If generate the module , define the R-module homomorphismThis is a surjection by the definition of generation. Conversely, an R-module homomorphism that is a surjection sends the standard basis vectors of the free module to a generating family, since every vector in is their linear combination. ThusThis is the finite generation as a quotient of a finite free module criterion. The zero module causes no exception: it is generated by the empty family, or by one zero element.
For the requested example, take , with the usual integer scalar action. Reducing both coordinates modulo two gives an R-module homomorphism that is a surjection with nonzero kernel , so it is not an isomorphism. Every image of is a cyclic module, whereas every element of has additive order at most two and has four elements. Hence admits no such surjection from .
A metric space is a complete metric space when every Cauchy sequence converges to a point of that space: for each , the condition for all sufficiently large must imply existence of with .
A Cauchy sequence in is also Cauchy in , so it converges there by the assumed completeness. Its limit remains between zero and one, since inequalities are preserved under limits. ThereforeThis is an instance of the fact that a closed subset of a complete metric space is complete with its induced metric.
The rational sequence satisfies . It is therefore a Cauchy sequence in the induced metric on . Any limit in would also be its real limit, which is . ThusCompleteness concerns limits lying in the space, so being a dense subset of does not suffice.
Let . The points lie on the specified graph and converge in to . They form a Cauchy sequence in the induced metric, but their only possible limit is absent from the space. Adding does not supply that missing limit. Hence the specified space is not complete.
For the unheaded request on , use the arctangent pullback metricPositivity, symmetry and the triangle inequality follow from the ordinary distance, and injectivity of gives only if . The sequence is Cauchy for this metric, because , but cannot converge to any finite real : that would require . Thus this metric makes incomplete, even though it induces its usual topology.
The product topology has as a basis of a topology all sets , where is open in and is open in . Open sets are arbitrary unions of these rectangles. The projection maps are and . For any open and ,These are open rectangles, including the empty case. Taking inverse images of open sets therefore proves that both projection maps are continuous functions.
If is Hausdorff, every pair has disjoint open neighborhoods and . The rectangle is an open neighborhood of disjoint from the diagonal. Hence every point of its complement is interior, so the diagonal is a closed set.
Conversely, if the diagonal is closed, its complement is open in the product topology. For , the rectangle-basis property gives open and with disjoint from the diagonal. If , then lies in that rectangle, a contradiction. Thus , giving the Hausdorff separation condition. ConsequentlyThe argument includes spaces with zero or one point, for which both conditions hold.
Let be the Laplace transform of . The initial values give and , while . Therefore, for sufficiently large,The partial fraction decomposition isInverting the elementary Laplace transforms givesThese coefficients give and ; the transformed equation, or direct differentiation, verifies the forcing. Uniqueness follows from uniqueness for the corresponding linear initial-value ordinary differential equation.
Write for the complex coordinate. The inverse stereographic projection iswith mapped to the north pole. A rotation about the third axis sends to , represented byFor the rotation , substitution in the stereographic projection givesBoth displayed matrices are unitary with determinant one, hence belong to the special unitary group.
Use the rotation-generation result that every can be written , with angles chosen suitably. This is the Euler-angle decomposition, which is allowed here. Composition of Möbius transformations corresponds to multiplication of their matrix representatives, soThe formulas extend at poles in the Riemann sphere. This realizes sphere rotations as special-unitary Möbius transformations. The two representatives and define the same Möbius transformation, as expected for the double covering of the special orthogonal group.
For the boundary constraint , the Lagrange multiplier equations for areNeither coordinate can vanish at a stationary point. Substitution gives . For , and ; for , and . The constraint circle is compact, its gradient is nowhere zero, and every extremum must occur among these stationary points. ThusThe paired signs in each expression are linked. The inequality also confirms the global values.
