Forward Particle Research Articles

Origin, Variability, and Pathways of East Sea Intermediate Water in a High‐Resolution Ocean Reanalysis

AbstractThe East Sea Intermediate Water (ESIW) is the subsurface salinity minimum layer in the depth range 200–400 m in the East/Japan Sea. The origin, variability, and pathways of the ESIW were investigated using a 4‐year‐long (2015–2018) high‐resolution (1/24°) ocean reanalysis and Lagrangian particle modeling. A backward particle tracking analysis revealed that the ESIW was formed south of Vladivostok and shows strong interannual variability. In 2018, owing to strong northwesterly winds, heat loss to the air intensified, and freshwater transport from the northern East/Japan Sea was simultaneously decreased by about 18% compared with the previous year. Furthermore, there was increased formation of water masses heavier than that of the typical ESIW, and the volume of the ESIW was reduced. A forward particle tracking analysis showed that the contribution of the particles originated from the northern end of the East/Japan Sea was about two times greater than those from the southern end. The major portion of the ESIW's freshwater came from the northern East/Japan Sea, where sea ice melted and the Amur River discharged. The remaining portion was from the Changjiang River, which came through the Korea Strait. The ESIW reached the Ulleung Basin over the course of a year mainly through the deep channel, the Ulleung Trough, located to the north of the basin. The diapycnal diffusivity of 1.0 × 10−4 m2 s−1 could erode away the low salinity core in about 27 years.

Assessment of Respiratory Droplet Transmission During the Ophthalmic Slit-Lamp Exam: A Particle Tracking Analysis

PurposeThe global COVID-19 pandemic has resulted in a renewed focus on the importance of personal protective equipment (PPE) and other interventions to decrease spread of infectious diseases. Although several ophthalmology organizations have released guidance on appropriate PPE for surgical procedures and ophthalmology clinics, there is limited experimental evidence that demonstrates the efficacy of various interventions that have been suggested. In this study, we evaluated high-risk aspects of the slit-lamp exam and the effect of various PPE interventions, specifically the use of a surgical mask and a slit-lamp shield.DesignExperimental simulation study.MethodsThis was a single-center study in a patient simulation population. This study examined the presence of particles in the air near or on a slit-lamp, a simulated slit-lamp examiner, or a simulated patient using a fluorescent surrogate of respiratory droplets.ResultsSimulated coughing without a mask or slit-lamp shield resulted in widespread dispersion of fluorescent droplets during the model slit-lamp examination. Coughing with a mask resulted in the most significant decrease in droplets; however, particles still escaped from the top of the mask. Coughing with the slit-lamp shield alone blocked most of forward particle dispersion; however, significant distributions of respiratory droplets were found on the slit-lamp joystick and table. Coughing with both a mask and slit-lamp shield resulted in the least dispersion to the simulated examiner and the simulated patient. Scanning electron microscopy demonstrated particle sizes of 3-100 μm.ConclusionsMasking had the greatest effect in limiting spread of respiratory droplets, whereas slit-lamp shields and gloves also contributed to limiting exposure to droplets from SARS-CoV-2 during slit-lamp examination.

Multi-parameter inversion with the aid of particle velocity field reconstruction

Multi-parameter inversion for medical ultrasound leads to an improved tissue classification. In general, simultaneous reconstruction of volume density of mass and compressibility would require knowledge of the particle velocity field along with the pressure field. However, in practice the particle velocity field is not measured. Here, the authors propose a method for multi-parameter inversion where the particle velocity field is reconstructed from the measured pressure field. To this end, the measured pressure field is described using outward propagating Hankel functions. For a synthetic setup, it is shown that the reconstructed particle velocity field matches the forward modelled particle velocity field. Next, the reconstructed particle velocity field is used together with the synthetically measured pressure field to reconstruct density and compressibility profiles with the aid of contrast source inversion. Finally, comparing the reconstructed speed of sound profiles obtained via single-parameter versus multi-parameter inversion shows that multi-parameter outperforms single-parameter inversion with respect to accuracy and stability.

