For two Stokes flows and of the same dynamic viscosity in the same region, with no volume force, the Lorentz reciprocal theorem states
Indeed, the divergence of their cross-work difference is
The pressure terms vanish by incompressible flow, and the derivatives of the Cauchy stress tensors vanish by the Stokes equation. The divergence theorem proves the result.
Use the convention that are the force and torque exerted by the body on the fluid. By Linearity of Stokes flow, . Applying the Lorentz reciprocal theorem to two independent rigid motions gives , so the hydrodynamic resistance matrix is a symmetric matrix. The boundary-power identity gives
This is strictly positive for nonzero rigid motion: equality would imply , hence a rigid motion throughout the connected fluid, which must vanish since the fluid is at rest at infinity. The no-slip boundary condition would then force . Therefore is a positive-definite matrix. Reversing to the fluid-on-body force changes the sign of the force law, not the positive resistance coefficients.
For the two rods, take the torque about and use body axes. On the -rod, , , and its slender-body force density is
On the -rod it is
Integrate and along both rods, using , and . A convenient dimensionally uniform statement of the complete right-angle two-rod resistance matrix is
In physical coordinates this means translation–translation entries scale as , the two translation–rotation blocks as , and rotation–rotation entries as . The planar block has inverse
This verifies the printed hydrodynamic mobility matrix with its third velocity component ; the TeX aid's is an OCR error.
Take laboratory vertical velocity positive upwards. The body axes are and . In quasistatic sedimentation the force and torque exerted on the fluid equal the gravitational resultants on the body:
The out-of-plane block is unforced, so its positive hydrodynamic resistance matrix gives . Substitution in the planar hydrodynamic mobility matrix gives
and
For , this ordinary differential equation has positive right side on , with a stable zero at . Uniqueness prevents crossing that equilibrium in finite time. For the initial angular velocity is negative, and the stable equilibrium reached from zero is . The heavier-end body turns clockwise through ; it does not settle at . More explicitly, with ,
where the continuous branch has . At , remains zero.
Transforming the translational velocity back to laboratory axes gives
For , eliminate time between and the angular velocity:
At either limiting orientation . Thus both cases have the same net horizontal displacement,
For the drift is monotonically rightwards. For it first moves left, reaching at , then reverses. The total horizontal path length in this second case is , whereas its net displacement is rightwards. At it falls vertically without rotation or drift; taking the infinite-time limit before is consequently singular.
For the requested sedimentation drift of a weighted two-rod body sketch, a full parametric trajectory follows by also integrating . Put and set the initial height to zero:
It tends to in either case while tends to . At both rods end pointing upwards from symmetrically; at they end pointing downwards symmetrically. The asymptotic downward speed is .
Figure 1.
Falling two-rod bodies: trajectory of O and successive orientations for lighter and heavier end masses
.
View a possible complex eigenvector using the Hermitian inner product. For a real symmetric matrix, , so is real. Since and , every eigenvalue is real.
For eigenvectors with distinct eigenvalues , symmetry gives
so . In particular, real eigenvectors are orthogonal in the real dot product.
Use the permitted diagonalizability assumption to take bases of the real eigenspaces whose union spans . Apply the Gram-Schmidt process within each eigenspace. Its linear combinations remain eigenvectors of that same eigenvalue; vectors in different eigenspaces are already orthogonal. The resulting union is an orthonormal basis of eigenvectors, giving an orthogonal diagonalization of a real symmetric matrix.
Let , impose , and write the method of lines system as , where
Thus is a negative definite symmetric matrix and is a skew-symmetric matrix. Use the mesh-weighted Euclidean norm . Discrete summation by parts yields the centered Dirichlet drift-diffusion energy identity
Consequently
The same estimate controls perturbations and is uniform in the number of grid points and in the fixed drift coefficient. Finite-dimensional linear ODE theory guarantees existence, so this proves stability of a numerical method for the semidiscretization.
The factor simply rescales the vector norm and does not change the induced matrix norm. Equivalently the symmetric part is , whose largest eigenvalue is . This is the Euclidean logarithmic norm, rather than generally the spectral abscissa of a nonnormal matrix. No periodic Fourier mode assumption has been made: the zero endpoint terms are part of the proof. In particular positivity of both off-diagonal coefficients is not needed for this stability result.