Let denote the stated unit cost of cylindrical wall, and assume . The circular cylinder and hemisphere give the volume constraint and total costOnly the walls and cap have specified costs, so no separate base cost is included. Eliminating giveswith from . Now vanishes at . Moreover and the stationary point is feasible, so it is the unique global minimum. The optimal dimensions are
The substitution removes the zero-order term: and , so the partial differential equation becomes . Its method of characteristics givesThe invariant is . Therefore . The initial line is noncharacteristic, and the boundary data give . HenceEach characteristic meets the data line once, ensuring uniqueness among differentiable solutions, and substituting the result verifies both the equation and the data.
Inside the infinite square well, the time-independent Schrodinger equation is . The infinite exterior potential imposes . For , the first condition leaves a sine and the second requires . A zero or negative energy gives only the zero solution under these conditions. The normalized energy eigenstates and eigenvalues areThe wavefunctions vanish outside the well, and a constant phase is immaterial. Normalization uses .
The Born rule gives the probability of as the squared coefficient of the initial state in the energy eigenstate basis. Direct integration givesThe strict energy cutoff corresponds to , so only contribute. Both coefficients equal , and thereforeThe discontinuous initial wavefunction is a legitimate normalized state for this spectral probability calculation, although it is not in the Hamiltonian's differentiability domain; finite mean energy is not required to compute this probability.
A reversible Markov chain has a stationary law for which every finite path has the same distribution as its time-reversed path:For a transition matrix , the equivalent detailed balance condition is for all . It implies by summing over . Multiplying the balance identities along a path shows equality of its forward and reverse probabilities when ; conversely, taking paths of length one gives those identities.
For the usual undirected graph with at least two vertices, a simple random walk chooses a neighbor uniformly at each step, so when and are adjacent and zero otherwise, where is the degree of a vertex. The handshaking lemma gives . Thus the stationary distribution of a graph random walk isFor adjacent , , and for nonadjacent pairs both sides vanish. By detailed balance, this is an invariant distribution and the walk started from it is a reversible Markov chain. Connectedness makes the finite walk an irreducible Markov chain, giving uniqueness of its invariant distribution. No aperiodicity assumption is needed for uniqueness, so a bipartite graph is allowed.
If the connected graph has a single isolated vertex, the usual neighbor-choice formula is undefined. With the natural absorbing convention , its unique invariant distribution is and it is reversible. The degree-normalization formula presupposes at least one edge.
Associate to the symmetric bilinear form . If is identically zero, every basis is diagonal. Otherwise choose with . Every has the decompositionwhose second term lies in . Thus , with no cross term in . Induction on dimension gives a diagonal basis. Rescaling its nonzero entries reduces the form towith additional zero coordinates. Define the rank of a quadratic form and its signature . Rank is intrinsic, since it is the rank of , equivalently . Also is the greatest dimension of a subspace on which the restriction of is a positive-definite quadratic form: any such subspace intersects the negative-plus-zero coordinate space only at zero, so its dimension is at most , while the positive coordinate space attains . The corresponding negative statement identifies . This proves the basis independence of and , the Sylvester's law of inertia conclusion.
For a totally isotropic subspace on which vanishes, polarization identity also makes vanish on . Quotient by the radical of a bilinear form. In the resulting nondegenerate form, projection of an isotropic subspace to either the positive or negative coordinate space is injective, so its dimension is at most . Consequently . The radical of a bilinear form together with the vectors , , attains this bound. The maximum dimension of a totally isotropic subspace is thereforeThe criterion for membership in a diagonal basis follows similarly: a nonzero vector can belong to a diagonal basis if it has nonzero quadratic value, by the same orthogonal splitting, or if it lies in the radical of a bilinear form, by choosing a radical basis containing it. An isotropic vector in a diagonal basis must be orthogonal to every basis vector, and hence must lie in that radical. For the specified form, its radical is the -axis, giving exactlyThe zero vector never belongs to a basis.
A Euclidean domain is an integral domain with a function such that for each and there are with and either or . Some conventions add a multiplicative monotonicity condition; it is unnecessary for this implication.
