigate this, a proposal was made to increase the likelihood of detecting the first Cherenkov photons by positioning two photosensors in opposition at the entrance and exit faces of the scintillator and subsequently selectively picking an earlier timestamp. Nonetheless, the timing variation arising from the photon transit time remains affected by the entire length of the crystal, thereby presenting a possibility for further enhancement. Approach. In this study, we aimed to improve the timing performance of the dual-ended BGO Cherenkov TOF PET detector by capitalizing on the synergistic advantages of applying depth-of-interaction (DOI) information and crystal surface finishes or reflector properties. A dual-ended BGO detector was implemented using a 3 × 3 × 15 mm3 BGO crystal. Coincidence events were acquired against a 3 × 3 × 3 mm3 LYSO:Ce:Mg reference detector. The timing performance of the dual-ended BGO detectors was analyzed using conventionally proposed timestamp methods before and after DOI correction. Results. Through a DOI-based correction of photon transit time spread, we demonstrated a further improvement in the timing resolution of the BGO-based Cherenkov TOF PET detector utilizing a dual-ended detector configuration and adaptive arrival time pickoff. We achieved further improvements in timing resolution by correcting the offset spread induced by the fluctuation of timing signal rise time in the dual-ended detector. Significance. Although polishing the crystal surface was still favorable in terms of full-width-half-maximum value, incorporating DOI information from the unpolished crystal to compensate for photon travel time facilitated additional enhancement in the overall timing performance, thereby surpassing that achieved with the polished crystal.

Exotic collective excitation patterns in triaxially deformed <sup>131</sup>Ba

<sec>In the last two decades, several unique phenomena in triaxially deformed nuclei, such as chiral doublet bands and wobbling motion have been revealed. Up to now, there are still many open questions which require further experimental and theoretical studies. To explore the collective motion in <sup>131</sup>Ba, an experiment was performed using the XTU Tandem accelerator in the Legnaro laboratory, Italy. High-spin states of <sup>131</sup>Ba have been populated via the heavy-ion fusion-evaporation <sup>122</sup>Sn(<sup>13</sup>C, 4n) reaction. <i>γ</i>-rays, charged particles and neutrons emitted from the residues were detected by the GALILEO array, EUCLIDES silicon ball, and the Neutron Wall, respectively. A total of 1.2<inline-formula><tex-math id="M12">\begin{document}$ \times $\end{document}</tex-math><alternatives><graphic specific-use="online" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="11-20240212_M12.jpg"/><graphic specific-use="print" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="11-20240212_M12.png"/></alternatives></inline-formula>10<sup>9</sup> triple- or higher-fold events were collected by the GALILEO data acquisition system. The <i>γ</i>-<i>γ</i>-<i>γ</i> coincidence events were sorted into a three-dimensional histogram (cube) and the analysis was carried out with the RADWARE and GASPWARE software packages.</sec><sec>Through analysis of the coincidences between <i>γ</i>-rays, the most comprehensive level schemes of <sup>131</sup>Ba to date was deduced from the present work. The extended level-scheme consists of 15 rotational bands, and newly observed transitions are marked in red. Three nearly degenerate pairs of doublet bands (Band 3–8) are identified in <sup>131</sup>Ba. Two pairs of chiral doublets (Band 3–6) with configuration <inline-formula><tex-math id="M20">\begin{document}$ {\textit{\pi}}h_{11/2}(g_{7/2},d_{5/2}){\otimes}{\nu}h_{11/2} $\end{document}</tex-math><alternatives><graphic specific-use="online" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="11-20240212_M20.jpg"/><graphic specific-use="print" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="11-20240212_M20.png"/></alternatives></inline-formula> are interpreted as a set of pseudospin-chiral quartet bands. The quartet bands are fed by another pair of chiral doublet bands (Band 7–8) built on a <inline-formula><tex-math id="M21">\begin{document}$ {\textit{\pi}}h^2_{11/2}{\otimes}{\nu}h_{11/2} $\end{document}</tex-math><alternatives><graphic specific-use="online" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="11-20240212_M21.jpg"/><graphic specific-use="print" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="11-20240212_M21.png"/></alternatives></inline-formula> configuration via a series of enhanced E1 transitions. We extracted the energy displacement <i>δ</i>E and the B(E1)/B(E2) branching ratios between the positive-parity band 3 and the negative-parity band 7 in <sup>131</sup>Ba and in comparison with those in <sup>124</sup>Ba, <sup>224</sup>Th, <sup>133</sup>Ce and <sup>135</sup>Nd. The energy displacement <i>δ</i>E and the B(E1)/B(E2) branching ratios in <sup>131</sup>Ba are comparable with those in <sup>124</sup>Ba but deviate appreciably from those in <sup>224</sup>Th which has been reported to have stable octupole deformation. The results indicate the existence of octupole correlations in <sup>131</sup>Ba without stable octupole deformation. A new rotational band (Band 10) discovered in the low-spin region exhibits a level structure similar to a wobbling band. Assuming it as a wobbling band, the wobbling frequency was extracted and compared with other reported wobbling bands in the neighboring nuclei. The wobbling frequency of this band decreases with increasing angular momentum, and even exhibits negative value at the highest spin. Considering that the wobbling phonon should contribute a positive amount to the excitation energy, this band is unlikely to be explained by this mechanism. The band may originate from other collective excitation mechanisms such as <i>γ</i> vibration. The newly identified rotational band (Band 9) composed of M1 transitions is tentatively assigned as a magnetic rotational band through a systematic analysis of the level structure. Finally, the configurations of other 4 bands, Band 12-15, are also suggested based on previous researches and the extracted quasiparticle alignments.</sec>

