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Substructuring, FETI-DP and BDDC
1 · Prerequisites
- Binary Operations, Monoids, Groups and Subgroups
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Countability and Uncountability
- Determinants of Matrices over a Commutative Ring
- Direct Matrix Factorisations: LU, Cholesky and QR
- Finite Counting, Factorials and Binomial Coefficients
- Finite-element meshes and interpolation
- Foundations of the Real Numbers for Analysis
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Roots, Rational Powers, and Classical Inequalities
- The ZFC Axioms and the Basic Set Constructions
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
This page develops the primal and dual interface formulations for a conforming scalar discretization of second-order diffusion. It defines local discrete harmonic extensions and Schur complements, proves exact static condensation, and shows how primal corner constraints remove floating-subdomain constants. BDDC restores interface continuity through coefficient-scaled averaging; FETI-DP enforces the remaining jumps with multipliers in the range of the jump map, so redundant multiplier rows do not create retained zero modes. The two preconditioners share their nonunit spectrum when they use the same constraints and scaling.
The polylogarithmic estimate is proved only for two-dimensional polygonal subdomains with bounded shape complexity, matching quasiuniform shape-regular triangulations, scalar coefficients constant on each subdomain, all subdomain vertices primal, and coefficient-based edge scaling. Both condition-number claims also assume nonzero assembled and multiplier spaces; zero-dimensional solves are trivial and have no asserted condition number. The proof establishes the local trace lift, edge cutoff logarithm and averaging stability. It makes no three-dimensional vertex-only or arbitrary-geometry claim. Coarse-solver work is kept separate from conditioning.
The schematic interface convention is shown below. Rectangles are subdomains, the shared vertical side is an interface, filled dots are primal corners, and open circles are dual edge nodes. The drawing encodes only these definitions; no proof uses it.
\begin{tikzpicture}[scale=0.9]
\draw (0,0) rectangle (4,2);
\draw (2,0) -- (2,2);
\node at (1,1.5) {$\Omega_i$};
\node at (3,1.5) {$\Omega_j$};
\fill (2,0) circle (2pt);
\fill (2,2) circle (2pt);
\draw[fill=white] (2,0.65) circle (2pt);
\draw[fill=white] (2,1.00) circle (2pt);
\draw[fill=white] (2,1.35) circle (2pt);
\node[anchor=west] at (2.08,0.65) {dual nodes};
\node[anchor=west] at (2.08,1.90) {primal corners};
\end{tikzpicture}
3 · Logical flowchart
4 · Definitions, theorems and proofs
Scalar finite-element substructuring model
Definition
Fix a bounded, connected polygonal open set with a nonempty Dirichlet boundary segment. A finite subdomain partition is a family of connected polygonal open sets , , whose closures cover , whose interiors are disjoint, and for which () is a whole common side, a common vertex, or empty. The outer Dirichlet segment is a union of mesh boundary sides. The edge-adjacency graph of each triangulated subdomain is connected, and the subdomain adjacency graph is connected to the Dirichlet boundary. Each subdomain has a matching affine simplicial triangulation; the triangulations match on every shared side. The family has a fixed shape-regularity bound, quasiuniform mesh size , uniformly bounded polygon side count, corner angles bounded below, inradius comparable to , and a uniform interior-cone parameter. Write and .
Use continuous piecewise-affine () scalar functions on each triangulation. The reference-element and face-matching conventions are those of Reference finite elements and unisolvent degrees of freedom, Matching affine simplicial meshes and shape regularity, and Broken and conforming polynomial spaces on a matching mesh: local polynomials are affine, their nodal values determine them, and conforming functions have equal traces across a shared side. For each subdomain choose a coefficient , constant on but allowed to jump across interfaces. Its local energy is
The global finite-element space consists of the continuous piecewise-affine functions on the subdomain meshes that vanish on the outer Dirichlet boundary, with energy . Local interior degrees of freedom are the mesh vertices strictly inside ; local boundary degrees of freedom are its remaining vertices, with outer Dirichlet values fixed to zero. A floating local block means the same local energy before any outer-boundary values are fixed. A subdomain corner is a vertex of its polygonal boundary.
For uniform estimates, the fixed polygon-shape parameters include the scaled Lipschitz character: after rescaling each subdomain to diameter one, its boundary has a graph-chart cover with uniformly bounded chart count and Lipschitz constants and a uniformly positive neighborhood radius. The scaled mean-zero Poincaré constants are also included among these fixed shape parameters. A pointwise interior-cone bound alone is not a substitute for this uniform boundary-chart data. All constants in later two-dimensional estimates may depend on these polygon-shape, side-count, and mesh shape-regularity bounds, but not on , , the number of subdomains, or the positive numbers .
