Rainbow Simulation - Water Droplets

Researchers at UC San Diego have been working on creating simulations that accurately model the formation of rainbows. In their news releases and presentations they talk about the physics behind rainbow creation and in particular the new discoveries that have been made about rainbows as a result of their work. Here is a quote from a press release:

"Computer scientists at UC San Diego, who set out to simulate all rainbows found in nature, wound up answering  questions about the physics of rainbows as well. The scientists recreated a wide variety of rainbows – primary rainbows, secondary rainbows, redbows that form at sunset and cloudbows that form on foggy days – by using an improved method for simulating how light interacts with water drops of various shapes and sizes. Their new approach even yielded realistic simulations of difficult-to-replicate “twinned” rainbows that split their primary bow in two."

...

"Until now, most simulations of rainbows had assumed that water drops are spherical, which isn’t true for large rain drops, ... researchers have  adopted a completely different approach and developed a more realistic model to recreate rainbows...offer the prospect of a better understanding of real rainbows,”


Stemming from a study of rainbow formation, there is an almost infinite set of topics we can learn more about from looking closely at the  behavior of variously shaped water droplets. Here are a few ideas:

• Weather modeling and forecasting

• Animations in feature films

• Atmospheric behavior on other planets that are found to contain water

• Inspiration for new forms of studio art

• Educational STEM software development

• Frozen food storage behaviors over time

I could go further with my imagination but I'd like to know: What other ideas do you have?

I look forward to hearing your thoughts - you can comment here.


(UCSD Press release)

Interdisciplinary Computing in a Big Way: The Center for Science of Information

If you followed the 3 earlier posts on An Interdisciplinary Puzzle, the Wireless Car, and finally Banana Trucks and Stock Traders, then you know that information theory was at the heart of the discussion. And if you were really curious, and followed the link hint I provided in the last of the posts, then you figured out that there is an exciting body of work in this area going on at: The Center for Science of Information. Their mission is "to advance science and technology through a new quantitative understanding of the representation, communication, and processing of information in biological, social and engineered systems". A mouthful, but a mouthful that hopefully makes sense after reading the other posts.

The Center's web pages contain an incredible amount of information about their interdisciplinary research, teaching and outreach activities. No one institution or discipline could do their work alone; through bringing experts together from across disciplines, they hope to develop new cross-cutting principles governing the storage, compression and transmission of information (examples in the earlier posts!). Nine universities participate in the Center as well as collaborators from a wide range of corporations and industries. In addition, students, undergraduate and graduate, and post-doctoral researchers have the opportunity to become immersed in this cutting edge research. 

I had a fascinating conversation about the Center with Deepak Kumar of Bryn Mawr College. Deepak is the Associate Director of Diversity and Education for the Center, as well as a professor of Computer Science. Even prior to the creation of the Center, he has been teaching interesting interdisciplinary computing courses. One example is an undergraduate course on emergence. Emergent behavior appears everywhere in the natural world and is a perfect topic for demonstrating the utility of computational modeling.

For example, here in Southern California it is amazing to watch a group of Brown Pelicans cruise along in formation just over your head and then almost as one swoop down, realign into a row and ride the wind currents of ocean waves in the surf. They never touch each other or the ocean, although they can be inches from both.

Have you ever watched a flock of birds and wondered why they never crash into one another? I wonder: How do the Pelicans all know when to turn sharply, descend in unison, line up exactly the same distance from each other, and at some point, without apparent reason, rise up together again into the sky? If I watch any one bird, I can identify how it behaves. But somehow, and this is the puzzle, a group behavior emerges. Flocking birds are a classic example of emergent behavior which can be studied through computational modeling and Deepak uses this example in his course.

If birds don't suit your fancy, there are emergent behaviors to be studied computationally in linguistics, social networks, epidemiology (just for starters). Bryn Mawr is a perfect institution to be part of the Center for Information Science team not only because of courses like this, but because they have a  minor in Computational Methods that actively collaborates with departments across the college.

I asked Deepak to tell me more about the role computer scientists play in advancing information theory. He obliged; here are a few things he shared. [I'm going somewhat technical for the rest of this paragraph] For starters, computer scientists understand algorithms and complexity. They know that how a problem is modeled will lead to various algorithms with different complexities. Which one(s) best fit the constraints and goals of the subject matter? A computer scientist can help determine what kind of processor to use, what algorithms to use, all the ins and outs of dynamic problems and dynamic programming. Computer scientists have an expertise in the classification of problems; they can identify a set of problems as of a certain type (e.g. NP-hard) and the relationship between how a problem is modeled and the resultant effect on the model. There is more, but you get the idea.

