Generator

markov-blowup

One function in the lti library, called 5 times across 1 essay. Below: what it draws at its defaults, what it draws at every value an essay asks for, the 7 claims it put to the test while drawing them, and where it stands against the rule this site is named for.

At its defaults it draws the markov parameters of a 24-state model: 10 exact zeros, then thirty orders. |CAᵏB| against k. The first 10 are exactly zero — not small, zero, with no rounding in them — because A is a three-point stencil and information takes one step per grid point to travel the 10 points from the actuator to the sensor. After that they grow like ‖A‖ᵏ with ‖A‖ = (n+1)² = 625, reaching a ratio of 2.37·10³³ across the run. A Hankel matrix of these numbers has a dynamic range no rank decision can see through, which is why the textbook route to the McMillan degree returns the wrong integer while the route that reads only samples of H returns the right one.

markov-blowup is one function in lib/figures/lti.js — a model that is a rational function — the degree that is a rank, by two routes that disagree. Everything below came out of it during this build, at arguments taken from the essays rather than invented for this page. A figure here is the figure a reader meets in an essay, and if the generator changes, this page changes with it.

At its defaults

Drawn even though every essay passes arguments — which on this site is every essay, at 100% of placements since the standard pass. A default nothing exercises is a trap for the next essay to call this with none, and this is the page where a default that has drifted from the figures around it becomes visible.

The Markov parameters of a 24-state model: 10 exact zeros, then thirty orders|CAᵏB| against k. The first 10 are exactly zero — not small, zero, with no rounding in them — because A is a three-point stencil and information takes one step per grid point to travel the 10 points from the actuator to the sensor. After that they grow like ‖A‖ᵏ with ‖A‖ = (n+1)² = 625, reaching a ratio of 2.37·10³³ across the run. A Hankel matrix of these numbers has a dynamic range no rank decision can see through, which is why the textbook route to the McMillan degree returns the wrong integer while the route that reads only samples of H returns the right one.02468101214161810²⁹10³³10³⁷10⁴¹10⁴⁵10⁴⁹10⁵³10⁵⁷10⁶¹k|CAᵏB|10 exact zerosa definition that will not computestates24exact zeros10‖A‖, as (n+1)²625range across the run2.4·10³³zero for the travel timethen ‖A‖ᵏ

|CAᵏB| against k. The first 10 are exactly zero — not small, zero, with no rounding in them — because A is a three-point stencil and information takes one step per grid point to travel the 10 points from the actuator to the sensor. After that they grow like ‖A‖ᵏ with ‖A‖ = (n+1)² = 625, reaching a ratio of 2.37·10³³ across the run. A Hankel matrix of these numbers has a dynamic range no rank decision can see through, which is why the textbook route to the McMillan degree returns the wrong integer while the route that reads only samples of H returns the right one.

n: 24

The arguments are the ones A model that is a rational function passes. A value drawn at the generator's defaults instead would be a picture no essay asked for and no assertion has been run against.

The Markov parameters of a 24-state model: 10 exact zeros, then thirty orders|CAᵏB| against k. The first 10 are exactly zero — not small, zero, with no rounding in them — because A is a three-point stencil and information takes one step per grid point to travel the 10 points from the actuator to the sensor. After that they grow like ‖A‖ᵏ with ‖A‖ = (n+1)² = 625, reaching a ratio of 2.37·10³³ across the run. A Hankel matrix of these numbers has a dynamic range no rank decision can see through, which is why the textbook route to the McMillan degree returns the wrong integer while the route that reads only samples of H returns the right one.02468101214161810²⁹10³³10³⁷10⁴¹10⁴⁵10⁴⁹10⁵³10⁵⁷10⁶¹k|CAᵏB|10 exact zerosa definition that will not computestates24exact zeros10‖A‖, as (n+1)²625range across the run2.4·10³³zero for the travel timethen ‖A‖ᵏ

|CAᵏB| against k. The first 10 are exactly zero — not small, zero, with no rounding in them — because A is a three-point stencil and information takes one step per grid point to travel the 10 points from the actuator to the sensor. After that they grow like ‖A‖ᵏ with ‖A‖ = (n+1)² = 625, reaching a ratio of 2.37·10³³ across the run. A Hankel matrix of these numbers has a dynamic range no rank decision can see through, which is why the textbook route to the McMillan degree returns the wrong integer while the route that reads only samples of H returns the right one.

n: 8

The arguments are the ones A model that is a rational function passes. A value drawn at the generator's defaults instead would be a picture no essay asked for and no assertion has been run against.