Transverse-momentum Spectra of Hadrons in \(p+p\) Collisions at CERN SPS Energies from the UrQMD Transport Model

Abstract The UrQMD transport model, version 3.4, is used to study the new experimental data on transverse momentum spectra of π ± , K ± , p and p ¯ produced in inelastic p + p interactions at SPS energies, recently published by the NA61/SHINE Collaboration. The comparison of model predictions to these new measurements is presented as a function of collision energy for central and forward particle rapidity intervals. In addition, the inverse slope parameters characterizing the transverse momentum distributions are extracted from the predicted spectra and compared to the corresponding values obtained from NA61/SHINE distributions, as a function of particle rapidity and collision energy. A complex pattern of deviations between the experimental data and the UrQMD model emerges. For charged pions, the fair agreement visible at top SPS energies deteriorates with the decreasing energy. For charged K mesons, UrQMD significantly underpredicts positive kaon production at lower beam momenta. It also underpredicts the central rapidity proton yield at top collision energy and overpredicts antiproton production at all considered energies. We conclude that the new experimental data analyzed in this paper still constitute a challenge for the present version of the model.

Detecting and studying high-energy collider neutrinos with FASER at the LHC

Neutrinos are copiously produced at particle colliders, but no collider neutrino has ever been detected. Colliders produce both neutrinos and anti-neutrinos of all flavors at very high energies, and they are therefore highly complementary to those from other sources. FASER, the Forward Search Experiment at the LHC, is ideally located to provide the first detection and study of collider neutrinos. We investigate the prospects for neutrino studies with FASERnu , a proposed component of FASER, consisting of emulsion films interleaved with tungsten plates with a total target mass of 1.2 t, to be placed on-axis at the front of FASER. We estimate the neutrino fluxes and interaction rates, describe the FASERnu detector, and analyze the characteristics of the signals and primary backgrounds. For an integrated luminosity of 150~text {fb}^{-1} to be collected during Run 3 of the 14 TeV LHC in 2021–23, approximately 1300 electron neutrinos, 20,000 muon neutrinos, and 20 tau neutrinos will interact in FASERnu , with mean energies of 600 GeV to 1 TeV. With such rates and energies, FASER will measure neutrino cross sections at energies where they are currently unconstrained, will bound models of forward particle production, and could open a new window on physics beyond the standard model.

Evaluation of the performance of a hydraulic barrier by the Null space Monte Carlo method

A gasoline leak caused the contamination of a shallow alluvial aquifer in an urbanized area in Northern Italy. A rapid intervention was conceived to stop the spreading of contamination: a hydraulic barrier has been placed downstream of the source to collect both the floating oil and the contaminated groundwater. A numerical model has been built to assess the performance of the existing barrier, and to design a new configuration of the hydraulic barrier aimed at stopping the hydrocarbon plume already dispersed downstream. A preliminary model was built and calibrated against groundwater levels measured in 41 monitoring wells. Hydraulic conductivities in pilot points, recharge zones and constant head BCs were calibrated. The non-uniqueness of the calibrated parameters led to identify 283 alternative parameter sets, all able to represent the observed heads within an absolute average error of 10 cm. These sets, generated with the Null space Monte Carlo method, served to build 283 models, used to simulate the dispersion of solved contamination through forward particle tracking. A further step was the censoring of all simulations resulting in particle paths at a distance closer than 5 meters from monitoring wells where contamination was never found since the spilled occurred. Analysis was performed of the particle paths generated with the 187 models that were retained. Overall, the barrier captures 89% of all particles. Moreover, in 74% of all realizations, at least a particle escapes, with a mean and median of 7 particles in each realization where it happens. Two main contamination paths are identified: while one is confirmed by the monitoring wells already present, another one would require the placement of new wells to assess the actual presence of contamination. Thus, the validity of the stochastic simulation would be assessed together with the need to improve the performance of the hydraulic barrier.

Nonreciprocity and thermoelectric performance in a double-dot Aharonov–Bohm interferometer

We investigate nonreciprocity and thermoelectric performance beyond the linear response regime in a double-dot Aharonov–Bohm interferometer that is connected to three reservoirs. In the presence of a magnetic flux (broken time-reversal symmetry), we find that the difference between the forward and reverse particle currents can reach the order of 10% under certain conditions. We also show that when the temperature gradient is reversed, the thermoelectric efficiency and output power both change; however, the discrepancies are minimal. Indeed, although breaking time-reversal symmetry can enhance the maximum efficiency, it reduces the maximum power in the present model. These results could be useful for the design of nanoscale thermoelectric devices.

