I just started up a new wiki called AstroBaki. The main reason I did this was that my MoinMoin AIPY wiki was clunky to use and was getting spammed lots. I switched to the MediaWiki engine, which has better automated control over these kinds of things. As an added bonus, MediaWiki has support for latex math. This got me thinking...
When I started grad school, I had a hard time transitioning from feeling like I was producing and contributing (I was working as a development engineer for SETI) to just absorbing knowledge. To make myself feel better and more invested in learning, I started doing something for which I became moderately famous around the department: latexing lecture notes on-the-fly. For full disclosure, I should mention that I copycatted the idea of latexing on-the-fly from my friend Phil.
The key to success is to use lots of "defs", and to recognize when you need to def a sequence of commands. When the same sequence of symbols started popping up, I would pretend that I had already def'd the command and start using it, and when there was a pause in the derivation, I would remember to scribble down what that command should mean. In my later years, I also started drawing figures in paint for inclusion in latex.
Anyway, I now have about 4 or 5 latex'd class notes that I have put on my website. From what I hear, they are still regularly used in UCB classes, and I occasionally get happy emails from grad students thanking me for the effort. Meanwhile, I've been reading a book about Nicolas Bourbaki, a famous pseudonym for a group of (mostly French) mathematicians who collaboratively re-wrote mathematics from 1935 to the 70s. Nicolas Bourbaki was a wiki, ahead of its time.
"Now wouldn't it be cool," I thought to myself, "if students using these lecture notes could fix them when they are wrong (after all, they were written on-the-fly), and re-organize them to make more sense?" Could these notes become a sort of open-source textbook for astronomy? So AstroBaki was born.
The difficulty, I am finding, is in translating latex (especially latex heavy in defs) into mediawiki. The best tool I've found so far has been pandoc, which didn't do the defs, but did everything else pretty well. I'm loath to do things by hand, so I'll see what can be automated, and I'll keep you posted.
Wednesday, February 10, 2010
Friday, January 22, 2010
Where is GCC for FPGAs?
A lot of the digital signal processing that gets done in radio astronomy these days is done on Field Programmable Gate Arrays (FPGAs), and one of the projects I've been working on from the beginning in my research is developing open-source libraries for programming these chips. My part in this has generally been on the algorithmic/mathematical side: writing FFTs, filters, cross-correlation engines, etc. Another key aspect of this work, though, is a toolflow that allows people to design systems at a high level with parameterized algorithmic cores, and to turn that design into the wiring instructions that tell the FPGA how to implement the system.
We currently use a design entry system based on Simulink running on Matlab, and while it is an extremely powerful environment, we've also found it to be limiting, frustrating, and hard to maintain designs in. In October, I volunteered at an international workshop on astronomy signal processing to explore alternatives to this environment. My current favorite is MyHDL, which uses Python to generate lower-level code in Verilog or VHDL, and I may start looking more deeply into porting a design to use MyHDL.
Something that is bothering me, though, is that however much we work on porting our toolflow open-source equivalents, there is currently no open-source compiler for FPGAs. The state of affairs in FPGA-land is something like PCs in the '70s, when every personal computer had its own specialized compiler. For PCs, the problem was solved by GCC (the Gnu Compiler Collection), which became the default open-source solution for compiling most languages to target the many CPU architectures that exist in the world today.
I'm keeping my eye on gEDA, and notably Icarus, which seems to be a free synthesis tool (synthesis, mapping, and routing are the 3 main stages of compiling for an FPGA). Perhaps mapping and routing can never be open-source, since they tend to be very chip-specific. But here's hoping...
We currently use a design entry system based on Simulink running on Matlab, and while it is an extremely powerful environment, we've also found it to be limiting, frustrating, and hard to maintain designs in. In October, I volunteered at an international workshop on astronomy signal processing to explore alternatives to this environment. My current favorite is MyHDL, which uses Python to generate lower-level code in Verilog or VHDL, and I may start looking more deeply into porting a design to use MyHDL.
Something that is bothering me, though, is that however much we work on porting our toolflow open-source equivalents, there is currently no open-source compiler for FPGAs. The state of affairs in FPGA-land is something like PCs in the '70s, when every personal computer had its own specialized compiler. For PCs, the problem was solved by GCC (the Gnu Compiler Collection), which became the default open-source solution for compiling most languages to target the many CPU architectures that exist in the world today.
