Apply the conjugation op to destination axes in bipermutedimsopadd!#184
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Apply the conjugation op to destination axes in bipermutedimsopadd!#184mtfishman wants to merge 5 commits into
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## main #184 +/- ##
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## Summary Makes `conj` dualize graded axes consistently across GradedArrays, matching `Base.conj(::AbelianGradedArray)`. The materialization path (`bipermutedimsopadd!` on an `AbstractSectorArray` with `op = conj`) now routes through `Base.conj`, which dualizes the sectors and carries the fermionic reversal phase that a bare block-data conjugation drops. The `SectorStyle` broadcast picks up the same behavior: `broadcasted_sector` is op-aware, so `conj.(x)` dualizes the result axes, and a broadcast that conjugates only some operands such as `conj.(s) .- t` now errors as a sector mismatch rather than silently keeping the original axes. `Base.conj` on the structural factors `AbelianSectorDelta` and `SectorIdentity` dualizes their axes. Builds on ITensor/TensorAlgebra.jl#184, which makes the `bipermutedimsopadd!` and `permutedimsop` `op` apply to the destination axes. ## TODO - [ ] Drop the `[sources]` pin on TensorAlgebra and confirm the `0.11.2` compat floor once ITensor/TensorAlgebra.jl#184 merges and registers.
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## Summary `bipermutedimsopadd!` and `permutedimsop` now apply their element-wise `op` to the destination axes, so a conjugating permutation (`op = conj`) dualizes graded axes and keeps axes and data in sync. `op` acts as a conjugation flag, either `identity` or `conj`: on a graded axis `conj` dualizes, and on a dense axis it is a no-op, so dense arrays are unaffected. Transposition is carried by the permutation arguments rather than by `op`. This also adds `linearbroadcasted(*, ::Number, ::ConjBroadcasted)`, so scaling a conjugated broadcast operand such as `conj.(a) ./ β` lowers correctly instead of erroring.
`bipermutedimsopadd!`'s `op` is a conjugation flag, either `identity` or `conj`. `check_input` now rejects any other function with an `ArgumentError`, so an unsupported `op` fails with a clear message at the boundary rather than later as a `MethodError` from applying it to an axis.
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Added a compatibility function for bipermutedimsopadd! to maintain backward compatibility.
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Summary
bipermutedimsopadd!andpermutedimsopnow apply their element-wiseopto the destination axes, so a conjugating permutation (op = conj) dualizes graded axes and keeps axes and data in sync.opacts as a conjugation flag, eitheridentityorconj: on a graded axisconjdualizes, and on a dense axis it is a no-op, so dense arrays are unaffected.check_inputrejects any otheropwith an informative error. Transposition is carried by the permutation arguments rather than byop.This also adds
linearbroadcasted(*, ::Number, ::ConjBroadcasted), so scaling a conjugated broadcast operand such asconj.(a) ./ βlowers correctly instead of erroring.