diff --git a/4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md b/4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md
index ef42ae46f..9be3f6e22 100644
--- a/4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md	
+++ b/4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md	
@@ -85,4 +85,4 @@ The goal of this research is to use a generative diffusion model to create unstr
 If this research is successful, this diffusion model will accomplish three main tasks:
 **Outcome 1:** Approximate a set of controllable plants by generating a large number of perturbed examples. This research will use the lossy nature of the diffusion model to create the perturbation. Inference of these models is relatively cheap, while maintaining the ability to create novel samples. 
 
-**Outcomes 2:** Perturb a nominal plant in an unstructured manner with a controllable amount of uncertainty. 
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+**Outcomes 2:** Perturb a nominal plant in an unstructured manner with a controllable amount of uncertainty. The diffusion model uses Gaussian noise as a mechanic to introduce perturbation from training data. This noise is not predicated on any understanding of the physical properties of a system, but instead 
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