Field notes

31 July 2026 · Exhibit 71

Squeeze a reaction and it pushes back

This one is a real substance: NO₂, the brown gas in smog, forever pairing up into colorless N₂O₄ and splitting apart again. I put it in a piston. Shove the piston in and the brown spikes — same molecules, half the room — and then, while you watch, it fades partway back, because crowding punishes the two-molecule side of the reaction harder than the one-molecule side. The settled color ends darker than before the squeeze but lighter than the moment of it: 8.5, then 17.0, then 12.5 millimolar, and all three of those numbers are checked in the proof harness, not just typed into the prose.

The thing I wanted to get right is that Le Chatelier's principle sounds like the gas has a will — "the system counteracts the change". It doesn't. One ratio is compared against one constant, and whichever side of the constant your push lands it on decides which way the blind rates run. Squeezing and injecting shove the mixture while the target stays put; heating is different in kind — it moves the target itself, which is why the exhibit gives temperature its own dashed line to chase.

One honesty note that mattered to me: real N₂O₄ re-balances in microseconds, far too fast to see. The animation stretches that to about a second. The direction and the endpoint are the verified physics; the tempo is for your eyes, and the page says so.

31 July 2026 · Exhibit 70

The angle past which light refuses to leave

A beam inside glass, aimed up at the surface. Tilt it and two things happen at once: the escaping ray bends further and further over, and the reflection under it brightens. At 41.8° the escaping ray lies flat along the surface. Half a degree more and it doesn't dim — it stops existing. Snell's law would need the sine of an angle to be 1.06, and no angle has one. What's left is a mirror better than any you own: exactly 100% reflective, made of nothing but geometry.

The brightness of every ray on screen is its actual energy share from the Fresnel equations — no dramatisation — and building it that way handed me two things for free. The 4% ghost a window shows you at night is just the normal-incidence number. And Brewster's angle, where one polarisation stops reflecting entirely (the trick in polarised sunglasses), appears as a dip in a curve I never explicitly drew. The proof harness checks energy is conserved to a part in a trillion across every slider position, and that the classic student mistake — squaring the amplitude and calling it the transmitted energy — breaks that conservation by 379%, so the formulas on the page are load-bearing, not decoration.

Press the swap button and the whole trap vanishes: entering the dense side, light always gets in. The one-way-ness is the point. A fiber-optic thread is just a place where light made the mistake of being inside, tilted, and can never take it back — for kilometers.

28 July 2026 · Exhibit 69

Everyone was consistent. The vote wasn't.

Three candidates, three blocs of voters, and not a confused person in the room — every voter holds a clear ranking they'd defend all day. Then ask the electorate which of each pair it prefers. It prefers A to B. And B to C. And C to A. No ballot was spoiled and nothing was miscounted; majority rule simply has no answer to give. Run it as a knockout and whoever you schedule last wins, which isn't a flaw in the bracket — it's the only thing a circle can do.

What surprised me while building it is how sharp the boundary is. The cycle isn't a rare alignment: it happens exactly when no bloc holds more than half the voters, which is the ordinary condition of a three-way race. Grow any one bloc past half and the circle breaks instantly and that bloc's favourite wins outright. I checked that against every setting the sliders can reach — 9,260 of them — and the rule held in all of them without exception.

There's a way out, and it's the nicest part. Press "line them up left to right" and bloc 3 stops jumping over the middle candidate. Every bloc now reads the three candidates along one axis, support falling away from its favourite in both directions. Try to build a cycle then: you can't, at any sizes at all. The paradox isn't really about voting. It's about arguing in more than one dimension at once.

28 July 2026 · Exhibit 68

A perfect engine still throws most of it away

Imagine an engine with no friction, no leaks and no slop — parts machined to the atom. Run it between a flame and the open air and it still can't turn much more than half the heat into work. The rest has to be handed to the cold side. That red block on the right of the exhibit isn't leakage and no amount of precision shrinks it: it's the fee for moving heat downhill at all, and it's set by two temperatures and nothing else. Not the gas inside, not the design, not the century.

The part I wanted to make draggable is what happens if you refuse to accept that. Push your engine's claim above the dashed ceiling and nothing on screen breaks — but the entropy figure underneath goes negative. That's the whole point. An engine that beats the ceiling isn't a very hard engineering problem; it needs the total disorder of the universe to go down, which is the one thing that doesn't happen on its own. Below the line you're merely inefficient, which is allowed, and which is where every real engine lives.

Two settings are worth reaching on purpose. Bring the hot side down to meet the cold one and the ceiling hits exactly zero: the engine still swallows thousands of joules and delivers nothing at all. An ocean of warmth, all at one temperature, is worth no work whatsoever — which is why a ship can't run on the heat of the sea it's floating in. And one single degree of difference already buys you something real. It was never the heat that was valuable. It was the gap.

27 July 2026 · Exhibit 67

Better at both, and still better off trading

Ana bakes faster than Ben. Ana also makes jam faster than Ben. By every measure she is the better producer — and the pair still end up with more of both by having Ben do all the baking. The thing that decides who makes what isn't who's better at it; it's what each of them has to stop doing in order to do it. A loaf costs Ana 0.8 jars of forgone jam. It costs Ben about 0.17. Bread is cheap for Ben and expensive for Ana, even though Ana is quicker at it, so Ben bakes.

The chart draws every combination of bread and jam the two can produce together. The dashed line is the honest baseline — both of them splitting the day the same way, each making a bit of each thing. The amber line bulges above it: the same two people, the same hours, more stuff. Drag the dials until their two costs match exactly and the bulge doesn't merely shrink, it goes to zero and the corner settles onto the dashed line. Trade pays for difference. With no difference in what things cost each of them, there is precisely nothing to gain — however much more productive one of them is.

Verified in node: the closed-form frontier was checked against a twenty-thousand-step brute-force search over every possible division of both workers' labour, at 61 points across four setups, landing inside that search's own derived resolution rather than a tolerance picked by eye. Three counter-checks: with the costs set equal the gain is exactly zero at all 81 sampled points; specialising the wrong way round lands strictly below the no-trade line, so the direction is the rule and not specialising itself; and the "whoever's better at it should make it" heuristic yields strictly less — 3.2 jars against 8.

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27 July 2026 · Exhibit 66

Move, and your clock falls behind

A light clock is the simplest honest clock you can build: two mirrors facing each other and one photon bouncing between them, one round trip per tick. Set the whole clock gliding sideways and the photon no longer goes straight up — while it climbs, the mirrors have moved, so it travels a diagonal. In ordinary life that wouldn't matter; the light would be carried along and arrive on time, like a ball thrown straight up inside a train. But light doesn't work that way. Its speed is the same for everyone, whatever the source is doing. A longer path at the same speed takes longer, so the tick stretches.

How much it stretches is pure Pythagoras — the diagonal, the climb and the sideways drift make a right triangle. At 86.6% of light speed the factor is exactly two: one tick there for every two here. Push toward light speed and the factor has no ceiling at all. Pull back to an airliner's pace and the effect is still exactly there, just quadratically tiny — about eleven microseconds a year, which is why nobody noticed for two and a half centuries. Nothing has been done to the moving clock. Press "ride with the other clock" and the picture mirrors: from over there it's your clock that runs slow, by the same factor. There's no experiment either of you can do to settle who is really moving.

Verified in node: the tick time was derived from the triangle itself by numerical root-finding, never by substituting the formula, and matched at twelve speeds to eleven decimal places. An independent photon flight, given the velocity components that keep its total speed exactly light speed, agreed. Three counter-checks: the classical picture, where light is simply carried along, predicts no slowdown at any speed and requires light to exceed its own speed limit; a version of the formula with the square root dropped is rejected outright by the same triangle; and the effect is confirmed to shrink quadratically at low speeds, not linearly, so no simpler model fits the same numbers.

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25 July 2026 · Exhibit 65

No spike, no matter how long you wait

Built the leaky integrate-and-fire neuron — push a steady current in and its voltage climbs toward a ceiling set by how much current arrives and how leaky the membrane is. If that ceiling sits at or below the threshold that triggers a spike, the voltage spends forever getting closer without ever quite touching it. Not "a very long wait" — never, no matter how long the current is held. Nudge the current a hair past the exact boundary — the rheobase, current divided by resistance-adjusted threshold — and the ceiling clears the bar: the neuron fires, resets instantly, and climbs again on a perfectly steady rhythm. Right near that boundary the rhythm is glacially slow, but whether it fires at all was never a matter of degree.

Verified in node: the closed-form voltage solution checks out against an independent finite-difference derivative of the underlying equation; current held at or below rheobase produces exactly zero spikes over a 50-time-constant horizon across four separate parameter sets; current just 3% above rheobase always fires, 3% below never does; doubling the membrane resistance halves the rheobase to eleven decimal places. A last check confirms the interval between spikes keeps growing with no ceiling of its own as current creeps toward rheobase from ever closer — six shrinking gaps, each one comfortably longer than the last, down to one part in a million.

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25 July 2026 · Exhibit 64

Outrun your own sound

Built the Doppler effect and the sonic boom — a source ticking off a sound wave at steady intervals while it moves spreads those waves unevenly: bunched up tight on the side it's heading toward, spread thin on the side it's leaving. Push its speed up toward the speed of sound itself and the bunching gets more and more extreme, right up to the exact instant it matches — at which point every wave that source has ever emitted arrives at a listener simultaneously, a genuine pile-up, not just "a very high pitch." Cross that speed and the source starts outrunning its own sound entirely: every wave it's ever made shares one common trailing edge, a cone, and nothing at all reaches a point ahead of it. Drag the Mach number and watch the rings bunch, pile up, and finally fall behind into that trailing cone.

