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Satyendra Nath Bose

Satyendra Nath Bose FRS, MP [ 1 ] (/ ˈ b oʊ s / ; [ 4 ] [ a ] 1 January 1894 – 4 February 1974) was an Indian theoretical physicist and mathematician. He is best known for his work on quantum mechanics in the early 1920s, in developing the foundation for Bose–Einstein statistics, and the theory of the Bose–Einstein condensate. A Fellow of the Royal Society, he was awarded India’s second highest civilian award, the Padma Vibhushan, in 1954 by the Government of India. [ 5 ] [ 6 ] [ 7 ]

The eponymous particles class described by Bose’s statistics, bosons, were named by Paul Dirac. [ 8 ] [ 9 ]

A polymath, he had a wide range of interests in varied fields, including physics, mathematics, chemistry, biology, mineralogy, philosophy, arts, literature, and music. He served on many research and development committees in India, after independence. [ 10 ] .

Mathematical approach makes uncertainty in AI quantifiable

How reliable is artificial intelligence, really? An interdisciplinary research team at TU Wien has developed a method that allows for the exact calculation of how reliably a neural network operates within a defined input domain. In other words: It is now possible to mathematically guarantee that certain types of errors will not occur—a crucial step forward for the safe use of AI in sensitive applications.

From smartphones to self-driving cars, AI systems have become an everyday part of our lives. But in applications where safety is critical, one central question arises: Can we guarantee that an AI system won’t make serious mistakes—even when its input varies slightly?

A team from TU Wien—Dr. Andrey Kofnov, Dr. Daniel Kapla, Prof. Efstathia Bura and Prof. Ezio Bartocci—bringing together experts from mathematics, statistics and computer science, has now found a way to analyze neural networks, the brains of AI systems, in such a way that the possible range of outputs can be exactly determined for a given input range—and specific errors can be ruled out with certainty.

3D Time Could Solve Physics’ Biggest Problem, Says Bizarre New Study

Clocks might be far more fundamental to physics than we ever realized.

A new theory suggests what we see around us – from the smallest of quantum actions to the cosmic crawl of entire galaxies – could all be literally a matter of time. Three dimensions of time, in fact.

The basic idea of 3D time isn’t new. But University of Alaska geophysicist Gunther Kletetschka says his mathematical framework is the first to reproduce known properties of the Universe, making it a somewhat serious contender for uniting physics under one consistent model.

Kentucky invests $300,000 in space research to find cures for Alzheimer’s, Parkinson’s and multiple sclerosis

The National Stem Cell Foundation, which is based in Louisville, has been awarded a $3.1 million grant from NASA to continue research on brain cell behavior in space as a way to find treatments and cures for neurogenerative conditions, and Kentucky is investing $300,000 toward the project as part of a 10% match.

Kentucky’s portion was allocated in the 2024 legislative session in Senate Bill 1. The announcement was made Wednesday, March 26 at the Kentucky State Capitol.

Pointing to the space research Kentucky students have done at the Craft Academy for Excellence in Science and Mathematics and NASA’s presence at Morehead State University, Senate President Robert Stivers, R-Manchester, said it was easy for him and his colleagues to support this type of research in hopes of making Kentucky a hub for it.

Navier–Stokes existence and smoothness

The problem concerns the mathematical properties of solutions to the Navier–Stokes equations, a system of partial differential equations that describe the motion of a fluid in space. Solutions to the Navier–Stokes equations are used in many practical applications. However, theoretical understanding of the solutions to these equations is incomplete. In particular, solutions of the Navier–Stokes equations often include turbulence, which remains one of the greatest unsolved problems in physics, despite its immense importance in science and engineering.

Reports in Advances of Physical Sciences

In this paper, the authors propose a three-dimensional time model, arguing that nature itself hints at the need for three temporal dimensions. Why three? Because at three different scales—the quantum world of tiny particles, the realm of everyday physical interactions, and the grand sweep of cosmological evolution—we see patterns that suggest distinct kinds of “temporal flow.” These time layers correspond, intriguingly, to the three generations of fundamental particles in the Standard Model: electrons and their heavier cousins, muons and taus. The model doesn’t just assume these generations—it explains why there are exactly three and even predicts their mass differences using mathematics derived from a “temporal metric.”


This paper introduces a theoretical framework based on three-dimensional time, where the three temporal dimensions emerge from fundamental symmetry requirements. The necessity for exactly three temporal dimensions arises from observed quantum-classical-cosmological transitions that manifest at three distinct scales: Planck-scale quantum phenomena, interaction-scale processes, and cosmological evolution. These temporal scales directly generate three particle generations through eigenvalue equations of the temporal metric, naturally explaining both the number of generations and their mass hierarchy. The framework introduces a metric structure with three temporal and three spatial dimensions, preserving causality and unitarity while extending standard quantum mechanics and field theory.

Scientists Crack the 500-Million-Year-Old Code That Controls Your Immune System

A collaborative team from Penn Medicine and Penn Engineering has uncovered the mathematical principles behind a 500-million-year-old protein network that determines whether foreign materials are recognized as friend or foe. How does your body tell the difference between friendly visitors, like me