Improving the predictability of compound dry and hot extremes through complexity science

Compound dry and hot extremes (CDHE) will have an adverse impact on socioeconomic factors during the Indian summer monsoon, and a future exacerbation is anticipated. The occurrence of CDHE is influenced by teleconnections, which play a crucial role in determining its likelihood on a seasonal scale. Despite the importance, there is a lack of studies unraveling the teleconnections of CDHE in India. Previous investigations specifically focused on the teleconnections between precipitation or temperature and climate indices. Hence, there is a need to unravel the teleconnections of CDHE. In this study, we present a framework that combines event coincidence analysis (ECA) with complexity science. ECA evaluates the synchronization between CDHE and climate indices. Subsequently, complexity science is utilized to construct a driver-CDHE network to identify the key drivers of CDHE. To evaluate the effectiveness of the proposed drivers, a logistic regression model is employed. The occurrence of CDHE exhibits distinct patterns from July to September when considering intra-seasonal variability. Our findings contribute to the identification of drivers associated with CDHE. The primary driver for Eastern, Western India and Central India is the indices in the Pacific Ocean and Atlantic Ocean, respectively, followed by the indices in the Indian Ocean. These identified drivers outperform the traditional Niño 3.4-based predictions. Overall, our results demonstrate the effectiveness of integrating ECA and complexity science to enhance the prediction of CDHE occurrences.

The Beta-decay Paul Trap Mk IV: Design and commissioning

The Beta-decay Paul Trap is an open-geometry, linear trap used to measure the decays of 8Li and 8B to search for a tensor contribution to the weak interaction. In the latest 8Li measurement of Burkey et al. (2022), β scattering was the dominant experimental systematic uncertainty. The Beta-decay Paul Trap Mk IV reduces the prevalence of β scattering by a factor of 4 through a redesigned electrode geometry and the use of glassy carbon and graphite as electrode materials. The trap has been constructed and successfully commissioned with 8Li in a new data campaign that collected 2.6 million triple coincidence events, an increase in statistics by 30% with 4 times less β scattering compared to the previous 8Li data set.