The Markov parameters of a 8-state model: 4 exact zeros, then thirty orders|CAᵏB| against k. The first 4 are exactly zero — not small, zero, with no rounding in them — because A is a three-point stencil and information takes one step per grid point to travel the 4 points from the actuator to the sensor. After that they grow like ‖A‖ᵏ with ‖A‖ = (n+1)² = 81, reaching a ratio of 4.59·10²³ across the run. A Hankel matrix of these numbers has a dynamic range no rank decision can see through, which is why the textbook route to the McMillan degree returns the wrong integer while the route that reads only samples of H returns the right one.02468101210⁸10¹²10¹⁶10²⁰10²⁴10²⁸10³²k|CAᵏB|4 exact zerosa definition that will not computestates8exact zeros4‖A‖, as (n+1)²81range across the run4.6·10²³zero for the travel timethen ‖A‖ᵏ

|CAᵏB| against k. The first 4 are exactly zero — not small, zero, with no rounding in them — because A is a three-point stencil and information takes one step per grid point to travel the 4 points from the actuator to the sensor. After that they grow like ‖A‖ᵏ with ‖A‖ = (n+1)² = 81, reaching a ratio of 4.59·10²³ across the run. A Hankel matrix of these numbers has a dynamic range no rank decision can see through, which is why the textbook route to the McMillan degree returns the wrong integer while the route that reads only samples of H returns the right one.

n: 48

The arguments are the ones A model that is a rational function passes. A value drawn at the generator's defaults instead would be a picture no essay asked for and no assertion has been run against.

The Markov parameters of a 48-state model: 20 exact zeros, then thirty orders|CAᵏB| against k. The first 20 are exactly zero — not small, zero, with no rounding in them — because A is a three-point stencil and information takes one step per grid point to travel the 20 points from the actuator to the sensor. After that they grow like ‖A‖ᵏ with ‖A‖ = (n+1)² = 2401, reaching a ratio of 2.82·10⁴⁰ across the run. A Hankel matrix of these numbers has a dynamic range no rank decision can see through, which is why the textbook route to the McMillan degree returns the wrong integer while the route that reads only samples of H returns the right one.024681012141618202224262810⁶⁹10⁷³10⁷⁷10⁸¹10⁸⁵10⁸⁹10⁹³10⁹⁷10¹⁰¹10¹⁰⁵10¹⁰⁹k|CAᵏB|20 exact zerosa definition that will not computestates48exact zeros20‖A‖, as (n+1)²2401range across the run2.8·10⁴⁰zero for the travel timethen ‖A‖ᵏ

|CAᵏB| against k. The first 20 are exactly zero — not small, zero, with no rounding in them — because A is a three-point stencil and information takes one step per grid point to travel the 20 points from the actuator to the sensor. After that they grow like ‖A‖ᵏ with ‖A‖ = (n+1)² = 2401, reaching a ratio of 2.82·10⁴⁰ across the run. A Hankel matrix of these numbers has a dynamic range no rank decision can see through, which is why the textbook route to the McMillan degree returns the wrong integer while the route that reads only samples of H returns the right one.

n: 16

The arguments are the ones A model that is a rational function passes. A value drawn at the generator's defaults instead would be a picture no essay asked for and no assertion has been run against.

