Two square matrices are similar when for some invertible matrix . A Jordan normal form is a block-diagonal matrix whose blocks have one eigenvalue on the diagonal, ones on the superdiagonal, and zeros elsewhere; over an algebraically closed field every matrix is similar to such a form, unique up to reordering its Jordan blocks.
Both displayed matrices have characteristic polynomial
However,
so their eigenspace dimensions are respectively two and one. Thus has Jordan form , whereas has Jordan form . By uniqueness of Jordan normal form,
For an oriented smooth embedded surface, the Gauss map sends each point to its chosen unit normal. This surface is the ring torus with major radius two and minor radius one. Its outward Gauss map is
On the cross-section, the normal points radially away from the center of each generating circle, which gives this formula for and then rotational symmetry gives it for all .
The upper hemisphere condition is , hence . For this torus, the Gaussian curvature and area element are
Therefore the positive outer and negative inner contributions cancel:
The boundary arcs meet at and . The Möbius transformation
sends these points to and infinity, sends the real boundary segment to the positive real axis, and sends the circular boundary arc to the ray of argument . Hence it maps onto the sector
The power maps this sector conformally onto the lower half-plane. Finally, the Cayley map maps the lower half-plane onto the unit disc. Thus a requested conformal equivalence is
An operator is Hermitian when
on its domain. Hermitian operators represent quantum observables because their expectation values and eigenvalues are real. In a normalized state,
Positivity of the norm of for every real gives
The middle expectation is real because is Hermitian. The discriminant of this quadratic is nonpositive, so
Apply this to the centered operators and , whose commutator is still . This yields the Robertson uncertainty principle
Noncommuting observables therefore cannot both have arbitrarily sharply concentrated measurement distributions in the same state.
Gaussian elimination gives the LU decomposition
The prescribed diagonal entries of are visible, and direct multiplication gives .
First solve by forward substitution:
Then solve by backward substitution, obtaining
Direct substitution verifies .
The likelihood contributes precision and precision-weighted mean , while the prior contributes precision and precision-weighted mean . By normal-normal conjugacy with known observation variance, the posterior is
Thus the posterior mean is
When , its expectation under true parameter is and its variance is . Hence its frequentist mean squared error is
Write the absolute-value constraint as
Introduce slacks . In the simplex algorithm, let enter and leave, then let enter and leave. The final dictionary is
Thus
For sufficiently small perturbations, the same two constraints remain active:
Solving gives
and therefore the perturbed optimal value is
The rank of a matrix is the dimension of its column space, equivalently the dimension of the image of a linear map represented by the matrix. For , the rank-nullity theorem gives
An injective endomorphism of a finite-dimensional vector space is surjective, hence invertible. By the adjugate matrix identity
is invertible when ; conversely, multiplicativity of the determinant shows that an invertible has nonzero determinant. Therefore
Let be the matrix unit with its only nonzero entry at . The following matrices are all nonsingular:
Indeed, is an elementary shear when , while is diagonal with one diagonal entry equal to two. Their linear span contains every except initially , because , and it then contains
Thus spans the -dimensional space and, having members, is a basis. This also covers , when .
Now let be a nonsingular zero-one matrix. If it had fewer than zero entries, at least two rows would contain no zero at all. Those two rows would both be the all-one row, contradicting linear independence. Hence every such matrix has at most
ones. The bound is attained. Let be the all-one matrix and set
where there are initial diagonal ones. If and , the first row equations give , while the last gives . Hence every , so is nonsingular and has exactly ones. Therefore
The structure theorem for finitely generated modules over a principal ideal domain applies because every Euclidean domain is a principal ideal domain. It says that a finitely generated -module is isomorphic to
where the nonzero nonunits are unique up to multiplication by units. They are the invariant factors.
For , multiplication by is the linear map . Since is finite-dimensional over , is a finitely generated torsion module over the polynomial ring , so it has no free summand. Choosing each invariant factor to be monic gives
The basis of each cyclic summand makes multiplication by a companion matrix. Concatenating these bases therefore puts in rational canonical form.
On , a polynomial annihilates multiplication by exactly when it is divisible by . It follows that the minimal polynomial and characteristic polynomial are
The second identity follows blockwise from the characteristic polynomial of a companion matrix. Since every divides , the product annihilates every cyclic summand. Thus , which is the Cayley-Hamilton theorem.
For the displayed matrix, the given generators of are the columns of
Elementary row and column operations over give the Smith normal form
Consequently the nonunit invariant factors are
and, as a check,
A function is differentiable at if there is a linear map such that
The map , which is unique, is the derivative .