Unraveling atmospheric moisture transport linkages to extreme precipitation events and associated synoptic features over India

This study explores the physical mechanisms underlying extreme precipitation events linked to atmospheric moisture transport (IVT-P). It identifies regions where IVT influences extreme precipitation and investigates changes in synoptic-scale weather patterns over the Indian subcontinent. The study finds a strong association between daily IVT and precipitation over the core monsoon region and complex terrains of the Western Ghats and Himalayas. Event Coincidence Analysis reveals that extreme IVT can be used to forecast extreme precipitation in these regions. The dynamic component of moisture transport strongly influences daily and extreme precipitation over complex terrains, while the thermodynamic component influences precipitation over regions with abundant water vapor and weak horizontal winds. The study also identifies synoptic features and moisture transport ahead of IVT-P events and finds intense low-pressure anomalies, transition from ridge to trough patterns, and intense 700 hPa relative humidity in the specified regions. Overall, the study provides insights into the physical mechanisms underlying IVT linked extreme precipitation events.

Abrupt drought termination in the British–Irish Isles driven by high atmospheric vapour transport

During protracted dry spells, there is considerable interest from water managers, media and the public in when and how drought termination (DT) will occur. Robust answers to these questions require better understanding of the hydroclimatic drivers of DT than currently available. Integrated vapour transport (IVT) has been found to drive DT in Western North America, but evidence elsewhere is lacking. To evaluate this association for the British–Irish Isles, event coincidence analysis is applied to 354 catchments in the UK and Ireland over the period 1900–2010 using ERA-20C reanalysis IVT data and 7589 DT events extracted from reconstructed river flow series. Linkages are identified for 53% of all DT events across all catchments. Associations are particularly strong for catchments in western and southern regions and in autumn and winter. In Western Scotland, 80% of autumn DTs are preceded by high IVT, whilst in Southern England more than two thirds of winter DTs follow high IVT episodes. High IVT and DT are most strongly associated in less permeable, wetter upland catchments of Western Britain, reflecting their maritime setting and orographic enhancement of prevailing south-westerly high IVT episodes. Although high IVT remains an important drought-terminating mechanism further east, it less frequently results in DT. Furthermore, the highest rates of DT occur with increasing IVT intensity, and the vast majority of the most abrupt DTs only occur following top decile IVT and under strongly positive North Atlantic Oscillation (NAO) conditions. Since IVT and NAO forecasts may be more skilful than those for rainfall which underpin current forecasting systems, incorporating these findings into such systems has potential to underpin enhanced forecasting of DTs. This could help to mitigate impacts of abrupt recoveries from drought including water quality issues and managing compound drought–flood hazards concurrently.

Genomic inference of a severe human bottleneck during the Early to Middle Pleistocene transition.

Population size history is essential for studying human evolution. However, ancient population size history during the Pleistocene is notoriously difficult to unravel. In this study, we developed a fast infinitesimal time coalescent process (FitCoal) to circumvent this difficulty and calculated the composite likelihood for present-day human genomic sequences of 3154 individuals. Results showed that human ancestors went through a severe population bottleneck with about 1280 breeding individuals between around 930,000 and 813,000 years ago. The bottleneck lasted for about 117,000 years and brought human ancestors close to extinction. This bottleneck is congruent with a substantial chronological gap in the available African and Eurasian fossil record. Our results provide new insights into our ancestry and suggest a coincident speciation event.

Experimental quantum imaging distillation with undetected light.

Imaging based on the induced coherence effect makes use of photon pairs to obtain information of an object without detecting the light that probes it. While one photon illuminates the object, only its partner is detected, so no measurement of coincidence events is needed. The sought-after object's information is revealed, observing a certain interference pattern on the detected photon. Here, we demonstrate experimentally that this imaging technique can be made resilient to noise. We introduce an imaging distillation approach based on the interferometric modulation of the signal of interest. We show that our scheme can generate a high-quality image of an object even against noise levels up to 250 times the actual signal of interest. We also include a detailed theoretical explanation of our findings.