Eigenvalue bounds from a left-inverse preconditioner
Statement
Let be symmetric positive definite on a finite-dimensional real vector space, and let , satisfy . Every eigenvalue of
lies in , where . When , set for its unique endomorphism. In that case forces , the spectrum of is empty, and the eigenvalue assertion is vacuous.
Facts & Assumptions
Given: Finite-dimensional real spaces , a symmetric positive definite operator , linear maps and , and .
The energy form is positive for every nonzero , and is the identity on .
Proof
If , the identity forces and has no eigenvalues, so the assertion holds with the stated zero-space norm convention. Assume henceforth . Put , which is SPD because is injective (if , then ), and , which is SPD because is onto (it has right inverse ). Hence is similar to the symmetric positive definite matrix and has positive real eigenvalues. For an eigenvector with eigenvalue , let , so and .
By [A1], . Cauchy–Schwarz in the inner product gives . Dividing by the positive square gives .
Also . For the eigenvector, the left side is and step 1.1 makes the right side . Divide by the positive factor to obtain .
Floating local kernels and positive interior blocks
Statement
In the setting of Scalar finite-element substructuring model, the nullspace of the floating local energy matrix on a connected is exactly the one-dimensional space of constants. The principal stiffness block on interior nodal values with zero boundary trace is positive definite (including the empty -dimensional block convention). The assembled global Dirichlet stiffness matrix is positive definite.
Facts & Assumptions
Given: A connected, face-matched triangulation of each , , and the nonempty global Dirichlet boundary from Scalar finite-element substructuring model.
Scalar finite-element substructuring model: ; local functions are continuous and affine on every triangle; each subdomain's triangle edge-adjacency graph is connected.
Scalar finite-element substructuring model: the global functions are continuous across every subdomain interface and vanish on a nonempty outer boundary segment.
Proof
If , each nonnegative term is zero. Since is constant on each triangle, it vanishes on every triangle, so is constant there. Continuity across every shared edge makes neighboring constants equal; connectedness of the triangle adjacency graph makes one constant on all of . Conversely, a constant has zero gradient, hence lies in the kernel. This proves the floating-block nullspace claim.
A vector in the interior block's kernel defines a local function with zero boundary trace and zero energy. Step 1.1 makes it constant and the zero boundary trace makes that constant zero. Thus the interior quadratic form is strictly positive on every nonzero vector, so its symmetric matrix is positive definite. If there are no interior vertices, the unique map on the zero vector space is invertible.
If the global energy vanishes, step 1.1 applied triangle by triangle gives one constant on every subdomain. Interface continuity makes adjacent subdomain constants equal; connectedness propagates one constant through . The nonempty Dirichlet segment forces it to be zero. Hence only the zero global vector has zero quadratic energy, proving positive definiteness.
Primal interface spaces and jump convention
Definition
For each , let be the vector space of local boundary nodal traces compatible with the fixed outer Dirichlet values, and set (all interface copies independent). Let be the subspace whose nodal traces agree at every shared interface node; let be the inclusion. Choose a set of primal constraints, meaning finitely many linear functionals on local traces whose values are required to agree across their incident subdomains. Vertex values and normalized edge averages are examples. The partially assembled space is the subspace of satisfying those primal equalities, so .
The remaining continuity equations are collected in a jump map with . It may contain redundant rows. Fix the redundant-multiplier convention with its inherited Euclidean inner product: multiplier vectors are elements of this range, not arbitrary row-coordinate vectors modulo an unstated choice. Then is injective on . For the PE26 two-dimensional estimate, all subdomain vertices are primal and the only remaining jump rows are nodal differences on open interface edges, each shared by exactly two subdomains.
An interface corner is primal whenever its value is among the selected primal functionals. An edge average on a side is , which is a finite sum of nodal values for a trace. The two-dimensional bound below uses corner constraints; no edge-average bound is claimed there.
