1. notice
  2. English
  3. logic-topic
  4. 1. logic
  5. 2. basic
  6. 3. map
  7. 4. order
  8. 5. combinatorics
  9. calculus
  10. 6. real-numbers
  11. 7. limit-sequence
  12. 8. division-algebra
  13. 9. Euclidean-space
  14. 10. Minkowski-space
  15. 11. polynomial
  16. 12. analytic-Euclidean
  17. 13. analytic-struct-operation
  18. 14. ordinary-differential-equation
  19. 15. volume
  20. 16. integral
  21. 17. divergence
  22. 18. limit-net
  23. 19. topology
  24. 20. compact
  25. 21. connected
  26. 22. topology-struct-operation
  27. 23. exponential
  28. 24. angle
  29. geometry
  30. 25. manifold
  31. 26. metric
  32. 27. metric-connection
  33. 28. geodesic-derivative
  34. 29. curvature-of-metric
  35. 30. Einstein-metric
  36. 31. constant-sectional-curvature
  37. 32. simple-symmetric-space
  38. 33. principal-bundle
  39. 34. group
  40. 35. stereographic-projection
  41. 36. Hopf-bundle
  42. field-theory
  43. 37. point-particle-non-relativity
  44. 38. point-particle-relativity
  45. 39. scalar-field
  46. 40. scalar-field-current
  47. 41. scalar-field-non-relativity
  48. 42. projective-lightcone
  49. 43. spacetime-momentum-spinor-representation
  50. 44. Lorentz-group
  51. 45. spinor-field
  52. 46. spinor-field-current
  53. 47. electromagnetic-field
  54. 48. Laplacian-of-tensor-field
  55. 49. Einstein-metric
  56. 50. interaction
  57. 51. harmonic-oscillator-quantization
  58. 52. spinor-field-misc
  59. 53. reference
  60. ไธญๆ–‡
  61. 54. notice
  62. ้€ป่พ‘
  63. 55. ้€ป่พ‘
  64. 56. ๅŸบ็ก€
  65. 57. ๆ˜ ๅฐ„
  66. 58. ๅบ
  67. 59. ็ป„ๅˆ
  68. ๅพฎ็งฏๅˆ†
  69. 60. ๅฎžๆ•ฐ
  70. 61. ๆ•ฐๅˆ—ๆž้™
  71. 62. ๅฏ้™คไปฃๆ•ฐ
  72. 63. Euclidean ็ฉบ้—ด
  73. 64. Minkowski ็ฉบ้—ด
  74. 65. ๅคš้กนๅผ
  75. 66. ่งฃๆž (Euclidean)
  76. 67. ่งฃๆž struct ็š„ๆ“ไฝœ
  77. 68. ๅธธๅพฎๅˆ†ๆ–น็จ‹
  78. 69. ไฝ“็งฏ
  79. 70. ็งฏๅˆ†
  80. 71. ๆ•ฃๅบฆ
  81. 72. ็ฝ‘ๆž้™
  82. 73. ๆ‹“ๆ‰‘
  83. 74. ็ดง่‡ด
  84. 75. ่ฟž้€š
  85. 76. ๆ‹“ๆ‰‘ struct ็š„ๆ“ไฝœ
  86. 77. ๆŒ‡ๆ•ฐๅ‡ฝๆ•ฐ
  87. 78. ่ง’ๅบฆ
  88. ๅ‡ ไฝ•
  89. 79. ๆตๅฝข
  90. 80. ๅบฆ่ง„
  91. 81. ๅบฆ่ง„็š„่”็ปœ
  92. 82. Levi-Civita ๅฏผๆ•ฐ
  93. 83. ๅบฆ่ง„็š„ๆ›ฒ็އ
  94. 84. Einstein ๅบฆ่ง„
  95. 85. ๅธธๆˆช้ขๆ›ฒ็އ
  96. 86. simple-symmetric-space
  97. 87. ไธปไธ›
  98. 88. ็พค
  99. 89. ็ƒๆžๆŠ•ๅฝฑ
  100. 90. Hopf ไธ›
  101. ๅœบ่ฎบ
  102. 91. ้ž็›ธๅฏน่ฎบ็‚น็ฒ’ๅญ
  103. 92. ็›ธๅฏน่ฎบ็‚น็ฒ’ๅญ
  104. 93. ็บฏ้‡ๅœบ
  105. 94. ็บฏ้‡ๅœบ็š„ๅฎˆๆ’ๆต
  106. 95. ้ž็›ธๅฏน่ฎบ็บฏ้‡ๅœบ
  107. 96. ๅ…‰้”ฅๅฐ„ๅฝฑ
  108. 97. ๆ—ถ็ฉบๅŠจ้‡็š„่‡ชๆ—‹่กจ็คบ
  109. 98. Lorentz ็พค
  110. 99. ๆ—‹้‡ๅœบ
  111. 100. ๆ—‹้‡ๅœบ็š„ๅฎˆๆ’ๆต
  112. 101. ็”ต็ฃๅœบ
  113. 102. ๅผ ้‡ๅœบ็š„ Laplacian
  114. 103. Einstein ๅบฆ่ง„
  115. 104. ็›ธไบ’ไฝœ็”จ
  116. 105. ่ฐๆŒฏๅญ้‡ๅญๅŒ–
  117. 106. ๆ—‹้‡ๅœบๆ‚้กน
  118. 107. ๅ‚่€ƒ

