From 3bea4636d041183098f7b75849199c5401156f3b Mon Sep 17 00:00:00 2001 From: Thibaut Lacroix <57836508+tfmlaX@users.noreply.github.com> Date: Tue, 21 Nov 2023 23:14:57 +0100 Subject: [PATCH] Update README.md --- README.md | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 57cc199..ed8bdb7 100644 --- a/README.md +++ b/README.md @@ -71,8 +71,7 @@ We may then wish to construct some observables to measure along the trajectory. ob1 = OneSiteObservable("sz", sz, 1) ``` -creates an object which represents the measurement of the expectation of on the first site of the chain, i.e. on the spin. +creates an object which represents the measurement of the expectation of $\sigma_z$ on the first site of the chain, i.e. on the spin. The string passed to the first argument is just a label that will be used to retrieve the measurement data after the run. Any type `Type` can be used as an observable by defining a function `measure(A, ob::Type)`, where `A` is an MPS. @@ -92,8 +91,8 @@ import MPSDynamics: disp ob3 = TwoSiteObservable("SXdisp", sx, disp(d), [1], collect(2:N+1)) ``` -will measure where - is the displacement operator of the chain site and the index *i* runs over +will measure $\langle\sigma_x\hat{q}_i\rangle$ where +$\hat{q}_i$ is the displacement operator of the chain site and the index *i* runs over all chain sites. Finally we launch the simulation with the function `runsim`. @@ -133,8 +132,13 @@ using Plots plot(dat["data/times"], dat["convdata/sz"],label=["Dmax=2" "Dmax=4" "Dmax=6"], xlabel="t",ylabel="sz") heatmap(dat["data/times"], collect(1:N), abs.(dat["data/SXdisp"][1,:,:]), xlabel="t",ylabel="i") ``` - - + + Convergence plot of <sz> with increasing bond dimension Dmax + + + + Heatmap of the <sx q_i> correlation as a function of time and chain modes + The data is stored in the JLD format which is based on HDF5. Loading the data in Julia using the [JLD](https://github.com/JuliaIO/JLD.jl) package will recover the full type information of the Julia variables that were