P. 291 of Theorem List - Metamath Proof Explorer

Type

Label

Description

Statement

Theorem

axlowdimlem4 29001

Lemma for axlowdim 29017. Set up a particular constant function. (Contributed by Scott Fenton, 17-Apr-2013.)

⊢ 𝐴 ∈ ℝ    &   ⊢ 𝐵 ∈ ℝ    ⇒   ⊢ {⟨1, 𝐴⟩, ⟨2, 𝐵⟩}:(1...2)⟶ℝ

Theorem

axlowdimlem5 29002

Lemma for axlowdim 29017. Show that a particular union is a point in Euclidean space. (Contributed by Scott Fenton, 29-Jun-2013.)

⊢ 𝐴 ∈ ℝ    &   ⊢ 𝐵 ∈ ℝ    ⇒   ⊢ (𝑁 ∈ (ℤ_≥‘2) → ({⟨1, 𝐴⟩, ⟨2, 𝐵⟩} ∪ ((3...𝑁) × {0})) ∈ (𝔼‘𝑁))

Theorem

axlowdimlem6 29003

Lemma for axlowdim 29017. Show that three points are non-colinear. (Contributed by Scott Fenton, 29-Jun-2013.)

⊢ 𝐴 = ({⟨1, 0⟩, ⟨2, 0⟩} ∪ ((3...𝑁) × {0}))    &   ⊢ 𝐵 = ({⟨1, 1⟩, ⟨2, 0⟩} ∪ ((3...𝑁) × {0}))    &   ⊢ 𝐶 = ({⟨1, 0⟩, ⟨2, 1⟩} ∪ ((3...𝑁) × {0}))    ⇒   ⊢ (𝑁 ∈ (ℤ_≥‘2) → ¬ (𝐴 Btwn ⟨𝐵, 𝐶⟩ ∨ 𝐵 Btwn ⟨𝐶, 𝐴⟩ ∨ 𝐶 Btwn ⟨𝐴, 𝐵⟩))

Theorem

axlowdimlem7 29004

Lemma for axlowdim 29017. Set up a point in Euclidean space. (Contributed by Scott Fenton, 29-Jun-2013.)

⊢ 𝑃 = ({⟨3, -1⟩} ∪ (((1...𝑁) ∖ {3}) × {0}))    ⇒   ⊢ (𝑁 ∈ (ℤ_≥‘3) → 𝑃 ∈ (𝔼‘𝑁))

Theorem

axlowdimlem8 29005

Lemma for axlowdim 29017. Calculate the value of 𝑃 at three. (Contributed by Scott Fenton, 21-Apr-2013.)

⊢ 𝑃 = ({⟨3, -1⟩} ∪ (((1...𝑁) ∖ {3}) × {0}))    ⇒   ⊢ (𝑃‘3) = -1

Theorem

axlowdimlem9 29006

Lemma for axlowdim 29017. Calculate the value of 𝑃 away from three. (Contributed by Scott Fenton, 21-Apr-2013.)

⊢ 𝑃 = ({⟨3, -1⟩} ∪ (((1...𝑁) ∖ {3}) × {0}))    ⇒   ⊢ ((𝐾 ∈ (1...𝑁) ∧ 𝐾 ≠ 3) → (𝑃‘𝐾) = 0)

Theorem

axlowdimlem10 29007

Lemma for axlowdim 29017. Set up a family of points in Euclidean space. (Contributed by Scott Fenton, 21-Apr-2013.)

⊢ 𝑄 = ({⟨(𝐼 + 1), 1⟩} ∪ (((1...𝑁) ∖ {(𝐼 + 1)}) × {0}))    ⇒   ⊢ ((𝑁 ∈ ℕ ∧ 𝐼 ∈ (1...(𝑁 − 1))) → 𝑄 ∈ (𝔼‘𝑁))

Theorem

axlowdimlem11 29008

Lemma for axlowdim 29017. Calculate the value of 𝑄 at its distinguished point. (Contributed by Scott Fenton, 21-Apr-2013.)

⊢ 𝑄 = ({⟨(𝐼 + 1), 1⟩} ∪ (((1...𝑁) ∖ {(𝐼 + 1)}) × {0}))    ⇒   ⊢ (𝑄‘(𝐼 + 1)) = 1

Theorem

axlowdimlem12 29009

Lemma for axlowdim 29017. Calculate the value of 𝑄 away from its distinguished point. (Contributed by Scott Fenton, 21-Apr-2013.)

⊢ 𝑄 = ({⟨(𝐼 + 1), 1⟩} ∪ (((1...𝑁) ∖ {(𝐼 + 1)}) × {0}))    ⇒   ⊢ ((𝐾 ∈ (1...𝑁) ∧ 𝐾 ≠ (𝐼 + 1)) → (𝑄‘𝐾) = 0)

Theorem

axlowdimlem13 29010

Lemma for axlowdim 29017. Establish that 𝑃 and 𝑄 are different points. (Contributed by Scott Fenton, 21-Apr-2013.)

⊢ 𝑃 = ({⟨3, -1⟩} ∪ (((1...𝑁) ∖ {3}) × {0}))    &   ⊢ 𝑄 = ({⟨(𝐼 + 1), 1⟩} ∪ (((1...𝑁) ∖ {(𝐼 + 1)}) × {0}))    ⇒   ⊢ ((𝑁 ∈ ℕ ∧ 𝐼 ∈ (1...(𝑁 − 1))) → 𝑃 ≠ 𝑄)

Theorem

axlowdimlem14 29011

Lemma for axlowdim 29017. Take two possible 𝑄 from axlowdimlem10 29007. They are the same iff their distinguished values are the same. (Contributed by Scott Fenton, 21-Apr-2013.)

⊢ 𝑄 = ({⟨(𝐼 + 1), 1⟩} ∪ (((1...𝑁) ∖ {(𝐼 + 1)}) × {0}))    &   ⊢ 𝑅 = ({⟨(𝐽 + 1), 1⟩} ∪ (((1...𝑁) ∖ {(𝐽 + 1)}) × {0}))    ⇒   ⊢ ((𝑁 ∈ ℕ ∧ 𝐼 ∈ (1...(𝑁 − 1)) ∧ 𝐽 ∈ (1...(𝑁 − 1))) → (𝑄 = 𝑅 → 𝐼 = 𝐽))

Theorem

axlowdimlem15 29012*

Lemma for axlowdim 29017. Set up a one-to-one function of points. (Contributed by Scott Fenton, 21-Apr-2013.)

⊢ 𝐹 = (𝑖 ∈ (1...(𝑁 − 1)) ↦ if(𝑖 = 1, ({⟨3, -1⟩} ∪ (((1...𝑁) ∖ {3}) × {0})), ({⟨(𝑖 + 1), 1⟩} ∪ (((1...𝑁) ∖ {(𝑖 + 1)}) × {0}))))    ⇒   ⊢ (𝑁 ∈ (ℤ_≥‘3) → 𝐹:(1...(𝑁 − 1))–1-1→(𝔼‘𝑁))

Theorem

axlowdimlem16 29013*

Lemma for axlowdim 29017. Set up a summation that will help establish distance. (Contributed by Scott Fenton, 21-Apr-2013.)

⊢ 𝑃 = ({⟨3, -1⟩} ∪ (((1...𝑁) ∖ {3}) × {0}))    &   ⊢ 𝑄 = ({⟨(𝐼 + 1), 1⟩} ∪ (((1...𝑁) ∖ {(𝐼 + 1)}) × {0}))    ⇒   ⊢ ((𝑁 ∈ (ℤ_≥‘3) ∧ 𝐼 ∈ (2...(𝑁 − 1))) → Σ𝑖 ∈ (3...𝑁)((𝑃‘𝑖)↑2) = Σ𝑖 ∈ (3...𝑁)((𝑄‘𝑖)↑2))

Theorem

axlowdimlem17 29014

Lemma for axlowdim 29017. Establish a congruence result. (Contributed by Scott Fenton, 22-Apr-2013.) (Proof shortened by Mario Carneiro, 22-May-2014.)

⊢ 𝑃 = ({⟨3, -1⟩} ∪ (((1...𝑁) ∖ {3}) × {0}))    &   ⊢ 𝑄 = ({⟨(𝐼 + 1), 1⟩} ∪ (((1...𝑁) ∖ {(𝐼 + 1)}) × {0}))    &   ⊢ 𝐴 = ({⟨1, 𝑋⟩, ⟨2, 𝑌⟩} ∪ ((3...𝑁) × {0}))    &   ⊢ 𝑋 ∈ ℝ    &   ⊢ 𝑌 ∈ ℝ    ⇒   ⊢ ((𝑁 ∈ (ℤ_≥‘3) ∧ 𝐼 ∈ (2...(𝑁 − 1))) → ⟨𝑃, 𝐴⟩Cgr⟨𝑄, 𝐴⟩)

Theorem

axlowdim1 29015*

The lower dimension axiom for one dimension. In any dimension, there are at least two distinct points. Theorem 3.13 of [Schwabhauser] p. 32, where it is derived from axlowdim2 29016. (Contributed by Scott Fenton, 22-Apr-2013.)

⊢ (𝑁 ∈ ℕ → ∃𝑥 ∈ (𝔼‘𝑁)∃𝑦 ∈ (𝔼‘𝑁)𝑥 ≠ 𝑦)

Theorem

axlowdim2 29016*

The lower two-dimensional axiom. In any space where the dimension is greater than one, there are three non-colinear points. Axiom A8 of [Schwabhauser] p. 12. (Contributed by Scott Fenton, 15-Apr-2013.)

⊢ (𝑁 ∈ (ℤ_≥‘2) → ∃𝑥 ∈ (𝔼‘𝑁)∃𝑦 ∈ (𝔼‘𝑁)∃𝑧 ∈ (𝔼‘𝑁) ¬ (𝑥 Btwn ⟨𝑦, 𝑧⟩ ∨ 𝑦 Btwn ⟨𝑧, 𝑥⟩ ∨ 𝑧 Btwn ⟨𝑥, 𝑦⟩))

Theorem

axlowdim 29017*

The general lower dimension axiom. Take a dimension 𝑁 greater than or equal to three. Then, there are three non-colinear points in 𝑁 dimensional space that are equidistant from 𝑁 − 1 distinct points. Derived from remarks in Tarski's System of Geometry, Alfred Tarski and Steven Givant, Bulletin of Symbolic Logic, Volume 5, Number 2 (1999), 175-214. (Contributed by Scott Fenton, 22-Apr-2013.)

