AutoSamplingTheory.TechnicalLemmas.InformationTheory.FisherTransport
3 named declarations scanned from AutoSamplingTheory/TechnicalLemmas/InformationTheory/FisherTransport.lean.
Declarations
theorem AutoSamplingTheory.TechnicalLemmas.InformationTheory.FisherTransport.sq_div_le_fisher_of_sq_le_mul Partial Not mapped
- Divide a Fisher--transport inequality by a positive squared transport radius. This is the algebraic step used in Chewi Theorem 8.4.1 after Wasserstein geodesic convexity and Cauchy--Schwarz establish `kl^2 ≤ fi * R2`.
theorem sq_div_le_fisher_of_sq_le_mul
{kl fi R2 : ℝ}
(hR2 : 0 < R2)
(hbridge : kl ^ 2 ≤ fi * R2) :
kl ^ 2 / R2 ≤ fi := by
rw [div_le_iff₀ hR2]
exact hbridge
/-- Combine Fisher--transport control with the negative one-half factor from
heat-flow KL dissipation.
The conclusion is written as `-((kl^2 / R2) / 2)` to keep this lemma purely
order-algebraic; source-facing assembly may rewrite it as
`-kl^2 / (2 * R2)`. -/
AutoSamplingTheory/TechnicalLemmas/InformationTheory/FisherTransport.lean:28published source at ed709a7f320d
theorem AutoSamplingTheory.TechnicalLemmas.InformationTheory.FisherTransport.neg_half_fisher_le_neg_half_sq_div Partial Not mapped
- Combine Fisher--transport control with the negative one-half factor from heat-flow KL dissipation. The conclusion is written as `-((kl^2 / R2) / 2)` to keep this lemma purely order-algebraic; source-facing assembly may rewrite it as `-kl^2 / (2 * R2)`.
theorem neg_half_fisher_le_neg_half_sq_div
{kl fi R2 : ℝ}
(hR2 : 0 < R2)
(hbridge : kl ^ 2 ≤ fi * R2) :
-(fi / 2) ≤ -((kl ^ 2 / R2) / 2) := by
have hratio : kl ^ 2 / R2 ≤ fi :=
sq_div_le_fisher_of_sq_le_mul hR2 hbridge
linarith
/-- Source-shaped algebraic composition: if the KL derivative is exactly
`-FI/2`, then the Fisher--transport inequality gives the reciprocal-KL style
differential upper bound used in the proximal proof. -/
AutoSamplingTheory/TechnicalLemmas/InformationTheory/FisherTransport.lean:42published source at ed709a7f320d
theorem AutoSamplingTheory.TechnicalLemmas.InformationTheory.FisherTransport.kl_derivative_upper_bound_of_fisher_transport Partial Not mapped
- Source-shaped algebraic composition: if the KL derivative is exactly `-FI/2`, then the Fisher--transport inequality gives the reciprocal-KL style differential upper bound used in the proximal proof.
theorem kl_derivative_upper_bound_of_fisher_transport
{kl fi R2 kdot : ℝ}
(hR2 : 0 < R2)
(hbridge : kl ^ 2 ≤ fi * R2)
(hdiss : kdot = -(fi / 2)) :
kdot ≤ -((kl ^ 2 / R2) / 2) := by
rw [hdiss]
exact neg_half_fisher_le_neg_half_sq_div hR2 hbridge
end FisherTransport
end InformationTheory
end TechnicalLemmas
end AutoSamplingTheory
AutoSamplingTheory/TechnicalLemmas/InformationTheory/FisherTransport.lean:54published source at ed709a7f320d
Complete Lean source
AutoSamplingTheory/TechnicalLemmas/InformationTheory/FisherTransport.lean — full module with imports and context
import Mathlib.Tactic
/-!
# Fisher--transport algebra leaves
Pure real-field consequences of the source inequality
`KL^2 ≤ FI * W2^2`.
This file deliberately does **not** define relative Fisher information or
Wasserstein distance. Those analytic objects have regularity and measure-level
contracts owned by the corresponding shared ASTIS layers. The leaves here are
reusable once those layers supply non-negative real values satisfying the
source inequality.
-/
namespace AutoSamplingTheory
namespace TechnicalLemmas
namespace InformationTheory
namespace FisherTransport
/-- Divide a Fisher--transport inequality by a positive squared transport
radius.
This is the algebraic step used in Chewi Theorem 8.4.1 after Wasserstein
geodesic convexity and Cauchy--Schwarz establish
`kl^2 ≤ fi * R2`. -/
theorem sq_div_le_fisher_of_sq_le_mul
{kl fi R2 : ℝ}
(hR2 : 0 < R2)
(hbridge : kl ^ 2 ≤ fi * R2) :
kl ^ 2 / R2 ≤ fi := by
rw [div_le_iff₀ hR2]
exact hbridge
/-- Combine Fisher--transport control with the negative one-half factor from
heat-flow KL dissipation.
The conclusion is written as `-((kl^2 / R2) / 2)` to keep this lemma purely
order-algebraic; source-facing assembly may rewrite it as
`-kl^2 / (2 * R2)`. -/
theorem neg_half_fisher_le_neg_half_sq_div
{kl fi R2 : ℝ}
(hR2 : 0 < R2)
(hbridge : kl ^ 2 ≤ fi * R2) :
-(fi / 2) ≤ -((kl ^ 2 / R2) / 2) := by
have hratio : kl ^ 2 / R2 ≤ fi :=
sq_div_le_fisher_of_sq_le_mul hR2 hbridge
linarith
/-- Source-shaped algebraic composition: if the KL derivative is exactly
`-FI/2`, then the Fisher--transport inequality gives the reciprocal-KL style
differential upper bound used in the proximal proof. -/
theorem kl_derivative_upper_bound_of_fisher_transport
{kl fi R2 kdot : ℝ}
(hR2 : 0 < R2)
(hbridge : kl ^ 2 ≤ fi * R2)
(hdiss : kdot = -(fi / 2)) :
kdot ≤ -((kl ^ 2 / R2) / 2) := by
rw [hdiss]
exact neg_half_fisher_le_neg_half_sq_div hR2 hbridge
end FisherTransport
end InformationTheory
end TechnicalLemmas
end AutoSamplingTheory