bluuebunny/crossref_metadata_2025 huggingface dataset:
CMOS-based area-and-power-efficient neuron and synapse circuits for time-domain analog spiking neural networks
Authors: Chen Xiangyu , Byambadorj Zolboo , Yajima Takeaki , Inoue Hisashi , Inoue Isao H. , Iizuka Tetsuya
Published: February 2023

Conventional neural structures tend to communicate through analog quantities, such as currents or voltages; however, as CMOS devices shrink and supply voltages decrease, the dynamic range of voltage/current-domain analog circuits becomes narrower, the available margin becomes smaller, and noise immunity decreases. More than that, the use of operational amplifiers (op-amps) and continuous-time or clocked comparators in conventional designs leads to high energy consumption and large chip area, which would be detrimental to building spiking neural networks. In view of this, we propose a neural structure for generating and transmitting time-domain signals, including a neuron module, a synapse module, and two weight modules. The proposed neural structure is driven by a leakage current of MOS transistors and uses an inverter-based comparator to realize a firing function, thus providing higher energy and area efficiency compared to conventional designs. The proposed neural structure is fabricated using a TSMC 65 nm CMOS technology. The proposed neuron and synapse occupy the area of 127 and 231 μm2, respectively, while achieving millisecond time constants. Actual chip measurements show that the proposed structure implements the temporal signal communication function with millisecond time constants, which is a critical step toward hardware reservoir computing for human–computer interaction. Simulation results of the spiking neural network for reservoir computing with the behavioral model of the proposed neural structure demonstrates the learning function.
Relaxation dynamics measure the aggregation propensity of amyloid-β and its mutants
Authors: Dey Priya , Biswas Parbati
Published: February 2023

Atomistic molecular dynamics simulations are employed to investigate the global and segmental relaxation dynamics of the amyloid-β protein and its causative and protective mutants. Amyloid-β exhibits significant global/local dynamics that span a broad range of length and time scales due to its intrinsically disordered nature. The relaxation dynamics of the amyloid-β protein and its mutants is quantitatively correlated with its experimentally measured aggregation propensity. The protective mutant has slower relaxation dynamics, whereas the causative mutants exhibit faster global dynamics compared with that of the wild-type amyloid-β. The local dynamics of the amyloid-β protein or its mutants is governed by a complex interplay of the charge, hydrophobicity, and change in the molecular mass of the mutated residue.
Crossover from strong to weak exciton confinement in thickness-controlled epitaxial PbI2 thin films
Authors: Nakamura Masao , Namba Ryuichi , Yasunami Takahiro , Ogawa Naoki , Tokura Yoshinori , Kawasaki Masashi
Published: February 2023

Spatially confined excitons undergo two distinct quantization effects depending on the confinement length, the enhanced binding energy under strong confinement, and the center-of-mass quantization under weak one. However, the transition between them has not been experimentally identified in two-dimensional (2D) materials due to the lack of thin films satisfying large-scale uniformity and atomic-level flatness in a wide thickness range. Here, we reveal the crossover in high-quality epitaxial thin films of a 2D semiconductor PbI2 grown by molecular beam epitaxy. The absorption spectra exhibit oscillatory structures manifesting the exciton center-of-mass quantization, and the quantization energies show an additional blue shift associated with the strong confinement effect below five-layer thickness (35 Å). The precise control of exciton quantum states will lead to the further development of optoelectronic functionalities of 2D materials.
Compressibility effects on turbulence production
Authors: Viganò Davide , Maddalena Luca
Published: February 2023

Turbulence in compressible flows plays a major role in a variety of applications such as air/fuel mixing strategies for scramjet combustors. Therefore, the ability of controlling its production is of particular interest. However, compressible turbulence is more challenging than its incompressible counterpart due to the fact that thermodynamic quantities also fluctuate. In particular, the compressible turbulent kinetic energy production is a function of both velocities and density fluctuations. The so-called Morkovin's hypothesis has been often used in the literature to express the density fluctuations as a function of the velocity ones and the local Mach number. In this work, we discuss the validity of this hypothesis, and we use its expression to reformulate the turbulence production as a function of velocity only. The resulting expression shows that the planar component of turbulence production is substantially unaffected by compressibility effects. This result validates a previous work aimed at the sustainment of turbulence production using streamwise vortices. On the other hand, the turbulence production terms aligned with the convective velocity are affected by compressibility, even at relatively low Mach numbers.
Composite phosphorylated-modified rice straw prepared for highly effective immobilisation of cadmium in agriculture contaminated soil
Authors: Li Xiaohui , Ai Xianbin , Wang Xiyang , Li Liang , Xin Zaijun , Sun Xiaoyan
Published: February 2023