The Markov parameters of a 16-state model: 6 exact zeros, then thirty orders|CAᵏB| against k. The first 6 are exactly zero — not small, zero, with no rounding in them — because A is a three-point stencil and information takes one step per grid point to travel the 6 points from the actuator to the sensor. After that they grow like ‖A‖ᵏ with ‖A‖ = (n+1)² = 289, reaching a ratio of 2.01·10²⁹ across the run. A Hankel matrix of these numbers has a dynamic range no rank decision can see through, which is why the textbook route to the McMillan degree returns the wrong integer while the route that reads only samples of H returns the right one.0246810121410¹⁵10¹⁹10²³10²⁷10³¹10³⁵10³⁹10⁴³k|CAᵏB|6 exact zerosa definition that will not computestates16exact zeros6‖A‖, as (n+1)²289range across the run2·10²⁹zero for the travel timethen ‖A‖ᵏ

|CAᵏB| against k. The first 6 are exactly zero — not small, zero, with no rounding in them — because A is a three-point stencil and information takes one step per grid point to travel the 6 points from the actuator to the sensor. After that they grow like ‖A‖ᵏ with ‖A‖ = (n+1)² = 289, reaching a ratio of 2.01·10²⁹ across the run. A Hankel matrix of these numbers has a dynamic range no rank decision can see through, which is why the textbook route to the McMillan degree returns the wrong integer while the route that reads only samples of H returns the right one.

n: 32

The arguments are the ones A model that is a rational function passes. A value drawn at the generator's defaults instead would be a picture no essay asked for and no assertion has been run against.

The Markov parameters of a 32-state model: 12 exact zeros, then thirty orders|CAᵏB| against k. The first 12 are exactly zero — not small, zero, with no rounding in them — because A is a three-point stencil and information takes one step per grid point to travel the 12 points from the actuator to the sensor. After that they grow like ‖A‖ᵏ with ‖A‖ = (n+1)² = 1089, reaching a ratio of 9.6·10³⁵ across the run. A Hankel matrix of these numbers has a dynamic range no rank decision can see through, which is why the textbook route to the McMillan degree returns the wrong integer while the route that reads only samples of H returns the right one.0246810121416182010³⁷10⁴¹10⁴⁵10⁴⁹10⁵³10⁵⁷10⁶¹10⁶⁵10⁶⁹10⁷³k|CAᵏB|12 exact zerosa definition that will not computestates32exact zeros12‖A‖, as (n+1)²1089range across the run9.6·10³⁵zero for the travel timethen ‖A‖ᵏ

|CAᵏB| against k. The first 12 are exactly zero — not small, zero, with no rounding in them — because A is a three-point stencil and information takes one step per grid point to travel the 12 points from the actuator to the sensor. After that they grow like ‖A‖ᵏ with ‖A‖ = (n+1)² = 1089, reaching a ratio of 9.6·10³⁵ across the run. A Hankel matrix of these numbers has a dynamic range no rank decision can see through, which is why the textbook route to the McMillan degree returns the wrong integer while the route that reads only samples of H returns the right one.

What it checked while drawing

Every figure above asserted its own claims on the way to being drawn, and a claim that failed would have failed the build rather than drawn a wrong picture. Those assertions used to leave no trace at all: a passing one returned true and the only evidence the figure had checked anything was that nothing crashed. The list below is what they actually said, collected by running this generator with an observer installed — not a description of what it is believed to check.

7 distinct claims across 6 sets of arguments, grouped below by shape — because most of them are one sentence with a different number in it, and how many separate times that sentence was put to the test is the informative part.

a grid fine enough to have modes and coarse enough to draw

a grid the products can afford

a run long enough to outlast the travel distance

an actuator and a sensor on the grid

and some of them are not

every Markov parameter below the travel distance is exactly zero

matmul shapes agree

Against the rule

The rule does not apply to it. It factorises nothing, so there is no residual it could be withholding. That is worth stating rather than leaving blank: a site that reported the rule as satisfied by every generator would be counting mostly generators the rule never reached.

Across the library: the rule bites on 192 of 346 generators — 174 print a residual and 18 are exempt with a published reason; 154 factorise nothing. Read from lib/residual-rule.js, which is the same body the gate enforces from, and the gate's last check fails the build if this page and it disagree about any generator.

Where it is called

Changing this generator changes every figure on this list. That is what makes the list worth publishing rather than keeping in a check script.

The whole library · All essays · What must fail