Second-order adjoint sensitivity analysis of a general ratio of functionals of the forward and adjoint fluxes in a multiplying nuclear system with source

In the present work, the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) is applied to a generic multiplying subcritical nuclear system comprising a non-fission neutron source in order to compute efficiently and exactly all of the 1st- and 2nd-order functional derivatives (“sensitivities”) of a system response with respect to the system’s many parameters. The system response is defined to be a ratio of two general nonlinear functionals of the forward and adjoint particle fluxes, while the system parameters include isotopic number densities, microscopic cross sections, fission spectrum parameters, neutron sources, and detector response functions. Such ratios of functionals represent the most general models for quantities of fundamental importance in reactor physics, including eigenvalues, ratios of reaction rates and forward/adjoint flux-weighted multi-group cross sections. The exact expressions obtained in this work will be used in subsequent works to perform a large-scale sensitivity analysis of a polyethylene-reflected plutonium metal sphere experimental benchmark to the nuclear data characterizing this benchmark, comprising 21,976 first-order sensitivities and 482,944,576 second-order sensitivities.

Comparative study for target fragmentation in 4He and 6Li interactions with emulsion nuclei at Elab = 3.7A GeV

The multiplicity characteristics of the grey and black particles are studied in 3.7A GeV 4He and 6Li interactions with emulsion nuclei. The dependence on the system size is examined. The data are classified according the emission direction in the 4π space. The forward or backward emitted grey particle multiplicities distributions are approximated by exponential decay law. The black particle distributions also have the decay shapes, except for the CNO target nuclei; they are shoulder-shaped curves. The production probabilities and average multiplicities increase linearly with the target size. Multiplicity correlations are carried out. Regarding the nuclear limiting fragmentation hypothesis, the grey and black particle productions are independent of the projectile size.

The Roussopoulos and Schwinger Functionals for Nuclear Systems Involving Imprecisely Known Fluxes and Parameters: Distinctions and Equivalences

For over 60 years, the Roussopoulos and Schwinger functionals have been used in many works and textbooks under the assumption that they provide “second-order accurate” trial functions for the forward and adjoint fluxes when computing reaction rates and/or particle detector responses in source-driven nuclear systems. The Schwinger functional has been employed as a particularly useful form of the Roussopoulos functional for systems in which the forward and adjoint particle fluxes were normalized. When using these functionals, however, the expressions for the approximate fluxes were postulated arbitrarily while the system parameters were unrealistically assumed to be perfectly well known. This work revisits the Roussopoulos and Schwinger functionals within the realistic practical context of imprecisely known model parameters, including imprecisely known cross sections, number densities, fission spectra, and forward and adjoint sources. By applying the Second-Order Adjoint Sensitivity Analysis (2nd-ASAM) methodology, this work shows that the first-order sensitivities of the Roussopoulos and Schwinger functionals to model parameters are not identically zero. This fact implies that neither the Roussopoulos nor the Schwinger functionals are accurate to second order in parameter variations/uncertainties, which implies, in turn, that these functionals are not accurate to second order variations in the flux when such flux-variations are caused by imprecisely known model parameters. Furthermore, the 2nd-ASAM methodology applied in this work also provides exactly and efficiently all of the second-order sensitivities of the Roussopoulos and Schwinger functionals to the imprecisely known model parameters. The new results presented in this work place in the correct light the results published hitherto in works that have used the Roussopoulos and Schwinger functionals while also indicating the correct path for future possible uses of these functionals for performing sensitivity and uncertainty analyses of both forward and inverse problems in nuclear systems.

Second-order sensitivities of a general functional of the forward and adjoint fluxes in a multiplying nuclear system with source

This work presents an application of the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) to compute efficiently and exactly all of the 1st- and 2nd-order functional derivatives (“sensitivities”) of a generic scalar-valued response to parameters for a multiplying subcritical system comprising a non-fission neutron source. The response is defined to be a nonlinear functional of the forward and adjoint particle fluxes while the system parameters include isotopic number densities, microscopic cross sections, fission spectrum, sources, and detector response functions. As indicated by the general theoretical considerations underlying the 2nd-ASAM, the number of computations required to obtain the 1st- and 2nd-order increases linearly in augmented Hilbert spaces as opposed to increasing exponentially in the original Hilbert space. This unique feature provides the fundamental reason for the unmatched efficiency of the 2nd-ASAM for computing exactly all of the 1st- and 2nd-order responses sensitivities to model parameters. The results presented in this work are currently being implemented in several production-oriented three dimensional neutron transport code systems for analyzing specific subcritical systems.