Environmental context Rice straw is generated in vast quantities each year, but although the cellulose structure is stable, only 20% is used effectively. The structure of rice straw gives it high porosity and active functional groups, which means it easily adsorbs metals, but few studies have applied it to metal-contaminated soil. This study showed that composite phosphorylated-rice straw can be highly effective for the immobilization of cadmium in contaminated soils. Rationale Rice straw is generated in vast quantities each year, but the effective utilisation rate is low. In order to develop full utilisation of rice straw and seek high-efficiency immobilising agents for cadmium contaminated soil, the objectives of this paper was to prepare a new modified rice straw material. Methodology Composite phosphorylated rice straw (CPRS) and phosphorylated rice straw (PRS) were synthesised, the apparent morphology and functional groups of CPRS and PRS were characterised by SEM-EDS and FT-IR, and the remediation ability of CPRS and PRS on cadmium contaminated soil were studied by pot experiment. Results The results showed that the order of maximum adsorption capacity (Qmax) for Cd2+ was CPRS > PRS > RS, Qmax of CPRS for Cd2+ was 53.57 g kg−1. CPRS had a richer porosity, evidenced a PO43−EN22041_IE1.gif group stretching vibration and had calcium salt well-dispersed on its surface. The application of CPRS to Cd contaminated soil significantly improved the plant biomass (fresh biomass increased 66.97%, over control) and decreased the Chinese cabbage uptake of Cd (decreased 67.16%, over control). The chemical stability of cadmium in soil was enhanced by applying CPRS due to a decrease in the exchangeable Cd in soil in proportion (decreased 95.38–99.10%) to the increasing fractions of Cd bound to Fe/Mn oxides (increased 141.15–158.90%), and residual Cd (increased 4.76–6.99 times) following the application of CPRS as compared to control treatments. Discussion CPRS had an excellent immobilisation ability for cadmium contaminated soil, which was related to improved soil pH and cation exchange capacity. It possibly immobilises Cd in the soil via surface complexation through Cd–O groups at the surface of CPRS. Modified rice straw materials could be highly recommended as an efficient stabiliser to immobilise Cd in polluted agricultural soils.
ALK fusion NSCLC oncogenes promote survival and inhibit NK cell responses via
SERPINB4
expression
Authors: Chuang Tzu-Po , Lai Wei-Yun , Gabre Jonatan L. , Lind Dan E. , Umapathy Ganesh , Bokhari Abdulmalik A. , Bergman Bengt , Kristenson Linnea , Thorén Fredrik B. , Le Anh , Doebele Robert C. , Van den Eynden Jimmy , Palmer Ruth H. , Hallberg Bengt
Published: February 2023

Anaplastic lymphoma kinase (ALK) fusion variants in Non-Small Cell Lung Cancer (NSCLC) consist of numerous dimerizing fusion partners. Retrospective investigations suggest that treatment benefit in response to ALK tyrosine kinase inhibitors (TKIs) differs dependent on the fusion variant present in the patient tumor. Therefore, understanding the oncogenic signaling networks driven by different ALK fusion variants is important. To do this, we developed controlled inducible cell models expressing either Echinoderm Microtubule Associated Protein Like 4 (EML4)-ALK-V1, EML4-ALK-V3, Kinesin Family Member 5B (KIF5B)-ALK, or TRK-fused gene (TFG)-ALK and investigated their transcriptomic and proteomic responses to ALK activity modulation together with patient-derived ALK-positive NSCLC cell lines. This allowed identification of both common and isoform-specific responses downstream of these four ALK fusions. An inflammatory signature that included upregulation of the Serpin B4 serine protease inhibitor was observed in both ALK fusion inducible and patient-derived cells. We show that Signal transducer and activator of transcription 3 (STAT3), Nuclear Factor Kappa B (NF-κB) and Activator protein 1 (AP1) are major transcriptional regulators of
SERPINB4
downstream of ALK fusions. Upregulation of
SERPINB4
promotes survival and inhibits natural killer cell-mediated cytotoxicity, which has potential for therapeutic impact targeting the immune response together with ALK TKIs in NSCLC.
The birth and evolution of solvated electrons in the water
Authors: Novelli Fabio , Chen Kaixuan , Buchmann Adrian , Ockelmann Thorsten , Hoberg Claudius , Head-Gordon Teresa , Havenith Martina
Published: February 2023

The photo-induced radiolysis of water is an elementary reaction in biology and chemistry, forming solvated electrons, OH radicals, and hydronium cations on fast time scales. Here, we use an optical-pump terahertz-probe spectroscopy setup to trigger the photoionization of water molecules with optical laser pulses at ~400 nm and then time-resolve the transient solvent response with broadband terahertz (THz) fields with a ~90 fs time resolution. We observe three distinct spectral responses. The first is a positive broadband mode that can be attributed to an initial diffuse, delocalized electron with a radius of (22 ± 1) Å, which is short lived (<200 fs) because the absorption is blue-shifting outside of the THz range. The second emerging spectroscopic signature with a lifetime of about 150 ps is attributed to an intermolecular mode associated with a mass rearrangement of solvent molecules due to charge separation of radicals and hydronium cations. After 0.2 ps, we observe a long-lasting THz signature with depleted intensity at 110 cm
−1
that is well reproduced by ab initio molecular dynamics. We interpret this negative band at 110 cm
−1
as the solvent cage characterized by a weakening of the hydrogen bond network in the first and second hydration shells of the cavity occupied by the localized electron.
The smectic Z
A
phase: Antiferroelectric smectic order as a prelude to the ferroelectric nematic
Authors: Chen Xi , Martinez Vikina , Korblova Eva , Freychet Guillaume , Zhernenkov Mikhail , Glaser Matthew A. , Wang Cheng , Zhu Chenhui , Radzihovsky Leo , Maclennan Joseph E. , Walba David M. , Clark Noel A.
Published: February 2023

