improve coverage some more

Author: lkdvos

test/algorithms.jl

@@ -950,51 +950,94 @@ module TestAlgorithms
     end
 
     @testset "Finite temperature methods" begin
-        L = 6
-        H = transverse_field_ising(; L)
-        trscheme = truncdim(20)
-        verbosity = 1
-        beta = 0.1
+        imaginary_evolution = true
+        @testset "Finite-size" begin
+            L = 6
+            H = transverse_field_ising(; L)
+            trscheme = truncdim(20)
+            verbosity = 1
+            beta = 0.1
+
+            # exact diagonalization
+            H_dense = convert(TensorMap, H)
+            Z_dense_1 = tr(exp(-beta * H_dense))^(1 / L)
+            Z_dense_2 = tr(exp(-2beta * H_dense))^(1 / L)
+
+            # taylor cluster
+            rho_taylor_1 = make_time_mpo(H, beta, TaylorCluster(; N = 2); imaginary_evolution)
+            Z_taylor_1 = tr(rho_taylor_1)^(1 / L)
+            @test Z_taylor_1 ≈ Z_dense_1 atol = 1.0e-2
+            Z_taylor_2 = real(dot(rho_taylor_1, rho_taylor_1))^(1 / L)
+            @test Z_taylor_2 ≈ Z_dense_2 atol = 1.0e-2
+
+            E_x_taylor = @constinferred expectation_value(rho_taylor_1, 1 => S_x())
+            E_xx_taylor = @constinferred expectation_value(rho_taylor_1, (1, 2) => S_xx())
+
+            # WII
+            rho_wii = make_time_mpo(H, beta, WII(); imaginary_evolution)
+            Z_wii = tr(rho_wii)^(1 / L)
+            @test Z_wii ≈ Z_dense_1 atol = 1.0e-2
+            @test expectation_value(rho_wii, 1 => S_x()) ≈ E_x_taylor atol = 1.0e-2
+            @test expectation_value(rho_wii, (1, 2) => S_xx()) ≈ E_xx_taylor atol = 1.0e-2
+
+            # MPO multiplication
+            rho_mps = convert(FiniteMPS, rho_taylor_1)
+            rho_mps, = approximate(rho_mps, (rho_taylor_1, rho_mps), DMRG2(; trscheme, verbosity))
+            Z_mpomul = tr(convert(FiniteMPO, rho_mps))^(1 / L)
+            @test Z_mpomul ≈ Z_dense_2 atol = 1.0e-2
+
+            # TDVP
+            rho_0 = MPSKit.infinite_temperature_density_matrix(H)
+            rho_0_mps = convert(FiniteMPS, rho_0)
+            rho_mps, = timestep(rho_0_mps, H, 0.0, beta, TDVP2(; trscheme); imaginary_evolution)
+            Z_tdvp = real(dot(rho_mps, rho_mps))^(1 / L)
+            @test Z_tdvp ≈ Z_dense_2 atol = 1.0e-2
+
+            @test expectation_value(rho_0_mps, 1 => S_x()) ≈ 0
+            @test expectation_value(rho_0_mps, (1, 2) => S_xx()) ≈ 0
+            @test expectation_value(rho_mps, 1 => S_x()) ≈ E_x_taylor atol = 1.0e-2
+            @test expectation_value(rho_mps, (1, 2) => S_xx()) ≈ E_xx_taylor atol = 1.0e-2
+        end
 
