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A. B. Moubissi

Publications and source records attributed to A. B. Moubissi.

2 recordsLinked to original sources

Classical observable coalescence as a discriminating diagnostic for spectral degeneracies in non-Hermitian systems

Exceptional points (EPs) are conventionally identified through eigenvector coalescence, inaccessible in classical platforms lacking a Hamiltonian spectrum. We introduce classical observable coalescence as a diagnostic identifying EPs directly from physical configurations, and demonstrate it in a known non-Hermitian Ising chain with coupling $J$ and staggered imaginary field $γ$, chosen for verifiability against established quantum results. A mean-field reduction of the Heisenberg dynamics yields equilibrium branches organising into two symmetry-related families whose fusion at the boundary of the EP supersurface $|γ|=|J|$ exhibits the characteristic $\sqrt{J^2-γ^2}$ branch-point structure and two-sheeted Riemann topology. Crucially, the degeneracy at $γ=0,η=0 $ is shown to be a diabolic point, producing no observable coalescence, establishing the diagnostic as discriminating rather than merely suggestive. An exact Jordan-Wigner and Bogoliubov-de Gennes treatment confirms eigenvector coalescence at the same threshold, and a coupled gain-loss circuit realisation is proposed, establishing classical observables as experimentally accessible signatures of non-Hermitian criticality.

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Topologically Protected Learning from Exceptional Point Braiding: Toward Braid Programming

We present a framework for topological learning based on exceptional point (EP) braiding in a non-Hermitian Bogoliubov-de Gennes Hamiltonian. A closed algebraic equation for the EP super-surface is derived; through momentum quantisation in finite systems, it predicts the exact number and parameter positions of all EPs in real space, irrespective of system size. The EP topology is characterised by two quantised invariants the state-swap fidelity and the normalised Berry phase which cannot both be zero for a topological EP. A complete topological map shows that all EPs lie within a specefic region. Adiabatic encirclements confirm robust state swapping and yield a universal set of braid gates, including Pauli-X, Pauli-Y, Pauli-Z, a Hadamard-like gate, the T-gate, and a SWAP operation, with the special case where a is 0, providing additional phase gates. Building on these generators, we reformulate learning as braid programming a discrete search over the braid group that replaces gradient descent on continuous weights with combinatorial optimisation. A proof-of-concept genetic search successfully discovers short braid words that reproduce the standard Hadamard gate and the H.Z gate with perfect fidelity. This paradigm offers inherent noise immunity, catastrophic-forgetting prevention through compositional concatenation, and guaranteed generalisation by mathematical construction, establishing EP braiding as a promising substrate for robust, interpretable, and topologically protected neuromorphic computation.

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