Jishnu Bhattacharya

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Similarly, ```julia julia> SymmetricToeplitz(Float64[1,2,3,4]) \ Float64[1,2,3,4] 4-element Vector{Float64}: NaN NaN NaN NaN julia> Matrix(SymmetricToeplitz(Float64[1,2,3,4])) \ Float64[1,2,3,4] 4-element Vector{Float64}: 1.0 0.0 0.0 0.0 ```

It should be cheap, but since the docstrings of `adjoint` and `transpose` suggest that these are lazy wrappers, and that `the adjoint of an adjoint unwraps the parent`, perhaps it's...

I see, although `adjoint(adjoint(H::Hermitian)) === H` still holds. In any case, reducing memory allocation is perhaps a good idea? This might make it easier to port such matrices to GPUs...

In the real `Toeplitz` case, this may not matter much, but there are other cases where this will save allocating one or two vectors ```julia julia> C = Circulant(fill(2,1000)); julia>...

To reduce the number of methods that need to be defined, which may improve the package-load and compile times slightly (although I haven't benchmarked these). From a design perspective, it...

Please don't remove deprecated functions such as `gausschebyshev` without a breaking change, as these used to be a part of the official API. By default, Julia doesn't warn about the...

Yes, we should move these to an extension eventually. Presumably, `LinearAlgebra` will be excised in Julia v1.11, so we should do it in the next few months.

This certainly seems like a good optimization to include, but extending `Base.:(+)(xs::AbstractArray, oe::OneElement)` opens one up to ambiguities: ```julia julia> Base.:(+)(xs::AbstractArray, oe::OneElement) = add(xs, oe) julia> Base.:(+)(oe::OneElement, xs::AbstractArray) = +(xs,...

Not sure if I understand. This uses ``` copy(::MulAdd{BandedMatrices.BandedColumns{DenseColumnMajor}, BandedMatrices.BandedColumns{DenseColumnMajor}, ...) ``` Perhaps some special cases may be added to `gbmm!` to deal with the diagonal cases?