For the given orthonormal basis, the orthogonal projection is
It belongs to , and for every basis vector. Thus . For any , decompose . The summands are orthogonal, so the Pythagorean theorem in an inner-product space for the inner product gives
Equality holds exactly when . Hence is the unique closest point of to . This proves the minimizing property as well as the formula, including and .
A polynomial in is a primitive polynomial when the greatest common divisor of its coefficients is one. The Gauss lemma for polynomials states that a product of primitive integer polynomials is primitive, and that a primitive positive-degree integer polynomial is reducible over exactly when it factors into positive-degree integer polynomials. More generally, polynomial content is multiplicative up to sign.
The Eisenstein criterion states that a primitive polynomial is irreducible over if there is a prime such that , for every , and . These criteria permit integer coefficient tests for rational irreducibility; the following parts apply them with their exact divisibility hypotheses.
Use the Eisenstein criterion with prime . The leading coefficient is one; every lower coefficient, including the zero coefficients, is divisible by ; and the constant coefficient is not divisible by . The polynomial is monic and hence primitive. Therefore it is irreducible over .
A cubic over a field is reducible exactly when it has a root in that field: a nontrivial factorization must contain a degree-one factor. By the rational root theorem, a rational root of this monic integer polynomial must be an integer dividing its constant coefficient, hence either or . Substitution gives and , respectively. Neither is zero. Thus the cubic is irreducible over .
Let denote the polynomial under consideration. The change is an automorphism of and preserves degrees, so it preserves reducibility. Its transformed polynomial is
It is monic; every other coefficient is divisible by , because is prime and ; and its constant coefficient is , not divisible by . The Eisenstein criterion proves that is irreducible, and therefore is irreducible. The argument also includes , when the polynomial is linear. This is the prime-index case of an irreducible polynomial arising as a cyclotomic polynomial.
The map is differentiable at when there exists a linear map such that
The increments are taken sufficiently small to stay in the open domain; is the derivative. This is a joint approximation in all directions, not just the existence of coordinate partial derivatives.
At with , choose . If , neither coordinate changes sign, and
Thus the remainder in the differentiability definition is identically zero throughout that neighborhood. Consequently
which proves the requested differentiability directly.
The disc lies in the upper-right half-plane and avoids zero and the negative real axis. On the slit plane take the holomorphic logarithm with . Its derivative is , and . Therefore the holomorphic square root
is analytic and satisfies . One can also construct it without a global branch theorem: fix either scalar square root of and expand by its convergent binomial series. The series converges on the entire disc because . Either sign gives an admissible choice.
The slit plane is connected and contains . If two holomorphic functions on it extend the same , their difference vanishes on the nonempty open disc . The identity theorem forces their difference to vanish on the entire slit plane. Thus there is at most one analytic extension of the chosen . Choosing the opposite square root initially changes that chosen function; it does not produce two extensions of the same function.
Suppose an analytic extension existed on the punctured plane. The identity theorem would extend from to that connected domain, so would never vanish and differentiation would give . Integrate around the positively oriented unit circle. The argument principle says is times the integer winding number of the closed curve about zero, whereas
This would make that winding number , a contradiction. Hence no such analytic extension exists. Equivalently, continuation of a square root once around zero reverses its sign, preventing a single-valued holomorphic function on the punctured plane.
Use the Fourier transform convention
This convention also gives the sign of the inverse transform in 15A. The Parseval identity, in its bilinear form, is
In particular . Initially take to be Schwartz functions; the formula then extends to with Fourier transforms interpreted by completion.
Here is a proof which also justifies the needed limit operations. For , form
Absolute integrability allows Fubini's theorem to replace the transformed factors by their defining integrals. The elementary Gaussian integral gives
so , with convolution . The kernel is nonnegative, has integral one, and its mass outside any fixed neighborhood of zero tends to zero. Since a Schwartz function is bounded and uniformly continuous, splitting the convolution difference into small and large proves uniformly. As , the last integral consequently tends to .