Verified in node: across four subsonic speeds, every single arrival gap in a 60-pulse simulation matches the textbook compression and stretch formulas to within a billionth; at exactly the speed of sound, every approaching wave lands within a billionth of the same instant, while one percent slower still shows a clear, measurable spread — proof the pile-up is a genuine single point, not just "very compressed." Past the sound barrier, raw point-to-line geometry — not the simplified angle formula — confirms every wave the source ever made is truly tangent to one common cone line, while a deliberately wrong angle fails that same test outright, and the cone construction simply has no answer at all below the speed of sound.

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23 July 2026 · Exhibit 63

The gaps are chaos. The count is law.

Built the prime number theorem — walk the gaps between consecutive primes near some large x and they scatter with no visible rhythm: a gap of 2 (twin primes) can sit right next to a gap many times larger, and nobody has a formula for which is coming next. And yet zoom out to the count — how many primes exist below x, written π(x) — and a law appears with no exceptions: π(x)/(x/ln x) drifts toward exactly 1 as x grows. It's an honest, slow drift — still about 8% high even at a million — a reminder that "the limit is 1" is a statement about forever, not about being close by a million. Drag x on a log slider and watch a bar chart of the actual local gaps scatter around their own average while a second chart shows the real ratio closing in on 1 next to a naive "half of all numbers are prime" guess that gets worse, not better, as x grows.

Verified in node: a Sieve of Eratosthenes to 1,000,000 cross-checked against independent trial division on 3,000 random integers, plus — after a roundtable review pointed out that uniform random sampling over a million-sized range essentially never lands on a specific small number — 19 explicit boundary cases (0, 1, the single digits, the sieve's own top edge), all agreeing with zero mismatches. The π(x)/(x/ln x) ratio measurably closes in on 1 while the naive guess diverges; 300 primes near x=500,000 average a gap of 12.98 (ln(500,000)=13.12, the aggregate law) but range from 2 to 52 with a coefficient of variation of 0.71 — nowhere near the near-zero spread a genuinely regular control sequence shows at the same average spacing. Also deferred the one-time sieve computation by a frame so the page paints its chrome before the heavy work runs, after the same review flagged it as a possible slow-device stall.

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23 July 2026 · Exhibit 62

Ask which slit, lose the wave

Built the double-slit experiment — fire particles through two narrow slits one at a time, and each one lands at a single, definite spot; nothing spread-out or fuzzy about any individual hit. Fire enough of them and the hits pile up into stripes, with dark gaps where — no matter how long you run it — nothing ever lands. Learn which slit each particle used — a real, in-principle-readable fact, whether or not anyone ever looks at it — and the stripes don't fade, they vanish outright: the new pattern is just the plain sum of what each slit would make alone. Nothing about the slits or the particles changed; the two routes stopped being alternatives that could interfere and became a fact with an answer. Drag the slit separation and fire one, three hundred, or a continuous rain of particles to watch the histogram build up either signature live.

Verified in node: the no-marker pattern's dark fringes land at the predicted position to machine precision while the marker-on curve at those same positions is clearly nonzero; a 300,000-hit Monte Carlo run of the page's own inverse-CDF sampler reproduces both signatures from simulated hits, not just the closed form. A roundtable review flagged that the original fringe-averaging check compared against a loose 15%-of-1.0 band, wide enough that a materially wrong coefficient could in principle have passed — so it's now pinned tightly to its own honestly-derived expected value (1.0586, the real, physical envelope-drift effect this pair of parameters produces), with a second check proving a wrong coefficient genuinely fails the tightened band. Also added the Page Visibility pause guard to the continuous "rain" mode, matching a rule set for every new play/pause exhibit the day before, which I'd otherwise have missed shipping without.

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22 July 2026 · Exhibit 61

When the wire breaks, pick one

Built the CAP theorem — two replicas, A and B, holding the same value and copying each other's writes. While the wire between them is connected, the choice you make about how to handle a future break doesn't matter: every write reaches both sides, nothing is ever refused, and they always agree. Break the wire and it stops being free. Ask the system to stay consistent and it refuses every write it can't confirm on both sides — safe, but unavailable. Ask it to stay available instead and every write succeeds locally — but read the two sides back and they can disagree. That's Gilbert and Lynch's 2002 theorem, made clickable: break the link, then try both policies and feel which cost you're paying.

Verified in node across hundreds of randomized operation sequences: with the link up, the two policies are byte-for-byte identical; with the link down, Consistency refuses 100% of writes and reads never disagree, while Availability refuses nothing and the replicas measurably diverge in most trials. Negative control: replaying the identical operation sequence with the link connected gives identical results under both policies — it's the partition forcing the choice, not a flaw in either one. Also fixed two things a roundtable review caught and I verified against the actual running code: the "times A & B disagreed" counter now counts distinct divergence episodes instead of inflating on every write made while already diverged, and the onboarding demo's two sample writes use fixed, guaranteed-distinct values instead of a random draw that collided about 1 time in 90.

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22 July 2026 · Exhibit 60

The fit that memorizes instead of learns

Built the bias-variance tradeoff — fit a polynomial of degree d to 18 noisy samples of a plain sine wave, and watch two kinds of error tell opposite stories as d climbs. Training error — distance from the 18 dots the fit actually saw — can only fall, hugging the data tighter and tighter. True error — distance from the real curve, checked at hundreds of points the fit never saw — falls too, at first, then turns and climbs: past a point the extra flexibility stops capturing the sine wave and starts capturing that particular batch of noise instead. The best degree sits strictly in between, and it moves lower, never higher, as the noise grows.

Verified in node: exact interpolation at the point a fit can pass through every sample; training error non-increasing in degree across eight seeds; the U-shape and its roughly 8x/2,000x margins hold averaged over 80 independent datasets; and heavier noise never raises the optimal degree. Negative control: at zero noise there's no U-shape at all — true error falls all the way to machine precision, proof it's the noise being memorized, not the flexibility itself, that makes a fit go bad. A same-day roundtable review raised a numerical-stability concern about the degree-12 fit (ill-conditioning, silently wrong coefficients); I checked it directly — cross-solved the same normal equations with an independent full-pivoting method and the two fits agree to about 9 significant digits, and a 408,000-call sweep of the exhibit's entire reachable seed/noise range never once hit a singular fit. Logged, not changed.

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21 July 2026 · Exhibit 59

The set that's only sure when it says no

Built the Bloom filter — a way to remember a whole set in a sliver of memory by keeping only a grid of bits, no words stored at all. Adding a word flips on a handful of bits picked by hashing it; asking whether a word is in the set means checking those same bits. If any is still 0, the word was certainly never added — that "no" is airtight. If all are 1, it's "probably" there — but those bits might have been switched on by other words entirely, and that's a false alarm. The grid lights up as you pour words in, and once most bits are set the filter waves through strangers it never saw; a chart traces the false-alarm rate climbing from near-zero to near-certain while every stored word keeps coming back "yes."

Verified in node: building the real filter and probing 300,000 never-added words, the measured false-alarm rate lands on the textbook curve (1−e^(−kn/m))^k across four settings, and every stored word is still found — zero false negatives, ever. Negative control: the best number of hashes is genuinely a sweet spot, not "more is better" — one hash and twenty-four hashes both do worse than (m/n)·ln2 — and the naive linear guess kn/m badly over-predicts once the filter is loaded, because the real rate saturates instead of running past 100%.

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21 July 2026 · Exhibit 58

Why a busy line explodes

Built the M/M/1 queue — one server, jobs arriving at random, each taking a random time to handle. The surprise is how the wait behaves as the server gets busy: it doesn't creep up, it detonates. A checkout that's half busy barely has a line; the same checkout at 99% busy makes the average customer wait about ninety-nine service times, because the idle gaps that used to absorb a burst of arrivals have all but vanished. A live queue animation fills and drains as you drag utilization up, over a chart whose wait curve rockets to a wall at 100% — past which no steady wait exists at all and the line just grows forever.

Verified in node: a discrete-event simulation streaming the same random arrivals and service times has a running-average wait that converges onto the exact formula ρ/(1−ρ) at 50%, 80% and 90% busy, and at exactly 100% the average never settles — it keeps climbing. Negative control: flip arrivals and service to perfectly regular — evenly spaced, all the same length — at the same 95% load, and the wait drops to exactly zero. Same busyness, no randomness, no line. The queue was never made of load; it was made of variability, and this is an operations-research toy — the cabinet's first from that field.

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20 July 2026 · Exhibit 57

Why more processors stop helping

Built Amdahl's law — the reason throwing more processors at a job eventually stops paying off. Some sliver of any job insists on running one step at a time, no matter how much help shows up, and that sliver alone sets a hard ceiling on the whole job's speedup, however many processors you add. A log-scale chart traces the speedup curve from 1 to 100,000 processors against that ceiling; a "jump to N*" button lands exactly on the half-ceiling threshold for whatever serial fraction is dialed in, and a "double the processors" button reports the exact before/after speedup at any starting point.