Let be a nonzero ideal. Choose minimizing , possible because the values lie in the nonnegative integers. For , division by gives , with . A nonzero remainder would contradict minimality, so and . Since , the reverse inclusion also holds. The zero ideal is . Thus
Reducing coefficients modulo gives the ring isomorphismIf , its monic leading coefficient remains one modulo , so . Polynomial division gives a unique representative of degree less than : existence follows by division, and the difference of two such representatives cannot be a nonzero multiple of a degree- monic polynomial. There are choices for each of the coefficients, provingIrreducibility of is not needed for finiteness; without it the quotient ring need not be a field.
Write the Gaussian integer , with , and set . Complex conjugation preserves , because . Choose a nonzero . Then is a positive integer in . It cannot be one because is a proper prime ideal. Factoring into rational primes and applying primality repeatedly gives a prime .
The element satisfies the monic polynomial . Evaluation induces a ring homomorphism that is a surjectionThe source has elements by part (b), soIf , use instead and get at most elements. Moreover is an integral domain, so its finiteness makes it a field. This proves the finite residue-field theorem for Gaussian integer orders without incorrectly assuming that every Gaussian integer order is a principal ideal domain.
A contraction mapping satisfies for all , with one fixed . The contraction mapping theorem states that such a map on a nonempty complete metric space has a unique fixed point and that every sequence of iterates converges to it.
Choose and put . Iteration gives , so for ,Thus the iterates form a Cauchy sequence and converge by completeness to . The Lipschitz bound gives continuity of , hence . Two fixed points satisfy , forcing equality of the points. Passing also gives the usual geometric error estimate. For , convergence occurs after one application.
If is a contraction mapping, let be its unique fixed point. The commutation identity gives , so uniqueness implies . Any fixed point of is a fixed point of , giving uniqueness, without even assuming continuous. On the complete discrete metric space , the map , has constant second iterate but is not a contraction: .
For the specified function, on because it starts at zero and has derivative . Therefore maps the complete half-line into itself. Its derivative satisfiesThe mean value theorem therefore makes it a contraction of constant at most . Hence
Fix . The Cauchy integral formula and the uniformly convergent geometric series on giveDefiningthe remainder after degree has modulus at most , which tends to zero uniformly on each smaller disk. Differentiating the integral formula at zero identifies , independently of . Since is an entire function, can be chosen larger than any given , proving the global Taylor series.
For the requested radius , the same coefficient integral gives the Cauchy estimateTo characterize equality in the Cauchy coefficient estimate, parametrize its circle:If , the identity theorem gives . Otherwise equality in the modulus bound requires the continuous integrand to have both constant modulus and constant complex argument. To see this directly, rotate its average to the positive real axis: its real part is bounded above by , and equality of its average with forces that real part to equal everywhere. Thus on the circle. The identity theorem extends that equality to the plane. Conversely every such monomial attains the bound. Thereforeincluding the zero function and, when , arbitrary constant functions.
At a regular point, choose the unit normal . The first fundamental form is the induced squared lengthThe second fundamental form isThe Gaussian curvature is the determinant of the shape operator, , independent of the normal orientation.
For the given graph, and , so with ,ThereforeThe surface is regular everywhere. The printed description “hyperboloid” is a naming error: this graph is a hyperbolic paraboloid, and the computation uses the actual parametrization.
Assume the parametrization is and regular, so its curvature is defined. Write and . Since and , its first fundamental form isFor the unit normal , the mixed coefficient of the second fundamental form iswhere the term containing twice vanishes. Also , while . ThusThe Gaussian curvature vanishes exactly when the displayed scalar triple product is zero. This is the Gaussian curvature of a ruled surface criterion; at a singular point with , curvature and the claimed equivalence are not defined.
Interpret the three conditions at zero as an initial-value problem on , with interior source . A causal Green function satisfies and vanishes for . Since the leading coefficient of the third derivative is one, the jump conditions for a third-order Green function require and continuous and to jump by one. For , the homogeneous roots are . Solving , yieldsFor it vanishes near zero, so all three initial boundary conditions hold. The matching conditions ensure that supplies precisely a Dirac delta, without unwanted delta derivatives.
