Revert variable mapping change - original was correct

The ordering from mmprob.f matches unknowns(mtk_simplified) ordering,
so the simple index-based mapping was correct after all.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <[email protected]>

Author: claude

benchmarks/DAE/NANDGateProblem.jmd

@@ -211,42 +211,12 @@ mmprob = ODEProblem(mmf, y0, tspan)
 # ModelingToolkit version via modelingtoolkitize
 mtk_sys = modelingtoolkitize(mmprob)
 mtk_simplified = structural_simplify(mtk_sys)
-
-# Properly map initial conditions by matching variable names
-original_vars = unknowns(mtk_sys)
-simplified_vars = unknowns(mtk_simplified)
-
-# Create mapping from original to simplified system
-u0_mtk = []
-for var in simplified_vars
-    # Find the corresponding variable in the original system
-    orig_idx = findfirst(v -> isequal(v, var), original_vars)
-    if orig_idx !== nothing
-        push!(u0_mtk, var => mmprob.u0[orig_idx])
-    else
-        # If variable not found, it might be a new auxiliary variable - use zero
-        push!(u0_mtk, var => 0.0)
-    end
-end
-
+u0_mtk = [mtk_simplified.states[i] => mmprob.u0[i] for i in 1:length(mmprob.u0)]
 mtkprob = ODEProblem(mtk_simplified, u0_mtk, mmprob.tspan)
 
 # DAEProblem version
-du_orig = mmprob.f(mmprob.u0, mmprob.p, 0.0)
-
-# Map derivatives to simplified system
-du0 = []
-for var in simplified_vars
-    # Find the corresponding variable in the original system
-    orig_idx = findfirst(v -> isequal(v, var), original_vars)
-    if orig_idx !== nothing
-        push!(du0, D(var) => du_orig[orig_idx])
-    else
-        # If variable not found, use zero derivative
-        push!(du0, D(var) => 0.0)
-    end
-end
-
+du = mmprob.f(mmprob.u0, mmprob.p, 0.0)
+du0 = D.(unknowns(mtk_simplified)) .=> du
 daeprob = DAEProblem(mtk_simplified, du0, [], tspan)
 
 # Generate reference solutions