arXiv subjects

Zhouhao Guo

Publications and source records attributed to Zhouhao Guo.

3 recordsLinked to original sources

arXiv2026

Single-eigenstate test of eigenstate thermalization hypothesis via perturbed eigenstate quench

We propose and numerically validate an efficient single-eigenstate diagnostic for the eigenstate thermalization hypothesis (ETH) based on a perturbed eigenstate quench protocol. By introducing a weak random perturbation to an energy eigenstate to break its stationarity, we characterize the time-averaged subsystem evolution speed as a function of the subsystem-to-total system size ratio. The diagnostic relies on a robust qualitative distinction: eigenstates satisfying ETH exhibit an S-shaped curve with a clear inflection point near half the system size, while ETH-violating eigenstates display a convex J-shaped profile. We benchmark the criterion across paradigmatic one-dimensional spin chains covering chaotic, integrable, many-body localized, and quantum many-body scar regimes, obtaining full agreement with established thermalization phenomenology. Our method circumvents the need for explicit thermal ensemble construction, providing a robust, experimentally feasible probe of eigenstate thermalization at the single-eigenstate level.

quant-ph↗

arXiv2026

Additivity of disjoint interval entanglement in quasiparticle excited states

We investigate mixed-state entanglement measures, namely reflected entropy, mutual information and logarithmic negativity, for two disjoint intervals in one-dimensional systems excited by a finite number of quasiparticles. While whole system is in a pure state, the two disjoint intervals are in a generically mixed state. To address the problem that natural subsystem bases are generically non-orthonormal in such excited states, we use a general and efficient algorithm that computes these measures directly from the density matrix expressed in an arbitrary non-orthonormal basis. Applying this method to classical, bosonic, and fermionic quasiparticle excitations on a circle, we discover a universal additivity property: in the limit of large momentum differences, the mixed-state entanglement of a multi-quasiparticle state decomposes exactly into the sum of independent contributions. This additivity unifies the entanglement behavior across classical and quantum statistics, with the classical result emerging naturally as a special case. Our findings establish a robust computational framework for mixed-state entanglement in excited many-body systems and reveal a generic decoupling mechanism that governs entanglement distribution beyond the ground state.

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arXiv2025

Efficient computation of average subsystem Bures distance between fermionic Gaussian states

The average subsystem trace distance has been proposed as an indicator of quantum many-body chaos and integrability. However, evaluating it presents two main difficulties: high computational cost for large systems and ambiguities in defining and ordering eigenstates in integrable systems. In this work, we develop an efficient algorithm to compute the Bures distance between fermionic Gaussian states, enabling access to larger system sizes. Using this method, we calculate the average subsystem Bures distance for eigenstates in the spin-1/2 transverse-field Ising chain and the Dirac fermion formulation of the quadratic Sachdev-Ye-Kitaev (Dirac SYK$_2$) model, as well as for random pure fermionic Gaussian states. To handle degeneracy in the Ising chain, we consider simultaneous eigenstates of all local conserved charges and employ these charges to systematically order degenerate states. Our results are consistent with the earlier conjecture of a linear growth with subsystem size. We show that the distinct scaling of the average subsystem distances in chaotic versus integrable systems originates from discontinuities of local conserved charges across the spectrum in integrable models. For the Dirac SYK$_2$ model and random pure Gaussian states, we obtain similar results for the average subsystem distances, which do not show a linear increase.

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