Samplinglib
Lean gate not recorded for this source state main · 0e31a3cda412

New companion frontiers

Smoothed Picard HMC, Proximal BPS, and their proxy-stable composition: two source cases, one shared proof route; local formalization remains open.

Read the frontier theorems and proof graph → · Reusable proof technology →

Sampling frontier · source-linked theorem casebook

SampleWiki in ASTIS

A mathematical reading interface for frontier sampling results. Every case separates what the source states, how the proof runs, what assumptions are inherited, and what Lean has actually verified.

Cross-library worked problem · sampling structure meets quantum state preparation

Smooth auxiliary states for Schrödingerisation of PDEs

Jin–Liu–Ma’s Schrödingerisation construction for PDEs with physical boundary or interface conditions introduces a smooth auxiliary \(p\)-register initial state. If its \(2^{n_p}\) grid amplitudes are treated as unrelated data, generic loading is exponential in the register width. QuantumComputinglib/ASPBE instead exploits the exact Hermite–Bernstein/tensor-train representation and proves a constructive circuit bound

\[G\le 48n_p(2k+6)^3,\qquad q=\lceil\log_2(2k+6) ceil.\]

Thus, for fixed smoothness order \(k\), the gate count is linear in \(n_p\), rather than the generic \(\Theta(2^{n_p})\) amplitude-loading dependence. This is a SampleWiki-style lesson beyond sampling itself: the decisive question is often whether analytical structure exposes a bounded-memory representation before one accepts a black-box oracle or dense table.

Jin–Liu–Ma: source PDE / Schrödingerisation construction · Holmes–Matsuura: prior smooth-function-to-MPS state-preparation route

Open the Lean-verified QuantumComputinglib construction and proof →

Cross-library pointer only: Samplinglib does not claim this quantum theorem as a local Lean result, and the general function-to-MPS idea is prior art.

Choose a mathematical regime
Current formalization focus

Ideal proximal chain

Theorem statement
\[\operatorname{KL}(\mu_n^X\Vert\pi^X)\le \frac{W_2^2(\mu_0^X,\pi^X)}{nh}\]
Open theorem, proof route, and Lean boundary →