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Polynomial approximation and Chebyshev interpolation
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Approximation and Compactness in C(K)
- Binary Operations, Monoids, Groups and Subgroups
- Compactness
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Countability and Uncountability
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Fundamental Trigonometric Identities
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Metric Spaces
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Order, Zorn's Lemma, and the Axiom of Choice
- Polynomial interpolation and remainder
- Power Series and Real-Analytic Functions
- Properties of the Integral and the Working FTC
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sine, Cosine, and the Definition of Pi
- Subspaces, Products, and Quotients
- Suprema and Infima
- The Derivative and the Mean Value Theorems
- The Exponential Function
- The Logarithm and General Powers
- The Riemann Integral: Definition and Integrability
- The Topology of Euclidean Space
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
For , is the best degree- uniform error. The first-kind root and Chebyshev–Lobatto interpolation operators use their specified angular nodes, with the one-node case stated separately. Their Lebesgue constants are bounded by for , and their interpolation errors are at most .
The logarithmic estimate is proved from the trigonometric cardinal formulas, nearest-node separation, and a harmonic sum. Weierstrass density proves only ; interpolation convergence requires a rate strong enough to control the logarithmic factor. Barycentric evaluation and finite-precision conditioning are separate topics. No stability claim for rounded evaluations is made here.
3 · Logical flowchart
4 · Definitions, theorems and proofs
Best uniform polynomial error and Chebyshev interpolation operators
Definition
Let be the real continuous functions on , with . Let be the restrictions to of real polynomials of degree at most , including the zero polynomial. Interval notation is that of Intervals of : the nine order-convex forms, nondegeneracy, and length. Continuity and polynomial degree have the conventions of Continuity of at a point of and on : the - condition, its agreement with at a limit point, and continuity at an isolated point and Formal real polynomials, evaluation, degree, leading coefficient, and monic polynomials.
For each (with naturals in real expressions interpreted by their canonical real images), the first-kind Chebyshev root angles and nodes are They are the roots of by and for every . For , the Chebyshev–Lobatto angles and nodes are They include both endpoints and are the extrema of by the same identity. At , define the Lobatto node to be . The cosine is strictly decreasing on , so each listed family has distinct nodes; the root family at also consists of .
For either family , write its nodes as and define These are the cardinal formula and interpolation sum of Cardinal-polynomial interpolation specialized to this node family. The displayed cosine arrays decrease, whereas that supplier orders nodes increasingly: use and data . Its cardinal function with index is exactly the displayed , by reindexing the finite product, and its interpolation sum is . The empty product at is , so the same identification holds for the single node. Distinctness makes every denominator nonzero; Cardinal interpolation functions are polynomials of the stated degrees supplies the degree and cardinal values. The finite sum is linear in the data and maps into . Its operator norm is If , then for ; hence whenever . Define the best degree- uniform approximation error by
These quantities are real and well-defined. Polynomial functions are continuous, and sums and scalar multiples of continuous functions remain continuous by Sums, scalar multiples, products, absolute values, maxima, minima and quotients with nonvanishing denominator of continuous functions are continuous, as are constants, the identity and every polynomial function. The interval is nonempty, closed, and bounded, so For a nonempty subset of with , compactness, closedness and boundedness, pseudocompactness, and attainment of extrema by every continuous real-valued function are equivalent implies that for every such continuous function there are finite minimum and maximum values . Since , one has , so each supremum norm above is finite. The set defining contains the zero function and is bounded above by the displayed finite coefficient sum. The set defining contains the zero polynomial and is bounded below by zero. Completeness of (Complete ordered field (least-upper-bound property)) therefore gives the stated finite supremum and infimum. Also, has positive real image by The canonical natural of a field and Canonical naturals are positive and strictly increasing, and has positive real image when ; thus the root-angle denominator and the Lobatto denominator in its stated range are nonzero.
The displayed root-family nodes are all the real roots of . The degree statement Degrees and leading coefficients of the Chebyshev polynomials gives , and A nonzero real polynomial of degree has no more than distinct real roots excludes any additional real root beyond the distinct nodes above.
Sine chord and Lipschitz bounds
Statement
For , For all real ,
Facts & Assumptions
Given: Real , with for the first inequality.
Sums, scalar multiples, products and quotients: , , , and when : products and quotients of differentiable functions obey the product and quotient rules wherever the denominator is nonzero.
The mean value theorem, as the case of Cauchy's: for continuous on with and differentiable on there is with : a function continuous on a closed interval and differentiable on its interior has a point where its endpoint increment equals its derivative times the interval length.
For a natural the function is differentiable everywhere with derivative ; for it is the constant , with derivative ; for a natural the function is differentiable at every with derivative ; consequently every polynomial function is differentiable at every real, with the derivative computed term by term and A function differentiable at is continuous at : the identity function has derivative , and every differentiable real function is continuous at each point where it is differentiable.