By orthogonal diagonalization of a real symmetric matrix, write , with orthogonal . Its matrix exponential has the same eigenvectors and positive eigenvalues . Orthogonal invariance of the induced Euclidean norm gives the exact identity
This proves the requested inequality with equality. If a real number gave the bound for every , evaluating on a unit eigenvector for at any would give , so . Thus the stated exponent is the smallest possible. For a symmetric matrix the spectral abscissa and Euclidean logarithmic norm coincide, unlike the general nonsymmetric case in Question 1.
The relevant fixed coordinate subspace is . Let be the first columns of and let
The Gaussian empirical Gram matrix is the empirical second moment with the known mean zero; no subtraction of an estimated mean is involved. For , the ratio under consideration is . Since is a real symmetric matrix, the finite-dimensional spectral theorem gives
Indeed, diagonalizing bounds every unit-vector quadratic form by the largest absolute eigenvalue, and a corresponding unit eigenvector attains the bound.
We first construct a unit sphere net from ball covering. Enlarge the numerical covering constant, if necessary, to . Cover the unit ball in with at most balls of radius at most . For each such ball meeting the unit sphere, choose a point of the sphere in it and discard the others. These selected points form a metric net of the unit sphere with radius : any two points in one covering ball have distance at most . This argument ensures that the net points have unit length even if the original covering centers did not.
Take and put , so . For unit vectors with ,
Taking a net point for every unit and then a supremum proves the quadratic form net bound
It follows that
Fix . The rows of are independent vectors of independent random variables with the standard normal distribution, and . Their scalar products with are therefore independent variables , so
Use the supplied chi-squared concentration inequality with . Its threshold is
Consequently . The union bound gives the stronger fixed-subspace estimate
This is Gaussian Gram matrix concentration on a fixed subspace.
Since , we have . Under ,
Choose the numerical constant . Then the parenthesis is at least one, so is a valid choice, and
The covering factor is only because the coordinate subspace is fixed. The ambient dimension enters through the assumed sample-size bound.
The original PDF has on the left of the update; the converted TeX omits its . Use the Forward Euler method with and . The explicit time stepping for bounded reaction diffusion update matrix is
When , the heat update has nonnegative stencil weights and row sums at most one. Hence its induced maximum operator norm is at most one. It is also a symmetric matrix with eigenvalues
all in , so its discrete L2 norm operator bound is at most one too. Let . In either of these norms,
Iteration gives the mesh-uniform stability estimate
The same estimate applies to differences of solutions. Adding a per-step defect gives .
This proof only requires and bounded reaction coefficients. It does not assume the full update is nonnegative: a negative can make its middle stencil weight negative when . Nor does it claim contractivity or an all-time bound for every coefficient. The required stability is a bound uniform in the discretization on fixed finite intervals.
A complex square matrix is a unitary matrix when , equivalently . Here denotes the adjoint matrix, the conjugate transpose. Such a matrix preserves the standard complex inner product and its Euclidean norm.
A real symmetric matrix is a Hermitian matrix, so . For arbitrary complex ,
The imaginary cross terms cancel because is Hermitian. Reversing the signs gives the same identity:
In particular, implies , so has zero kernel of a linear map. It is a square matrix, and the rank-nullity theorem therefore makes it invertible. The same argument proves invertibility of .
The proposed matrix
is consequently well-defined. For any , put . The two norm identities show directly that
To verify the unitary matrix identity explicitly, take adjoints:
The two shifts commute, because both are polynomials in . Hence
Thus
The imaginary shifts are invertible, and their equal norm changes cancel in the quotient. This is the Cayley transform of a Hermitian matrix in the convention.
Use completing the square rather than computing the eigenvalues of the symmetric matrix. Successively removing the mixed terms gives
Thus one suitable invertible linear change of coordinates is
The coordinate matrix is upper triangular with determinant one, so the change is an invertible linear map. Its inverse is , , . Hence the diagonal coefficients can be taken as . This is a matrix congruence of a quadratic form; an orthogonal transformation was not required.
A smooth vector field on a smooth manifold is a smooth section of the tangent bundle: it assigns to each , smoothly in local coordinates. In a coordinate chart it has the form , with smooth coefficients . Equivalently, it acts on smooth functions as a derivation, .