We have structurally characterized the liquid crystal (LC) phase that can appear as an intermediate state when a dielectric nematic, having polar disorder of its molecular dipoles, transitions to the almost perfectly polar-ordered ferroelectric nematic. This intermediate phase, which fills a 100-y-old void in the taxonomy of smectic LCs and which we term the “smectic Z
A
,” is antiferroelectric, with the nematic director and polarization oriented parallel to smectic layer planes, and the polarization alternating in sign from layer to layer with a 180 Å period. A Landau free energy, originally derived from the Ising model of ferromagnetic ordering of spins in the presence of dipole–dipole interactions, and applied to model incommensurate antiferroelectricity in crystals, describes the key features of the nematic–SmZ
A
–ferroelectric nematic phase sequence.
Effect of initial microstructures on microstructures and properties of extruded AZ31 alloy
Authors: Zhu Huiwen , Yu Baoyi , Cai Jingkai , Bian Jiancong , Zheng Li
Published: February 2023

The raw materials for extruded preparing magnesium alloy tubes were electromagnetic stirring (EMS) AZ31 magnesium alloy billets and conventional casting (CC) AZ31 magnesium alloy billets. According to the findings, the mechanical properties of the EMS extrusion tubes were far superior to those of the CC extrusion tubes. The key explanation was that the samples of EMS billet had variable initial grain sizes and twin boundaries, which provide additional nucleation sites for DRX nucleation during the extrusion process. With the increase of extrusion temperature and extrusion ratio, the elongation of the tube is further improved. During the extrusion process, the recrystallization mechanism changed from continuous dynamic recrystallization (CDRX) to discontinuous dynamic recrystallization (DDRX).
Scale-invariance at the core of quantum black holes
Authors: Borissova Johanna N , Held Aaron , Afshordi Niayesh
Published: February 2023

We study spherically-symmetric solutions to a modified Einstein–Hilbert action with renormalization group (RG) scale-dependent couplings, inspired by Weinberg’s Asymptotic Safety scenario for quantum gravity. The RG scale is identified with the Tolman temperature for an isolated gravitational system in thermal equilibrium with Hawking radiation. As a result, the point of infinite local temperature is shifted from the classical black-hole horizon to the origin and coincides with a timelike curvature singularity. Close to the origin, the spacetime is determined by the scale-dependence of the cosmological constant in the vicinity of the Reuter fixed point: the free components of the metric can be derived analytically and are characterized by a radial power law with exponentα=3−1. Away from the fixed point, solutions for different masses are studied numerically and smoothly interpolate between the Schwarzschild exterior and the scale-invariant interior. Whereas the exterior of objects with astrophysical mass is described well by vacuum general relativity, deviations become significant at a Planck distance away from the classical horizon and could lead to observational signatures. We further highlight potential caveats in this intriguing result with regard to our choice of scale-identification and identify future avenues to better understand quantum black holes in relation to the key feature of scale-invariance.
Magnetic solitons due to interfacial chiral interactions
Authors: Paula Mellado , Tapia Ignacio
Published: February 2023

We study solitons in a zig-zag lattice of magnetic dipoles. The lattice comprises two sublattices of parallel chains with magnetic dipoles at their vertices. Due to orthogonal easy planes of rotation for dipoles belonging to different sublattices, the total dipolar energy of this system is separable into a sum of symmetric and chiral long-ranged interactions between the magnets where the last takes the form of Dzyaloshinskii–Moriya (DM) coupling. For a specific range of values of the offset between sublattices, the dipoles realize an equilibrium magnetic state in the lattice plane, consisting of one chain settled in an antiferromagnetic (AF) parallel configuration and the other in a collinear ferromagnetic fashion. If the offset grows beyond this value, the internal DM field stabilizes two Bloch domain walls at the edges of the AF chain. The dynamics of these solitons is studied by deriving the long-wavelength lagrangian density for the easy axis antiferromagnet. We find that the chiral couplings between sublattices give rise to an effective magnetic field that stabilizes the solitons in the antiferromagnet. When the chains displace respect to each other, an emergent Lorentz force accelerates the domain walls along the lattice.
Macrotexture deterioration for micromilled tunnel concrete pavement using 3D laser data
Authors: Yang Xinyi , Lu Bin , Jing Qingsong , Li Yang , Zhou Yukun
Published: February 2023