Proof
Define . By [F1], [F2], and [F5], is differentiable and hence continuous, with on by [F4]. For , the mean value theorem on gives ; at equality is immediate.
For , define . By the quotient rule, the identity derivative in [F5], and step 1.1, . The function is continuous on by [F5], so the mean value theorem gives by [F3] and [F4]; at equality holds. Multiplying by and checking proves the first inequality.
If , sine is continuous on the closed interval between them and differentiable inside by [F1] and [F5]. The mean value theorem gives for some interior , by [F3] and [F4]. If , both sides are zero.
Chebyshev cardinal interpolation reproduces polynomials and its norm is the cardinal sum
Statement
For either Chebyshev node family and every , the cardinal polynomials in Best uniform polynomial error and Chebyshev interpolation operators satisfy when and otherwise. They are the unique degree-at-most- polynomials with those cardinal values. Consequently for every . Moreover,
Facts & Assumptions
Given: An integer , one of the two node families, and .
Best uniform polynomial error and Chebyshev interpolation operators: the node families are distinct, , , and .
Existence and uniqueness of the cardinal-polynomial interpolant: at increasingly ordered distinct real nodes, the supplied cardinal sum is the unique real polynomial of degree at most interpolating its prescribed data, including .
Cardinal interpolation functions are polynomials of the stated degrees: the supplied cardinal functions are degree- polynomials with Kronecker node values, and their data sum is a polynomial of degree at most .
Proof
Put , so by [F1]. Under this reverse indexing, the supplier cardinal function at index is by the specialization in [F1]. Applying [F3] gives its degree and cardinal values, including the one-node empty-product case .
Put . For every with , the defining sum gives , hence .
Prescribe data at and otherwise on the increasingly ordered nodes from step 1.1. The polynomial has these data by step 1.1. The supplier uniqueness theorem [F2] makes it the unique degree-at-most- polynomial with the required cardinal values.
Prescribe on the ordered nodes in step 1.1. By [F1] and [F3], their cardinal sum is and has degree at most . The polynomial itself interpolates those data, so the supplier uniqueness theorem [F2] gives .
Fix . Define for , for , and for , and prescribe at each node. These values lie in and satisfy by cases. Sort nodes increasingly, interpolate these values linearly, and extend constantly to the interval endpoints; each interpolated value is a convex combination of endpoint values, so the resulting continuous has norm at most . The cardinal sum gives , so . Taking the supremum in and using step 1.2 proves equality. For the same construction is constant on the interval.
Best polynomial errors vanish for continuous functions
Statement
For every , as . This statement concerns best polynomial errors only; it does not assert convergence of interpolation at arbitrary node arrays.
Facts & Assumptions
Given: and .
Polynomials are uniformly dense in for every closed interval: every continuous real function on a closed interval is uniformly approximable by polynomials.
Proof
By [F1], choose a polynomial and an integer with such that ; if , take .
For every , , so [F2] gives . Since was arbitrary, . This conclusion concerns alone; it does not show that .
Trigonometric formulas for Chebyshev cardinal polynomials
Statement
Let , , and choose so . Then For the Lobatto family, put for and otherwise. If , then
Facts & Assumptions
Given: , , and one of the node families.
Best uniform polynomial error and Chebyshev interpolation operators defines the nodes and cardinal polynomials.
Chebyshev cardinal interpolation reproduces polynomials and its norm is the cardinal sum: these nodes are distinct and their cardinal polynomials are the unique degree-at-most- polynomials with the cardinal values.
and for every : and .
Chebyshev polynomials of the first and second kinds by their three-term recurrences and Degrees and leading coefficients of the Chebyshev polynomials: and have degree for ; has degree .
The chain rule, in one line from Carathéodory: if is differentiable at and is differentiable at , then is differentiable at with , The derivatives of sine and cosine are cosine and minus sine, Sums, scalar multiples, products and quotients: , , , and when , and For a natural the function is differentiable everywhere with derivative ; for it is the constant , with derivative ; for a natural the function is differentiable at every with derivative ; consequently every polynomial function is differentiable at every real, with the derivative computed term by term: polynomial functions and sine/cosine are differentiable, and the chain and product rules compute their derivatives.
A real polynomial vanishing at is divisible by : a polynomial that vanishes at factors as .
Proof
Put and . By [F3], . Differentiating using [F4]–[F5] gives , hence by [F7].
Set . By [F3], , so it vanishes at every Lobatto node; its degree is by [F4]. For an interior node , differentiating this identity gives , hence by [F7].
Differentiating at gives and by [F7]. The product rule then gives and , so at every Lobatto node .
By [F6], is a polynomial. Writing and differentiating gives ; at every other node vanishes. Therefore is a degree-at-most- cardinal polynomial, which equals by uniqueness [F2]. Substitution of and [F3] gives the first formula.