I'm keeping my eye on gEDA, and notably Icarus, which seems to be a free synthesis tool (synthesis, mapping, and routing are the 3 main stages of compiling for an FPGA). Perhaps mapping and routing can never be open-source, since they tend to be very chip-specific. But here's hoping...
Friday, January 8, 2010
Hands-On Cosmology Education
Yesterday I spent the morning giving a gosh-wow talk about cosmology to a physics class at Athenian High School taught by my housemate Dave Otten. It was a lot of fun, and the students were all very enthusiastic. It was almost entirely driven by their questions, and they loved being pitched curveballs (time is reference-frame dependent, the universe is expanding, spiral arms are standing waves, etc). The hour-and-a-half lecture was over before we knew it.
Afterward, Dave mentioned that it would be really cool if there were a way to talk about galactic-scale astronomy and cosmology that was in keeping with the philosophy of their school, which emphasizes lab-based, hands-on learning. He mentioned that PhET is a free resource he uses for providing interactive simulations that make hands-on labs out of subjects that otherwise would be too slow, small, big, fast, or dangerous to perform live in a classroom. He also lamented that there aren't any galactic- or cosmological-scale simulators there that could help to understand how systems on this scale behave, and that could perhaps illustrate exactly where the problems of dark matter and dark energy are encountered. Has anyone seen something like this?
Afterward, Dave mentioned that it would be really cool if there were a way to talk about galactic-scale astronomy and cosmology that was in keeping with the philosophy of their school, which emphasizes lab-based, hands-on learning. He mentioned that PhET is a free resource he uses for providing interactive simulations that make hands-on labs out of subjects that otherwise would be too slow, small, big, fast, or dangerous to perform live in a classroom. He also lamented that there aren't any galactic- or cosmological-scale simulators there that could help to understand how systems on this scale behave, and that could perhaps illustrate exactly where the problems of dark matter and dark energy are encountered. Has anyone seen something like this?
Monday, November 9, 2009
The Need for SPEAD
I've been absent for a good while now as a result of participating in a (successful) deployment of our PAPER experiment in South Africa. The Karoo desert in SA, where we were stationed, was very reminiscent of Rangely, CO where I grew up, except for the occasional baboon or kudu in the road. Though it came at a price of a lot of work piled up for me when I got back, and an awfully long time away from J, the isolation from all but our experiment helped ferment some ideas I'd been having about migrating the AIPY toolkit I've been developing to use a streaming data format that would avoid unnecessary disk accesses, would allow AIPY to be integrated directly with the correlators developed by our CASPER project, and would help our experiment develop a real-time analysis pipeline for compensating for ionospheric distortion in our data.
After chatting with a lot of guys working on the Karoo Array Telescope in Cape Town, we came up with a concrete protocol build on something already being used for CASPER correlator output. I just got done writing my first grant proposal to the NSF, funding a graduate student to work on this protocol--the Streaming Protocol for Exchanging Astronomical Data (SPEAD, pronounced "speed"). The process of writing a grant myself was a learning process, and helped me understand where a lot of the questions I got asked by my previous advisors were coming from.
A lesson I got to take away from SA was this: the reason we were in SA (as opposed to Australia) for PAPER was because we had been working with the KAT team, sharing correlator development. The reason we were working with the KAT team was because CASPER and KAT started up a collaboration a few years before. And that collaboration was started up because Dan Werthimer went down to visit SA some years ago to help advise them in a review of the design of their telescope electronics. Dan was invited there because he struck up a fast friendship with Alan Langman (the KAT director) at an earlier conference. The moral of this chain of causes and effects being that sometimes large projects go in new directions because of personal friendships, and sometimes those friendships end up making the difference in the success of a project.
Sunday, September 6, 2009
"Guess What I Was Thinking" Logic Puzzles (A Rant)
Probably more than most, I like logic puzzles. They're fun. But there's a variety of logic puzzles, especially prevalent in IQ/Mensa tests, that I really dislike. They are the "what's the next symbol in the pattern"-type of puzzles, and I HATE them. They are written like there is one (and only one) answer, and you must be dense not to see it. But can't I put anything in that blank space and call it a "pattern"? And what if the pattern that I see when looking at the provided sequence isn't the one you were thinking of? Is anyone with me in recognizing that these aren't logic puzzles at all? They're "guess what I was thinking of" puzzles! They aren't adequately constrained. They don't specify the parameter space from which the sequence is drawn. Anything can be a pattern! Anything!