Discrete harmonic extension and interface Schur complement
Definition
Use the interior/interface ordering of Scalar finite-element substructuring model. The boundary-trace spaces , , the conforming space , the partially assembled space , and the inclusion are those of Primal interface spaces and jump convention. In particular, identifies the copies of a conforming interface trace. In subdomain , write its stiffness matrix as
By Floating local kernels and positive interior blocks, is positive definite when nonempty; on the zero-dimensional interior space its unique endomorphism is invertible. For admissible boundary trace , the discrete harmonic extension is
The local interface Schur complement is
This is the Schur complement in Block LU factorisation and the associated Schur complement. The local Schur form on a trace is . The block identity and the associated block LU factorization use An invertible leading block yields block LU through its Schur complement with leading block . Assembling local Schur forms on gives ; restricting the same block-diagonal form to gives the partially assembled operator .
Primal constraints remove local floating kernels
Statement
Assume the hypotheses of Primal interface spaces and jump convention and the energy setting of Floating local kernels and positive interior blocks. If each floating local component has at least one primal vertex value fixed in its dual subproblem, its local dual stiffness is positive definite. If all subdomain vertices are primal and the global Dirichlet boundary is nonempty, the partially assembled interface energy is positive definite; hence the BDDC and FETI-DP exact local and coarse solves are well-defined.
Facts & Assumptions
Given: A conforming finite partition with connected subdomain adjacency, a nonempty global Dirichlet boundary, and primal constraints containing every subdomain vertex for the PE26 branch.
Floating local kernels and positive interior blocks: each connected floating local energy has kernel exactly the constants.
Primal interface spaces and jump convention: shares primal corner values and is the fully continuous trace space.
Discrete harmonic extension and interface Schur complement: and ; restricts to . The interior inverse includes the empty-space convention established there.
Proof
From [F3], block multiplication gives and therefore . Thus a zero local Schur energy is precisely zero energy of its harmonic lift. In a local dual subproblem the primal values are prescribed, so a zero-energy local vector, or the harmonic lift of a zero-energy dual trace, is constant by [F1]. A primal corner value is among its prescribed values; because the dual correction has zero primal values, that constant is zero. The local dual quadratic form therefore has trivial kernel and, being symmetric positive semidefinite, is positive definite.
For , [F3] and step 1.1 give . Each summand is a nonnegative local energy. If the partially assembled energy is zero, every summand is zero, so [F1] makes each local harmonic extension constant on its subdomain. Neighboring local constants agree at their shared primal corner. The adjacency graph is connected, so all constants agree; the global Dirichlet boundary makes the common value zero. Thus the partially assembled trace is zero, and its assembled energy matrix is positive definite.
The BDDC local dual solves use the positive local restrictions from step 1.1 and its coarse solve uses the positive partially assembled energy from step 2.1. The FETI-DP operator uses the same invertible partially assembled energy and the jump quotient of [F2]. Hence the exact local, coarse and dual systems named in the Statement are well-defined.
Discrete harmonic extension minimizes energy
Statement
For every admissible local trace , from Discrete harmonic extension and interface Schur complement is the unique finite-element function with trace minimizing . The minimum is .
Facts & Assumptions
Given: The local block matrix , positive definite interior block , trace , harmonic lift , and Schur matrix .
Floating local kernels and positive interior blocks: is positive definite, so its quadratic form is nonnegative and vanishes only at zero.
Proof
Any local vector with trace has the form . By [F1], the interior block row of is . Hence the energy cross term between and vanishes, and .
By [F2], the last term is nonnegative and is zero only for . Thus is the unique minimizer. Multiplying the block expression in [F1] gives .
Static condensation is the exact interface problem
Statement
Let be local load contributions whose assembly is the global Galerkin load. For the global conforming Dirichlet finite-element system from Scalar finite-element substructuring model, eliminating all subdomain interior variables gives the assembled interface Schur system. Its solution trace is exactly the trace of the unique global Galerkin solution. After solving for this trace, reconstruct each local interior vector by
These interior values recover the unique global Galerkin solution; the trace-dependent homogeneous part of each local reconstruction is the discrete harmonic extension.
Facts & Assumptions
Given: The assembled global Galerkin right-hand side and stiffness system, its local interior/interface block partitions, the positive definite interior blocks, the local Schur complements, and the harmonic extensions. The local load vectors are chosen to assemble to that global right-hand side: interior entries are local, while contributions to a shared interface degree of freedom are summed.
Scalar finite-element substructuring model: the global stiffness is the sum of local subdomain contributions, with shared interface degrees of freedom assembled by equality of their nodal values.
Discrete harmonic extension and interface Schur complement: each local block has invertible , Schur complement , and harmonic extension .
