Johanna Langner , Anjan Sadhukhan , Jayanta K. Saha , Henryk A. Witek
{"title":"从稳定化方法中自动提取谐振参数的算法","authors":"Johanna Langner , Anjan Sadhukhan , Jayanta K. Saha , Henryk A. Witek","doi":"10.1016/j.cpc.2025.109815","DOIUrl":null,"url":null,"abstract":"<div><div>The application of the stabilization method (Hazi and Taylor, 1970 [1]) to extract accurate energy and lifetimes of resonance states is challenging: The process requires labor-intensive numerical manipulation of a large number of eigenvalues of a parameter-dependent Hamiltonian matrix, followed by a fitting procedure. In this article, we present <span>ReSMax</span>, an efficient algorithm implemented as an open-access <span>Python</span> code, which offers full automation of the stabilization diagram analysis in a user-friendly environment while maintaining high numerical precision of the computed resonance characteristics. As a test case, we use <span>ReSMax</span> to analyze the natural parity doubly-excited resonance states (<span><math><mmultiscripts><mrow><mtext>S</mtext></mrow><none></none><mrow><mtext>e</mtext></mrow><mprescripts></mprescripts><none></none><mrow><mn>1</mn></mrow></mmultiscripts></math></span>, <span><math><mmultiscripts><mrow><mtext>S</mtext></mrow><none></none><mrow><mtext>e</mtext></mrow><mprescripts></mprescripts><none></none><mrow><mn>3</mn></mrow></mmultiscripts></math></span>, <span><math><mmultiscripts><mrow><mtext>P</mtext></mrow><none></none><mrow><mtext>o</mtext></mrow><mprescripts></mprescripts><none></none><mrow><mn>1</mn></mrow></mmultiscripts></math></span>, and <span><math><mmultiscripts><mrow><mtext>P</mtext></mrow><none></none><mrow><mtext>o</mtext></mrow><mprescripts></mprescripts><none></none><mrow><mn>3</mn></mrow></mmultiscripts></math></span>) of helium, demonstrating the accuracy and efficiency of the developed methodology. The presented algorithm is applicable to a wide range of resonances in atomic, molecular, and nuclear systems.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> <span>ReSMax</span></div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/8yny7jycgz.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/giogina/ReSMax</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> MIT</div><div><em>Programming language:</em> Python</div><div><em>Nature of problem:</em> The stabilization method is a widely used indirect approach for identifying resonance states (RSs) in atomic and molecular systems. It analyzes the behavior of energy eigenvalues of the system's Hamiltonian as a function of a basis set parameter, as visualized in stabilization diagrams (SDs) [1]. Resonance states manifest as plateaus in these SDs and are characterized by the position and width of the associated Lorentzian peaks in the density of states (DOS) [2]. However, applying this method in practice remains labor-intensive and error-prone: analyzing large eigenvalue datasets, identifying plateau regions, and fitting DOS peaks manually requires significant effort and expert judgment. These difficulties limit the method's scalability and reproducibility, especially for systems with many closely spaced resonances or high angular momentum states. There is currently no widely available open-source tool that automates the entire workflow in a robust, accurate, and user-friendly way.</div><div><em>Solution method:</em> <span>ReSMax</span> is an open-source Python program that automates the extraction of resonance parameters from stabilization diagrams. Given an input file containing the eigenvalue spectrum of a Hamiltonian across a range of basis set parameter values, it computes the density of states (DOS) for each root, identifies local maxima corresponding to potential resonances, and fits them to Lorentzian functions. Peaks are grouped into resonance candidates based on energy proximity and root uniqueness, and the best-fitting peak is selected for each resonance. A combination of numerical filtering, symmetry checks, and fit quality metrics ensures robust peak detection. Automatic resonance detection completes in a few seconds. An interactive interface allows optional refinement of resonance assignments before final export of the results.