Chance coincidence analysis for capture-gated neutron spectrometry with a composite scintillator

Neutron spectrometry is important for radiation metrology, radiation protection, accelerator physics etc. The spectral response of a capture-gated detector to mono-energetic neutrons contains a significant peak, making it easy to be analyzed. But this system output not only capture-gated events (CGE) but also chance coincidence events (CCE). It is critical to identify and eliminate CCE. However, chance coincidence has not been analyzed in detail before. This paper aims to find a way to eliminate CCE and get the spectrum of CGE. Thus, categories of CCE were analyzed and their probability equations were established. Then recorded pulses from a composite scintillator measured in mixed radiation fields were used to verify CCE and explore the influence of timing gate. Results show that n/γ discrimination is effective to distinguish CCE caused by γ-rays and calculate the amount of CCE caused by fast neutrons. Timing gate should be determined according to the different distributions of CGE and CCE. Spectrum of CGE can be acquired by subtracting that of fast neutron CCE from the fast neutron spectrum of coincidence events.

Sequential minimum optimization algorithm with small sample size estimators

Sequential minimum optimization is a machine learning global search training algorithm. It is applicable when the functional dependence of the cost function on a tunable parameter given the other parameters can be cheaply determined. This assumption is satisfied by quantum circuits built of known gates. We apply it to photonic circuits where the additional challenge appears: low frequency of coincidence events lowers the speed of the algorithm. We propose to modify the algorithm such that small sample size estimators are enough to successfully run the machine learning task. We demonstrate the effectiveness of the modified algorithm applying it to a photonic classifier with data reuploading.

Experimental characterization of impact damage in foam-core sandwich structures using acoustic emission, optical scanning and X-ray computed tomography techniques

Sandwich structures used in transportation and energy industries are commonly subjected to low-velocity impact in the course of manufacturing, service and maintenance, which can lead to the premature degradation of structural stiffness and strength. A single non-destructive evaluation technique is often difficult to provide a comprehensive assessment on impact damage from online to offline and from visible to invisible. In the present study, acoustic emission (AE), three-dimensional (3D) optical scanning and X-ray computed tomography (CT) techniques are combined to provide a systematic approach for damage characterization of thick foam-core sandwich panels under low-velocity impact. In the tests, the mechanical responses such as force-time and force-displacement curves are obtained from the testing system. The AE technique is adopted to monitor damage initiation and evolution in situ; optical scanning and X-ray computed tomography techniques are used for off-line damage identification and quantification. The results show that the AE signal waveform stream, cumulative counts and cumulative energy correlate well with the mechanical responses of the sandwich panel under the low-velocity impact, enabling capture of valuable information for online damage monitoring. Unlike general cases, the AE signals generated from low-velocity impact are found to be presented in strong bursts of nearly coincident events in the short duration. Therefore, the distributions of AE amplitude and peak frequency between adjacent AE counts are extracted to study the different damage modes and damage mechanisms. The X-ray computed tomography images enable to precisely visualize the fracture behaviors of the PET foam-core inside the sandwich panel in a nondestructive fashion, which evidently supports the AE and optical scanning results. The study is anticipated to demonstrate effectiveness and capability of the proposed experimental methodology for damage detection and characterization on sandwiched composite structures subjected to impact loading.

A virtual-pinhole PET device for improving contrast recovery and enhancing lesion detectability of a one-meter-long PET scanner: a simulation study

This paper presents a simulation study to demonstrate that the contrast recovery coefficients (CRC) and detectability of small lesions of a one-meter-long positron emission tomography (PET) scanner can be further enhanced by the integration of high resolution virtual-pinhole (VP) PET devices. The scanner under investigation is a Siemens Biograph Vision Quadra which has an axial field-of-view (FOV) of 106 cm. The VP-PET devices contain two high-resolution flat panel detectors, each composed of 2 × 8 detector modules each of which consists of 32 × 64 lutetium-oxyorthosilicate crystals (1.0 × 1.0 × 10.0 mm3 each). Two configurations for the VP-PET device placement were evaluated: (1) place the two flat-panel detectors at the center of the scanner’s axial FOV below the patient bed; (2) place one flat-panel detector at the center of the first and the last quarter of the scanner’s axial FOV below the patient bed. Sensitivity profiles were measured by moving a point 22Na source stepwise across the scanner’s FOV axially at different locations. To assess the improvement in CRC and lesion detectability by the VP-PET devices, an elliptical torso phantom (31.6 × 22.8 × 106 cm3) was first imaged by the native scanner then subsequently by the two VP-PET geometry configurations. Spherical lesions (4 mm in diameter) having 5:1 lesion-to-background radioactivity concentration ratio were grouped and placed at nine regions in the phantom to analyze the dependence of the improvement in plane. Average CRCs and their standard deviations of the 7 tumors in each group were computed and the receiver operating characteristic (ROC) curves were drawn to evaluate the improvement in lesion detectability by the VP-PET device over the native long axial PET scanner. The fraction of coincidence events between the inserts and the scanner detectors was 13%–16% (out of the total number of coincidences) for VP-PET configuration 1 and 2, respectively. The VP-PET systems provide higher CRCs for lesions in all regions in the torso, with more significant enhancement at regions closer to the inserts, than the native scanner does. For any given false positive fraction, the VP-PET systems offer higher true positive fraction compared to the native scanner. This work provides a potential solution to further enhance the image resolution of a long axial FOV PET scanner to maximize its lesion detectability afforded by its super high effective sensitivity.