To ensure driving safety and cost effectively preserve pavements, unlike the traditional grooving, cutting joints, highway tunnels used micromilling resurfacing method to improve the skid resistance of concrete pavement. The sensor measured texture depth (SMTD) has been established for quantitatively evaluating micromilled surface quality. This paper explores the possibility of using three-dimensional line laser imaging technology to obtain the ‘full lane’ elevation data of the pavement, then through the calculation of the index SMTD, construct a road surface spatial and temporal deterioration model, and provide quality control covering the whole lane, and identify the problem areas. The results show that the road wear condition gradually worsens with the increase in opening time, after 24 months, the proportion of the good level (>0.55 mm) of the three cells is 70.5%, 75.1%, and 70.2%. Analysis of the test data for three cells revealed that the tunnel pavement shows canalization in wear. The most severely abraded section is offset by 200–300 mm toward the roadway median compared to the theoretical vehicle wheel track zone. Subsequent studies can expand the experimental conditions and consider more influencing factors to study further the texture deterioration of the micromilled pavement.
Development of an abdominal dose accumulation tool and assessments of accumulated dose in gastrointestinal organs
Authors: Zhang Yuhang , Balter James , Dow Janell , Cao Yue , Lawrence Theodore S , Kashani Rojano
Published: February 2023

Objective. Online adaptive radiotherapy has demonstrated improved dose conformality in response to inter-fraction geometric variations in the abdomen. The dosimetric impact of intra-fractional variations in anatomic configuration resulting from breathing, gastric contraction and slow configuration motion, however, have been largely ignored, leading to differences between delivered and planned. To investigate the impact of intra-fractional abdominal motions on delivered dose, anatomical deformations due to these three motion modes were extracted from dynamic MRI data using a previously developed hierarchical motion modeling methodology. Approach. Motion magnitudes were extracted from deformation fields between a reference state and all other motion states of the patient. Delivered dose estimates to various gastrointestinal organs (stomach, duodenum, small bowel and colon) were calculated on each motion state of the patient and accumulated to estimate the delivered dose to each organ for the entire treatment fraction. Main results. Across a sample of 10 patients, maximal motions of 33.6, 33.4, 47.6 and 49.2 mm were observed over 20 min for the stomach, duodenum, small bowel and colon respectively. Dose accumulation results showed that motions could lead to average increases of 2.0, 2.1, 1.1, 0.7 Gy to the maximum dose to 0.5cc (D0.5cc) and 3.0, 2.5, 1.3, 0.9 Gy to the maximum dose to 0.1cc (D0.1cc) for these organs at risk. From the 40 dose accumulations performed (10 for each organ at risk), 27 showed increases of modeled delivered dose compared to planned doses, 4 of which exceeded planned dose constraints. Significance. The use of intra-fraction motion measurements to accumulate delivered doses is feasible, and supports retrospective estimation of dose delivery to improve estimates of delivered doses, and further guide strategies for both plan adaptation as well as advances in intra-fraction motion management.
Applying the column generation method to the intensity modulated high dose rate brachytherapy inverse planning problem
Authors: Antaki Majd , Renaud Marc-André , Morcos Marc , Seuntjens Jan , Enger Shirin A
Published: February 2023

Objective. Intensity modulated high dose rate brachytherapy (IMBT) is a rapidly developing application of brachytherapy where anisotropic dose distributions can be produced at each source dwell position. This technique is made possible by placing rotating metallic shields inside brachytherapy needles or catheters. By dynamically directing the radiation towards the tumours and away from the healthy tissues, a more conformal dose distribution can be obtained. The resulting treatment planning involves optimizing dwell position and shield angle (DPSA). The aim of this study was to investigate the column generation method for IMBT treatment plan optimization. Approach. A column generation optimization algorithm was developed to optimize the dwell times and shield angles. A retrospective study was performed on 10 prostate cases using RapidBrachyMCTPS. At every iteration, the plan was optimized with the chosen DPSA which would best improve the cost function that was added to the plan. The optimization process was stopped when the remaining DPSAs would not add value to the plan to limit the plan complexity. Main results. The average number of DPSAs and voxels were 2270 and 7997, respectively. The column generation approach yielded near-optimal treatment plans by using only 11% of available DPSAs on average in ten prostate cases. The coverage and organs at risk constraints passed in all ten cases. Significance. The column generation method produced high-quality deliverable prostate IMBT plans. The treatment plan quality reached a plateau, where adding more DPSAs had a minimal effect on dose volume histogram parameters. The iterative nature of the column generation method allows early termination of the treatment plan creation process as soon as the dosimetric indices from dose volume histogram satisfy the clinical requirements or if their values stabilize.
Coplanar superconducting resonators with nonlinear kinetic inductance bridge
Authors: Kalacheva Daria , Fedorov Gleb , Khrapach Ivan , Astafiev Oleg
Published: February 2023