</div><div><em>Additional comments including restrictions and unusual features:</em> Resonances indicated by descending plateaus in the SD — which can appear due to insufficient basis set size for fluorescence-active resonances as well as directly below ionization thresholds — are assigned approximate energies and flagged for manual inspection. While <span>ReSMax</span> was developed for helium-like ions, the method is general and capable of detecting resonance states of a wide range of systems.</div></div><div><h3>References</h3><div><ul><li><span>[1]</span><span><div>A.U. Hazi, H.S. Taylor, Phys. Rev. A 1 (1970) 1109.</div></span></li><li><span>[2]</span><span><div>V.A. Mandelshtam, T.R. Ravuri, H.S. Taylor, Phys. Rev. Lett. 70 (1993) 1932.</div></span></li></ul></div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"316 ","pages":"Article 109815"},"PeriodicalIF":3.4000,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An algorithm for automated extraction of resonance parameters from the stabilization method\",\"authors\":\"Johanna Langner , Anjan Sadhukhan , Jayanta K. Saha , Henryk A. Witek\",\"doi\":\"10.1016/j.cpc.2025.109815\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The application of the stabilization method (Hazi and Taylor, 1970 [1]) to extract accurate energy and lifetimes of resonance states is challenging: The process requires labor-intensive numerical manipulation of a large number of eigenvalues of a parameter-dependent Hamiltonian matrix, followed by a fitting procedure. In this article, we present <span>ReSMax</span>, an efficient algorithm implemented as an open-access <span>Python</span> code, which offers full automation of the stabilization diagram analysis in a user-friendly environment while maintaining high numerical precision of the computed resonance characteristics. As a test case, we use <span>ReSMax</span> to analyze the natural parity doubly-excited resonance states (<span><math><mmultiscripts><mrow><mtext>S</mtext></mrow><none></none><mrow><mtext>e</mtext></mrow><mprescripts></mprescripts><none></none><mrow><mn>1</mn></mrow></mmultiscripts></math></span>, <span><math><mmultiscripts><mrow><mtext>S</mtext></mrow><none></none><mrow><mtext>e</mtext></mrow><mprescripts></mprescripts><none></none><mrow><mn>3</mn></mrow></mmultiscripts></math></span>, <span><math><mmultiscripts><mrow><mtext>P</mtext></mrow><none></none><mrow><mtext>o</mtext></mrow><mprescripts></mprescripts><none></none><mrow><mn>1</mn></mrow></mmultiscripts></math></span>, and <span><math><mmultiscripts><mrow><mtext>P</mtext></mrow><none></none><mrow><mtext>o</mtext></mrow><mprescripts></mprescripts><none></none><mrow><mn>3</mn></mrow></mmultiscripts></math></span>) of helium, demonstrating the accuracy and efficiency of the developed methodology. The presented algorithm is applicable to a wide range of resonances in atomic, molecular, and nuclear systems.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> <span>ReSMax</span></div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/8yny7jycgz.1</span><svg><path></path></svg></span></div><div><em>Developer's repository link:</em> <span><span>https://github.com/giogina/ReSMax</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> MIT</div><div><em>Programming language:</em> Python</div><div><em>Nature of problem:</em> The stabilization method is a widely used indirect approach for identifying resonance states (RSs) in atomic and molecular systems. It analyzes the behavior of energy eigenvalues of the system's Hamiltonian as a function of a basis set parameter, as visualized in stabilization diagrams (SDs) [1]. Resonance states manifest as plateaus in these SDs and are characterized by the position and width of the associated Lorentzian peaks in the density of states (DOS) [2]. However, applying this method in practice remains labor-intensive and error-prone: analyzing large eigenvalue datasets, identifying plateau regions, and fitting DOS peaks manually requires significant effort and expert judgment. These difficulties limit the method's scalability and reproducibility, especially for systems with many closely spaced resonances or high angular momentum states. There is currently no widely available open-source tool that automates the entire workflow in a robust, accurate, and user-friendly way.