⊢ (𝑁 ∈ (ℤ_≥‘3) → ∃𝑝∃𝑥 ∈ (𝔼‘𝑁)∃𝑦 ∈ (𝔼‘𝑁)∃𝑧 ∈ (𝔼‘𝑁)(𝑝:(1...(𝑁 − 1))–1-1→(𝔼‘𝑁) ∧ ∀𝑖 ∈ (2...(𝑁 − 1))(⟨(𝑝‘1), 𝑥⟩Cgr⟨(𝑝‘𝑖), 𝑥⟩ ∧ ⟨(𝑝‘1), 𝑦⟩Cgr⟨(𝑝‘𝑖), 𝑦⟩ ∧ ⟨(𝑝‘1), 𝑧⟩Cgr⟨(𝑝‘𝑖), 𝑧⟩) ∧ ¬ (𝑥 Btwn ⟨𝑦, 𝑧⟩ ∨ 𝑦 Btwn ⟨𝑧, 𝑥⟩ ∨ 𝑧 Btwn ⟨𝑥, 𝑦⟩)))

Theorem

axeuclidlem 29018*

Lemma for axeuclid 29019. Handle the algebraic aspects of the theorem. (Contributed by Scott Fenton, 9-Sep-2013.)

⊢ ((((𝐴 ∈ (𝔼‘𝑁) ∧ 𝐵 ∈ (𝔼‘𝑁)) ∧ (𝐶 ∈ (𝔼‘𝑁) ∧ 𝑇 ∈ (𝔼‘𝑁))) ∧ (𝑃 ∈ (0[,]1) ∧ 𝑄 ∈ (0[,]1) ∧ 𝑃 ≠ 0) ∧ ∀𝑖 ∈ (1...𝑁)(((1 − 𝑃) · (𝐴‘𝑖)) + (𝑃 · (𝑇‘𝑖))) = (((1 − 𝑄) · (𝐵‘𝑖)) + (𝑄 · (𝐶‘𝑖)))) → ∃𝑥 ∈ (𝔼‘𝑁)∃𝑦 ∈ (𝔼‘𝑁)∃𝑟 ∈ (0[,]1)∃𝑠 ∈ (0[,]1)∃𝑢 ∈ (0[,]1)∀𝑖 ∈ (1...𝑁)((𝐵‘𝑖) = (((1 − 𝑟) · (𝐴‘𝑖)) + (𝑟 · (𝑥‘𝑖))) ∧ (𝐶‘𝑖) = (((1 − 𝑠) · (𝐴‘𝑖)) + (𝑠 · (𝑦‘𝑖))) ∧ (𝑇‘𝑖) = (((1 − 𝑢) · (𝑥‘𝑖)) + (𝑢 · (𝑦‘𝑖)))))

Theorem

axeuclid 29019*

Euclid's axiom. Take an angle 𝐵𝐴𝐶 and a point 𝐷 between 𝐵 and 𝐶. Now, if you extend the segment 𝐴𝐷 to a point 𝑇, then 𝑇 lies between two points 𝑥 and 𝑦 that lie on the angle. Axiom A10 of [Schwabhauser] p. 13. (Contributed by Scott Fenton, 9-Sep-2013.)

⊢ ((𝑁 ∈ ℕ ∧ (𝐴 ∈ (𝔼‘𝑁) ∧ 𝐵 ∈ (𝔼‘𝑁) ∧ 𝐶 ∈ (𝔼‘𝑁)) ∧ (𝐷 ∈ (𝔼‘𝑁) ∧ 𝑇 ∈ (𝔼‘𝑁))) → ((𝐷 Btwn ⟨𝐴, 𝑇⟩ ∧ 𝐷 Btwn ⟨𝐵, 𝐶⟩ ∧ 𝐴 ≠ 𝐷) → ∃𝑥 ∈ (𝔼‘𝑁)∃𝑦 ∈ (𝔼‘𝑁)(𝐵 Btwn ⟨𝐴, 𝑥⟩ ∧ 𝐶 Btwn ⟨𝐴, 𝑦⟩ ∧ 𝑇 Btwn ⟨𝑥, 𝑦⟩)))

Theorem

axcontlem1 29020*

Lemma for axcont 29032. Change bound variables for later use. (Contributed by Scott Fenton, 20-Jun-2013.)

⊢ 𝐹 = {⟨𝑥, 𝑡⟩ ∣ (𝑥 ∈ 𝐷 ∧ (𝑡 ∈ (0[,)+∞) ∧ ∀𝑖 ∈ (1...𝑁)(𝑥‘𝑖) = (((1 − 𝑡) · (𝑍‘𝑖)) + (𝑡 · (𝑈‘𝑖)))))}    ⇒   ⊢ 𝐹 = {⟨𝑦, 𝑠⟩ ∣ (𝑦 ∈ 𝐷 ∧ (𝑠 ∈ (0[,)+∞) ∧ ∀𝑗 ∈ (1...𝑁)(𝑦‘𝑗) = (((1 − 𝑠) · (𝑍‘𝑗)) + (𝑠 · (𝑈‘𝑗)))))}

Theorem

axcontlem2 29021*

Lemma for axcont 29032. The idea here is to set up a mapping 𝐹 that will allow to transfer dedekind 11300 to two sets of points. Here, we set up 𝐹 and show its domain and codomain. (Contributed by Scott Fenton, 17-Jun-2013.)

⊢ 𝐷 = {𝑝 ∈ (𝔼‘𝑁) ∣ (𝑈 Btwn ⟨𝑍, 𝑝⟩ ∨ 𝑝 Btwn ⟨𝑍, 𝑈⟩)}    &   ⊢ 𝐹 = {⟨𝑥, 𝑡⟩ ∣ (𝑥 ∈ 𝐷 ∧ (𝑡 ∈ (0[,)+∞) ∧ ∀𝑖 ∈ (1...𝑁)(𝑥‘𝑖) = (((1 − 𝑡) · (𝑍‘𝑖)) + (𝑡 · (𝑈‘𝑖)))))}    ⇒   ⊢ (((𝑁 ∈ ℕ ∧ 𝑍 ∈ (𝔼‘𝑁) ∧ 𝑈 ∈ (𝔼‘𝑁)) ∧ 𝑍 ≠ 𝑈) → 𝐹:𝐷–1-1-onto→(0[,)+∞))

Theorem

axcontlem3 29022*

Lemma for axcont 29032. Given the separation assumption, 𝐵 is a subset of 𝐷. (Contributed by Scott Fenton, 18-Jun-2013.)

⊢ 𝐷 = {𝑝 ∈ (𝔼‘𝑁) ∣ (𝑈 Btwn ⟨𝑍, 𝑝⟩ ∨ 𝑝 Btwn ⟨𝑍, 𝑈⟩)}    ⇒   ⊢ (((𝑁 ∈ ℕ ∧ (𝐴 ⊆ (𝔼‘𝑁) ∧ 𝐵 ⊆ (𝔼‘𝑁) ∧ ∀𝑥 ∈ 𝐴 ∀𝑦 ∈ 𝐵 𝑥 Btwn ⟨𝑍, 𝑦⟩)) ∧ (𝑍 ∈ (𝔼‘𝑁) ∧ 𝑈 ∈ 𝐴 ∧ 𝑍 ≠ 𝑈)) → 𝐵 ⊆ 𝐷)

Theorem

axcontlem4 29023*

Lemma for axcont 29032. Given the separation assumption, 𝐴 is a subset of 𝐷. (Contributed by Scott Fenton, 18-Jun-2013.)

⊢ 𝐷 = {𝑝 ∈ (𝔼‘𝑁) ∣ (𝑈 Btwn ⟨𝑍, 𝑝⟩ ∨ 𝑝 Btwn ⟨𝑍, 𝑈⟩)}    ⇒   ⊢ (((𝑁 ∈ ℕ ∧ (𝐴 ⊆ (𝔼‘𝑁) ∧ 𝐵 ⊆ (𝔼‘𝑁) ∧ ∀𝑥 ∈ 𝐴 ∀𝑦 ∈ 𝐵 𝑥 Btwn ⟨𝑍, 𝑦⟩)) ∧ ((𝑍 ∈ (𝔼‘𝑁) ∧ 𝑈 ∈ 𝐴 ∧ 𝐵 ≠ ∅) ∧ 𝑍 ≠ 𝑈)) → 𝐴 ⊆ 𝐷)

Theorem

axcontlem5 29024*

Lemma for axcont 29032. Compute the value of 𝐹. (Contributed by Scott Fenton, 18-Jun-2013.)

⊢ 𝐷 = {𝑝 ∈ (𝔼‘𝑁) ∣ (𝑈 Btwn ⟨𝑍, 𝑝⟩ ∨ 𝑝 Btwn ⟨𝑍, 𝑈⟩)}    &   ⊢ 𝐹 = {⟨𝑥, 𝑡⟩ ∣ (𝑥 ∈ 𝐷 ∧ (𝑡 ∈ (0[,)+∞) ∧ ∀𝑖 ∈ (1...𝑁)(𝑥‘𝑖) = (((1 − 𝑡) · (𝑍‘𝑖)) + (𝑡 · (𝑈‘𝑖)))))}    ⇒   ⊢ ((((𝑁 ∈ ℕ ∧ 𝑍 ∈ (𝔼‘𝑁) ∧ 𝑈 ∈ (𝔼‘𝑁)) ∧ 𝑍 ≠ 𝑈) ∧ 𝑃 ∈ 𝐷) → ((𝐹‘𝑃) = 𝑇 ↔ (𝑇 ∈ (0[,)+∞) ∧ ∀𝑖 ∈ (1...𝑁)(𝑃‘𝑖) = (((1 − 𝑇) · (𝑍‘𝑖)) + (𝑇 · (𝑈‘𝑖))))))

Theorem

axcontlem6 29025*

Lemma for axcont 29032. State the defining properties of the value of 𝐹. (Contributed by Scott Fenton, 19-Jun-2013.)

⊢ 𝐷 = {𝑝 ∈ (𝔼‘𝑁) ∣ (𝑈 Btwn ⟨𝑍, 𝑝⟩ ∨ 𝑝 Btwn ⟨𝑍, 𝑈⟩)}    &   ⊢ 𝐹 = {⟨𝑥, 𝑡⟩ ∣ (𝑥 ∈ 𝐷 ∧ (𝑡 ∈ (0[,)+∞) ∧ ∀𝑖 ∈ (1...𝑁)(𝑥‘𝑖) = (((1 − 𝑡) · (𝑍‘𝑖)) + (𝑡 · (𝑈‘𝑖)))))}    ⇒   ⊢ ((((𝑁 ∈ ℕ ∧ 𝑍 ∈ (𝔼‘𝑁) ∧ 𝑈 ∈ (𝔼‘𝑁)) ∧ 𝑍 ≠ 𝑈) ∧ 𝑃 ∈ 𝐷) → ((𝐹‘𝑃) ∈ (0[,)+∞) ∧ ∀𝑖 ∈ (1...𝑁)(𝑃‘𝑖) = (((1 − (𝐹‘𝑃)) · (𝑍‘𝑖)) + ((𝐹‘𝑃) · (𝑈‘𝑖)))))

Theorem

axcontlem7 29026*

Lemma for axcont 29032. Given two points in 𝐷, one preceeds the other iff its scaling constant is less than the other point's. (Contributed by Scott Fenton, 18-Jun-2013.)

