Related papers: Generative AI for Validating Physics Laws
The scientific method is the cornerstone of human progress across all branches of the natural and applied sciences, from understanding the human body to explaining how the universe works. The scientific method is based on identifying…
Our interdisciplinary study investigates how effectively U.S. laws confront the challenges posed by Generative AI to human values. Through an analysis of diverse hypothetical scenarios crafted during an expert workshop, we have identified…
Generative artificial intelligence (AI) systems can now reliably solve many standard tasks used in introductory physics courses, producing correct equations, graphs, and explanations. While this capability is often framed as an opportunity…
At any sustained positive growth rate of energy demand, depletion of all terrestrial energy resources, including non-renewable deuterium fusion and renewable solar, occurs within a remarkably compressed period. The time to depletion is…
We introduce an approach for analyzing the responses of dynamical systems to external perturbations that combines score-based generative modeling with the Generalized Fluctuation-Dissipation Theorem (GFDT). The methodology enables accurate…
Generative Artificial Intelligence (gen-AI) is rapidly becoming more integrated into today's classrooms in all ranges of education. In higher education, Gen-AI is often seen as a resource for students, aiding them in drafting outlines,…
Artificial intelligence (AI) systems impose substantial and growing environmental costs, yet transparency about these impacts has declined even as their deployment has accelerated. This paper makes three contributions. First, we collate…
This paper introduces the Future Atmospheric Conditions Training System (FACTS), a novel platform that advances climate resilience education through place-based, adaptive learning experiences. FACTS combines real-time atmospheric data…
We give an exact information-theory treatment of the $n$-dimensional black-body radiation process in a non-extensive scenario. We develop a $q$ generalization of the laws of i) Stefan Boltzmann, ii) Planck, and iii) Wien, and show that…
We develop a data-driven model to map stellar parameters (effective temperature, surface gravity and metallicity) accurately and precisely to broad-band stellar photometry. This model must, and does, simultaneously constrain the…
The detailed simulation of extensive air showers, produced by primary cosmic rays interacting in the atmosphere, is a task that is traditionally undertaken by means of Monte Carlo methods. These processes are computationally intensive,…
High throughput experimentation tools, machine learning (ML) methods, and open material databases are radically changing the way new materials are discovered. From the experimentally driven approach in the past, we are moving quickly…
Massive particle and antiparticle pair production and oscillation on the horizon form a holographic and massive pair plasma state in the Friedman Universe. Via this state, the Einstein cosmology term (dark energy) interacts with matter and…
The gravitational lensing signal produced by a galaxy or a galaxy cluster is determined by its total matter distribution, providing us with a way to directly constrain their dark matter content. State-of-the-art numerical simulations…
We derive a distribution function for the position of a tagged active particle in a slowly varying in space external potential, in a system of interacting active particles. The tagged particle distribution has the form of the Boltzmann…
Artificial intelligence (AI) is regarded as one of the most disruptive technology of the century and with countless applications. What does it mean for radiation protection? This article describes the fundamentals of machine learning (ML)…
Sea subsurface temperature, an essential component of aquatic wildlife, underwater dynamics and heat transfer with the sea surface, is affected by global warming in climate change. Existing research is commonly based on either physics-based…
We conduct an incentivized laboratory experiment to study people's perception of generative artificial intelligence (GenAI) alignment in the context of economic decision-making. Using a panel of economic problems spanning the domains of…
A rigorous thermodynamic analysis has been done at the apparent horizon of a spatially flat Friedmann-Lemaitre-Robertson-Walker universe for the gravitationally induced particle creation scenario with constant specific entropy and an…
Learning-based analysis of images is commonly used in the fields of mobility and robotics for safe environmental motion and interaction. This requires not only object recognition but also the assignment of certain properties to them. With…