Expanding in a matrix increment gives
Therefore is differentiable everywhere and
The inverse function theorem states that if is continuously differentiable near and is invertible, then restricts to a bijection between neighbourhoods of and ; its local inverse is continuously differentiable, with derivative
In the normalized case and , continuity of gives a closed ball on which
For small , define . The mean value inequality makes a contraction mapping with constant . If , then
so maps the ball into itself. The contraction mapping theorem gives a unique fixed point , and the fixed-point equation is precisely . Moreover,
so . Thus is a continuous local inverse.
For the polynomial map in the question,
The derivative is invertible, so the inverse function theorem supplies some and a continuously differentiable such that
There can be no inverse on all of , because
so is not injective.
The curve is symmetric in both coordinate axes and under interchange of and . Its shape, including its eight inflection points, is:
Writing , the surface of revolution has equation
Let
Its gradient is
If this vanished, then and , but at such a point , not five. Hence zero is a regular value, and the regular level set theorem shows that is a smooth embedded surface.
For a surface of revolution, the two principal curvatures are the curvature of the meridian and the normal curvature of a parallel. Along ,
so the normal is vertical in the meridian plane and the parallel principal curvature vanishes. Therefore the Gaussian curvature, the product of the principal curvatures, is zero there.
These are not the only zero-curvature points. The meridian itself has inflection points, at which its principal curvature vanishes. Setting and , their positive squared coordinates satisfy
Besides interchanging and , the solution is approximately
Each corresponding meridian inflection point sweeps out another circle on , so does not exhaust the zero set of the Gaussian curvature.
An analytic branch of a square root determined by the branch is
If and are two such branches, their ratio is analytic and satisfies . Since a domain is connected and takes values in the discrete set , is constant. Thus throughout or throughout .
For , the principal square root is
On , one may instead take
The respective removed half-axes are their branch cuts.
On , define
It is analytic there, its square is , and
so it is the required branch. Substitution gives, for ,
The binomial series yields
hence the first three terms of the Laurent series are
Since
its residue at zero is . Under the change of variable , the two orientation reversals cancel, and the residue theorem gives
In polar coordinates,
With the change of radial coordinate , the detection functional becomes
It is therefore times ordinary path length in the -plane. The shortest path is the line segment from to , so
Returning to gives the logarithmic spiral
Its minimum detection probability is
The functional depends only on the geometric path and not its parametrization, so tiptoeing and running give the same probability.
For the improved sensor, omit the irrelevant positive factor and use the Lagrangian
The coordinate is cyclic, so its conjugate momentum is conserved. Equivalently,
is constant. Because has no explicit time dependence, the associated conservation of energy gives the constant
Multiplying by and using gives the required equation
Expand in its Fourier sine series
By separation of variables, the decaying solution of Laplace equation in each half-strip has th mode proportional to . Continuity at and integration of the equation across the Dirac delta function require the normal-derivative jump
The jump of is , so
For , its Fourier coefficients are
Thus
Translation in gives the Dirichlet Green function for an infinite strip with source :
A stationary state has the form
For a time-independent quantum observable , the global phases cancel in the expectation value:
It is therefore independent of time.
For the infinite square well,
The possible energy measurement results are
with respective Born rule probabilities and . Normalization gives .
At time ,
The required matrix elements are
Consequently
where the angular frequency is
Finally, , so
The electric potential of a point charge at the origin is
For the two charges forming the dipole,
The first-order Taylor expansion at large is
and therefore, with the electric dipole moment ,
to leading order. Taking the interaction of a second dipole with the corresponding electric field gives the stated electric dipole-dipole interaction
Let the lattice spacing be and write the central dipole as
Its two horizontal neighbours have moment . For either one, the expression in parentheses, after extracting , is
Its two vertical neighbours have moment , and each contributes instead
Adding all four nearest-neighbour interactions and using the Pythagorean trigonometric identity gives
The angle has cancelled, so the energy is independent of .
For a velocity potential, . The incompressible flow condition therefore becomes Laplace equation . The Laplace equation in polar coordinates gives
so positivity of and requires
The velocity components are
The no-penetration boundary condition on both walls says at and , hence . If , changes sign inside the wedge. The stated sign condition therefore selects , and
A streamline satisfies
Integration gives
The radius is smallest on the wedge bisector , where . Labelling that radius by therefore gives
Every streamline arrives from infinity along one wall, reaches its closest point on the bisector, and returns to infinity along the other wall:
Using and the Pythagorean trigonometric identity,
so the speed is independent of . Since ,
and the speed tends to zero at the vertex. The steady irrotational Bernoulli equation gives
Thus the fluid pressure is also independent of , with
In particular, the pressure difference between the vertex and is
Define the cardinal polynomials
They satisfy . Hence evaluating the proposed polynomial interpolation formula at gives , so the required coefficients are
The polynomial has degree at most and takes every prescribed value. Its uniqueness follows because the difference of two such polynomials would have distinct roots while having degree at most .
