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Since #784, disjoint dense JLArrays sharing one allocation are reported as aliases, rejecting valid buffer-backed contractions in QuantumKitHub/TensorOperations.jl#310.
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Base.mightalias(::JLArray, ::JLArray)using half-open byte ranges, following CUDA's dense-array implementation (linked in the source comment). Zero-byte arrays return false. Keep shared-allocationdataidsfor conservative wrapper checks and the #716 broadcast fix.Validation on Julia 1.13.1: The shared GPUArrays aliasing testsuite uses the supplied array type, with nine assertions covering self-aliasing, adjacent and overlapping slices in both orders, independent allocations, mixed element sizes, and empty views. All 18 assertions pass for Array and JLArray through the standard test runner. With this fix and the companion StridedViews #57, all 219 original TensorOperations allocator assertions pass. The JLArrays fix can also be backported to the 0.3 release line.