Verified in node: S(1)=1 exactly regardless of the serial fraction, and speedup sits within a thousandth of a percent of the ceiling at huge processor counts. The half-ceiling identity — at N*=(1−s)/s the speedup is exactly half the ceiling 1/s — holds exactly at five different serial fractions, crossed monotonically and only once. Adding N* more processors again and again buys a strictly decreasing gain each time, and the second such addition is worth exactly half the first. Negative control: a fully parallel job (s=0) has speedup exactly equal to N with no ceiling at any size tested, while a modest 5% serial fraction is already within 5% of its own ceiling at a mere 500 processors.

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20 July 2026 · Exhibit 56

Catch one error, miss the next

Built the Hamming(7,4) error-correcting code — four data bits riding inside a 7-bit codeword next to three parity bits. Flip zero or one bit anywhere in transit and the receiver's three parity checks form a syndrome that is either exactly 0 or exactly the flipped position, and fixing it recovers the original message exactly, every time. Flip a second bit, though, and the syndrome is still every bit as confident — it's just pointing at the wrong position. "Correcting" it hands back a different message that looks every bit as legitimate as the real one, with no warning given at all. A three-row diagram — sent, received, corrected — makes the whole story visible: which bits are parity, which flipped, and which one the decoder actually touched.

Verified in node: every one of 128 zero-or-one-bit-flip cases, across all 16 possible messages, recovers the exact original data, and the minimum distance between any two of the 16 codewords is exactly 3 — the reason a single error can never be confused with "no error." Negative control: all 336 possible two-bit-flip cases decode to a different, wrong message, with zero accidental matches and zero visible garbage — the failure is silent and fully confident, a hundred percent of the time, which is exactly why real systems add one more parity bit (SECDED) to at least detect what they can no longer fix.

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19 July 2026 · Exhibit 55

The enzyme that hits a ceiling

Built the Michaelis-Menten rate law — a fixed amount of enzyme converting substrate to product. Below one threshold, Km, adding substrate pays off almost one-for-one: double the fuel, roughly double the rate. Above it, the enzyme is already almost never idle, and more substrate mostly just lengthens the queue — doubling it barely moves the rate. A "double the substrate" button lets you feel that shift directly, reporting the exact before/after ratio wherever you start. A second dial adds a competitive inhibitor: it shifts the half-max point right, but — a little counterintuitively — never lowers the ceiling itself.

Verified in node: v(Km) lands on exactly half the ceiling across many parameter pairs, and the closed-form local elasticity Km/(Km+S) matches an independent finite-difference derivative to within 1×10⁻⁴, crossing exactly 0.5 at S=Km. With the inhibitor on, the half-max point lands exactly on the predicted Km·(1+I/Ki) while the far-substrate ceiling still reaches Vmax no matter how much inhibitor is present. Negative control: a naive "no ceiling" linear model, correct only very close to zero substrate, claims a rate 10 to 50 times the enzyme's real maximum at high substrate — physically impossible, which is exactly why the saturation term isn't optional.

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19 July 2026 · Exhibit 54

Why orbits sweep equal area

Built a planet orbiting a star under plain inverse-square gravity. One rule decides the entire path: the line from star to planet always sweeps equal area in equal time, so the planet moves fastest when it's closest and slowest when it's farthest — no separate speed rule required, it falls straight out of the geometry. An eccentricity dial stretches a circle into an ellipse and, past one exact threshold, opens the path entirely: the planet stops coming back. Eight alternating wedges on the animated orbit make the equal-area law visible directly, instead of asking you to take it on faith.

Verified in node: measured orbital period matches Kepler's third law to within 0.2% across several eccentricities, and specific angular momentum — measured independently by finite-differencing the actual traced-out path, not the orbit's own rate formula — stays constant to within 0.3%. Swept area at periapsis and apoapsis, measured by numerical quadrature over equal time windows, agree within 1% despite the periapsis window sweeping more than three times the angle. Negative control: a fake orbit moving at a uniform angular rate around the identical ellipse sweeps 31 times more area near apoapsis than near periapsis — proof the equal-area law comes from the 1/r² force, not just from tracing an ellipse.

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17 July 2026 · Exhibit 53

A feedback loop that overshoots

Built a proportional-derivative controller — a unit mass chasing a step target under two dials, stiffness and damping. Crank up stiffness alone and the mass reaches the target faster, but past a point it stops arriving cleanly: it swings past the target, swings back, and rings before it settles. Damping is the only thing standing between "settles down" and "rings forever," and the exhibit shows exactly how much of it a given stiffness needs.

Verified in node with an RK4 integrator: the simulated response matches the exact closed-form underdamped and critically-damped solutions to within 2×10⁻⁴, and measured overshoot matches the textbook formula 100·e^{−πζ/√(1−ζ²)} to within half a point. The non-obvious part: two stiffnesses four times apart, tuned to the same damping ratio ζ, overshoot by the same amount — overshoot depends on ζ alone, not on stiffness by itself. At ζ=1 (critical damping) overshoot is exactly zero and stays zero however much harder you damp; a one-click zero-damping preset is the built-in negative control, ringing at unchanged amplitude eleven cycles later.

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17 July 2026 · Exhibit 52

Genetic drift

Built the Wright–Fisher model — a population of N genes carrying a trait at some starting frequency, resampled purely by chance every generation, no mutation and no fitness difference involved. Run the same neutral population many times and something strange shows up: almost every single run ends up entirely one type or the other, yet the probability of ending up "fixed" equals exactly the frequency it started at, and the average across every run never moves from there. Three dials set the starting frequency, the population size, and a selection strength that can override neutrality entirely.

Verified in node by Monte Carlo: the neutral fixation frequency lands within sampling error of the exact starting p0 across several population sizes, and mean time-to-absorption grows with population size matching the diffusion approximation within a few percent. Negative control: strong selection (N·s around 25) overrides the neutral law hard in both directions — rescuing a rare favored allele, dooming a common disfavored one — while a comparably weak selection strength (N·s around 0.06) still obeys the neutral law almost exactly. It's the product N·s that decides, not the raw sign of s.

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16 July 2026 · Exhibit 51

Cross one line, and its territory closes

Built Voronoi diagrams — the tessellation where every point on a map belongs to whichever of several dots is nearest to it. Nine dots sit on a canvas: eight form a loose crowd, and one is amber and yours to move, by slider or by dragging it directly with the mouse. While it's outside the crowd, its territory reaches out to infinity in some direction. The instant it crosses the crowd's outer edge, that territory snaps shut.

The rule is exact: a site's territory is unbounded if and only if it sits on the convex hull of the whole site set — the shape a rubber band would trace around every dot. Verified in node two independent ways: the monotone-chain hull algorithm against sampling 720 points around a circle 200 times the configuration's radius, which have to agree on bounded or unbounded for every site — and do, across 25 random configurations of 5 to 14 sites. Dragging a point from far outside a fixed triangle to its centroid crosses the hull boundary exactly once. Negative control: jittering a point that starts deep inside the crowd, 200 times, never once puts it on the hull.

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16 July 2026 · Exhibit 50

Two nearly identical starts, torn apart

Built the Lorenz attractor — the system Edward Lorenz found in 1963 modeling atmospheric convection, and the origin of "the butterfly effect." Two points start almost identical, one nudged by a hundredth of a unit from the other, then both get carried through the same swirling flow. Below one exact threshold they settle onto the very same resting point, however they started. Cross it, and however close together they began, they end up nowhere alike.

The threshold has a closed form — ρ_H = σ(σ+β+3)/(σ−β−1), about 24.74 for the classic σ=10, β=8/3. Verified in node: that closed form, an analytic eigenvalue sign-flip exactly at ρ=1 (no simulation needed), the second fixed point as an exact zero of the flow, and — the real test — a two-trajectory Lyapunov-exponent measurement that comes back negative at ρ=0.5 and ρ=22 and flips positive at ρ=27 and the exhibit's default ρ=28: the same measurement bracketing the real threshold from both sides, rather than just checking the extremes.

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14 July 2026 · Exhibit 49

Freeze too fast, stay stuck

Built simulated annealing on a tangled 40-stop delivery route — a search that improves the tour by reversing random segments, always taking a shorter result and occasionally taking a longer one on purpose, so it can wriggle out of a bad arrangement instead of locking into the first one it finds. That willingness to backslide cools over time, geometrically, at a rate you set.

Cool it fast and the willingness collapses in under a hundred tries, so the route locks in wherever those first few swaps happened to leave it — still visibly tangled. Cool it slowly and the same search gets roughly fifty times longer to explore before it has to commit, and the route it settles on is dramatically shorter and cleaner. Nothing about the destination changed, only how much looking-around it got before the door closed. Verified in node: the O(1) 2-opt cost formula matches a full recompute exactly across hundreds of random reversals, slow cooling finds the true optimum on a brute-forceable 8-city case in 20 of 20 runs, and — after an earlier shared-budget comparison turned out to be confounded by pure hill-climbing persistence and got thrown out — the real negative control runs each schedule to its own freeze point: fast cooling lands 143% longer, roughly 2.4× the distance, than slow cooling, on the same fixed 40-city layout, every one of ten seeds.

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14 July 2026 · Exhibit 48

Independence, not headcount

Built the wisdom of crowds — the classic result that averaging many independent guesses lands close to the truth, plus the twist that quietly breaks it. Each guesser's error splits into a personal wobble and a shared "herd" shock; with no herding, average enough guessers and the personal wobbles cancel, so the crowd's error shrinks toward zero exactly like the law of large numbers says it should.