By [F6], write with a polynomial. Differentiating this factorization gives ; at every other Lobatto node vanishes because does. Thus is a degree-at-most- cardinal polynomial, hence by [F2]. Substitution of and gives the second formula.
Chebyshev interpolation error is controlled by best polynomial error
Statement
For either Chebyshev node family, every , and every , Here is the best degree- uniform error and is the operator norm defined in Best uniform polynomial error and Chebyshev interpolation operators.
Facts & Assumptions
Given: , , and .
Best uniform polynomial error and Chebyshev interpolation operators defines , , and .
Proof
Fix and put . By [F2], , so . If , then and the asserted bound follows; otherwise lies in with , so the definition in [F1] gives . Pointwise, , so taking suprema gives .
Step 1.1 holds for every . The unit ball in [F1] contains the zero function and each norm is nonnegative, so and . Taking the infimum of the right-hand side over the nonempty set therefore gives , proving the claim.
Chebyshev-root and Lobatto interpolation norms have logarithmic upper bounds
Statement
For , let be the operator norm of interpolation at the roots of , and let be the operator norm at the Chebyshev–Lobatto nodes. With the conventions in Best uniform polynomial error and Chebyshev interpolation operators, Here is the natural logarithm of The natural logarithm as the inverse of the exponential function. For , both one-node operators have norm ; the logarithmic estimate is stated for .
Facts & Assumptions
Given: An integer , , and either angular node family.
Best uniform polynomial error and Chebyshev interpolation operators defines , , and the equally spaced root and Lobatto angles.
Trigonometric formulas for Chebyshev cardinal polynomials: for roots, ; for Lobatto nodes, , with .
Sine chord and Lipschitz bounds: for , and for all real .
The addition formulas for sine and cosine, The subtraction formulas for sine and cosine, Signs, monotonicity intervals, and ranges of sine and cosine, and Quarter-turn values and shifts by pi/2 and pi: the addition/subtraction formulas give and ; on , sine is nonnegative, increasing up to , and satisfies , while for every real .
The natural logarithm as the inverse of the exponential function: is the natural logarithm; The canonical natural of a field and Canonical naturals are positive and strictly increasing: natural indices in real expressions use their canonical images, and positive natural indices have positive real image.
Cosine is continuous on by The derivatives of sine and cosine are cosine and minus sine and A function differentiable at is continuous at . Its endpoint values are and by Quarter-turn values and shifts by pi/2 and pi, and by Pi as twice the smallest positive zero of cosine. The intermediate value theorem Intermediate value theorem, by bisection with a canonical left-half rule: a continuous function on takes every value between and therefore shows that every value in is for some . Conversely, cosine has range by Signs, monotonicity intervals, and ranges of sine and cosine, so .
Proof
In either angular grid the spacing is for roots and for Lobatto nodes. Choose a nearest grid angle and put . Then ; if , the triangle inequality gives . At most two indices occur for each .
For , put and . Since the two angles lie in , . The addition/subtraction formulas in [F5] give ; the monotonicity and supplementary identity in [F5] then give , so each numerator is at most . Those same formulas give , and [F4] gives . Thus both ratios and are at most .
For roots, [F3] and step 2.1 give . At the nearest node , , and the cosine addition formula plus [F4] gives , so its term is at most . For other nodes use and step 1.1; summing over at most two nodes per distance rank yields . At a node the cardinal sum is .
For Lobatto nodes, [F3] and step 2.1 give . At the nearest node , , so [F4] gives and its term is at most because . For other nodes use and step 1.1; summing over at most two nodes per distance rank yields . At a node the cardinal sum is .
Since , the shifted sum is at most , where . For , , so [F6] gives . Positivity of the real image of is [F7], so these logarithms are defined. The integral formula also gives and by integrating over , , and . Since and , we have and . Thus both sums are at most . By [F8], the angular supremum is over exactly ; taking it and using [F2] proves both bounds. At , each one-node operator has norm directly.
5 · Examples, counterexamples and false statements
None yet.
Sources
- Lloyd N. Trefethen, Approximation Theory and Approximation Practice, Chs. 2–5
- Tobin A. Driscoll and Richard J. Braun, Fundamentals of Numerical Computation, Polynomial interpolation
- Lloyd N. Trefethen, Approximation Theory and Approximation Practice, Ch. 3
- Tobin A. Driscoll and Richard J. Braun, Fundamentals of Numerical Computation, Problems and conditioning
- Lloyd N. Trefethen, Approximation Theory and Approximation Practice, Ch. 5
- Lloyd N. Trefethen, Approximation Theory and Approximation Practice, Ch. 6
- Lloyd N. Trefethen, Approximation Theory and Approximation Practice, Chs. 2–6
- Tobin A. Driscoll and Richard J. Braun, Fundamentals of Numerical Computation, Polynomial interpolation and conditioning