The homogeneous solution carrying the nonzero initial data is . The Green-function representation therefore givesFor the integral vanishes. For , set and integrate to obtain . ThusThe bracket and its first two derivatives vanish at , so match continuously there; its third derivative jumps by the stated forcing. The value assigned to is immaterial. The source at the initial endpoint would need a separate endpoint-delta convention, which is not used in this integral.
The orbital angular momentum operators areIn particular . For smooth compactly supported functions , integration by parts produces no boundary term, and . HenceThis proves Hermiticity on the common test-function domain, and the same calculation applies on suitable decaying domains. As an unbounded operator, it is not defined on every function: the usual self-adjoint operator realization is the generator of unitary rotations about the third axis. Thus the integration statement includes its necessary domain/boundary assumptions.
Take a normalized state for which the indicated variances and operator pairings exist. Set and . For real , positivity of the squared norm givesThe canonical commutation relations yield . Thus the quadratic polynomial in is nonnegative everywhere only if its discriminant is nonpositive. This gives the Robertson uncertainty principleIf either variance is zero, the same polynomial argument forces the commutator expectation to vanish, so that edge case is included. Centering the operators is essential to obtain variances rather than uncentered second moments.
Use the radial exponential shown in the original PDF; the TeX's is a transcription defect. Every orbital angular momentum operator annihilates a radial function, so it acts only on . The angular momentum of a radial function times a linear polynomial is determined by its degree-one angular factor: direct application of the rotation derivatives givesEquivalently its restriction to the sphere is a degree-one spherical harmonic. ThusFurthermore . Its expected value is proportional to the integral of . The cross terms are odd in a coordinate, and the integrals of and agree by rotational symmetry. HenceThe state need not be an eigenstate of . If normalization is desired, , so ; the zero expectation holds after normalization for any nonzero initial .
Let the smaller charge be at and the other charge be at , where ; an overall sign reversal changes no zero-potential locus. Put . The electrostatic potential vanishes exactly when . Completing the square gives the Apollonius sphereThe distances from its center to the charge positions are and . Thus it encloses exactly the charge of smaller magnitude. Unequal magnitudes are essential: the equal-magnitude case instead gives the perpendicular bisector plane.
Write . In SI units, the exterior electrostatic potential solveswith the point-charge singularity . The image charge for a grounded conducting sphere choiceslie inside the sphere. On , direct squaring gives . Thereforesatisfies the source equation, grounded boundary value and decay at infinity. The Uniqueness of the Dirichlet problem, applied to the harmonic difference with its singularity removed, identifies this with the physical exterior potential. Thus its gradient gives the required exterior electric field.
The charge feels the induced field, equivalently the field of the image charge, excluding its own singular field. Their separation is , so Coulomb's law givesIts magnitude is and its direction is toward the sphere's center, independent of the sign of . No factor one-half belongs in this force; that factor occurs in induced electrostatic energy instead.
For constant-density incompressible inviscid flow with conservative body force, Euler equations for an inviscid fluid give . Using , take the curl to obtain . Since both divergences vanish, the vector identity expands this toWithout incompressibility or the constant-density/barotropic hypothesis, extra compression or baroclinic terms are present; the printed equation uses these flow assumptions.
Let , with . Axisymmetric mass conservation is . If is independent of , then is affine in . The impermeable moving-plate conditions force , and integrating the radial equation gives . Regularity at the axis excludes . The meridional part of the axisymmetric inviscid flow between moving parallel plates is thereforeFor no swirl, completes the field. Continuity alone does not determine azimuthal motion; this must be specified separately. More generally, prescribe a smooth regular initial profile independent of . The azimuthal part of Euler equations for an inviscid fluid isso conservation of along radial particle paths gives , where . Together with the meridional components above, this gives a family of complete fields, with a suitable pressure determined by the radial and vertical equations. The field is therefore not unique without rotational data.