Next year Deepak will be teaching a course in the Science of Information. This class will bring the work and ideas behind the Center for Science of Information directly to his undergraduate population. The course, and related activities such as internships and mentoring, will provide opportunities for his students to interact with other institutions and personnel on the Center team. Deepak is very excited about running this course; in fact he told me that the most inspiring aspect of his role in Center activities is the opportunity to bring new superstar research to his computing students and to make it outward looking.

It is going to be very interesting to watch how all of this work develops over the next few years. 

Computing and the Reduction of Global Conflict

I came across some creative examples of university faculty who are using computing for societal benefit. I located these faculty through podcasts produced out of New Zealand by "The Sustainable Lens". One faculty member is taking an empirical approach to studying factors that promote peace.

A broadcast from 5/13/11 profiles the work of Juan Pablo Hourcade at the University of Iowa. Hourcade earned his doctorate in Computer Science with a focus in HCI. One of his goals is to convince people in the computing field that computing technologies can be used to reduce global conflict. He recognizes that a key to making the study of peace acceptable is to apply empirical scientific methodologies to the research. There are many aspects of this work. One of the most fascinating is the mining of masses of data to identify factors that increase or decrease the chances of conflict. These data are drawn from a myriad of sources including: demographic, historic, financial and economic, supply chain analysis, social and human condition, gender and inequality, environmental stress, social stress, and consumer behavior data. The power of computing is also leveraged to provide transparency of connections between individuals and transactions.

Computing is used to identify the factor(s) that matter the most in supporting or reducing conflict and are drawn from contemporary and historic sources - some going back several thousand years. Predictive modeling has a role as well. Visualization renders complex results easier to understand (there is a small pun in there by the way). The precision of computing provides the ability to zero in on the interaction of critical factors, providing the all important empirical (rather than philosophical) basis for making large scale policy decisions. Hourcade also discusses at some length implications for personal decision making.

Using known information about human psychology, Hourcade talks about how social media can be actively used to promote compassion - which he claims psychology has shown is key to reducing or altogether avoiding conflict. Social media can be used to bring together people who might see things from different perspectives. Psychology refers to this as reducing personal distance, a proven highly effective method of promoting the "humanization" of those who appear threatening but do not necessarily need to be so.

Although he only touched on the topic in one sentence during the interview, my ears perked up when Hourcade said he saw a role in conflict reduction for electronic voting systems. As I have learned through researching this topic for my book project (here is an earlier post I wrote about internet voting), electronic voting is incredibly controversial and often promotes passionate conflict! I wish there had been more time in the interview to pursue Hourcade's view on the role of electronic voting.

Hourcade made the interesting observation that there has been a significant amount of research in the computing field into ways to improve warfare and very little research aimed at reducing it. Good point.

Why not put the power of computing to work for the cause of global conflict reduction?

Is there any plausible reason not to pursue this line of research?

What ideas do you have about why computing research for peace has not been explored as much as say...economics? (Much of the data comes from the same sources.)

Computing has an Important Role to Play in Earthquake Preparedness and Response

When devastation as large as that currently happening in Japan occurs, it can be hard to know what to say or do. If you are like me, you have been reading the news daily (or more often), caught up in a mix of complicated reactions. This morning for example I watched computer generated weather simulations of possible flow patterns of radioactive contamination (via the BBC).  As the simulation looped over and over I couldn't help but be transfixed by one large multicolored plume as it slid like a mutant amoeba over Southern California. Right here in other words. The colors registered different levels of radiation. Computers generated those simulations and unsettling as they were, I'm glad to be able to see them. It is better to have knowledge from a reliable source than no knowledge, even when that knowledge is based on probabilities and a great deal of the unknown.

I was very grateful for computer science when the recent earthquake struck New Zealand. A friend lives in Christchurch and it was only a matter of a few nerve wracking days before a brief post appeared on Facebook telling all of us that she was ok - no doubt considerably freaked out, but ok. Thank you to the computer scientist creators of social networking.

The situation was very different in 2004 when the tsunami hit Sri Lanka and someone I know was very near the coast. It was over a week before we learned that he and his family were alive. There was no email access, no smart phones, no Facebook page, nothing but waiting and telephone calls to the US State Department (who were terrific by the way). The computing communication infrastructure either was not there to start with or had been completely disabled by the dual natural disasters of earthquake and tsunami.

Watching the developing situation in Japan, the triple disasters unfolding as nuclear contamination possibilities are added to realities of earthquake and tsumani, watching the weather models, I was reminded of the researchers around the world who work full time developing models of earthquake simulation and  who perform seismic hazard analysis. They work on these models so that we can know as much as possible about what can happen, how it can happen, how we can best prepare, where to erect buildings and other structures and how to protect them as best we can.