-        # exact diagonalization
-        H_dense = convert(TensorMap, H)
-        Z_dense_1 = tr(exp(-beta * H_dense))^(1 / L)
-        Z_dense_2 = tr(exp(-2beta * H_dense))^(1 / L)
-
-        # taylor cluster
-        rho_taylor_1 = make_time_mpo(H, beta, TaylorCluster(; N = 2); imaginary_evolution = true)
-        Z_taylor_1 = tr(rho_taylor_1)^(1 / L)
-        @test Z_taylor_1 ≈ Z_dense_1 atol = 1.0e-2
-        Z_taylor_2 = real(dot(rho_taylor_1, rho_taylor_1))^(1 / L)
-        @test Z_taylor_2 ≈ Z_dense_2 atol = 1.0e-2
-
-        E_x_taylor = @constinferred expectation_value(rho_taylor_1, 1 => S_x())
-        E_xx_taylor = @constinferred expectation_value(rho_taylor_1, (1, 2) => S_xx())
-
-        # WII
-        rho_wii = make_time_mpo(H, beta, WII(); imaginary_evolution = true)
-        Z_wii = tr(rho_wii)^(1 / L)
-        @test Z_wii ≈ Z_dense_1 atol = 1.0e-2
-        @test expectation_value(rho_wii, 1 => S_x()) ≈ E_x_taylor atol = 1.0e-2
-        @test expectation_value(rho_wii, (1, 2) => S_xx()) ≈ E_xx_taylor atol = 1.0e-2
-
-        # MPO multiplication
-        rho_mps = convert(FiniteMPS, rho_taylor_1)
-        rho_mps, = approximate(rho_mps, (rho_taylor_1, rho_mps), DMRG2(; trscheme, verbosity))
-        Z_mpomul = tr(convert(FiniteMPO, rho_mps))^(1 / L)
-        @test Z_mpomul ≈ Z_dense_2 atol = 1.0e-2
-
-        # TDVP
-        rho_0 = MPSKit.infinite_temperature_density_matrix(H)
-        rho_0_mps = convert(FiniteMPS, rho_0)
-        rho_mps, = timestep(rho_0_mps, H, 0.0, beta, TDVP2(; trscheme); imaginary_evolution = true)
-        Z_tdvp = real(dot(rho_mps, rho_mps))^(1 / L)
-        @test Z_tdvp ≈ Z_dense_2 atol = 1.0e-2
-
-        @test expectation_value(rho_0_mps, 1 => S_x()) ≈ 0
-        @test expectation_value(rho_0_mps, (1, 2) => S_xx()) ≈ 0
-        @test expectation_value(rho_mps, 1 => S_x()) ≈ E_x_taylor atol = 1.0e-2
-        @test expectation_value(rho_mps, (1, 2) => S_xx()) ≈ E_xx_taylor atol = 1.0e-2
+        @testset "Infinite-size" begin
+            H = transverse_field_ising()
+            trscheme = truncdim(20)
+            verbosity = 1
+            beta = 0.1
+
+            # taylor cluster
+            alg_taylor = TaylorCluster(; N = 2)
+            rho_taylor = make_time_mpo(H, beta, alg_taylor; imaginary_evolution)
+            rho_taylor_2 = make_time_mpo(H, 2beta, alg_taylor; imaginary_evolution)
+            E_taylor = @constinferred expectation_value(rho_taylor, H)
+            E_taylor2 = @constinferred expectation_value(rho_taylor_2, H)
+
+            E_z_taylor = @constinferred expectation_value(rho_taylor, 1 => S_z())
+            @test E_z_taylor ≈ 0 atol = 1.0e-4 # no spontaneous symmetry breaking at finite T
+
+            # WII
+            rho_wii = make_time_mpo(H, beta, WII(); imaginary_evolution)
+            @test expectation_value(rho_wii, H) ≈ E_taylor atol = 1.0e-2
+            @test expectation_value(rho_wii, 1 => S_z()) ≈ E_z_taylor atol = 1.0e-2
+
+            # MPO multiplication
+            rho_mps = convert(InfiniteMPS, rho_taylor)
+            rho_mps2, = approximate(rho_mps, (rho_taylor, rho_mps), IDMRG(; verbosity))
+            E_mpomul = expectation_value(rho_mps2, H)
+            @test E_mpomul ≈ E_taylor2 atol = 1.0e-2
+
+            # TDVP
+            rho_0 = MPSKit.infinite_temperature_density_matrix(H)
+            rho_0_mps, = changebonds(convert(InfiniteMPS, rho_0), H, OptimalExpand(; trscheme = truncdim(20)))
+            rho_mps_tdvp, = timestep(rho_0_mps, H, 0.0, beta, TDVP(); imaginary_evolution)
+            E_tdvp = expectation_value(rho_mps_tdvp, H)
+            @test E_tdvp ≈ E_taylor atol = 1.0e-2
+
+            num_vals = 2
+            vals_taylor = @constinferred(transfer_spectrum(convert(InfiniteMPS, rho_taylor); num_vals))
+            vals_mps = @constinferred(transfer_spectrum(rho_mps; num_vals))
+            @test vals_taylor[1:num_vals] ≈ vals_mps[1:num_vals]
+        end
     end
 
     @testset "Sector conventions" begin