Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences最新文献_第2页

Numerical analysis, spectral graph theory, orthogonal polynomials and quantum algorithms. 数值分析，谱图理论，正交多项式和量子算法。

IF 3.7 3区综合性期刊

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Pub Date : 2025-10-09 DOI: 10.1098/rsta.2024.0426

Anastasiia Minenkova, Gamal Mograby, Hanmeng Zhan

{"title":"Numerical analysis, spectral graph theory, orthogonal polynomials and quantum algorithms.","authors":"Anastasiia Minenkova, Gamal Mograby, Hanmeng Zhan","doi":"10.1098/rsta.2024.0426","DOIUrl":"10.1098/rsta.2024.0426","url":null,"abstract":"Recent progress in quantum computing shows the need to incorporate many branches of mathematics (graph theory, matrix theory, optimization, theory of orthogonal polynomials and more) into physics, computer science and chemistry. At the 2024 SIAM Quantum Intersections Convening, Bert de Jong (Lawrence Berkeley National Laboratory) gave a talk entitled 'Quantum Science Needs Mathematicians' (Report of the SIAM Quantum Intersections Convening. Integrating Mathematical Scientists into Quantum Research, 7-9 October 2024, Tysons, Virginia (doi:10.11337/25M1741017)), since despite the growing demand for research in these domains, the mathematical sciences community has remained largely disengaged from quantum research, with only a few isolated areas of active involvement. This issue brings together researchers from different areas of mathematics to show the relation between spectral graph theory, the theory of orthogonal polynomials and numerical analysis. This interconnectedness highlights the versatility and importance of these areas of mathematics in the context of quantum computing.This article is part of the theme issue 'Numerical analysis, spectral graph theory, orthogonal polynomials and quantum algorithms'.","PeriodicalId":19879,"journal":{"name":"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences","volume":"383 2306","pages":"20240426"},"PeriodicalIF":3.7,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12508770/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145252120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Trilateration of blast wave arrival time: an inverse method for determining explosive yield and position. 爆炸波到达时间的三边测量：一种确定爆炸当量和爆炸位置的逆方法。

IF 3.7 3区综合性期刊

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Pub Date : 2025-09-25 DOI: 10.1098/rsta.2024.0040

Jay Karlsen, Dain G Farrimond, Tommy J Lodge, Samuel E Rigby, Andrew Tyas, Sam D Clarke, Timothy R Brewer

{"title":"Trilateration of blast wave arrival time: an inverse method for determining explosive yield and position.","authors":"Jay Karlsen, Dain G Farrimond, Tommy J Lodge, Samuel E Rigby, Andrew Tyas, Sam D Clarke, Timothy R Brewer","doi":"10.1098/rsta.2024.0040","DOIUrl":"10.1098/rsta.2024.0040","url":null,"abstract":"This paper details the development of a rapid inverse approach to determine the yield and location of an explosion through trilateration of empirical laws for blast wave arrival time. A rigorous sensitivity analysis of measurement uncertainty is first performed. From this, a probabilistic framework is proposed that utilizes Monte Carlo sampling of datasets to mitigate the effects of the variability and uncertainties typically present in blast events. Subsequently, the trilateration method is successfully applied to two existing datasets. Analysing well-controlled small-scale laboratory experiments, charge mass is predicted within 6.3% of the true yield, and position within 3.65 charge radii of the true centre. Social media footage of the 2020 Beirut explosion is then used to assess performance against data collected under in-field conditions. The predicted yield of 0.52 kt[Formula: see text] shows good agreement with the literature, and charge position is predicted to within the radius of the crater. Trilateration is shown to be able to rapidly and reliably determine explosive yield and centre, despite large levels of sensor noise. The sub-second computation time of this approach offers the possibility to better model and predict the damage and injury patterns immediately after an explosion, facilitating more effective disaster response planning.This article is part of the theme issue 'Frontiers of applied inverse problems in science and engineering'.","PeriodicalId":19879,"journal":{"name":"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences","volume":"383 2305","pages":"20240040"},"PeriodicalIF":3.7,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12461223/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145138325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Boosting positron emission tomography reconstruction with positional encoding-based deep image prior. 基于位置编码的深度图像先验增强正电子发射层析成像重建。

IF 3.7 3区综合性期刊

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Pub Date : 2025-09-25 DOI: 10.1098/rsta.2024.0049

Saima Ashraf, Qianxue Shan, Wuqing Ning, Dong Liu

{"title":"Boosting positron emission tomography reconstruction with positional encoding-based deep image prior.","authors":"Saima Ashraf, Qianxue Shan, Wuqing Ning, Dong Liu","doi":"10.1098/rsta.2024.0049","DOIUrl":"https://doi.org/10.1098/rsta.2024.0049","url":null,"abstract":"In this paper, we leverage the structured foundation of deep image prior to delve into the complexities of positron emission tomography (PET) image reconstruction. We aim to underscore the potential of deep learning in overcoming inherent challenges associated with PET imaging. Acknowledging the limitations of conventional supervised learning in this domain, we propose an innovative unsupervised approach employing deep neural networks to enhance PET reconstruction. A central focus of our study revolves around the spectral bias issue that arises during PET image reconstruction. To tackle this challenge, we introduce a comprehensive framework that incorporates Gaussian Fourier features and Uniform Positional encoding. Our approaches undergo rigorous testing on both Brainweb data and naive rat data, revealing a noticeable improvement in image reconstruction performance. This underscores the efficacy of our framework in advancing PET imaging methodologies.This article is part of the theme issue 'Frontiers of applied inverse problems in science and engineering'.","PeriodicalId":19879,"journal":{"name":"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences","volume":"383 2305","pages":"20240049"},"PeriodicalIF":3.7,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145138216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Segmentation of experimental eddy current testing data via matching component analysis. 基于匹配分量分析的实验涡流检测数据分割。