On the spectral side, repeated integration by parts makes the transforms rapidly decreasing; their product is integrable. The dominated convergence theorem therefore gives . Equating the two limits proves the displayed identity. For general functions, approximate by Schwartz functions. The norm identity makes their transforms Cauchy in with the prescribed factor; the limit defines the Fourier transform independently of the approximation. Taking limits in the bilinear identity proves it for all pairs. Thus the proof includes the hypotheses and avoids unjustified exchanges of nonabsolutely convergent integrals.
Divide the differential equation by . Its Sturm-Liouville form is
Here and weight . Multiply the equations for by the other polynomial and subtract. Integration by parts gives a boundary term , which vanishes at both endpoints because polynomial derivatives are finite and . Hence
With the standard nonnegative degree indices , this proves orthogonality for . If signed integer indices are used literally, the condition is : , so merely would not suffice.
Set and . The chain rule gives , so . For , . A polynomial has , forcing . At , and the same endpoint condition gives . Therefore every polynomial solution is proportional to
The cosine recurrence yields , , confirming that these functions are polynomials. In this normalization the Chebyshev polynomial weight identity is
It is simply cosine orthogonality after .
The four-momentum is . It transforms by the same Lorentz boost as other four-vectors. For an observer moving at in the positive direction, its time and longitudinal components transform as
Substituting the given momentum components proves all three displayed transformation relations.
A photon has zero rest mass, so the relativistic energy-momentum relation gives on the positive-energy branch. Lorentz invariance preserves , and for . Therefore . Dividing the transformed longitudinal momentum by gives the relativistic aberration formula
As , for every fixed the ratio tends to : photon directions are concentrated along the negative direction in the observer's frame. The exactly forward photon is exceptional: if , then for every , and its energy tends to zero. For other fixed angles diverges. The limiting angular behavior is not uniform near , and itself is not an admissible inertial observer velocity.
Taking the curl of the Euler equation gives the vorticity equation for an inviscid incompressible flow without body forces:
The given velocity has divergence and curl . Its vorticity is spatially uniform, so its advective derivative vanishes. The stretching term is . Thus
The signed vertical component is ; its magnitude is , with the source's magnitude convention taking . As an additional consistency check, after imposing this equation the material acceleration is , so a pressure satisfies the full Euler equation.
Write . When , minimizing gives the strictly convex quadratic normal equation . The least-squares estimator is therefore
This is linear regression through the origin, with no fitted intercept. For , let and . An orthonormal change of coordinates in the Gaussian vector separates the unit design direction from its orthogonal residual directions. The first coordinate is normal with mean and variance ; the remaining coordinates are independent centered normals with that variance. Consequently
and these variables are independent. Thus under the null, the Student t test for regression through the origin statistic is
For a prescribed significance level , reject the two-sided null when . The two-sided p-value is . There is one fitted coefficient, so the variance degrees of freedom are , not .
The assumptions and matter. If all , the distribution contains no information about and no informative test is possible. With one nonzero design observation there is no residual variance degree of freedom, so the stated unknown-variance t test cannot be constructed.
Take a finite directed flow network with distinct source , sink and finite nonnegative flow network edge capacities. A flow assigns to each edge with and obeys flow conservation at every vertex except . Its value is net outflow from the source, . A maximal flow here means a maximum flow: one with greatest value among feasible flows. A source-to-sink cut of a flow network is a partition with , ; its cut capacity is , counting directed edges leaving .
The max-flow min-cut theorem states
Summing conservation over cancels internal edges and gives
This is the upper bound for every flow and every cut. To prove equality, a maximum exists: the feasible edge vectors form a nonempty closed bounded subset of a finite-dimensional real space, and flow value is continuous.
For a maximum , construct its residual network. Each edge has a forward residual edge of capacity and a backward residual edge of capacity ; retain those of positive capacity. If a residual source-to-sink path existed, augment by the smallest residual capacity on that finite path. Increasing original forward flows and decreasing backward flows preserves all feasibility conditions and increases value, contradicting maximality. Thus no such augmenting path exists.