An invertible leading block yields block LU through its Schur complement: for an invertible leading block , block elimination factors the matrix through and the same equations are solved by first eliminating the leading variables and then solving the Schur system.
Floating local kernels and positive interior blocks: the global Dirichlet stiffness matrix is positive definite and every local interior block is invertible.
Proof
Let be local load contributions whose assembly is the chosen global Galerkin load vector, as specified above. The global interior rows are local to each subdomain and give The local interface residual contribution is . Substituting the interior formula makes it , precisely the local Schur contribution in [F3]. The global interface rows are the assembled sum of these contributions, not separate local interface equations.
Sum the reduced equations from step 1.1 over subdomains and identify copies of each shared nodal value as in [F1]. Because both the stiffness and the local load vectors assemble by summing their shared interface components, this gives the assembled interface Schur system with the correspondingly reduced global right-hand side. Any solution of the original global system yields this trace. Conversely, a solution of the assembled interface system and the uniquely defined interior values from step 1.1 satisfy every local interior equation and the assembled sum of interface equations, hence the assembled global system.
The global stiffness is positive definite by [F4], so the original solution is unique. Once the interface trace is solved, each local interior vector is exactly the reconstruction formula in step 1.1, which is unique because is invertible. Its trace-dependent homogeneous part is from [F2]. Therefore static condensation is exact in both directions.
Coefficient-scaled averaging and BDDC
Definition
Use the spaces and partial Schur operator of Primal interface spaces and jump convention and Discrete harmonic extension and interface Schur complement. Let average every remaining interface degree of freedom and preserve every already-shared primal value. It is a scaled average if the weights for all copies of each such degree of freedom sum to one. Put . Then and is a projection onto .
In the PE26 two-dimensional corner-constraint branch, each non-primal node is interior to one interface edge shared by exactly two subdomains . Set
At primal nodes the copies already agree, so the average is the common value. For any finite-dimensional positive definite partial Schur operator , the BDDC preconditioner is
for the assembled interface system with operator . Its constrained partial-energy interpretation is established in BDDC is the constrained partial-energy minimizer ↗.
Discrete Schur energy and the fractional trace norm
Statement
Let be one of the shape-regular polygonal subdomains in Scalar finite-element substructuring model, with a matching quasiuniform mesh. For any continuous piecewise-linear boundary trace , let be the Schur complement of the floating local stiffness matrix, before outer Dirichlet values are fixed, formed by the same interior elimination as in Discrete harmonic extension and interface Schur complement. Define
This seminorm is taken modulo constants. The floating local Schur energy satisfies
where depend only on the fixed scaled polygon-shape parameters (including boundary-chart and mean-zero Poincaré bounds), mesh shape-regularity and quasiuniformity. The upper bound is realized by a boundary-preserving finite-element lifting; the minimum-energy lifting is the floating discrete harmonic extension. For an admissible trace , whose outer Dirichlet values are zero, for the Dirichlet-restricted Schur matrix of Discrete harmonic extension and interface Schur complement, so the same inequalities hold for that matrix on its domain.
Facts & Assumptions
Given: A fixed polygonal subdomain, a shape-regular quasiuniform matching affine triangulation, an arbitrary boundary trace , and the floating local stiffness matrix.
Scalar finite-element substructuring model: the local energy is , and all geometric constants are uniform over the specified family.
Discrete harmonic extension and interface Schur complement: the Schur complement is formed by eliminating the invertible interior block; on admissible traces its harmonic lift has energy .
Discrete harmonic extension minimizes energy: for an admissible trace , its harmonic extension minimizes energy among all local finite-element lifts of .
Proof
On the upper half-plane, Fourier transformation in the tangential variable gives, for a smooth lift with trace , Indeed, integrate and apply . Integration in proves the trace seminorm bound. Conversely, has gradient energy . In a bounded chart, multiply the half-plane extension by a fixed cutoff in the inward coordinate; the added gradient term is controlled by the localized boundary norm, hence by the full H1/2 norm after constants are removed. A finite collection of Lipschitz graph charts covers the polygon boundary, including its corners. Flattening each chart is bi-Lipschitz, so it changes the gradient and boundary Gagliardo seminorm by bounded factors. Applying a partition of unity and the half-plane trace inequality to arbitrary chart-localized lifts gives . Subtract the domain mean of and use scaled Poincar'e to replace the full norm by . In the other direction, apply a partition of unity to boundary data, use the half-plane extensions, and sum to obtain a right inverse of the trace. First subtract a boundary constant; the fractional Poincaré bound on the whole boundary controls the localized full norms: for the boundary mean , , by integrating . Add that constant back as a constant lift, which has zero gradient. The chart count, scaled radii, Lipschitz constants and mean-zero Poincaré bounds are precisely the fixed shape parameters in [F1]; a pointwise interior-cone condition alone would not justify this uniformity.