⊢ 𝐷 = {𝑝 ∈ (𝔼‘𝑁) ∣ (𝑈 Btwn ⟨𝑍, 𝑝⟩ ∨ 𝑝 Btwn ⟨𝑍, 𝑈⟩)}    &   ⊢ 𝐹 = {⟨𝑥, 𝑡⟩ ∣ (𝑥 ∈ 𝐷 ∧ (𝑡 ∈ (0[,)+∞) ∧ ∀𝑖 ∈ (1...𝑁)(𝑥‘𝑖) = (((1 − 𝑡) · (𝑍‘𝑖)) + (𝑡 · (𝑈‘𝑖)))))}    ⇒   ⊢ ((((𝑁 ∈ ℕ ∧ 𝑍 ∈ (𝔼‘𝑁) ∧ 𝑈 ∈ (𝔼‘𝑁)) ∧ 𝑍 ≠ 𝑈) ∧ (𝑃 ∈ 𝐷 ∧ 𝑄 ∈ 𝐷)) → (𝑃 Btwn ⟨𝑍, 𝑄⟩ ↔ (𝐹‘𝑃) ≤ (𝐹‘𝑄)))

Theorem

axcontlem8 29027*

Lemma for axcont 29032. A point in 𝐷 is between two others if its function value falls in the middle. (Contributed by Scott Fenton, 18-Jun-2013.)

⊢ 𝐷 = {𝑝 ∈ (𝔼‘𝑁) ∣ (𝑈 Btwn ⟨𝑍, 𝑝⟩ ∨ 𝑝 Btwn ⟨𝑍, 𝑈⟩)}    &   ⊢ 𝐹 = {⟨𝑥, 𝑡⟩ ∣ (𝑥 ∈ 𝐷 ∧ (𝑡 ∈ (0[,)+∞) ∧ ∀𝑖 ∈ (1...𝑁)(𝑥‘𝑖) = (((1 − 𝑡) · (𝑍‘𝑖)) + (𝑡 · (𝑈‘𝑖)))))}    ⇒   ⊢ ((((𝑁 ∈ ℕ ∧ 𝑍 ∈ (𝔼‘𝑁) ∧ 𝑈 ∈ (𝔼‘𝑁)) ∧ 𝑍 ≠ 𝑈) ∧ (𝑃 ∈ 𝐷 ∧ 𝑄 ∈ 𝐷 ∧ 𝑅 ∈ 𝐷)) → (((𝐹‘𝑃) ≤ (𝐹‘𝑄) ∧ (𝐹‘𝑄) ≤ (𝐹‘𝑅)) → 𝑄 Btwn ⟨𝑃, 𝑅⟩))

Theorem

axcontlem9 29028*

Lemma for axcont 29032. Given the separation assumption, all values of 𝐹 over 𝐴 are less than or equal to all values of 𝐹 over 𝐵. (Contributed by Scott Fenton, 20-Jun-2013.)

⊢ 𝐷 = {𝑝 ∈ (𝔼‘𝑁) ∣ (𝑈 Btwn ⟨𝑍, 𝑝⟩ ∨ 𝑝 Btwn ⟨𝑍, 𝑈⟩)}    &   ⊢ 𝐹 = {⟨𝑥, 𝑡⟩ ∣ (𝑥 ∈ 𝐷 ∧ (𝑡 ∈ (0[,)+∞) ∧ ∀𝑖 ∈ (1...𝑁)(𝑥‘𝑖) = (((1 − 𝑡) · (𝑍‘𝑖)) + (𝑡 · (𝑈‘𝑖)))))}    ⇒   ⊢ (((𝑁 ∈ ℕ ∧ (𝐴 ⊆ (𝔼‘𝑁) ∧ 𝐵 ⊆ (𝔼‘𝑁) ∧ ∀𝑥 ∈ 𝐴 ∀𝑦 ∈ 𝐵 𝑥 Btwn ⟨𝑍, 𝑦⟩)) ∧ ((𝑍 ∈ (𝔼‘𝑁) ∧ 𝑈 ∈ 𝐴 ∧ 𝐵 ≠ ∅) ∧ 𝑍 ≠ 𝑈)) → ∀𝑛 ∈ (𝐹 “ 𝐴)∀𝑚 ∈ (𝐹 “ 𝐵)𝑛 ≤ 𝑚)

Theorem

axcontlem10 29029*

Lemma for axcont 29032. Given a handful of assumptions, derive the conclusion of the final theorem. (Contributed by Scott Fenton, 20-Jun-2013.)

⊢ 𝐷 = {𝑝 ∈ (𝔼‘𝑁) ∣ (𝑈 Btwn ⟨𝑍, 𝑝⟩ ∨ 𝑝 Btwn ⟨𝑍, 𝑈⟩)}    &   ⊢ 𝐹 = {⟨𝑥, 𝑡⟩ ∣ (𝑥 ∈ 𝐷 ∧ (𝑡 ∈ (0[,)+∞) ∧ ∀𝑖 ∈ (1...𝑁)(𝑥‘𝑖) = (((1 − 𝑡) · (𝑍‘𝑖)) + (𝑡 · (𝑈‘𝑖)))))}    ⇒   ⊢ (((𝑁 ∈ ℕ ∧ (𝐴 ⊆ (𝔼‘𝑁) ∧ 𝐵 ⊆ (𝔼‘𝑁) ∧ ∀𝑥 ∈ 𝐴 ∀𝑦 ∈ 𝐵 𝑥 Btwn ⟨𝑍, 𝑦⟩)) ∧ ((𝑍 ∈ (𝔼‘𝑁) ∧ 𝑈 ∈ 𝐴 ∧ 𝐵 ≠ ∅) ∧ 𝑍 ≠ 𝑈)) → ∃𝑏 ∈ (𝔼‘𝑁)∀𝑥 ∈ 𝐴 ∀𝑦 ∈ 𝐵 𝑏 Btwn ⟨𝑥, 𝑦⟩)

Theorem

axcontlem11 29030*

Lemma for axcont 29032. Eliminate the hypotheses from axcontlem10 29029. (Contributed by Scott Fenton, 20-Jun-2013.)

⊢ (((𝑁 ∈ ℕ ∧ (𝐴 ⊆ (𝔼‘𝑁) ∧ 𝐵 ⊆ (𝔼‘𝑁) ∧ ∀𝑥 ∈ 𝐴 ∀𝑦 ∈ 𝐵 𝑥 Btwn ⟨𝑍, 𝑦⟩)) ∧ ((𝑍 ∈ (𝔼‘𝑁) ∧ 𝑈 ∈ 𝐴 ∧ 𝐵 ≠ ∅) ∧ 𝑍 ≠ 𝑈)) → ∃𝑏 ∈ (𝔼‘𝑁)∀𝑥 ∈ 𝐴 ∀𝑦 ∈ 𝐵 𝑏 Btwn ⟨𝑥, 𝑦⟩)

Theorem

axcontlem12 29031*

Lemma for axcont 29032. Eliminate the trivial cases from the previous lemmas. (Contributed by Scott Fenton, 20-Jun-2013.)

⊢ (((𝑁 ∈ ℕ ∧ (𝐴 ⊆ (𝔼‘𝑁) ∧ 𝐵 ⊆ (𝔼‘𝑁) ∧ ∀𝑥 ∈ 𝐴 ∀𝑦 ∈ 𝐵 𝑥 Btwn ⟨𝑍, 𝑦⟩)) ∧ 𝑍 ∈ (𝔼‘𝑁)) → ∃𝑏 ∈ (𝔼‘𝑁)∀𝑥 ∈ 𝐴 ∀𝑦 ∈ 𝐵 𝑏 Btwn ⟨𝑥, 𝑦⟩)

Theorem

axcont 29032*

The axiom of continuity. Take two sets of points 𝐴 and 𝐵. If all the points in 𝐴 come before the points of 𝐵 on a line, then there is a point separating the two. Axiom A11 of [Schwabhauser] p. 13. (Contributed by Scott Fenton, 20-Jun-2013.)

⊢ ((𝑁 ∈ ℕ ∧ (𝐴 ⊆ (𝔼‘𝑁) ∧ 𝐵 ⊆ (𝔼‘𝑁) ∧ ∃𝑎 ∈ (𝔼‘𝑁)∀𝑥 ∈ 𝐴 ∀𝑦 ∈ 𝐵 𝑥 Btwn ⟨𝑎, 𝑦⟩)) → ∃𝑏 ∈ (𝔼‘𝑁)∀𝑥 ∈ 𝐴 ∀𝑦 ∈ 𝐵 𝑏 Btwn ⟨𝑥, 𝑦⟩)

16.4.2.3  EE^n fulfills Tarski's Axioms

Syntax

ceeng 29033

Extends class notation with the Tarski geometry structure for 𝔼↑𝑁.

class EEG

Definition

df-eeng 29034*

Define the geometry structure for 𝔼↑𝑁. (Contributed by Thierry Arnoux, 24-Aug-2017.)

⊢ EEG = (𝑛 ∈ ℕ ↦ ({⟨(Base‘ndx), (𝔼‘𝑛)⟩, ⟨(dist‘ndx), (𝑥 ∈ (𝔼‘𝑛), 𝑦 ∈ (𝔼‘𝑛) ↦ Σ𝑖 ∈ (1...𝑛)(((𝑥‘𝑖) − (𝑦‘𝑖))↑2))⟩} ∪ {⟨(Itv‘ndx), (𝑥 ∈ (𝔼‘𝑛), 𝑦 ∈ (𝔼‘𝑛) ↦ {𝑧 ∈ (𝔼‘𝑛) ∣ 𝑧 Btwn ⟨𝑥, 𝑦⟩})⟩, ⟨(LineG‘ndx), (𝑥 ∈ (𝔼‘𝑛), 𝑦 ∈ ((𝔼‘𝑛) ∖ {𝑥}) ↦ {𝑧 ∈ (𝔼‘𝑛) ∣ (𝑧 Btwn ⟨𝑥, 𝑦⟩ ∨ 𝑥 Btwn ⟨𝑧, 𝑦⟩ ∨ 𝑦 Btwn ⟨𝑥, 𝑧⟩)})⟩}))

Theorem

eengv 29035*

The value of the Euclidean geometry for dimension 𝑁. (Contributed by Thierry Arnoux, 15-Mar-2019.)

