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   Harper, Graham ; Liu, Jiangguo ; Tavener, Simon ; Zheng, Bin ( March 2019 , Journal of Scientific Computing)
2. Brane brick models for the Sasaki-Einstein 7-manifolds Yp,k(ℂℙ1 × ℂℙ1) and Yp,k(ℂℙ2)

   https://doi.org/10.1007/JHEP03(2023)050  

   Franco, Sebastián ; Ghim, Dongwook ; Seong, Rak-Kyeong ( March 2023 , Journal of High Energy Physics)

   A bstract The 2 d (0 , 2) supersymmetric gauge theories corresponding to the classes of Y p,k (ℂℙ 1 × ℂℙ 1 ) and Y p,k (ℂℙ 2 ) manifolds are identified. The complex cones over these Sasaki-Einstein 7-manifolds are non-compact toric Calabi-Yau 4-folds. These infinite families of geometries are the largest ones for Sasaki-Einstein 7-manifolds whose metrics, toric diagrams, and volume functions are known explicitly. This work therefore presents the largest list of 2 d (0 , 2) supersymmetric gauge theories corresponding to Calabi-Yau 4-folds with known metrics. 

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3. Modular aerogel brick fabrication via 3D-printed molds

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   Joo, Piljae ; Yao, Yimin ; Teo, Nicholas ; Jana, Sadhan C. ( October 2021 , Additive Manufacturing)

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   https://doi.org/10.1016/j.autcon.2022.104307  

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5. Performing Bayesian Analyses With AZURE2 Using BRICK: An Application to the 7Be System

   https://doi.org/10.3389/fphy.2022.888476  

   Odell, Daniel ; Brune, Carl R. ; Phillips, Daniel R. ; deBoer, Richard James ; Paneru, Som Nath ( June 2022 , Frontiers in Physics)

   Phenomenological R -matrix has been a standard framework for the evaluation of resolved resonance cross section data in nuclear physics for many years. It is a powerful method for comparing different types of experimental nuclear data and combining the results of many different experimental measurements in order to gain a better estimation of the true underlying cross sections. Yet a practical challenge has always been the estimation of the uncertainty on both the cross sections at the energies of interest and the fit parameters, which can take the form of standard level parameters. Frequentist ( χ 2 -based) estimation has been the norm. In this work, a Markov Chain Monte Carlo sampler, emcee , has been implemented for the R -matrix code AZURE2 , creating the Bayesian R -matrix Inference Code Kit ( BRICK ). Bayesian uncertainty estimation has then been carried out for a simultaneous R -matrix fit of the 3 He ( α , γ ) 7 Be and 3 He ( α , α ) 3 He reactions in order to gain further insight into the fitting of capture and scattering data. Both data sets constrain the values of the bound state α -particle asymptotic normalization coefficients in 7 Be. The analysis highlights the need for low-energy scattering data with well-documented uncertainty information and shows how misleading results can be obtained in its absence. 

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