Construct an interpolant as follows. For each interior mesh vertex choose one incident triangle and set its coefficient to the average of on that triangle. For each boundary vertex choose one incident boundary edge and set its coefficient to the integral of the trace of against the -dual function to the endpoint nodal basis on that edge. These dual functionals reproduce every affine edge trace, so the trace of is exactly whenever the trace of is . All coefficients reproduce constants. For a triangle , the chosen elements and edges for its vertices lie in a connected patch of diameter at most containing a uniformly bounded number of triangles; these patches have bounded overlap. Let be the mean of on . Scaled Poincaré gives , and the scaled trace inequality gives on a selected boundary edge . Thus each interior average coefficient of is bounded by . A boundary dual function has norm at most , so its coefficient has the same bound. Since and the affine basis functions have uniformly bounded gradient norms in two dimensions, . Summing and using bounded overlap proves .
For any finite-element lift of , step 1.1 gives . For the floating matrix, put . Symmetry of the local Poisson form and its zero interior row give . The positive interior block from [F2] therefore makes the unique fixed-trace minimum, by the same identity as [F3]. Taking that minimum gives the lower Schur bound. For the upper bound, step 1.1 supplies a continuous lift with gradient energy at most , and step 1.2 gives a boundary-preserving finite-element lift with the same bound up to a uniform factor. The just-proved floating minimality bounds its energy by this lift. Multiplication by proves both inequalities. If is admissible, the fixed-trace feasible lifts already vanish on the outer Dirichlet portion; [F2]–[F3] identify the same minimum with .
BDDC is the constrained partial-energy minimizer
Statement
For every assembled residual , the unique minimizer over of
is . The conforming correction returned by BDDC is .
Facts & Assumptions
Given: The positive definite partial Schur operator , the averaging map , and an assembled residual .
Coefficient-scaled averaging and BDDC: is linear and .
Primal constraints remove local floating kernels: under the stated primal anchoring, is positive definite.
Proof
Differentiating the finite-dimensional quadratic in a direction gives . Thus its critical point solves , whose unique solution is .
For any , expansion about the critical point yields . By [F2] the added term is positive unless , so is the unique global minimizer. Applying gives the displayed BDDC correction by [F1].
FETI-DP dual system and preconditioner
Definition
Use , , , , and as defined in Primal interface spaces and jump convention and Coefficient-scaled averaging and BDDC. Assume that is symmetric positive definite. In the PE26 corner branch this follows from Primal constraints remove local floating kernels when all subdomain vertices are primal and the global Dirichlet boundary is nonempty; for other primal choices it is a separate admissibility requirement. Use the inherited Euclidean inner product to identify with in the transpose and coordinate formulas below. Regard as a projection on . Since , each class of traces with the same jump has a unique representative in . Define by assigning to that unique representative with and . This is the scaled right inverse; it obeys and . The latter identity makes the primal and dual projections complementary. In the two-subdomain edge case, its two entries are the coefficient-scaled jump weights complementary to those in .
The FETI-DP dual operator and its preconditioner are
The multiplier convention removes dependent row coordinates: is in , so no arbitrary multiplier component in is retained. Elimination of the partially assembled displacement and the resulting exact dual system are proved in FETI-DP is the exact dual Schur system ↗.
Two-dimensional logarithmic edge cutoff estimates
Statement
Let be a side of a shape-regular polygon of diameter with a matching quasiuniform boundary mesh of size . Let be the piecewise-linear boundary function equal to at the interior nodes of and at the endpoints and all other boundary nodes. For
one has . Also every continuous piecewise-affine on satisfies
Consequently, for the edge mean ,
where is nodal piecewise-linear interpolation on .
Facts & Assumptions
Given: A bounded-shape polygon, a shape-regular quasiuniform mesh, one side , and the seminorm/lifting equivalence of Discrete Schur energy and the fractional trace norm.
Scalar finite-element substructuring model: is the subdomain-to-mesh ratio, and shape regularity, polygon angles, the interior-cone parameter, scaled boundary-chart bounds and scaled mean-zero Poincare constants are uniform.