note-math

Using the alternation of tensor-induced-quadratic-form

Iterate over all , orthonormal basis with , obtaining signature

let . Prop span <==>

Abbreviation

[quadratic-form-inequality-Euclidean] Inner product inequality (Euclidean). . i.e. or

[triangle-inequality-Euclidean] Triangle inequality (Euclidean)

  • Proof

  • Proof

  • A more general inequality for should be . For simplicity, this more general assumption is not used for now

    For the norm

    The infimum of , or

    The supremum for , is

    Proof

    First compute an upper bound for , then prove it is the supremum

    Use differential techniques to prove for . Using to reduce to a single variable, prove

    Compute the maximum of . Due to homogeneity, scaling does not affect the result. Assume . Use differential method to compute the maximum of , which is .

    For each norm component of , let . use

    Sum these norm components

    let . use

    Using the embedding with to illustrate that the inequality can achieve equality , thus is the supremum.

    When , , which causes the usual triangle inequality to fail.

[Euclidean-space-topology] Euclidean topology. is continuous at :=

let

[closure] Closure :=

[closed-set] Closed set :=

(open) ball

[open-set] Open set :=

open <==> closed

[interval] Interval refers to a subset of with property that the order is uninterrupted

[best-interval-decomposition] Optimal interval decomposition of

Def as the set of all intervals, including open, closed, half-open half-closed, and single point

No need to restrict to only open intervals, as this is not defining a topology, nor does it need to generalize to higher dimensions

Def , i.e., the set of all intervals among the subsets of

Due to the existence of single-point intervals, and

has linear order chains. Taking of each maximal linear order chain yields an interval. The set of these intervals is denoted

and

The intervals in are pairwise disjoint, and the decomposition is unique, thus these intervals constitute the optimal interval decomposition of

  • When , is an interval, connected
  • When , is not connected. Example

If is a closed set, then the intervals in are all closed intervals

[bounded-closed-interval-is-compact] A bounded closed interval of ==> compact

Proof

Assume is a bounded closed interval, is a net of

Since is closed, the definition of is the same for the topologies of and

Since is bounded, we can define the non-empty infimum set and the supremum set

By the property of the net (or using the corresponding interval net ), it can be proved that numbers in are numbers in

has an upper bound, has a lower bound, so we can take the infimum/supremum, and it satisfies

Prop

Take , prove

Proof

Define

because

is a closed set, so

Therefore

That is,

Next, prove

For each , since is a net, there exists such that

Thus , so and

And , so

By the arbitrariness of the selection of , is an upper bound of , thus , i.e.,

Hence

Since , we have

By the arbitrariness of the selection of , we have

Thus

By the arbitrariness of the selection of , is compact

[compact-imply-subsequence-converge] compact ==> sequence has a convergent subsequence. Similarly for nets

Proof

forms a net

compact ==>

let

let and

use the definition of closure

We can inductively choose such that is a subsequence. Proof . Choose such that and

==>

  • The closed unit ball
  • The unit sphere

[circle-is-compact] compact

Proof is continuous

is continuously isomorphic to (quotient-topology) is continuously isomorphic to i.e. collapsing endpoints (quotient-topology)

is a bounded closed interval, hence compact ==> the quotient is compact. by quotient preserves compactness

