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Bertrand is a programming language designed for scientific computing, developed at Sandia National Laboratories. It combines the high performance capabilities of Fortran with the user-friendly interfaces found in MATLAB and Python, making it an ideal tool for mathematicians and engineers looking to express their work programmatically. The language includes linear algebraic operations, array-handling features similar to APL and J, and domain-specific constructs for direct mathematical model specification, eliminating the need for an intermediate representation like ODEs. Bertrand prioritizes clean presentation and ease of use for both symbolic and numerical simulations with the goal of simplifying coding for non-computer scientists.

Bertrand boasts several unique features that set it apart from other programming languages in scientific computing. It offers a blend of high performance reminiscent of Fortran combined with user-friendly interfaces found in MATLAB and Python. The language provides capabilities for linear algebraic operations and efficient array handling while introducing domain-specific constructs that allow users to directly specify mathematical models without intermediary representations like ODEs. This focus on clean syntax, usability for symbolic and numerical simulations, and accessibility to non-computer scientists allows Bertrand to stand out as a unique tool tailored specifically to expressing scientific work programmatically.

Bertrand's main competitors include Fortran, MATLAB, and Python—all established options in scientific computing. Fortran is known for its computational speed; MATLAB excels in matrix operations and visualization; Python offers versatility with an extensive library ecosystem. Bertrand sets itself apart by merging these strengths into one package: combining Fortran's performance with MATLAB's ease-of-use interface along with Python’s versatility makes it particularly suited for mathematicians or engineers who require both computational power and accessible coding environments. Its streamlined approach—highlighted by direct model specifications without intermediary steps—further simplifies tasks, providing significant competitive advantages tailored specifically toward those engaged in scientific computing without a deep background in computer science.

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