For fixed interpolation nodes , interpolate any as
Integrating shows that the unique weights making the quadrature rule exact through degree are
Now let the nodes be the zeros of the degree- orthogonal polynomial . Given any , polynomial division gives
Orthogonality gives , while makes the quadrature sum for vanish. The rule is already exact on , so it is exact on . This is the defining precision property of Gaussian quadrature.
The displayed Rodrigues formula gives the Legendre polynomial
A four-node Gaussian rule is exact through degree . Solving first for gives the four nodes
The rule is not exact for every polynomial of degree eight: its quadrature value on is zero because every node is a root of , whereas
Let . The likelihood function is
On its feasible range , this is decreasing in . Therefore the maximum likelihood estimator is
A statistic is sufficient for if the conditional distribution of the full sample given does not depend on . It is minimal sufficient if it is a function of every sufficient statistic.
The likelihood factors as
so the Fisher-Neyman factorization theorem shows that , and hence its one-to-one transform , is sufficient. Moreover, for two samples and , the ratio is independent of exactly when their maxima agree. The likelihood-ratio criterion for minimal sufficiency therefore shows that and are minimal sufficient.
For , the sample mean is not sufficient: two samples can have the same mean but different maxima, and their likelihood ratio then depends on through the support indicators. It is consequently not minimal sufficient. For the degenerate special case , the sample mean and maximum coincide and both conclusions reverse.
The scaled maximum
has cumulative distribution function for . Thus
The mean squared error of the maximum likelihood estimator is therefore
Each from the uniform distribution on has mean and variance . The sample mean is unbiased and has variance , hence
Because , for fixed and sufficiently large ,
Therefore
Equivalently, converges in distribution to an exponential distribution of rate one.
Put . The limiting probability
and the certain inequality suggest the approximate confidence interval
Since , its expected length is
as required.
A random time is a stopping time for the natural filtration of a Markov chain when for every . The Strong Markov property says that, conditionally on and , the process after is a fresh copy of the chain started from , independent of the pre- history.
Before capture define the half-separation
For , independence of the two moves gives the transition probabilities
Ignore the holding steps. The resulting embedded chain is a biased random walk that moves left with probability and right with probability . Its expected number of moves needed to descend one level is ; this follows either from first-step analysis or from its drift . A non-holding move occurs with probability at each time, so its mean waiting time is two. Hence, for every , the expected time to go from separation to is
Let be the expected capture time starting from , so . The Strong Markov property at successive first passages to lower levels and part (a) give
At , the next state is zero with probability , one with probability , and two with probability . First-step analysis therefore gives
or
Solving,
Substituting now yields
which is the required expected capture time.
Fix . If , then normality of gives
Thus the transitive group action of permutes the orbits of a group action of , so all -orbits have the same cardinality . They partition the prime-sized set , hence divides . The only possibilities are and . The first would make every element of fix every point, contrary to the assumption that acts nontrivially. Therefore and
Now suppose . Define the orbit map
It is surjective by transitivity of . If , then , so ; hence is bijective. For ,
Thus is an equivariant map: conjugation by on corresponds exactly to the given action of on .
Write . The zero and constant-one polynomials give and . Also,
so is closed under finite intersections. Every nonzero one-variable complex polynomial has only finitely many roots, and every finite subset is the zero set of . Consequently is exactly the cofinite topology: its open sets are the empty set and the complements of finite sets. An arbitrary union of such sets is again empty or has finite complement, so is a topology.
The product topology on is the topology with basis
The proposed complement need not be open. Take
Then is the diagonal. If its complement were open, a point such as would have a basic neighbourhood contained in that complement. But and are nonempty cofinite subsets of , so . For , the point belongs both to and to the diagonal, a contradiction. Hence
Because the constraint determines
the constrained function is
Its stationary points satisfy
When , these equations give
When , subtracting the two bracketed equations gives , and substitution then gives
with the two signs chosen independently. These are exactly the constrained stationary points; equivalently they follow from the Lagrange multiplier equations.
Under the additional restriction , the constraint gives the compact elliptical disc . On its boundary , the objective is zero. At the four nonzero interior stationary points,
with the sign determined by . Therefore
Use the angular-frequency Fourier transform
Then
with the continuous value .
The convolution is times the length of the overlap of the intervals and . Thus
The convolution theorem states, for this convention, that
Since , it follows that
again interpreted continuously at , where .
