FormalConjectures/ErdosProblems/160.lean
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- Lean4 Domain Explanation Language
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Project sources: Pinned project documentation, Formal Conjectures paper, arXiv v1
5 declarations, 4 contain sorry, 0 declared as axioms
Erdős Problem 160
Reference: erdosproblems.com/160
Imports (1)
- def
Erdos160.erdos_160.hDocumented declaration: h line 34 sourceSource documentation
Let $h(n)$ be the smallest $k$ such that $\{1,\ldots,n\}$ can be coloured with $k$ colours so that every four-term arithmetic progression must contain at least three distinct colours.
standard axioms: Classical.choice, Quot.sound, propext what this means
Statement uses:
NatProof uses:
InfSet.sInf,Set.ofPred,Exists,Subtype,Membership.mem,Finset,Finset.Icc,OfNat.ofNat,Fin,Set,And,LE.le, Set.IsAPOfLength,ENat,Set.ncard,Set.image15 instances, coercions and auxiliary constants left out.
noncomputable def erdos_160.h (n : ℕ) : ℕ := …
- theorem
Erdos160.erdos_160.known_upperOn Mathoverflow user leechlattice shows that $h(n) \ll n^{\frac 2 3}$ sorry line 48 sourceSource documentation
On Mathoverflow user leechlattice shows that $h(n) \ll n^{\frac 2 3}$.
L4DEL explanation
On Mathoverflow user leechlattice shows that $h(n) \ll n^{\frac 2 3}$.
Sources and attribution: Pinned Lean source (1646ca16afd6)
depends on sorry what this means
Statement uses:
Asymptotics.IsBigO,Nat,Real,Filter.atTop, Erdos160.erdos_160.h,HPow.hPow,HDiv.hDiv,OfNat.ofNatProof uses:
sorryAx,Lean.Name,Bool.false,Lean.Name.num,Lean.Name.str,Lean.Name.anonymous26 instances, coercions and auxiliary constants left out.
Tactic trace: 1 steps
Open to load the checked before-and-after goal states.
theorem erdos_160.known_upper : (fun n => (erdos_160.h n : ℝ)) =O[atTop] fun n => (n : ℝ) ^ ((2 : ℝ) / 3) := by …Mentions: Erdos160.erdos_160.h
- theorem
Erdos160.erdos_160.better_upperEstimate $h(n)$ by finding a better upper bound sorry line 58 sourceSource documentation
Estimate $h(n)$ by finding a better upper bound.
depends on sorry what this means
Statement uses:
Nat,Real,sorryAx,Bool.false,And,Asymptotics.IsBigO,Filter.atTop, Erdos160.erdos_160.h,Asymptotics.IsLittleO,HPow.hPow,HDiv.hDiv,OfNat.ofNatProof uses:
Lean.Name,Lean.Name.num,Lean.Name.str,Lean.Name.anonymous26 instances, coercions and auxiliary constants left out.
Tactic trace: 1 steps
Open to load the checked before-and-after goal states.
theorem erdos_160.better_upper : let upper_bound : ℕ → ℝ := answer(sorry) … - theorem
Erdos160.erdos_160.better_lowerEstimate $h(n)$ by finding a better lower bound sorry line 68 sourceSource documentation
Estimate $h(n)$ by finding a better lower bound.
depends on sorry what this means
Statement uses:
Nat,Real,sorryAx,Bool.false,And,Asymptotics.IsBigO,Filter.atTop, Erdos160.erdos_160.h,GT.gt,OfNat.ofNat,Real.exp,HMul.hMul,HPow.hPow,Real.log,HDiv.hDiv,Asymptotics.IsLittleOProof uses:
Lean.Name,Lean.Name.num,Lean.Name.str,Lean.Name.anonymous40 instances, coercions and auxiliary constants left out.
Tactic trace: 1 steps
Open to load the checked before-and-after goal states.
theorem erdos_160.better_lower: let lower_bound : ℕ → ℝ := answer(sorry) … - theorem
Erdos160.erdos_160.variants.known_lowerThe observation of Zachary Hunter in that question coupled with the bounds of Kelley-Meka KeMe23 imply that $$h(N) \gg \exp(c(\log N)^{\frac 1 {12}})$$ for some $c > 0$ sorry line 83 sourceSource documentation
The observation of Zachary Hunter in that question coupled with the bounds of Kelley-Meka KeMe23 imply that $$h(N) \gg \exp(c(\log N)^{\frac 1 {12}})$$ for some $c > 0$.
L4DEL explanation
The observation of Zachary Hunter in that question coupled with the bounds of Kelley-Meka KeMe23 imply that $$h(N) \gg \exp(c(\log N)^{\frac 1 {12}})$$ for some $c > 0$.
Sources and attribution: Pinned Lean source (1646ca16afd6)
depends on sorry what this means
Statement uses:
Exists,Real,And,GT.gt,OfNat.ofNat,Asymptotics.IsBigO,Nat,Filter.atTop,Real.exp,HMul.hMul,HPow.hPow,Real.log,HDiv.hDiv, Erdos160.erdos_160.hProof uses:
sorryAx,Lean.Name,Bool.false,Lean.Name.num,Lean.Name.str,Lean.Name.anonymous40 instances, coercions and auxiliary constants left out.
Tactic trace: 1 steps
Open to load the checked before-and-after goal states.
theorem erdos_160.variants.known_lower : ∃ c > 0, (fun (n : ℕ) => exp (c * log (n : ℝ) ^ ((1 : ℝ) / 12))) =O[atTop] fun n => (erdos_160.h n : ℝ):= by …Mentions: c, Erdos160.erdos_160.h