Articles tagged with Statistical Mechanics
Researchers at Institute of Science Tokyo have discovered a stable superfluid that inherently hosts singularities known as exceptional points. The study reveals how dissipation can stabilize this unique superfluid phase, which features a finite order parameter and emerges deep inside a strongly interacting phase.
A new paper proposes a way to calculate the thermodynamic costs of metabolic processes, ranking them according to their biological efficiency. The method estimates the improbability of a network behaving in a certain way, considering maintenance and restriction costs.
A new mathematical framework, STIV, can predict larger-scale effects like proteins unfolding and crystals forming without costly simulations or experiments. The framework solves a 40-year-old problem in phase-field modeling, allowing for the design of smarter medicines and materials.
Researchers at Pohang University of Science & Technology experimentally demonstrated the existence of nanometer-sized liquid clusters in supercritical fluids, overturning the prevailing notion of a single phase. These clusters persisted for up to an hour and have significant implications for industrial processes and natural environments.
UC San Diego researchers Guru K. Jayasingh and Nigel Goldenfeld have predicted that a pipe's curvature can lead to a discontinuous turbulent transition beyond a critical flow velocity. This phenomenon is mathematically equivalent to the freezing of water, leveraging tricritical directed percolation theory.
A research team led by Prof. PAN Ding and Dr. LI Shuo-Hui has developed a novel direct sampling method based on deep generative models for statistical mechanics. This method enables efficient sampling of the Boltzmann distribution across a continuous temperature range, overcoming energy barriers in simulations.
A new study applies network analysis to large-scale data from the French labor market, identifying four main clusters: diffusers, channels, hubs, and condensers. Diffuser occupations offer wide exit opportunities but are hard to enter, while channels and hubs face accessibility issues.
Mathematicians at University of Leicester applied statistical mechanics to detect human-made and natural causes of climate change, enabling early warnings of potential disasters. The theory provides a more advanced understanding of climate mechanisms driving change.
A new study by an international team, including MIT and CNRS, observed that similarities exist between the behavior of birds in flight and physical systems. The research suggests that the transition from disorder to coordination is not as different between particles and biological elements as previously thought.
A team of researchers led by Nigel Goldenfeld and Björn Hof used statistical mechanics to study turbulence in fluid flows. They discovered that the transitions between laminar and turbulent flows occur through a non-equilibrium phase transition, known as directed percolation, at the critical point of the transition.
A mathematical model developed by Alexandre Solon and Eric Bertin describes the movement of particles in situations similar to cars on a road or bacteria attracted to a nutrient source. The model identifies conditions that favor traffic jams, including high vehicle density and driver inertia.
Researchers at the University of Oldenburg have developed a new statistical model that accurately describes wind turbulence and generates fully three-dimensional wind fields using limited measurement points. This breakthrough enables precise wind turbine load estimation and improves wind farm planning, with applications in various fiel...
Research by Kirill Kavokin found that around 100 hair cells in an animal's inner ear can act as effective biological compass needles, allowing them to detect the magnetic field. This discovery could bring biologists closer to understanding the origins of magnetoreception and identifying mechanisms responsible.
A mathematical enigma, the Riemann conjecture, has been unraveled thanks to a new approach from statistical physics. The solution lies in chaotic motions and probability laws that regulate them.
Joel L. Lebowitz, director of the Center for Mathematical Sciences Research at Rutgers University, has been awarded the 2021 Dannie Heineman Prize for Mathematical Physics for his significant contributions to nonequilibrium statistical mechanics. His work investigates how macroscopic systems behave dynamically in a nonequilibrium state.
Researchers found that the nature of the boundary at which an antiferromagnet transitions to disorder depends on its lattice arrangement. Calculations showed subtle differences in transition points between honeycomb and square lattices.
A new study using statistical mechanics improves climate prediction accuracy for IPCC-class models, bridging gap between scenarios and models. This approach enables real-time scenario construction and facilitates the assessment of tipping points, a crucial aspect of understanding climate change.
Researchers from Trinity College Dublin used supercomputers to simulate quantum systems and found a deep link between entanglement and thermalisation. The study provides new insights into the fundamental process of thermalisation and its relationship with quantum mechanics.
Researchers introduce concept of 'live' process emerging from interactions between molecules and environment, identifying earliest hallmark of life. They suggest this process could lead to emergence of complex living organisms with characteristics currently known.
At temperatures near absolute zero, systems of atoms violate basic laws of statistical mechanics and thermodynamics. A novel non-equilibrium state, coined as dynamical glass phase, is observed where energy is not evenly distributed, leading to a new understanding of complex systems.
Computational statistical mechanics was born from numerical models of fluids developed in the 1950s, initially as a pet project by physicists. These Monte Carlo and Molecular Dynamics simulations were later confirmed through clever applications of importance sampling, proving reliable evidence for describing matter.
Researchers developed a novel approach to solve difficult computational problems using statistical mechanics and reversible logic gates, avoiding phase transitions that slow down the process. The vertex model can be applied to machine learning, circuit optimization, and other major computational challenges.
Researchers analyzed conflicts within a captive community of macaque monkeys to understand how agitated individuals can trigger large-scale brawls. They found that a small number of agitated monkeys can destabilize the system, but individual differences among group members may allow for more controlled distance from criticality.
Scientists from Argonne National Laboratory have developed a way to reconcile two fundamentally different pictures of reality in statistical mechanics. The new approach provides a general and exact solution for the density of states, which is essential for understanding system behavior.
HongKun Zhang will use the $100,000 award to work with colleagues in France and St. Louis on a mathematical conjecture arising in statistical mechanics. Her research aims to improve conceptual understanding of physical systems and predict their behavior.
Research by physics professor Victor Yakovenko links income inequality with bursting financial bubbles. He models income distribution using statistical physics, finding a long tail in the upper 3% of incomes that correlates with investment downturns.
Rutgers Professor Joel Lebowitz is recognized for his tireless personal activism to secure basic freedoms and ensure scientists' ability to practice their professions openly. He has improved society's quality of life, demonstrated outstanding teaching, and led the quest for international human rights or peace.
H. Eugene Stanley is honored for his innovative and original research on disordered systems, aggregation, and phase transitions. His work has also applied to complex networks, including those related to biology and terrorism.