Let be the vertices reachable from in the residual network. Then . Every original edge leaving is saturated, since otherwise its positive forward residual edge would make its endpoint reachable. Every original edge entering has zero flow, since otherwise its backward residual edge would give the same contradiction. Hence
Together with the universal upper bound this proves equality and identifies a minimum cut. This proof covers real capacities without assuming that an augmenting-path algorithm terminates after finitely many steps. Merely being impossible to increase all edge flows coordinatewise is not the optimization meaning of “maximal” used in the theorem.
For a Hermitian operator , every eigenvalue is real. Indeed, if with , self-adjointness gives . To prove the finite-dimensional spectral theorem, proceed by induction on the dimension. The fundamental theorem of algebra supplies a root of the characteristic polynomial, hence a unit eigenvector . Its orthogonal complement is invariant: for , . The restriction of to that complement is again Hermitian. Induction supplies an orthonormal basis of eigenvectors there; adjoining gives an orthonormal eigenbasis of the whole space. The zero-dimensional case is immediate. Consequently a Hermitian operator is diagonal in an orthonormal basis, with real diagonal entries.
The adjoint reverses products, so for the two Hermitian operators
Thus is Hermitian if and only if . No positivity hypothesis is needed for this equivalence.
Choose an orthonormal basis of eigenvectors of the positive-definite operator using the proved spectral theorem. Its eigenvalues are strictly positive, because . Define . It is a positive-definite Hermitian operator and , establishing existence of the positive square root of an operator.
For uniqueness, let be any positive-definite Hermitian square root. The identity implies , so preserves each eigenspace of . Its restriction to that space is Hermitian and positive-definite. Diagonalize that restriction by the same spectral theorem. Every resulting eigenvalue satisfies and , hence . Therefore acts as on the entire eigenspace, even when is repeated. These eigenspaces span the space, so the positive-definite Hermitian square root is unique, with eigenvalues .
In the polynomial ring , the ideal is nonzero and prime: the quotient ring is isomorphic to the integral domain , by evaluation at zero. It is not maximal, since that quotient is not a field. Equivalently . Thus is a nonzero prime ideal which is not maximal.
Consider the ideal in . It is proper: evaluation at zero followed by reduction modulo maps the ring onto and has kernel . Suppose . Then divides the constant polynomial , so is a constant integer dividing . Up to sign, the only possibilities are and . The first would make the ideal the whole ring; the second cannot divide in . Both are impossible. This proves the integer polynomial ring is not a principal ideal domain result: is not a principal ideal domain.
The coefficient identity
holds over every field. Both factors have positive degree, including in characteristics and , because their leading coefficients remain one. Therefore there is no field over which this polynomial is irreducible.
In the quotient ring, the classes of and are nonzero: neither nonzero polynomial of degree less than three belongs to the ideal generated by . But their product is the zero class, since
The quotient thus contains zero divisors, so it is not an integral domain.
Use the usual convention that a ring homomorphism preserves the identity. Such a map from the quotient ring to fixes : it fixes integers, and preservation of inverses fixes rational numbers. It is therefore determined by the image of the class of . The defining relation forces . Conversely, evaluation at any such annihilates and hence factors through the quotient. Thus there are exactly three unital homomorphisms, namely
If the convention permits nonunital ring homomorphisms, add the zero map. These are the only extra possibilities: the image of is an idempotent in , hence either zero or one, and image zero forces the whole map to vanish.
The inverse function theorem says that a continuously differentiable map on an open subset of whose derivative at a point is invertible has a continuously differentiable inverse between neighborhoods of that point and its image. The derivative of the inverse is the inverse derivative matrix.
For the given map the Jacobian matrix and its determinant are
Hence every point of the nonempty open set
has a local continuously differentiable inverse. At its image, the derivative of that inverse is
At the omitted points a differentiable inverse with differentiable composition cannot exist, since the chain rule would force the singular derivative to be invertible.
