bluuebunny/crossref_metadata_2025_split huggingface dataset:
Semi-Equivariant GNN Architectures for Jet Tagging
Authors: Murnane Daniel , Thais Savannah , Wong Jason 
Published: February 2023

Abstract
Composing Graph Neural Networks (GNNs) of operations that respect physical symmetries has been suggested to give better model performance with a smaller number of learnable parameters. However, real-world applications, such as in high energy physics have not born this out. We present the novel architecture VecNet that combines both symmetry-respecting and unconstrained operations to study and tune the degree of physics-informed GNNs. We introduce a novel metric, the ant factor, to quantify the resource-efficiency of each configuration in the search-space. We find that a generalized architecture such as ours can deliver optimal performance in resource-constrained applications.
Signal to background discrimination for the production of double Higgs boson events via vector boson fusion mechanism in the decay channel with four charged leptons and two b-jets in the final state at the LHC experiment
Authors: D’Anzi Brunella , De Filippis Nicola , Elmetenawee Walaa , Miniello Giorgia 
Published: February 2023

Abstract
At the CERN Large Hadron Collider experiment, the non-resonant double Higgs production via vector-boson fusion represents a unique mean to probe the VVHH (V=Z, W±) Higgs self-coupling at the current center of mass energies. Such a rare signal cannot be separated efficiently from huge backgrounds by applying a few-observables cut-based selection. Indeed, in this work, a Deep Learning algorithm is used to decide whether an event is more signal- or background-like. In particular, we report on two main aspects: results on a hyper-parameters parallel scanning strategy to distribute the training process across multiple nodes on the ReCaS-Bari data center computing resources and on the discriminating performance of a Deep Neural Network architecture.
Slicing with deep learning models at ProtoDUNE-SP
Authors: Rossi M 
Published: February 2023

Abstract
DUNE is a cutting-edge experiment aiming to study neutrinos in detail, with a special focus on the flavor oscillation mechanism. The prototype of the DUNE Far Detector Single Phase TPC (ProtoDUNE-SP) was built and operated at CERN with a full set of reconstruction tools. To implement these reconstruction tools, Pandora, a multi-algorithm framework, has been developed. A large number of these algorithms, some of them being exploiting traditional clustering, detector physics and deep learning approaches, have been applied to images to gradually build up a picture out of singular events. One of such algorithms is the Pandora slicing algorithm which aims to partition the detector hits of an event in sets called slices. Each slice represents a single interaction in the detector and should identify all the hits related to the interacting particle and its subsequent decay products. We expect the order of tens of slices per event in ProtoDUNE-SP. In this paper we present a deep learning approach to the problem, designing a model able to outperform the state-of-the-art slicing algorithm which is currently implemented within Pandora. We assess the performance of our tool in terms of efficiency and accuracy, while exploiting hardware accelerating setups. The ultimate goal is to incorporate this deep learning approach in the Pandora reconstruction tool.
Treatment of systematic uncertainties with Bayesian networks
Authors: Grilli di Cortona G. , Messina A. , Piacentini S. 
Published: February 2023

Abstract
We show an innovative approach based on Bayesian networks and linear algebra providing a solid and complete solution to the problem of the detector response and the related systematic effects. As a case study, we consider the dark matter direct detection searches. In this context, it is crucial to develop a reliable analysis framework, which is able to take into account all the relevant systematic effects in a clean and accessible way. The relations connecting the calibration parameters of the experiment to the final observed data spectrum are characterized by substantial complexity and non linearity. Usual approaches to direct detection data analysis involve multi-templates techniques. By means of our technique however it is possible to represent the full detector response to any background/signal event keeping the dependence on the detector parameters explicit. The advantage of this kind of approach is twofold: from the statistical point of view it is a solid and rigorous way to perform the analysis; from the computational point of view, we demonstrate that it is possible to represent the response of the detector by a set of matrices, allowing to use a GPU accelerated analysis code to improve the performance of the fit.
Algebraic geometry and p-adic numbers for scattering amplitude ansätze
Authors: De Laurentis Giuseppe 
Published: February 2023

