In the basis, the transformations whose columns are the new basis vectors are
Thus is a rotation through , while is a real orthogonal reflection, equivalently a rotation with one basis-vector phase reversed.
For any real orthogonal matrix with columns ,
Applying this to and and normalizing proves
For the real Bell state , real one-qubit vectors satisfy
For each adjacent pair , , and , the two same-label overlaps have magnitude . Hence every matching-label probability is
It follows that
Rotational invariance makes this an isotropic vector, hence it is ; oddness gives the same result.
Differentiating a vector using twice yields
.
Path-connected means every pair is joined by a continuous map from ; a separation would pull back to a separation of an interval, so it implies connectedness. One valid boundary pair follows the bottom then right edges and the left then top edges. If opposite-corner paths were disjoint, normalising a continuous separation vector would construct the forbidden map , so they intersect. A path in between the other corners, together with a path in between its corners, would contradict that intersection result; hence those corners lie in different path components.
Differentiability at means for a linear map ; partial derivatives are its values on coordinate vectors. Integrating the partial derivatives along the two coordinate segments and using continuity at proves the stated sufficient condition. Here with and . Since , is differentiable everywhere. But does not approach at zero, so is exactly where .
The parity-check matrix has rank , so its kernel has dimension and size ; see linear code. Its columns are precisely the seven distinct nonzero vectors of . Thus no weight-one or weight-two word is in the kernel, while three dependent columns give a weight-three word. Hence .
Differentiate expected utility at the optimum in each portfolio direction:
Rearranging gives the claimed vector identity.
For points , count the distinct vectors ; maximize over samples to get . The shattering coefficient equals exactly when some sample is shattered, and the largest such is .
The required properties are those of a strict Lyapunov function; the domain of stability is the set of initial states whose forward trajectories converge to the fixed point.
For ,
Thus when , proving that disc lies in the basin. On , (with the tangency points checked from the vector field), so trajectories outside cannot enter the basin through that boundary. Hence the basin is contained in .
The power method repeatedly normalizes and estimates the eigenvalue with the Rayleigh quotient . It converges when the dominant eigenvalue is unique in modulus and the initial vector has a nonzero component in its eigendirection.
Across the cut , the two conditional vectors and are linearly independent when , so the Schmidt rank exceeds one. Hence the state cannot be a three-qubit product for any .
Under a coordinate change, the inhomogeneous second-derivative terms arising from each partial derivative cancel between and . The remainder transforms with one contravariant Jacobian, so the commutator is a vector field.
Insert and into the Lorentz force and use vector identities plus Faraday's law. Rearrangement gives . Here is field momentum density and is the Maxwell stress tensor, whose surface traction transports momentum.
Write and use canonical parameter . Then
where . Geometrically the residual vector is orthogonal to every design column. For , use a two-sided Wald statistic (or likelihood-ratio statistic), rejecting at the corresponding normal or chi-square critical value.
Polar vector 2026-10-06
A polar vector transforms as under an orthogonal matrix , including an orientation-reversing transformation. Displacement, velocity and force are polar vectors. An axial vector instead transforms as .
Positive-definite matrix Created 2026-09-24 Updated 2026-10-03
A real symmetric matrix is positive definite when
for every nonzero real vector . It therefore defines the inner product and is invertible.
If a real matrix has a positive diagonal matrix such that is a symmetric matrix, then is a symmetric matrix related to by a similarity transformation: gives . Thus is a diagonalizable matrix with real eigenvalues. If for all real vectors , its eigenvalues are nonpositive. This converts symmetry in a weighted inner product into Euclidean symmetry.
A Hermitian form is positive semidefinite when for every vector. It need not define an inner product, because a nonzero vector may have zero squared norm. The Cauchy-Schwarz inequality still holds: applying nonnegativity to and minimizing the quadratic expression in gives when ; when , varying forces . Thus its zero-norm vectors are exactly the radical of a Hermitian form. Quotienting this radical of a Hermitian form gives a positive inner product; taking its Hilbert space completion then gives a Hilbert space. This is the final positivity step in the Gupta-Bleuler null-state quotient.