To locate the exceptions on the curve, substitute into its defining relation. This gives . The two exceptional points are therefore
At any other point of the curve, and the local inverse exists. Because the first coordinate of is , its inverse at has the form . The function is continuously differentiable for in a sufficiently small interval containing . Shrink an interval containing so that lies in the inverse neighborhood and . A point of the curve in that rectangle maps to , so injectivity forces it to be . Conversely all these inverse images belong to the curve. This proves the requested local graph description by the inverse function theorem, rather than merely asserting an implicit-function conclusion. Differentiating the relation also gives there.
The form of Rouché's theorem used here is as follows. Suppose and are holomorphic on a neighborhood of the closure of a bounded Jordan domain, and on its positively oriented boundary. Then and have the same number of zeros inside, counted with multiplicity.
To prove this form, put for . The strict inequality prevents from vanishing on the boundary. The argument principle counts its interior zeros by . This integral varies continuously with : the integrand is continuous and its denominator stays uniformly away from zero on the compact boundary times . Its values are integers, so the integral is constant. Its values at are the respective zero counts. This proves Rouché's theorem with the multiplicities and boundary hypotheses required below.
On , the perturbation has modulus . Thus Rouché's theorem gives three roots inside , counted with multiplicity.
For the quadrant information, compare instead with , whose roots are , , . Their pairwise distances are . On the circle ,
The three unit discs are disjoint, and Rouché localization of polynomial roots gives one root in each, counted with multiplicity. The disc around lies strictly in the first quadrant in its interior; that around lies in the fourth quadrant; and that around lies in . Consequently there is exactly one root in each of those two right-hand quadrants, and exactly one root in the left half-plane. The same count also shows that each root is simple.
At the left-hand root is , and the derivative of the polynomial with respect to is . The holomorphic implicit function theorem states that if is holomorphic near , and , there is a unique holomorphic function near , with and . It therefore supplies an analytic root branch near zero. Differentiate its equation:
It follows that and
For sufficiently small positive its imaginary part is . By the unique-root localization from the preceding part, this is the root in the left half-plane. Thus that root lies above the real axis for all sufficiently small positive .
With the Fourier transform convention of 5A, use the printed Fourier inversion formula directly. The possible choice of values at has no effect on the integral. Integration over the support gives
Combining the two fractions yields
In particular is imaginary-valued and odd, as expected from the real odd transformed function with this inverse-transform sign.
Take the Fourier transform in of the Laplace equation. Writing for the transformed solution gives . Its boundary values give
with the multiplier at understood as . The particular data simplify this to for , and zero outside. Thus, with , the Fourier solution of the strip Dirichlet problem is
The displayed closed expression applies in the open strip. The integral defines its continuous boundary values, including the removable point . It gives and . Differentiation under this finite integral verifies directly, since each integrand has opposite second derivatives in and .
The boundary conditions alone do not specify a unique solution without a growth restriction: adding preserves both boundary values and harmonicity. The constructed solution is bounded, and it is unique among bounded solutions continuous on the closed strip. To see this, apply the maximum principle for harmonic functions to a bounded real or imaginary component of the difference. For , the positive harmonic function has a positive minimum factor in . For any , the functions are nonpositive on the horizontal sides of a sufficiently wide rectangle and on its vertical sides, because is bounded and grows there. The maximum principle gives at every fixed point. Letting proves uniqueness in this natural Fourier solution class.
For the radial Helmholtz Dirichlet Green function, set . Multiplication of the radial equation by gives
The first endpoint follows from the required boundedness of at zero. For and , use the left solution and right solution . Their Wronskian is . Matching continuity and the derivative jump therefore gives, with and ,
This is finite at zero, vanishes at one, is continuous at , and has . Thus it has exactly the prescribed delta source, not its negative. Its weighted reciprocity is , as expected for the radial weight.
Integrating the Green function against the constant forcing gives
The integrals are respectively and . After cancellation their weighted sum is . Hence
The values at zero are interpreted by continuity. At the limit exists: and .
The exceptional nonzero values need a genuine qualification. There is then a nonzero bounded homogeneous solution satisfying both endpoint conditions, so an inverse Green function does not exist. Moreover the stated forcing is incompatible, not merely nonunique. If solved the problem, multiply by and integrate by parts using . The left side is zero, whereas
Thus there is no solution for nonzero . This explains exactly when the generic formula is applicable.