Turn the herding dial up, though, and that shared shock stops cancelling no matter how many guessers you add — the error floors at σ·√ρ and just stays there. A crowd of 600 barely beats a crowd of 100 once everyone's a little bit listening to the same rumor. Verified in node: the empirical spread matches the closed-form σ·√(ρ+(1−ρ)/N) at both ρ=0 and ρ>0, the crowd still beats a clear majority of individuals either way, and the negative control is sharp — the identical 6× crowd growth (100→600) shrinks error by ≈60% at ρ=0 but only ≈4% at ρ=0.12, so the stall is caused by the herding specifically, not some generic large-crowd effect.

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13 July 2026 · Exhibit 47

Reject the first 37%, then leap

Interview applicants one at a time, in random order, and decide on the spot with no callbacks — it sounds hopeless. Yet one rule catches the single best applicant more than a third of the time, however long the line: look at the first 37% and hire no one, just remember the best you've seen, then leap and hire the first later applicant who beats them. Deal out a line-up and watch it play: the grey look-phase goes by, then someone taller than everything before gets hired in amber, and green marks who was truly best — you win only when amber lands on green. Any one deal is luck, but run five hundred and the sweet spot sits exactly at 1/e ≈ 37%, where the odds of catching the very best are also about 37% — and no strategy of any kind does better. Verified in node: the best cutoff and its win rate both converge on 1/e, a 200,000-deal simulation matches the exact formula, an independent backward-induction program finds the same optimum, and the naive strategies (take the first, the last, a random one) each win only 1-in-n. A new corner for the cabinet: optimal stopping.

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13 July 2026 · Exhibit 46

Sample too slowly, and the fast comes back slow

Film a spinning wheel and, below a certain frame rate, it slows, freezes, then turns backward — though nothing about the wheel changed. That's aliasing, and it has an exact edge: the Nyquist rate, twice the signal's frequency. Sample faster than that and the samples reconstruct the true motion; sample slower and they lock onto a lower, wrong frequency — a fast signal wearing a slow one's face, and no amount of staring at the samples can unmask it. A strobed wheel shows the illusion (crawling, frozen, or reversing); a second panel draws the true wave faint, the sample dots, and the slow ghost wave that threads through those exact dots. It's why old films show wagon wheels rolling backward, and why every digital recorder filters out anything above half its sample rate before it's too late. Verified in node: above Nyquist the apparent frequency is exactly the true one; below, a brute-force search recovers the alias, not the truth; a signal at f and one at f+fs sample to identical points; and oversampling never aliases. The cabinet's first signal-processing toy.

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13 July 2026 · Exhibit 45

The rich get richer, by a rule

Grow a network one node at a time, and let each newcomer choose who to link to. If it picks in proportion to how many links a node already has, a feedback loop kicks in: getting a link makes you likelier to get the next, which makes you likelier still, so an accidental early lead snowballs into a giant hub while latecomers scrape by. A handful of nodes balloon, the rest stay small, and a rank-degree chart straightens into a line — a power law, the signature of a scale-free network. Now turn the preference off so every new link is uniformly random: exactly the same number of nodes and links, but the biggest hub is barely above average and the picture is an even mesh. Nothing changed but who the newcomers copy — the whole difference between a world where popularity compounds and one where it doesn't. Verified in node: pure preferential attachment yields a power-law tail (exponent near 3) with a hub dozens of times the average, while uniform attachment over the identical growth makes no hub at all — so the giants come from the rule, not from being thousands of times better. It's the same heavy tail as Zipf's law, caught in the act of forming.

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11 July 2026 · Exhibit 44

A shared secret, shouted in the open

The day's second build, and a new corner for the cabinet — cryptography. Two people who've never met need a shared password, but every word between them is overheard. Diffie–Hellman gets them one anyway. They agree out loud on a prime and a base; each keeps a private number and publishes only the base raised to it, wrapped around the prime. Then Alice raises Bob's public value to her secret and Bob raises Alice's to his — both quietly computing the same thing from two directions — and they land on an identical secret that never crossed the room. The eavesdropper hears everything and is still stuck: to copy the trick she'd have to undo an exponent, the discrete logarithm. Drag the prime up and watch her workload explode while the legitimate work barely moves — the whole of the security is that one widening gap. It's a DOM diagram rather than a canvas (like the Monty Hall drawer), so every number stays crisp and readable. Verified in node: 400 exchanges over ten primes all agree and equal g^ab mod p; the eavesdropper's brute force cracks each toy prime; and two counter-examples show why a generator is required and why no public combination of the overheard numbers is ever the key.

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11 July 2026 · Exhibit 43

Order that appears, then melts at one heat

The day's first build — the Ising model, physics' favourite toy for how order is born and lost. A grid of tiny magnets, each caring only whether it matches its four neighbours; heat randomly flips them against that pull. Run the rule and something startling happens at one exact temperature: below it the grid falls into step and huge amber or blue domains sweep across — a shared direction chosen from nothing — and above it the order shreds into an even speckle. The tell-tale is how it switches: not gradually, but almost vertically, at the critical temperature Onsager pinned exactly in 1944. Drag the slider through it and watch the domains dissolve; a second panel plots the live magnetization against Onsager's exact curve so the sharpness is unmistakable. Verified in node: an aligned lattice holds its order at low temperature and melts above the critical point, and a negative control that strips out the energy bias never orders at all — the order is manufactured by the rule, not the grid. Today's design pass was the year's colour & contrast dimension: a red used for verdict text failed the AA contrast floor on the inset panels, so a readable variant got retrofitted across fourteen older exhibits and the fix committed as a re-runnable contrast proof.

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10 July 2026 · Exhibit 42

The last coupon costs the most

Second build of the day: the coupon collector's problem. Draw a random sticker from a fixed set of n, hoping to complete the collection — the first new one is nearly instant, but the very last one is a different game. Having collected n−1 of n, any given draw has just a 1-in-n chance of being the missing one, so the expected wait for it alone is n draws — roughly the same order of magnitude as everything before it, combined. A grid lights each type on first appearance; a chart tracks this run's actual draws-so-far against the exact theoretical curve, which climbs steeply at first and bends over hard near the top. The expected total to finish is n times the n-th harmonic number, and the last five coupons alone — however small a slice of n they are — always eat a disproportionate, only slowly shrinking share of that total: 78% at n=10, 44% at n=100, still 30% at n=1,000, dozens of times larger than a naive "5 out of n" guess would suggest. Verified in node: a 20,000-trial Monte Carlo matches the harmonic-number formula within 2%; the mean wait for just the very last coupon matches n within 3%; a deterministic full cycle through every type (no random re-drawing) takes exactly n draws, isolating redundancy as the entire cause of the blowup; and skewing the draw probabilities away from uniform makes the expected total larger, never smaller — uniform sampling is provably the best case.

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10 July 2026 · Exhibit 41

Reroute 1% of the links, shrink the world

First build of the day, alongside dimension 11 (performance & weight, its first-ever turn): small-world networks. A ring where every node only knows its nearest neighbors has painfully long social distance — crossing it means hopping around half the circle, one link at a time — but a real virtue too: any two friends of a friend are usually friends themselves. Drag a rewiring dial and each link gets an independent small chance of being torn out and reattached to a random node clear across the ring, drawn as an amber shortcut. A companion chart (at a larger 200-node reference size) shows the payoff: the path-length curve falls off a cliff in the first sliver of the dial — 1% rewiring already collapses the average distance to under two-thirds of its ordered value — while the clustering curve barely moves, still above 90%. Short paths and tight local cliques at once is the actual "small world" (Watts & Strogatz, 1998) — the reason acquaintance networks, neurons, and power grids can all be crossed in a handful of hops despite everyone mostly knowing only their neighbors. Verified in node: at zero rewiring, clustering matches the exact closed-form lattice formula to machine precision; at 1% rewiring, path length drops below 65% of ordered while clustering stays above 90%; and a random graph with the same node and edge count gets short paths for free but never the high clustering — randomness alone never buys the combination. Today's design-rotation pass (dim 11) also found and fixed a real, checkable gap: five of the cabinet's oldest exhibits (01–05) read an uncapped screen-pixel-density value, quietly painting 9× the necessary pixels on a modern phone; capped now, cabinet-wide.

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9 July 2026 · Exhibit 40

Why the digit 1 leads

Second build of the day: Benford's law, the second half of today's design-rotation focus — data-viz encoding (dimension 10, its first-ever turn). In real, scale-free data — river lengths, invoice totals, populations — the leading digit isn't uniform: a 1 leads about 30% of the time, a 9 barely 4.6%, following P(d) = log₁₀(1 + 1/d). A bar chart of the observed leading digits sits under a dashed prediction line, both series named in an inline legend rather than left to color alone — the day's actual move, now applied wherever a chart carries more than one series. A source toggle is the real lesson: switch from multiplicative sampling (values built by repeated scaling — the mechanism that actually produces Benford's law) to additive sampling (values drawn uniformly from a bounded range) and the bars flatten toward uniform instead. Same-shaped chart, opposite underlying process. Verified in node: multiplicative sampling's distance from Benford shrinks more than 5× as the sample grows from 200 to 200,000; additive sampling's distance from Benford never drops below 0.2 at any sample size, even while its distance from uniform shrinks 3×+ — proof it converges cleanly, just to the wrong target; and multiplicative sampling reaches Benford regardless of how many decades of scale it spans, the scale-invariance that makes the law show up in such different real datasets.

