How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Periodic two-velocity heat limit for well-prepared data
Statement
Assume . Fix , , and a nonnegative . For each , let solve the two-velocity periodic model with well-prepared initial data , and put . Let , which has units , and define the heat evolution
Then is the smooth periodic solution of with , and for every finite ,
This conclusion concerns only the density of the stated linear two-velocity model with well-prepared data.
Statement references
Facts & Assumptions
Given: , the scaling and Fourier conventions of Two-velocity periodic diffusive-scaling model, , and with .
Assume the Axiom of Countable Choice, (The Axiom of Countable Choice ()), as required by the Fourier basis supplier.
Two-velocity periodic diffusive-scaling model: , , , and obey the two displayed transport/switching equations.
Well-posedness, positivity and contraction for two-velocity transport: for these data the unique global smooth solution exists, and the two-component evolution contracts the norm.
The Fourier basis and Parseval's identity on the finite torus: under , the characters form an orthonormal basis of , so Fourier expansions and Parseval hold. The change of variable transfers this statement to with normalized measure and coefficients .
The second fundamental theorem: if is differentiable on with and is integrable, then : integration of a continuous derivative on a compact interval gives the endpoint difference. Applied repeatedly to periodic smooth initial data, it gives rapid decay of their Fourier coefficients by integration by parts.
Proof
Define . Adding the two equations in [F1] gives . Subtracting them and multiplying by gives . The initial condition implies .
Under [A1], take Fourier coefficients in in these two identities, with and from [F1]; differentiate under the compact spatial integral using the smooth solution [F2], and integrate by parts in real and imaginary parts separately using [F4] after the measure-preserving rescaling . Then satisfies , , and . The heat series in the Statement has coefficients .
Repeated integration by parts in the real and imaginary parts using [F4] gives for every integer ; convergence follows by grouping after choosing more than derivatives. Therefore the heat series and every differentiated series converge uniformly on compact time intervals, and its coefficient equation proves with . For any other smooth periodic solution , integration by parts in its Fourier coefficients gives with initial value . Multiplying by shows that has zero derivative, so for every and . Fourier completeness [F3] therefore gives as classes for each fixed , hence almost everywhere. Both are continuous in ; if they differed at a point, their difference would be bounded away from zero on some nonempty open arc, which has positive normalized Lebesgue measure . This contradicts equality almost everywhere, so pointwise for every .
For , the mass mode is constant and equals the heat mode. Fix . For all sufficiently small with , set and . The solution of the scalar mode equation is , where and ; these coefficients solve and . Rationalizing the slow root gives , while , , and . Put ; both and are nonpositive, so integrating the derivative of with [F4] gives on . Since both exponentials have modulus at most one, . The right side tends to zero independently of , proving uniform convergence of this Fourier mode.
Let denote the Fourier projection onto , applied componentwise to pairs. The mode equations from step 2.1 are decoupled, so the projected pair solves the same system with initial pair ; uniqueness in [F2] identifies it with that evolution. Applying [F2] gives . Since , it follows that . The heat multiplier has modulus at most one, hence .
By Parseval [F3], as . Given , choose so that twice this tail is below . The finitely many modes converge uniformly on by step 3.2, so for all sufficiently small their combined error is below . Step 3.3 bounds the remaining density difference by twice the chosen tail, uniformly in and . Therefore for all sufficiently small , proving the claim.
Depends on
Dependency tree · 2 levels
Sources
- Thomas Hillen and Amanda Swan, The Diffusion Limit of Transport Equations in Biology, Lecture Notes in Mathematics 2167, 2016
- Thomas Hillen and Hans G. Othmer, The Diffusion Limit of Transport Equations Derived from Velocity-Jump Processes, SIAM Journal on Applied Mathematics 61(3), 2000
- Edward A. Codling, Michael J. Plank and Simon Benhamou, Random Walk Models in Biology, Journal of the Royal Society Interface 5(25), 2008