With metric signature , four-momentum is ; for a particle of rest mass it satisfies . For a massive particle , where is its four-velocity. The total four-momentum is the sum of the individual four-momenta. If that sum is timelike, its center-of-momentum frame exists and the total energy in that frame is
This follows because the spatial momentum is zero in that frame and the Minkowski norm is invariant under a Lorentz boost. A null total momentum, such as parallel photons, would not have such a rest frame.
For the photon striking an electron initially at rest, the initial invariant gives . The three final particles have total rest energy . Their center-of-momentum energy is at least this value, with equality when all have zero relative momentum. Energy-momentum conservation therefore requires
The photon-induced triplet pair-production threshold is consequently four electron rest-energy units. This is attainable as a kinematic threshold: at equality the center-of-momentum speed in the laboratory is , and boosting the three resting final particles gives each energy and momentum . Their totals are the initial and . Recoil of the original electron is why twice the rest energy is insufficient.
For steady incompressible flow of constant density without a body force, the Euler equation and mass conservation give
Apply the divergence theorem componentwise to a fluid volume. With its outward normal, the integral momentum flux balance is
If a solid bounds part of the volume, retain its pressure contribution; that contribution supplies the force on the fluid. This derivation includes pressure as well as transported momentum.
Choose the axis in the incoming jet direction. The printed diagram measures between that axis and the downstream sheet: it is the cone's half-angle. Along a streamline, the steady Euler equation integrates to the Bernoulli equation . At the incoming free jet and the outgoing free sheet the pressure is atmospheric. With gravity neglected, the outgoing speed is therefore . This argument uses far free surfaces; it does not assert atmospheric pressure on the wetted sphere.
At radial distance , the sheet's circumference is . Its cross-section normal to its velocity is this circumference times its small thickness . Conservation of mass gives , hence
For the axial momentum balance, transverse contributions cancel by axial symmetry. The outgoing axial momentum rate is and the incoming rate is . Uniform atmospheric pressure cancels on the closed control surface when expressed as gauge pressure. The sphere's force on the fluid is therefore in the axis direction. By action and reaction, the fluid force on the sphere is downstream, with magnitude
The downstream direction in the original diagram fixes this sign and the factor . If one calls the full cone opening its vertex angle, that full opening is ; using as the full opening would conflict with the printed thickness formula.
A Bayes estimator minimizes the integrated loss function under the prior and sampling distribution. For a nonnegative loss, Tonelli's theorem and the posterior distribution give the risk decomposition
where is the marginal density. Thus choosing, for each observed , a measurable minimizer of the posterior expected loss minimizes the integrated risk. Observations of marginal probability zero do not affect the rule.
Here the likelihood is and the prior is on positive parameters. Put . Their product is , and . The marginal density and posterior are therefore
This Gamma-exponential conjugacy calculation gives a Gamma distribution with shape and rate . It is the posterior, rather than the prior alone, which determines both requested estimators.
Under squared-error loss, the posterior expected loss decomposes as
It is uniquely minimized by the posterior mean. Integrating the Gamma posterior gives . Hence the Bayes estimator is
This relative absolute-error loss weights each parameter by . Its posterior expected loss is
The effective density for the Bayes estimator under weighted absolute loss is proportional to , hence an exponential distribution of rate . Its median solves .
More explicitly, for , differentiating the split integrals at gives and . For , the loss has derivative , so its minimum cannot lie there. The unique global minimum is therefore
This is the weighted posterior median; the ordinary median of the Gamma posterior would minimize unweighted absolute loss and would give a different answer.
Each coordinate lies in . Since , , with equality exactly when or . Summing gives . Equality under the simplex constraint forces exactly one coordinate to be one. Thus the minimum is , attained exactly at the vertices of the probability simplex.
For the maximum, is strictly concave on . The Jensen inequality gives
Strict concavity makes equality possible exactly when all coordinates agree. Hence the extrema of a concave power sum on a simplex are
For the simplex is a single point, and both descriptions coincide.

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