From 846d38b88c6468bd5a5b1a99a795f697c39d9a55 Mon Sep 17 00:00:00 2001
From: Marvin Erdmann <106394656+Marvmann@users.noreply.github.com>
Date: Fri, 15 Sep 2023 08:21:19 +0200
Subject: [PATCH] Update Publications Section in README.md

added most recent publication by Kiwit et al.
---
 README.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 50112926..fe1fa4af 100644
--- a/README.md
+++ b/README.md
@@ -5,9 +5,9 @@ QUARK supports various applications, like the traveling salesperson problem (TSP
 It also features different solvers (e.g., simulated /quantum annealing and the quantum approximate optimization algorithm (QAOA)), quantum devices (e.g., IonQ and Rigetti), and simulators.
 It is designed to be easily extendable in all of its components: applications, mappings, solvers, devices, and any other custom modules.
 
-## Paper
-Details about the motivations for the framework can be found in the accompanying QUARK paper: https://arxiv.org/abs/2202.03028. 
-Even though the architecture changed significantly with the 2.0 release of QUARK, the guiding principles still remain.
+## Publications
+Details about the motivations for the original framework can be found in the [accompanying QUARK paper from Finžgar et al](https://arxiv.org/abs/2202.03028).
+Even though the architecture changes significantly from QUARK 1.0 to 2.0, the guiding principles still remain. The most recent publication from [Kiwit et al.](https://arxiv.org/abs/2308.04082) provides an updated overview of the functionalities and quantum machine learning features of QUARK 2.0.
 
 ## Documentation
 Documentation with a tutorial and developer guidelines can be found here: https://quark-framework.readthedocs.io/en/dev/.