2 Exponential sums in Lp

Recall: studying f(x)=∑⁡ξ∈Re(ξ⋅x). When R does not have (linear) structure, expect |f(x)|∼|R|12 (“sqrt cancellation”) in an appropriate sense (in Lp), more than when R is structured.

Linear R f(x)=∑⁡n=1Ne(nx) vs convex R g(x)=∑⁡n=1Ne(n2x).

Have

∫[0,1]|f(x)|2dx=N=∫[0,1]|g(x)|2dx.

Have |f(x)|∼N on [0,cN−1], and |g(x)|∼N on [0,cN−2].

PIC

L2 does not distinguish f,g. L∞ does not distinguish. However, 2<p<∞ does.

What about 1≤p≤2? We don’t usually study this range because the estimates tend to be trivial / not interesting.

Focus on 2<p<∞. Preduct size of

∫[0,1]|f|p.

Square root cancellation lower bound:

N=∫[0,1]|f|2≤Hölder’s(∫[0,1]|f|2⋅p2)2p(1)□

⟹Np∕2≤∫[0,1]|f|p.

Constant integral lower bound:

∫[0,1]|f|p≥∫[0,cN−1]|f|p≳NpN−1∫[0,1]|g|p≥∫[0,cN−2]|g|p≳NpN−2

∫|f|p≲Np∕2+Np−1, ∫|g|p≲Np∕2+Np−2.

Note that for the f bound, Np−1 is bigger than Np−1 (as long as p>2), so the constant integral dominates!

For g, if 2≤p≤4, the square root cancellation dominates, but for p>4 the constant integral takes over.

Assuming:

Theorem 2.1. - p>2 - bn∈ℂ Then:

∫|∑nbne(nx)|p≤Np2−1∥bn∥2p.

Proof. Consider: ∑⁡n=1Nbne(nx), bn∈ℂ.

∫[0,1]|∑nbne(nx)|pdx≤∥∑nbne(nx)∥∞p−2∫[0,1]|∑nbne(nx)|2dx≤(N12∥bn∥2)p−2∥bn∥22CS=Np2−1∥bn∥2p□

Note that this is sharp when bn≡1.

∑⁡n=1Nbne(n2x). Focus on p=4.

∫[0,1]|∑nbne(n2x)|4dx=∑n1∑n2∑n3∑n4bn1bn2bn3¯bn4¯∫[0,1]e((n12+n22−n32−n42)x)dx.

The integral vanishes unless n12−n32=n42−n22.

Number Theory lemma: If m∈ℤ, then

# divisors of m≲log⁡m.

Follows from unique prime factorisation.

Warning. The above lemma is false.

See correction later.

For fixed n1,n3,

#{(n2,n4):n12−n32=(n4+n2)(n4−n2)}⏟=:Sn1,n3≲ log ⁡⁡N.

Hence

∫[0,1]|∑nbne(n2x)|4dx≤∑n1∑n3|bn1bn3||∑(n2,n4)∈Sn1,n3bn2bn4¯|≲(log⁡N)∥bn∥24

We will now use ≾ to mean ≲ up to powers of log⁡N.

2<p<4: 1p=𝜃2+1−𝜃4, 𝜃∈[0,1], h=∑⁡nbne(n2x), ∥h∥p≤∥h∥2𝜃∥h∥41−𝜃≾∥bn∥2𝜃∥bn∥21−𝜃≈∥bn∥2.

p≥4:

∫[0,1]|h|p≾∥h∥∞p−4∥bn∥24≤CS(N12∥bn∥2)p−4∥bn∥24≈Np2−2∥bn∥2p.

Assuming:

Theorem 2.2. - 2>p Then:

∫|∑nbne(n2x)|pdx≾(1=Np2−2)∥bn∥2p.

Sharp by bn≡1.

Positive take away: estimates are sharp, proofs are elementary. Easy to think of sharp examples.

Number Theory counting idea shows:

∫[0,1]2|u(x,t)|6dxdt≾∥bn∥26u(x,t)=∑|n|∼Nn∈ℤbne(nx+n2t)∫[0,1]3|u(x,t)|4dxdt≾∥bn∥24u(x,t)=∑|n|∼Nn∈ℤ2bne(n⋅x+|n|2t)

Sharp, 6,4=pcrit.

Strichartz estimate for periodic Schrödinger equation, observed by Bourgain in 1990s.

Negatives: on 𝕋3 → pcrit=103, but this technique can only work on even integer values of p.

𝕋1, 𝕋2 only sharp Strichartz estimates per Schrödinger until 2015!

2015: Bourgain-Demeter proved (l2,Lp) sharp decoupling estimate. Gives sharp Strichartz estimate for Schrödinger in 𝕋d for all d.

Proved earlier:

N−2∫[0,N2]|∑n∼Ne(n2N2x)|pdx≤(1+Np2−2)∥bn∥2p.

(where n∼N means N≤n≤2N).

Conjecture:

−∫[0,N2]|∑n∈Nbne(anx)|pdx≲(1+Np2−2)∥bn∥2p

an∈[0,1], an+1−an∼1N, an+2−an+1−(an+1−an)∼1N2.

Example: {an}∼{n3N3}n=N2N.