Update README.md

README.md

@@ -4,7 +4,7 @@ tags: []
 ---
 
 <!-- Provide a quick summary of what the model is/does. -->
-Foundation Neural-Network Quantum State trained on the two-dimension \\(J_1\\)- \\(J_2\\) Heisenberg on a \\(10\times 10\\) square lattice at \\(J_2/J_1=0.5\\). 
+Foundation Neural-Network Quantum State trained on the two-dimension \\(J_1\\)- \\(J_2\\) Heisenberg on a \\(10\times 10\\) square lattice. 
 The system is described by the following Hamiltonian (with periodic boundary conditions):
 
 $$
@@ -12,7 +12,7 @@ $$
     + J_2 \!\!\!\!\sum_{\langle \langle {\boldsymbol{r}},{\boldsymbol{r'}} \rangle \rangle} \!\!\!\hat{\boldsymbol{S}}_{\boldsymbol{r}}\cdot\hat{\boldsymbol{S}}_{\boldsymbol{r'}} \ .
 $$
 
-The model has been trained on \\(R=100\\) different disorder realization equispaced in the interval \\(J_2 \in [0.4, 0.6]\\),
+The architecture has been trained on \\(R=100\\) different couplings \\(J_2\\) equispaced in the interval \\(J_2 \in [0.4, 0.6]\\),
 using a total batch size of \\(M=16000\\) samples.
 
 The computation has been distributed over 4 A100-64GB GPUs for few hours.
@@ -20,7 +20,7 @@ The computation has been distributed over 4 A100-64GB GPUs for few hours.
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model. In particular, we sample the model for a fixed value of the external field \\(h\\) using NetKet.
+Use the code below to get started with the model. In particular, we sample the architecture for a fixed value of the coupling \\(J_2\\) using NetKet.
 
 ```python
 from functools import partial