⊢ (𝑁 ∈ ℕ → (EEG‘𝑁) = ({⟨(Base‘ndx), (𝔼‘𝑁)⟩, ⟨(dist‘ndx), (𝑥 ∈ (𝔼‘𝑁), 𝑦 ∈ (𝔼‘𝑁) ↦ Σ𝑖 ∈ (1...𝑁)(((𝑥‘𝑖) − (𝑦‘𝑖))↑2))⟩} ∪ {⟨(Itv‘ndx), (𝑥 ∈ (𝔼‘𝑁), 𝑦 ∈ (𝔼‘𝑁) ↦ {𝑧 ∈ (𝔼‘𝑁) ∣ 𝑧 Btwn ⟨𝑥, 𝑦⟩})⟩, ⟨(LineG‘ndx), (𝑥 ∈ (𝔼‘𝑁), 𝑦 ∈ ((𝔼‘𝑁) ∖ {𝑥}) ↦ {𝑧 ∈ (𝔼‘𝑁) ∣ (𝑧 Btwn ⟨𝑥, 𝑦⟩ ∨ 𝑥 Btwn ⟨𝑧, 𝑦⟩ ∨ 𝑦 Btwn ⟨𝑥, 𝑧⟩)})⟩}))

Theorem

eengstr 29036

The Euclidean geometry as a structure. (Contributed by Thierry Arnoux, 15-Mar-2019.)

⊢ (𝑁 ∈ ℕ → (EEG‘𝑁) Struct ⟨1, ;17⟩)

Theorem

eengbas 29037

The Base of the Euclidean geometry. (Contributed by Thierry Arnoux, 15-Mar-2019.)

⊢ (𝑁 ∈ ℕ → (𝔼‘𝑁) = (Base‘(EEG‘𝑁)))

Theorem

ebtwntg 29038

The betweenness relation used in the Tarski structure for the Euclidean geometry is the same as Btwn. (Contributed by Thierry Arnoux, 15-Mar-2019.)

⊢ (𝜑 → 𝑁 ∈ ℕ)    &   ⊢ 𝑃 = (Base‘(EEG‘𝑁))    &   ⊢ 𝐼 = (Itv‘(EEG‘𝑁))    &   ⊢ (𝜑 → 𝑋 ∈ 𝑃)    &   ⊢ (𝜑 → 𝑌 ∈ 𝑃)    &   ⊢ (𝜑 → 𝑍 ∈ 𝑃)    ⇒   ⊢ (𝜑 → (𝑍 Btwn ⟨𝑋, 𝑌⟩ ↔ 𝑍 ∈ (𝑋𝐼𝑌)))

Theorem

ecgrtg 29039

The congruence relation used in the Tarski structure for the Euclidean geometry is the same as Cgr. (Contributed by Thierry Arnoux, 15-Mar-2019.)

⊢ (𝜑 → 𝑁 ∈ ℕ)    &   ⊢ 𝑃 = (Base‘(EEG‘𝑁))    &   ⊢ − = (dist‘(EEG‘𝑁))    &   ⊢ (𝜑 → 𝐴 ∈ 𝑃)    &   ⊢ (𝜑 → 𝐵 ∈ 𝑃)    &   ⊢ (𝜑 → 𝐶 ∈ 𝑃)    &   ⊢ (𝜑 → 𝐷 ∈ 𝑃)    ⇒   ⊢ (𝜑 → (⟨𝐴, 𝐵⟩Cgr⟨𝐶, 𝐷⟩ ↔ (𝐴 − 𝐵) = (𝐶 − 𝐷)))

Theorem

elntg 29040*

The line definition in the Tarski structure for the Euclidean geometry. (Contributed by Thierry Arnoux, 7-Apr-2019.)

⊢ 𝑃 = (Base‘(EEG‘𝑁))    &   ⊢ 𝐼 = (Itv‘(EEG‘𝑁))    ⇒   ⊢ (𝑁 ∈ ℕ → (LineG‘(EEG‘𝑁)) = (𝑥 ∈ 𝑃, 𝑦 ∈ (𝑃 ∖ {𝑥}) ↦ {𝑧 ∈ 𝑃 ∣ (𝑧 ∈ (𝑥𝐼𝑦) ∨ 𝑥 ∈ (𝑧𝐼𝑦) ∨ 𝑦 ∈ (𝑥𝐼𝑧))}))

Theorem

elntg2 29041*

The line definition in the Tarski structure for the Euclidean geometry. In contrast to elntg 29040, the betweenness can be strengthened by excluding 1 resp. 0 from the related intervals (because of 𝑥 ≠ 𝑦). (Contributed by AV, 14-Feb-2023.)

⊢ 𝑃 = (Base‘(EEG‘𝑁))    &   ⊢ 𝐼 = (1...𝑁)    ⇒   ⊢ (𝑁 ∈ ℕ → (LineG‘(EEG‘𝑁)) = (𝑥 ∈ 𝑃, 𝑦 ∈ (𝑃 ∖ {𝑥}) ↦ {𝑝 ∈ 𝑃 ∣ (∃𝑘 ∈ (0[,]1)∀𝑖 ∈ 𝐼 (𝑝‘𝑖) = (((1 − 𝑘) · (𝑥‘𝑖)) + (𝑘 · (𝑦‘𝑖))) ∨ ∃𝑙 ∈ (0[,)1)∀𝑖 ∈ 𝐼 (𝑥‘𝑖) = (((1 − 𝑙) · (𝑝‘𝑖)) + (𝑙 · (𝑦‘𝑖))) ∨ ∃𝑚 ∈ (0(,]1)∀𝑖 ∈ 𝐼 (𝑦‘𝑖) = (((1 − 𝑚) · (𝑥‘𝑖)) + (𝑚 · (𝑝‘𝑖))))}))

Theorem

eengtrkg 29042

The geometry structure for 𝔼↑𝑁 is a Tarski geometry. (Contributed by Thierry Arnoux, 15-Mar-2019.)

⊢ (𝑁 ∈ ℕ → (EEG‘𝑁) ∈ TarskiG)

Theorem

eengtrkge 29043

The geometry structure for 𝔼↑𝑁 is a Euclidean geometry. (Contributed by Thierry Arnoux, 15-Mar-2019.)

⊢ (𝑁 ∈ ℕ → (EEG‘𝑁) ∈ TarskiG_E)

PART 17  GRAPH THEORY

To give an overview of the definitions and terms used in the context of graph theory, a glossary is provided in the following, mainly according to definitions in [Bollobas] p. 1-8 or in [Diestel] p. 2-28. Although this glossary concentrates on undirected graphs, many of the concepts are also useful for directed graphs.

Basic concepts:

Term	Reference	Definition	Remarks
Vertex	df-vtx 29054	A vertex of a graph 𝐺 is an element of the set of vertices (Vtx‘𝐺) of the graph 𝐺.	The set of vertices (Vtx‘𝐺) (corresponding to V(G) in [Bollobas] p. 1) is usually the first component 𝑉 of the graph 𝐺 if it is represented by an ordered pair ⟨𝑉, 𝐸⟩ (see opvtxfv 29060), or the base set (Base‘𝐺) of the graph 𝐺 if it is represented as extensible structure (see basvtxval 29072).
Edge	df-edg 29104	An edge of a graph 𝐺 is a nonempty set of vertices of the graph. It is said that these vertices are "joined" or "connected" by the edge, see [Bollobas] p. 1.	The set of edges (Edg‘𝐺) (corresponding to E(G) in [Bollobas] p. 1) is usually the range ran 𝐸 of the second component 𝐸 of the graph 𝐺 if it is represented by an ordered pair ⟨𝑉, 𝐸⟩, or the range of the component (.ef‘𝐺) of the graph 𝐺 if it is represented as extensible structure. If necessary, we distinguish between "hyperedges", i.e., edges connecting more than two (possibly infinitely many) vertices, "simple edges", i.e., edges connecting exactly two different vertices, and "loops", i.e., edges connecting a vertex with itself (see also the next entry). Usually, however, the context makes it clear which kind of edge is meant: pseudographs cannot contain hyperedges, and multigraphs resp. simple graphs contain simple edges only.
Loop		A loop in a graph 𝐺 is an edge which connects a single vertex with itself (or, according to [Bollobas] p. 7 "joins a vertex to itself").	In other words, a loop is an edge 𝑒 ∈ (Edg‘𝐺) which is a singleton consisting of a vertex 𝑣 ∈ (Vtx‘𝐺): 𝑒 = {𝑣}
Edge function resp. indexed edges	df-iedg 29055	An edge function (or indexed set of edges) of a graph 𝐺 is a mapping of an arbitrary index set to nonempty sets of vertices of the graph.	The edge function (iEdg‘𝐺) is usually the second component 𝐸 of the graph 𝐺 if it is represented by an ordered pair ⟨𝑉, 𝐸 > (see opiedgfv 29063), or the component (.ef‘𝐺) of the graph 𝐺 if it is represented as extensible structure (see edgfiedgval 29073). The set of edges of a graph 𝐺 is the range of its edge function: (Edg‘𝐺) = ran (iEdg‘𝐺), see edgval 29105. Whereas the concept of plain edges is sufficient for simple hypergraphs, indexed edges are required for e.g., multigraphs in which the same vertices may be connected by more than one edge.

Basic kinds of graphs:

Term	Reference	Definition	Remarks
Undirected hypergraph	df-uhgr 29114	a class 𝐺 with an edge function 𝐸 = (iEdg‘𝐺) which is a function into the power set of the vertices 𝑉 = (Vtx‘𝐺): ran 𝐸 ⊆ (𝒫 𝑉 ∖ {∅}).	In this most general definition of a graph, an "edge" may connect three or more vertices with each other, see [Berge] p. 1. In Wikipedia "Hypergraph", see https://en.wikipedia.org/wiki/Hypergraph 29114 (18-Jan-2020) such a hypergraph is called a "non-simple hypergraph", "multiple hypergraph" or "multi-hypergraphs". According to Wikipedia "Incidence structure", see https://en.wikipedia.org/wiki/Incidence_structure 29114 (18-Jan-2020) "Each hypergraph [...] can be regarded as an incidence structure in which the [vertices] play the role of "points", the corresponding family of [edges] plays the role of "lines" and the incidence relation is set membership". Notice that by using (Edg‘𝐺) the (possibly more than one) edges connecting the same vertices could not be distinguished anymore. Therefore, this representation will only be used for undirected simple hypergraphs.
Undirected simple hypergraph	df-ushgr 29115	a class 𝐺 with an edge function 𝐸 = (iEdg‘𝐺) which is a one-to-one function into the power set of the vertices 𝑉 = (Vtx‘𝐺): ran 𝐸 ⊆ (𝒫 𝑉 ∖ {∅}).	See also Wikipedia "Hypergraph", https://en.wikipedia.org/wiki/Hypergraph 29115 (18-Jan-2020). This is how a "hypergraph" is defined in Section I.1 in [Bollobas] p. 7 or the definition in section 1.10 in [Diestel] p. 27. A simple hypergraph has at most one edge between the same vertices, hence a pseudograph needs not be a simple hypergraph. According to [Berge] p. 1, "A simple hypergraph (or "Sperner family") is a hypergraph H = { E_1, E_2, ..., E_m } such that E_i C_ E_j => i = j". By this definition, a simple hypergraph cannot contain the edges E_1 = { v_1 , v_2 } and E_2 = { v_1, v_2, v_3 }, because E_1 C_ E_2, but 1 =/= 2.
Undirected loop-free hypergraph	---	an undirected hypergraph without a loop, i.e. all edges connect at least two vertices.
Undirected pseudograph	df-upgr 29138	a class 𝐺 with an edge function 𝐸 = (iEdg‘𝐺) which is a function into the set of (proper or not proper) unordered pairs of vertices 𝑉 = (Vtx‘𝐺).	A proper unordered pair contains two different elements, a not proper unordered pair contains two times the same element, so it is a singleton (see preqsn 4819). This means a pseudograph may contain loops. This definition corresponds to the definition of a "multigraph" in Section I.1 in [Bollobas] p. 7, "In a multigraph both multiple edges [joining two vertices] and multiple loops [joining a vertex to itself] are allowed", or in [Diestel] p. 28, "A multigraph is a pair (V,E) of disjoint sets (of vertices and edges) together with a map E -> V u. [V]^2 assigning to every edge either one or two vertices, its end(s).".
Undirected multigraph	df-umgr 29139	a class 𝐺 with an edge function 𝐸 = (iEdg‘𝐺) which is a function into the set of (proper!) unordered pairs of vertices 𝑉 = (Vtx‘𝐺).	This definition is according to Chartrand, Gary and Zhang, Ping (2012): "A First Course in Graph Theory.", Dover, ISBN 978-0-486-48368-9, section 1.4, p. 26: "A multigraph M consists of a finite nonempty set V of vertices and a set E of edges, where every two vertices of M are joined by a finite number of edges (possibly zero). If two or more edges join the same pair of (distinct) vertices, then these edges are called parallel edges." A proper unordered pair contains two different elements, therefore a multigraph does not have loops.
Undirected simple pseudograph	df-uspgr 29206	a class 𝐺 with an edge function 𝐸 = (iEdg‘𝐺) which is a one-to-one function into the set of (proper or not proper) unordered pairs of vertices 𝑉 = (Vtx‘𝐺).	This means that there is at most one edge between two vertices, and at most one loop from a vertex to itself.
Undirected simple graph	df-usgr 29207	a class 𝐺 with an edge function 𝐸 = (iEdg‘𝐺) which is a one-to-one function into the set of (proper!) unordered pairs of vertices 𝑉 = (Vtx‘𝐺).	An ordered pair ⟨𝑉, 𝐸⟩ of two distinct sets 𝑉 (the vertices) and 𝐸 (the edges), the "usual" definition of a "graph", see, for example, the definition in section I.1 of [Bollobas] p. 1 or in section 1.1 of [Diestel] p. 2, can be identified with an undirected simple graph without loops by "indexing" the edges with themselves, see usgrausgrb 29225.
Finite graph	df-fusgr 29373	a graph 𝐺 with a finite set of vertices 𝑉 = (Vtx‘𝐺).	See definitions in [Bollobas] p. 1 or [Diestel] p. 2. In simple graphs, the set of (indexed) edges (iEdg‘𝐺) (and therefore also the set of edges (Edg‘𝐺)) is finite if 𝑉 = (Vtx‘𝐺) is finite, see fusgrfis 29386. The number of edges is limited by (𝑛C2) (or "𝑛 choose 2") with 𝑛 = (♯‘𝑉), see fusgrmaxsize 29521. Analogously, the number of edges 𝐸 = (iEdg‘𝐺) of an undirected simple pseudograph (which may have loops) is limited by ((𝑛 + 1)C2). In pseudographs or multigraphs, however, 𝐸 can be infinite although 𝑉 is finite.
Graph of finite size	---	a graph 𝐺 with a finite set 𝐸 = (iEdg‘𝐺), i.e. with a finite number of edges.	A graph can be of finite size although its set of vertices is infinite (most of the vertices would not be connected by an edge).

Terms and properties of graphs:

Term	Reference	Definition	Remarks
Edge joining resp. connecting (two) vertices	---	An edge 𝑒 ∈ (Edg‘𝐺) joins resp. connects the vertices v_1, v_2, ... v_n (𝑛 ∈ ℕ) if 𝑒 = { v_1, v_2, ... v_n }.	If 𝑛 = 1, 𝑒 = { v_1 } is a loop, if 𝑛 = 2, 𝑒 = { v_1 , v_2 } is an edge as it is usually defined, see definition in Section I.1 in [Bollobas] p. 1.
(Two) Endvertices of an edge	see definition in Section I.1 in [Bollobas] p. 1.	If an edge 𝑒 ∈ (Edg‘𝐺) joins the vertices v_1, v_2, ... v_n (𝑛 ∈ ℕ), then the vertices v_1, v_2, ... v_n are called the endvertices of the edge 𝑒.
(Two) Adjacent vertices	see definition in Section I.1 in [Bollobas] p. 1/2.	The vertices v_1, v_2, ... v_n (𝑛 ∈ ℕ) are adjacent if there is an edge e = { v_1, v_2, ... v_n } joining these vertices. In this case, the vertices are incident with the edge e (see definition in Section I.1 in [Bollobas] p. 2) or connected by the edge e.
Edge ending at a vertex		An edge 𝑒 ∈ (Edg‘𝐺) is ending at a vertex 𝑣 if the vertex is an endvertex of the edge: 𝑣 ∈ 𝑒. In other words, the vertex 𝑣 is incident with the edge 𝑒.
(Two) Adjacent edges		The edges e_0, e_1, ... e_n (𝑛 ∈ ℕ) are adjacent if they have exactly one common endvertex.	Generalization of definition in Section I.1 in [Bollobas] p. 2.
Order of a graph	see definition in Section I.1 in [Bollobas] p. 3	The order of a graph 𝐺 is the number of vertices in the graph: (♯‘(Vtx‘𝐺)).
Size of a graph	see definition in Section I.1 in [Bollobas] p. 3	The size of a graph 𝐺 is the number of edges in the graph: (♯‘(iEdg‘𝐺)). Or, for a simple graph 𝐺: (♯‘(Edg‘𝐺))).
Neighborhood of a vertex	df-nbgr 29389 resp. definition in Section I.1 in [Bollobas] p. 3	A vertex connected with a vertex 𝑣 by an edge is called a neighbor of the vertex 𝑣. The set of neighbors of a vertex 𝑣 is called the neighborhood (or open neighborhood) of the vertex 𝑣. The closed neighborhood is the union of the (open) neighborhood of the vertex 𝑣 with {𝑣} (see df-clnbgr 48101).
Degree of a vertex	df-vtxdg 29523	The degree of a vertex is the number of the edges ending at this vertex.	In a simple graph, the degree of a vertex is the number of neighbors of this vertex, see definition in Section I.1 in [Bollobas] p. 3
Isolated vertex	usgrvd0nedg 29590	A vertex is called isolated if it is not an endvertex of any edge, thus having degree 0.
Universal vertex	df-uvtx 29442	A vertex is called universal if it is connected with every other vertex of the graph by an edge, thus having degree ((♯‘(Vtx‘𝐺)) − ).

Special kinds of graphs:

Term	Reference	Definition	Remarks
Complete graph	df-cplgr 29467	A graph is called complete if each pair of vertices is connected by an edge.	The size of a complete undirected simple graph of order 𝑛 is (𝑛C2) (or "𝑛 choose 2"), see cusgrsize 29511.
Empty graph	uhgr0e 29127	A graph is called empty if it has no edges.
Null graph	uhgr0 29129 and uhgr0vb 29128	A graph is called a null graph if it has no vertices (and therefore also no edges).
Trivial graph	usgr1v 29312	A graph is called the "trivial graph" if it has only one vertex and no edges.
Connected graph	df-conngr 30245 resp. definition in Section I.1 in [Bollobas] p. 6	A graph is called connected if for each pair of vertices there is a path between these vertices.

For the terms "Path", "Walk", "Trail", "Circuit", "Cycle" see the remarks below and the definitions in Section I.1 in [Bollobas] p. 4-5.

17.1  Vertices and edges

In the following, the vertices and (indexed) edges for an arbitrary class 𝐺 (called "graph" in the following) are defined and examined. The main result of this section is to show that the set of vertices (Vtx‘𝐺) of a graph 𝐺 is the first component 𝑉 of the graph 𝐺 if it is represented by an ordered pair ⟨𝑉, 𝐸⟩ (see opvtxfv 29060), or the base set (Base‘𝐺) of the graph 𝐺 if it is represented as extensible structure (see basvtxval 29072), and that the set of indexed edges resp. the edge function (iEdg‘𝐺) is the second component 𝐸 of the graph 𝐺 if it is represented by an ordered pair ⟨𝑉, 𝐸⟩ (see opiedgfv 29063), or the component (.ef‘𝐺) of the graph 𝐺 if it is represented as extensible structure (see edgfiedgval 29073). Finally, it is shown that the set of edges of a graph 𝐺 is the range of its edge function: (Edg‘𝐺) = ran (iEdg‘𝐺), see edgval 29105.

Usually, a graph 𝐺 is a set. If 𝐺 is a proper class, however, it represents the null graph (without vertices and edges), because (Vtx‘𝐺) = ∅ and (iEdg‘𝐺) = ∅ holds, see vtxvalprc 29101 and iedgvalprc 29102.

Up to the end of this section, the edges need not be related to the vertices. Once undirected hypergraphs are defined (see df-uhgr 29114), the edges become nonempty sets of vertices, and by this obtain their meaning as "connectors" of vertices.

17.1.1  The edge function extractor for extensible structures

Syntax

cedgf 29044

Extend class notation with an edge function.

class .ef

Definition

df-edgf 29045

Define the edge function (indexed edges) of a graph. (Contributed by AV, 18-Jan-2020.) Use its index-independent form edgfid 29046 instead. (New usage is discouraged.)

⊢ .ef = Slot ;18

Theorem

edgfid 29046

Utility theorem: index-independent form of df-edgf 29045. (Contributed by AV, 16-Nov-2021.)

⊢ .ef = Slot (.ef‘ndx)

Theorem

edgfndx 29047

Index value of the df-edgf 29045 slot. (Contributed by AV, 13-Oct-2024.) (New usage is discouraged.)

⊢ (.ef‘ndx) = ;18

Theorem

edgfndxnn 29048

The index value of the edge function extractor is a positive integer. This property should be ensured for every concrete coding because otherwise it could not be used in an extensible structure (slots must be positive integers). (Contributed by AV, 21-Sep-2020.) (Proof shortened by AV, 13-Oct-2024.)