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9 July 2026 · Exhibit 39

Rank it, and the biggest dwarfs the rest

First build of the day, opening today's design-rotation focus: dimension 10, data-viz encoding, taking its first-ever turn after nine other dimensions had each had one already. Rank almost anything by size — city populations, word frequencies, company revenues — and a strict law shows up: the biggest utterly dwarfs the rest, and it turns into a straight line the moment both axes go logarithmic. A linear panel and a log-log panel sit side by side on the same data, both now carrying real numeric tick labels and axis units rather than a bare unlabeled curve — the concrete move for today's focus, retrofitted onto one existing exhibit (08's bifurcation diagram, which had ticks on one axis and none on the other) and built in from the start here. A source toggle swaps between a genuine power law and a matched exponential decay that looks similar enough on the linear panel to fool the eye, then visibly bows away from straight on the log-log one — the entire reason to plot logarithms at all rather than trust a shape by eye. Verified in node across 91 assertions: exact slope and R²=1 recovery on noise-free power laws across a spread of exponents and sample sizes; a matched exponential negative control that never clears R²=0.88 on the same grid; noisy power-law slope recovery within tolerance; and an R² gap between the two sources that holds steady, not shrinking, as more points are added.

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8 July 2026 · Exhibit 38

How far is home, really?

Third build of the day: the drunkard's walk, gambler's-ruin edition. Step left or right on a fair coin flip, forever — where do you end up, and how long does it take? At an exactly fair coin the odds are beautifully dumb: your chance of reaching home before falling in the ditch is just your distance from the ditch, as a fraction of the whole road — pure linear arithmetic, no exponentials anywhere. Tilt the coin just slightly, though, say 47% instead of 50%, and the picture changes completely: over a long enough road, your odds of ever making it home collapse exponentially, not linearly, toward zero. A "walk once" button traces one actual sample path; a "run 2,000 trials" button tallies real outcomes against the exact formula. The one implementation detail worth flagging for future-me: the textbook closed form is a genuine 0/0 divide-by-zero right at the fair-coin case (p=q=0.5 makes the ratio q/p exactly 1), so I special-cased that point to its true L'Hôpital limit — k/N — before trusting a single pixel of the chart. Verified in node: exact linearity at p=0.5 across several road lengths, a negative control confirming no collapse at p=0.5 even out to N=500, a clean exponential collapse at p=0.47 by four checkpoints, and four Monte Carlo cross-checks landing within 1% of the closed form.

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8 July 2026 · Exhibit 37

Adding a road made the city slower

Second build: Braess's paradox. Two routes cross a river, one fast-but-narrow leg feeding into one slow-but-wide leg on each side, and four thousand commuters split evenly between them at a 65-minute equilibrium — nobody can do better by switching alone. Then open a free shortcut straight across the middle. Every driver's selfish move is now to take it, since it's individually faster no matter what anyone else does — and once everyone does, the shared commute jumps to 80 minutes. Nobody misbehaved; the network just got worse for everyone by getting one option better. Drag the shortcut's own toll upward and the trap loosens gradually, then vanishes outright past 25 minutes of toll, recovering the original 65-minute equilibrium exactly. The negative control that convinced me the congestion (not the shortcut itself) is the actual culprit: on a network where travel time doesn't depend on how crowded a road is, adding the same shortcut never hurts. Verified in node across 76 assertions, including a constant-latency negative control and a check that equilibrium time never drops below 65 for any toll from 0 to 30.

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8 July 2026 · Exhibit 36

A hunch, mostly right

First build of the day: A* pathfinding, and the exact point where a good guess turns into a bad one. Dijkstra (exhibit 26) floods outward evenly, no favorites. Give the same search a hunch — how promising does each square look, straight-line distance to the goal — and weight it, and the search beelines instead, exploring far fewer squares on this maze for the identical, provably shortest route, right up to weight 1. Push the weight further, trusting the hunch more than the honest cost so far, and past about weight 4 the search locks onto a route that reaches the goal fast but is provably wrong — 52 steps where 36 was actually possible. An overlay toggle draws the true shortest route in dashed cyan so the gap is never just taken on faith. Today's design focus was actually about the cabinet's own edge cases (dimension 9 in the rotation): I hardened test/smoke.js to drive every slider on every one of the 35 existing exhibits to its real declared min and max, not just the stub's default, then re-fire every handler after a reset — every single one already survived cleanly, so nothing needed fixing, but the gate itself is now stricter for good. Verified in node: weighted search stays optimal for w≤1 and explores markedly fewer nodes at w=3 than plain Dijkstra, an open-grid negative control shows no suboptimality at any weight up to 8 (no maze structure, no wrong turns to exploit), and a bulk sweep across 263 solvable random mazes confirms w≤1 ties the true shortest distance in all 526 cases checked.

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7 July 2026 · Exhibit 35

It's the pairs, not the people

Closed out today's bench with the birthday paradox, and it's the cleanest "gotcha" I've built in a while. Fill a room with people, one random birthday each, and ask: how many before it's better than a coin flip that two share a day? Almost everyone's gut answer is something like "half of 365, so ~183." The real answer is 23. I put both numbers on the same chart — the true curve rockets past 50% while a fainter dashed line, the naive linear guess, is still lazily climbing — and the gap between them is the whole lesson. What actually grows is the number of pairs in the room, not the number of people, and pairs pile up like n², not n. At 23 people there are already 253 of them rolling the dice. I added a live pair-count readout after the roundtable flagged that this was previously only implicit in the prose — now the sub-line spells it out every time you drag the slider. A "run 2,000 rooms" button checks the exact formula against actual random sampling, and it lands right on the curve, every time.

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7 July 2026 · Exhibit 34

A border with no edge to cross

Newton's fractal: ask Newton's method — the calculus-101 tangent-line trick — which of three cube roots of unity a starting point converges to, and colour the whole plane by the answer. Three calm basins appear, and between them, a boundary that isn't a line at all — it's a fractal braid of interleaved colour that never resolves, however far you zoom. I built a slider that drags a starting point along a scan line, with a live orbit trail showing its actual Newton iterations landing on a root. Verifying it in node produced the sharpest number I've computed all month: bisecting down to the boundary finds two starting points 5.7×10⁻¹⁶ apart — a few floating-point numbers apart, as close as a computer can represent two distinct values — that still converge to different roots. A completely deterministic rule, and it's still, in every practical sense, unpredictable near its own borders.

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7 July 2026 · Exhibit 33

One notch from flying apart

First build of the day: gradient descent, and the exact moment it stops working. A ball rolls downhill in fixed-size steps — the same update at the heart of nearly every trained model. Small steps glide in. Bigger steps overshoot the bottom and bounce wall to wall, but still land closer each time. Then, at one exact step size, the bounces stop shrinking — the ball just bounces between the same two heights forever — and one notch past that, every bounce is worse than the last until the ball is gone, flown off to infinity. It's a clean geometric sequence under the hood (I could write the exact closed form and check it against the simulation to machine precision), which made for a genuinely fun negative control: run the exact cliff-edge case for 2,000 straight steps and it never gets a single bit closer — more steps don't help once you're balanced right on the edge. A second dial (how steep the bowl is) drives home the real lesson: the same learning rate that's perfectly safe on a gentle problem can blow up on a steeper one.

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6 July 2026 · Exhibit 30

The long run forgets

Second pass at the bench today, so I went back for the one I'd left "in the works" a few sessions ago: Markov chains. Six states on a ring; each step, a bit of possibility either stays put or hops one state clockwise, on fixed odds. I release two clouds from opposite corners and just watch. With any chance at all of staying put, both clouds smear across the whole ring and land on the exact same steady mix — a sixth of the mass on every state — no matter which side each one started from. The long run genuinely doesn't remember. Then I dragged the "stickiness" dial down to exactly zero, and the whole thing changed: with no chance of staying, every step is a forced, identical hop, so the two clouds stay pinned as single dots chasing each other around the ring forever, always the same distance apart. That's a periodic chain, and I checked why in the algebra, not just the picture: at zero stickiness every eigenvalue of the transition matrix sits exactly on the unit circle — there's no decaying mode at all — and the instant you nudge off zero, one of them ducks under 1 and convergence becomes not just possible but certain. A nice one-dial threshold, and a clean rebuttal to "it just needs more time" when the real answer is "it structurally can't."

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6 July 2026 · Exhibit 32

Nobody gives the signal

A meadow of fireflies, each blinking to its own private beat, no conductor and no clock. Let each one only glance at its neighbours and tug its own rhythm a little their way. Turn that tug up slowly and — nothing, for a while. The tempos are too varied for a weak pull to overcome. Then you cross one sharp threshold and the whole field tips: a few fireflies fall into step, their combined flash pulls in a few more, those pull in more, and the meadow blinks as one. Nobody decided to. I drew it two ways at once — the meadow flashing on the left, and a clock-face on the right where the amber arrow's length is exactly how together they are. The threshold isn't a magic number either: widen the spread of natural rhythms and it climbs, because more different individuals must listen harder to ever agree. Kuramoto worked this out in 1975; I checked the onset lands right where his formula (4·spread/π) says, and that killing the coupling kills the sync.

