Collaborating on a wikibook on non-linear dynamics in accelerator physics:
Guide to non-linear dynamics in accelerator physics
Nice to just start getting some of this material out there.
Saturday, February 21, 2009
Monday, February 16, 2009
working with focussed people
Scientists are often people with very narrow focus. They like for a problem to be defined for them externally, and then within those contexts, use all their energy and creativity to find a solution.
This can go wrong when there is no clear direction to go in. People are so anxious to get to work. They want to create big things and just go go go. But it may be that the center doesn't hold in all this. That hard work just creates heat. And sometimes organizations and environments perpetuate this by rewarding hard work in itself. This is the case if the organization doesn't have a good grasp on what it is trying to do, or if it underestimates the difficulty or misunderstands the foundations of some of the work being done. Then people rise to power by simply making a lot of noise, pointing out flaws in others and making very confident sounding statements.
This can go wrong when there is no clear direction to go in. People are so anxious to get to work. They want to create big things and just go go go. But it may be that the center doesn't hold in all this. That hard work just creates heat. And sometimes organizations and environments perpetuate this by rewarding hard work in itself. This is the case if the organization doesn't have a good grasp on what it is trying to do, or if it underestimates the difficulty or misunderstands the foundations of some of the work being done. Then people rise to power by simply making a lot of noise, pointing out flaws in others and making very confident sounding statements.
Saturday, February 07, 2009
deceleration
I sometimes feel stuck in accelerator physics. I am running computer codes, reading papers and thinking about particles in storage rings that have been accelerated up to high energies. The machine I am working on for example, has electrons with energies of 3 GeV. This corresponds to a relativistic factor gamma of around 6000. Its a strange phenomenon to work at these extremes. Its not very grounded. There is not a feeling that you really understand things.
One of the aspects I've studied have been off-momentum dynamics. Whether particles with slightly different energies or momenta will still stay stable. Particles scattering for example causes a change in their energy and this can cause the particles to be lost.
As I finally start thinking about the relevant equations for off-energy particles, I imagine the deceleration process, the returning of these electrons to rest.
Even electrons themselves are hard to picture, and the whole field has an air of unreality to it.
I guess it says I've been too much of a theorist.
One of the aspects I've studied have been off-momentum dynamics. Whether particles with slightly different energies or momenta will still stay stable. Particles scattering for example causes a change in their energy and this can cause the particles to be lost.
As I finally start thinking about the relevant equations for off-energy particles, I imagine the deceleration process, the returning of these electrons to rest.
Even electrons themselves are hard to picture, and the whole field has an air of unreality to it.
I guess it says I've been too much of a theorist.
Wednesday, February 04, 2009
value of analysis
What is the value of finding simple formulas to explain things?
Our minds, in the midst of this computerized landscape, sometimes seem small and insignificant.
If a program exists to simulate a system, what is the value of searching for simple ways of looking at it? One answer is that it cuts down on the number of cases one needs to simulate. Getting at the important parameters limits and sharpens the questions and makes on more effective at using the simulation. But what if one can somehow ask the computer to do this? To write such a nice interface to the code that new structures are created based on results from running the code.
The research topic I'm involved in has a funny history with computation. I think that some of the people involved in the early days had something against mathematical reasoning, and the slow process of analysis. One can try to guess at the reasons. Perhaps they'd observed too many mathematicians or theorists making grand statements on practical problems where the methods were simply inadequate and did not actually solve the problem. Or maybe they were not great analysts themselves and just trying to keep the power in their own hands. Regardless, the closing of the SSC precipitated a battle that is still going today between computation and analysis. There is excess on both sides. The theoretical structures one sees are overly grandiose. There are lie algebras and differential algebras and non-standard analysis and geometrical concepts such as tensors and fiber bundles. These are spoken of both with reverence and spite. Those who invoke such concepts either are trying to appease those theorists who they admire or prevent people from thinking critically and trap them into a self-serving view. Some of the original theorists had good motivations and indeed a broader set of questions they were looking at where such abstraction may have been helpful. On the computing side, one sees object oriented computing concepts such as polymorphism, linked lists, discrete algorithmic type approaches, control theory, optimization, SVD, model theory.
Viewing physics from an information theory, algorithmic approach. It sounds modern and laudable in some sense, but behind it is a desire to kill analysis.
This snake's nest of buggy concepts and software in the end often solves the problems good enough to get by. But one sacrafices understandability in entering this field. One speaks of minimizing terms and higher order calculations where exactly what kinds of objects these terms are members of and sometimes even what is meant by order is typically murky. It resembles a religious cult or a radical political group more than solid physics. But the rhetoric is getting old.
So I've gotten a bit specific here. I meant to try to explore the value of analysis. I feel that clear analysis is the only way out of this mess, but just what that means and whether it is adequate is not always clear.
Our minds, in the midst of this computerized landscape, sometimes seem small and insignificant.
If a program exists to simulate a system, what is the value of searching for simple ways of looking at it? One answer is that it cuts down on the number of cases one needs to simulate. Getting at the important parameters limits and sharpens the questions and makes on more effective at using the simulation. But what if one can somehow ask the computer to do this? To write such a nice interface to the code that new structures are created based on results from running the code.
The research topic I'm involved in has a funny history with computation. I think that some of the people involved in the early days had something against mathematical reasoning, and the slow process of analysis. One can try to guess at the reasons. Perhaps they'd observed too many mathematicians or theorists making grand statements on practical problems where the methods were simply inadequate and did not actually solve the problem. Or maybe they were not great analysts themselves and just trying to keep the power in their own hands. Regardless, the closing of the SSC precipitated a battle that is still going today between computation and analysis. There is excess on both sides. The theoretical structures one sees are overly grandiose. There are lie algebras and differential algebras and non-standard analysis and geometrical concepts such as tensors and fiber bundles. These are spoken of both with reverence and spite. Those who invoke such concepts either are trying to appease those theorists who they admire or prevent people from thinking critically and trap them into a self-serving view. Some of the original theorists had good motivations and indeed a broader set of questions they were looking at where such abstraction may have been helpful. On the computing side, one sees object oriented computing concepts such as polymorphism, linked lists, discrete algorithmic type approaches, control theory, optimization, SVD, model theory.
Viewing physics from an information theory, algorithmic approach. It sounds modern and laudable in some sense, but behind it is a desire to kill analysis.
This snake's nest of buggy concepts and software in the end often solves the problems good enough to get by. But one sacrafices understandability in entering this field. One speaks of minimizing terms and higher order calculations where exactly what kinds of objects these terms are members of and sometimes even what is meant by order is typically murky. It resembles a religious cult or a radical political group more than solid physics. But the rhetoric is getting old.
So I've gotten a bit specific here. I meant to try to explore the value of analysis. I feel that clear analysis is the only way out of this mess, but just what that means and whether it is adequate is not always clear.
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