Discrete Schur energy and the fractional trace norm: the floating local Schur energy is the minimum over finite-element lifts of arbitrary boundary traces, is equivalent to the boundary Gagliardo seminorm modulo constants, and boundary data admit a stable finite-element lift.
Proof
If has no interior boundary node, then . If , scaling to unit length gives a uniform bound on both terms of . Otherwise the first and last mesh intervals have length comparable to , is linear from to and from to there, and it equals between them. The weighted integral on either endpoint interval is bounded by ; the plateau contributes at most . In the double integral, pairs in the plateau contribute zero. Pairs within one endpoint interval have integrand at most and hence contribute at most a constant. For one point in an endpoint interval and one outside it, integrating in the outside variable and then in gives a constant; the two endpoint intervals are treated in the same way. Therefore .
Put , , and . Choose a triangle containing a point where is maximal, and let be its centroid. Affine scaling gives . The uniform interior-cone condition in [F1] supplies at a cone of radius and angular interval of fixed positive length, contained in . Quasiuniformity and affine scaling give the global inverse bound . If is bounded, the inverse bound and mean-zero scaled Poincaré prove the claim directly. Otherwise choose . Along each cone ray, the integral of from to is at most , while weighted Cauchy–Schwarz gives Express by its value at minus these two radial integrals, square, and average with measure over , . The annulus has area comparable to ; the ray-energy term is independent of and integrates in to at most . Hence Mean-zero scaled Poincaré bounds the first term by , and the centroid comparison proves the asserted estimate. This is the radial argument underlying Widlund's estimate (5), with the centroid-to-maximum comparison included explicitly.
Put . In the first Gagliardo term use The weighted term is bounded by . Together these give On the two endpoint mesh intervals, is a quadratic interpolation error vanishing at both endpoints; scaling the interval to unit length bounds its norm by . The same estimate therefore holds for . The floating local Schur energy of the trace of is at most because it is the minimum over finite-element lifts; the lower trace-Schur bound in [F2] therefore gives . Also , so . Combining this with steps 1.1 and 1.2 proves the claimed squared-logarithmic multiplier estimate.
FETI-DP is the exact dual Schur system
Statement
Let and set . The constrained minimization problem
has the saddle equations , . Eliminating gives the FETI-DP dual system
On its matrix is positive definite, and the exact multiplier solution reconstructs the unique assembled interface solution .
Facts & Assumptions
Given: is positive definite on , is onto with , and is the projection used by BDDC.
FETI-DP dual system and preconditioner: and the multiplier space is .
Primal interface spaces and jump convention: and redundant multiplier rows are represented by their range.
Primal constraints remove local floating kernels: all subdomain vertices primal and a nonempty global Dirichlet boundary suffice for positive definiteness of . Here positive definiteness is an explicit hypothesis, also for other primal choices.
Proof
The Lagrangian is . Its derivative in arbitrary is , and its multiplier derivative is . Setting both derivatives to zero gives the displayed saddle equations.
By the assumed positive definiteness of , the first equation has the unique solution . Substitution into gives the displayed dual system.
If and , write using [F2]. Then , hence . Thus is injective on , and for every nonzero . The exact solution satisfies , so by [F2] it lies in and solves the assembled variational problem.
Complementary primal and dual projections share nonunit spectrum
Statement
Let be finite-dimensional real vector spaces, let be symmetric positive definite, and let , satisfy for and . Then the operators
have the same eigenvalues, with the same multiplicities, except possibly at the eigenvalue .
Facts & Assumptions
Given: Finite-dimensional spaces, symmetric positive definite, and the four displayed left-inverse and complementary-projection identities.
Proof
The products and act on and , respectively. Set and . By the given hypotheses, , , and . Expanding the products gives and . In detail, ; also .
If satisfies with , then , so . The identity gives , hence . For , the reverse map is ; the same identities show it is the inverse on the -eigenspaces. Thus these eigenspaces are isomorphic.
Choose bases of the finite-dimensional spaces and their dual bases. Both operators are diagonalizable: and are positive definite, so, writing , is similar to the symmetric positive definite product ; likewise is similar to , where . The left-inverse identities make injective and surjective, proving each factor is positive definite. Therefore equal eigenspace dimensions from step 2.1 give equal algebraic multiplicities for every .
Remarks
Coefficient-scaled averaging and BDDC: for BDDC, , , and .
FETI-DP dual system and preconditioner: for FETI-DP, , , , and .
