Article
Computer Science, Artificial Intelligence
Wei Fang, Zhenhao Zhu, Shuwei Zhu, Jun Sun, Xiaojun Wu, Zhichao Lu
Summary: This paper proposes a low-cost neural architecture search method (LoNAS) that addresses the problems of existing approaches by designing a variable-architecture encoding strategy, a training-free proxy, and a three-stage evolutionary algorithm. The experimental results show that LoNAS finds network architectures with competitive performance in test accuracy and the number of parameters, using less search time and fewer computational resources.
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE
(2023)
Article
Computer Science, Hardware & Architecture
Albert Segura, Jose Maria Arnau, Antonio Gonzalez
Summary: GPGPU architectures are widely used for parallel workloads, but irregular applications such as graph processing struggle to fully leverage their resources. To address this issue, this research proposes a novel hardware extension called IRU, which improves memory coalescing and reduces workload.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Software Engineering
David Corbalan-Navarro, Juan L. Aragon, Marti Anglada, Enrique de Lucas, Joan-Manuel Parcerisa, Antonio Gonzalez
Summary: This article introduces a microarchitectural technique called Omega-Test to reduce overdraw in tile-based rendering. By leveraging frame-to-frame coherence, the proposed approach utilizes discarded tile information from current frames to predict the visibility of tiles in the next frame. Experimental evaluation shows average energy savings of 26.4% and average speedup of 16.3% for the evaluated benchmarks.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2022)
Article
Computer Science, Hardware & Architecture
Xianfeng Li, Gengchao Li
Summary: Mobile games are increasingly demanding in computational complexity, leading to rapid battery drain of integrated CPUs and GPUs, hindering user experience improvement. By introducing a CPU-GPU governing framework that recognizes performance demand and selects the most energy-efficient hardware configuration for different game scenes, significant power savings can be achieved without compromising user experience.
IEEE TRANSACTIONS ON COMPUTERS
(2021)
Article
Computer Science, Software Engineering
David Gross, Stefan Gumhold
Summary: The paper introduces an efficient approach for high quality GPU-based rendering of line data with ambient occlusion and transparency effects. By utilizing GPU-based raycasting of rounded cones and efficient voxel cone tracing approach, the method achieves high-quality rendering of complex line data. A new fragment visibility sorting strategy and hierarchical opacity maps are proposed to improve performance.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2021)
Article
Computer Science, Hardware & Architecture
Run Yan, Yin Su, Hui Guo, Yashuai Lu, Jin Wang, Nong Xiao, Li Shen, Yongwen Wang, Libo Huang
Summary: This paper introduces an innovative mobile accelerator called Multilevel Parallel Ray Tracing Accelerator (MPRTA), aimed at addressing the challenges of interactive ray tracing on mobile devices. Experimental results demonstrate that MPRTA is 1.67 times more efficient than the currently best-reported mobile accelerator.
IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Timothy Gomez, Ryan Luna, Sheikh Ariful Islam
Summary: As Moore's law nears its end, processors are approaching their physical limits. The focus has shifted to multicore processors and distributed computational systems. However, along with the benefits of parallel computing, there are also concerns about reliability and security. This article provides a systematic overview of the current issues in extreme parallelism.
IEEE CONSUMER ELECTRONICS MAGAZINE
(2022)
Article
Biochemistry & Molecular Biology
Blaine H. M. Mooers, Marina E. Brown
Summary: PyMOL commands allow precise control over molecular model appearance, but many users struggle with poor command recall. In response, pymolsnips library was developed to provide code templates for easier PyMOL script writing, increasing productivity for users across various text editors and operating systems.