On the use of a running coupling in the calculation of forward hadron production at next-to-leading order

We study a puzzle raised recently regarding the running coupling prescription used in the calculation of forward particle production in proton-nucleus collisions at next-to-leading order: using a coordinate space prescription which is consistent with the one used in the high energy evolution of the target leads to results which can be two orders of magnitude larger than the ones obtained with a momentum space prescription. We show that this is an artefact of the Fourier transform involved when passing between coordinate and momentum space and propose a new coordinate space prescription which avoids this problem.

Study of contributions of diffractive processes to forward neutral particle production with the ATLAS-LHCf detector

LHCf is an experiment dedicated to verify the hadronic interaction models by measuring the forward neutral particle production at the LHC. Corresponding data are very important for understanding hadronic interactions occurring in air-shower development. According to the current LHCf results, no simulation model predicts the LHCf data perfectly. In order to provide more specific data, it is necessary to classify the LHCf observables into specific interaction types: diffraction or non-diffraction. Combining the information of ATLAS, LHCf is able to classify these specific interaction types experimentally. Especially, the ATLAS-LHCf joint experiment will have the unique sensitivity to low mass diffraction. LHCf and ATLAS have succeeded in the common data-taking in p-p collisions at √s = 13 TeV. We will report the first ATLAS-LHCf joint analysis result and discuss the impact of the corresponding joint analysis result to the determination of mass composition of ultra-high energy cosmic-rays.

Forecasting of Rainfall in Central Java using Hybrid GSTAR-NN-PSO Model

Forecasting of rainfall trends is essential for several fields, such as airline and ship management, flood control and agriculture. The rainfall data were recorded several time simultaneously at a number of locations and called the space-time data. Generalized Space Time Autoregressive (GSTAR) model is one of space-time models used to modeling and forecasting the rainfall. The aim of this research is to propose the nonlinear space-time model based on hybrid of GSTAR, Feed Forward Neural Network (FFNN) and Particle Swarm Optimization (PSO) and it called GSTAR-NN-PSO. In this model, input variable of the FFNN was obtained from the GSTAR model. Then use PSO to initialize the weight parameter in the FFNN model. This model is applied for forecasting monthly rainfall data in Jepara, Kudus, Pati and Grobogan, Central Java, Indonesia. The results show that the proposed model gives more accurate forecast than the linear space-time model, i.e. GSTAR and GSTAR-PSO. Moreover, further research about space-time models based on GSTAR and Neural Network is needed to improving the forecast accuracy especially the weight matrix in the GSTAR model.

Inference of an Optimal Ice Particle Model through Latitudinal Analysis of MISR and MODIS Data

The inference of ice cloud properties from remote sensing data depends on the assumed forward ice particle model, as they are used in the radiative transfer simulations that are part of the retrieval process. The Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 (MC6) ice cloud property retrievals are produced in conjunction with a single-habit ice particle model with a fixed degree of ice particle surface roughness (the MC6 model). In this study, we examine the MC6 model and five other ice models with either smoother or rougher surface textures to determine an optimal model to reproduce the angular variation of the radiation field sampled by the Multi-angle Imaging Spectroradiometer (MISR) as a function of latitude. The spherical albedo difference (SAD) method is used to infer an optimal ice particle model. The method is applied to collocated MISR and MODIS data over ocean for clouds with temperatures ≤233 K during December solstice from 2012–2015. The range of solar zenith angles covered by the MISR cameras is broader at the solstices than at other times of the year, with fewer scattering angles associated with sun glint during the December solstice than the June solstice. The results suggest a latitudinal dependence in an optimal ice particle model, and an additional dependence on the solar zenith angle (SZA) at the time of the observations. The MC6 model is one of the most optimal models on the global scale. In further analysis, the results are filtered by a cloud heterogeneity index to investigate cloudy scenarios that are less susceptible to potential 3D effects. Compared to results for global data, the consistency between measurements and a given model can be distinguished in both the tropics and extra-tropics. The SAD analysis suggests that the optimal model for thick homogeneous clouds corresponds to more roughened ice particles in the tropics than in the extra-tropics. While the MC6 model is one of the models most consistent with the global data, it may not be the most optimal model for the tropics.

