From a4a62ef52555b21d64901f77b9fa633141a80833 Mon Sep 17 00:00:00 2001
From: Anna Roubickova <38880646+aroubickova@users.noreply.github.com>
Date: Tue, 31 Oct 2023 19:29:49 +0000
Subject: [PATCH] Update README.md

---
 docs/README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/README.md b/docs/README.md
index 1d761f9..ee433ab 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -40,8 +40,8 @@ The example workflow uses a model that returns always 0s for the correction, mai
 The data generation schema below outlines the kind of data we need to collect for the model training --- we need to:
 1. run a fully resolved simulation (denoted F)
 2. coarsen some points on the fine trajectory (denoted C) -- these are *inputs* for the training process
-3. make a coarse simulation step from C (denoted by the arrow labelled \Delta t_c)
-4. calculate the difference between the fully resolved, coarsened grid and the coarse grid at the equivalent simulation step -- this is the *target* to train the model for
+3. make a coarse simulation step from C (denoted by the arrow labelled ∆t_c)
+4. calculate the difference between the fully resolved, coarsened grid and the coarse grid (denoted Ĉ at the equivalent simulation step -- this is the *target* to train the model for
 
 ![Data Generation](./assets/data_generation_schema.pdf)