Article
Computer Science, Theory & Methods
Jiesong Liu, Feng Zhang, Hourun Li, Dalin Wang, Weitao Wan, Xiaokun Fang, Jidong Zhai, Xiaoyong Du
Summary: This article introduces FineQuery engine for efficient query processing on CPU-GPU integrated edge devices, utilizing architectural features and query characteristics for fine-grained workload scheduling. Experimental results show that compared to using only GPU or CPU, FineQuery reduces latency by 42.81% and improves bandwidth utilization by 2.39x. Query processing at the edge provides significant performance-per-cost benefits and energy efficiency, with FineQuery offering a 21x performance-per-cost ratio and 4x energy efficiency compared to processing on a discrete GPU platform.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Yanxi Li, Minjing Dong, Yunhe Wang, Chang Xu
Summary: This paper proposes a method to search for the optimal neural architecture by minimizing a proxy of validation loss. It approximates the validation loss landscape by learning a mapping from neural architectures to their corresponding validate losses, allowing for easy identification of the optimal neural architecture. A novel architecture sampling strategy and an operation importance weight are developed to improve efficiency and balance randomness and certainty in architecture sampling. Experimental results demonstrate the effectiveness of the proposed method in both differentiable NAS and EA-based NAS.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Chemistry, Multidisciplinary
Run Yan, Libo Huang, Hui Guo, Yashuai Lu, Ling Yang, Nong Xiao, Yongwen Wang, Li Shen, Mengqiao Lan
Summary: This article introduces a novel architecture, the RT engine, that accelerates ray tracing by utilizing strategies such as multiple stacks, three-phase break method, and approximation method.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Information Systems
Peng Sun, Yonggang Wen, Ruobing Han, Wansen Feng, Shengen Yan
Summary: Scaling out deep neural network (DNN) training is crucial for reducing model training time, but high communication overhead in distributed DNN training is a major performance bottleneck. In this study, we propose GradientFlow, a communication backend, and employ various network optimization techniques to tackle this problem. By integrating methods such as ring-based allreduce, mixed-precision training, and computation/communication overlap, as well as introducing lazy allreduce and coarse-grained sparse communication, we were able to achieve impressive speedup ratios when training AlexNet and ResNet-50 on the ImageNet dataset using multiple GPUs.
IEEE TRANSACTIONS ON BIG DATA
(2022)
Article
Computer Science, Hardware & Architecture
Hoda Naghibijouybari, Ajaya Neupane, Zhiyun Qian, Nael Abu-Ghazaleh
Summary: GPUs are commonly used to enhance graphical workloads and accelerate data-intensive workloads in data centers and clouds. However, there is a security vulnerability where spy applications can monitor side channels to infer the behavior of victims. The paper demonstrates three end-to-end attacks, including fingerprinting websites, tracking user activities, inferring keystroke timings, and deriving internal parameters of neural network models used by other applications.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2021)
Article
Thermodynamics
Xin Wu, Qiang Han
Summary: This study investigated the thermal transport properties of pristine and defective 2D-PANI using extensive molecular dynamics simulations. The results showed that structural defects significantly reduce the lattice thermal conductivity of 2D-PANI, and this reduction follows a low-power law with defect concentration. The differences in thermal conductivity weakening between vacancy and topological defects are mainly attributed to their differential effects on low-frequency out-of-plane phonons.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2021)
Article
Computer Science, Artificial Intelligence
Lubin Yu, Lianfang Tian, Qiliang Du, Jameel Ahmed Bhutto
Summary: This study introduces a novel multi-stream adaptive spatial-temporal attention GCN model that addresses issues found in existing GCN models, enhancing network performance through the use of a learnable topology graph and spatial-temporal attention module.
IET COMPUTER VISION
(2022)
Article
Computer Science, Theory & Methods
Jintao Meng, Chen Zhuang, Peng Chen, Mohamed Wahib, Bertil Schmidt, Xiao Wang, Haidong Lan, Dou Wu, Minwen Deng, Yanjie Wei, Shengzhong Feng
Summary: FastConv is a template-based code auto-generation open-source library that generates high-performance deep learning convolution kernels for arbitrary matrices/tensors shapes. It addresses the optimization challenge for convolution layers of different shapes and achieves performance portability by automatically selecting the best combination of kernel shapes, cache tiles, loop orders, packing strategies, access patterns, and computations. FastConv outperforms NNPACK, ARM NN, and FeatherCNN on Kunpeng 920 CPU, with speedups ranging from 1.02x to 2.48x. It also demonstrates performance portability on various convolution shapes and achieves significant speedups over NNPACK and ARM NN using Winograd on Kunpeng 920, as well as other CPU architectures such as Snapdragon, Apple M1, and AWS Graviton2.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2022)
Article
Computer Science, Theory & Methods
Ping Gao, Xiaohui Duan, Bertil Schmidt, Wusheng Zhang, Lin Gan, Haohuan Fu, Wei Xue, Weiguo Liu, Guangwen Yang
Summary: Molecular dynamics simulations have become increasingly important in various fields. By optimizing the computation of interactions, we achieved significantly faster simulations and proposed a method to eliminate write conflicts, resulting in a significant speedup. Compared to other software packages, our implementation allows for simulations of a large number of atoms on a large-scale cluster with high efficiency.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2022)
Article
Computer Science, Theory & Methods
Kai Xu, Xiaohui Duan, Andre Muller, Robin Kobus, Bertil Schmidt, Weiguo Liu
Summary: This paper introduces FMapper, a highly scalable read mapper optimized for the SW26010 many-core architecture on the TaihuLight supercomputer. By implementing dynamic task scheduling, asynchronous I/O and data transfers, and a vectorized version of the banded Myers algorithm tailored to the SW26010 256 bit vector registers, FMapper outperforms other read mappers in performance evaluation.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2022)
Article
Computer Science, Theory & Methods
Daniel Juenger, Robin Kobus, Andre Mueller, Christian Hundt, Kai Xu, Weiguo Liu, Bertil Schmidt
Summary: Hash maps are versatile data structures widely used in data analytics and artificial intelligence. The WarpCore framework aims to improve both versatility and performance, providing acceleration for bioinformatics applications.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2022)
Article
Computer Science, Interdisciplinary Applications
Julian Cascitti, Stefan Niebler, Andre Mueller, Bertil Schmidt
Summary: RNACache is a novel approach based on context-aware locality sensitive hashing for detecting local similarities between transcriptomes and RNA-seq reads. It consists of a three-step processing pipeline that accurately identifies truly expressed transcript isoforms and offers better performance and scalability compared to other lightweight mapping tools.
