Comparison with related libraries

Feature	tmech	Eigen	FTensor	Fastor
Header-only	Yes	Yes	Yes	Yes
Arbitrary-rank tensors	Yes	Yes [1]	Yes	Yes
Expression templates	Yes	Yes	Yes	Yes
Symbolic differentiation	Yes [2]	No	No	No
Isotropic tensor functions	Yes	No	No	No
Decomposition derivatives	Yes	No	No	No
SIMD support	Optional	Yes	No	Yes
Index notation	Implicit	N/A	Yes	Yes

[1]

Eigen provides arbitrary-rank tensors only through its unsupported Eigen::Tensor module.

[2]

Experimental; see Symbolic differentiation.

The distinguishing feature of tmech is the integration of symbolic differentiation with tensor algebra. All four libraries provide expression templates for efficient evaluation; among them, only tmech also differentiates tensor expressions symbolically to produce tangent operators at compile time. General-purpose automatic-differentiation tools (such as Sacado, CoDiPack, autodiff, and Enzyme) achieve differentiation by other means (run-time tapes or external code generation).