The dual map reverses the direction of the linear map:Here the dual spaces consist of complex-linear functionals. Composition with is linear both as a functional on and as an operation on , so this does define a linear map between the dual spaces.
Let and be the chosen bases, and let and be their dual bases. If represents , then . ThereforeThe coefficient in row , column of the matrix of is thus , giving the matrix transpose . This calculation introduces no complex conjugation: the algebraic dual map uses complex-linear functionals, whereas a Hermitian transpose belongs to the inner-product adjoint construction.
The Fundamental theorem of finitely generated abelian groups expresses every finite abelian group of this order as a product of cyclic groups of prime-power order. Their exponents correspond to the partitions of an integer :These are pairwise nonisomorphic: the largest order of a group element distinguishes all except the two groups with largest element order , and those have respectively and elements annihilated by multiplication by . The classification exhausts the possibilities, so there are five isomorphism classes.
The sequence has uniform convergence to on precisely whenThe same must work throughout the interval; equivalently .
For each fixed , continuity of the logarithm gives the pointwise convergence . But at , which belongs to for ,Consequently the uniform error cannot tend to zero. In fact is unbounded as for every fixed . The pointwise limit is , and convergence is not uniform.
For each fixed , , so the pointwise limit is . Moreover givesThus the limit is , with uniform convergence on .
The argument principle states that if is meromorphic on a neighbourhood of a positively oriented simple closed contour and its interior, with neither zeros nor poles on the contour, thenwhere and count its interior zeros and poles with multiplicity. This integer is also the winding number of about zero.
Fix . Injectivity prevents from being constant on a neighbourhood of , so its Taylor expansion has the formChoose a small closed disk , centred at , such that and are nonzero throughout . Then has its sole zero at in , of multiplicity , while has no zero in . On its boundary let .
Choose . For every , the holomorphic function is nonzero on . By the argument principle, its number of zeros is an integer given by a contour integral varying continuously with , hence remains . At none of these zeros is , so their derivatives are nonzero and they are simple zeros. Thus there are distinct points taking the value . Injectivity forces , proving everywhere in .
Take the wave speed and introduce characteristic coordinates , . The chain rule givesThe wave equation therefore says . Integrating first with respect to gives , and integrating with respect to gives with twice differentiable . Conversely substitution shows that every such sum solves the wave equation. The two terms are travelling waves of unchanged shape, moving respectively to the left and right at speed .
The zero initial displacement gives , and the initial velocity gives . Hence the D'Alembert formula with initial velocity isFor a classical twice differentiable solution one may take . Differentiation gives and directly. The coordinate calculation also works for any nonzero signed , with physical speed . If the printed constant is allowed to be , the equation instead gives and these initial data give ; the displayed travelling-wave representation requires .
For the wavefunction of a particle of mass , the probability density and probability current areFor a real potential , the Time-dependent Schrödinger equation and its complex conjugate readMultiplying by and respectively yieldsThe potential terms cancel because is real. This is the continuity equation, expressing local conservation of probability.
For the given superposition the common time phase cancels in , andThe expression in the second parentheses is purely imaginary, so the second term is real and contributes nothing to the probability current. ThusIt is the incoming probability current minus the reflected probability current.
For a moving circuit, Faraday's law takes the formHere is the instantaneous wire contour, its local material velocity, and any spanning surface. The contour orientation and surface normal vector obey the right-hand convention. The integral on the right is the magnetic flux, differentiated with both the field and circuit position allowed to vary. The electric field term is the electric force per unit electric charge around the wire, and supplies the motional electromotive force. Their sum is the electromotive force driving charge around the moving circuit. The condition makes the magnetic flux independent of the spanning surface.
Choose the initial loop normal vector to be , so rotation about gives . The spatially uniform magnetic field givesUsing Ohm's law for the resistive loop,Positive electric current is measured in the contour orientation associated with . Reversing that convention reverses the signed answer. When , the magnetic flux is constant and the induced electric current vanishes. This uses the usual thin resistive-circuit approximation with self-inductance neglected.
Let . Direct evaluation on gives , so the Peano kernel theorem givesThis representation also follows by applying to the Taylor expansion of with integral remainder. The derivative at zero of the truncated quadratic is zero for , and its sampled values giveThe Peano kernel is nonnegative, andHence . For , the third derivative is , while and . Thus equality holds, proving the least constant is , attained by .
For a time-homogeneous Markov chain with transition matrix , two states are communicating states when each can be reached from the other with positive probability in finitely many steps:The convention includes communication of a state with itself.
