Quantum computing bottleneck: 37 competing software tools doing the same job

The density matrix renormalization group (DMRG) algorithm is a cornerstone computational method for studying quantum many-body systems, renowned for its accuracy and adaptability. Because DMRG provides a general framework applicable across various fields such as materials science, quantum chemistry, and quantum computing, one might expect a shared, flexible library to serve most users. Nevertheless, numerous independent implementations continue to appear, resulting in significant duplication of effort. To identify collaboration opportunities that can promote a more unified approach, we map the rapidly expanding DMRG software landscape and provide a comprehensive comparison of features across 37 existing packages. When comparing key features, such as parallelism strategies for high-performance computing and symmetry-adapted formulations that enhance efficiency, we found significant overlap among the packages. This overlap suggests opportunities for collaboration to modularize common functionality—e.g., tensor operations, symmetry representations, and eigensolvers—as the packages are mostly independent and share few third-party library dependencies. More collaboration on modularization could reduce duplication of effort, improve interoperability, and enable prioritization and quicker spread of new advances. We believe the current lack of modularity is more socially driven than a technical issue; hence, we see raising awareness about the existing implementations as a first step in the right direction. Ultimately, this work emphasizes the value of greater cohesion through modularity, which would benefit DMRG software and related tensor-network-centered software, enabling the solution of more complex and ambitious problems.