restore effective_excitation_hamiltonian

Author: lkdvos

src/algorithms/excitation/quasiparticleexcitation.jl

@@ -260,18 +260,35 @@ end
 Base.length(H::EffectiveExcitationHamiltonian) = length(H.operator)
 
 function (H::EffectiveExcitationHamiltonian)(ϕ::QP; kwargs...)
-    ϕ′ = similar(ϕ)
     qp_envs = environments(ϕ, H.operator, H.lenvs, H.renvs; kwargs...)
+    return effective_excitation_hamiltonian(H.operator, ϕ, qp_envs, H.energy)
+end
+function (H::Multiline{<:EffectiveExcitationHamiltonian})(ϕ::MultilineQP; kwargs...)
+    return Multiline(map((x, y) -> x(y; kwargs...), parent(H), parent(ϕ)))
+end
+
+function effective_excitation_hamiltonian(H, ϕ, envs=environments(ϕ, H))
+    E₀ = effective_excitation_renormalization_energy(H, ϕ, envs.leftenvs, envs.rightenvs)
+    return effective_excitation_hamiltonian(H, ϕ, envs, E₀)
+end
+function effective_excitation_hamiltonian(H, ϕ, qp_envs, E)
+    ϕ′ = similar(ϕ)
     tforeach(1:length(ϕ); scheduler=Defaults.scheduler[]) do loc
-        ϕ′[loc] = _effective_excitation_local_apply(loc, ϕ, H.operator,
-                                                    H.energy[loc], qp_envs)
+        ϕ′[loc] = _effective_excitation_local_apply(loc, ϕ, H, E[loc], qp_envs)
         return nothing
     end
     return ϕ′
 end
 
-function (H::Multiline{<:EffectiveExcitationHamiltonian})(ϕ::MultilineQP; kwargs...)
-    return Multiline(map((x, y) -> x(y; kwargs...), parent(H), parent(ϕ)))
+function effective_excitation_hamiltonian(H::MultilineMPO, ϕ::MultilineQP,
+                                          envs=environments(ϕ, H))
+    E₀ = map(effective_excitation_renormalization_energy, parent(H), parent(ϕ),
+             parent(envs).leftenvs, parent(envs).rightenvs)
+    return effective_excitation_hamiltonian(H, ϕ, envs, E₀)
+end
+function effective_excitation_hamiltonian(H::MultilineMPO, ϕ::MultilineQP, envs, E)
+    return Multiline(map(effective_excitation_hamiltonian,
+                         parent(H), parent(ϕ), parent(envs), E))
 end
 
 function _effective_excitation_local_apply(site, ϕ, H::MPOHamiltonian, E::Number, envs)

src/algorithms/toolbox.jl

@@ -227,22 +227,16 @@ function variance(state::InfiniteQP, H::InfiniteMPOHamiltonian, envs=environment
 
     # I don't remember where the formula came from
     # TODO: this is probably broken
-    E₀ = effective_excitation_renormalization_energy(H, state, envs.leftenvs,
-                                                     envs.rightenvs)
-    Heff = EffectiveExcitationHamiltonian(H, envs.leftenvs, envs.rightenvs, E₀)
-    E_ex = dot(state, Heff(state))
-
+    E_ex = dot(state, effective_excitation_hamiltonian(H, state, envs))
     rescaled_envs = environments(gs, H_regularized)
     GL = leftenv(rescaled_envs, 1, gs)
     GR = rightenv(rescaled_envs, 0, gs)
     E_f = @plansor GL[5 3; 1] * gs.C[0][1; 4] * conj(gs.C[0][5; 2]) * GR[4 3; 2]
 
     H2 = H_regularized^2
-    lenvs2 = environments(state.left_gs, H2)
-    renvs2 = state.trivial ? lenvs2 : environments(state.right_gs, H2)
-    E₁ = effective_excitation_renormalization_energy(H2, state, lenvs2, renvs2)
-    Heff2 = EffectiveExcitationHamiltonian(H2, lenvs2, renvs2, E₁)
-    return real(dot(state, Heff2(state)) - 2 * (E_f + E_ex) * E_ex + E_ex^2)
+
+    return real(dot(state, effective_excitation_hamiltonian(H2, state)) -
+                2 * (E_f + E_ex) * E_ex + E_ex^2)
 end
 
 function variance(ψ, H::LazySum, envs=environments(ψ, sum(H)))