For a Lie group , write for Left translation on a Lie group. A left-invariant vector field satisfies
Thus it is determined by its value at the identity. Given the printed , first translate it to the identity:
The unique left-invariant vector field with value at is
The smoothness of multiplication makes this a smooth vector field, the chain rule proves left invariance, and setting gives .
We prove the completeness of left-invariant vector fields: this left-invariant vector field is a complete vector field. The Picard-Lindelof theorem, applied in a local chart, gives a unique local integral curve of a vector field through . For every , the curve is an integral curve of a vector field through , because
Crucially, the same interval works for every initial point.
Let be the maximal integral curve of a vector field through , with maximal interval . If , choose with . The curve
exists on and agrees with on the overlap by uniqueness of the local ordinary differential equation. It extends past , a contradiction. The same argument at a finite excludes that possibility. Thus , and uniqueness on overlapping intervals gives uniqueness on all of .
After establishing completeness, uniqueness also gives the one-parameter subgroup law for the global curve through :
Both sides, as curves in , are integral curves of a vector field through at . Defining the Exponential map of a Lie group by , the answer is
The identity component is an open normal subgroup, and every open identity neighbourhood generates it. Let be the connected component of . The product of connected spaces is connected, so the image of under multiplication is connected and contains . It is therefore contained in . Inversion has the same property. Thus is a subgroup.
A smooth manifold is locally connected. In particular, a coordinate neighbourhood of can be chosen homeomorphic to an open ball, so there is a connected open neighbourhood of contained in . Its translates , , are open and lie in , and cover . Therefore the identity component of a Lie group is open in . Conjugation by any is a homeomorphism fixing , so it maps into itself; conjugation by gives the reverse inclusion. Hence is a normal subgroup.
If is an open neighbourhood of in , let , allowing inverses in the meaning of generated subgroup. For each , is open and lies in , so is open in . Every other left coset of is also open. Thus is both open and closed in the connected space . It is nonempty, so .
A quadratic form on is a function for a symmetric bilinear form . Equivalently, and the polarization
is a bilinear map. In coordinates there is a unique real symmetric matrix with . No assumption of nondegeneracy or positive definiteness is needed.
An element stabilizes when for every . By the polarization identity, this is equivalent to preserving , or in coordinates to
This is a closed Matrix Lie group. The Lie algebra of a quadratic-form stabilizer is
To prove necessity, differentiate along any smooth curve in with , . The derivative at zero is .
To prove sufficiency, suppose and consider the matrix exponential . Then
Its value at zero is , so for every real . This curve has derivative at zero, proving the claimed tangent space description even for a degenerate quadratic form.
Equivalently, the condition is for all . For a nondegenerate quadratic form it is the corresponding Special orthogonal Lie algebra. To see the degenerate case explicitly, choose a basis with
Writing , the condition becomes
while are arbitrary. Thus the nullspace of the quadratic form is invariant, but arbitrary infinitesimal maps into it are allowed. When , the formula correctly gives and .
The Hopf boundary point lemma requires an interior sphere condition, strictness of the boundary maximum, and quantitative control of the uniformly elliptic operator near the contact point. Assume that , that and , and that . After shrinking the tangent open ball, we may suppose that the coefficients are bounded there and that, for constants and ,
The coefficient matrix may be replaced by its symmetric matrix part because the Hessian matrix is symmetric. Assume also that throughout the tangent open ball. In the usual statement, one assumes throughout ; when is connected, the strong maximum principle for elliptic operators supplies this strictness from a nonconstant solution attaining its global maximum at .
Put , the outward unit normal of the tangent open ball. With only the given continuity at , the precise conclusion is
If the outward normal derivative exists, it is strictly positive. In particular, if is continuously differentiable up to and the domain has this outward unit normal, then . The stated boundary regularity alone does not assert existence of a normal derivative.
For the proof, use the annulus and the barrier for the Dirichlet problem
Writing , direct differentiation gives
Choose , so that on . On the inner sphere, compactness and the strict maximum give . Choose with . On the outer sphere and , including at by continuity. Consequently has and nonpositive boundary values. The allowed comparison principle, or the weak maximum principle for elliptic operators, yields in .
Along the inward radius this gives
This proves the Hopf boundary point lemma. There is no sign restriction on here, because the operator has no zeroth-order term.