We present a model and experimental realization of coplanar superconducting resonators terminated by a shunting kinetic inductance bridge made of ultra-thin Al films. The fabrication process that we propose allows us to create very homogeneous films, which makes them suitable for many applications in quantum devices. Due to the specific properties of the films, the resonators exhibit a Duffing oscillator behavior resulting in bifurcations and interactions between different power sources, which was previously observed in similar systems. Moreover, since the nonlinearity of such a system is concentrated at the bridge, while the wave propagates in a linear environment, it is possible to propose a simple model that accurately describes its behavior. We show that, when resonators are operated within a notch-port architecture, our model has a closed-form solution for the transmission coefficient and allows one to accurately extract parameters of the system, including the kinetic inductance of the bridge and its depairing current. Potential applications of such systems include tunable resonators, photon detectors, bifurcation and parametric amplifiers, as well as a measurement device for studying the properties of thin films.
Observation of an anomalous Hall effect in single-crystal Mn3Pt
Authors: Zuniga-Cespedes Belén E , Manna Kaustuv , Noad Hilary M L , Yang Po-Ya , Nicklas Michael , Felser Claudia , Mackenzie Andrew P , Hicks Clifford W
Published: February 2023

The Mn3X family of compounds was the first in which a large anomalous Hall effect (AHE) was predicted to arise from a purely antiferromagnetic structure, due to the Berry curvature in momentum space. Nearly simultaneously with this prediction, a large AHE was observed experimentally in one of the hexagonal members of this family, Mn3Sn. Aligning antiferromagnetic domains, a necessary step for observation of the AHE, is more challenging for the cubic members of the Mn3X family, due to a combination of smaller spontaneous ferromagnetic moments and much stronger magnetic anisotropy. Here, we use a combination of uniaxial stress and applied magnetic field to align domains of bulk single-crystal Mn3Pt, and demonstrate for the first time a substantial AHE in a bulk sample of a cubic member of the Mn3X family. The AHE remains locked in with essentially no quantitative variation when the stress is ramped back to zero, which shows that it is not a consequence of any stress-induced ferromagnetic moment.
One μ to rule them all: CMB spectral distortions can probe domain walls, cosmic strings and low scale phase transitions
Authors: Ramberg Nicklas , Ratzinger Wolfram , Schwaller Pedro
Published: February 2023

We present a new probe of purely gravitationally coupled sectors with large
anisotropies. These anisotropies are damped via gravitational interactions with the baryon-photon
fluid, which is heated up in the process. The injected heat causes measurable distortions of the
cosmic microwave background spectrum. We give analytic estimates for the size of the distortions
and outline how to calculate them from first principles. These methods are applied to anisotropies
in the form of a domain wall/cosmic string network or caused by a first order phase transition or
scalar field dynamics. We find that this method can potentially probe large regions of previously
unconstrained parameter space and is very much complementary to up-coming searches of
gravitational waves caused by such dark sectors.
Comparison of MHD stability properties between QH-mode and ELMy H-mode plasmas by considering plasma rotation and ion diamagnetic drift effects
Authors: Aiba N. , Chen X. , Osborne T.H. , Burrell K.H.
Published: February 2023

Magnetohydrodynamic (MHD) stability at tokamak edge pedestal in a quiescent H-mode (QH-mode) and type-I ELMy H-mode plasmas in DIII-D experiment was analyzed by considering plasma rotation and ion diamagnetic drift effects. QH-mode plasma is marginally stable to kink/peeling mode (K/PM), but ELMy H-mode one is almost unstable to peeling-ballooning mode (PBM). It was identified that there are three physics features responsible for the difference in the MHD stability properties between QH-mode plasma and ELMy H-mode one. These are the distance of pedestal foot from the last closed flux surface (LCFS), the amount of the ion diamagnetic drift frequency at pedestal, and impact of coupled rotation and ion diamagnetic drift effects. These features were confirmed through the numerical experiments that the stability properties of the QH-mode plasma can be changed to that of the ELMy H-mode one by shifting the plasma profiles inward in the radial direction and halving the ion diamagnetic drift frequency. The reasons of the change in the stability properties are thought as that K/PM is stabilized due to the inward shift of the bootstrap current profile, and PBM is destabilized due to the reduction of the coupled rotation and ion diamagnetic drift stabilizing effect. Importance of these features was validated through numerical experiments with experimental data of other QH-mode plasmas in DIII-D. All the results show that MHD stability properties of QH-mode plasma can be obtained in case that pedestal foot is close to LCFS, ion diamagnetic drift frequency is large due to high ion temperature, and strong rotation shear exists near pedestal.
Generators and the (Accelerated) Future
Authors: Isaacson J
Published: February 2023

With the High Luminosity LHC coming online in the near future, event generators will need to provide very large event samples to match the experimental precision. Currently, the estimated cost to generate these events exceeds the computing budget of the LHC experiments. To address these issues, the computing efficiency of event generators need to be improved. Many different approaches are being taken to achieve this goal. I will cover the ongoing work on implementing event generators on the GPUs, machine learning the matrix element, machine learning the phase space, and minimizing the number of negative weight events.
C++ Code Generation for Fast Inference of Deep Learning Models in ROOT/TMVA
Authors: An Sitong , Moneta Lorenzo , Sengupta Sanjiban , Hamdan Ahmat , Sossai Federico , Saxena Aaradhya
Published: February 2023

