Semilinear maps
Since linear maps appear everywhere in mathematics, it comes as no surprise that they have been part of mathlib for quite some time. However, as we were working on adding the basics of functional analysis to mathlib, a drawback quickly became apparent: conjugatelinear maps could not directly be expressed as linear maps. This meant that some constructions could not be formulated in their most natural way: for example, the map that takes an operator to its adjoint on a complex Hilbert space is a conjugate linear map, and so is the Riesz representation that maps a vector to its dual. This was also preventing us from developing the orthogonal group, the unitary group, etc, properly.
A few options were considered to introduce conjugatelinear maps. One possible way was to define the conjugate space of E
as a type copy where scalar multiplication is conjugated. Then, a conjugatelinear maps is a standard linear map to the conjugate space. This would have enabled us to reuse the API of linear maps without having too much to refactor, but an early attempt to do this was abandoned when converting between the conjugate space and the original space proved to be unwieldy. A further disadvantage is that the type copy would have also appeared in the real case for constructions involving is_R_or_C
. Another potential solution to the problem was to define conjugatelinear maps separately from linear maps. The big drawback here is that the API for linear maps would effectively have to be duplicated for those new maps.
This left the more arduous option, namely to redefine linear_map
to also include semilinear maps. A semilinear map f
is a map from an R
module to an S
module with a ring homomorphism σ
between R
and S
, such that f (c • x) = (σ c) • (f x)
. If we plug in the identity into σ
, we get regular linear maps, and if we plug in the complex conjugate, we get conjugate linear maps. There are also other examples (e.g. Frobeniuslinear maps) where this is useful which are covered by this general formulation. This implied a major refactor: we had to replace the basic definition of R
linear maps E →ₗ[R] F
by σ
semilinear maps E →ₛₗ[σ] F
while keeping the original notation for plain linear maps, and deal with the various problems that this inevitably created further down the import tree. The same also had to be done for linear equivalences, continuous linear maps/equivalences, and linear isometries. This idea had first been proposed by Yury Kudryashov about a year ago, but it then took several months to build up the motivation to embark on this project. Last July, Heather Macbeth, Rob Lewis and I finally managed to start working on it, and the result was merged into mathlib in late September.
The main issue that we had to overcome involved composition of semilinear maps, and symm
for linear equivalences. Suppose we have f : E₁ →ₛₗ[σ₁₂] E₂
and g : E₂ →ₛₗ[σ₂₃] E₃
, we would naturally end up with g.comp f : E₁ →ₛₗ[σ₂₃.comp σ₁₂] E₃
. However, in most cases of interest, this is very awkward: suppose, for example, that we have defined the adjoint as a conjugatelinear map: adjoint : (E →ₗ[ℂ] F) →ₛₗ[conj] (F →ₗ[ℂ] E)
, and want to express the fact that the adjoint of the adjoint is the identity; in other words, we want a lemma like^{1}:
lemma adjoint_adjoint : adjoint.comp adjoint = (id : E →ₗ[ℂ] F)
However, the general composition lemma for semilinear maps wouldn't give us this: the id
on the righthand side would actually be of type E →ₛₗ[conj.comp conj] F
! A similar problem arises for symm
for a semilinear equivalence. Suppose we have a semilinear equivalence e : E ≃ₛₗ[σ] F
, then e.symm
will naturally be of type F ≃ₛₗ[σ.symm] E
. Again this is undesirable in interesting cases: suppose we have defined the Riesz representation of a vector (i.e. the map that takes a vector v : E
to its dual λ x, ⟪v, x⟫
in a Hilbert space) as a conjugatelinear equivalence to_dual : E ≃ₛₗ[conj] (dual E)
. Then, of course we want to_dual.symm
to be of type (dual E) ≃ₛₗ[conj] E
, but the general lemma regarding symm
will yield a map of type (dual E) ≃ₛₗ[conj.symm] E
.
To solve these two issues, we created two typeclasses to make Lean infer the right ring homomorphism. The first one is [ring_hom_comp_triple σ₁₂ σ₂₃ σ₁₃]
which expresses the fact that σ₂₃.comp σ₁₂ = σ₁₃
, and the second one is [ring_hom_inv_pair σ₁₂ σ₂₁]
which states that σ₁₂
and σ₂₁
are inverses of each other. The ring homomorphism σ₁₃
(resp. σ₂₁
) is inferred silently by the typeclass system using out_param
. Then, to make our two examples go through properly, we just need to add instances for ring_hom_comp_triple conj conj id
and ring_hom_inv_pair conj conj
. There is also a third typeclass [ring_hom_surjective σ]
, which is a necessary assumption to generalize some basic lemmas.
This refactor is now mostly complete ("mostly" because there are still lots of lemmas left to generalize!), and we have also added notation specifically for conjugatelinear maps: E →ₗ⋆[ℂ] F
denotes conjugatelinear maps from E
to F
. Such maps are now slowly starting to appear, with the Riesz representation in PR #9924, and the adjoint coming soon!

The examples given here have been simplified to get to the core of the issue; in reality, these maps would involve continuous linear maps, we would most likely have to specify the type of
adjoint
for Lean to infer the correct types, etc. ↩