A simulation study of 1D U-Net-based inter-crystal scatter event recovery of PET detectors

To achieve high spatial resolution of reconstructed images in positron emission tomography (PET), the size of the scintillation crystal element is set small in current PET systems, which greatly increases the inter-crystal scattering (ICS) frequency. The ICS is a type of Compton scattering of the gamma photons from one crystal element to its neighborhood element, which obscures the determination of the first interaction position. In this study, we propose a 1D U-Net convolutional neural network to predict the first interaction position, which provides a universal way to efficiently solve the ICS recovery problem. The network is trained using the dataset collected from the GATE Monte Carlo simulation. The 1D U-Net structure is applied due to its capability of synthesizing both low-level and high-level information, which shows superiority in solving the ICS recovery problem. After being well trained, the 1D U-Net can generate a prediction accuracy of 78.1%. Compared to the coincidence events only composed from two photoelectric gamma photons, the sensitivity is improved by 149%. The contrast-to-noise ratio of the reconstructed contrast phantom increases from 6.973 to 10.795 for the 16 mm hot sphere. Compared to the take-energy-centroid method, the spatial resolution of the reconstructed resolution phantom can obtain the best improvement of 33.46%. Compared with the previous deep learning method based on the fully connected network, the proposed 1D U-Net can work more stably with considerably fewer network parameters. The 1D U-Net network model shows good universality when predicting different phantoms, and the computation speed is fast.

A depth-of-interaction rebinning method based on both geometric and activity weights

Background and objectiveFor positron emission tomography (PET) scanners with depth-of-interaction (DOI) measurement, the DOI rebinning method that utilizes DOI information to process the projection data is critical to image quality. Current DOI rebinning methods map coincidence events onto the rebinned sinogram based on the correlation of lines of response (LOR). This study aims to incorporate prior radioactivity distribution of the imaging object into DOI rebinning to obtain better image quality. MethodsA DOI rebinning method based on both geometric and activity weights was proposed to assign coincidence events to the rebinned sinogram defined by a virtual ring. The geometric weights, representing the correlation between LORs, were calculated based on the areas of intersection. The activity weights, reflecting the activity distribution of the imaging object, were derived from the previous reconstructed image. ResultsMonte Carlo simulation data from four phantoms, including the image quality phantom, Derenzo phantom, and two rat-like ROBY phantoms, was used to evaluate the proposed method. The recovery coefficient (RC), contrast recovery coefficient (CRC), structural similarity index measure (SSIM), and peak signal-to-noise ratio (PSNR) were used as image quality metrics. Compared to other DOI rebinning methods, the proposed method achieved the highest RC (maximum improvement of 32%) and CRC at the same noise level and was also optimal in terms of the SSIM and PSNR. Meanwhile, incorporating the prior activity distribution into DOI rebinning also improved the image reconstruction speed. ConclusionsThis work developed a new DOI rebinning method combining the correlation of LORs with the prior activity distribution, achieving relatively optimal image quality and reconstruction speed. Furthermore, it still needs to be evaluated on the actual equipment.