</div><div><em>Solution method:</em> <span>ReSMax</span> is an open-source Python program that automates the extraction of resonance parameters from stabilization diagrams. Given an input file containing the eigenvalue spectrum of a Hamiltonian across a range of basis set parameter values, it computes the density of states (DOS) for each root, identifies local maxima corresponding to potential resonances, and fits them to Lorentzian functions. Peaks are grouped into resonance candidates based on energy proximity and root uniqueness, and the best-fitting peak is selected for each resonance. A combination of numerical filtering, symmetry checks, and fit quality metrics ensures robust peak detection. Automatic resonance detection completes in a few seconds. An interactive interface allows optional refinement of resonance assignments before final export of the results.</div><div><em>Additional comments including restrictions and unusual features:</em> Resonances indicated by descending plateaus in the SD — which can appear due to insufficient basis set size for fluorescence-active resonances as well as directly below ionization thresholds — are assigned approximate energies and flagged for manual inspection. While <span>ReSMax</span> was developed for helium-like ions, the method is general and capable of detecting resonance states of a wide range of systems.</div></div><div><h3>References</h3><div><ul><li><span>[1]</span><span><div>A.U. Hazi, H.S. Taylor, Phys. Rev. A 1 (1970) 1109.</div></span></li><li><span>[2]</span><span><div>V.A. Mandelshtam, T.R. Ravuri, H.S. Taylor, Phys. Rev. Lett. 70 (1993) 1932.</div></span></li></ul></div></div>\",\"PeriodicalId\":285,\"journal\":{\"name\":\"Computer Physics Communications\",\"volume\":\"316 \",\"pages\":\"Article 109815\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2025-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Physics Communications\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0010465525003170\",\"RegionNum\":2,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Physics Communications","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010465525003170","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
摘要
应用稳定化方法(Hazi和Taylor, 1970[1])来提取共振态的精确能量和寿命是具有挑战性的:该过程需要对参数相关哈密顿矩阵的大量特征值进行劳动密集型数值操作,然后进行拟合程序。在本文中,我们提出了ReSMax,一个高效的算法实现作为一个开放访问的Python代码,它提供了稳定图分析的完全自动化在一个用户友好的环境中,同时保持计算谐振特性的高数值精度。作为测试用例,我们使用ReSMax分析了氦的自然宇称双激发共振态(Se1, Se3, Po1和Po3),证明了所开发方法的准确性和效率。该算法适用于原子、分子和核系统中广泛的共振。程序摘要程序标题:ReSMaxCPC库链接到程序文件:https://doi.org/10.17632/8yny7jycgz.1Developer's存储库链接:https://github.com/giogina/ReSMaxLicensing条款:mit编程语言:python问题的性质:稳定化方法是一种广泛使用的间接方法,用于识别原子和分子系统中的共振状态(RSs)。它分析了系统哈密顿量的能量特征值作为基集参数的函数的行为,如稳定化图(SDs)[1]所示。共振态在这些SDs中表现为平台态,其特征是在态密度(DOS)[2]中相关洛伦兹峰的位置和宽度。然而,在实践中应用该方法仍然是劳动密集型和容易出错的:分析大型特征值数据集,识别平台区域,手动拟合DOS峰值需要大量的努力和专家判断。这些困难限制了该方法的可扩展性和可重复性,特别是对于具有许多紧密共振或高角动量状态的系统。目前还没有广泛可用的开源工具能够以健壮、准确和用户友好的方式自动化整个工作流。解决方法:ReSMax是一个开源的Python程序,可以自动从稳定图中提取共振参数。给定一个包含哈密顿量在一系列基集参数值上的特征值谱的输入文件,它计算每个根的状态密度(DOS),识别对应于潜在共振的局部最大值,并将其拟合到洛伦兹函数中。根据能量接近性和根唯一性将峰值分组为候选共振,并为每个共振选择最适合的峰值。数值滤波,对称检查和拟合质量指标的组合确保了鲁棒的峰值检测。自动共振检测在几秒钟内完成。交互式界面允许在最终输出结果之前可选地细化共振分配。附加评论包括限制和不寻常的特征:由SD中下降的高原指示的共振-可能由于荧光活性共振的基集大小不足以及直接低于电离阈值而出现-被分配近似能量并标记为人工检查。虽然ReSMax是为类氦离子开发的,但该方法是通用的,能够检测各种系统的共振状态哈齐,H.S.泰勒,物理学家。Rev. 1 (1970) 1109.[2]曼德尔施塔姆,T.R.拉武里,H.S.泰勒,物理学家。Rev. Lett. 70(1993) 1932。
An algorithm for automated extraction of resonance parameters from the stabilization method