Two-dimensional scaled averaging energy bound
Statement
Assume the model of Scalar finite-element substructuring model, all subdomain vertices primal, and the coefficient-scaled average of Coefficient-scaled averaging and BDDC. Let be the complementary jump projection on , and let be the energy norm induced by the partially assembled Schur operator. Then
where depends only on the polygon/mesh shape bounds and bounded side count. It is independent of coefficient jumps, mesh size, subdomain diameter, and subdomain count.
Facts & Assumptions
Given: Positive coefficients constant on each subdomain; matching quasiuniform meshes; all polygon vertices primal; and the partial Schur energy.
Coefficient-scaled averaging and BDDC: on an edge , the average weights are and .
Primal interface spaces and jump convention: every open 2D interface side has two incident subdomains, and vanishes at primal vertices.
Discrete Schur energy and the fractional trace norm: local Schur energy is equivalent to the squared trace seminorm modulo constants.
Two-dimensional logarithmic edge cutoff estimates: the edge cutoff has squared norm , and its product with a mean-zero trace costs at most times the local energy.
Proof
Fix an open edge and let , be the local discrete harmonic extensions. Write and similarly for , by harmonic minimality and the definition of . The -copy of has nodal values at interior edge nodes and zero at its primal endpoints, so it is ; the -copy has the complementary coefficient . The norm controls the full boundary seminorm of an edge trace extended by zero off : the cross-edge integrals are bounded by the endpoint weight in that norm, with constants controlled by the model's scaled Lipschitz boundary-chart bounds, polygon angles and side count. Thus the trace-Schur upper bound [F3] applies to these supported traces.
Set , , and . At a primal endpoint , , so . Applying the discrete Sobolev estimate [F4] to and , and noting that a boundary mean differs from the domain mean by at most the same deviation, gives The factors and appear because [F4] is unweighted while includes .
Write and on , and set . The multiplier estimate [F4] bounds the squared norm of each by . Also [F4] bounds by . For the -copy use and the triangle inequality in the squared norm. After multiplication by its Schur coefficient , the mean-zero terms are bounded by and the constant term has the same bound by step 1.2. Since the -side contribution is at most . Interchanging gives the same estimate for the -side contribution, using .
Sum over all interface sides. Each polygon has uniformly bounded side count, so each local energy occurs a bounded number of times. On each subdomain the complementary trace is the sum of these edge-supported traces; the squared norm of that sum is bounded by the side count times the sum of the squared norms. The resulting bound is , with no coefficient-contrast or subdomain-count factor.
Conditioning and solver work are separate claims
Remarks
The condition-number theorem concerns the ideal exact local and coarse solves and the spectrum of the preconditioned interface operators. It does not bound elapsed time, communication, memory, or total arithmetic work. For example, under a dense direct-solver model with coarse dimension , a coarse factorization uses arithmetic and storage, while a dense local factorization for subdomain dimensions uses arithmetic before parallel scheduling. Therefore a growing primal space can make the coarse solve dominate even while the condition number remains polylogarithmic. An inexact local or coarse solve requires its own spectral-equivalence and cost hypotheses.
BDDC and FETI-DP have matching nontrivial spectra
Statement
For BDDC and FETI-DP built from the same positive definite partially assembled Schur operator, primal constraints, and scaled averaging, all eigenvalues of the two preconditioned operators other than agree with multiplicity. With the multiplier space fixed as , neither operator has a zero eigenvalue; retaining all redundant row coordinates instead would add only multiplier null modes that are removed by this convention. The multiplicity of is not asserted to agree.
Facts & Assumptions
Given: A positive definite partial Schur operator, a conforming trace subspace, a primal projection, and a jump map with multiplier space .
Coefficient-scaled averaging and BDDC: and is the BDDC projection.
Complementary primal and dual projections share nonunit spectrum: if and , the associated abstract products have matching nonunit eigenvalues with multiplicity.
Proof
Take , , , , , , , and . By [F1] and [F2], and . The first abstract product in [F3] is , exactly the BDDC preconditioned operator by [F1]; the second is , exactly the FETI-DP product by [F2].
Apply [F3] to conclude equal eigenvalues and multiplicities for every eigenvalue other than . The identities and make and injective and and surjective onto their ranges; since is positive definite, the four Gram operators in the two products are positive definite on their respective spaces. Thus both preconditioned products have positive eigenvalues. Taking removes redundant multiplier null modes. No step determines the multiplicity of eigenvalue .
