Popular Science: They Revealed the Mystery Behind "Complex Physical System"——Interpretation of the 2021 Nobel Prize in Physics
Xinhua News Agency, Beijing, October 5 (Reporter Peng Qian) There are many "complex systems" in the world of physics, ranging from variable weather to the movement of atoms in metals... They are chaotic and random, which is hard to imagine.
In 2021, the Nobel Prize in Physics was awarded to three scientists in recognition of their "groundbreaking contributions to the understanding of complex physical systems."
A complex system that is vital to mankind is our earth’s climate.
The work of Japanese-American scientist Manabe Shuro and German scientist Klaus Hasselman laid a solid scientific foundation for human understanding of climate.
Nowadays, the recognition that carbon dioxide and other greenhouse gases are the "culprit" that causes the earth's atmosphere to warm up is well known to the public, but it is Shuro Manabe who demonstrates how the increase in the concentration of carbon dioxide in the atmosphere can lead to the increase in the temperature of the earth's surface.
In the 1960s, he led the development of physical models of the earth's climate and was the first to explore the interaction between radiation balance and vertical air mass transportation. His work laid the foundation for the establishment of climate models.
Contemporary climate models are based on the laws of physics and evolved from weather prediction models.
Weather is described by meteorological indicators such as temperature, precipitation, wind or clouds, and is affected by ocean and land events. Climate models are based on statistical attributes calculated by weather, such as average values, standard deviations, and highest and lowest measured values.
For example, the climate model cannot clearly tell us the weather in Beijing in December next year, but it can tell us the average temperature and rainfall in Beijing that month.
Climate models are not only helpful for understanding climate, but also for understanding global warming caused by humans.
To understand how increased levels of carbon dioxide lead to higher temperatures, Shuro Manabe included the vertical transport of air masses due to convection and the latent heat of water vapor.
To facilitate calculations, he constructed a one-dimensional model that went 40 kilometers deep into the atmosphere and tested the model by changing the concentration of gas in the atmosphere.
He found that oxygen and nitrogen have a negligible effect on the surface temperature, while the effect of carbon dioxide is obvious: when the level of carbon dioxide doubles, the global temperature rises by more than 2 degrees Celsius.
Weather is a classic example of a chaotic and changeable system. Why are climate models still reliable?
About 10 years after Manabe Shuro's research, Klaus Hasselman created a model that relates weather and climate to answer this question.
Hasselman incorporated chaotic and changing weather phenomena as rapidly changing noise into his calculations and proved how this noise affects the climate, thus laying a solid scientific foundation for long-term climate forecasting.
Inspired by Einstein's theory of Brownian motion, he created a stochastic climate model that proved that a rapidly changing atmosphere actually causes the ocean to change slowly.
Hasselman has also developed methods that can identify human impacts on the climate system.
He found that climate models, observations and theoretical considerations all contained sufficient information about the characteristics of noise and signals.
For example, changes in solar radiation, volcanic-related particles, or greenhouse gas levels leave unique signals and marks that can be separated.
This imprint recognition method can also be applied to study the impact of humans on the climate system, clearing obstacles for further research on climate change.
Compared with Shuro Manabe and Hasselman, the research of Italian scientist George Parisi is more focused on the micro-scale.
Around 1980, he discovered how obvious random phenomena are governed by secret laws, laying the cornerstone of the theory of complex systems.
Parisi's research is closely related to an interesting concept-"spin glass".
This is not a kind of glass, but a metastable state of magnetic alloy materials.
"Spin glass" is an ultra-complex and chaotic system. If we observe the movement of atoms in a "spin glass" alloy material, we will find that iron atoms and copper atoms are randomly mixed.
The iron atom, which accounts for a small proportion of the material, changes the magnetic properties of the entire material in a puzzling way. Each iron atom is equivalent to a small magnet, that is, a "spin", and is also affected by other iron atoms around it.
In ordinary magnets, all "spins" point in the same direction, while in "spin glass", they are "frustrated". Some "spins" try to point in the same direction, while others point in the opposite direction. direction.
"Studying'spin glass' is like watching the human tragedy written by Shakespeare," Parisi said. "If you want to make friends with two people at the same time, but they hate each other, it's frustrating."
"Spin glass" provides a physical model for studying complex systems.
In 1979, Parisi made a breakthrough, successfully using a mathematical tool called "duplicate trick" to describe the "spin glass" problem.
This method was later used in many complex system studies.
Parisi’s pioneering discovery made it possible to understand and describe many different, apparently completely random, complex materials and phenomena. It not only had a profound impact on physics, but also brought research in the fields of mathematics, biology, neuroscience, and machine learning. Come enlightenment.