What they actually want you to do is find the most likely symbol given several measurements and a set of priors about the likelihood of the author picking a particular sequence, but they neglect to provide you with any information about those priors. Maybe they assume that you can guess the priors based on estimates of your own sequence-picking priors, but that only works if your brain works the same way as the authors'. And quite frankly, if the authors can't appreciate that answers to these puzzles they are writing are indeterminate, I'm pretty sure their brain isn't working the same way as mine. Quit calling these logic puzzles! Put them on a Berkeley Psychic Institute entrance exam, not a college entrance exam.
Ok. Done ranting.
What they actually want you to do is find the most likely symbol given several measurements and a set of priors about the likelihood of the author picking a particular sequence, but they neglect to provide you with any information about those priors. Maybe they assume that you can guess the priors based on estimates of your own sequence-picking priors, but that only works if your brain works the same way as the authors'. And quite frankly, if the authors can't appreciate that answers to these puzzles they are writing are indeterminate, I'm pretty sure their brain isn't working the same way as mine. Quit calling these logic puzzles! Put them on a Berkeley Psychic Institute entrance exam, not a college entrance exam.
Ok. Done ranting.
Wednesday, August 26, 2009
Graph-SLAM
After a trying, but ultimately successful month spent extracting the family from Puerto Rico and re-embedding us in Berkeley, I'm just starting to get back on top of things enough to think about posting...
I had lunch yesterday with a good friend of mine, Pierre, who co-founded a company that specializes in sensory and mapping systems such as those that are used to create Google's "Street View". I was impressed to learn about their system for combining data from GPS, LIDAR, car odometers, and IMUs to create a consistent picture of how a vehicle is located and oriented in space as a function of time. They've spent a lot of time calibrating their systems, and use some sophisticated MCMC post-processing methods for deriving the actual trajectory of a vehicle.
Although the antennas in the PAPER array (that's the low-frequency interferometer I'm working on), are much less mobile than a car, there was considerable overlap between the problem Pierre has been working to solve and the calibration problem I am facing the requires positioning antennas and celesital sources as a function of time in the face of ionospheric distortion, variable gains, etc. Pierre pointed me to Graph-SLAM as a formal description of the problem that we are trying to solve, and suggested that Kalman Filtering with RTS Smoothing was a powerful technique for converging to the optimal solution (with covariance information) in linear time.
I had lunch yesterday with a good friend of mine, Pierre, who co-founded a company that specializes in sensory and mapping systems such as those that are used to create Google's "Street View". I was impressed to learn about their system for combining data from GPS, LIDAR, car odometers, and IMUs to create a consistent picture of how a vehicle is located and oriented in space as a function of time. They've spent a lot of time calibrating their systems, and use some sophisticated MCMC post-processing methods for deriving the actual trajectory of a vehicle.
Although the antennas in the PAPER array (that's the low-frequency interferometer I'm working on), are much less mobile than a car, there was considerable overlap between the problem Pierre has been working to solve and the calibration problem I am facing the requires positioning antennas and celesital sources as a function of time in the face of ionospheric distortion, variable gains, etc. Pierre pointed me to Graph-SLAM as a formal description of the problem that we are trying to solve, and suggested that Kalman Filtering with RTS Smoothing was a powerful technique for converging to the optimal solution (with covariance information) in linear time.
Tuesday, July 14, 2009
The Voynich Manuscript: Bootstrapping Language
The internet is a powerful and dangerous thing. It all started when I read the latest xkcd, which warned me that visiting cracked.com was dangerous. Then I read about the "6 phenomena that science can't explain" (which was a very dramatic title for some underwhelming mysteries), and next thing I knew, I was reading about the Voynich Manuscript. I learned about cryptography, glossolalia, the Manchu language, among other things. Then I took a look at the manuscript and before I knew it, I had a transcribed version of the manuscript in electronic form using the European Voynich Alphabet. And it just went downhill from there.
To summarize, the Voynich Manuscript (hereafter VMS) is a handwritten text with some illustrations some 500 years old. It uses glyphs no one knows how to read, it is not clear if it corresponds to a known language, it may or may not be encrypted, and little progress has been made in deciphering any of it, despite the fact that some bright people have tried. So I decided to have a crack at it.
The reason I got interested is because of the similaries to SETI. Arecibo, back in 1974, transmitted a message off into space that had been designed to be decrypted. We might receive a message like that some day. Or we might intercept something much like the VMS--a bunch of data in a language that we have no prior knowledge of--and we may be finding ourself trying to figure out how to bootstrap a language. That is to say, to learn the grammar and semantics of a language from a static example, without outside help.