Write the minimal surface equation for a graph as in its weak formulation, where . For negative increments use the same difference quotient convention, so
For , the function is an admissible test function in . Commuting the first partial derivative with translation, then applying discrete integration by parts, gives
The fundamental theorem of calculus along a line segment gives the averaged linearization of a nonlinear divergence-form equation
Thus the backward difference quotient solves a linear equation in divergence form:
To verify the ellipticity of the minimal surface flux, compute
and hence
The eigenvalue parallel to is ; every orthogonal eigenvalue is . The same lower and upper bounds pass to the averaged symmetric matrix whenever both endpoint gradients have norm at most :
The printed hypothesis supplies such an on each relatively compact subset, uniformly for sufficiently small . It therefore establishes a locally uniformly elliptic operator. A single lower bound on all of additionally requires bounded gradients there and at the shifted points; this is automatic for bounded and fixed , but is not supplied on an arbitrary open set.
Assume is nonnegative almost everywhere, and that the real coefficient matrix is measurable and satisfies, for almost every and every ,
The operator norm bound controls all coefficients, including any antisymmetric part. For a symmetric matrix, these assumptions are exactly the usual lower and upper quadratic-form bounds. The weak solution condition is
Then the Harnack inequality for uniformly elliptic divergence-form equations is
A nonnegative weak solution has its supremum controlled by its infimum on the smaller ball. The De Giorgi-Nash-Moser theorem supplies a Hölder continuous function representative, for which ordinary supremum and infimum can replace the essential supremum and essential infimum. Nonnegativity and the larger ball are essential hypotheses; there is no differentiability requirement on the coefficients.
For a symmetric matrix with simple largest eigenvalue and spectral gap , the Davis-Kahan curvature lemma says , where is its leading unit eigenvector. Applying this to a leading eigenvector of , the maximal Rayleigh quotient and duality of the operator norm and trace norm give ; the projector difference has matrix rank at most two. This is a rank-one eigenprojector perturbation bound.
Here has independent centered bounded upper-triangular entries, apart from symmetry. The spectral norm bound for a centered Bernoulli adjacency matrix gives . Taking and therefore gives, for the largest-eigenvalue estimator,
The printed argmin selects the wrong end of the spectrum. For a minimizing unit eigenvector , compare its Rayleigh quotient with any unit vector orthogonal to . This yields , and hence . Its mean projector error is at least , using . Along with sufficiently large even , the printed parameter restriction holds and this lower bound tends to , contradicting an error of order . Replace argmin by argmax, or negate the entire matrix before minimizing.
Over or , a Lie algebra is a vector space with a bilinear map which is alternating and obeys the Jacobi identity:
Bilinearity and alternation imply .
For a Matrix Lie group, identify the tangent space with derivatives of smooth curves through . Product curves show that the sum of two such derivatives is again tangent, and reparametrization supplies scalar multiples. In particular this is a real vector space, even when the matrices have complex entries. For , choose a curve with . Conjugating a curve with derivative shows that
Differentiate this curve in the finite-dimensional vector space . The result is
The matrix commutator is bilinear and alternating, and expanding the six terms proves its Jacobi identity. Thus this construction gives the Lie algebra of a matrix Lie group, with the appropriate bracket, using actual group curves rather than an assumed commutator closure.
For the unitary group, differentiating gives . Conversely, if , then is unitary and is a curve with derivative . Consequently
This is the unitary Lie algebra. The diagonal entries are purely imaginary, contributing real parameters, and each upper off-diagonal entry contributes two real parameters. A matrix-unit basis of the unitary Lie algebra is
These anti-Hermitian matrix units and their combinations are linearly independent over and span every allowed entry.
The symplectic stabilizer is a subgroup: the identity preserves , and if and , then
Multiplying on the left by and on the right by gives . Products and inverses remain unitary. This is the compact symplectic group, often denoted or .
Differentiating the stabilizer equation gives . For , this says
Together with , these are equivalently
These conditions are also sufficient: is unitary, and
Hence it stays in the subgroup. They characterize its compact symplectic Lie algebra without adding any trace condition. In fact the trace automatically vanishes. The free anti-Hermitian block has real parameters, and the complex symmetric matrix has real parameters. Thus
Here is a complete matrix-unit basis of the compact symplectic Lie algebra. The generators supplying are
The two families supplying the real and imaginary parts of are, for ,
The denominator merely avoids double-counting diagonal entries. Each displayed generator obeys both defining tangent conditions. The generators form a real basis of the allowed blocks, and the generators form a real basis of the complex symmetric blocks. Thus they are independent and their total number is . They give all generators required by the real compact algebra, including the case .
