Thought Toys · Strategy & computation · Exhibit 101
A wire flips one bit in five. Common sense says every message through it is damaged goods. Shannon said: below a certain speed, you can be as reliable as you like — and above it, you can't, no matter how clever you are. Then he drew the line.
Every channel and every speed — the boundary between them your telegraph repetition
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The map is every conversation you could try to have over a noisy wire. Along the bottom: how often the wire flips a bit. Up the side: how fast you talk — message bits per use of the channel. The amber curve is Shannon's capacity, C = 1 − H(p), and it cuts the map in two. That curve is the entire theorem. Everything below it is reachable. Everything above it is not. There is nothing else on the map, because nothing else matters.
The bars on the right are not an illustration — they are a working telegraph. Each press of send builds a random codebook, pushes four hundred real message blocks through the noise you chose, and decodes each one by finding the codeword it most resembles. With your dot below the curve, watch the bars as the blocks lengthen: the share of blocks decoded wrong collapses while the rate you talk at stays exactly where it was. You are paying with block length instead — longer waits and more decoding work, never speed.
Now drag your rate above the curve. The same machinery, the same effort, and the bars grow instead of shrink — pressing up against the little red markers, Fano's floor: at that rate and that block length, no code of any design, by anyone, ever, gets its share of wrong blocks under the marker — and the floor itself climbs as the blocks grow. Longer blocks now make things worse. The boundary is not an engineering difficulty. It is a property of the universe's bookkeeping: a channel that flips bits with probability p simply does not contain more than 1 − H(p) bits of room per use.
Before 1948, the assumption was that reliability had one price: speed, paid all the way down. Press the old way to see it — repeat every bit and take the majority. It works, but look where the cyan dots march: straight down the rate axis. Getting a bit's error down to one in a million at a noise of one in five takes fifty-one copies of it — a rate of 0.02, fourteen times below the capacity that Shannon promises at any error you care to name. The pre-Shannon world thought that trade was the law. It was only a failure of imagination.
Two things are worth carrying away. First, the codebooks here are random — nobody designed them, and they still land the theorem — random codebooks are the idea Shannon's own proof runs on. What carries the information is shared structure: the proof script hands the decoder a different random codebook, and even far below capacity it decodes at chance. Second, slide the noise toward one half and watch the whole achievable country close to nothing: a channel that flips half its bits is a coin, and a coin has no room in it for a message of any length.
improve/verify/101-channel-capacity.js, 19 checks). The
capacity formula is earned, not assumed: a grid search over input distributions maximizes the mutual
information from first principles and lands on 1 − H(p) to 10⁻⁶, while the
plausible-but-wrong C = 1−p overshoots it 2.9×. Exact binomial repetition errors match a
200,000-throw Monte Carlo; reaching 10⁻⁶ by repetition at p = 0.2 is shown to need
n = 51, a rate 14× under capacity. With seeded random codes and nearest-codeword decoding, the
measured block error at fixed R = 0.125 falls 0.015 → 0.010 → 0.003 as
n grows 8 → 16 → 24, while at R = 0.75 it rises
0.470 → 0.643 and every point respects the Fano floor. Negative controls: at
p = 0.5 longer blocks do not help at all (error sits at chance for n = 8 and 16 alike);
a decoder holding a different codebook than the encoder decodes at chance even below capacity
(matched 0.005 vs mismatched 0.820), so it is the shared structure and not the block length that carries the
message; and at p = 0 any code decodes perfectly. The page's coder is the same construction the
proof uses, seeded, so what you watch is what was verified.
Also in Strategy & computation: Sorting algorithms →
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