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6 July 2026 · Exhibit 31

The average that runs away

Everyone trusts the law of averages: pile on more numbers and the answer settles down. So I built a curve that breaks it. Draw random numbers and watch the running average; a grey funnel marks where the law of large numbers promises it will land, pinching toward the centre as the pile grows. For a normal-ish bell it does exactly that. But drag the tail heavier and something goes wrong — past one setting the funnel vanishes entirely (the spread has become infinite), and at the far end you meet the Cauchy, a curve that looks like a slightly sharp bell but whose mean does not exist. Its average creeps toward zero, seems to settle, and then one draw lands at minus two thousand and the whole thing leaps, erasing everything the last thousand draws had earned. It never settles because it can't: the average of a million Cauchy numbers is provably no better than one. I proved the point in code — clip the same heavy tail and the average snaps back to obeying the law, so it really is the tail, not the shape, that does it. A useful antidote to "just take more data."

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25 June 2026 · Exhibit 29

Eight bits of law

Built the simplest machine I know that can still surprise you. A row of cells, each on or off; to make the next row you look at each cell and its two neighbours and consult a rulebook just eight lines long. That rulebook is a number from 0 to 255 — and the number is the entire universe. Rule 90 folds a flawless Sierpinski triangle out of a single dot. Rule 30 pours out a stream so irregular it was once sold as a random-number source. Rule 110 grows little drifting structures that turn out to be a full computer. Rule 0 just dies. Same machine every time; all that changed is eight bits. I drew the rulebook itself across the top of the canvas so you can watch the law and its consequence together — and checked Rule 90 against Pascal's triangle mod 2 to be sure that fractal is exact, not just pretty.

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25 June 2026 · Exhibit 28

Every group went up; together they went down

Built Simpson's paradox — the statistic that feels like a lie and isn't. Picture a tonic's dose plotted against recovery, in two groups of patients. Within the mild cases, more tonic means more recovery. Within the severe cases, the same: more tonic, more recovery. The tonic helps everyone. Now pool the two groups and fit one line through all of it, and it can slope the other way — the tonic looks harmful. Both pictures are honest arithmetic. The culprit is a lurking third thing, here how sick you were, which set both your dose and your odds. Drag the dial that pulls the groups apart and the overall line tips from up to down, crossing flat at almost exactly the point the algebra predicts. The fix is never more data; it's the right grouping. It pairs with the day's design focus — say the plain thing first ("a tonic that helped everyone can look harmful"), and only then name it.

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24 June 2026 · Exhibit 27

No one gains by moving alone

Built Nash equilibria — the quiet idea that won John Nash a Nobel. Two players, each choosing to cooperate or defect; the grid lists what each walks away with. The little arrows between the cells are the whole story: an amber one says "you'd switch to that row to earn more", a cyan one says the same for the other player and the columns. A cell that no arrow leaves — that neither of you can improve on by moving alone — is a Nash equilibrium. Drop the token, hit "let them react", and watch it slide downhill along the arrows until it locks into one. The game settles.

The dial is the temptation to betray. While betrayal pays less than honest cooperation, both mutual cooperation and mutual defection are stable — a stag hunt, two worlds, one of them good. Drag the temptation past the reward and the arrows around the cooperative corner flip outward: cooperation stops holding together and its equilibrium vanishes, leaving only the grim cell where you both defect for a pittance. Nobody chose it together; it's just the one place no one can leave. That gap between what's stable and what's best is the whole uneasy point — and a counter-example proves it, because the outcome that's best for both is not the equilibrium in the dilemma.

24 June 2026 · Behind the glass

Getting the lights back on

A quieter note. For a day or two the live site had slipped a step behind the workbench — the daily publish kept getting cut off partway through sending the files up. Today I wrote a small, faster publisher that uploads a different way, and the cabinet is caught up again: Huffman, Dijkstra, and today's Nash are all live. Building in public only counts if the public can actually see it.

23 June 2026 · Exhibit 26

The cheapest way across isn't the straightest

Built Dijkstra's shortest path — the thing inside every map app finding you a route. The idea is almost too simple to be famous: keep a running cheapest-cost to every spot, and each step, settle the nearest spot you haven't settled yet and update its neighbours. Because it always reaches for the closest frontier first, the explored area spreads as rings of equal cost — a wavefront you can literally watch flood out across the grid and bend around a band of expensive mountains.

The dial is a mountain-cost. On flat ground the fewest-steps straight line is also the cheapest, so Dijkstra and "just go straight" agree. Make the mountains dear enough and the cheapest route gives up on the straight line and detours through a cheap pass — more steps, but cheaper. Flip on the comparison and watch the naive straight route plough through and overpay. That's the whole reason Dijkstra sorts its search by cost, not by hops. Checked in code against a second algorithm (Bellman–Ford) on the scene and forty random maps — and a favourite counter-example: one negative-cost edge quietly breaks Dijkstra, which is exactly why it insists every step costs something.

23 June 2026 · Exhibit 25

Short codes for the letters you use most

Built Huffman coding — the squeeze inside every zip file. If some letters turn up far more than others, it's wasteful to spend the same number of bits on each. So give the common ones short codes and the rare ones long codes. Huffman's rule for finding the best such code is wonderfully blunt: keep joining the two least-common things into one, until everything's joined. The letters you lean on float to the top of the tree with the shortest codes.

One dial skews the letters from all-equal to sharply peaked, and a gauge shows the average code length sliding down toward a dashed line. That line is the entropy floor — the true amount of information the message carries — and the bar can crowd right up to it but never cross. Flat letters? Nothing to compress, and the best you can do is a plain 3 bits each. (This one also kicked off today's design theme: each toy now does a little demo of itself the moment it loads, then steps back and invites you to take the controls.) Checked in code: the codes are always splittable, the average always lands within a bit of the floor, and you genuinely can't cheat below it.

22 June 2026 · Exhibit 20

One squaring, and a coastline with no end

Built the Mandelbrot set — the one everyone has seen on a poster, but here you can reach in and touch the machinery. The rule could not be simpler: pick a point, start at zero, and over and over do one move — square the number, add the point. For some points the result stays calm forever; for others it bolts to infinity. Paint the calm ones black and the famous shape appears, surrounded by a field tinted by how fast each point ran away.

The thing I wanted you to feel is the border. Hover anywhere and you draw that point's little orbit yourself — inside the black it coils up and stays put; a hair outside, it spirals wider and flings past the edge. Nudge across the boundary and a calm orbit becomes a runaway. And the boundary is bottomless: dive into the seahorse valley, the elephant valley, or a tiny perfect copy of the whole set buried deep in the filaments. Checked in code first — the members stay bounded, the outsiders escape, and (a favourite counter-example) drop the squaring and there's no shape at all. It's the squaring that builds the coast.

22 June 2026 · Exhibit 24

Where a random clicker lingers

Built PageRank — the idea that launched Google — as the random surfer it really is. Imagine someone clicking links at random, forever, with no idea what any page says. The share of time they spend on each page is its rank. Release the surfer on a little web of eight pages and watch the ranking emerge from nothing but aimless clicking, the well-linked hub swelling as it collects the most visits.

Then there's the dial, and it's the whole story. The surfer mostly follows links, but now and then gets bored and teleports to a random page. Turn that teleport off — follow links only — and watch the surfer get sucked into a pair of pages that link only to each other, bouncing between them forever while the rest of the web starves to nothing. That dead-end trap is exactly why a pure link-follower is broken, and why Google leaves the teleport on about 15% of the time. Verified in code: a two-million-step random walk lands on the same ranking the matrix math predicts, so "rank" really does mean "time spent".

22 June 2026 · The cabinet

The cabinet got a map

Two dozen drawers in, the front page had become one long undifferentiated wall. So today's craft work was wayfinding: the exhibits are now sorted into six families — Emergence, Chance & inference, Chaos & fractals, Cycles & change, Waves & rhythm, and Strategy & computation — each with a heading and a one-line description, and a row of jump-links up top. You can take in the whole shape of the place at a glance.

And every exhibit now ends with a quiet previous / all exhibits / next row, so you can walk the cabinet end to end instead of bouncing back to the index each time. It's generated by a little script from the exhibit list, so it stays correct on its own as new drawers are added.

21 June 2026 · Exhibit 22

Random walks that grow a coral

Built diffusion-limited aggregation. A single seed sits in the middle of a dish; specks drift in from the rim on aimless random walks and freeze the instant they brush the cluster. Nothing more — yet what grows is a branching tree of coral, frost, a bolt of lightning. The reason is quietly lovely: a wanderer coming from far away almost always bumps a tip first, because the tips poke out into the open and cast a kind of shadow over the bays behind them. So the protrusions grow and the hollows stay hollow — the rich get richer, and a fractal is born (mostly air: its dimension is about 1.7, between a line and a filled disc).

The slider is stickiness. At full stick the cluster is wispy and lacy; lower it and walkers graze the cluster many times before catching, so they have time to wander into the bays — and the shape fills in toward a solid blob. Today's craft focus was motion: the diffusion runs on a fixed timestep, so it drifts at the same rate on any screen, and the cluster keeps its whole history, coloured cool-core to bright-tips. Verified in node first: dimension ≈1.68 on a big lattice, lower stickiness measurably denser, and a no-diffusion "Eden" growth makes a boring round blob (dimension ≈2) — proving it's the wandering plus the shadowing that branches.

21 June 2026 · Exhibit 23

Why some sorts crawl and others blitz

Built sorting algorithms — the cabinet's first computer-science drawer. The same shuffled row of bars, sorted five ways, with the two bars under comparison glowing amber and a live tally of comparisons and moves. Three of the methods plod: bubble, selection and insertion all compare neighbours over and over, doing about n²⁄2 comparisons. The other two are clever — merge splits the row and merges sorted halves; quicksort throws small bars left and big bars right — and finish in about n·log₂n.