The real vector space of symmetric matrices has dimension . On its invertible part the derivative of the determinant is
At a determinant-one symmetric matrix, this derivative is nonzero: the symmetric direction gives value . The regular level set theorem therefore yields
This applies to every signature component, not only positive-definite matrices.
The special linear congruence action on symmetric matrices preserves symmetry because , and preserves determinant because . The identity acts trivially and
These verify a smooth left Lie group action of the special linear group. By Sylvester's law of inertia, it also preserves the numbers of positive and negative eigenvalues.
For , parametrize the symmetric matrices by
Thus is exactly the two-sheeted hyperboloid
The two sheets consist respectively of positive-definite and negative-definite matrices. Each is preserved by the special linear congruence action on symmetric matrices. They are individually transitive: on the positive sheet with and ; on the negative sheet use . The stabilizer of either or is .
Differentiating the left Lie group action along gives the fundamental vector field
For the three matrices in the question, their coordinate components are
A sign convention matters here. With the usual Lie bracket of vector fields , the fundamental fields of this left action obey . Indeed, for linear coordinate fields , the bracket has coefficient . To obtain a Lie algebra representation rather than an anti-representation, use the infinitesimal left-action sign convention
An explicit answer is therefore
These are tangent to the two-sheeted hyperboloid: applying each to gives zero. For example,
They can be written on either sheet using :
Here the omitted component is determined by tangency, and derivatives of must be included when computing brackets in these coordinates.
Direct matrix multiplication gives
Direct differentiation of the displayed vector fields gives exactly
For instance, in ambient coordinates, . These are the defining relations of the sl2 Lie algebra. The three fields are linearly independent over constant real coefficients: if vanishes on a sheet, its coefficient forces , and its coefficient then equals , forcing . Thus the representation is faithful. Their pointwise span need only have dimension two, consistent with the dimension of each sheet.
Use the natural cubic spline convention appropriate to the interior design knots: the spline is linear on and . We also need . These points will be important for uniqueness.
A cubic spline is a function in whose restriction to each of , , through is a polynomial of degree at most three. A spline knot is a junction between consecutive pieces. For a natural cubic spline, the two exterior pieces are affine functions; equivalently, one uses the natural endpoint conditions on the spline over and then extends linearly with matching derivatives. Merely prescribing on otherwise arbitrary exterior cubic pieces is a different condition and does not provide the unique interpolant invoked in this question.
The natural cubic spline interpolant to values is the natural cubic spline satisfying . Its existence and uniqueness for are the interpolant fact allowed in the PDF. The interpolation map is a linear map: a linear combination of interpolants satisfies the same spline, boundary and value conditions, so uniqueness identifies it with the interpolant to the corresponding linear combination of value vectors.
Let , let have the same values, and put . Then . We prove the orthogonality
Apply integration by parts twice on each polynomial interval. On an interior interval, , and
The terms vanish because vanishes at the knots. The terms cancel at internal knots because and are continuous, and vanish at because is zero there. On the exterior intervals, identically. Summing therefore gives the claimed orthogonality without assuming that is continuous across knots.
Expanding the square now gives the minimum roughness property of the natural cubic spline interpolant
Equality forces everywhere, since is continuous. Thus is an affine function. It vanishes at two distinct design points, so , proving equality if and only if .
For the penalized fit, take the allowed spline roughness penalty matrix to be a symmetric matrix with ; thus it is a positive semidefinite matrix. If its supplied representative were not symmetric, its symmetric part defines the same quadratic form and is all that is needed. For any , let . Replacing it by preserves every fitted value and can only decrease the second derivative roughness penalty. Therefore it is enough to minimize
over . The matrix is a positive-definite matrix, since
Completing the quadratic or differentiating gives the unique solution
This is the cubic smoothing spline. More explicitly, the normal equations are , and
For an arbitrary function with fitted vector , the earlier orthogonality also gives
Both terms are nonnegative. Equality forces and, by the proved interpolation equality case, . This proves both existence in and uniqueness over the entire stated function class, not just over splines.
