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@@ -16,50 +16,22 @@ authors:
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-  - name: Marcus G. K. Williams
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   - name: Philipp Stratmann
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-  - name: Philipp Plank
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   - name: Sumedh Risbud
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-  - name: Philipp Weidel
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   - name: Ashish Rao Mangalore
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-  - name: Mathis Richter
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-  - name: Sumit Bam Shrestha
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-  - name: Joyesh Mishra
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   - name: Timothy Shea
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-  - name: Michael Beale
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   - name: Andreas Wild
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@@ -70,22 +42,48 @@ affiliations:
 date: 27 October 2023
 bibliography: paper.bib
 ---
+A list of the authors of the software and their affiliations, using the correct format (see the example below).
+
+
+JOSS welcomes submissions from broadly diverse research areas. For this reason, we require that authors include in the paper some sentences that explain the software functionality and domain of use to a non-specialist reader. We also require that authors explain the research applications of the software. The paper should be between 250-1000 words. Authors submitting papers significantly longer than 1000 words may be asked to reduce the length of their paper.
+
+As this short list shows, JOSS papers are only expected to contain a limited set of metadata (see example below), a Statement of need, Summary, Acknowledgements, and References sections. You can look at an example accepted paper. Given this format, a “full length” paper is not permitted, and software documentation such as API (Application Programming Interface) functionality should not be in the paper and instead should be outlined in the software documentation.
+
 
 # Summary
 
-`Lava Optimization`
+A summary describing the high-level functionality and purpose of the software for a diverse, non-specialist audience.
+
+- Challenges of optimization and opportunities of neuromorphic computing
+  - Scalability, low latency, optimality, energy
+  - Neuromorphic computing provides fine-grained parallel and event-driven copmutation, low energy consumption
+- Development cycle is typically long for neuromorphic computing due to the lack of effective abstraction frameworks
+- `Lava Optimization` increases productivity on developing and testing novel neuromorphic algorithms and applications
+- The library abstracts away the neuromoprhic aspect of the backend, exposing an API typical of constrained optimization (variables, constraints, cost, etc.)
+- Supports the community  in developing algorithms that are iterative, discrete, and distributed
+- We leveraged the library architecture to develop multi-backend QUBO and QP solvers, and received contirbutions from the community for a Bayesian and LCA solvers
 
 
 # Statement of need
 
+A Statement of need section that clearly illustrates the research purpose of the software and places it in the context of related work.
 
+- Energy Delay Product
 
 # Acknowledgements
 
 We acknowledge contributions from Chinonso Onah, Gavin Parpart, and Shay Snyder.
 
+# [OPTIONAL] On-going research using the library
+
+Mention (if applicable) a representative set of past or ongoing research projects using the software and recent scholarly publications enabled by it.
+
 # Financial support
 
+Acknowledgement of any financial support.
+
 This project was developed by the Neuromorphic Computing Lab at Intel Corporation.
 
 # References
+
+A list of key references, including to other software addressing related needs. Note that the references should include full names of venues, e.g., journals and conferences, not abbreviations only understood in the context of a specific discipline.
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