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On the properties of qudits

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arxiv 2405.13862 v1 pith:AN3OWA27 submitted 2024-05-22 quant-ph hep-phnucl-th

classification quant-phhep-phnucl-th
keywords propertiesstatessystemstwo-qubitwernerdimensionshighertwo-qudit
verification ladder T0 review T1 audit T2 compute T3 formal
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Motivated by the growing interest in the applications of quantum information science in astrophysical settings, especially for the neutrino transport in compact objects where three-flavors of neutrinos need to be mapped on qutrits, we review properties of one- and two-qudit systems. We contrast two-qubit and two-qudits systems by pointing out how some of the properties of two-qubit systems generalize to higher dimensions and explore emerging new properties for dimensions three or higher. One example is provided by the Werner states: when the density operator is written in the fundamental representation, we show that only two-qubit Werner states can be pure states, but not two-qudit Werner states when the qudit dimension is larger than two.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Three-flavor supernova neutrino simulation using a hybrid quantum-classical algorithm with qutrits

    hep-ph 2026-05 unverdicted novelty 7.0 of 10

    A hybrid qutrit-based algorithm simulates supernova neutrino flavor evolution and matches exact classical integration up to moderate times.

  2. Improved Approximations for Collective Neutrino Oscillations

    hep-ph 2026-07 conditional novelty 6.0 of 10

    Second-order BBGKY truncation of an su(n) one-plus-two-body Hamiltonian approximates collective neutrino dynamics beyond mean field at polynomial classical cost and reveals large-N phase and entanglement structure.

  3. Improved Approximations for Collective Neutrino Oscillations

    hep-ph 2026-07 conditional novelty 5.0 of 10

    A second-order BBGKY closure reproduces exact small-system neutrino dynamics about two orders of magnitude better than mean-field at polynomial cost, and predicts correlated large-N behavior.

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