A reduced model that interpolates exactly and has a pole in the right half plane
At its defaults it draws a reduced model that interpolates exactly and has a pole in the right half plane. A convection–diffusion system of 30 states at Péclet number 10, whose state matrix is tridiagonal and not symmetric and whose rightmost eigenvalue is -3.49 — stable. It is reduced to order three by two-sided interpolation at {s, 2s, 4s}, and the horizontal axis is s. The curve is the rightmost pole of the reduced model. Above the zero line the model is unstable: it is at 4 of the 19 placements, reaching 24.1. Every one of those unstable models still matches the full system's transfer function at each of its own three interpolation points, to 1.27·10⁻¹⁴ — the construction did exactly what it promised. The dashed line is balanced truncation of the same system at the same order, whose rightmost pole is -0.837: stable, as it is at every order, because stability is a theorem there rather than an outcome.
projection-stability is one function in lib/figures/redstab.js —
a model that interpolates exactly and cannot be run — and the method whose stability is a theorem. 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.
A convection–diffusion system of 30 states at Péclet number 10, whose state matrix is tridiagonal and not symmetric and whose rightmost eigenvalue is -3.49 — stable. It is reduced to order three by two-sided interpolation at {s, 2s, 4s}, and the horizontal axis is s. The curve is the rightmost pole of the reduced model. Above the zero line the model is unstable: it is at 4 of the 19 placements, reaching 24.1. Every one of those unstable models still matches the full system's transfer function at each of its own three interpolation points, to 1.27·10⁻¹⁴ — the construction did exactly what it promised. The dashed line is balanced truncation of the same system at the same order, whose rightmost pole is -0.837: stable, as it is at every order, because stability is a theorem there rather than an outcome.
show: "galerkin-coords"
The arguments are the ones A certificate written in coordinates passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
The 30-state convection–diffusion system at Péclet number 10, written in coordinates x = Dz with D diagonal, whose k-th entry is γ raised to the power tk and whose γ is the square root of the ratio of the two off-diagonals, for t from -3 to 3. The transfer function and the eigenvalues (rightmost -3.49) do not change. Top: the edge of the numerical range on a signed logarithmic axis. Bottom: of nineteen placements, how many one-sided models of orders 1, 2, 3 and 6 are unstable. t -3 (cond D 1.4·10⁶): edge 37.9, unstable 11, 6, 1, 2; t -2 (cond D 1.3·10⁴): edge 19.4, unstable 11, 5, 0, 1; t -1.5 (cond D 1186): edge 12.3, unstable 11, 4, 0, 0; t -1 (cond D 112): edge 6.59, unstable 1, 0, 0, 0; t -0.5 (cond D 11): edge 2.16, unstable 0, 0, 0, 0; t 0 (cond D 1): edge -0.986, unstable 0, 0, 0, 0; t 0.5 (cond D 11): edge -2.86, unstable 0, 0, 0, 0; t 1 (cond D 112): edge -3.49, unstable 0, 0, 0, 0; t 1.5 (cond D 1186): edge -2.86, unstable 0, 0, 0, 0; t 2 (cond D 1.3·10⁴): edge -0.986, unstable 0, 0, 0, 0; t 2.5 (cond D 1.3·10⁵): edge 2.16, unstable 0, 0, 0, 0; t 3 (cond D 1.4·10⁶): edge 6.59, unstable 0, 0, 0, 0.
show: "galerkin-poles", t: -2
The arguments are the ones A certificate written in coordinates passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
A 30-state centred-difference convection–diffusion system at Péclet number 10, written in coordinates rescaled by a diagonal matrix whose k-th entry is γ to the power -2k, of condition number 1.25·10⁴. Its rightmost eigenvalue is -3.49 and the edge of its numerical range — the largest eigenvalue of the symmetric part of A — is 19.4. For nineteen placements s from 0.1 to 100, the rightmost pole of a two-sided model of order 3 at {s, 2s, 4s}, a one-sided (Galerkin) model of order 3 at the same shifts, and a one-sided model of order 6 at six shifts from s to 4s, on a signed logarithmic axis. Unstable placements: two-sided 4, one-sided order 3 0, one-sided order 6 1. Worst poles: 24.1, -5.83 and 2.44.