On the threshold resummation in forward pA collisions

In this paper, using the Higgs production in forward rapidity region in proton-nucleus collisions as an example, we demonstrate that we can construct a systematic formalism for the threshold resummation for forward rapidity particle productions in the saturation formalism. The forward threshold jet function, which satisfies the corresponding renormalization group equation, is introduced into the new factorization formula. This calculation can be easily generalized to other processes, such as single forward hadron productions at forward rapidity region, and have important phenomenological implications.

Unscented Particle Smoother and Its Application to Transfer Alignment of Airborne Distributed POS

This paper deals with the problem of state estimation for the transfer alignment of airborne distributed position and orientation system (distributed POS). For a nonlinear system, especially with large initial attitude errors, the performance of linear estimation methods will degrade. In this paper, a nonlinear smoothing algorithm called the unscented particle smoother (UPS) is proposed and utilized in the off-line transfer alignment of airborne distributed POS. In this algorithm, the measurements are first processed by the forward unscented particle filter (UPF) and then a backward smoother is used to achieve the improved solution. The performance of this algorithm is compared with that of a similar smoother known as the unscented Rauch-Tung-Striebel smoother. The simulation results show that the UPS effectively improves the estimation accuracy and this work offers a new off-line transfer alignment approach of distributed POS for multiantenna synthetic aperture radar and other airborne earth observation tasks.

Image Resteoration by BP Neural Based on PSO

Based on PSO-BP algorithm combining particle swarm algorithm with BP neural network algorithm, this paper applies this algorithm to image restoration based on optimization. In the PSO-BP optimization algorithm model, on the one hand, the error of each training sample of BP algorithm is reversed, and the original image is used as the reference to modify the weight threshold of BP algorithm. On the other hand, it is optimized by forward particle swarm algorithm and BP algorithm. Finally, through the algorithm analysis and experimental data, the recovery effect of PSO-BP optimization algorithm is better than that of the same type algorithm.

Transient Groundwater Travel Time Distributions and Age‐Ranked Storage‐Discharge Relationships of Three Lowland Catchments

AbstractThe contribution of groundwater to streams is controlled by temporally and spatially variable groundwater flow paths with distinctive travel times. The aggregated average travel time distribution (TTD) of all these flow paths functions as a catchment characteristic. Currently, research on TTDs is expanding towards dynamic TTDs and building on this, we present dynamic backward TTDs and residence time distributions using forward particle tracking on a high‐resolution spatially distributed groundwater flow model (25*25 m). We show that the dynamic backward TTDs of three Dutch catchments are determined by the interplay between the activation of shallow short flow paths and the intensification of fluxes through all flow paths when groundwater levels rise. In addition, the preference for young water in our lowland catchments appears strongly controlled by drainage density. Variations in catchment mixing with time and between catchments were analyzed using dynamic StorAge Selection (SAS) functions. This showed the effect of differences in geology and topography on the shape of the SAS functions. Additionally, the variability of SAS functions in time was shown to depend on the extent to which new flow paths can be activated. Time‐varying SAS functions are required for computation of dynamic TTDs, and this research showed realistic values for the variability in the SAS functions of lowland catchments. The step towards dynamic TTDs is crucial for understanding the temporal and spatial behavior of streams, their chemical composition, and their ecological value.

Transverse momentum spectra of hadrons in p + p collisions at CERN SPS energies from the UrQMD transport model

The UrQMD transport model, version 3.4, is used to study the new experimental data on transverse momentum spectra of π±, K±, p and p¯ produced in inelastic p+p interactions at SPS energies, recently published by the NA61/SHINE Collaboration. The comparison of model predictions to these new measurements is presented as a function of collision energy for central and forward particle rapidity intervals. In addition, the inverse slope parameters characterizing the transverse momentum distributions are extracted from the predicted spectra and compared to the corresponding values obtained from NA61/SHINE distributions, as a function of particle rapidity and collision energy. A complex pattern of deviations between the experimental data and the UrQMD model emerges. For charged pions, the fair agreement visible at top SPS energies deteriorates with the decreasing energy. For charged K mesons, UrQMD significantly underpredicts positive kaon production at lower beam momenta. It also underpredicts the central rapidity proton yield at top collision energy and overpredicts antiproton production at all considered energies. We conclude that the new experimental data analyzed in this paper still constitute a challenge for the present version of the model.