[closed-ball-sphere-is-compact]

Proof

compact. Inductive hypothesis compact

  • compact

(Draw a picture) continuous. Isomorphism is obtained after quotienting the origin

compact. by product-topology-preserve-compact

compact

  • compact

Using polar coordinates to construct from , after quotient, obtain compact

Another method boundary collapses to a point to get compact

Proof

. Sphere corresponds to sphere , then corresponds to radius

Stereographic projection

The composite map plus the map to yields a map that remains continuous; after quotienting , it becomes a bijection,

Projective space (Euclidean) compact. Proof

Similarly (and ) compact

[Euclidean-set-distance]

  • [bounded] bounded :=
  • [unbounded] unbounded :=

is invariant

The point at infinity is translation-invariant

by stereographic projection

in Euclidean topology of

  • bounded <==> away from <==>
  • unbounded <==>

[Euclidean-space-compact-iff-bounded-closed] compact <==> is bounded and closed

Proof

  • <==

bounded closed set corresponds to a closed set in that does not include

compact + closed-set-in-compact-space-is-compact ==> is compact in

topology restricted back to subspace topology

obtain compact

  • ==>
  • closed set

let

forms a net of . Note that possibly

  • compact ==>

==>

i.e. closed

  • bounded
open ball is away from . The family of open balls covers . Take finite cover, finite union remains away from , thus is also away from , i.e., is bounded

[nested-closed-set-theorem] The intersection of a nested sequence of bounded closed sets in is nonempty. Its intersection is also a closed set, which can be understood as the minimal element of the โІ linearly ordered chain of nested closed sets

[closed-net-theorem] The intersection of a net of bounded closed sets in is nonempty Proof

Map closed set to closed set, is compact, so the intersection of a nested sequence or a net of closed sets is nonempty. The intersection is smaller than any bounded closed set, thus also away from , hence the intersection lies in

let be net of

[limit-distance-vanish-net] :=

or

The tail of a net is bounded

Sequences can form a net

[Cauchy-completeness-Euclidean]

in , a net with vanishing limit-distance converges to a point

bounded closed set = compact ==> let

limit-distance-vanish ==>

Some infinite-dimensional linear spaces e.g. Lebesgue-integrable , bounded closed sets do not imply compact, but still satisfy that a net with vanishing limit-distance converges to a point, due to the completeness of

By induction, finite summation is associative and commutative. But this does not guarantee it holds for infinite summation i.e.

let

  • converges to
  • Rearrangement

then may not converge or converge to another value

compare

Convergence (not ==>) absolute convergence

let be a sequence

  • converges ==>

    Proof

    ==> by the triangle inequality

  • ==> does not converge

Any sequence can define such that

Rearrangement does not change the tail behavior of the sequence

Prop If , is invariant under rearrangement

Proof

==>

==> (by )

==>

def

[series-rearrangement-absolutely-convergence-real] Prop Absolute convergence ==> converges and is invariant under rearrangement

Proof and use the arithmetic operations of convergent sequences

and ==> and invariant under rearrangement

Question The case of norm reduces to ?

Harmonic series vs , say that, convergence is closer to normal convergence.

Final possibilities

[series-rearrangement-real]

let and

Prop

  • Converges to
  • Does not converge to

Example

Proof

  • Converges to

. Meaning: is the smallest natural number such that the sum of positives exceeds

. Meaning: is the smallest natural number such that the negative sum is less than

And so on, exhausting all

Rearrange as

By the definition of

By the definition of

And so on

==>

  • Converges to

In the treatment of

Change to

Change to

  • Does not converge to

Change to

Change to

Similarly for

Prop A series in that is rearrangement invariant is also absolutely convergent

Prop converges ==>

[series-rearrangement-absolutely-convergence]

let be a sequence

==> converges and is rearrangement invariant

Proof

  • converges. By using the triangle inequality and the Cauchy sequence convergence in

  • Rearrangement invariant

Now consider the case where is not absolutely convergent

def

By the triangle inequality or the equivalence of -norm, -norm, -norm in

  • is a linear subspace

let . The component of converges absolutely

Consider the component of

[series-rearrangement]

let

  • and ==> converges to in the component, rearrangement invariant
  • . is rearrangement unstable in the component

The positive linear combination with of sequences with the same convergence pattern preserves their convergence pattern