Abstract
Scattering amplitudes in perturbative quantum field theory exhibit a rich structure of zeros, poles and branch cuts which are best understood in complexified momentum space. It has been recently shown that by leveraging this information one can significantly simplify both analytical reconstruction and final expressions for the rational coefficients of transcendental functions appearing in phenomenologically-relevant scattering amplitudes. Inspired by these observations, we present a new algorithmic approach to the reconstruction problem based on p-adic numbers and computational algebraic geometry. For the first time, we systematically identify and classify the relevant irreducible surfaces in spinor space with five-point kinematics, and thanks to p-adic numbers – analogous to finite fields, but with a richer structure to their absolute value – we stably perform numerical evaluations close to these singular surfaces, thus completely avoiding the use of floating-point numbers. Then, we use the data thus acquired to build ansätze which respect the vanishing behavior of the numerator polynomials on the irreducible surfaces. These ansätze have fewer free parameters, and therefore reduced numerical sampling requirements. We envisage future applications to novel two-loop amplitudes.
Amplitude evaluation with pySecDec: A Higgs + three gluons example
Authors: Paranjape C P , Heinrich G , Jones S P 
Published: February 2023

Abstract
We present an application of the major new features of pySecDec, a program designed to numerically calculate multi-loop integrals. One important new feature is the ability to integrate weighted sums of integrals in a way which is optimised to reach a given accuracy goal on the sums rather than on the individual integrals. Another feature is the option to perform asymptotic expansions. These new assets of the program represent an important step towards the efficient evaluation of multi-loop amplitudes in a largely automated way. We will illustrate them in a pedagogical example, through the calculation of the one-loop amplitude for Higgs plus jet production in the gluon channel, mediated by a top quark loop. Numerical results in the heavy top limit, compared to their analytic counterparts, are shown as well.
Differentiable Matrix Elements with MadJax
Authors: Heinrich Lukas , Kagan Michael 
Published: February 2023

Abstract
MadJax is a tool for generating and evaluating differentiable matrix elements of high energy scattering processes. As such, it is a step towards a differentiable programming paradigm in high energy physics that facilitates the incorporation of high energy physics domain knowledge, encoded in simulation software, into gradient based learning and optimization pipelines. MadJax comprises two components: (a) a plugin to the general purpose matrix element generator MadGraph that integrates matrix element and phase space sampling code with the JAX differentiable programming framework, and (b) a standalone wrapping code interface for accessing the matrix element code and its gradients, which are computed with automatic differentiation. The MadJax implementation and example applications of simulation based inference and normalizing flow based matrix element modeling, with capabilities enabled uniquely with differentiable matrix elements, are presented.
Particle generation through energy discretization and restrictive planes in GEANT4 simulations for potential applications of cosmic ray muon tomography
Authors: Ilker Topuz A. , Kiisk Madis , Giammanco Andrea 
Published: February 2023

Abstract
In this study, by attempting to resolve the difficulties related to the angular distribution during the particle generation for the muon tomography applications in the GEANT4 simulations, we exhibit an unconventional methodology that is hinged on the direction limitation via the vectorial construction from the generation location to the restriction area rather than using a certain angular distribution or interval. In other words, we favor a momentum direction that is determined by a vector constructed between an initial point randomly chosen on a generative point/plane and a second point arbitrarily selected on a restrictive plane of the same dimensions with the basal cross section of the volume-of-interest (VOI). On account of setting out such a generation scheme, we optimize the particle loss by keeping an angular acceptance that is directly dependent on the VOI geometry as well as the vertical position of the restrictive plane for a tomographic system of a finite size. We demonstrate our strategy for a set of target materials including aluminum, iron, copper, lead, and uranium with a dimension of 40×10×40 cm3 over three restrictive planes of different positions by using a discrete energy spectrum between 0.1 and 8 GeV and we compute the scattering angle, the number of absorption, and the particle loss. Upon our simulation outcomes, we show that the particle generation by means of restrictive planes is an effective strategy that is flexible towards a variety of computational objectives in the GEANT4 simulations.
Recent progress for five-particle two-loop scattering amplitudes with an off-shell leg
Authors: Kryś Jakub 
Published: February 2023

