3. Asymptotic Expansions Flashcards

1
Q

Function in terms of General Truncated Sum

A

f(ε) = Sn(ε) + Rn(ε)
-where:
Sn = Σ an*ε^n
-sum from n=0 to n=N
-here Sn is a partial sum involving expansion coefficients a0,a1,…,aN and Rn(ε) is a remainder term
-note that this is an exact expression for f(ε) so if Sn starts to diverge then Rn must diverge (in the opposite direction) so that the equality holds

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2
Q

Convergent Series

Definition

A
-convergence asks about the expression:
f(ε) = Sn(ε) + Rn(ε)
-as N->∞ at fixed ε we say that Sn->f if:
lim Rn(ε) = 0 at fixed ε
-limit as N->∞
-then:
f(ε) = Σ an*ε^n
-sum from n=0 to n=∞
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3
Q

Factorial vs Power Growth

A

-factorial growth always beats power growth

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4
Q

Asymptotic Series

Definition

A

-we can also ask what happens if Rn decreases rapidly to 0 as ε->0
-in particular, we demand:
|Rn| &laquo_space;ε^N as ε->0
<=>
lim |Rn|/ε^n -> 0 as ε->0
-limit as ε->0
-since the final term of Sn is aNε^N this means that the remainder will be much smaller than Sn as ε->0
-if this limit applies for all N, then:
f(ε) ~ Σ an
ε^n as ε->0
-sum from n=0 to n=∞
-we call this the asymptotic expansion of f (as ε-> 0)

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5
Q

Asymptotic vs. Convergent Series

A

-in practice the conditions for asymptotic and convergent series mean very different things for approximating f(ε)

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6
Q

Convergent Series

Tolerance

A

-given a tolerance δ, a convergent series can achieve this tolerance with sufficiently large N, for some range of ε, i.e. |R| < radius of convergence

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7
Q

Asymptotic Series

Tolerance

A

-for tolerance δ, an asymptotic series when truncated to any N can meet the tolerance but only for sufficiently small ε

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8
Q

Evaluating Asymptotic Series

A
  • for divergent series, there comes a point where adding more terms to the sequence makes the estimate worse and not better
  • and even if a series is convergent, simply summing many terms form the infinite series may note be efficient, especially if convergence is slow
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9
Q

Severe Truncation

A

-just take the first few terms of a series to make an estimate, e.g.
S1 = a0 + a1ε
S2 = a0 + a1
ε + a2*ε²
-provided the series is asymptotic, Rn &laquo_space;ε^n as ε->0, so |R1|<

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10
Q

Optimal Truncation

A
  • here we seek the specific value of N=N* where the terms of the series are minimised in magnitude, i.e. minimise aN*ε^N
  • for a divergent series, as a good working rule N* is found by taking N* to be the point where the terms of the series stop decreasing, i.e. when |aN*ε^N| is minimised
  • for a convergent series there may well never be such a point since the terms typically keep decreasing
  • this value, N*, depends on the chosen value of ε
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11
Q

Pade Approximant

Outline

A

-a superior technique for accelerating the convergence of a series given only its first few terms
-the idea is to rewrite the asymptotic expression:
f(ε) ~ Σ ak*ε^k
-sum from k=0 to k=∞
-as a rational function in which the numerator and denominator are polynomials of degree M and N respectively

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12
Q

Pade Approximant

Equation

A

-the [M/N] Pade approximant of f(ε):
PM/N = Σnkε^k / Σdkε^k
= [n0+n1ε+n2ε²+…+nMε^M] / [d0+d1ε+d2ε²+…+dNε^N]
-without loss of generality we can set d0=1 with M+N+1 remaining unknown constants

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13
Q

Pade Approximant

Determining Coefficients

A
  • the M+N+1 unknown constants are determined from the first M+N+1 coefficients in the asymptotic expansion for f(ε)
  • specifically, we require that the Pade approximant is the same as f(ε) ~ Σ ak*ε^k for the first M+N+1 terms (i.e. up to and including O(ε^M+N)
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14
Q

The Shanks Transform

Outline

A
  • we consider a series f(ε) ~ Σ akε^k (sum k=0 to k=∞) along with its partial sums SN(ε)=Σ akε^k (sum k=0 to k=N)
  • the Shanks transform is a technique for estimating f(ε) given a sequence of three consecutive partial sums
  • can be used on a divergent series or to accelerate convergence of a convergent series
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15
Q

The Shanks Transform

Equation

A

-given a sequence of three consecutive partial sums SN-1, SN, SN+1
-the prediction for f(ε) is:
σ(SN) = [SN-1*SN+1 - SN²] / [SN-1 + SN+1 - 2SN]

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16
Q

The Shanks Transform

Reapplication

A

-if the Shanks transform is applied three times to produce σ(SN-1), σ(SN), σ(SN+1), the Shanks transform can then be reapplied on these values:

σ(σ(SN)) = [σ(SN-1)*σ(SN+1) - σ(SN)²] / [σ(SN-1) + σ(SN+1) - 2σ(SN)]

17
Q

The Shanks Transform

Basis

A

-the basis for the Shanks transform is to suppose that the partial sums are in a geometric progression:
SN-1 = b + cr^(N-1)
SN = b + c
r^N
SN-1 = b + r^(N-1)
-we can then eliminate c and r to find b:
b = [SN-1
SN+1 - SN²] / [SN-1 + SN+1 - 2SN]

18
Q

The Shanks Transform

ε

A

-we can also use the Shanks transform with general ε
e.g.
f(ε) = 1 + ε + ε² + …
=>
S0 = 1
S1 = 1+ε
S2 = 1+ε+ε²
-then sub these into the Shanks transform equation

19
Q

General Asymptotic Expansion

Form

A
f(ε) = Σ an δn(ε) + RN(ε)
-sum from n=0 to n=N
-where {δn(ε)} is an asymptotic sequence of functions with:
δ0(ε) >> δ1(ε) >> δ2(ε) >> ...
-as ε->0
-more precisely:
lim δn+1(ε)/δn(ε) = 0 
-limit as ε->0 for all n≥0
20
Q

General Asymptotic Expansion

Asymptotic Expansion

A
-if, for all N:
lim RN/δN(ε) = 0
-limit as ε->0
-i.e. RN(ε) << δN(ε)
-we say that f(ε) has an asymptotic expansion, write:
f(ε) ~ Σ an δn(ε) as ε->0
21
Q

o Notation

A

-if lim f(ε)/g(ε) = 0
-limit as ε->0
-then we say that:
f(ε) = o(g(ε)) as ε->0
-i.e. f(ε) &laquo_space;g(ε)
-can actually be any limit, doesn’t have to be ε->0

22
Q

Os Notation

A

-if lim f(ε)/g(ε) = C for C∈R{0}
-limit taken as ε->0
-if C is finite and non-zero we can write:
f(ε) = Os(g(ε)) as ε->0
-and we say that f(ε) is strictly of order g(ε) as ε->0
-can actually be any limit, doesn’t have to be ε->0

23
Q

O Notation

A

-if lim f(ε)/g(ε) = C for C∈R then:
f(ε) = O(g(ε)) as ε->0
-f(ε) is no larger than g(ε)
-can actually be any limit, doesn’t have to be ε->0

24
Q

Expansion Coefficients

Formula for aN

A

aN = lim [f(ε) - Σan*δn(ε)]/δN(ε)

  • for N≥1
  • limit as ε->0 and sum from n=0 to n=N-1
25
Q

Expansion Coefficients

Generating δn(ε)

A
  • the formula for aN can also be used to generate δn(ε)
  • sub into the formula as normal leaving δN(ε) as a general expression
  • test possible function for δN(ε) searching for a function which gives a finite, non-zero limit
26
Q

Uniqueness of Asymptotic Expansions

A
  • for a given function has different asymptotic expansions in terms of different asymptotic sequences {δn(ε)} and {δn^(ε)}
  • for a given sequence {δn(ε)}, f(ε) has a unique asymptotic expansion
  • for a given sequence {δn(ε)}, different functions may have the same asymptotic expansion
27
Q

Exponentially/Transcendentally Small Terms and Uniqueness of Asymptotic Expansions

A

-any two functions which differ by an exponentially small term, e.g. e^(-1/ε²), have the same asymptotic expansion in δn(ε)=ε^n

28
Q

Operations on Asymptotic Expansions

Addition / Subtraction / Multiplication / Division

A

-asymptotic expansions can be added, subtracted multiplied and divided in the obvious way

29
Q

Operations on Asymptotic Expansions

Integration

A

-asymptotic expansions can also be integrated term by term, although you may need to be careful with terms in logε or inverse powers of ε as ε->0

30
Q

Operations on Asymptotic Expansions

Differentiation

A

-asymptotic expansions cannot IN GENERAL be differentiated term by term

31
Q

Uniform Asymptotic Expansion

Definition

A

-consider f(x;ε) where ε«1 with {δn(ε)}:
f(x;ε) ~ Σ an(x) δn(ε), ε->0
-we then need an+1(x)δn+1(ε) &laquo_space;an(x)δn(ε) as ε->0 to have an asymptotic expansion
-if the above holds for all x for which f is defined then the expansion is a uniform asymptotic expansion

32
Q

Non-Uniform Asymptotic Expansion

Definition

A

ε«1 with {δn(ε)}:
f(x;ε) ~ Σ an(x) δn(ε), ε->0
-we then need an+1(x)δn+1(ε) &laquo_space;an(x)δn(ε) as ε->0 to have an asymptotic expansion
-if the inequality does not hold then the expansion is non-uniform