Master Lovas-Andai and Equivalent Formulas Verifying the Two-Qubit Hilbert-Schmidt Separability Probability and Companion Rational-Valued Conjectures
arXiv:1701.01973 · doi:10.1007/s11128-018-1854-5
Abstract
We begin by investigating relationships between two forms of Hilbert-Schmidt two-re[al]bit and two-qubit "separability functions"--those recently advanced by Lovas and Andai (J. Phys. A 50 [2017] 295303), and those earlier presented by Slater (J. Phys. A 40 [2007] 14279). In the Lovas-Andai framework, the independent variable is the ratio of the singular values of the matrix formed from the two diagonal blocks () of a density matrix . In the Slater setting, the independent variable is the diagonal-entry ratio --with, of central importance, or when both and are themselves diagonal. Lovas and Andai established that their two-rebit "separability function" () yields the previously conjectured Hilbert-Schmidt separability probability of . We are able, in the Slater framework (using cylindrical algebraic decompositions [CAD] to enforce positivity constraints), to reproduce this result. Further, we newly find its two-qubit (yielding ), two-quater[nionic]-bit (yielding ) and "two-octo[nionic]-bit" (yielding ) counterparts. Then, we find a Lovas-Andai "master formula", encompassing both even and odd values of . C. Koutschan, then, using his HolonomicFunctions program, develops an order-4 recurrence satisfied by the predictions of the several formulas, establishing their equivalence.
59 pages, 29 figures, retitled, added App. A, presenting previously-obtained (arXiv:0805.0267) analogous ABSOLUTE separability probabilities
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- Numerical and Exact Analyses of Bures and Hilbert-Schmidt Separability and PPT-Probabilities
- Extensions of Generalized Two-Qubit Separability Probability Analyses to Higher Dimensions, Additional Measures and New Methodologies
- On the generation of random ensembles of qubits and qutrits Computing separability probabilities for fixed rank states
- Quasirandom estimations of two-qubit operator-monotone-based separability probabilities