Abstract
We report on the advances in the calculation of the two-loop scattering amplitudes for five-particle processes with one off-shell leg. Focusing on the production of a Higgs boson in association with a bottom quark pair, we outline how the newly developed technology allows us to overcome the computational bottlenecks. In particular, we discuss the use of finite field arithmetic and elucidate a convenient way to evaluate numerically the special functions appearing in the amplitudes.
Speeding up lattice QCD simulation on Arm architectures with multigrid algorithm
Authors: Sun Wei , Bi Yujiang 
Published: February 2023

Abstract
Lattice quantum chromodynamics (lattice QCD) is the non-perturbative definition of the QCD theory from first principle and can be systematically improved. Meanwhile, it is one of the most important high performance computing application in high energy physics. The physics research of lattice QCD benefited enormously from the development of computer hardware and algorithms, and particle physicists can now study strong interaction at physical pion mass, smaller lattice spacing and larger volume. On the other hand, with the emerging of supercomputers and clusters based on Arm architectures, it is necessary to implement the algorithms and conduct the simulations on these machines to maximize the utilization of the limited computing resources. In this paper, we implemented and ported the multigrid (MG) algorithm, the state of the art algorithm to solve the sparse linear Dirac equation Dx = b on the lattice for clover fermion on a cluster with Arm based processors.
Testing the boundaries: Normalizing Flows for higher dimensional data sets
Authors: Reyes-González Humberto , Torre Riccardo 
Published: February 2023

Abstract
Normalizing Flows (NFs) are emerging as a powerful class of generative models, as they not only allow for efficient sampling, but also deliver, by construction, density estimation. They are of great potential usage in High Energy Physics (HEP), where complex high dimensional data and probability distributions are everyday’s meal. However, in order to fully leverage the potential of NFs it is crucial to explore their robustness as data dimensionality increases. Thus, in this contribution, we discuss the performances of some of the most popular types of NFs on the market, on some toy data sets with increasing number of dimensions.
Evaluating the properties of compressed soil earth blocks after the addition of bagasse ash, marble powder and paddy straw
Authors: Ranjan Satish , Sharma Tarun 
Published: February 2023

Abstract
Constructing structures and their establishments with the help of non-toxic and ecological materials that reduce the environmental damages caused in the process and help protect nature can be termed sustainable construction. Red burnt clay bricks are being used for the construction which requires a lot of energy in the process. For the preparation of these bricks, cement is used as a stabilizer and we all are aware that the production of cement releases a lot of energy. Red burnt clay bricks are burnt in kilns which pollutes the environment. Many countries have started using compressed stabilized earth blocks (CSEBs) to overcome these situations. CSBEs are the blocks consisting of clay and one or more stabilizers which are compressed together with the help of a manual press or machines. This study used waste materials like rice straw, marble dust, and bagasse ash as stabilizers. Using waste materials in CSEBs can help us in sustainable development and also will help in reducing the cost of construction. In this study, rice straw is used in the percentages 0.75%, 0.90%, and 1.05%. Marble dust is used in the percentages of 8%, 10%, and 12%. And bagasse ash is used in the percentages of 27%, 32%, and 37%. A total of 27 combinations were selected with these percentages. And for each test, 2 blocks of size 220mm x 100mm x 100mm and beams of size 500mm x 100mm x 100mm were prepared. These blocks were cured by the sprinkling of water for 28 days. Various tests like OMC & MDD, and Flexural Strength were performed in this study.
Pullout behavior of helical soil nails in cohesionless soil: a laboratory investigation
Authors: Hussain Ubaid , Tangri Amanpreet 
Published: February 2023

