```

return xr.apply_ufunc(

    lambda x: (x - x[::-1]) / 2,

    conductance,

    input_core_dims=[dims],

    output_core_dims=[dims],

    vectorize=True,

Reading the article about how they filtered and cherry-picked specific regions, I got curious about the actual asymmetry computation, so I looked up the source code. Looking at it, they seem to have used memory offsets as if they were physical coordinates, but they're only looking at the array index order, not the actual values. x[::-1] isn't measuring physical coordinates; it's just reversing the array. So it seems this bias axis mentioned in the article only forms when things are symmetric. But in typical numerical computations, isn't it pretty common to reverse arrays like this? In this case, there must be a reason why the physical coordinates change. Should we be verifying invariants here? Sometimes I see people who find these kinds of issues and I think they're really amazing. Even after reading the article, tracing it, and debugging it, I kept wondering what the problem was..

Edit: Oh, The Register is a true tech paper, guess the name makes sense for that. Got mixed up cause there are a bunch of general papers called something Register.

May be it is just me but when I see all these quantum computing pseudo results I wonder how people can believe this thing has any hope to work at all so much it is ungrounded to reality.

All in all, the whole fundation of the quantum treatment is flawed in my humble opinion because of the idea of wave-packet collapse, when a measurement is done, is by itself completely unsound. However they assume it holds perfectly and base a ton on speculative calculations assuming that principle holds perfectly which is far from true.

Successful engineering and technology development is not done having a crazy idea that holds only based on a number of highly incertain assumptions but it needs solid ideas developed incrementally iterating from things we already know. First electricity, then basic electronics, the diode, then bipolar transistors, then J-FET, then MOSFET and so on.

> Microsoft insisted its work is sound and in early June 2026 announced Majorana 2, a "next-generation topological quantum chip" it developed with the help of its own agentic AI.

AI hallucinates quantum computing bullshit as well or better than humans can hallucinate quantum computing bullshit. Couldn't have a better combination of technologies helping each other out.

https://en.wikipedia.org/wiki/Majorana_fermion

https://en.wikipedia.org/wiki/Ettore_Majorana