show: "galerkin-coords", pe: 40
The arguments are the ones A certificate written in coordinates passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
The 30-state convection–diffusion system at Péclet number 40, written in coordinates x = Dz with D diagonal, whose k-th entry is γ raised to the power tk and whose γ is the square root of the ratio of the two off-diagonals, for t from -1.5 to 2. The transfer function and the eigenvalues (rightmost -11.5) do not change. Top: the edge of the numerical range on a signed logarithmic axis. Bottom: of nineteen placements, how many one-sided models of orders 1, 2, 3 and 6 are unstable. t -1.5 (cond D 3.1·10¹⁴): edge 78.9, unstable 11, 11, 9, 2; t -1 (cond D 4.6·10⁹): edge 40.6, unstable 10, 10, 8, 2; t -0.75 (cond D 1.8·10⁷): edge 26.6, unstable 10, 7, 6, 2; t -0.5 (cond D 6.8·10⁴): edge 15.4, unstable 10, 4, 2, 2; t -0.25 (cond D 260): edge 6.58, unstable 10, 0, 0, 3; t 0 (cond D 1): edge -0.247, unstable 0, 0, 0, 0; t 0.5 (cond D 6.8·10⁴): edge -8.81, unstable 0, 0, 0, 0; t 1 (cond D 4.6·10⁹): edge -11.5, unstable 0, 0, 0, 0; t 1.5 (cond D 3.1·10¹⁴): edge -8.81, unstable 0, 0, 0, 0; t 2 (cond D 2.1·10¹⁹): edge -0.247, unstable 0, 0, 0, 0.
show: "galerkin-cond"
The arguments are the ones A certificate written in coordinates passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
For rescalings that skew the convection–diffusion operator further than its original coordinates, the number of nineteen placements at which a one-sided model of order 1 (solid) and order 3 (dashed) is unstable, against the condition number of the rescaling on a logarithmic axis. Pe 10: cond 1.4·10⁶ → 11, 1, cond 1.3·10⁴ → 11, 0, cond 1186 → 11, 0, cond 112 → 1, 0, cond 11 → 0, 0, cond 1 → 0, 0; Pe 25: cond 1.2·10⁸ → 10, 6, cond 2.4·10⁵ → 10, 2, cond 1.1·10⁴ → 11, 0, cond 492 → 10, 0, cond 22 → 0, 0, cond 1 → 0, 0; Pe 40: cond 3.1·10¹⁴ → 11, 9, cond 4.6·10⁹ → 10, 8, cond 1.8·10⁷ → 10, 6, cond 6.8·10⁴ → 10, 2, cond 260 → 10, 0, cond 1 → 0, 0.
show: "galerkin-poles", t: 1
The arguments are the ones A certificate written in coordinates passes. A value nobody placed would be a picture no essay asked for and no claim was ever checked against.
A 30-state centred-difference convection–diffusion system at Péclet number 10, written in coordinates rescaled by a diagonal matrix whose k-th entry is γ to the power 1k, of condition number 112. Its rightmost eigenvalue is -3.49 and the edge of its numerical range — the largest eigenvalue of the symmetric part of A — is -3.49. For nineteen placements s from 0.1 to 100, the rightmost pole of a two-sided model of order 3 at {s, 2s, 4s}, a one-sided (Galerkin) model of order 3 at the same shifts, and a one-sided model of order 6 at six shifts from s to 4s, on a signed logarithmic axis. Unstable placements: two-sided 4, one-sided order 3 0, one-sided order 6 0. Worst poles: 24.1, -3.91 and -3.49.
What it checked while drawing
Every figure above checked its own claims on the way to being drawn, and a claim that failed
would have stopped the picture rather than shipped a wrong one. Those checks 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.
