SearcharxivSearch

arXiv subjects

Yangyang Du

Publications and source records attributed to Yangyang Du.

3 recordsLinked to original sources

Non-Abelian Spin Counting of Ordered Stochastic Trajectories: Reentrant Finite-Time Chern Numbers

Conventional full counting statistics assigns commuting phases to integrated stochastic currents and therefore resolves net transport but not, in general, the temporal ordering of events associated with different cycles. We introduce a non-Abelian counting construction in which crossings of two fundamental cycles rotate an auxiliary spin about different axes. The resulting ordered trajectory statistic has an exact finite-dimensional evolution equation for its first moment. The two rotation angles form a counting torus, and whenever the mean spin is nonzero its normalized direction defines a map $\mathbb T^2\to\mathbb S^2$, equivalently a complex eigenline bundle with a Chern number. Our main analytical result is a Chern--parity correspondence. Reflection symmetry equips this eigenline with a real structure and expresses $C_T\bmod2$ through first Stiefel--Whitney classes on the circles fixed by reflection. When the transverse polarization has no additional zeros along the reflection-fixed circles, these classes reduce to ordinary current-parity statistics at the four high-symmetry counting points. For a five-state nonequilibrium figure-eight network, varying only the observation time produces four polarization-gap closings and the reentrant sequence $C_T=0\to-1\to0\to-1\to0$. Every transition occurs at $(\pi,\pi)$ and coincides with a sign reversal of $\mathbb E[(-1)^{Q_1+Q_2}]$, while the full integer Chern number is obtained independently from the two-dimensional spin texture. Finite observation time can therefore organize a fixed stochastic process into distinct topological sectors of its ordered path ensemble.

cond-mat.stat-mech

Mazur's knot and the Octahedron

Mazur's knot exterior admits a geometric description using a single regular ideal octahedron. The resulting hyperbolic structure is closely related to the Whitehead link exterior through Adams' theorem on thrice-punctured spheres. The same octahedral framework applies to the family of Jester manifolds introduced by Sparks. Using hyperbolic geometry, Thurston's hyperbolic Dehn filling theorem, and Mostow--Prasad rigidity, we prove that Mazur and Jester boundary 3-manifolds are pairwise distinct up to finite ambiguity. Using recent results on systolic geodesics, we remove the remaining finite ambiguity and prove that the boundaries of all Mazur and Jester manifolds are pairwise nonhomeomorphic, regardless of orientation. Consequently, the corresponding compact, contractible $4$-manifolds are pairwise nonhomeomorphic.

math.GT

Geometric Phase of Stochastic Oscillators

Several definitions of phase have been proposed for stochastic oscillators, among which the mean-return-time phase and the stochastic asymptotic phase have drawn particular attention. Quantitative comparisons between these two definitions have been done in previous studies, but physical interpretations of such a relation are still missing. In this work, we illustrate this relation using the geometric phase, which is an essential concept in both classical and quantum mechanics. We use properties of probability currents and the generalized Doob's h-transform to explain how the geometric phase arises in stochastic oscillators. Such an analogy is also reminiscent of the noise-induced phase shift in oscillatory systems with deterministic perturbation, allowing us to compare the phase responses in deterministic and stochastic oscillators. The resulting framework unifies these distinct phase definitions and reveals that their difference is governed by a geometric drift term analogous to curvature. This interpretation bridges spectral theory, stochastic dynamics, and geometric phase, and provides new insight into how noise reshapes oscillatory behavior. Our results suggest broader applications of geometric-phase concepts to coupled stochastic oscillators and neural models.

math-ph