Tuesday, March 21, 2017

Emergence frames many of the grand challenges and big questions in universities

What are the big questions that people are (or should be) wrestling within universities?
What are the grand intellectual challenges, particularly those that interact with society?

Here are a few. A common feature of those I have chosen is that they involve emergence: complex systems consisting of many interacting components produce new entities and there are multiple scales (whether length, time, energy, the number of entities) involved.

How does one go from microeconomics to macroeconomics?
What is the interaction between individual agents and the surrounding economic order?
A recent series of papers(see here and references therein) have looked at how the concept of emergence played a role in the thinking of Friedrich Hayek.

How does one go from genotype to phenotype?
How do the interactions between many proteins produce a biochemical process in a cell?

The figure above shows a protein interaction network and taken from this review.

How do communities and cultures emerge?
What is the relationship between human agency and social structures?

Public health and epidemics
How do diseases spread and what is the best strategy to stop them?

Computer science
Artificial intelligence.
Recently it was shown how Deep learning can be understood in terms of the renormalisation group.

Community development, international aid, and poverty alleviation
I discussed some of the issues in this post.

Intellectual history
How and when do new ideas become "popular" and accepted?

Climate change

How do you define consciousness?

Some of the issues are covered in the popular book, Emergence: the connected lives of Ants, Brains, Cities, and Software.
Some of these phenomena are related to the physics of networks, including scale-free networks. The most helpful introduction I have read is a Physics Today article by Mark Newman.

Given this common issue of emergence, I think there are some lessons (and possibly techniques) these fields might learn from condensed matter physics. It is arguably the field which has been the most successful at understanding and describing emergent phenomena. I stress that this is not hubris. This success is not because condensed matter theorists are smarter or more capable than people working in other fields. It is because the systems are "simple" enough and the presence (sometimes) of a clear separation of scales that they are more amenable to analysis and controlled experiments.

Some of these lessons are "obvious" to condensed matter physicists. However, I don't think they are necessarily accepted by researchers in other fields.

These are very hard problems, progress is usually slow, and not all questions can be answered.

The limitations of reductionism.
Trying to model everything by computer simulations which include all the degrees of freedom will lead to limited progress and insight.

Find and embrace the separation of scales.
The renormalisation group provides a method to systematically do this. A recent commentary by Ilya Nemenman highlights some recent progress and the associated challenges.

The centrality of concepts.

The importance of critically engaging with experiment and data.
They must be the starting and end point. Concepts, models, and theories have to be constrained and tested by reality.

The value of simple models.
They can give significant insight into the essentials of a problem.

What other big questions and grand challenges involve emergence?

Do you think condensed matter [without hubris] can contribute something?


  1. "Condensed Matter Without Hubris" sounds like a good candidate for a new journal title.....

  2. Regarding your last question: it is my feeling that generally the answer is "no", with the exception of the very few that have a broad enough overview while still being able to go deep enough to truly grasp disparate concepts.
    And with "few" I mean less than 10 in the world.

    For the common researcher, I think it is almost impossible to take this step (- within the boundary conditions of current research climate...).

    And I second Prof. Sholl's remark!

    1. I am not suggesting that most CMP people change fields.

      The goal of the post is much more modest.

      * Point out how there are some interesting similarities.

      * Perhaps encourage CMP to talk to their colleagues in other fields a little more.

      * Dream that an economist or sociologist or ... might try and initiate some discussion with a CMP.

      * Stimulate the gifted few [more than 10 I would say] to consider changing fields. I agree that for many faculty this is extremely difficult or risky. But for a Ph.D student or postdoc, their next position could be in a different field.

  3. 1. Will the quintessential academic return and replace the managerial one?
    2. Will academics return to discussing an entire paper in terms of quality rather than getting obsessed with metrics of a paper.
    3. A vague question. Does the human body have condensed matter ? or what is the condensed matter in biological systems.

  4. I smiled and then groaned at 1. and 2.

    3. There is a lot of soft condensed matter in biological systems.


  5. "The limitations of reductionism.
    Trying to model everything by computer simulations which include all the degrees of freedom will lead to limited progress and insight.

    Find and embrace the separation of scales.
    The renormalisation group provides a method to systematically do this. "

    Isn't RG effectively a reductionism? ;)

    1. I don't see RG as a reductionism, but the opposite. You are use RG to justify an effective Hamiltonian at a higher scale and throw out lots of details.

    2. I get what you mean. But I feel some "unease" with the terminology. Let me explain why.

      I would say: I take my microscopic Hamiltonian (level A), I apply RG and get an effective description at a different scale (level B)

      The causal direction in this case is still

      level A => level B

      I am not aware of any physical theory that reverses this arrow. These scenarios have been discussed however in the philosophy of science, where they are known as "Downward causation". While indeed the typical emergent features appear to be level B => level A, these effects are still mediated by level A and therefore reducible to level A.

      Its true that systems exhibiting emergence are best described on level B, but there is no need for RG in the first place if we are not also interested in what level A looks like.

      In that sense I would argue we are always interested to see a reduction of level B phenomena to those of level A.

      RG is able to provide an explanation for level B physics in terms of level A physics.

    3. Thanks for the come back. It made me think hard. I see your point. However, we need to be careful (or disagree) about what we mean by "explain" and "reduce".

      Consider two concrete examples, critical exponents in classical phase transitions and the Kondo effect. RG is key to understanding each. For the first we start with an Ising model, then derive a Landau-Wilson functional, and then do RG to find fixed points, calculate exponents, and explain universality. I think the RG is the explanation of the exponents (level B) not the Ising model or the GW functional (level A). RG is describing what happens at level B.

      Similarly for the Kondo problem. One starts with the Anderson single impurity model, derives Kondo model, and then does RG and finds there is a strong coupling fixed point. This explains the Kondo effect not the Anderson Hamiltonian.

  6. The Fall of the Faculty: The Rise of the All-Administrative University and Why It Matters
    By Benjamin Ginsberg is a good read. Written by a Prof of Political science is relevant to even science and engineering.