Mechanisms of simultaneous linear and nonlinear computations at the mammalian cone photoreceptor synapse

Neurons enhance their computational power by combining linear and nonlinear transformations in extended dendritic trees. Rich, spatially distributed processing is rarely associated with individual synapses, but the cone photoreceptor synapse may be an exception. Graded voltages temporally modulate vesicle fusion at a cone’s ~20 ribbon active zones. Transmitter then flows into a common, glia-free volume where bipolar cell dendrites are organized by type in successive tiers. Using super-resolution microscopy and tracking vesicle fusion and postsynaptic responses at the quantal level in the thirteen-lined ground squirrel, Ictidomys tridecemlineatus, we show that certain bipolar cell types respond to individual fusion events in the vesicle stream while other types respond to degrees of locally coincident events, creating a gradient across tiers that are increasingly nonlinear. Nonlinearities emerge from a combination of factors specific to each bipolar cell type including diffusion distance, contact number, receptor affinity, and proximity to glutamate transporters. Complex computations related to feature detection begin within the first visual synapse.

The (mis)identification of high-latitude dust events using remote sensing methods in the Yukon, Canada: a sub-daily variability analysis

Abstract. The observation and quantification of mineral dust fluxes from high-latitude sources remains difficult due to a known paucity of year-round in situ observations and known limitations of satellite remote sensing data (e.g. cloud cover and dust detection). Here we explore the chronology of dust emissions at a known and instrumented high-latitude dust source: Lhù'ààn Mân (Kluane Lake) in Yukon, Canada. At this location we use oblique time-lapse (RC) cameras as a baseline for analysis of aerosol retrievals from in situ metrological data, AERONET, and co-incident MODIS MAIAC to (i) investigate the daily to annual chronology of dust emissions recorded by these instrumental and remote sensing methods (at timescales ranging from minutes to years) and (ii) use data intercomparisons to comment on the principal factors that control the detection of dust in each case. Lhù'ààn Mân is a prolific mineral dust source; on 24 May 2018 the RC captured dust in motion throughout the entire day, with the longest dust-free period lasting only 30 min. When compared with time series of RC data, optimized AERONET data only manage an overall 26 % detection rate for events (sub-day) but 100 % detection rate for dust event days (DEDs) when dust was within the field of view. In this instance, RC and remote sensing data were able to suggest that the low event detection rate was attributed to fundamental variations in dust advection trajectory, dust plume height, and inherent restrictions in sun angle at high latitudes. Working with a time series of optimized aerosol optical depth (AOD) data (covering 2018/2019), we were able to investigate the gross impacts of data quality (DQ) choice on DED detection at the month or year scale. Relative to ground observations, AERONET's DQ2.0 cloud-screening algorithm may remove as much as 97 % of known dust events (3 % detection). Finally, when undertaking an AOD comparison for DED and non-DED retrievals, we find that cloud screening of MODIS/AERONET lead to a combined low sample of co-incident dust events and weak correlations between retrievals. Our results quantify and explain the extent of under-representation of dust in both ground and space remote sensing methods; this is a factor that impacts on the effective calibration and validation of global climate and dust models.

Modeling directed weighted network based on event coincidence analysis and its application on spatial propagation characteristics.

The problem of synchronicity quantification, based on event occurrence time, has become the research focus in different fields. Methods of synchrony measurement provide an effective way to explore spatial propagation characteristics of extreme events. Using the synchrony measurement method of event coincidence analysis, we construct a directed weighted network and innovatively explore the direction of correlations between event sequences. Based on trigger event coincidence, the synchrony of traffic extreme events of base stations is measured. Analyzing topology characteristics of the network, we study the spatial propagation characteristics of traffic extreme events in the communication system, including the propagation area, propagation influence, and spatial aggregation. This study provides a framework of network modeling to quantify the propagation characteristics of extreme events, which is helpful for further research on the prediction of extreme events. In particular, our framework is effective for events that occurred in time aggregation. In addition, from the perspective of a directed network, we analyze differences between the precursor event coincidence and the trigger event coincidence and the impact of event aggregation on the synchrony measurement methods. The precursor event coincidence and the trigger event coincidence are consistent when identifying event synchronization, while there are differences when measuring the event synchronization extent. Our study can provide a reference for the analysis of extreme climatic events such as rainstorms, droughts, and others in the climate field.