⊢ (.ef‘ndx) ∈ ℕ

Theorem

edgfndxid 29049

The value of the edge function extractor is the value of the corresponding slot of the structure. (Contributed by AV, 21-Sep-2020.) (Proof shortened by AV, 28-Oct-2024.)

⊢ (𝐺 ∈ 𝑉 → (.ef‘𝐺) = (𝐺‘(.ef‘ndx)))

Theorem

basendxltedgfndx 29050

The index value of the Base slot is less than the index value of the .ef slot. (Contributed by AV, 21-Sep-2020.) (Proof shortened by AV, 30-Oct-2024.)

⊢ (Base‘ndx) < (.ef‘ndx)

Theorem

basendxnedgfndx 29051

The slots Base and .ef are different. (Contributed by AV, 21-Sep-2020.)

⊢ (Base‘ndx) ≠ (.ef‘ndx)

17.1.2  Vertices and indexed edges

The key concepts in graph theory are vertices and edges. In general, a graph "consists" (at least) of two sets: the set of vertices and the set of edges. The edges "connect" vertices. The meaning of "connect" is different for different kinds of graphs (directed/undirected graphs, hyper-/pseudo-/ multi-/simple graphs, etc.). The simplest way to represent a graph (of any kind) is to define a graph as "an ordered pair of disjoint sets (V, E)" (see section I.1 in [Bollobas] p. 1), or in the notation of Metamath: ⟨𝑉, 𝐸⟩.

Another way is to regard a graph as a mathematical structure, which consists at least of a set (of vertices) and a relation between the vertices (edge function), but which can be enhanced by additional features (see Wikipedia "Mathematical structure", 24-Sep-2020, https://en.wikipedia.org/wiki/Mathematical_structure): "In mathematics, a structure is a set endowed with some additional features on the set (e.g., operation, relation, metric, topology). Often, the additional features are attached or related to the set, so as to provide it with some additional meaning or significance.". Such structures are provided as "extensible structures" in Metamath, see df-struct 17078.

To allow for expressing and proving most of the theorems for graphs independently from their representation, the functions Vtx and iEdg are defined (see df-vtx 29054 and df-iedg 29055), which provide the vertices resp. (indexed) edges of an arbitrary class 𝐺 which represents a graph: (Vtx‘𝐺) resp. (iEdg‘𝐺). In literature, these functions are often denoted also by "V" and "E", see section I.1 in [Bollobas] p. 1 ("If G is a graph, then V = V(G) is the vertex set of G, and E = E(G) is the edge set.") or section 1.1 in [Diestel] p. 2 ("The vertex set of graph G is referred to as V(G), its edge set as E(G).").

Instead of providing edges themselves, iEdg is intended to provide a function as mapping of "indices" (the domain of the function) to the edges (therefore called "set of indexed edges"), which allows for hyper-/pseudo-/multigraphs with more than one edge between two (or more) vertices. For example, e₁ = e(1) = { a, b } and e₂ = e(2) = { a, b } are two different edges connecting the same two vertices a and b (in a pseudograph). In section 1.10 of [Diestel] p. 28, the edge function is defined differently: as "map E -> V u. [V]^2 assigning to every edge either one or two vertices, its end.". Here, the domain is the set of abstract edges: for two different edges e₁ and e₂ connecting the same two vertices a and b, we would have e(e₁) = e(e₂) = { a, b }. Since the set of abstract edges can be chosen as index set, these definitions are equivalent.

The result of these functions are as expected: for a graph represented as ordered pair (𝐺 ∈ (V × V)), the set of vertices is (Vtx‘𝐺) = (1^st ‘𝐺) (see opvtxval 29059) and the set of (indexed) edges is (iEdg‘𝐺) = (2^nd ‘𝐺) (see opiedgval 29062), or if 𝐺 is given as ordered pair 𝐺 = ⟨𝑉, 𝐸⟩, the set of vertices is (Vtx‘𝐺) = 𝑉 (see opvtxfv 29060) and the set of (indexed) edges is (iEdg‘𝐺) = 𝐸 (see opiedgfv 29063).

And for a graph represented as extensible structure (𝐺 Struct ⟨(Base‘ndx), (.ef‘ndx)⟩), the set of vertices is (Vtx‘𝐺) = (Base‘𝐺) (see funvtxval 29074) and the set of (indexed) edges is (iEdg‘𝐺) = (.ef‘𝐺) (see funiedgval 29075), or if 𝐺 is given in its simplest form as extensible structure with two slots (𝐺 = {⟨(Base‘ndx), 𝑉⟩, ⟨(.ef‘ndx), 𝐸⟩}), the set of vertices is (Vtx‘𝐺) = 𝑉 (see struct2grvtx 29083) and the set of (indexed) edges is (iEdg‘𝐺) = 𝐸 (see struct2griedg 29084).

These two representations are convertible, see graop 29085 and grastruct 29086: If 𝐺 is a graph (for example 𝐺 = ⟨𝑉, 𝐸⟩), then 𝐻 = {⟨(Base‘ndx), (Vtx‘𝐺)⟩, ⟨(.ef‘ndx), (iEdg‘𝐺)⟩} represents essentially the same graph, and if 𝐺 is a graph (for example 𝐺 = {⟨(Base‘ndx), 𝑉⟩, ⟨(.ef‘ndx), 𝐸⟩}), then 𝐻 = ⟨(Vtx‘𝐺), (iEdg‘𝐺)⟩ represents essentially the same graph. In both cases, (Vtx‘𝐺) = (Vtx‘𝐻) and (iEdg‘𝐺) = (iEdg‘𝐻) hold. Theorems gropd 29087 and gropeld 29089 show that if any representation of a graph with vertices 𝑉 and edges 𝐸 has a certain property, then the ordered pair ⟨𝑉, 𝐸⟩ of the set of vertices and the set of edges (which is such a representation of a graph with vertices 𝑉 and edges 𝐸) has this property. Analogously, theorems grstructd 29088 and grstructeld 29090 show that if any representation of a graph with vertices 𝑉 and edges 𝐸 has a certain property, then any extensible structure with base set 𝑉 and value 𝐸 in the slot for edge functions (which is also such a representation of a graph with vertices 𝑉 and edges 𝐸) has this property.

Besides the usual way to represent graphs without edges (consisting of unconnected vertices only), which would be 𝐺 = ⟨𝑉, ∅⟩ or 𝐺 = {⟨(Base‘ndx), 𝑉⟩, ⟨(.ef‘ndx), ∅⟩}, a structure without a slot for edges can be used: 𝐺 = {⟨(Base‘ndx), 𝑉⟩}, see snstrvtxval 29093 and snstriedgval 29094. Analogously, the empty set ∅ can be used to represent the null graph, see vtxval0 29095 and iedgval0 29096, which can also be represented by 𝐺 = ⟨∅, ∅⟩ or 𝐺 = {⟨(Base‘ndx), ∅⟩, ⟨(.ef‘ndx), ∅⟩}. Even proper classes can be used to represent the null graph, see vtxvalprc 29101 and iedgvalprc 29102.

Other classes should not be used to represent graphs, because there could be a degenerate behavior of the vertex set and (indexed) edge functions, see vtxvalsnop 29097 resp. iedgvalsnop 29098, and vtxval3sn 29099 resp. iedgval3sn 29100. Avoid directly depending on this detail so that theorems will not depend on the Kuratowski construction of ordered pairs, see also the comment for df-op 4588.

17.1.2.1  Definitions and basic properties

Syntax

cvtx 29052

Extend class notation with the vertices of "graphs".

class Vtx

Syntax

ciedg 29053

Extend class notation with the indexed edges of "graphs".

class iEdg

Definition

df-vtx 29054

Define the function mapping a graph to the set of its vertices. This definition is very general: It defines the set of vertices for any ordered pair as its first component, and for any other class as its "base set". It is meaningful, however, only if the ordered pair represents a graph resp. the class is an extensible structure representing a graph. (Contributed by AV, 9-Jan-2020.) (Revised by AV, 20-Sep-2020.)

⊢ Vtx = (𝑔 ∈ V ↦ if(𝑔 ∈ (V × V), (1^st ‘𝑔), (Base‘𝑔)))

Definition

df-iedg 29055

Define the function mapping a graph to its indexed edges. This definition is very general: It defines the indexed edges for any ordered pair as its second component, and for any other class as its "edge function". It is meaningful, however, only if the ordered pair represents a graph resp. the class is an extensible structure (containing a slot for "edge functions") representing a graph. (Contributed by AV, 20-Sep-2020.)

⊢ iEdg = (𝑔 ∈ V ↦ if(𝑔 ∈ (V × V), (2^nd ‘𝑔), (.ef‘𝑔)))

Theorem

vtxval 29056

The set of vertices of a graph. (Contributed by AV, 9-Jan-2020.) (Revised by AV, 21-Sep-2020.)

⊢ (Vtx‘𝐺) = if(𝐺 ∈ (V × V), (1^st ‘𝐺), (Base‘𝐺))

Theorem

iedgval 29057

The set of indexed edges of a graph. (Contributed by AV, 21-Sep-2020.)

⊢ (iEdg‘𝐺) = if(𝐺 ∈ (V × V), (2^nd ‘𝐺), (.ef‘𝐺))

Theorem

1vgrex 29058

A graph with at least one vertex is a set. (Contributed by AV, 2-Mar-2021.)

⊢ 𝑉 = (Vtx‘𝐺)    ⇒   ⊢ (𝑁 ∈ 𝑉 → 𝐺 ∈ V)

17.1.2.2  The vertices and edges of a graph represented as ordered pair

Theorem

opvtxval 29059

The set of vertices of a graph represented as an ordered pair of vertices and indexed edges. (Contributed by AV, 9-Jan-2020.) (Revised by AV, 21-Sep-2020.)

⊢ (𝐺 ∈ (V × V) → (Vtx‘𝐺) = (1^st ‘𝐺))

Theorem

opvtxfv 29060

The set of vertices of a graph represented as an ordered pair of vertices and indexed edges as function value. (Contributed by AV, 21-Sep-2020.)

⊢ ((𝑉 ∈ 𝑋 ∧ 𝐸 ∈ 𝑌) → (Vtx‘⟨𝑉, 𝐸⟩) = 𝑉)

Theorem

opvtxov 29061

The set of vertices of a graph represented as an ordered pair of vertices and indexed edges as operation value. (Contributed by AV, 21-Sep-2020.)

⊢ ((𝑉 ∈ 𝑋 ∧ 𝐸 ∈ 𝑌) → (𝑉Vtx𝐸) = 𝑉)

Theorem

opiedgval 29062

The set of indexed edges of a graph represented as an ordered pair of vertices and indexed edges. (Contributed by AV, 21-Sep-2020.)

⊢ (𝐺 ∈ (V × V) → (iEdg‘𝐺) = (2^nd ‘𝐺))

Theorem

opiedgfv 29063

The set of indexed edges of a graph represented as an ordered pair of vertices and indexed edges as function value. (Contributed by AV, 21-Sep-2020.)