With the stated solid-body rotation, and . The vorticity equation gives , henceFor a fluid particle, , so is constant and is constant. This is conservation of angular momentum about the axis: radial spreading when the plates approach decreases the angular velocity. The meridional and rotating fields satisfy the inviscid equations with an appropriate pressure; no tangential no-slip condition is imposed on inviscid plates.
Let be the distinct interior roots of where its sign changes, and put . If , orthogonality gives . But has constant sign on , apart from its isolated zeros, because every sign change has been canceled. It is not identically zero, and the positive weight makes its integral nonzero, a contradiction. Thus . Degree forces exactly distinct simple roots, all inside .
For distinct nodes, let . Lagrange interpolation polynomial gives for every polynomial of degree at most . Integrating this identity proves exactness with .
For the Gaussian quadrature nodes, divide any as , with . The integral of vanishes by orthogonality, and its nodal values vanish because . The remaining polynomial is integrated exactly by the preceding interpolation result. HenceIts weights are positive: exactness applied to gives .
Define the error functional . It annihilates polynomials of degree at most . For , the Peano kernel theorem giveswhere a formal Peano kernel with the normalization made explicit isNo evaluation of is needed. The supplied inner product presupposes an integrable positive weight on the finite interval, so the integral and point-evaluation error functional is bounded on continuous functions.
The Gauss-Markov theorem states that with full-column-rank design, mean-zero errors and covariance , the ordinary least squares estimator is the best linear unbiased estimator: its covariance is no larger than any other such estimator's in the Loewner order. Normality is unnecessary for that theorem.
In the given normal linear model, maximizing the likelihood function is equivalent to minimizing . The normal equations and full rank giveFor a direct variance comparison, write . Unbiasedness for every requires . Set and , so . The cross covariance terms vanish because . ThereforeThis proves the requested comparison for every contrast without relying only on the theorem's name.
Write the one-column design as and . Maximizing the normal linear model likelihood first gives . Its minimized residual sum of squares is . For variance , the remaining log likelihood is plus a constant, whose maximum is atHere almost surely because and the true variance is positive. In the exceptional data case , the likelihood is unbounded as , so there is no positive-variance maximum.
Let , the orthogonal projection matrix onto the design column. Then and . These are orthogonal linear projections of an isotropic multivariate normal distribution, hence independent. An orthonormal coordinate system adapted to makes the residual squared length a sum of independent squared standard normals. Thus the joint distribution of least-squares and variance estimators is the product lawIn particular the maximum likelihood variance estimator is biased: ; the unbiased residual estimator uses denominator .
In a matrix game, entry is the row player's payoff, and the column player's payoff is . A mixed strategy is a probability vector over the available rows or columns. With strategies , the row payoff is . Its optimal mixed strategy maximizes its guaranteed payoff, while the column player minimizes the largest row payoff:The equality is the finite minimax theorem. Equivalently the row player maximizes , and the column player minimizes . Each optimal strategy guarantees its corresponding bound against every opponent strategy; for the column player's own negative payoff this is also a maximin strategy.
For a real antisymmetric matrix , for every real vector . Thus for each row strategy , the column player could choose , giving . Hence the row security value is at most zero. Conversely, for each column strategy , the row choice gives , so the column security value is at least zero. The minimax theorem equates these values, provingThe choices matching the opponent in this proof establish inequalities for security levels; they do not by themselves specify a single universal optimal strategy.
In this consecutive-number antisymmetric game, with the row player's number denoted , the payoff matrix isIt is an antisymmetric matrix, so the matrix game has value zero for every . For ,satisfies and , proving optimality for both players.
For any larger , extend the same strategy by zero probabilities:Indeed, the first three coordinates of are zero. For , ; for , all three supported numbers are at least two below , so . Hence and, by antisymmetry, . The column player using prevents positive payoff, while the row player using prevents negative payoff, a mixed-strategy optimality certificate for a matrix game. This explicitly checks all the additional strategies rather than assuming the three-number subgame remains optimal.
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