JOURNAL OF COMPUTATIONAL SCIENCE
(2022)
Article
Biochemical Research Methods
Konstantin Bob, David Teschner, Thomas Kemmer, David Gomez-Zepeda, Stefan Tenzer, Bertil Schmidt, Andreas Hildebrandt
Summary: This study demonstrates the effectiveness of locality-sensitive hashing in signal classification in mass spectrometry raw data, achieving superior performance by balancing false-positive and false-negative rates through appropriate algorithm parameters. This approach significantly reduces data size while preserving important information in processing large-scale mass spectrometry data.
BMC BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Felix Kallenborn, Julian Cascitti, Bertil Schmidt
Summary: This article presents CARE 2.0, a context-aware read error correction tool based on multiple sequence alignment for Illumina datasets. With the use of new optimizations and a classifier based on random decision forests, CARE 2.0 reduces false-positive corrections significantly and achieves high numbers of true-positive corrections. The results demonstrate the applicability of CARE 2.0 in improving k-mer analysis and de novo assembly with real-world data.
BMC BIOINFORMATICS
(2022)
Article
Computer Science, Theory & Methods
Kai Xu, Jinxiao Zhang, Xiaohui Duan, Xiaobo Wan, Niu Huang, Bertil Schmidt, Weiguo Liu, Guangwen Yang
Summary: This paper presents the porting and optimization of UCSF DOCK3.7 on the Sunway TaihuLight supercomputer. Several strategies, such as the producer-consumer strategy, a new binary file format, and ligand orientation scoring optimization, are employed to improve the performance and efficiency of molecular docking.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2022)
Article
Computer Science, Theory & Methods
Xiaohui Duan, Qi Shao, Junben Weng, Bertil Schmidt, Lin Gan, Guohui Li, Haohuan Fu, Wei Xue, Weiguo Liu, Guangwen Yang
Summary: In this paper, a new MD implementation named Bio-ESMD is presented, which improves computational efficiency by reorganizing the cell list data structure to adopt bond lists with guaranteed data locality. Compared to SW_GROMACS, the implementation achieves speedups of over two on Sunway TaihuLight and exhibits linear weak scaling efficiency, achieving simulation of systems with 308.8 million atoms at 1.33 ns/day or 14.44 million atoms at 17.28 ns/day.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2023)
Article
Biochemical Research Methods
Hao Zhang, Honglei Song, Xiaoming Xu, Qixin Chang, Mingkai Wang, Yanjie Wei, Zekun Yin, Bertil Schmidt, Weiguo Liu
Summary: The continuous growth of generated sequencing data has resulted in the development of bioinformatics tools. However, many of these tools are restricted by slow execution times due to parsing files. This motivates the design of RabbitFX, a framework that efficiently parses sequencing data on modern multi-core systems. It provides optimized formatting implementation and user-friendly APIs that can integrate into applications to increase file parsing speed. Integration of RabbitFX into three I/O-intensive applications shows significant speedups compared to the original versions. RabbitFX is open-source software available at https://github.com/RabbitBio/RabbitFX.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Thomas Kemmer, Sebastian Hack, Bertil Schmidt, Andreas Hildebrandt
Summary: Protein interactions are crucial for understanding biological function. This study presents an implicit, yet exact representation for dense and asymmetric system matrices of boundary element methods (BEM) for nonlocal protein electrostatics, allowing for the analysis of protein surface meshes with large numbers of elements in memory-limited environments.