Abstract
The soil reinforcing method of incorporating helical soil nails is a technique involving the introduction of passive elements into the soil. The combined action of helical bearing and shaft skin friction from helical soil nails gives better reinforcement against failure of the composite soil mass. The current study is aimed to explore the laboratory pullout response of helical soil nails in cohesionless soil (river sand) under varying shaft cross-section (Circular & Square), shaft type (Hollow & Solid), transition in the position of the third helix, and overburden pressure to optimize the most suitable soil nail. In this study, pullout tests are conducted on the soil nails in the laboratory using the physical model setup. The pullout capacity of circular nails is higher than the corresponding square nail. Moreover, a solid shaft nail depicts a higher pullout load capacity than a hollow shaft soil nail. Maximum pullout load is achieved at third helix spacing of about 3.8 Dh and gives a 7.40% increase in pullout load as compared to the reference soil nail. SSCN1. Further, as the overburden pressure is increased, the pullout capacity also increases.
Preparation of biodiesel and experimental investigation of biodiesel blends on diesel engine at varying speed.
Authors: Prasad Anumukonda Vara , Sharma Dugala Navdeep 
Published: February 2023

Abstract
Because the world’s fossil fuel reserves are depleting at an alarming rate as a result of increased consumption, biodiesel is a useful alternative to fossil fuels in many scenarios. Since biodiesel emits fewer harmful emissions, it’s an environmentally friendly fuel. Biodiesel can be produced at a lower cost and can be used without any modifications in the engine. The most acceptable process for biodiesel production is base-catalysed transesterification.
In this present research work we prepared and compared the characteristics of the biodiesel with conventional diesel fuel. Waste fry oil taken form potato chip industry and Jatropha from Jatropha seeds methyl ester-based biodiesel was prepared using transesterification process. The pure bio-diesel was blended with diesel in some proportions making it as B20, B30, B40, B50 blends and tested in a four-stroke, four-cylinder, diesel ignition engine running at five different engine speeds 1600, 1800, 2000, 2200, 2400 respectively.
RETRACTED: Performance Analysis to Produce Biodiesel from Seed
Authors: Sood Devansh , Sharma Dugala Navdeep 
Published: February 2023

Abstract
In recent years, there has been a steady increase in the number of solid wastes because of the increasing human population and urbanisation. Solids include industrial waste, agricultural waste, forest waste and waste bio-products. Bioenergy has produced a total 10% participation of energy of global energy production, energy produced from the source of biomass: plants, animal, and organic waste.
In some seeds like Juliform seed, Watermelon Seed oil is prepared and blended together to produce the biodiesel and to check the performance of the biodiesel. The study also includes examination of physical and chemical properties such as pH value, viscosity, density, flash point, fire point and acid values on the produced biodiesel as well as on the conventional diesel for comparison. The study revealed that the properties of the biodiesel are very close to the conventional diesel.
Evaluation of Seismic Response of Irregular Buildings: A Review
Authors: Tomer Sahil , Bhandari Mohit 
Published: February 2023

Abstract
The modern design and construction of buildings have led to the adoption of irregular shapes buildings which can attract large seismic forces and induce stress concentrations in the building itself. To investigate this fact a large number of research studies have been carried out. This study presents a review summary of seismic performance of irregular buildings considering vertical irregularity subjected to earthquake loadings. The seismic performance can be found by using linear and nonlinear time history analysis. Different types of irregular buildings are analyzed to review the seismic performance of the structure. It was found that the buildings with the soft story having variation in the storey stiffness yield large inter-storey drift values showing more damage as compared to types of building irregularities.
Comparative Effectiveness of Equivalent Static Analysis & Response Spectrum Analysis in Extreme Seismic Zones
Authors: Faiz Milad , Kumar Rajeev 
Published: February 2023