We report the latest development in ROOT/TMVA, a new tool that takes trained ONNX deep learning models and emits C++ code that can be easily included and invoked for fast inference of the model, with minimal dependency. An introduction to SOFIE (System for Optimized Fast Inference code Emit) is presented, with examples of interface and generated code. We discuss the latest expanded support of a variety of neural network operators, including convolutional and recurrent layers, as well as the integration with RDataFrame. We demonstrate the latest performance of this framework with a set of benchmarks.
Demonstration of FPGA Acceleration of Monte Carlo Simulation
Authors: Barbone M. , Howard A. , Tapper A. , Chen D. , Novak M. , Luk W.
Published: February 2023

We present results from a stand-alone simulation of electron single Coulomb scattering as implemented completely on an Field Programmable Gate Array (FPGA) architecture and compared with an identical simulation on a standard CPU. FPGA architectures offer unprecedented speed-up capability for Monte Carlo simulations, however with the caveats of lengthy development cycles and resource limitation, particularly in terms of on-chip memory and DSP blocks. As a proof of principle of acceleration on an FPGA, we chose a single scattering process of electrons in water at an energy of 6 MeV. The initial code-base was implemented in C++ and optimised for CPU processing. To measure the potential performance gains of FPGAs compared to modern multi-core CPUs we computed 100M histories of a 6 MeV electron interacting in water. Without performing any hardware-specific optimisation, the results show that the FPGA implementation is over 110 times faster than an optimised parallel implementation running on 12 CPU-cores, and over 270 times faster than a sequential single-core CPU implementation. The results on both architectures were statistically equivalent. The successful implementation and acceleration results are very encouraging for the future exploitation of more sophisticated Monte Carlo simulation on FPGAs for High Energy Physics applications.
Evaluating Awkward Arrays, uproot, and coffea as a query platform for High Energy Physics Data
Authors: Gray L. , Smith N.
Published: February 2023

Query languages for High Energy Physics (HEP) are an ever present topic within the field. A query language that can efficiently represent the nested data structures that encode the statistical and physical meaning of HEP data will help analysts by ensuring their code is more clear and pertinent. As the result of a multi-year effort to develop an in-memory columnar representation of high energy physics data, the NumPy, Awkward Array, and uproot Python packages present a mature and efficient interface to HEP data. Atop that base, the coffea package adds functionality to launch queries at scale, manage and apply experiment-specific transformations to data, and present a rich object-oriented columnar data representation to the analyst. Recently, a set of Analysis Description Language (ADL) benchmarks has been established to compare HEP queries in multiple languages and frameworks. In this paper we present these benchmark queries implemented within the coffea framework and discuss their readability and performance characteristics. We find that the columnar queries perform as well or better than the implementations given in previous studies.
GPU acceleration of the ATLAS calorimeter clustering algorithm
Authors: Fernandes Nuno
Published: February 2023

Given the upcoming High-Luminosity LHC Upgrade, the performance requirements for the trigger systems associated with the LHC experiments will increase due to the larger volume of data to be processed. One of the possibilities that the ATLAS Collaboration is evaluating for upgrading the software-based portion of its trigger system is the use of Graphical Processing Units as hardware accelerators. The present work focuses on the GPU acceleration of the Topological Clustering algorithm, which is used to reconstruct calorimeter showers by grouping cells according to their signal-to-noise ratio. A more GPU parallelizable version of the Topological Clustering, called Topo-Automaton Clustering, was implemented within AthenaMT, the software framework of the ATLAS trigger, and its results were compared to those of the standard CPU algorithm to ensure physical validity is maintained. Time measurements suggest an average improvement of the event processing time by a factor between 3.5 and 5.5 (depending on the kind of the event), though less than 20% of that time corresponds to the algorithm itself, suggesting that the main bottleneck lies in data transfers and conversions.
Graph-based algorithm for the understanding of failures in the ATLAS infrastructure
Authors: Uribe Gustavo A , Tortajada Ignacio Asensi , Solans Sánchez Carlos , Rummler André , Oyulmaz Kaan Yüksel , Denizli Haluk
Published: February 2023

The ATLAS Technical Coordination Expert System is a knowledge-based application which describes and simulates the ATLAS experiment based on its components and their relationships with differing levels of granularity but with an emphasis on general infrastructure. It facilitates the sharing of knowledge and improves the communication among experts with different backgrounds and domains of expertise. The developed software has become essential for the planning of interventions as it gives easily insight into their consequences. Furthermore, it has also proven to be useful for exploring the most effective ways to improve the ATLAS operation and reliability by identifying points of failure with significant impact. The underlying database describes more than 13,000 elements with 89,000 relationships among them. It combines information from diverse domains such as detector control and safety systems, gas and water supplies, cooling, ventilation, cryogenics, and electricity distribution. As the most recent addition, a tool to identify the most probable cause of a failure state has been developed. This paper discusses the graph-based algorithm currently implemented by that tool and shows its behaviour based on the parameters entered by the user. An example in form of a real failure event is given which demonstrates the potential of the Expert System for understanding major failures faster in urgent situations.
Key4hep Software Stack for Detector Studies
Authors: Fang Wenxing , Declara Placido Fernandez , Gaede Frank-Dieter , Ganis Gerardo , Hegner Benedikt , Helsens Clement , Huang Xingtao , Hyun Ko Sang , Madlener Thomas , Li Teng , Li Weidong , Lin Tao , Sailer Andre , Stapf Birgit Sylvia , Volkl Valentin , Wang Joseph , Zou Jiaheng
Published: February 2023