Let be the first positive return time. A recurrent state is one for whichThe subscript means that the Markov chain starts at . The positive-time condition distinguishes a genuine return from the automatic visit at time zero.
Communication is reflexive because , and symmetric by its definition. If and , choose positive-probability paths in steps and in steps. The Chapman-Kolmogorov equation givesCombining the reverse paths gives a positive-probability path as well. Thus communication is transitive and is an equivalence relation.
To transfer recurrence, first establish the recurrence criterion by return probabilities. Put and let under . After each return the Strong Markov property restarts the chain at , so . ThereforeFor this equals ; for it is infinite. The expectation identity follows by summing the nonnegative indicators, so remains valid when the expectation is infinite. Consequently is a recurrent state exactly when its return-probability series diverges.
If , choose with and . For every ,Summing over , recurrence of forces the return-probability series for to diverge. The proved criterion shows is recurrent, so recurrence is a property of the communicating class.
The Cayley-Hamilton theorem states that every square complex matrix satisfies its own characteristic polynomial: if , thenFor a proof, expand the adjugate matrix as . The adjugate identity givesComparing coefficients yields , for , and . Multiply the middle identities on the left by , include the first identity, and add . The terms involving the cancel consecutively:Their right sides sum to . This proves the theorem without any substitution of noncommuting matrices into a scalar polynomial identity.
For a matrix, the characteristic polynomial is . The given matrix trace and determinant therefore make it . By the Cayley-Hamilton theorem, , and hence . Since , the order of a group element cannot be or . If , then , also impossible. Thus the order is .
First, the orbit-stabilizer theorem applied to a face gives : its stabilizer subgroup consists of the identity and the two rotations through about the axis through the centres of that face and its opposite. A rotation preserving a face must preserve its outward normal and cyclically permute its three vertices, so there are no further stabilizing rotations.
The conjugacy classes are as follows:
There are edge axes, face axes, and vertex axes. They give respectively , , and distinct nonidentity rotations, already accounting for all nonidentity elements.
To justify the class assertions, conjugation by a rotation carries the rotation axis to its image and preserves the rotation angle about the transported oriented axis. The transitive group action on edges puts all half-turns in one conjugacy class. The transitive group action on faces puts the rotations defined using outward face normals in one conjugacy class; opposite faces encode opposite signs about the same unoriented axis. The same reasoning with outward vertex directions gives a class of twelve rotations and a class of twelve rotations, including their inverses. These last classes cannot merge: the matrix trace of a three-dimensional rotation is , which differs for and . Thus the list is complete.
The face action gives , as calculated above. Every normal subgroup contains the identity and is a union of whole conjugacy classes. Thus its possible order is plus a subset sum of . The distinct resulting numbers areBy Lagrange's theorem for finite groups, a subgroup order divides . Only and in this list do so. Consequently the normal subgroups are and , and the rotational symmetry group of a regular icosahedron is a simple group.
In the Poincaré half-plane model, has Riemannian metricIts orientation-preserving isometries are the Möbius transformations with real coefficients and , with a simultaneous sign change representing the same map. The full isometry group also contains their compositions with , which reverse orientation. The hyperbolic lines are vertical Euclidean lines and upper semicircles centred on the real axis; each meets the boundary orthogonally.
A hyperbolic line with finite endpoints is mapped to the imaginary axis byIts coefficient determinant is , so rescaling the coefficients makes this an orientation-preserving isometry. The endpoints map to and , which characterize the imaginary-axis hyperbolic line. For a vertical line with endpoints , use . If send the two prescribed lines to the imaginary axis, sends the first to the second. This proves transitivity on hyperbolic lines.
For two ultraparallel hyperbolic lines, choose their common perpendicular and map it to the imaginary axis. A hyperbolic line perpendicular to that axis is a semicircle centred at zero: orthogonality at forces the circle centre to have real coordinate zero. Thus the reflecting lines become semicircles of distinct radii . The hyperbolic reflection in the radius- semicircle is ; it fixes that semicircle pointwise and reverses orientation. Their composition isIts th power is , and no positive power is the identity since and . Conjugation by the chosen isometry preserves order of a group element, so the original composition has infinite order. Reversing the order of the reflections replaces by and gives the same conclusion.
The contraction mapping theorem says that if is a nonempty complete metric space and satisfies for a constant , then has exactly one fixed point.
For the proof, start at and set . Iterating the contraction bound gives . The triangle inequality then gives, for ,Thus is a Cauchy sequence and has a limit by completeness. Since the contraction is continuous, . If is another fixed point, then , forcing distance zero. This proves existence and uniqueness.