Coincidence-based reconstruction for reactor antineutrino detection in gadolinium-doped Cherenkov detectors

A reconstruction algorithm has been developed to capitalize on advances in Cherenkov technology for reactor antineutrino detection.Large gadolinium-doped water (Gd-H2O) Cherenkov detectors are a developing technology which use Gd loading to increase the visibility of the neutrons produced in inverse beta decay (IBD) interactions, which produce positron–neutron pairs coincident in time and space. In this paper, we describe the reconstruction which uses the combined light from both events in an IBD pair to accurately reconstruct the interaction vertex.Using simulation, the algorithm has been applied to the reconstruction of reactor antineutrinos in Gd-H2O and in Gd-doped water-based liquid scintillator (Gd-WbLS), an advanced detector medium which is also currently in development.Compared to a single-event reconstruction, the combined reconstruction improves vertex resolution for reactor IBD positrons by up to a factor of 4.5 at the lowest energies. IBD-neutron vertex resolution was found to improve by more than 30% in most instances.Powerful background rejection with the coincidence reconstruction can be achieved by requiring a minimum quality of fit. This was found to reject up to 94% of accidental coincidences of uncorrelated background events, while retaining at least 97.5% of the IBD signal pairs.

Enhanced light signal for the suppression of pile-up events in Mo-based bolometers for the 0nu beta beta decay search.

Random coincidences of events could be one of the main sources of background in the search for neutrino-less double-beta decay of ^{100}Mo with macro-bolometers, due to their modest time resolution. Scintillating bolometers as those based on Li_2MoO_4 crystals and employed in the CROSS and CUPID experiments can eventually exploit the coincident fast signal detected in a light detector to reduce this background. However, the scintillation provides a modest signal-to-noise ratio, making difficult a pile-up pulse-shape recognition and rejection at timescales shorter than a few ms. Neganov–Trofimov–Luke assisted light detectors (NTL-LDs) offer the possibility to effectively increase the signal-to-noise ratio, preserving a fast time-response, and enhance the capability of pile-up rejection via pulse shape analysis. In this article we present: (a) an experimental work performed with a Li_2MoO_4 scintillating bolometer, studied in the framework of the CROSS experiment, and utilizing a NTL-LD; (b) a simulation method to reproduce, synthetically, randomly coincident two-neutrino double-beta decay events; (c) a new analysis method based on a pulse-shape discrimination algorithm capable of providing high pile-up rejection efficiencies. We finally show how the NTL-LDs offer a balanced solution between performance and complexity to reach background index sim 10^{-4} counts/keV/kg/year with 280 g Li_2MoO_4 (^{100}Mo enriched) bolometers at 3034 keV, the Q_{beta beta } of the double-beta decay, and target the goal of a next generation experiment like CUPID.

Increased likelihood of compound dry and hot extremes in India

Compound dry and hot extremes (CDHE) are periods of prolonged dry and hot weather. Their joint occurrence typically impacts society and nature stronger compared to the occurrence of the single hazards. Understanding the likelihood, variability and drivers of CDHE is challenging due to the complexity of the climate system involving interactions and feedbacks among atmosphere-land processes. In this study, we first investigate the role of the dependence between precipitation and temperature for the likelihood of CDHEs. We demonstrate that both the dependence strength and its type, i.e. the degree of tail dependence, substantially affect the CDHE likelihood. We then analyze the space-time variation of CDHE characteristics during the Indian Summer Monsoon across India for the period 1961–2014. We find strong negative association and substantial tail dependence between precipitation and temperature in some regions. Event coincidence analysis reveals that low soil moisture preconditioned by dry extremes is responsible for 55–65% of CDHE occurrence. Our analysis of the temporal evolution of CDHE characteristics finds an increasing negative association between precipitation and temperature leading to a 2 to 3-fold rise of CDHE frequency for some regions of India.