arXiv - PHYS - Data Analysis, Statistics and Probability最新文献_第8页

Heron: Visualizing and Controlling Chemical Reaction Explorations and Networks 苍鹭可视化和控制化学反应探索和网络

arXiv - PHYS - Data Analysis, Statistics and Probability Pub Date : 2024-06-13 DOI: arxiv-2406.09541

Charlotte H. Müller, Miguel Steiner, Jan P. Unsleber, Thomas Weymuth, Moritz Bensberg, Katja-Sophia Csizi, Maximilian Mörchen, Paul L. Türtscher, Markus Reiher

{"title":"Heron: Visualizing and Controlling Chemical Reaction Explorations and Networks","authors":"Charlotte H. Müller, Miguel Steiner, Jan P. Unsleber, Thomas Weymuth, Moritz Bensberg, Katja-Sophia Csizi, Maximilian Mörchen, Paul L. Türtscher, Markus Reiher","doi":"arxiv-2406.09541","DOIUrl":"https://doi.org/arxiv-2406.09541","url":null,"abstract":"Automated and high-throughput quantum chemical investigations into chemical\u0000processes have become feasible in great detail and broad scope. This results in\u0000an increase in complexity of the tasks and in the amount of generated data. An\u0000efficient and intuitive way for an operator to interact with these data and to\u0000steer virtual experiments is required. Here, we introduce Heron, a graphical\u0000user interface that allows for advanced human-machine interactions with quantum\u0000chemical exploration campaigns into molecular structure and reactivity. Heron\u0000offers access to interactive and automated explorations of chemical reactions\u0000with standard electronic structure modules, haptic force feedback, microkinetic\u0000modeling, and refinement of data by automated correlated calculations including\u0000black-box complete active space calculations. It is tailored to the exploration\u0000and analysis of vast chemical reaction networks. We show how interoperable\u0000modules enable advanced workflows and pave the way for routine\u0000low-entrance-barrier access to advanced modeling techniques.","PeriodicalId":501065,"journal":{"name":"arXiv - PHYS - Data Analysis, Statistics and Probability","volume":"93 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141500982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A minimalistic and general weighted averaging method for inconsistent data 针对不一致数据的简约通用加权平均法

arXiv - PHYS - Data Analysis, Statistics and Probability Pub Date : 2024-06-12 DOI: arxiv-2406.08293

Martino Trassinelli, Marleen Maxton

{"title":"A minimalistic and general weighted averaging method for inconsistent data","authors":"Martino Trassinelli, Marleen Maxton","doi":"arxiv-2406.08293","DOIUrl":"https://doi.org/arxiv-2406.08293","url":null,"abstract":"The weighted average of inconsistent data is a common and tedious problem\u0000that many scientists have encountered. The standard weighted average is not\u0000recommended for these cases, and different alternative methods are proposed in\u0000the literature. Here, we introduce a new method based on Bayesian statistics\u0000for a broad application that keeps the number of assumptions to a minimum. The\u0000uncertainty associated with each input value is considered just a lower bound\u0000of the true unknown uncertainty. By assuming a non-informative (Jeffreys')\u0000prior for true uncertainty and marginalising over its value, a modified\u0000Gaussian distribution is obtained with smoothly decreasing wings, which allows\u0000for a better treatment of scattered data and outliers. The proposed method is\u0000tested on a series of data sets: simulations, CODATA recommended value of the\u0000Newtonian gravitational constant, and some particle properties from the\u0000Particle Data Group, including the proton charge radius and the mass of the W\u0000boson. For the latter in particular, contrary to other works, our prediction\u0000lies in good agreement with the Standard Model. A freely available Python\u0000library is also provided for a simple implementation of our averaging method.","PeriodicalId":501065,"journal":{"name":"arXiv - PHYS - Data Analysis, Statistics and Probability","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141500984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On the archetypal `flavours', indices and teleconnections of ENSO revealed by global sea surface temperatures 全球海面温度揭示的厄尔尼诺/南方涛动的原型 "色彩"、指数和远距离联系

arXiv - PHYS - Data Analysis, Statistics and Probability Pub Date : 2024-06-12 DOI: arxiv-2406.08694

