That is awesome. And I am so sad an individual that my first thought was of a software plug-in that would use this frequency to generate realistic candle-flicker effects.
To continue this tangent, legend has it that some of those battery powered tea candle lights actually reuse the chip from cheap music playing trinkets. If you replace the yellow LED with a speaker, you might hear beepy christmas music or happy birthday.
I've never found one myself (most of them have a better candle simulation chip than that), but they are apparently out there.
While technically a PIC12 is a computer since it has I/O, tiny storage, a PC and an ALU - it’s hard to even think of it in the same category as what most think of as a computer. IMHO the takeaway is more what the bare minimum it takes to be a computer, which isn’t much. (In other terms, a PIC does not meet the DOOM threshold).
PICs are so old and rudimentary that they started out as peripheral controllers for “real” computers in the 70s. It turns out you can do some useful embedded stuff with a basic chip, but even the newest of these are on 30 year old semiconductor tech at this point.
That may sound jaded, on the other hand I do find mass production of modern level integration and speeds to still be marvelous.
And as an EE, the “white” LED in the candle is more interesting than the uC!
In strings of programmable LED lights every single LED is actually an LED combined with a computer. This allows the LEDs to be addressed individually without loads of wires.
Computer is overselling it a bit. It's a fixed logic latch+shifter. Basically each LED takes first few bytes for itself and shifts out the rest down the chain.
Still awesome this is small and cheap enough to put into individual lights of course.
Chaotic circuits are neat, but they are actually not random (their output distribution is not uniform or gaussian). And candles are not random either :)
> "More in details, Ando and Graziani demonstrated that the Chua's circuit can be used to generate either a gaussian or a uniform white noise. To do this, they investigate the statistical and spectral characteristics of the signals generated by a Chua's circuit with respect to different values of the parameters α and β. They then applied the x^2 method to determine which set of parameters leads to a signal having the statistical and spectral characteristics more similar to those of either a Gaussian or uniform noise. By using this method, a signal with a Gaussian-like distribution is obtained with a confidence of 95% for this set of parameters: ..."
They've got charts of the probability density functions for each that seem reasonable to me.
Nice, I was not aware of that! Quite interesting. Thank you for the source.
It seems to be a corner case. As I learned to know them, chaotic circuits have unpredictable cyclic behavior. Chua's circuit typically follows an oscillatory behavior with a double attractor.
If true randomness is the goal, it is much easier to use other sources of randomness like avalanche transistors, jitter of ring-oscillators in the analog domain or LFSRs if you are in the digital domain.
I think the main confusion for analog implementations of chaotic circuits is that they often have an inherent source of noise (e.g. johnson or flicker noise of resistors, transistors) which will be amplified into large changes by the sensitivity of the system to initial (and also intermediate) conditions.
So the actual implementation has an unpredictable behavior, but this is because the randomness of the components is amplified.
I don't know what the most obvious distinction between a chaotic analog circuit and a TRNG is. For me it was always obvious that any kind of visible structure in the trajectory (the attractors) contradicts randomness. But whenever people see Chua's circuit brought up, there are lots of commends regarding random number generators. It turned into a bit of a pet peeve of mine.
I don't know much (or really anything) about circuits and circuit noise.
There is a long history of deterministic pseudo RNGs, which you may already know about. https://en.wikipedia.org/wiki/Pseudorandom_number_generator. These are sometimes chaotic. In this line of thinking, a thing that generates unpredictable noise and adds chaos would make probably a good hardware PRNG.
But the chaotic part is not actually random (although it's hard for attackers to predict). And whether the noise is random depends on a bunch of physics.
But if this has gotten to the point of a pet peeve to you, you might be interested in Randomness Extractors (https://en.wikipedia.org/wiki/Randomness_extractor) which are a way of thinking about questions like "we have an unpredictable source of bits, but it's not as random as it seems... how can we extract actual randomness from it?"
For example, extractors can take low quality somewhat random non-uniform (or non-gaussian) output and use it to create high quality uniform (or gaussian output).
Related to this, I once read that the reason nearly every car alarm in the 1990-2010 approx era had the same pattern of awful sound patterns was that they all simply used the same off the shelf sound IC which was produced in such quantities as to make any custom option untenable.
The “car alarm sequence” of 10s patterns was just the self-test demo program for the sound chip.
I believe they were the HK628 and UM3561 chips which were launched in the 1980s for toys. You can actually hear that alarm sound on some toys from that decade. They were simple chips that stored 8-16 preprogrammed sounds and the urban legend is that the car companies just kept the alarm demo sound (I think there were two different ones). The chips ended up everywhere: toys, care, appliances, industrial machinery, etc.
Very neat! I've also seen that some will use Linear Feedback Shift Registers [0] for the candle effect, or maybe that's the same thing you're talking about.
Edit: I see the article in a sibling comment makes note of this too.