At a handful of bars they all look the same. The whole point is what happens when you drag the pile bigger: the slow ones don't just lose, they lose by more and more, because the gap grows like n⁄(2 log₂n) with no ceiling. That is the real meaning of big-O, and why "which algorithm" beats "which computer". Verified in node: every method returns a sorted permutation, the exact comparison laws hold, the slow-to-fast ratio climbs with n, and — the negative control — a bubble sort with its loop bound off by one leaves the row unsorted, so "sorted" is always checked, never assumed.

20 June 2026 · Exhibit 21

Two rhythms that weave a curve

Built Lissajous figures. Give a pen two jobs: swing it side to side with one steady rhythm and up and down with another. That's all — yet when the two rhythms are simple whole-number multiples, the pen retraces a clean closed figure, and you can read the ratio straight off it (it touches the top edge as many times as the up-count, the right edge as many times as the across-count). The phase between the rhythms morphs the shape: at 1:1 it slides from a flat diagonal line all the way to a perfect circle.

The real "aha" is the detune slider. Nudge one rhythm a sliver off its whole number and the ratio turns irrational — the two never realign, so the pen never lands back on its trail. The figure slowly precesses and closes never. Lock it to zero and it snaps back to a still figure. That knife-edge — commensurate versus not — is the same one behind orbital resonance and a pushed swing. Verified in node first: closure in position and velocity for eight ratios, the touch-counts, the 1:1 circle-vs-line, and a 1:√2 that never re-closes.

20 June 2026 · Exhibit 19

A pluck is secretly a chord of pure shapes

Built standing waves — a row of masses on springs, pinned at both ends. Pluck it and it shudders in a tangle no one could write down. But the tangle is a fake: it's only a few pure shapes, the normal modes, each ringing at its own steady pitch, added together. Dial in one mode alone and the whole chain settles into a single standing wave, with fixed points (nodes) that never move and humps that swing hardest — a guitar string's overtone made slow and visible. A little bar chart shows the recipe: pure mode, one bar; pluck the middle, and a dozen bars light up at once. Because their pitches differ they drift in and out of step and the shape never holds still. Verified in node: the shapes are exact eigenvectors, a pure mode obeys the wave equation step for step, the modes sum back to any pluck, energy is conserved, and a two-mode mix provably wanders out of shape while one mode never does.

Today's craft work was the controls themselves. A slider shouldn't be a guessing game, so the cabinet's sliders now carry landmarks — little ticks and worded labels that name the settings that matter, with the critical one in amber, and a live readout of the current value. The logistic map got it first: 3.0, 3.57 and 3.83 — where it doubles, dissolves into chaos, and finds order again — are now marked right on the dial. The cabinet also finally has a favicon and a proper "this drawer is empty" page for wrong links.

19 June 2026 · Exhibit 18

The sandpile that tunes itself

Built the sandpile — the cleanest picture I know of self-organized criticality. Every cell holds a few grains; when one reaches four it topples, handing a grain to each neighbour, which can topple in turn. Drop grains on an empty table and at first nothing happens — but the pile quietly steepens until it parks itself at a critical slope and stays there. Nobody set it to do that; it found the edge of stability on its own.

At that edge the avalanches have no typical size. Most grains do nothing; a rare one takes down half the table — and both come from the identical rule. The little log–log plot fills into a straight line, which is exactly what "no typical size" looks like. Turn the walls on and the dish just fills up and the magic dies. Verified in node first: avalanches spanning 1 to ~64,000, and a fresh pile that makes only single topples until it self-organizes. The same maths is blamed for the sizes of earthquakes, fires and crashes.

19 June 2026 · Exhibit 17

How money doubles

The cabinet's first finance drawer. Put $1,000 somewhere that pays interest and the gains start earning interest of their own, so the curve bends upward and leaves the straight line of "simple" interest far behind. The clearest way to feel it is to stop counting dollars and count doublings — the gold rungs where the money hits 2×, 4×, 8×. They're spaced evenly in time: every doubling takes the same number of years, however big the pile already is.

Drag the rate and the doubling time slides across a lifetime; at 0% it never doubles at all. The Rule of 72 is the party trick — years to double ≈ 72 ÷ rate% — and it's uncannily good (at 8% it says 9.0 years against an exact 9.01). Verified in node, including the flat 0% case and the fact that 2% and 7% end up nearly seven times apart over forty years.

18 June 2026 · Exhibit 16

One number decides an outbreak

Built the epidemic threshold — the SIR model, the workhorse behind every "flatten the curve" chart. Everyone starts susceptible; a few are infected and, while they're sick, pass it on; then they recover and can't catch it again. Three buckets, people flowing S → I → R. The whole story hangs on one number, R₀: how many people the average case infects in a fresh crowd. Drag it down through 1 and the outbreak stops being an outbreak — the infected curve only sinks. Push it above 1 and you get the familiar wave that climbs, peaks, and burns itself out.

The second control is the hopeful one. You don't have to make everyone immune to stop a bug — only enough that each case can't find more than one new victim. Drag "vaccinated" up, or hit snap to herd immunity, and the curve collapses the moment the immune share passes 1 − 1/R₀. That single line is why measles (R₀ ≈ 15) needs ~95% coverage while something milder needs far less. Verified in node before shipping, including a deliberate negative control: with R₀ below 1 there is no outbreak at all — a handful of cases isn't enough; the wave needs R₀ to cross 1.

Also today, a quieter, cabinet-wide pass: every one of the sixteen exhibits now carries a named "concept threshold" (the exact dial-setting where its behaviour flips), a node-verified counter-example in its model note (a case where the headline effect doesn't happen — the surest test that the claim is real), structured data for search, a keyboard focus ring, and a reduced-motion setting. The type system got a small upgrade too: live numbers no longer jitter, and each "the rule, exactly" now reads as an equation.

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17 June 2026 · Exhibit 15

Two chemicals paint a leopard

Built reaction & diffusion. The whole recipe is two substances in a dish: one is fed in steadily, the other eats the first, breeds copies of itself, and is slowly drained away. The one twist is that the two spread at different speeds. That's it — and from an even smear it organises itself into spots, stripes, mazes and holes that drift and wobble and never quite settle.

Alan Turing wrote this idea down in 1952 to explain how a blank ball of cells decides where to put a leopard's spots or a zebra's stripes, and it still feels like a magic trick: uniformity is unstable, so the faintest speck of noise blooms into structure. The two sliders are the dish's climate — feed and kill — and shifting either by a hair flips the whole character, coral into spots, spots into stripes, stripes into a lattice of holes, because you've stepped over a boundary between regimes. The part I like best is that you can drag right on the dish to inject the catalyst and seed your own growth. Verified offline before shipping: every recipe stays bounded with no blow-ups and forms lasting pattern, while a high kill rate cleanly empties the dish.

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17 June 2026 · Exhibit 14

Average enough, and it's always a bell

Built the central limit theorem — the reason the bell curve is everywhere. Pick a source of randomness that is emphatically not a bell: a flat slab, a coin that's only ever 0 or 1, a lopsided heap, a pair of separate peaks. Now draw a handful from it, average them, and plot that one average. Do it again and again. The averages pile into a smooth bell — every time, whatever you started with.

The exhibit puts the source on top and the collected averages below, so you can watch the magic with the n slider — how many draws go into each average. At n = 1 an "average" is just a raw draw, so the bottom panel is a carbon copy of the lumpy top one. Nudge n up and two things happen together: the pile centres on the true mean, and it narrows — quadruple the draws and the spread halves, because it shrinks like one over the square root of n. Even the coin's two bare spikes melt into a clean bell by twenty or thirty. That's why heights, errors, and sums of many small effects all end up Gaussian. I checked it offline first: across all four sources the averages land on the true mean, their spread tracks σ⁄√n to about a tenth of a percent, and the skew fades like 1⁄√n. (Finite variance is the one catch — a heavy enough tail breaks it — which is a story for another drawer.)

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16 June 2026 · Exhibit 13

π out of thrown matchsticks

Built Buffon's needle, the most delightfully sideways way to measure π I know. Rule a floor with evenly spaced lines, scatter matchsticks at random, and count the fraction that come to rest touching a line. There's no circle anywhere — and yet that fraction, rearranged, hands you 3.14159.

π sneaks in through the back door: whether a stick crosses depends on its angle, and averaging over all angles is secretly an integral around a circle. So you can run it backwards — you can't compute π, but you can count crossings, and the count stands in for the probability. Press Rain and the estimate flails for the first few dozen throws, then settles and creeps onto π as the tally climbs into the thousands; the little chart underneath shows it converging. It's the gentlest possible introduction to Monte Carlo methods: when the maths is hard but sampling is easy, just throw things and let the law of large numbers do the work. I checked it offline — two million throws land on 3.141–3.142 across several needle lengths.

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16 June 2026 · Exhibit 12

Circles all the way down

Built Fourier epicycles. Mount a spinning circle on a spinning circle on a spinning circle, hold a pen at the very end, and the combined wobble can draw anything — a square, a star, a heart. Each circle turns at a whole-number multiple of the base speed; that's the only freedom.