Abstract
Earthquake is one of the horrible natural disasters. With the considerable developments in the constructional science, the experts have been able to find out the factor forces that cause earthquakes the damage and destructions in different types of buildings, including residential and commercial buildings, caused by earthquake are of high importance and need to be considered. The damage caused by earthquakes in multi-story buildings is usually in the weak points of the building, which is caused by Strength and changes in stiffness. this paper deal with two methods of analyze, linear static analysis (Equivalent Static Analysis) and linear dynamic analysis (Response Spectrum Analysis) on three different height structures(5-Storey, 10-Storey, 15-Storey) with regular plan in two various seismic zones (IV, V) as per IS1893-2016 and compared parameters, max story displacement, max drift ratio, base shear, max axial force in column, max bending moment in column and fundamental time period from the effect of two analysis methods, using ETABS software. After the analysis, these conclusions were made:
Effect of equivalent static analysis in both seismic zones IV, V in Max Story Displacement is more than response spectrum analysis, 36% in 15 Storey building, 38% in 10 Storey building and 34% in 5 Storey building. Fundamental Time Period is equal in equivalent static analysis and response spectrum analysis in both seismic zones and with the 5 storey gap between each buildings time period, 9.5% less from 15 storey to 10 storey and 29% less from 10 storey to 5 storey. Effect of equivalent static analysis in both seismic zones at Max Drift Ratio 27%, 33%, 30% in (15,10,5) storeys buildings is more than response spectrum analysis. In general, it can be said that the values coming from the all parameters in equivalent static analysis are to most of the values of response spectrum analysis.
The effective placing of Shear Wall for Seismic Resistance of G+5 Story building on sloping Ground
Authors: Mohammadi M H , kumar P , Rishi V 
Published: February 2023

Abstract
The buildings located on the sloped ground are irregular. Therefore, Prone to hard destruction when acted by earthquake forces. These types of buildings have different stiffness and mass in the horizontal and vertical directions. As result, the centre of rigidity and centre of mass does not coincide on a different floor and cause to suffer high damage due to irregularity during an earthquake. Because it is considered that, the seismic performance of the building in a sloped area is much more different from the plain area. Present study deal with the Earthquake manner of the G+5 story building with a shear wall in a hilly area. The fundamental aims are to; investigate the performance of G+5 story building on the sloped area for different positioning of the shear wall, and to understand the impressiveness of SW on a sloped area. In this paper, G+5 story buildings with and without shear walls resting on the sloped ground are observed. Modelling and analysis are done by considering the response spectrum with the assistance of STAAD Pro and different configurations of a shear wall compared with considering story displacement, maximum bending moment, base shear, and axial forces.
A Review on the Synthesis and Photocatalytic Application of Silver Nano Particles
Authors: Madhu  , Sharma Renu , Bharti Ruchi 
Published: February 2023

Abstract
Recently, the area of nanotechnology has been the most powerful tool for the exploration of nanoparticles in material sciences because of their unique properties (size and shape depending on optical, antimicrobial, and electrical properties). Nanoparticles are usually atoms in size range of 1-100 nm. Developing such strategies for nanoparticle synthesis is a fundamental key that is less environmentally harmful and reliable, and recently it has emerged as one of the most vibrant areas in various sectors. Nanoparticle particles of silver have gained considerable attention as they have low potential toxicity, unique physicochemical properties, bio-functions behavior, anti-inflammatory, antibacterial, antiviral, and antifungal. Much research has been reported on the properties of AgNPs due to their extensive use in various fields, including medical, food, healthcare, consumer, and industrial purposes. Because of the unique physical and chemical properties (optical, electrical, thermal, high electrical conductivity, and biological properties), these NPs are an exciting subject of study. This review article has tried to give an overview of different synthetic procedures using chemical, physical and biological methodologies to synthesize AgNPs. We have also discussed the Photocatalytic applications of AgNPs.