The application of the stabilization method (Hazi and Taylor, 1970 [1]) to extract accurate energy and lifetimes of resonance states is challenging: The process requires labor-intensive numerical manipulation of a large number of eigenvalues of a parameter-dependent Hamiltonian matrix, followed by a fitting procedure. In this article, we present ReSMax, an efficient algorithm implemented as an open-access Python code, which offers full automation of the stabilization diagram analysis in a user-friendly environment while maintaining high numerical precision of the computed resonance characteristics. As a test case, we use ReSMax to analyze the natural parity doubly-excited resonance states (, , , and ) of helium, demonstrating the accuracy and efficiency of the developed methodology. The presented algorithm is applicable to a wide range of resonances in atomic, molecular, and nuclear systems.
Program summary
Program Title:ReSMax
CPC Library link to program files:https://doi.org/10.17632/8yny7jycgz.1
Nature of problem: The stabilization method is a widely used indirect approach for identifying resonance states (RSs) in atomic and molecular systems. It analyzes the behavior of energy eigenvalues of the system's Hamiltonian as a function of a basis set parameter, as visualized in stabilization diagrams (SDs) [1]. Resonance states manifest as plateaus in these SDs and are characterized by the position and width of the associated Lorentzian peaks in the density of states (DOS) [2]. However, applying this method in practice remains labor-intensive and error-prone: analyzing large eigenvalue datasets, identifying plateau regions, and fitting DOS peaks manually requires significant effort and expert judgment. These difficulties limit the method's scalability and reproducibility, especially for systems with many closely spaced resonances or high angular momentum states. There is currently no widely available open-source tool that automates the entire workflow in a robust, accurate, and user-friendly way.
Solution method:ReSMax is an open-source Python program that automates the extraction of resonance parameters from stabilization diagrams. Given an input file containing the eigenvalue spectrum of a Hamiltonian across a range of basis set parameter values, it computes the density of states (DOS) for each root, identifies local maxima corresponding to potential resonances, and fits them to Lorentzian functions. Peaks are grouped into resonance candidates based on energy proximity and root uniqueness, and the best-fitting peak is selected for each resonance. A combination of numerical filtering, symmetry checks, and fit quality metrics ensures robust peak detection. Automatic resonance detection completes in a few seconds. An interactive interface allows optional refinement of resonance assignments before final export of the results.
Additional comments including restrictions and unusual features: Resonances indicated by descending plateaus in the SD — which can appear due to insufficient basis set size for fluorescence-active resonances as well as directly below ionization thresholds — are assigned approximate energies and flagged for manual inspection. While ReSMax was developed for helium-like ions, the method is general and capable of detecting resonance states of a wide range of systems.
References
[1]
A.U. Hazi, H.S. Taylor, Phys. Rev. A 1 (1970) 1109.
期刊介绍:
The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper.
Computer Programs in Physics (CPiP)
These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged.
Computational Physics Papers (CP)
These are research papers in, but are not limited to, the following themes across computational physics and related disciplines.
mathematical and numerical methods and algorithms;
computational models including those associated with the design, control and analysis of experiments; and
algebraic computation.
Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.