130 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.
no weighted model fails, Pe 10, ratio 1 — checked 21 times
no one-sided model is unstable where the range is in the left half plane (t = 0, order 1) — checked 20 times
the Lyapunov-weighted projection is stable at t = -3, order 1 — checked 18 times
no weighted model fails, Pe 40, ratio 1, centred — checked 14 times
no weighted model fails, Pe 40, ratio 1, upwind — checked 14 times
no one-sided pole crosses the range edge at Pe 4 — checked 8 times
a centred or an upwind convection stencil
a grading of 100 or 1,000
a grading ratio between a uniform mesh and ten thousand
a grading ratio of 10, 100 or 1,000
a grid the reductions can afford
a Lyapunov equation with a solution
a Péclet number the centred difference can carry
a Péclet number the error sweep is drawn at: 10, 25 or 40
a Péclet number the graded sweep measures: 10, 40 or 100
a Péclet number the rescaling sweep is drawn at: 10, 25 or 40
a Péclet number this reading is drawn at: 4, 10, 16, 25 or 40
a Péclet number whose Gramians this site can solve for
a projection that exists
a reduction that removes something and keeps something
a rescaling exponent this reading is drawn at: −2, −1, 0 or 1
a sweep with something in it
a truncation above the numerical rank of the Gramians
an interpolation point that adds a direction
and a band of shift placements returns an unstable reduced model
and balanced truncation at the same order does not lose stability
and some rescaling makes one-sided models unstable
at t = 1 the numerical range is the spectrum
every one-sided model of order 6 is stable
every one-sided pole lies inside the numerical range
every weighted model is stable
every weighted upwind model is stable
Jacobi needs a symmetric matrix
LU is for square matrices
matmul shapes agree
small cells at the outflow or at the inflow
the projection is biorthogonal as normalised
the system being reduced is stable
the two-sided model's poles do not depend on the coordinates
the unstable models interpolate at the points they were given
while others return stable ones, so it is a band rather than a rule
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 217
of 397 generators —
199 print a residual and
18 are exempt with a published reason;
180 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.
A certificate written in coordinates
Every one-sided reduced model of the convection–diffusion system was stable, because its poles cannot leave the numerical range and the range sat in the left half plane. Rescale the state by a diagonal matrix and nothing about the system changes — not its eigenvalues, not its transfer function, not one pole of any two-sided model — but the numerical range moves. At Péclet 40 a rescaling with condition number 260 pushes its edge to +6.6 and ten placements of nineteen return unstable one-sided models. Projecting in the inner product of a Lyapunov solution puts the certificate back in any coordinates.
Reduction, and what a model is forA model that cannot be run
A stable system, reduced by matching its transfer function at three points exactly, comes back with a pole in the right half plane at four of nineteen placements — and matches at all three points to 1.3·10⁻¹⁴ while doing it. The construction did what it promised.
Reduction, and what a model is forHalf the conditions and a certificate
A two-sided interpolatory reduction of a stable convection–diffusion system came back unstable at four placements of nineteen. The one-sided reduction built from the same kind of solves came back stable at all 152 placements measured across eight Péclet numbers, and not by luck: every pole of a Galerkin model lies inside the numerical range of the operator, whose edge here is exactly the diffusion term's largest eigenvalue, −0.986 at Péclet 10. The price is the slope conditions, and spent as six one-sided shifts instead of three two-sided ones it beats the stable two-sided model at seven placements of ten.
Reduction, and what a model is forThe inner product the mesh already computed
A Galerkin reduced model is certified stable when the operator's numerical range sits in the left half plane, and the certificate belongs to the coordinates. The coordinates that broke it before were a constructed rescaling. Grade a convection–diffusion mesh towards its outflow boundary layer — the grading anyone resolving the layer would choose — and nodal values break it too: the range's edge is past zero at a ratio of ten and reaches +8.9 at a thousand, and at Péclet 100 seven reduced models come back unstable. Weight the projection by the cell sizes the discretisation already computed and every model at every grading is stable, with the range's edge back at −0.098.
Reduction, and what a model is forThe smaller cell downstream
Nodal values on a convection–diffusion mesh graded towards its outflow layer put the numerical range in the right half plane, and Galerkin reduced models then fail. A code that grades towards the layer usually also upwinds, and upwinding adds diffusion. It does not give the certificate back: at Péclet 100 and a grading of a thousand the range's edge falls from 8.94 to 6.78 and stays positive, and 18 reduced models fail where 23 did. Each row of the upwind stencil's symmetric part sums to half the difference between the inverse widths of the cell after the node and the cell before it, so wherever the cells shrink downstream the dissipation upwinding adds is outweighed by the coupling to the smaller cell next door.