⊢ ((𝑉 ∈ 𝑋 ∧ 𝐸 ∈ 𝑌) → (iEdg‘⟨𝑉, 𝐸⟩) = 𝐸)

Theorem

opiedgov 29064

The set of indexed edges of a graph represented as an ordered pair of vertices and indexed edges as operation value. (Contributed by AV, 21-Sep-2020.)

⊢ ((𝑉 ∈ 𝑋 ∧ 𝐸 ∈ 𝑌) → (𝑉iEdg𝐸) = 𝐸)

Theorem

opvtxfvi 29065

The set of vertices of a graph represented as an ordered pair of vertices and indexed edges as function value. (Contributed by AV, 4-Mar-2021.)

⊢ 𝑉 ∈ V    &   ⊢ 𝐸 ∈ V    ⇒   ⊢ (Vtx‘⟨𝑉, 𝐸⟩) = 𝑉

Theorem

opiedgfvi 29066

The set of indexed edges of a graph represented as an ordered pair of vertices and indexed edges as function value. (Contributed by AV, 4-Mar-2021.)

⊢ 𝑉 ∈ V    &   ⊢ 𝐸 ∈ V    ⇒   ⊢ (iEdg‘⟨𝑉, 𝐸⟩) = 𝐸

17.1.2.3  The vertices and edges of a graph represented as extensible structure

Theorem

funvtxdmge2val 29067

The set of vertices of an extensible structure with (at least) two slots. (Contributed by AV, 12-Oct-2020.) (Revised by AV, 7-Jun-2021.) (Revised by AV, 12-Nov-2021.)

⊢ ((Fun (𝐺 ∖ {∅}) ∧ 2 ≤ (♯‘dom 𝐺)) → (Vtx‘𝐺) = (Base‘𝐺))

Theorem

funiedgdmge2val 29068

The set of indexed edges of an extensible structure with (at least) two slots. (Contributed by AV, 12-Oct-2020.) (Revised by AV, 7-Jun-2021.) (Revised by AV, 12-Nov-2021.)

⊢ ((Fun (𝐺 ∖ {∅}) ∧ 2 ≤ (♯‘dom 𝐺)) → (iEdg‘𝐺) = (.ef‘𝐺))

Theorem

funvtxdm2val 29069

The set of vertices of an extensible structure with (at least) two slots. (Contributed by AV, 22-Sep-2020.) (Revised by AV, 7-Jun-2021.) (Revised by AV, 12-Nov-2021.)

⊢ 𝐴 ∈ V    &   ⊢ 𝐵 ∈ V    ⇒   ⊢ ((Fun (𝐺 ∖ {∅}) ∧ 𝐴 ≠ 𝐵 ∧ {𝐴, 𝐵} ⊆ dom 𝐺) → (Vtx‘𝐺) = (Base‘𝐺))

Theorem

funiedgdm2val 29070

The set of indexed edges of an extensible structure with (at least) two slots. (Contributed by AV, 22-Sep-2020.) (Revised by AV, 7-Jun-2021.) (Revised by AV, 12-Nov-2021.)

⊢ 𝐴 ∈ V    &   ⊢ 𝐵 ∈ V    ⇒   ⊢ ((Fun (𝐺 ∖ {∅}) ∧ 𝐴 ≠ 𝐵 ∧ {𝐴, 𝐵} ⊆ dom 𝐺) → (iEdg‘𝐺) = (.ef‘𝐺))

Theorem

funvtxval0 29071

The set of vertices of an extensible structure with a base set and (at least) another slot. (Contributed by AV, 22-Sep-2020.) (Revised by AV, 7-Jun-2021.) (Revised by AV, 12-Nov-2021.)

⊢ 𝑆 ∈ V    ⇒   ⊢ ((Fun (𝐺 ∖ {∅}) ∧ 𝑆 ≠ (Base‘ndx) ∧ {(Base‘ndx), 𝑆} ⊆ dom 𝐺) → (Vtx‘𝐺) = (Base‘𝐺))

Theorem

basvtxval 29072

The set of vertices of a graph represented as an extensible structure with the set of vertices as base set. (Contributed by AV, 14-Oct-2020.) (Revised by AV, 12-Nov-2021.)

⊢ (𝜑 → 𝐺 Struct 𝑋)    &   ⊢ (𝜑 → 2 ≤ (♯‘dom 𝐺))    &   ⊢ (𝜑 → 𝑉 ∈ 𝑌)    &   ⊢ (𝜑 → ⟨(Base‘ndx), 𝑉⟩ ∈ 𝐺)    ⇒   ⊢ (𝜑 → (Vtx‘𝐺) = 𝑉)

Theorem

edgfiedgval 29073

The set of indexed edges of a graph represented as an extensible structure with the indexed edges in the slot for edge functions. (Contributed by AV, 14-Oct-2020.) (Revised by AV, 12-Nov-2021.)

⊢ (𝜑 → 𝐺 Struct 𝑋)    &   ⊢ (𝜑 → 2 ≤ (♯‘dom 𝐺))    &   ⊢ (𝜑 → 𝐸 ∈ 𝑌)    &   ⊢ (𝜑 → ⟨(.ef‘ndx), 𝐸⟩ ∈ 𝐺)    ⇒   ⊢ (𝜑 → (iEdg‘𝐺) = 𝐸)

Theorem

funvtxval 29074

The set of vertices of a graph represented as an extensible structure with vertices as base set and indexed edges. (Contributed by AV, 22-Sep-2020.) (Revised by AV, 7-Jun-2021.) (Revised by AV, 12-Nov-2021.)

⊢ ((Fun (𝐺 ∖ {∅}) ∧ {(Base‘ndx), (.ef‘ndx)} ⊆ dom 𝐺) → (Vtx‘𝐺) = (Base‘𝐺))

Theorem

funiedgval 29075

The set of indexed edges of a graph represented as an extensible structure with vertices as base set and indexed edges. (Contributed by AV, 21-Sep-2020.) (Revised by AV, 7-Jun-2021.) (Revised by AV, 12-Nov-2021.)

⊢ ((Fun (𝐺 ∖ {∅}) ∧ {(Base‘ndx), (.ef‘ndx)} ⊆ dom 𝐺) → (iEdg‘𝐺) = (.ef‘𝐺))

Theorem

structvtxvallem 29076

Lemma for structvtxval 29077 and structiedg0val 29078. (Contributed by AV, 23-Sep-2020.) (Revised by AV, 12-Nov-2021.)

⊢ 𝑆 ∈ ℕ    &   ⊢ (Base‘ndx) < 𝑆    &   ⊢ 𝐺 = {⟨(Base‘ndx), 𝑉⟩, ⟨𝑆, 𝐸⟩}    ⇒   ⊢ ((𝑉 ∈ 𝑋 ∧ 𝐸 ∈ 𝑌) → 2 ≤ (♯‘dom 𝐺))

Theorem

structvtxval 29077

The set of vertices of an extensible structure with a base set and another slot. (Contributed by AV, 23-Sep-2020.) (Proof shortened by AV, 12-Nov-2021.)

⊢ 𝑆 ∈ ℕ    &   ⊢ (Base‘ndx) < 𝑆    &   ⊢ 𝐺 = {⟨(Base‘ndx), 𝑉⟩, ⟨𝑆, 𝐸⟩}    ⇒   ⊢ ((𝑉 ∈ 𝑋 ∧ 𝐸 ∈ 𝑌) → (Vtx‘𝐺) = 𝑉)

Theorem

structiedg0val 29078

The set of indexed edges of an extensible structure with a base set and another slot not being the slot for edge functions is empty. (Contributed by AV, 23-Sep-2020.) (Proof shortened by AV, 12-Nov-2021.)

⊢ 𝑆 ∈ ℕ    &   ⊢ (Base‘ndx) < 𝑆    &   ⊢ 𝐺 = {⟨(Base‘ndx), 𝑉⟩, ⟨𝑆, 𝐸⟩}    ⇒   ⊢ ((𝑉 ∈ 𝑋 ∧ 𝐸 ∈ 𝑌 ∧ 𝑆 ≠ (.ef‘ndx)) → (iEdg‘𝐺) = ∅)

Theorem

structgrssvtxlem 29079

Lemma for structgrssvtx 29080 and structgrssiedg 29081. (Contributed by AV, 14-Oct-2020.) (Proof shortened by AV, 12-Nov-2021.)

⊢ (𝜑 → 𝐺 Struct 𝑋)    &   ⊢ (𝜑 → 𝑉 ∈ 𝑌)    &   ⊢ (𝜑 → 𝐸 ∈ 𝑍)    &   ⊢ (𝜑 → {⟨(Base‘ndx), 𝑉⟩, ⟨(.ef‘ndx), 𝐸⟩} ⊆ 𝐺)    ⇒   ⊢ (𝜑 → 2 ≤ (♯‘dom 𝐺))

Theorem

structgrssvtx 29080

The set of vertices of a graph represented as an extensible structure with vertices as base set and indexed edges. (Contributed by AV, 14-Oct-2020.) (Proof shortened by AV, 12-Nov-2021.)

⊢ (𝜑 → 𝐺 Struct 𝑋)    &   ⊢ (𝜑 → 𝑉 ∈ 𝑌)    &   ⊢ (𝜑 → 𝐸 ∈ 𝑍)    &   ⊢ (𝜑 → {⟨(Base‘ndx), 𝑉⟩, ⟨(.ef‘ndx), 𝐸⟩} ⊆ 𝐺)    ⇒   ⊢ (𝜑 → (Vtx‘𝐺) = 𝑉)

Theorem

structgrssiedg 29081

The set of indexed edges of a graph represented as an extensible structure with vertices as base set and indexed edges. (Contributed by AV, 14-Oct-2020.) (Proof shortened by AV, 12-Nov-2021.)

⊢ (𝜑 → 𝐺 Struct 𝑋)    &   ⊢ (𝜑 → 𝑉 ∈ 𝑌)    &   ⊢ (𝜑 → 𝐸 ∈ 𝑍)    &   ⊢ (𝜑 → {⟨(Base‘ndx), 𝑉⟩, ⟨(.ef‘ndx), 𝐸⟩} ⊆ 𝐺)    ⇒   ⊢ (𝜑 → (iEdg‘𝐺) = 𝐸)

Theorem

struct2grstr 29082

A graph represented as an extensible structure with vertices as base set and indexed edges is actually an extensible structure. (Contributed by AV, 23-Nov-2020.)

⊢ 𝐺 = {⟨(Base‘ndx), 𝑉⟩, ⟨(.ef‘ndx), 𝐸⟩}    ⇒   ⊢ 𝐺 Struct ⟨(Base‘ndx), (.ef‘ndx)⟩

Theorem

struct2grvtx 29083

The set of vertices of a graph represented as an extensible structure with vertices as base set and indexed edges. (Contributed by AV, 23-Sep-2020.)