Let be distance from the common centre. By Gauss's law, the electric field is radial and equals
Taking the electric potential to vanish at infinity and requiring continuity across each shell gives
The electrostatic energy is the integral of the electric-field energy density:
Only the two nonzero-field regions contribute, so
Therefore
Let the upper plate in flow A move at speed , with the lower plate fixed. The Couette flow profile is
so its mid-plane speed is and its total viscous dissipation per unit plate area is
Write for the constant pressure-gradient magnitude in flow B. The plane Poiseuille flow profile is
Equality of the mid-plane speeds gives
Since ,
Hence
Set
Conditioning on gives the affine recurrence
Its fixed point is the first component of the stationary distribution,
Thus , and gives
Starting instead from state two gives the same recurrence with initial value zero. Therefore
An endomorphism is a projection onto its image precisely when it is the identity on and kills a complementary subspace. If , then
so is the identity on its image. Moreover,
and . Hence
and is the projection onto its image along its kernel. Conversely, every projection is the identity after one application, so applying it twice has the same effect: .
Statement (i) is false. On a two-dimensional vector space, take the nonzero nilpotent endomorphism
Then , but , so is not idempotent.
Statement (ii) is false. The condition is necessary for an idempotent, but it is not sufficient. For example,
satisfies , hence , while
over, for example, .
Statement (iii) is false over an arbitrary field. Expanding the assumed idempotence gives
Multiplying this relation on the left and right by shows
Thus , so the conclusion would be true in characteristic different from two. In characteristic two, however, take . Then , , and are idempotent, but .
Statement (iv) is false because need not imply . For example, over any field take
Both maps are idempotent and , but
Consequently
Gauss lemma for polynomials states that the product of two primitive polynomials over a unique factorization domain is primitive. In particular, a primitive polynomial in is reducible over exactly when it is reducible over .
Eisenstein criterion says that a primitive polynomial
is irreducible over if there is a prime such that , for every , and . To prove it, suppose with both factors of positive degree. After removing contents, Gauss's lemma lets us take primitive. Reduction modulo gives
so both reduced factors are monomials of positive degree. Their constant terms are therefore divisible by , making divide , a contradiction.
An algebraic integer is a complex number satisfying a monic polynomial in . Let be one and let be its monic minimal polynomial. The usual proof using polynomial content shows that . The set
is the kernel of the polynomial-evaluation ring homomorphism, hence an ideal. Every is divisible by in . Because is monic, polynomial division of by takes place in , and the remainder must vanish by minimality. Therefore
where is monic and irreducible.
For
translation gives
This is Eisenstein at , so and therefore are irreducible over . Hence
Irreducibility and Gauss's lemma also show that is a prime ideal of , so
It is not a field. The class of is nonzero but not a unit: reducing further modulo gives a nonzero quotient
in which the image of is zero, whereas a unit must remain a unit under every unital quotient map. Thus
Here
The L1 norm and uniform norm satisfy
so the identity from the metric to the metric is one-Lipschitz and therefore continuous. The two metrics do not induce the same topology on all of . For
one has but . Thus convergence need not imply uniform convergence.
A map is Lipschitz continuous if there is such that
for all . Evaluation at is one-Lipschitz because
Choose distinct and define
The Vandermonde determinant is nonzero, so is a bijection. It is one-Lipschitz for the two uniform metrics. If are the associated Lagrange cardinal polynomials, then
and hence
Thus is also Lipschitz.
Let be the polynomials whose values lie in . Its image under lies in the bounded cube . It is closed: if , then the Lipschitz inverse gives uniform convergence , and passing to the limit pointwise preserves . By the Heine-Borel theorem, is compact, and the continuous inverse carries compactness back to . Therefore
The identity map
is a continuous bijection by . Its domain is compact by part (i), and its codomain is a Hausdorff space because every metric space is Hausdorff. The compact-to-Hausdorff continuous bijection theorem therefore makes the identity a homeomorphism. Consequently
For a continuously differentiable curve in the Poincare half-plane model, its hyperbolic length is
The hyperbolic lines are the geodesics: vertical Euclidean lines and Euclidean semicircles whose centres lie on the real axis.
The unique hyperbolic line through distinct can be carried by an upper-half-plane Möbius transformation to the imaginary axis. Such transformations are isometries by hypothesis, so it is enough to consider endpoints and . Every joining curve satisfies
Equality holds for the monotone vertical parametrization
Thus the appropriately parametrized hyperbolic-line segment attains the infimum defining .
Now let have positive infimum distance. They neither intersect nor share an ideal endpoint: an intersection would give distance zero directly, while lines sharing an ideal endpoint approach one another arbitrarily closely near that endpoint. Hence they are ultraparallel. An upper-half-plane isometry puts them into the form
This is the normal form underlying the common perpendicular of ultraparallel hyperbolic lines. Put . Since
the metric becomes
Every path from to therefore has
Equality requires and monotone , so it is attained on the imaginary axis, which meets both semicircles orthogonally. Its intersection points and realize the distance
For a nonattained example, take the vertical lines and . They share the ideal endpoint at infinity. The horizontal segment at height has hyperbolic length , so their infimum distance is zero, but distinct points of always have positive distance. Hence the infimum is not attained.
The partial fraction decomposition is
For , expand the second term as a geometric series:
Hence
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