Is this possible? For grammar, I'm pretty sure of it. I can imagine an algorithm (maybe Maximum Entropy Modeling and Bayesian learning applied to grouping and parsing) that uses correlations in the appearances of language elements (starting with letters and building up) and correlations in the behaviors of these elements relative to one another to build a model for parsing a language. For the VMS, I used something similar to this (not the MEM and Bayesian part) to show that spaces, line breaks, and paragraph breaks show similar grouping correlations relative to other VMS letters, and so can probably be considered one grammatical element of whitespace. That's a pretty simple thing to deduce, but it was actually something I was worried about in getting started with the VMS.
Sematics is another issue. Once upon a time, I would have had an optomistic answer to bootstrapping sematics from text that was not written for that purpose. However, after watching my child mysteriously acquire language, illustrating how hard-wired the human brain is for learning language from another human, and how much it relies on shared experience and feedback, I'm less sure.
I would be interested to know if there is a field of mathematics that studies sematics and the properties that a self-contained system needs to have to be able to generate sematical relationships. The Arecibo message relied on a shared physical environment to try to bootstrap sematics. I wonder if it would be enough to describe the rules of the grammar of a language in the language itself. That one, once the reader had deduced the relationships between elements, you would have a shared knowledge of that subject that might enable a reader to correlate the structure of the descriptions with the grammatical structure and thereby establish the first sematical relationships.
Anyway, after preliminary analysis of the VMS, I'm pretty sure that it's not random gibberish (there are correlations between elements on levels ranging from letters to words), and if it's encrypted, it's a weak form of encryption that preserves these correlations. My pet theory, extended from the glossalalia idea, is that this is actually plaintext in a natural language with an invented set of symbols, but that the natural language might be the accidental or intentional creation of a savant or scholar.
To summarize, the Voynich Manuscript (hereafter VMS) is a handwritten text with some illustrations some 500 years old. It uses glyphs no one knows how to read, it is not clear if it corresponds to a known language, it may or may not be encrypted, and little progress has been made in deciphering any of it, despite the fact that some bright people have tried. So I decided to have a crack at it.
The reason I got interested is because of the similaries to SETI. Arecibo, back in 1974, transmitted a message off into space that had been designed to be decrypted. We might receive a message like that some day. Or we might intercept something much like the VMS--a bunch of data in a language that we have no prior knowledge of--and we may be finding ourself trying to figure out how to bootstrap a language. That is to say, to learn the grammar and semantics of a language from a static example, without outside help.
Is this possible? For grammar, I'm pretty sure of it. I can imagine an algorithm (maybe Maximum Entropy Modeling and Bayesian learning applied to grouping and parsing) that uses correlations in the appearances of language elements (starting with letters and building up) and correlations in the behaviors of these elements relative to one another to build a model for parsing a language. For the VMS, I used something similar to this (not the MEM and Bayesian part) to show that spaces, line breaks, and paragraph breaks show similar grouping correlations relative to other VMS letters, and so can probably be considered one grammatical element of whitespace. That's a pretty simple thing to deduce, but it was actually something I was worried about in getting started with the VMS.
Sematics is another issue. Once upon a time, I would have had an optomistic answer to bootstrapping sematics from text that was not written for that purpose. However, after watching my child mysteriously acquire language, illustrating how hard-wired the human brain is for learning language from another human, and how much it relies on shared experience and feedback, I'm less sure.
I would be interested to know if there is a field of mathematics that studies sematics and the properties that a self-contained system needs to have to be able to generate sematical relationships. The Arecibo message relied on a shared physical environment to try to bootstrap sematics. I wonder if it would be enough to describe the rules of the grammar of a language in the language itself. That one, once the reader had deduced the relationships between elements, you would have a shared knowledge of that subject that might enable a reader to correlate the structure of the descriptions with the grammatical structure and thereby establish the first sematical relationships.
Anyway, after preliminary analysis of the VMS, I'm pretty sure that it's not random gibberish (there are correlations between elements on levels ranging from letters to words), and if it's encrypted, it's a weak form of encryption that preserves these correlations. My pet theory, extended from the glossalalia idea, is that this is actually plaintext in a natural language with an invented set of symbols, but that the natural language might be the accidental or intentional creation of a savant or scholar.
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