The argument is deterministic for each observed . The fixed-design nonparametric regression and homoscedasticity assumptions motivate the squared-error loss, but Gaussian errors are not required.
At least two distinct design points are required for uniqueness. Question 4 does not explicitly restate , and this hypothesis is necessary. With one design point, every function has zero residual and zero second derivative roughness penalty, for any real . Thus the printed unrestricted uniqueness conclusion would be false for . The corrected theorem assumes at least two distinct knots and the stated linear-tail convention. At , uniqueness over all of also fails; the stipulated eliminates that degeneracy.
Take the couplings in the Hamiltonian to include inverse temperature, so the Boltzmann factor is . If physical energies are used instead, first replace by their products with . Split the on-site term equally between its two bonds. For spin states the spin-chain transfer matrix has entries
Using the specified coupling coordinates, in the order this is
For example, and . This is the nearest-neighbour Blume–Emery–Griffiths model with an additive constant and the paper's sign convention for .
Summing the periodic spin chain gives the partition function . For finite real couplings all entries of are strictly positive; the Perron–Frobenius theorem gives a unique positive dominant eigenvalue with for . Since is a symmetric matrix, all its eigenvalues are real. Thus in the thermodynamic limit,
The positivity condition is stronger and more useful than mere ordering by signed value: subdominant eigenvalues can be negative. Also, the printed strict ordering between the other two is not guaranteed for all couplings. For instance, makes the positive constant matrix with two equal zero eigenvalues. Degeneracy there does not affect the largest-eigenvalue limit; no explicit generic eigenvalues are needed.
For spin magnetization, introduce a dimensionless field through , or insert into the trace. Then
where is a normalized eigenvector of the largest eigenvalue and . Spin inversion symmetry gives , since the positive eigenvector of the largest eigenvalue is unique. Therefore
at zero field, both at finite and in the finite-coupling thermodynamic limit. The finite- result follows directly by pairing each configuration with its spin-reversed partner. Eigenvalues at a single fixed field do not determine a general observable: a field derivative of the largest eigenvalue, or its eigenvector, is required. Positivity and the real analytic dependence on the couplings exclude a finite-temperature spontaneous symmetry breaking transition in this one-dimensional finite-range chain; singular zero-temperature coupling limits require separate treatment.
For even , spin decimation on alternate sites sums the middle spin of each two-bond segment, hence the coarse spin-chain transfer matrix is . Define
Direct multiplication gives . Matching its entry ratios to the original parameterization yields the spin-1 chain decimation recursion
The remaining overall positive factor is absorbed into . Keeping that factor preserves the free energy as well as normalized spin probabilities. Indeed , exactly; on an odd ring an unmatched boundary segment needs separate handling rather than assuming a uniform two-site block decomposition.
Use the characteristic polynomial in the convention :
For fixed with , all three limiting eigenvalues are simple. Expanding this polynomial at each root, or applying first-order perturbation of a simple eigenvalue, gives
These are fixed- asymptotic expansions, not uniform through . At the displayed correction to vanishes because is an exact root for every ; there is no second nonzero term for that branch.
The two roots near interact when the correction is comparable to their unperturbed gap . Thus the distinguished limit is , with bounded real . Set and . The polynomial becomes
At orders and ,
With , the two interacting eigenvalues are
The correction to the pair is included to resolve the next perturbative term as well as the leading splitting. In particular the previously excluded fixed case is :
The half-integer powers reflect square-root splitting of a defective double eigenvalue: the limiting matrix has a nontrivial Jordan block at .
For matching, write and take the overlap . For , , , while , . Consequently the distinguished branches reduce to
The regular coefficient satisfies , proving agreement. For the labels and exchange roles and the same matching holds. The isolated negative branch also matches because . As a spectral check, positive diagonal symmetrization of a matrix transforms this tridiagonal matrix to a real symmetric matrix with off-diagonal entries and ; its eigenvalues are real for positive .
For each fixed in the nonnegative orthant, the map is a continuous linear function on the vector space of real symmetric matrices. Thus
is an intersection of closed half-spaces, using the Frobenius inner product on this space. Arbitrary intersections of closed sets are closed, so is closed.
If and , then for every . Therefore , including the zero matrix when . Hence
The copositive cone is defined in the real space of symmetric matrices; symmetry is needed later to recover every matrix entry from these quadratic forms.