The two-dimensional BDDC and FETI-DP polylogarithmic bound
Statement
Assume the scalar model of Scalar finite-element substructuring model, matching shape-regular quasiuniform meshes on bounded-shape polygonal subdomains in two dimensions, all subdomain vertices primal, coefficient scaling on each open interface edge, and nonzero assembled and multiplier spaces. Then both preconditioned interface operators satisfy
The constant is independent of , , the number of subdomains, and arbitrary positive jumps in the coefficient values . If either preconditioned space is zero-dimensional, that interface solve is trivial and its condition number is not asserted. This statement does not cover three-dimensional vertex-only constraints, arbitrary graph or mesh geometries, or unaligned/intra-subdomain high-contrast coefficients.
Facts & Assumptions
Given: The scalar second-order subdomain diffusion family and its primal/dual preconditioners; write for the operator norm induced by the partially assembled Schur energy.
Eigenvalue bounds from a left-inverse preconditioner: for , preconditioned eigenvalues lie between and .
Coefficient-scaled averaging and BDDC: BDDC has .
FETI-DP dual system and preconditioner: FETI-DP has , , and ; the latter convention makes injective on .
BDDC and FETI-DP have matching nontrivial spectra: the two positive preconditioned spectra agree except possibly at .
Proof
Apply [F2] with and . The BDDC eigenvalues are at least one and at most . By the triangle inequality for the induced operator norm, . Since , squaring yields the BDDC bound with a geometry-only constant.
Apply [F2] with and . This bounds the eigenvalues of below by one and above by by [F1] and [F4]. The Gram factors and are positive definite: is injective on by [F4], is injective by , and is positive definite. Thus both maps are isomorphisms, and the stated product has the same spectrum because
The lower eigenvalue bounds bound both condition numbers by their respective largest eigenvalues. The common nonunit spectrum in [F5] confirms that the paired methods have the same nontrivial convergence spectrum; neither assertion introduces a 3D, arbitrary-graph or unaligned-coefficient claim excluded in the Statement.
5 · Examples, counterexamples and false statements
None yet.
Sources
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, pp. 35–37, 83–89
- Oliver Rheinbach, Parallel Scalable Iterative Substructuring, Chapter 2, §§2.1–2.4
- Jan Mandel and Bedřich Sousedík, BDDC and FETI-DP under Minimalist Assumptions, §4, Lemma 4.1
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, pp. 94–95
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, pp. 35–37 and 83–84
- Oliver Rheinbach, Parallel Scalable Iterative Substructuring, Chapter 2, §§2.1–2.3
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, pp. 83–89
- Jan Mandel and Bedřich Sousedík, BDDC and FETI-DP under Minimalist Assumptions, §3.1
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, pp. 35–37
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, pp. 83–86
- Jan Mandel and Bedřich Sousedík, BDDC and FETI-DP under Minimalist Assumptions, §5
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, pp. 87–90 and 96–97
- Jan Mandel and Bedřich Sousedík, BDDC and FETI-DP under Minimalist Assumptions, §§3.1–3.2
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, pp. 24–26
- Oliver Rheinbach, Parallel Scalable Iterative Substructuring, Chapter 1 §1.7 and Chapter 2 §2.4
- Jan Mandel and Bedřich Sousedík, BDDC and FETI-DP under Minimalist Assumptions, §3.2
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, §§87–88
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, §§83–90
- Jan Mandel and Bedřich Sousedík, BDDC and FETI-DP under Minimalist Assumptions, §§3.1 and 3.3
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, pp. 25–33
- Oliver Rheinbach, Parallel Scalable Iterative Substructuring, Chapter 2 §2.4, pp. 40–44
- Jan Mandel and Bedřich Sousedík, BDDC and FETI-DP under Minimalist Assumptions, §3.3
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, §§83–84 and 89
- Jan Mandel and Bedřich Sousedík, BDDC and FETI-DP under Minimalist Assumptions, §4, Lemmas 4.1–4.2
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, pp. 90–93
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, pp. 94–97
- Oliver Rheinbach, Parallel Scalable Iterative Substructuring, Chapter 2 §2.4, pp. 39–44
- Olof B. Widlund, Introduction to the Design and Theory of Domain Decomposition Algorithms, DD20 Tutorial, pp. 3 and 87–89
- Jan Mandel and Bedřich Sousedík, BDDC and FETI-DP under Minimalist Assumptions, §4
- Oliver Rheinbach, Parallel Scalable Iterative Substructuring, Chapter 2 §2.4, Theorems 2.4.1–2.4.3