JOSS: copy edits/bib

paper/paper.bib

@@ -30,7 +30,7 @@ @article{VillaPetraGhattas21
   address    = {New York, NY, USA},
   articleno  = {16},
   issue_date = {March 2021},
-  journal    = {ACM Trans. Math. Softw.},
+  journal    = {ACM Transactions on Mathematical Software},
   month      = apr,
   numpages   = {34},
   publisher  = {Association for Computing Machinery},
@@ -96,7 +96,7 @@ @ARTICLE{2020SciPy-NMeth
 @Article{LiuNocedal89,
   Title                    = {On the limited memory {BFGS} methods for large scale optimization},
   Author                   = {Liu, D. C. and Nocedal, J.},
-  Journal                  = {Math. Prog.},
+  Journal                  = {Mathematical Programming},
   Year                     = {1989},
   Pages                    = {503--528},
   Volume                   = {45},
@@ -170,7 +170,7 @@ @article{AlnaesMartinLoggEtAl14
 issn = {0098-3500},
 url = {https://doi.org/10.1145/2566630},
 doi = {10.1145/2566630},
-journal = {ACM Trans. Math. Softw.},
+journal = {ACM Transactions on Mathematical Software},
 month = {mar},
 articleno = {9},
 numpages = {37},
@@ -216,4 +216,4 @@ @techreport{KouriRidzalWinckel17
      institution = {Sandia National Laboratories},
      month = {01},
      url = {https://trilinos.github.io/pdfs/ROL.pdf}
-}
+}

paper/paper.md

@@ -58,7 +58,7 @@ Problems of PDE-constrained optimization under uncertainty arise due to the ubiq
 In deterministic PDE-constrained optimization, the goal is typically to optimize a quantity of interest (QoI) that is a function of the system's state and quantifies its performance, where the optimization and state variables are related through the underlying PDE model. 
 Compared to this deterministic counterpart, PDE-constrained OUU involves an added layer of complexity, 
 since the QoI becomes a random variable due to its dependence on the uncertain model parameters.
-In OUU, the cost functional and/or constraints are instead given in terms of risk measures, which are statistical quantity summarizing the QoI's distribution. 
+In OUU, the cost functional and/or constraints are instead given in terms of risk measures, which are statistical quantities summarizing the QoI's distribution. 
 A canonical example of such a risk measure is the expected value of the QoI, 
 though other measures that account for the tail behavior of the distribution such as 
 the variance, or superquantile/CVaR are common choices.
@@ -124,4 +124,4 @@ Figure sizes can be customized by adding an optional second parameter:
 We acknowledge contributions from Brigitta Sipocz, Syrtis Major, and Semyeong
 Oh, and support from Kathryn Johnston during the genesis of this project. -->
 
-# References
+# References