Detector optimisation and physics performance studies are an integral part of the development of future collider experiments. The Key4hep project aims to design a common set of software tools for future, or even present, High Energy Physics projects. Based on the iLCSoft and FCCSW frameworks an integrated solution for detector simulation, reconstruction and analyses is being developed. This presentation will give a short overview of the major ingredients of the Key4hep turnkey software; the common event datamodel – EDM4hep, the Gaudi based event processing framework, some dedicated packages developed on top of these, and the use of the Spack package manager, which enables installations on a variety of platforms. A first example highlights the synergies that were already achieved by the collaboration of the different collider communities (CEPC, CLIC, FCC, ILC). It shows the seamless integration of fast simulation with Delphes and the LCFIplus vertexing processor from iLCSoft. This combination is possible due to EDM4hep, the processor wrapper (k4MarlinWrapper), and the k4SimDelphes framework integration in Key4hep. As a second example, the multi-threaded execution of the iLCSoft processors in the Gaudi framework making use of the k4MarlinWrapper will be showcased. The third example will demonstrate the execution of a multi-threaded simulation of a drift chamber in the CEPC experiment. The chosen application will take information of primary ionizations generated by an incident charged particle as input and will create the waveform as the final output, which represents the signal collected by the chamber’s signal wire. The simulation algorithm is based on a neural network model which can be used to simulate the effects from the ionization electron’s drift and avalanches. Using these examples we review some of the challenges and issues that we encountered as well as how they were addressed in the end. We close with a brief discussion of the next steps for the Key4hep project.
Offline Software Framework for the Super Tau Charm Facility
Authors: Huang W. H. , Li T. , Li Q. Y. , Li H. , Liu D. , Huang X. T.
Published: February 2023

The Super Tau Charm Facility (STCF) is a high-luminosity electron-positron collider proposed to study the tau and charm physics, precisely test Standard Model (SM) and hunt for new physics beyond SM. The Offline Software of Super Tau ChARm Facility (OSCAR) is designed and developed based on SNiPER for the whole offline data processing, including detector simulation, calibration, reconstruction as well as physics analysis. Several state-of-art software and tools in the HEP community are adopted, such as the Detector Description Toolkit for High Energy Physics (DD4hep) for the consistent detector description, the plain-old-data I/O (podio) for the efficient implementation of event data model (EDM), etc. This paper focuses on the design and implementation of OSCAR, particularly the way to integrate Geant4, DD4hep and podio into SNiPER to provide the unified computing environment and platform for detector simulation, reconstruction and visualization. Now OSCAR is used to facilitate the design of STCF detectors, conduct detector performance study as well as physics potential study. OSCAR also provides a potential solution for other light-weighted HEP experiments.
Offloading electromagnetic shower transport to GPUs
Authors: Amadio G , Apostolakis J , Buncic P , Cosmo G , Dosaru D , Gheata A , Hageboeck S , Hahnfeld J , Hodgkinson M , Morgan B , Novak M , Petre A A , Pokorski W , Ribon A , Stewart G A , Vila P M
Published: February 2023

Making general particle transport simulation for high-energy physics (HEP) single-instruction-multiple-thread (SIMT) friendly, to take advantage of accelerator hardware, is an important alternative for boosting the throughput of simulation applications. To date, this challenge is not yet resolved, due to difficulties in mapping the complexity of Geant4 components and workflow to the massive parallelism features exposed by graphics processing units (GPU). The AdePT project is one of the R&D initiatives tackling this limitation and exploring GPUs as potential accelerators for offloading some part of the CPU simulation workload. Our main target is to implement a complete electromagnetic shower demonstrator working on the GPU. The project is the first to create a full prototype of a realistic electron, positron, and gamma electromagnetic shower simulation on GPU, implemented as either a standalone application or as an extension of the standard Geant4 CPU workflow. Our prototype currently provides a platform to explore many optimisations and different approaches. We present the most recent results and initial conclusions of our work, using both a standalone GPU performance analysis and a first implementation of a hybrid workflow based on Geant4 on the CPU and AdePT on the GPU.
Predicting ALICE Grid throughput using recurrent neural networks
Authors: Popa Mircea , Grigoras Costin , Vallecorsa Sofia
Published: February 2023

