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Shedding light on dark matter

A team of researchers, led by Hagit Shatkay, is developing computational methods to accelerate discovery in astroparticle physics, a crucial step towards understanding dark matter. By analyzing noisy sensor data from an underground experiment, the team aims to detect and identify dark-matter particles.

Order hidden in disorder

Scientists found that amorphous systems converge to hyperuniformity, a hidden order on large scales, as they optimize individual cells' geometrical properties. This discovery has implications for the development of novel materials, including photonic metamaterials and block copolymers.

SourceKarlsruher Institut für Technologie (KIT)·JournalNature Communications·DateApr 3, 2019

Cooler computing through statistical physics?

A team of researchers from the Santa Fe Institute has published a paper on the thermodynamics of computation, which involves elements of statistical physics, computer science, cellular biology, and neurobiology. The study aims to understand how computers process information and reduce energy waste by optimizing computational processes.

SourceSanta Fe Institute·JournalACM SIGACT News·DateJun 20, 2018

Why is it so hot at night in some cities?

Urban heat islands are caused by cities trapping more heat than surrounding areas due to their structure, affecting energy consumption and air quality. Researchers studied 50 cities and found that well-organized cities with straight streets retain more heat at night, leading to increased energy bills in hot climates.

SourceCNRS·JournalPhysical Review Letters·DateMar 12, 2018

Tiny super magnets could be the future of drug delivery

Researchers have discovered a method to control the movement of microscopic crystals, enabling precise targeting of diseased organs for drug delivery. The crystals, which exhibit superparamagnetic properties, can be directed using a magnetic field, opening new applications for improving lives.

SourceElsevier·JournalPhysics Letters A·DateNov 14, 2016

Even physicists are 'afraid' of mathematics

A new study published in New Journal of Physics found that physicists pay less attention to articles with dense mathematical details, indicating real and widespread barriers to scientific communication. The researchers suggest improving clearer presentation of technical work is key to bridging this gap.

SourceUniversity of Exeter·JournalNew Journal of Physics·DateNov 11, 2016

From nanocrystals to earthquakes, solid materials share similar failure characteristics

Researchers discovered that solid materials, including nanocrystals and the Earth's crust, share similar deformation properties due to slip-avalanches. This study enables the transfer of results across different scales and materials, providing new tools for predicting material deformation and hazard prevention.

IUPUI study: Finding Occam's razor in an era of information overload

A new study led by Steve Pressé reveals a preferred strategy for picking mathematical models with the greatest predictive power, emphasizing simplicity and avoiding unnecessary complexity. The study's findings support Occam's razor principle, suggesting that simpler theories are more likely to be correct.

How to be a social climber

Researchers discovered that all individuals are social climbers, as they seek to enhance their social importance through connections with central nodes. In hierarchical societies, this inclination leads to a clear identification of central nodes, resulting in an increasing number of social climbers.

SourceInternational School of Advanced Studies (SISSA)·JournalJournal of Statistical Physics·DateJan 30, 2013

Spurious switching points in traded stock dynamics

A study by Vladimir Filimonov and Didier Sornette challenges the existence of power laws governing stock market volatility, volume, and intertrade times. They found that 'switching points' are actually caused by biased interpretation of market data statistics.

SourceSpringer·JournalThe European Physical Journal B·DateMay 15, 2012

When molecules leave tire tracks

Scientists have created a simple model that can predict the patterns observed in molecular self-organization on surfaces. By combining statistical physics and detailed simulations with images obtained by scanning tunnelling microscopy (STM), researchers were able to formulate a model that can generate a wide variety of patterns, reprod...

Modern physics is critical to global warming research

Researchers like Brad Marston use statistical physics to analyze climate patterns, providing insights into the driving concepts behind global warming. By focusing on the larger mechanisms that drive changes in rainfall, scientists can improve their understanding of climate change and its effects.

SourceBrown University·JournalJournal of the Atmospheric Sciences·DateMar 11, 2008

Creation of a magnetic field in a turbulent fluid

Researchers successfully created a magnetic field in a highly turbulent flow of liquid sodium, exhibiting remarkable similarities with cosmic magnetic fields. This breakthrough advances our understanding of the mechanisms behind the formation of natural magnetic fields.

SourceCNRS·JournalPhysical Review Letters·DateMar 10, 2007

Fractal extremes predict impending breakdowns

Fractal extremes help predict when surfaces will reach critical points of erosion or accumulation, enabling better material designs and reliable devices. The study uses scaling math and extreme-value statistics to model surface growth and erosion processes, providing a more accurate method for predicting these events.

SourceUniversity of Rochester·JournalPhysical Review Letters·DateSep 26, 2001

'Hard' NP-complete computer problems explained

The article explains that 'hard' NP-complete problems are difficult due to discontinuous phase transitions, making them impractical to solve even with moderate-sized inputs. The research suggests exploiting certain properties of these abrupt transitions to make the problems easier by nailing down critical variables.

SourceCornell University·JournalNature·DateAug 12, 1999