JOURNAL OF COMPUTATIONAL SCIENCE
(2023)
Article
Computer Science, Information Systems
Hao Zhang, Zekun Yin, Yanjie Wei, Bertil Schmidt, Weiguo Liu
Summary: With the development of sequencing technologies, somatic mutation analysis has become important in cancer research and treatment. VarDict is commonly used for this task, but it may detect false positive variants. To address this problem, we propose DeepFilter, a deep-learning based filter for VarDict, which can effectively filter out false positive variants.
TSINGHUA SCIENCE AND TECHNOLOGY
(2023)
Article
Genetics & Heredity
Alexander Wichmann, Etienne Buschong, Andre Mueller, Daniel Juenger, Andreas Hildebrandt, Thomas Hankeln, Bertil Schmidt
Summary: Deep learning has had a significant impact on scientific research and this paper introduces a self-attention-based deep learning tool called MetaTransformer for metagenomic analysis. MetaTransformer outperforms previous methods in species and genus classification and achieves improved performance and reduced memory consumption through different embedding schemes.
NAR GENOMICS AND BIOINFORMATICS
(2023)
Article
Computer Science, Theory & Methods
Ping Gao, Xiaohui Duan, Bertil Schmidt, Wubing Wan, Jiaxu Guo, Wusheng Zhang, Lin Gan, Haohuan Fu, Wei Xue, Weiguo Liu, Guangwen Yang
Summary: This article introduces the method of simulating carbon and hydrocarbon systems using the AIREBO potential in LAMMPS on the new Sunway supercomputer. By implementing parallel two-level building scheme, periodic buffering strategy, and optimized nearest-neighbor access algorithms, efficient simulation and computation are achieved.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2023)
Proceedings Paper
Computer Science, Hardware & Architecture
Valentin Henkys, Bertil Schmidt, Niklaus Berger
Summary: The Mu3e experiment aims to observe physics beyond the Standard Model by observing the decay products of high-density muons. An online event selection algorithm is used to reduce the data rate by using simple geometric selection and reconstruction methods, achieving the targeted performance requirements.
2022 21ST INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED COMPUTING (ISPDC 2022)
(2022)
Article
Computer Science, Interdisciplinary Applications
Usman Riaz, E. Seegyoung Seol, Robert Hager, Mark S. Shephard
Summary: The accurate representation and effective discretization of a problem domain into a mesh are crucial for achieving high-quality simulation results and computational efficiency. This work presents recent developments in extending an automated tokamak modeling and meshing infrastructure to better support the near flux field following meshing requirements of the XGC Gyro-kinetic Code.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhenglu Li, Gabriel Antonius, Yang-Hao Chan, Steven G. Louie
Summary: This article presents a workflow for practical calculations of electron-phonon coupling and includes the effect of many-electron correlations using GW perturbation theory. The workflow combines different software packages to enable accurate calculations at the level of quasiparticle band structures.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Akihiro Koide, Sara Rabouli, Pierre Le Meur, Sylvain Tricot, Philippe Schieffer, Didier Sebilleau, Calogero R. Natoli
Summary: We present the MsSpec Atomic Scattering Amplitude Package (MASAP), which includes a computation program and a graphical interface for generating atomic scattering amplitude (ASA). The study investigates the applicability of plane wave (PW) and curved spherical wave (SW) scattering in describing electron propagation. The results show that the imaginary part of the optical potential enhances the elastic scattering in the forward direction but causes damping effects in other directions.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
A. Bagci, Gustavo A. Aucar
Summary: The electron repulsion integrals over Slater-type orbitals with non-integer principal quantum numbers are investigated in this study. These integrals are important in calculations of many-electron systems. New relationships free from hyper-geometric functions are derived to simplify the calculations. With the use of auxiliary functions and straightforward recurrence relationships, these integrals can be efficiently computed, providing initial conditions for the evaluation of expectation values and potentials.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Andrzej Daniluk
Summary: RHEED_DIFF_2D is an open-source software for qualitative numerical simulations of RHEED oscillation intensity changes with layer deposition, used for interpreting heteroepitaxial structures under different scattering crystal potential models.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Niklas Kuehl, Hendrik Fischer, Michael Hinze, Thomas Rung
Summary: The article presents a strategy and algorithm for simulation-accompanying, incremental Singular Value Decomposition (SVD) for time-evolving, spatially parallel discrete data sets. The proposed method improves computational efficiency by introducing a bunch matrix, resulting in higher accuracy and practical applicability.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Jose M. Rodriguez-Borbon, Xian Wang, Adrian P. Dieguez, Khaled Z. Ibrahim, Bryan M. Wong
