Not the OP, but a computational physicist writing a fairly decent sized codebase for a long term project, just went through the language choice and initial prot

Not the OP, but a computational physicist writing a fairly decent sized codebase for a long term project, just went through the language choice and initial prototyping phase. I have extensively used Julia, Python, MATLAB, C99, C++98/11/14, Fortran and D for work and I believe in picking the right tool for the job. I chose C++ (writing in a fairly modern style, but not eschewing aliasing-restricted pointers, etc. where beneficial) because it handily beats everything except Fortran for performance and is vastly superior to Fortran in terms of zero-cost abstraction. I'm writing code that's largely portable between CPUs and accelerators (mostly GPUs) and has a lot of interchangeable parts. With C++ I can use templates to achieve compile time polymorphism and genericity, while retaining Fortran level performance on CPUs at the cost of higher code complexity. The Fortran story on GPUs has also been very disappointing initially, especially for those of us not interested in proprietary compilers, though I understand the situation is improving there. Ultimately, in my experience, while individual strengths of C++ can be reproduced in other languages, there's no other language that does it all. I hope that changes some day (for now, D looks like the most promising alternative to me) as writing C++ is often an exercise in frustration, but that's where we're at.