arXiv subjects

Jeffrey Z. Song

Publications and source records attributed to Jeffrey Z. Song.

2 recordsLinked to original sources

arXiv2025

A theory of quasiballistic spin transport

A recent work [Mierzejewski et al., Phys. Rev. B 107, 045134 (2023)] observed "quasiballistic spin transport" - long-lived and transiently ballistic modes of the magnetization density - in numerical simulations of infinite-temperature XXZ chains with power-law exchange interactions. We develop an analytical theory of such quasiballistic spin transport. Previous work found that this effect was maximized along a specific locus in the space of model parameters, which interpolated smoothly between the integrable Haldane-Shastry and XX models and whose shape was estimated from numerics. We obtain an analytical estimate for the lifetime of the spin current and show that it has a unique maximum along a different locus, which interpolates more gradually between the two integrable points. We further rule out the existence of a conserved two-body operator that protects ballistic spin transport away from these integrable points by proving that a corresponding functional equation has no solutions. We discuss connections between our approach and an integrability-transport conjecture for spin.

cond-mat.stat-mech↗

arXiv2025

Vari-Cool: a non-unitary quantum variational protocol for simulated cooling

We introduce a variational approach for preparing low energy states of arbitrary target Hamiltonians. The protocol is defined in terms of a repeated cycle consisting of p layers of unitary gates applied to the system and ancilla "bath" qubits, followed by reset of the bath qubits. The gate parameters within each cycle are optimized such that the steady state achieved after many cycles has a low energy expectation value with respect to the target Hamiltonian, and that the energy converges toward the steady state value in as few cycles as possible. We illustrate the protocol for the transverse field Ising model, and study its systematic behaviors with respect to system size, model parameters, and noise using tensor network based classical simulations. We then experimentally demonstrate its operation on IBM's ibm_kingston quantum processor for up to 28 system qubits coupled to 14 bath sites. Classical training on small system sizes and with few unitary layers per cycle gives robust results that transfer well to larger system sizes and to noisy hardware.

quant-ph↗