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Nature Electronics

Untangling the challenges of quantum computing

Published Mar 30, 2026• 0 citations
Publisher
DOI
10.1038/s41928-026-01607-2

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Quantum Separation Logic (QSL) has been proposed as an effective tool to improve the scalability of deductive reasoning for quantum programs. In QSL, separation is interpreted as disentanglement, and the frame rule brings a notion of entanglement-local specification (one that only talks about the qubits entangled with those acted upon by the program). In this paper, we identify two notions of locality unique to the quantum domain, and we construct a novel quantum separation logic, RapunSL, which is able to soundly reduce reasoning about superposition states to reasoning about pure states (basis-locality), and reasoning about mixed states arising from measurement to reasoning about pure states (outcome-locality). To do so, we introduce two connectives, linear combination and mixing, which together with separation provide a dramatic improvement in the scalability of reasoning, as we demonstrate on a series of challenging case studies.
In my research, we developed a method to distinguish knots. A knot is a mathematical depiction of the everyday knot that occurs in ropes and cords. The distinguishing of knots is a computationally hard problem, which is equivalent with the untangling of knots. Often, knots are distinguished by a so called knot invariant. Such an invariant is a label that can be attributed to any knot, such that the label is identical for two identical knots. The theory of knots is closely related to quantum computing and lattices of atoms. The distinguishing of knots is a problem that can be solved in an exponential number of computations, in the number of crossings of a knot. Our invariants can be computed in polynomial time. This means that the number of computations is a power of the number of crossings of a knot. Another advantage of our method is that for the knots that have been calculated, the invariant was able to distinguish as the most effective methods combined. In fact, by removing unnecessary information from the conventional knot invariants, we obtained an invariant that can be computed much faster, and is as effective as the usual invariants.