The Worldwide LHC Computing Grid (WLCG) is the infrastructure enabling the storage and processing of the large amount of data generated by the LHC experiments, and in particular the ALICE experiment. With the foreseen increase in the computing requirements of the future High Luminosity LHC experiments, a data placement strategy which increases the efficiency of the WLCG computing infrastructure becomes extremely relevant for the scientific success of the LHC scientific programme. Currently, the data placement at the ALICE Grid computing sites is determined by heuristic algorithms. Optimisation of the data storage could yield substantial benefits in terms of efficiency and time-to-result. This has however proven to be arduous due to the complexity of the problem. In this work we propose a modelisation of the behaviour of the system via principal component analysis, time series analysis and deep learning, starting from the detailed data collected by the MonALISA monitoring system. We show that it is possible to analyse and model the throughput of the ALICE Grid to a level that has not been possible before, comparing the performance of different deep learning architectures based on recurrent neural networks. Analyzing about six weeks of activity, the Grid I/O throughput trend is successfully predicted with a mean relative error of 4%, while the prediction of the throughput itself performs at 5%.
The unseen: revealing the blind production procedure and experience for NP data
Authors: Van Buren G , Lauret J
Published: February 2023

A unique experiment was conducted by the STAR Collaboration in 2018 to investigate differences between collisions of nuclear isobars, a potential key to unraveling one of the physics mysteries in our field: why the universe is made predominantly of matter. Enhancing the credibility of findings was deemed to hinge on blinding analyzers from knowing which dataset they were examining, necessitating efforts by the data production team to investigate and implement new (in our field) blinding practices. With nearly two decades of established machinery intended to provide open data and metadata access in STAR, the breadth of details to consider for a successful blinding process was substantial.

In this paper, we will review the experience of the first-ever species-blind data production in high energy collider physics. Considerations of what needed blinding, how to blind it, and from whom, will be discussed. Practical impositions on the selection of data to produce and how to produce it will also be highlighted as tell-tales can arise even where there were operational efforts to avoid them. With the appropriate blinding achieved, analyzers and reviewers have been empowered to focus on the physics of interest.
Ensemble Models for Calorimeter Simulations
Authors: Jaruskova K , Vallecorsa S
Published: February 2023

Foreseen increasing demand for simulations of particle transport through detectors in High Energy Physics motivated the search for faster alternatives to Monte Carlo-based simulations. Deep learning approaches provide promising results in terms of speed up and accuracy, among which generative adversarial networks (GANs) appear to be particularly successful in reproducing realistic detector data. However, the GANs tend to suffer from different issues such as not reproducing the full variability of the training data, missing modes problem, and unstable convergence. Various ensemble techniques applied to image generation proved that these issues can be moderated either by deploying multiple generators or multiple discriminators. This work follows a development of a GAN with two-dimensional convolutions that reproduces 3D images of an electromagnetic calorimeter. We build on top of this model and construct an ensemble of generators. With each new generator, the ensemble shows better agreement with the Monte Carlo images in terms of shower shapes and the sampling fraction.
Explainability of High Energy Physics events classification using SHAP
Authors: Pezoa R , Salinas L , Torres C
Published: February 2023

Complex machine learning models have been fundamental for achieving accurate results regarding events classification in High Energy Physics (HEP). However, these complex models or black-box systems lack transparency and interpretability. In this work, we use the SHapley Additive exPlanations (SHAP) method for explaining the output of two event machine learning classifiers, based on eXtreme Gradient Boost (XGBoost) and deep neural networks (DNN). We compute SHAP values to interpret the results and analyze the importance of individual features, and the experiments show that SHAP method has high potential for understanding complex machine learning model in the context of high energy physics.
The Fast Simulation Chain in The ATLAS Experiment
Authors: Aitbenchikh Brahim
Published: February 2023

The physics program in the ATLAS experiment at the Large Hadron Collider has achieved high-quality and competitive physics results since its inception, based on large and accurate datasets of simulated Monte Carlo events. Generating these billions of Monte Carlo using the Geant4 framework requires significant computing resources. As such the ATLAS CPU is limited and taking into account the expected increase of the average number of proton-proton collisions during the high luminosity LHC phase, a very fast detector simulation is critical when high accuracy is not needed. In order to solve this problem and to meet the challenge of simulated sample statistics requirements, fast alternatives approaches have been developed by ATLAS to replace the algorithms currently used in the standard MC production chain. This document provides a description of the Fast simulation chain tools and also presents the latest physics performance studies: Fast tracking detector simulation, Fast digitization and Pile-up simulation.
Generative models uncertainty estimation
Authors: Anderlini L , Chimpoesh C , Kazeev N , Shishigina A
Published: February 2023

In recent years fully-parametric fast simulation methods based on generative models have been proposed for a variety of high-energy physics detectors. By their nature, the quality of data-driven models degrades in the regions of the phase space where the data are sparse. Since machine-learning models are hard to analyse from the physical principles, the commonly used testing procedures are performed in a data-driven way and can’t be reliably used in such regions. In our work we propose three methods to estimate the uncertainty of generative models inside and outside of the training phase space region, along with data-driven calibration techniques. A test of the proposed methods on the LHCb RICH fast simulation is also presented.