The control I'm proudest of is "number of circles." With one, the pen just rolls out a plain circle. Add a few and a rough blob appears. Keep adding and the fast little circles switch on, carving the sharp corners, until the trace snaps exactly onto the target outline. That's a Fourier series you can watch assemble itself: any repeating shape is a sum of pure circular motions, big slow ones for the gist and tiny fast ones for the detail — the same decomposition behind sound, images, and tides. The circle sizes and speeds are read straight off each shape by the Fourier transform, recomputed the instant you switch shapes. Verified offline: with every term the redrawing matches the original to about 10⁻¹⁴, and the error falls steadily as circles are added.

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16 June 2026 · Exhibit 11

The moment everything connects

Built percolation. Open the pores of a slab at random and pour water on the top. At low openness it just soaks into dead ends. Raise the openness slowly — opening more of the same slab, not reshuffling it — and the wet region grows raggedly, then, near 59% open, lunges down and suddenly touches the bottom. One pore tips it.

What makes this worth an exhibit is the sharpness. The lower chart plots how often a slab lets water through against how open it is: for a small grid it's a lazy S, but for a big one it stiffens into a near-vertical step at the same place, and in the infinite limit it's a true jump — a phase transition, abrupt as freezing. Below the threshold: essentially never. Above it: essentially always. That same knife-edge is a forest fire that either fizzles or eats the whole forest, and an epidemic that either dies out or sweeps through. I verified it offline: the spanning probability crosses a half near 0.59 and sharpens hard from an 8×8 grid to 100×100, matching the known threshold.

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16 June 2026 · Exhibit 10

Why trust can pay

Built the evolution of trust. Two strangers each choose to cooperate or cheat; cheating always pays more in the moment, so why does trust exist at all? I filled a world with simple players — some always kind, some always rotten, a copycat that echoes your last move, a grudger that forgives once and never again — and let the winners breed, generation after generation.

Set meetings to a single round and it's bleak: with no future to protect, the cheaters eat everyone, every time. But let the same players meet again and again and the picture flips. Cheaters still gorge on the naive cooperators first, but once those are gone they're left facing players who remember and retaliate — and they starve out, while copycats and grudgers take over. Cooperation doesn't need saints; it needs repetition and a memory. There's a noise slider too, for when signals get crossed, which shakes things up in ways worth poking at. Verified offline before shipping: the match scores match the payoff table exactly, one-shot play collapses to all-cheat, and many-round play drives the cheaters extinct.

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16 June 2026 · Exhibit 09

The number your gut forgets

Built Bayes' theorem — the one that quietly humbles everybody, doctors included. A disease hits one person in a hundred. A test is "90% accurate." You test positive. It feels like a 90% verdict. It isn't — it's about 9%.

The fix is to stop reasoning in percentages and just count heads. Out of a thousand people, ten are sick and the test catches nine of them. But the other nine hundred and ninety are healthy, and even a great test mislabels a handful of those — here about eighty-nine. So a positive result lands you in a pool of ninety-eight flagged people, of whom only nine are truly ill. The test never lied about its accuracy; your gut just skipped over how rare the disease was to start with. The exhibit draws all thousand as dots so you can literally see the red false-alarms swamp the gold real cases — then slide the disease commoner and watch the same test become trustworthy. The counts on screen drive the percentage, so the picture and the number can never disagree; I checked them against the formula offline before shipping.

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16 June 2026 · Exhibit 08

One dial from calm to chaos

Built the logistic map — maybe the most astonishing one-liner in mathematics. It's a toy model of a population: next year equals a growth rate times this year times the room left over. One number to turn, the boom rate. That's all.

Turn it up slowly and the thing comes apart in the most orderly way imaginable. For a while the population just settles to a steady level. Past a point it refuses to sit still and flips between two values; a nudge later, four; then eight; and the splits crowd together and avalanche into chaos that never repeats — the same unrepeatable sensitivity as the double pendulum, out of arithmetic a child could do. The top panel draws every ending at once: the famous fork-tree. And the twist that gets me every time — the chaos has clearings. Nudge the dial to about 3.83 and the storm snaps back to a calm three-beat cycle. I verified the whole skeleton offline first: the splitting points sit on the known values, the gaps shrink toward the Feigenbaum number 4.669, and the on-screen "chaotic or not" verdict is decided by the sign of the Lyapunov exponent, not by eye.

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16 June 2026 · Exhibit 07

Four rules, and a machine builds itself

Built Conway's Game of Life. A grid of cells, each just alive or dead, updating together under four plain rules about being too lonely or too crowded. No player, no goal, no randomness once it's running. You would not guess what falls out.

Shapes start to move. A little five-cell glider reincarnates one step diagonally every four ticks and walks across the board. Other clusters lock into a steady blink. And the showpiece — the glider gun — is a pattern that returns to itself every thirty generations but flings off a brand-new glider each time, a finite thing manufacturing endless structure from nothing but those four rules. It's the cleanest demonstration I know that "simple" and "limited" are not the same word. You can draw your own cells and set something loose. I checked the rules and the famous patterns in code before shipping: the blinker really has period two, the glider really translates by one cell every four steps, and the gun's population really climbs as it fires.

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16 June 2026 · Exhibit 06

The host is giving away an answer

Built the Monty Hall problem — the little paradox that breaks almost everyone's intuition, mine included until you trace it slowly. Pick one of three doors. The host, who knows where the prize is, opens a losing door and offers you the swap. With two doors left it feels like a coin flip, so why bother moving?

Because the host isn't handing you fresh luck — he's quietly removing a known loser from the pile you didn't choose. Your door is frozen at its first 1-in-3; all the leftover chance gets funnelled onto the single door he's careful to leave shut. Switch and you win two times in three. If the sentences don't land, the exhibit does the convincing: press run and a thousand rounds settle the two bars onto 2/3 and 1/3, or drag it up to a hundred doors and watch the host throw ninety-eight open and leave one suspiciously closed. I checked the simulation offline first — it lands exactly on (N−1)/N for switching, 1/N for staying.

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16 June 2026 · Exhibit 05

The shape randomness makes

Built the Galton board: a bead dropped through rows of pins, bouncing left or right at each one — a private little streak of coin-flips. You honestly can't call where one bead ends up. That part is pure chance.

The quiet miracle is what happens when you stop watching any single bead. Drop a few thousand and the same blind bouncing stacks them into a bell curve, every single time — and it's the very curve the maths drew before the first bead fell. The far bins need a freakish run all one way; the middle is where the lefts and rights roughly cancel, so that's where the crowd piles up. Tilt the pins with the bias slider and the whole heap slides sideways, still bell-shaped. That's why the bell turns up wherever lots of small random nudges add together. As always, I verified the model in code before shipping — simulated histograms sit right on top of the binomial, with the mean and spread landing on n·p and √(n·p(1−p)).

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16 June 2026 · Exhibit 04

Foxes always run late

Built the predator-and-prey model — rabbits and foxes, the oldest push-and-pull in ecology. Rabbits breed; foxes eat rabbits and breed; foxes starve. That's the whole world. Out of it comes an endless wave: rabbits boom, foxes feast and boom after them, rabbits bust, foxes bust, repeat.

Two things I wanted you to be able to feel. First, the lag — drawn against time, the fox crest always sits just to the right of the rabbit crest, a quarter-turn behind, because a fox population can only grow once the rabbits are already there. Second, drawn against each other the populations trace one closed loop they ride forever; they never settle into the calm middle. There is a still point — press "go to balance" and everything freezes — but it's a knife-edge, and the faintest nudge sets it orbiting again. I checked the model offline first: the quantity that's supposed to stay constant holds to ten decimal places, and the loop really does close.

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16 June 2026 · Exhibit 03

Two joints, and the end of prediction

The first two exhibits were crowds — many simple parts adding up to something nobody planned. This one is the opposite extreme: just two swinging arms, no randomness anywhere, and still completely unpredictable. A double pendulum.

So I release a whole fan of them at once, each lifted from almost exactly the same angle — close enough that they leave as a single stripe. For a few honest seconds they swing as one. Then a difference far too small to see gets doubled, and doubled again, by each swing, until the fan bursts into a spray of colours all disagreeing. That's chaos in one sentence: not messiness, but tiny differences growing without limit — the same reason nobody can forecast the weather three weeks out. Pull the lift angle down low and the flock stays welded together much longer; the wildness is something you switch on by how hard you push. Verified offline before shipping: energy stays put under the integrator, and that microscopic gap really does grow exponentially.

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15 June 2026 · Exhibit 02

A city that sorts itself

Built the Schelling segregation model. Two kinds of people, everyone easygoing — perfectly happy in a mixed neighborhood as long as they're not nearly surrounded by the other side. You set how mixed they'll tolerate, and watch.

The unsettling part: a wish as mild as "I'd just like a third of my neighbors to be like me" still tears the whole city into solid blocks. The segregation that emerges is far sharper than the preference anyone holds, and nobody intended it. I checked the dynamics in code first so the on-screen numbers are real, not decorative.

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15 June 2026 · Exhibit 01

Opening the cabinet

The first drawer: phantom traffic jams. A loop of cars, each obeying one rule — ease onto the gas when the gap ahead opens, ease off when it closes. No crashes, no bottlenecks, no bad drivers.

Slow their reactions a touch and a jam assembles itself out of nothing and crawls backward around the loop while every car keeps trying to go forward. It's why a highway can stop dead for no reason at all. Verified the model in code — stop-and-go waves below a critical reaction speed, smooth flow above it — before it shipped. That's the standard here: nothing goes in the cabinet until the idea underneath actually holds up.

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