Didier P. Monselesan, James S. Risbey, Benoit Legresy, Sophie Cravatte, Bastien Pagli, Takeshi Izumo, Christopher C. Chapman, Mandy Freund, Abdelwaheb Hannachi, Damien Irving, P. Jyoteeshkumar Reddy, Doug Richardson, Dougal T. Squire, Carly R. Tozer

{"title":"On the archetypal `flavours', indices and teleconnections of ENSO revealed by global sea surface temperatures","authors":"Didier P. Monselesan, James S. Risbey, Benoit Legresy, Sophie Cravatte, Bastien Pagli, Takeshi Izumo, Christopher C. Chapman, Mandy Freund, Abdelwaheb Hannachi, Damien Irving, P. Jyoteeshkumar Reddy, Doug Richardson, Dougal T. Squire, Carly R. Tozer","doi":"arxiv-2406.08694","DOIUrl":"https://doi.org/arxiv-2406.08694","url":null,"abstract":"El Ni~no-Southern Oscillation global (ENSO) imprint on sea surface\u0000temperature comes in many guises. To identify its tropical fingerprints and\u0000impacts on the rest of the climate system, we propose a global approach based\u0000on archetypal analysis (AA), a pattern recognition method based on the\u0000identification of extreme configurations in the dataset under investigation.\u0000Relying on detrended sea surface temperature monthly anomalies over the 1982 to\u00002022 period, the technique recovers central and eastern Pacific ENSO types\u0000identified by more traditional methods and allows one to hierarchically add\u0000extra flavours and nuances to both persistent and transient phases of the\u0000phenomenon. Archetypal patterns found compare favorably to phase identification\u0000from K-means, fuzzy C-means and recently published network-based\u0000machine-learning algorithms. The AA implementation is modified for the\u0000identification of ENSO phases in sub-seasonal-to-seasonal prediction systems\u0000and complements current alert systems in characterising the diversity of ENSO\u0000and its teleconnections. Tropical and extra-tropical teleconnection composites\u0000from various oceanic and atmospheric fields derived from the analysis are shown\u0000to be robust and physically relevant. Extending AA to sub-surface ocean fields\u0000improves the discrimination between phases when the characterisation of ENSO\u0000based on sea surface temperature is uncertain. We show that AA on detrended\u0000sea-level monthly anomalies provides a clearer expression of ENSO types.","PeriodicalId":501065,"journal":{"name":"arXiv - PHYS - Data Analysis, Statistics and Probability","volume":"76 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141500983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative Analysis of $k$-essence and Quintessence Scalar Field Models: A Data Analysis Approach k$-essence和Quintessence标量场模型的比较分析：数据分析方法

arXiv - PHYS - Data Analysis, Statistics and Probability Pub Date : 2024-06-11 DOI: arxiv-2406.07179

Saddam Hussain, Sarath Nelleri, Kaushik Bhattacharya

引用次数: 0

Experimental verification of the optimal fingerprint method for detecting climate change 检测气候变化的最佳指纹法的实验验证

arXiv - PHYS - Data Analysis, Statistics and Probability Pub Date : 2024-06-11 DOI: arxiv-2406.11879

Jinbo Hu, Hong Yuan, Letian Chen, Nan Zhao, C. P. Sun

引用次数: 0

Binary asteroid candidates in Gaia DR3 astrometry 盖亚DR3天体测量中的候选双小行星

arXiv - PHYS - Data Analysis, Statistics and Probability Pub Date : 2024-06-11 DOI: arxiv-2406.07195

Luana Liberato, Paolo Tanga, David Mary, Kate Minker, Benoit Carry, Federica Spoto, Przemyslaw Bartczak, Bruno Sicardy, Dagmara Oszkiewicz, Josselin Desmars