Developing 3-D and 4-D maps and models are classic computing problems of large scale data analysis: selecting and applying the "best" constraints, knowing that the model you develop will depend upon choices about possible epicenter (location of the earth directly above the underground origin of the earthquake), focal depth (how deep the origin is), magnitude (amount of energy released) and possible paths the seismic waves may follow. There are innumerable factors to include or leave out of this type of model such as local and regional variations, ground type, land masses, rock type...just for starters. It is all about improving probabilities and predictions.

The paths of seismic waves are not always what one might expect. For example, one reason Los Angeles gets hit so hard by some earthquakes on the famous San Andreas fault is because there is a natural "funnel" that directs ground motion directly into the city from a section of the fault well east of the city. Complex modeling and a solid knowledge of the land revealed this important information. 

You have to know your hardware, firmware and software; you have to know how to work with the latest and most sophisticated networks of high performance computing. Operating system, algorithm and programming language optimization. Databases to hold all those data and sophisticated networks to link the distributed grids of computers.

If you have an interest in earth science and scientific computing (you don't need expertise in both - this is where collaboration between fields comes in) then here is an area where you can work to make a difference in people's lives.

An Unusual Computational Science Educator

Sometimes crisis propels an existing passion to the forefront of someone's life. This is the one line explanation of how Shodor was founded 15 years ago to advance science education via computational modeling and simulation.

When I first posted about the Interdisciplinary Computing meeting I attended last week, I made a point of mentioning Bob Panoff. Bob is not only a truly interdisciplinary individual but a great person to talk to. So as soon as I could I pried him away from others so that he could speak to me for this report.

If you haven't already looked at his company web site, before you do so, think about what his company name might mean and why he chose it. Don't peek. We'll come back to that. It says a lot about Bob's attitude towards life and work.

You never know where a conversation with Bob will go. It starts at point X and the next thing you know you are somewhere else entirely. But it all makes sense.

It often starts with some interesting comment or question.  He asked me: Do you know what "Quantitative Emotion" is? Given my background, I started thinking about AI. But that was not what he had in mind. He teaches the answer this way: by sending 8th grade students (approx age 13) out into shopping malls to ask people one of two questions.

"is 40% large or small?" Most people respond "it is large".

"is 2/5 large or small?" Most people respond "it is small".

Hmm.... Changing the representation of data makes people feel differently about what something means. Quantitative Emotion. Interesting....

A post-mall conversation with the students (and me!) leads to discussion of multiple representations, and how to present data in different ways - generally through computation and simulation of that data. Bob is all about computational simulation.

One of Bob's very favorite questions, which he also sprung on me, is: "How do I know that it is true?" 

What? Know what is true? Answer: most anything. How do you know that it is true?

This question underpins much of Shodor's work in developing science education materials. "How do you know?" Computation and simulation provide the means to analyse and answer the question. How did Bob arrive at this central question? While in graduate school he taught himself how to use computational simulations to analyse the interactions between pieces of physics problems and to measure the validity of calculations.

Although not a computer science student, he read as many numerical methods books as he could find, most of which had been written in the pre-computer era. (Part of me wondered just where he found these ancient dusty texts, but we were racing the clock against lunch break so I didn't ask). He taught himself to use computing to apply those numerical methods and solve the physics problems.

Pattern recognition and pattern characterization then fueled his interest in simulations. The more he created simulations the more convinced he became that science education in general could be improved through creating effective simulations. How to choose between different approaches in the lab for example, how to compute the properties of materials such as liquid helium, deuterium and solids with impurities. He refers to himself at that period of his life, when he worked in academia, as a computational physicist. Along the way he worked in a supercomputing center. He spent time looking for commonalities between disciplines and how they did use or could use computing, and he worked to share those ideas with other disciplines. In his spare time he started a group  to improve science education. He started by delivering workshops.

Crisis struck in 1994 when he was told he had a kidney tumor and 6 months to live. At this point he decided to follow his true passion with what time he had left. Abandoning formal academia, he incorporated Shodor and went full steam ahead with computational science simulation with the mission of improving science education at all levels.

Short and Dorky. Bob was once called "SHOrt and DORky" by a student, hence the company name. Of course. Creative and humorous and ready to use whatever comes his way.

15 years later Bob Panoff and Shodor are still at it and highly successful. Bob works full time following his passion for computation in the service of science education. As important, his desire to share his work and ideas land him in places like our meeting. Go Bob.