Top Mathematics discussions

NishMath - #analysis

@mathoverflow.net //
Researchers are delving into advanced mathematical analysis, focusing on the intricacies of Fourier series and transforms. A key area of investigation involves determining the precise solutions for complex analytical problems. This includes using Fourier analysis to find the exact values of infinite sums, and finding closed-form expressions for integrals. Specifically, they are working with a specific function involving cotangent and an indicator function, applying Fourier transforms to unravel its integral form and also finding the value of sums such as $\sum_{m=-\infty}^\infty \frac{(-1)^m}{(2m-3)(2m-1)(2m+1)}$ and $\sum_{n=0}^\infty \frac{1}{(2n+1)^2}$ using Fourier series techniques.

The research further examines how Fourier analysis enhances understanding of infinite series and integral transformations by looking at the convergence of Fourier series using Dirichlet and Fejér kernels. This exploration demonstrates how Fourier techniques can be used to solve analytical problems. They are also studying the minimization of the total of tails of the Fourier transform of functions that have compact support. This work aims to enhance the use of Fourier analysis in complex mathematical problems.

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References :
  • math.stackexchange.com: Get the exact values of $\sum_{m=-\infty}^\infty \frac{(-1)^m}{(2m-3)(2m-1)(2m+1)}$ and $\sum_{n=0}^\infty \frac{1}{(2n+1)^2}$ using Fourier series
  • medium.com: Fourier Series: Understanding Convergence With Dirichlet and Fejér Kernels
  • math.stackexchange.com: What is the Fourier transform of $x \cot(\pi x/2) 1_{[-1,1]}$?

@mathworld.wolfram.com //
Research is exploring the connections between probability distributions and generalized function distributions, also known as distribution theory. Both concepts use functions and measures, but probability distributions adhere to axioms like non-negativity and normalization, which are not required in generalized function theory. Scientists are looking for structural similarities that go beyond their shared terminology, aiming to potentially bridge these two distinct mathematical areas. The term "distribution" appears in both theories, with probability distributions predating the formal development of generalized function theory.

While probability distributions are defined by axioms including the probability of an event being non-negative and the total probability equal to one, generalized functions, defined as linear functionals acting on test functions, do not share these properties. Generalized functions don't have a normalization requirement. Researchers are investigating if there are more meaningful connections than their reliance on functions or measures, seeking to understand if shared term usage can justify a unification of ideas. It is hoped that discovering behavioral or structural similarities could advance the understanding of both theories.

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References :
  • math.stackexchange.com: What connects the concept of distributions in probability theory and distribution theory?

admin@ICNAAM 2025 //
References: ICNAAM 2025 , medium.com
The International Conference of Numerical Analysis and Applied Mathematics (ICNAAM) 2025 will feature a symposium on Statistical Modeling and Data Analysis. The event, organized by Luis M. Grilo from the University of Évora and the Research Centre for Mathematics and Applications in Portugal, aims to gather researchers from various fields with expertise in statistical models and data analysis. Academics, professionals, and students interested in these areas are encouraged to submit original, unpublished results for peer review.

Applications with real-world data are particularly welcome, spanning disciplines such as Health Sciences, Natural and Life Sciences, Social and Human Sciences, Economics, Engineering, Education, Sports, and Tourism. The conference aims to foster collaboration and knowledge sharing within the international Numerical and Applied Mathematics community. It is organized with the cooperation of the European Society of Computational Methods in Sciences and Engineering (ESCMCE).

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References :
  • ICNAAM 2025: Organizers: Luis M. Grilo, University of Évora (UÉ); Research Centre for Mathematics and Applications (CIMA), UÉ; Portugal
  • medium.com: Statistics for Data Science — Part 5: Advanced Statistical Concepts

@tracyrenee61.medium.com //
Recent discussions have highlighted the importance of several key concepts in probability and statistics, crucial for data science and research. Descriptive measures of association, statistical tools used to quantify the strength and direction of relationships between variables are essential for understanding how changes in one variable impact others. Common measures include Pearson’s correlation coefficient and Chi-squared tests, allowing for the identification of associations between different datasets. This understanding helps in making informed decisions by analyzing the connection between different factors.

Additionally, hypothesis testing, a critical process used to make data-driven decisions, was explored. It determines if observations from data occur by chance or if there is a significant reason. Hypothesis testing involves setting a null hypothesis and an alternative hypothesis then the use of the P-value to measure the evidence for rejecting the null hypothesis. Furthermore, Monte Carlo simulations were presented as a valuable tool for estimating probabilities in scenarios where analytical solutions are complex, such as determining the probability of medians in random number sets. These methods are indispensable for anyone who works with data and needs to make inferences and predictions.

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Math Attack@mathoverflow.net //
References: sci-hub.usualwant.com
Recent discussions in the mathematical community have centered around complex problems in topology and analysis. One such area involves a deep dive into the proof of Cayley's Theorem, specifically within the context of Topological Groups. This research explores the fundamental structures of groups with the additional layer of topological properties, blending abstract algebra with the study of continuity and limits. Additionally, there is an ongoing discussion around the analytic continuation of a particular function which contains a sinc function as well as the polylogarithm and digamma functions, showing the intersection of real and complex analysis.

The challenges also include the calculation of integrals involving the digamma function. The exploration of this particular function’s integral representation is proving useful in approximations of other functions. There's also a practical approach being explored for finding approximate formula for the nth prime, using integral transformations of a function with the digamma function. The discussion also includes using Sci-Hub to provide greater access to research papers and help facilitate collaboration on these advanced mathematical topics.

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