For the integral map, the fundamental theorem of calculus shows that is continuous whenever is continuous. In the supremum norm,Hence . We can chooseThe space with this supremum norm is complete: a uniformly Cauchy sequence has pointwise real limits, the Cauchy bound passes to those limits to give uniform convergence, and a uniform limit of continuous functions is continuous. The contraction mapping theorem therefore gives a unique continuous with . The fundamental theorem of calculus makes this differentiable, with and . Conversely every solution of that initial-value problem obeys the integral equation, so uniqueness transfers to the ordinary differential equation. Explicitly on , as direct differentiation confirms.
The closure is the intersection of all closed subsets containing ; equivalently it consists of the points whose every open neighbourhood meets .
Suppose is continuous and . For any open neighbourhood of , continuity makes an open neighbourhood of , so it meets . Hence meets , showing . This proves .
Conversely suppose this inclusion holds for every subset . For a closed subset , let . Then and therefore . By the assumed inclusion, , so . Since always, is closed. Thus every closed set has closed preimage, equivalently every open set has open preimage. This is continuity, proving the claimed equivalence.
For each integer , the open balls cover the compact metric space . Compactness supplies a finite subcover with centres forming a finite set . Define , a countable union of finite sets and therefore countable.
For any and , choose with . One of the covering balls contains , so there is with . Every open neighbourhood of therefore meets , giving . Thus , and is a countable dense subset. If is empty, simply take .
For an integer and , the definition of the Laplace transform gives . For , integration by parts givesThe endpoint term vanishes because exponential decay dominates every fixed power of . Induction therefore gives . Multiplication by replaces by in the defining integral, soThe second formula holds for and is the Laplace transform shift theorem.
By the Bromwich inversion formula, for and ,Close the upward vertical segment by a left semicircle of radius centred at . On that arc , so , while is bounded below by a constant times for large . Its length is , hence the arc integral tends to zero as . The contour is positively oriented and encloses the double poles at and .
Their residues areandThe residue theorem therefore yieldsThe value at zero follows by continuity and is .
Part (i) gives and . The convolution theorem for Laplace transforms therefore givesRepeated integration by parts yieldsSubstitution gives , agreeing with the contour integration result.
Write . Using the Laplace transform of a derivative and the initial data givesThe transformed equation is , so . The preceding inverse Laplace transform therefore givesFor a direct check, , , , and . These satisfy both the ordinary differential equation and all four initial conditions.
For fixed endpoints, the Euler-Lagrange equation is . Since has no explicit dependence on , differentiating givesThus , the Beltrami identity.
With , the arc length element and the prescribed speed give the travel-time functionalFor the circular road , this is .
For the integrand , the Beltrami identity simplifies toThe candidate has and the required endpoints. To prove it really minimizes the travel time, rather than merely satisfies a first integral, put . ThenThis is the Euclidean arc length integrand for the inverted curve , whose endpoints are and . Every connecting curve has length at least their Euclidean distance , by the triangle inequality. Equality is attained by the straight line segment . In polar form it gives , hence the proposed . It stays strictly positive throughout the interval. ConsequentlyThis travel-time minimization with speed proportional to squared radius is globally solved by the inversion: its minimum is strictly less than .
Let the photon momenta be , with . Four-momentum conservation gives total energy and total momentum for the pion. Its mass shell relation therefore givesSince , the sine is nonnegative, and taking the positive square root yields
In the pion rest frame, conservation of three-momentum makes the electron and massless neutrino momenta equal and opposite, of common magnitude . Their energies obeySquaring and cancelling givesThe electron four-momentum satisfies . Thus, for the physically allowed decay ,
For constant mass density and incompressible flow, use in the Euler equations for an inviscid fluid. Taking the curl removes the pressure and kinetic energy gradients, giving . The supplied vector identity, with and , yields the vorticity equationIn a two-dimensional flow is independent of , and . The right side vanishes, so : each material element retains its vorticity. The vortex lines are parallel to and are carried by the planar velocity. Also planar incompressibility preserves the area of a material cross-section; integrating its conserved vorticity over that area shows that its circulation, or vortex strength, stays constant. Thus the vortex lines move with the fluid without changing strength.
