InnerLayer (GGJ) - NEW - rotated-ray collocation backend (:ray), robust to |Q| ~ 500

Project.toml

@@ -25,6 +25,7 @@ PlotlyJS = "f0f68f2c-4968-5e81-91da-67840de0976a"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 QuadGK = "1fd47b50-473d-5c70-9696-f719f8f3bcdc"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Roots = "f2b01f46-fcfa-551c-844a-d8ac1e96c665"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
@@ -57,14 +58,11 @@ QuadGK = "2.11.3"
 Roots = "2.2.13"
 SparseArrays = "1"
 SpecialFunctions = "2.5.1"
+Random = "1"
 StaticArrays = "1.9.15"
 Statistics = "1"
 TOML = "1"
 Test = "1"
 julia = "1.11"
 
-[extras]
-Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 
-[targets]
-test = ["Random"]

src/InnerLayer/GGJ/GGJ.jl

@@ -1,15 +1,20 @@
 # GGJ.jl
 #
-# Glasser–Greene–Johnson resistive inner-layer model. Provides two
+# Glasser–Greene–Johnson resistive inner-layer model. Provides three
 # interchangeable solvers selected via the `solver` type-parameter of
 # `GGJModel`:
 #
-#   - `:shooting`  – stable backward shoot from X_max → 0 (Phase 3)
-#   - `:galerkin`  – Hermite-cubic finite element method (Phase 4)
+#   - `:shooting`  – stable backward shoot from X_max → 0;
+#                    numerically stable only for |Q| ≪ 1, should not be used
+#   - `:galerkin`  – Hermite-cubic finite element method;
+#                    real-axis method, degrades for |Q| ≳ 1 off the real axis
+#   - `:ray`       – rotated-contour spectral-element collocation (Ray.jl);
+#                    robust to |Q| ~ 500 on/near the imaginary axis
 #
-# Both solvers share the same `inps` Wasow asymptotic-basis kernel
-# (`InnerAsymptotics.jl`) for the large-x boundary condition. They return
-# the parity-projected matching data `(Δ_odd, Δ_even)` of GWP2016 Eqs. (34)–(35).
+# All solvers share the same `inps` Wasow asymptotic-basis kernel
+# (`InnerAsymptotics.jl`, complex-x extension in `RayAsymptotics.jl`) for the
+# large-x boundary condition. They return the parity-projected matching data
+# `(Δ_odd, Δ_even)` of GWP2016 Eqs. (34)–(35) in the same (deltac) convention.
 #
 # Equation references throughout this module use two source papers:
 #
@@ -31,32 +36,46 @@ module GGJ
 
 using LinearAlgebra
 using StaticArrays
+using SparseArrays
+using Random
+using Printf
+using DoubleFloats: Double64
 
 import ..InnerLayerModel, ..solve_inner
 
 """
     GGJModel{S} <: InnerLayerModel
 
 Glasser–Greene–Johnson resistive inner-layer model. The type parameter `S`
-selects the solver: `:galerkin` (default) for the Hermite-cubic finite element
-solver and `:shooting` for the backward stable-shoot solver. Both
-implementations consume the same `inps` asymptotic-basis kernel and return
-the parity-projected matching data.
+selects the solver: `:ray` (default) for the rotated-contour collocation
+solver (robust at large |Q| on/near the imaginary axis; agrees with
+`:galerkin` within its error bar at moderate Q), `:galerkin` for the
+Hermite-cubic finite element solver (real-axis method; degrades for
+|Q| ≳ 1), and `:shooting` for the backward stable-shoot solver (|Q| ≪ 1
+only). All implementations consume the same `inps` asymptotic-basis kernel
+and return the parity-projected matching data in the same convention.
+Note the backends take different numerical-knob keywords: pass
+`GGJModel(solver=:galerkin)` explicitly when using `nx`/`xfac`-style
+Galerkin knobs.
 """
 struct GGJModel{S} <: InnerLayerModel end
 
-GGJModel(; solver::Symbol=:galerkin) = GGJModel{solver}()
+GGJModel(; solver::Symbol=:ray) = GGJModel{solver}()
 
 include("GGJParameters.jl")
 include("InnerAsymptotics.jl")
+include("RayAsymptotics.jl")
 include("Reference.jl")
 include("Shooting.jl")
 include("Galerkin.jl")
+include("Ray.jl")
 
 export GGJModel, GGJParameters
 export mercier_di, mercier_dr, inner_Q, rescale_delta
 export build_asymptotics, evaluate_asymptotics, pick_xmax
 export InnerAsymptoticsCache
 export glasser_wang_2020_eq55
+export solve_ray, RaySolveResult, pick_smax, physical_ua_dua
+export delta_convergence, solution_profile, asymptotic_profile, q4_surface_benchmark
 
 end # module GGJ