IF 3.7 3区综合性期刊

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Pub Date : 2025-09-25 DOI: 10.1098/rsta.2024.0048

Laura Homa, Matthew Cherry, John Wertz

{"title":"Segmentation of experimental eddy current testing data via matching component analysis.","authors":"Laura Homa, Matthew Cherry, John Wertz","doi":"10.1098/rsta.2024.0048","DOIUrl":"https://doi.org/10.1098/rsta.2024.0048","url":null,"abstract":"Microtexture regions (MTRs) are collections of grains with similar crystallographic orientation. When present in aerospace components, they can potentially limit component life. As such, a non-destructive evaluation (NDE) method to detect and characterize MTR is desired. One potential solution is to use an electromagnetic NDE method known as eddy current testing (ECT), which is sensitive to local conductivity variations associated with MTR. Recent work has shown that MTR boundaries and orientation can be determined from ECT data using a variant of matching component analysis (MCA) combined with a regularization method originally developed for image deblurring. However, this method has only been demonstrated on simulated ECT data. In this work, we apply the previously developed method to experimental ECT data of a large grain titanium specimen. We show that we are able to determine grain boundaries and orientation from experimental ECT data, serving as a first step to full MTR characterization.This article is part of the theme issue 'Frontiers of applied inverse problems in science and engineering'.","PeriodicalId":19879,"journal":{"name":"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences","volume":"383 2305","pages":"20240048"},"PeriodicalIF":3.7,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145138331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Coefficient-to-Basis Network: a fine-tunable operator learning framework for inverse problems with adaptive discretizations and theoretical guarantees. 系数到基网络：具有自适应离散化和理论保证的逆问题的可微调算子学习框架。

IF 3.7 3区综合性期刊

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Pub Date : 2025-09-25 DOI: 10.1098/rsta.2024.0054

Zecheng Zhang, Hao Liu, Wenjing Liao, Guang Lin

{"title":"Coefficient-to-Basis Network: a fine-tunable operator learning framework for inverse problems with adaptive discretizations and theoretical guarantees.","authors":"Zecheng Zhang, Hao Liu, Wenjing Liao, Guang Lin","doi":"10.1098/rsta.2024.0054","DOIUrl":"https://doi.org/10.1098/rsta.2024.0054","url":null,"abstract":"We propose a Coefficient-to-Basis Network (C2BNet), a novel framework for solving inverse problems within the operator learning paradigm. C2BNet efficiently adapts to different discretizations through fine-tuning, using a pre-trained model to significantly reduce computational cost while maintaining high accuracy. Unlike traditional approaches that require retraining from scratch for new discretizations, our method enables seamless adaptation without sacrificing predictive performance. Furthermore, we establish theoretical approximation and generalization error bounds for C2BNet by exploiting low-dimensional structures in the underlying datasets. Our analysis demonstrates that C2BNet adapts to low-dimensional structures without relying on explicit encoding mechanisms, highlighting its robustness and efficiency. To validate our theoretical findings, we conducted extensive numerical experiments that showcase the superior performance of C2BNet on several inverse problems. The results confirm that C2BNet effectively balances computational efficiency and accuracy, making it a promising tool to solve inverse problems in scientific computing and engineering applications.This article is part of the theme issue 'Frontiers of applied inverse problems in science and engineering'.","PeriodicalId":19879,"journal":{"name":"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences","volume":"383 2305","pages":"20240054"},"PeriodicalIF":3.7,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145138208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep learning-based artefact reduction in low-dose dental cone beam computed tomography with high-attenuation materials. 基于深度学习的高衰减材料低剂量牙锥束计算机断层伪影减少。

IF 3.7 3区综合性期刊

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Pub Date : 2025-09-25 DOI: 10.1098/rsta.2024.0045