Summary: This paper presents an open-source software package called TRAVOLTA for massively parallelized quantum optimal control calculations on GPUs. The TRAVOLTA package is an improvement on the previous NIC-CAGE algorithm and incorporates algorithmic improvements for faster convergence. Three different variants of GPU parallelization are examined to evaluate their performance in constructing optimal control fields in various quantum systems. The benchmarks show that the GPU-enhanced TRAVOLTA code produces the same results as previous CPU-based algorithms but with a speedup of more than ten times. The GPU enhancements and algorithmic improvements allow large quantum optimal control calculations to be efficiently executed on modern multi-core computational hardware.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Weijie Hua
Summary: This work introduces a program called MCNOX for computing and analyzing ultrafast nonlinear X-ray spectra. It is designed for cutting-edge applications in photochemistry/photophysics enabled by X-ray free-electron lasers and high harmonic generation light sources. The program can calculate steady-state X-ray absorption spectroscopy and three types of ultrafast nonlinear X-ray spectra, and it is capable of identifying major electronic transitions and providing physical and chemical insights from complex signals.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Leandro Benatto, Omar Mesquita, Lucimara S. Roman, Rodrigo B. Capaz, Graziani Candiotto, Marlus Koehler
Summary: Photoluminescence Quenching Simulator (PLQ-Sim) is a user-friendly software for studying the dynamics of photoexcited states at the interface between organic semiconductors. It provides important information on organic photovoltaic and photothermal devices and calculates transfer rates and quenching efficiency.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Dongming Li, James Kestyn, Eric Polizzi
Summary: This study introduces a practical and efficient approach to calculate the all-electron full potential band structure in real space using a finite element basis. Instead of the k-space method, this method solves the Kohn-Sham equation self-consistently within a larger finite system enclosing the unit-cell. Non-self-consistent calculations are then performed in the Brillouin zone to obtain the band structure results, which are found to be in excellent agreement with the pseudopotential k-space method. Furthermore, the study successfully observes the band bending of core electrons.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
R. Kleiber, M. Borchardt, R. Hatzky, A. Koenies, H. Leyh, A. Mishchenko, J. Riemann, C. Slaby, J. M. Garcia-Regana, E. Sanchez, M. Cole
Summary: This paper describes the current state of the EUTERPE code, focusing on the implemented models and their numerical implementation. The code is capable of solving the multi-species electromagnetic gyrokinetic equations in a three-dimensional domain. It utilizes noise reduction techniques and grid resolution transformation for efficient computation. Additionally, various hybrid models are implemented for comparison and the study of plasma-particle interactions. The code is parallelized for high scalability on multiple CPUs.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Pengliang Yang
Summary: This paper presents an open source software called SMIwiz, which combines seismic modelling, reverse time migration, and full waveform inversion into a unified computer implementation. SMIwiz supports both 2D and 3D simulations and provides various computational recipes for efficient calculation. Its independent processing and batchwise job scheduling ensure scalability, and its viability is demonstrated through applications on benchmark models.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Christian Tantardini, Miroslav Ilias, Matteo Giantomassi, Alexander G. Kvashnin, Valeria Pershina, Xavier Gonze
Summary: Material discovery has been an active research field, and this study focuses on developing pseudopotentials for actinides and super-heavy elements. These pseudopotentials are crucial for accurate first-principles calculations and simulations.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
S. Blanes, F. Casas, C. Gonzalez, M. Thalhammer
Summary: This paper explores the extension of modified potential operator splitting methods to specific classes of nonlinear evolution equations. Numerical experiments confirm the advantages of the proposed fourth-order modified operator splitting method over traditional splitting methods in dealing with Gross-Pitaevskii systems.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Siegfried Kaidisch, Thomas U. Hilger, Andreas Krassnigg, Wolfgang Lucha
Summary: Motivated by a use case in theoretical hadron physics, this paper revisits an application of a pole-sum fit to dressing functions of a confined quark propagator. Specifically, it investigates approaches to determine the number and positions of singularities closest to the origin for a function known numerically on a specific grid on the positive real axis. Comparing the efficiency of standard techniques to a pure artificial-neural-network approach and a combination of both, it finds that the combined approach is more efficient. This approach can be applied to similar situations where the positions of poles need to be estimated quickly and reliably from real-axis information alone.
COMPUTER PHYSICS COMMUNICATIONS
(2024)