Place a line vortex of circulation at above the wall . Its velocity field is . The method of images puts a vortex of circulation at . With , the resulting stream function isIt is identically zero on the wall, so there. In the fluid half-plane it has just the required vortex singularity, with no other singularities, and its velocity decays at infinity. This is the no-background-flow solution with the wall: the difference from another such solution is a regular irrotational, divergence-free decaying field with zero normal velocity. Reflect its tangential component evenly and its normal component oddly across the wall. The reflected components are bounded harmonic functions on the whole plane, so they are constant by harmonic Liouville theorem, and decay forces both constants to be zero. Thus replacing the wall by the image gives the same flow. The real vortex moves under the image velocity, excluding its own singular velocity, soIts signed velocity parallel to the wall is , and its speed is .
For the quarter-plane, place images of circulation at and , and at . The paired stream functions make both walls streamlines. Summing their velocities at the real vortex givesIn polar coordinates,It follows directly thatThus the line-vortex trajectory in a quarter-plane is .
Write and . For an identifiable two-parameter linear regression assume ; for the variance estimate and test below also assume . The least-squares normal equations areUsing givesThe residual sum of squares has positive-definite quadratic part , so these equations give its unique minimum. The normal distribution of the independent errors gives the log-likelihoodFor every fixed positive , maximizing this over is exactly minimizing the same residual sum of squares. Thus the ordinary least squares estimators are also the maximum-likelihood estimators.
The printed hypotheses do not explicitly require or . If , all vanish and is unidentifiable; this is an intercept-only model with residual degrees of freedom. For its residual is identically zero, so the likelihood has no finite maximizer with positive variance. If but , the fit is saturated, leaving no residual variance estimate or Student test with positive degrees of freedom. The following nondegenerate formulas use and .
Let . Differentiating the log-likelihood in givesFor this changes from positive to negative at , soTo find its bias, substitute the model and use the orthogonal fit directions and , obtainingThe three expectations are , , and , respectively: and . Hence , giving the unbiased estimatorWith , a zero residual sum of squares is a probability-zero event in the model. For that exceptional dataset the likelihood is unbounded as , rather than having a maximum at a positive variance. In the intercept-only case , the corresponding unbiased multiplier is for .
Set and . These are orthonormal because . Complete them to an orthonormal basis of . An orthogonal transformation of the standard normal error vector has independent normal random variables as coordinates : its joint probability density remains because the transformation preserves squared length and has Jacobian determinant of absolute value one.
Projection onto these basis directions givesTherefore the joint distribution of least-squares and variance estimators isThe last law is the chi-squared distribution of a sum of squared independent normal random variables with mean zero and variance one, and independence follows because the three statistics use disjoint independent coordinate sets. When all , omit the slope direction: and are independent, and there is no identifiable slope estimator.
Under the null hypothesis, the standardized intercept is standard normal, and is independent with chi-squared distribution of degrees of freedom. Consequently the Student t test for a simple-regression intercept usesChoose a significance level before observing the test result. For the two-sided alternative, reject when , where the subscript denotes the indicated quantile of the Student t-distribution. The null rejection probability is exactly , independent of the nuisance slope and variance. Equivalently report the p-value . The test assumes the normal independent-error model and a positive residual variance estimate. In the intercept-only case with , use and instead.
Use payoff , so maximization of is equivalent to the required minimization. In the given simplex tableau, can increase the payoff. The simplex ratio test has candidate ratios in the row and in the row; the negative coefficient in the row imposes no upper bound. Thus enters the simplex basis and leaves.
Divide the pivot row by , then eliminate from the other rows. The resulting simplex dictionary isAll slack variables and original variables are nonnegative. The last row therefore proves for every feasible point; setting the nonbasic variables to zero attains it and leaves all basic variables nonnegative. HenceThe slack vector is .
The amended payoff is . Using the previous simplex dictionary,Thus enters. The positive pivot-column coefficients give ratios from and from ; the coefficient in the row gives no bound. The simplex ratio test makes leave. Dividing that row by and eliminating givesThe positive objective-row coefficients and nonnegative slack variables prove optimality at . ThereforeAll three constraints are equalities at this point. Strict positivity of the three objective-row coefficients also forces every optimal point to have all three slacks zero; the displayed dictionary then makes the optimizer unique.
Write the amended primal as with , . A convenient linear programming duality convention uses and gives subject to . Explicitly the dual isThe optimal dual vector is the negative of the three payoff-row slack coefficients:Indeed substitution gives , so all dual inequalities hold. To certify optimality directly by weak duality, for any feasible primal and dual vectors,where the second inequality uses and . Our feasible primal and dual vectors have equal values , so neither can be improved. This is a linear programming optimality certificate.
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