Hyoung Suk Park, Kiwan Jeon, J K Seo

{"title":"Deep learning-based artefact reduction in low-dose dental cone beam computed tomography with high-attenuation materials.","authors":"Hyoung Suk Park, Kiwan Jeon, J K Seo","doi":"10.1098/rsta.2024.0045","DOIUrl":"10.1098/rsta.2024.0045","url":null,"abstract":"This paper examines the current challenges in computed tomography (CT), with a critical exploration of existing methodologies from a mathematical perspective. Specifically, it aims to identify research directions to enhance image quality in low-dose, cost-effective cone beam CT (CBCT) systems, which have recently gained widespread use in general dental clinics. Dental CBCT offers a substantial cost advantage over standard medical CT, making it affordable for local dental practices; however, this affordability brings significant challenges related to image quality degradation, further complicated by the presence of metallic implants, which are particularly common in older patients. This paper investigates metal-induced artefacts stemming from mismatches in the forward model used in conventional reconstruction methods and explains an alternative approach that bypasses the traditional Radon transform model. Additionally, it examines both the potential and limitations of deep learning-based methods in tackling these challenges, offering insights into their effectiveness in improving image quality in low-dose dental CBCT.This article is part of the theme issue 'Frontiers of applied inverse problems in science and engineering'.","PeriodicalId":19879,"journal":{"name":"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences","volume":"383 2305","pages":"20240045"},"PeriodicalIF":3.7,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12461222/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145138373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine-learning perspectives on Volterra system identification. Volterra系统识别的机器学习视角。

IF 3.7 3区综合性期刊

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Pub Date : 2025-09-25 DOI: 10.1098/rsta.2024.0053

Keith Worden, Timothy Rogers, Oliver Preston

引用次数: 0

Separable hierarchical priors applied to analysis of synergies in human locomotion. 可分离层次先验在人体运动协同效应分析中的应用。

IF 3.7 3区综合性期刊

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Pub Date : 2025-09-25 DOI: 10.1098/rsta.2024.0055

Daniela Calvetti, Andrea N Arnold, Alexander P Hoover, Giorgio Davico, Erkki Somersalo

{"title":"Separable hierarchical priors applied to analysis of synergies in human locomotion.","authors":"Daniela Calvetti, Andrea N Arnold, Alexander P Hoover, Giorgio Davico, Erkki Somersalo","doi":"10.1098/rsta.2024.0055","DOIUrl":"https://doi.org/10.1098/rsta.2024.0055","url":null,"abstract":"It has been hypothesized that during a motion task the central nervous system controls the skeletal muscles partitioning them into synergetic groups, hence effectively reducing the dimensionality of the control problem. The identification of muscle groups that are co-activated remains an open problem: its solution could have important implications in the design of training or rehabilitation protocols. In this article, we combine Bayesian inverse problem techniques and data science algorithms to identify muscle synergies in human motion from the motion tracker time series of positions of fiducial markers on the body during the task. The inverse problem of estimating the muscle activation patterns from the motion tracking data is cast in the Bayesian framework, and the posterior distribution of muscle activations is explored using Myobolica, a Gibbs-sampler-based Markov chain Monte Carlo sampler. A low-rank approximation of the muscle activation patterns is then obtained via a sparsity promoting Bayesian non-negative matrix factorization of the sample mean, where the sparse coefficient vectors correspond to groups of muscles that show co-activation over the sample.This article is part of the theme issue 'Frontiers of applied inverse problems in science and engineering'.","PeriodicalId":19879,"journal":{"name":"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences","volume":"383 2305","pages":"20240055"},"PeriodicalIF":3.7,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145138363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On orthogonality sampling method for Maxwell's equations and its applications to experimental data. 麦克斯韦方程组的正交抽样方法及其在实验数据中的应用。

IF 3.7 3区综合性期刊

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Pub Date : 2025-09-25 DOI: 10.1098/rsta.2024.0051

Thu Le, Dinh-Liem Nguyen

引用次数: 0

Towards using explainable data-driven surrogate models for treating performance-based seismic design as an inverse engineering problem. 采用可解释的数据驱动替代模型，将基于性能的地震设计作为逆向工程问题来处理。

IF 3.7 3区综合性期刊

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Pub Date : 2025-09-25 DOI: 10.1098/rsta.2024.0050

Mohsen Zaker Esteghamati

{"title":"Towards using explainable data-driven surrogate models for treating performance-based seismic design as an inverse engineering problem.","authors":"Mohsen Zaker Esteghamati","doi":"10.1098/rsta.2024.0050","DOIUrl":"https://doi.org/10.1098/rsta.2024.0050","url":null,"abstract":"This study presents a methodology to treat performance-based seismic design (PBSD) as an inverse engineering problem, where design parameters are directly derived to achieve specific performance objectives (POs). By implementing explainable machine learning (ML) models, this methodology directly maps design variables and performance metrics, thereby tackling the computational inefficiencies associated with performance-based design. The resultant ML model is integrated as an evaluation function into a genetic optimization algorithm to solve the inverse problem. The developed methodology is then applied to two different inventories of steel and concrete moment frames in Los Angeles and Charleston to obtain sectional properties of frame members that minimize expected annualized seismic loss in terms of repair costs. The results show high accuracy of the surrogate models (e.g. R2 > 90%) across a diverse set of building types, geometries, seismic design and site hazard, where the optimization algorithm could identify the optimum values of members' properties for a fixed set of geometric variables, consistent with engineering principles.This article is part of the theme issue 'Frontiers of applied inverse problems in science and engineering'.","PeriodicalId":19879,"journal":{"name":"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences","volume":"383 2305","pages":"20240050"},"PeriodicalIF":3.7,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145138323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0