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

note-math

Natural number addition

is counting times , is counting times first, then counting times

  • Associative law:
  • Commutative law:

Proof The intuition in the real world is that for counting , no matter how the counting task is manually divided into several subtasks, the result will not be affected, and the total decomposition methods are limited. The associative and commutative laws of addition are just special cases. Just as we recognize natural numbers by counting, we can always recognize the commutative and associative laws by counting. Everything reduces to the case of complete additive decomposition, with only the commutative and associative laws of a large number of s.

There are two definitions of addition, or . By swapping the inputs (midway) in one definition of addition, we can get the other definition of addition. Proving the commutativity of addition means proving that the two definitions give the same output for the same inputs. Intuitively, the result is of course the same, it's just that the amount to be counted is placed in a different "slot position", thus "commutative"

Alternatively, for a function of counting in two positions, if one position is counted first and then used as the "base position," and the other position is counted again and used as the "incrementing position," the result is the "total count" . The commutative property states that swapping the two positions still yields the same resultโ€”the "total count."

Natural number multiplication

is counting times of counting times

It also satisfies the commutative and associative laws. The intuition in the real world is "two-dimensional and three-dimensional rectangles". For counting , no matter how it is decomposed into subtasks of product decomposition, it will not affect the result. Therefore, the commutative and associative laws of multiplication are just special cases of complete multiplication decomposition i.e. prime factorization, and the total number of decompositions is limited

Distributive law of natural number operations

The intuition is to decompose the side length of a two-dimensional rectangle into sum

Integer

The number axis has two directions

Rational number

equal division operation, the inverse of multiplication

Do not confuse it with the division and remainder of , which is a successive subtraction of a number by another number , rather than equal division

Real number

One intuition of real numbers is length. Or contain rational number + linear order + order completeness

Given the intuitiveness of real numbers, we can assume that it exists and use many axioms to define real numbers i.e. assume a true proposition. But you can also "recover" real numbers from rational numbers

Examples of irrational numbers

Algebraic integer

The "integer" in algebraic integer is because

Proof (p.43 of ref-8)

Take and make them relatively prime. Substitute into the equation, multiply by

The right side is divisible by . But are relatively prime, so or .

So . Thus

Special case . But and

So that is is not a rational number

Algebraic number

Note that is not required, is not restricted, including all rational numbers , some irrational numbers e.g.

Algebraic number is a countable set, real number is an uncountable set

Transcendental number . are transcendental numbers

Decimal, binary vs nested interval vs segmentation

Decimal (nested interval) seems very intuitive

However, decimal cannot natively handle

Many different nested intervals of have the same limit, e.g. vs , which requires a limit-distance-vanish quotient.

let . let and , define the limit-distance-vanish equivalence relation (alias Cauchy convergence) for :=

The nested rational intervals of can be changed to general rational intervals whose length limit approaches zero linear order chain or more general rational intervals (maximal) whose length approaches zero net.

A rational interval is a subset with the property that the order is uninterrupted.

From an operational simplicity perspective, Dedekind-cut should be used. "Operational simplicity" means

  • let , one-to-one correspondence
  • So and one-to-one correspondence

[Dedekind-cut] irrational number

one-to-one corresponds to

. Record as again

Real number

Logically, we can use only half, for example, any left semi-infinite interval of the rational numbers , and then automatically get the right semi-infinite interval by doing the complement in . But here we use the more symmetrical representation

  • [order-real] order

let

  • [add-real] addition. let

Because of the existence of , multiplication does not preserve order. But the multiplication of preserves order. First deal with the case of , and then use reflection to get the case of

  • [multiply-real] multiplication. let

's all have associativity, commutativity, and distributivity

In fact, for multiplication and its theorems, a possible more convenient approach than using Dedekind partitioning and linear ordering might be to use the limit of a rational interval net (net lies between partial and linear order).

[completeness-real] completeness

[exact-bound] Least-upper-bound property

let have an upper bound

Supremum

[monotone-convergence] monotone bound convergence Proof use exact-bound

[nested-closed-interval-theorem] Nested interval theorem

Whether it is nested intervals or linearly ordered chain nested intervals, linear order means the monotonicity of interval endpoints, use supremum to set of lower end point, and use infimum to set of upper end point, then get , and get that the intersection of nested closed intervals is a closed interval . can be understood as the minimal element of linear order chain nested closed sets

[closed-interval-intersection-theorem]

In fact, we only need to ensure that the smaller endpoints of closed intervals are all less than or equal to the larger endpoints to obtain a non-empty intersection.

Proof Similarly, applying the supremum to the smaller endpoints and the infimum to the larger endpoints, we obtain that with , the intersection of the family of closed intervals is a closed interval .

[closed-interval-net-theorem] Closed interval net intersection is non-empty

Proof

Closed interval net ==> The smaller endpoints of closed intervals are all the larger endpoints

The reverse statement, "the smaller endpoints of closed intervals are all the larger endpoints ==> closed interval net" does not hold. Consider a family of closed intervals consisting of only two intervals with a non-empty intersection and ; there is no third interval in their intersection. Although after adding finite intersection, it's true

let

def sequence monotone decreasing, monotone increasing

[limsup] Upper limit

[liminf] Lower limit

Example

For the sequence, define

For a general net, define

[limit-distance-vanish-sequence] := i.e. tail distance vanish

[limit-distance-vanish-net] :=

[Cauchy-completeness-real] limit-distance-vanish sequence or net converges

Proof

limit-distance-vanish ==>

let , then

==> The limit-distance-vanish sequence is bounded

==> The monotonically increasing or decreasing bounded sequences have limits

limit-distance-vanish property ==>

Thus converges to

For nets, by the upper and lower bounds of closed interval net. Using limit-distance-vanish-net, we obtain that the net converges

Conversely, a convergent sequence is limit-distance-vanish. by the triangle inequality

Sequence or net converges to <==> limit-distance-vanish

[uncountable-real] The real number is uncountable

It has been proved that . cf. cardinal-increase

recall

Proof

According to the nested interval theorem, the binary decimal point representation of real numbers: The -th digit takes or

==> . Where, quotient the possible two equivalent choices in binary

by linear map or affine map

by

Proof

It represents in binary, the first position where appears is , the second position is โ€ฆ

Compare , vs

Distance