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Mark Newman
Born
Alma mater Merton College, Oxford
Scientific career
Fields Physics
Institutions University of Michigan
Santa Fe Institute
Doctoral advisor David Sherrington

Mark Newman is a British physicist and a special professor of Physics at the University of Michigan. He is also part of the Santa Fe Institute. He is well-known for his big ideas in complex systems and complex networks. Because of his work, he won the Lagrange Prize in 2014 and the APS Kadanoff Prize in 2024.

Mark Newman's Journey

Mark Newman grew up in Bristol, England. He went to Bristol Cathedral School. He then studied physics at the University of Oxford. There, he earned both his first degree and his PhD.

After finishing his studies, he moved to the United States. He did research first at Cornell University. Later, he worked at the Santa Fe Institute. In 2002, Newman joined the University of Michigan. Today, he is a distinguished professor there. He also teaches at the university's Center for the Study of Complex Systems.

Understanding Complex Networks

Professor Newman is famous for his research on complex networks. Think of a network like a giant web. It connects many different things. For example, social media is a network of friends. The internet is a network of computers.

He studied how these networks are built. He looked at how they behave. Some of his key ideas include:

  • Random graph theory: This helps us understand networks where connections happen by chance.
  • Assortative mixing: This is about how things in a network like to connect with similar things. For example, smart kids might hang out with other smart kids.
  • Community structure: This looks at groups or "communities" within a network. Imagine friend groups in a school.
  • Percolation theory: This helps us understand how things spread through a network. It could be water through coffee grounds or information online.

He also studied how scientists work together. He looked at how diseases spread through networks. This is called network epidemiology.

Early Discoveries

Early in his career, he worked with Steven Strogatz and Duncan Watts. They created the "configuration model." This is a basic model for understanding networks. It uses math to predict how networks will look.

Around the same time, he helped make "community structure" popular. This idea helps find groups within networks. He also studied how things mix in networks. He worked with Michelle Girvan on this.

Networks and Health

In network epidemiology, he studied how diseases spread. He looked at how the SIR model (which tracks Susceptible, Infected, and Recovered people) connects to percolation theory. He also applied his ideas to real infections. These included SARS, pneumonia, and group B strep.

Later Research

More recently, he has looked at other areas. These include "spectral graph theory." This uses math to study network properties. He also works on "network reconstruction." This is about figuring out how a network is built.

Beyond Networks

Professor Newman has also worked on other topics in statistical physics. This field uses math to understand large systems. He helped create the Newman-Ziff algorithm. This is a computer method for studying percolation systems.

He has published papers in many different fields. These include mathematics, computer science, and biology. He has also written about ecology, epidemiology, and sociology.

Power-Law Distributions

He has studied "power-law distributions." These are special patterns found in many systems. They show up in human populations and earthquakes. They are also seen in spoken languages and solar flares.

With Aaron Clauset and Cosma Shalizi, he created ways to study these patterns. They checked if certain behaviors really followed a power law. Sometimes they confirmed it, sometimes they showed it was not true.

Mapping the World

He also invented a way to make special maps called cartograms. He did this with Michael Gastner. These maps change the size of places based on data. For example, a country might look bigger if it has more people. Their maps became famous after the 2004 US presidential election. They showed the election results in a new way.

Impact of His Work

Professor Newman's work is very important. Many other scientists use and refer to his research. A study in 2019 ranked him very high. It said he had one of the highest impacts of any active scientist in the world. In 2021, he was named a Clarivate Citation Laureate. This award recognizes scientists whose work is as important as Nobel Prize winners. His 2003 paper "The structure and function of complex networks" was the most cited math paper for ten years.

Awards and Honors

Mark Newman has received many awards and honors. These show how important his work is.

He won the 2014 Lagrange Prize from the ISI Foundation. He also received the 2021 Euler Award from the Network Science Society. In 2024, he won the Leo P. Kadanoff Prize from the American Physical Society.

See also

  • Complex network
  • Social network
  • Random graph
  • Assortative mixing
  • Community structure
  • Percolation theory
  • Cartogram

Selected publications

Books

  • Networks: An Introduction. Oxford University Press, 2010. Second edition, September 2018. ISBN: 978-0198805090.
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