⊢ 𝐺 = {⟨(Base‘ndx), 𝑉⟩, ⟨(.ef‘ndx), 𝐸⟩}    ⇒   ⊢ ((𝑉 ∈ 𝑋 ∧ 𝐸 ∈ 𝑌) → (Vtx‘𝐺) = 𝑉)

Theorem

struct2griedg 29084

The set of indexed edges of a graph represented as an extensible structure with vertices as base set and indexed edges. (Contributed by AV, 23-Sep-2020.) (Proof shortened by AV, 12-Nov-2021.)

⊢ 𝐺 = {⟨(Base‘ndx), 𝑉⟩, ⟨(.ef‘ndx), 𝐸⟩}    ⇒   ⊢ ((𝑉 ∈ 𝑋 ∧ 𝐸 ∈ 𝑌) → (iEdg‘𝐺) = 𝐸)

Theorem

graop 29085

Any representation of a graph 𝐺 (especially as extensible structure 𝐺 = {⟨(Base‘ndx), 𝑉⟩, ⟨(.ef‘ndx), 𝐸⟩}) is convertible in a representation of the graph as ordered pair. (Contributed by AV, 7-Oct-2020.)

⊢ 𝐻 = ⟨(Vtx‘𝐺), (iEdg‘𝐺)⟩    ⇒   ⊢ ((Vtx‘𝐺) = (Vtx‘𝐻) ∧ (iEdg‘𝐺) = (iEdg‘𝐻))

Theorem

grastruct 29086

Any representation of a graph 𝐺 (especially as ordered pair 𝐺 = ⟨𝑉, 𝐸⟩) is convertible in a representation of the graph as extensible structure. (Contributed by AV, 8-Oct-2020.)

⊢ 𝐻 = {⟨(Base‘ndx), (Vtx‘𝐺)⟩, ⟨(.ef‘ndx), (iEdg‘𝐺)⟩}    ⇒   ⊢ ((Vtx‘𝐺) = (Vtx‘𝐻) ∧ (iEdg‘𝐺) = (iEdg‘𝐻))

Theorem

gropd 29087*

If any representation of a graph with vertices 𝑉 and edges 𝐸 has a certain property 𝜓, then the ordered pair ⟨𝑉, 𝐸⟩ of the set of vertices and the set of edges (which is such a representation of a graph with vertices 𝑉 and edges 𝐸) has this property. (Contributed by AV, 11-Oct-2020.)

⊢ (𝜑 → ∀𝑔(((Vtx‘𝑔) = 𝑉 ∧ (iEdg‘𝑔) = 𝐸) → 𝜓))    &   ⊢ (𝜑 → 𝑉 ∈ 𝑈)    &   ⊢ (𝜑 → 𝐸 ∈ 𝑊)    ⇒   ⊢ (𝜑 → [⟨𝑉, 𝐸⟩ / 𝑔]𝜓)

Theorem

grstructd 29088*

If any representation of a graph with vertices 𝑉 and edges 𝐸 has a certain property 𝜓, then any structure with base set 𝑉 and value 𝐸 in the slot for edge functions (which is such a representation of a graph with vertices 𝑉 and edges 𝐸) has this property. (Contributed by AV, 12-Oct-2020.) (Revised by AV, 9-Jun-2021.)

⊢ (𝜑 → ∀𝑔(((Vtx‘𝑔) = 𝑉 ∧ (iEdg‘𝑔) = 𝐸) → 𝜓))    &   ⊢ (𝜑 → 𝑉 ∈ 𝑈)    &   ⊢ (𝜑 → 𝐸 ∈ 𝑊)    &   ⊢ (𝜑 → 𝑆 ∈ 𝑋)    &   ⊢ (𝜑 → Fun (𝑆 ∖ {∅}))    &   ⊢ (𝜑 → 2 ≤ (♯‘dom 𝑆))    &   ⊢ (𝜑 → (Base‘𝑆) = 𝑉)    &   ⊢ (𝜑 → (.ef‘𝑆) = 𝐸)    ⇒   ⊢ (𝜑 → [𝑆 / 𝑔]𝜓)

Theorem

gropeld 29089*

If any representation of a graph with vertices 𝑉 and edges 𝐸 is an element of an arbitrary class 𝐶, then the ordered pair ⟨𝑉, 𝐸⟩ of the set of vertices and the set of edges (which is such a representation of a graph with vertices 𝑉 and edges 𝐸) is an element of this class 𝐶. (Contributed by AV, 11-Oct-2020.)

⊢ (𝜑 → ∀𝑔(((Vtx‘𝑔) = 𝑉 ∧ (iEdg‘𝑔) = 𝐸) → 𝑔 ∈ 𝐶))    &   ⊢ (𝜑 → 𝑉 ∈ 𝑈)    &   ⊢ (𝜑 → 𝐸 ∈ 𝑊)    ⇒   ⊢ (𝜑 → ⟨𝑉, 𝐸⟩ ∈ 𝐶)

Theorem

grstructeld 29090*

If any representation of a graph with vertices 𝑉 and edges 𝐸 is an element of an arbitrary class 𝐶, then any structure with base set 𝑉 and value 𝐸 in the slot for edge functions (which is such a representation of a graph with vertices 𝑉 and edges 𝐸) is an element of this class 𝐶. (Contributed by AV, 12-Oct-2020.) (Revised by AV, 9-Jun-2021.)

⊢ (𝜑 → ∀𝑔(((Vtx‘𝑔) = 𝑉 ∧ (iEdg‘𝑔) = 𝐸) → 𝑔 ∈ 𝐶))    &   ⊢ (𝜑 → 𝑉 ∈ 𝑈)    &   ⊢ (𝜑 → 𝐸 ∈ 𝑊)    &   ⊢ (𝜑 → 𝑆 ∈ 𝑋)    &   ⊢ (𝜑 → Fun (𝑆 ∖ {∅}))    &   ⊢ (𝜑 → 2 ≤ (♯‘dom 𝑆))    &   ⊢ (𝜑 → (Base‘𝑆) = 𝑉)    &   ⊢ (𝜑 → (.ef‘𝑆) = 𝐸)    ⇒   ⊢ (𝜑 → 𝑆 ∈ 𝐶)

Theorem

setsvtx 29091

The vertices of a structure with a base set and an inserted resp. replaced slot for the edge function. (Contributed by AV, 18-Jan-2020.) (Revised by AV, 16-Nov-2021.)

⊢ 𝐼 = (.ef‘ndx)    &   ⊢ (𝜑 → 𝐺 Struct 𝑋)    &   ⊢ (𝜑 → (Base‘ndx) ∈ dom 𝐺)    &   ⊢ (𝜑 → 𝐸 ∈ 𝑊)    ⇒   ⊢ (𝜑 → (Vtx‘(𝐺 sSet ⟨𝐼, 𝐸⟩)) = (Base‘𝐺))

Theorem

setsiedg 29092

The (indexed) edges of a structure with a base set and an inserted resp. replaced slot for the edge function. (Contributed by AV, 7-Jun-2021.) (Revised by AV, 16-Nov-2021.)

⊢ 𝐼 = (.ef‘ndx)    &   ⊢ (𝜑 → 𝐺 Struct 𝑋)    &   ⊢ (𝜑 → (Base‘ndx) ∈ dom 𝐺)    &   ⊢ (𝜑 → 𝐸 ∈ 𝑊)    ⇒   ⊢ (𝜑 → (iEdg‘(𝐺 sSet ⟨𝐼, 𝐸⟩)) = 𝐸)

17.1.2.4  Representations of graphs without edges

Theorem

snstrvtxval 29093

The set of vertices of a graph without edges represented as an extensible structure with vertices as base set and no indexed edges. See vtxvalsnop 29097 for the (degenerate) case where 𝑉 = (Base‘ndx). (Contributed by AV, 23-Sep-2020.)

⊢ 𝑉 ∈ V    &   ⊢ 𝐺 = {⟨(Base‘ndx), 𝑉⟩}    ⇒   ⊢ (𝑉 ≠ (Base‘ndx) → (Vtx‘𝐺) = 𝑉)

Theorem

snstriedgval 29094

The set of indexed edges of a graph without edges represented as an extensible structure with vertices as base set and no indexed edges. See iedgvalsnop 29098 for the (degenerate) case where 𝑉 = (Base‘ndx). (Contributed by AV, 24-Sep-2020.)

⊢ 𝑉 ∈ V    &   ⊢ 𝐺 = {⟨(Base‘ndx), 𝑉⟩}    ⇒   ⊢ (𝑉 ≠ (Base‘ndx) → (iEdg‘𝐺) = ∅)

17.1.2.5  Degenerated cases of representations of graphs

Theorem

vtxval0 29095

Degenerated case 1 for vertices: The set of vertices of the empty set is the empty set. (Contributed by AV, 24-Sep-2020.)

⊢ (Vtx‘∅) = ∅

Theorem

iedgval0 29096

Degenerated case 1 for edges: The set of indexed edges of the empty set is the empty set. (Contributed by AV, 24-Sep-2020.)

⊢ (iEdg‘∅) = ∅

Theorem

vtxvalsnop 29097

Degenerated case 2 for vertices: The set of vertices of a singleton containing an ordered pair with equal components is the singleton containing the component. (Contributed by AV, 24-Sep-2020.) (Proof shortened by AV, 15-Jul-2022.) (Avoid depending on this detail.)

⊢ 𝐵 ∈ V    &   ⊢ 𝐺 = {⟨𝐵, 𝐵⟩}    ⇒   ⊢ (Vtx‘𝐺) = {𝐵}

Theorem

iedgvalsnop 29098

Degenerated case 2 for edges: The set of indexed edges of a singleton containing an ordered pair with equal components is the singleton containing the component. (Contributed by AV, 24-Sep-2020.) (Proof shortened by AV, 15-Jul-2022.) (Avoid depending on this detail.)

⊢ 𝐵 ∈ V    &   ⊢ 𝐺 = {⟨𝐵, 𝐵⟩}    ⇒   ⊢ (iEdg‘𝐺) = {𝐵}

Theorem

vtxval3sn 29099

Degenerated case 3 for vertices: The set of vertices of a singleton containing a singleton containing a singleton is the innermost singleton. (Contributed by AV, 24-Sep-2020.) (Avoid depending on this detail.)

⊢ 𝐴 ∈ V    ⇒   ⊢ (Vtx‘{{{𝐴}}}) = {𝐴}

Theorem

iedgval3sn 29100

Degenerated case 3 for edges: The set of indexed edges of a singleton containing a singleton containing a singleton is the innermost singleton. (Contributed by AV, 24-Sep-2020.) (Avoid depending on this detail.)

⊢ 𝐴 ∈ V    ⇒   ⊢ (iEdg‘{{{𝐴}}}) = {𝐴}