updated docs

docs/src/tut/anyonic_statmech.md

@@ -27,7 +27,7 @@ init = InfiniteMPS([physical],[virtual]);
 
 and then pass it on to "leading_boundary":
 ```julia
-(dominant,_) = leading_boundary(init,mpo,Vumps());
+(dominant,_) = leading_boundary(init,mpo,VUMPS());
 ```
 
 This dominant eigenvector contains a lot of hidden information, for example the following calculates the free energy:
@@ -55,7 +55,7 @@ envs = environments(dominant,mpo);
 #this will take a fairly long time
 for Ds in 5:5:50
     (dominant,envs) = changebonds(dominant,mpo,OptimalExpand(trscheme = truncdim(5)),envs);
-    (dominant,envs) = leading_boundary(dominant,mpo,Vumps(maxiter=200));
+    (dominant,envs) = leading_boundary(dominant,mpo,VUMPS(maxiter=200));
     push!(entropies,real(entropy(dominant)[1]));
     push!(corlens,correlation_length(dominant));
 end

docs/src/tut/haldane.md

@@ -21,7 +21,7 @@ physical_space = Rep[SU₂](1=>1);
 virtual_space = Rep[SU₂](0=>20,1=>20,2=>10,3=>10,4=>5);
 
 initial_state = FiniteMPS(rand,ComplexF64,len,physical_space,virtual_space);
-(gs,envs,delta) = find_groundstate(initial_state,ham,Dmrg());
+(gs,envs,delta) = find_groundstate(initial_state,ham,DMRG());
 ```
 
 The typical way to find excited states is to minmize the energy while adding an error term ``lambda | gs > < gs | ``. Here we will instead use the [quasiparticle ansatz](https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.111.080401).
@@ -53,7 +53,7 @@ A much nicer way of obtaining the haldane gap is by working directly in the ther
 ```julia
 virtual_space = Rep[SU₂](1//2=>20,3//2=>20,5//2=>10,7//2=>10,9//2=>5); # this is bond dimension 300!
 initial_state = InfiniteMPS([physical_space],[virtual_space]);
-(gs,envs,delta) = find_groundstate(initial_state,ham,Vumps());
+(gs,envs,delta) = find_groundstate(initial_state,ham,VUMPS());
 ```
 
 One difference with the finite size case is that we not only can - but also have to - specify a momentum label. We can scan for k = 0 to pi by calling:

docs/src/tut/isingcft.md

@@ -108,7 +108,7 @@ ham = periodic_boundary_conditions(nonsym_ising_ham(),circumference);
 
 state = FiniteMPS(circumference,ℂ^2,ℂ^50 #=bond dimension=#);
 
-(gs,envs) = find_groundstate(state,ham,Dmrg());
+(gs,envs) = find_groundstate(state,ham,DMRG());
 ```
 
 Excitations on top of the groundstate can be found using the quasiparticle ansatz. This returns quasiparticle states, which you can just convert back to the usual finite mps's.

docs/src/tut/timeev.md

@@ -37,7 +37,7 @@ init = FiniteMPS(rand,ComplexF64,len,ℂ^2,ℂ^10);
 
 Find the pre-quench groundstate
 ```julia
-(ψ₀,_) = find_groundstate(init,ising_ham(0.5),Dmrg());
+(ψ₀,_) = find_groundstate(init,ising_ham(0.5),DMRG());
 ```
 
 We can define a help function that measures the loschmith echo
@@ -51,7 +51,7 @@ we will initially use a 2site tdvp scheme to increase the bond dimension while t
 ψₜ = deepcopy(ψ₀);
 dt = 0.01;
 
-(ψₜ,envs) = timestep(ψₜ,ising_ham(2),dt,Tdvp2(trscheme=truncdim(20)));
+(ψₜ,envs) = timestep(ψₜ,ising_ham(2),dt,TDVP2(trscheme=truncdim(20)));
 ```
 
 "envs" is a kind of cache object that keeps track of all environments in ψ. It is often advantageous to re-use the environment, so that mpskit doesn't need to recalculate everything.
@@ -60,7 +60,7 @@ Putting it all together, we get
 ```julia
 function finite_sim(len; dt = 0.05, finaltime = 5.0)
     ψ₀ = FiniteMPS(rand,ComplexF64,len,ℂ^2,ℂ^10);
-    (ψ₀,_) = find_groundstate(ψ₀,ising_ham(0.5),Dmrg());
+    (ψ₀,_) = find_groundstate(ψ₀,ising_ham(0.5),DMRG());
 
     post_quench_ham = ising_ham(2);
     ψₜ = deepcopy(ψ₀);
@@ -70,7 +70,7 @@ function finite_sim(len; dt = 0.05, finaltime = 5.0)
     times = collect(0:dt:finaltime);
 
     @showprogress for t = times[2:end]
-        alg = t > 3*dt ? Tdvp() : Tdvp2(trscheme = truncdim(50))
+        alg = t > 3*dt ? TDVP() : TDVP2(trscheme = truncdim(50))
         (ψₜ,envs) = timestep(ψₜ,post_quench_ham,dt,alg,envs);
         push!(echos,echo(ψₜ,ψ₀))
     end

docs/src/tut/xxz_groundstate.md

@@ -28,7 +28,7 @@ state = InfiniteMPS([random_data]);
 
 The groundstate can then be found by calling find_groundstate.
 ```julia
-(groundstate,cache,delta) = find_groundstate(state,ham,Vumps());
+(groundstate,cache,delta) = find_groundstate(state,ham,VUMPS());
 ```
 
 As you can see, vumps strugles to converge. On it's own, that is already quite curious.
@@ -62,12 +62,12 @@ ham = repeat(ham,2);
 
 Running vumps
 ```julia
-(groundstate,cache,delta) = find_groundstate(state,ham,Vumps(maxiter=100,tol_galerkin=1e-12));
+(groundstate,cache,delta) = find_groundstate(state,ham,VUMPS(maxiter=100,tol_galerkin=1e-12));
 ```
 we get convergence, but it takes an enormous amount of iterations. The reason behind this becomes more obvious at higher bond dimensions
 
 ```julia
-(groundstate,cache,delta) = find_groundstate(state,ham,Idmrg2(trscheme=truncdim(100),maxiter=100,tol_galerkin=1e-12));
+(groundstate,cache,delta) = find_groundstate(state,ham,IDMRG2(trscheme=truncdim(100),maxiter=100,tol_galerkin=1e-12));
 
 entanglementplot(groundstate)
 ```
@@ -105,5 +105,5 @@ Even though the bond dimension is higher then in the non symmetric example:
 
 Vumps converges much much faster
 ```julia
-(groundstate,cache,delta) = find_groundstate(state,ham,Vumps(maxiter=400,tol_galerkin=1e-12));
+(groundstate,cache,delta) = find_groundstate(state,ham,VUMPS(maxiter=400,tol_galerkin=1e-12));
 ```