{"title":"Binary asteroid candidates in Gaia DR3 astrometry","authors":"Luana Liberato, Paolo Tanga, David Mary, Kate Minker, Benoit Carry, Federica Spoto, Przemyslaw Bartczak, Bruno Sicardy, Dagmara Oszkiewicz, Josselin Desmars","doi":"arxiv-2406.07195","DOIUrl":"https://doi.org/arxiv-2406.07195","url":null,"abstract":"Asteroids with companions constitute an excellent sample for studying the\u0000collisional and dynamical evolution of minor planets. The currently known\u0000binary population were discovered by different complementary techniques that\u0000produce, for the moment, a strongly biased distribution, especially in a range\u0000of intermediate asteroid sizes (approximately 20 to 100 km) where both mutual\u0000photometric events and high-resolution adaptive optic imaging are poorly\u0000efficient. A totally independent technique of binary asteroid discovery, based\u0000on astrometry, can help to reveal new binary systems and populate a range of\u0000sizes and separations that remain nearly unexplored. In this work, we describe\u0000a dedicated period detection method and its results for the Gaia DR3 data set.\u0000This method looks for the presence of a periodic signature in the orbit\u0000post-fit residuals. After conservative filtering and validation based on\u0000statistical and physical criteria, we are able to present a first sample of\u0000astrometric binary candidates, to be confirmed by other observation techniques\u0000such as photometric light curves and stellar occultations.","PeriodicalId":501065,"journal":{"name":"arXiv - PHYS - Data Analysis, Statistics and Probability","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141500985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fisher's Mirage: Noise Tightening of Cosmological Constraints in Simulation-Based Inference 费雪的幻影：基于模拟推断的宇宙学约束的噪声紧缩

arXiv - PHYS - Data Analysis, Statistics and Probability Pub Date : 2024-06-10 DOI: arxiv-2406.06067

Christopher Wilson, Rachel bean

{"title":"Fisher's Mirage: Noise Tightening of Cosmological Constraints in Simulation-Based Inference","authors":"Christopher Wilson, Rachel bean","doi":"arxiv-2406.06067","DOIUrl":"https://doi.org/arxiv-2406.06067","url":null,"abstract":"We systematically analyze the implications of statistical noise within\u0000numerical derivatives on simulation-based Fisher forecasts for large scale\u0000structure surveys. Noisy numerical derivatives resulting from a finite number\u0000of simulations, $N_{sims}$, act to bias the associated Fisher forecast such\u0000that the resulting marginalized constraints can be significantly tighter than\u0000the noise-free limit. We show the source of this effect can be traced to the\u0000influence of the noise on the marginalization process. Parameters such as the\u0000neutrino mass, $M$, for which higher-order forward differentiation schemes are\u0000commonly used, are more prone to noise; the predicted constraints can be akin\u0000to those purely from a random instance of statistical noise even using\u0000$(1mathrm{Gpc}/h)^{3}$ simulations with $N_{sims}=500$ realizations. We\u0000demonstrate how derivative noise can artificially reduce parameter degeneracies\u0000and seemingly null the effects of adding nuisance parameters to the forecast,\u0000such as HOD fitting parameters. We mathematically characterize these effects\u0000through a full statistical analysis, and demonstrate how confidence intervals\u0000for the true noise-free, $N_{sims} rightarrow infty$, Fisher constraints can\u0000be recovered even when noise comprises a consequential component of the\u0000measured signal. The findings and approaches developed here are important for\u0000ensuring simulation-based analyses can be accurately used to assess upcoming\u0000survey capabilities.","PeriodicalId":501065,"journal":{"name":"arXiv - PHYS - Data Analysis, Statistics and Probability","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141500995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Time-series-analysis-based detection of critical transitions in real-world non-autonomous systems 基于时间序列分析的真实世界非自主系统关键转换检测

arXiv - PHYS - Data Analysis, Statistics and Probability Pub Date : 2024-06-07 DOI: arxiv-2406.05195

Klaus Lehnertz

引用次数: 0

Generative Diffusion Models for Fast Simulations of Particle Collisions at CERN 用于欧洲核子研究中心粒子碰撞快速模拟的生成扩散模型

arXiv - PHYS - Data Analysis, Statistics and Probability Pub Date : 2024-06-05 DOI: arxiv-2406.03233

Mikołaj Kita, Jan Dubiński, Przemysław Rokita, Kamil Deja

引用次数: 0

Precise interpretations of traditional fine-tuning measures 传统微调措施的精确解释

arXiv - PHYS - Data Analysis, Statistics and Probability Pub Date : 2024-06-05 DOI: arxiv-2406.03533

Andrew Fowlie, Gonzalo Herrera

引用次数: 0