activity
20172026
most citedBethe-Boltzmann Hydrodynamics and Spin Transport in the XXZ Chain

294 citations · 1.2k across the 35 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cond-mat.stat-mech2021★ 53 cited

Onset of many-body quantum chaos due to breaking integrability

Vir B. Bulchandani, David A. Huse, Sarang Gopalakrishnan

Integrable quantum systems of finite size are generically robust against weak enough integrability-breaking perturbations, but become quantum chaotic and thermalizing if the integr…

cond-mat.stat-mech2021

Quasiparticle kinetic theory for Calogero models

Vir B. Bulchandani, Manas Kulkarni, Joel E. Moore +1

We show that the quasiparticle kinetic theory for quantum and classical Calogero models reduces to the free-streaming Boltzmann equation. We reconcile this simple emergent behaviou…

quant-ph2021★ 2 cited

How smooth is quantum complexity?

Vir B. Bulchandani, S. L. Sondhi

The "quantum complexity" of a unitary operator measures the difficulty of its construction from a set of elementary quantum gates. While the notion of quantum complexity was first…

cond-mat.str-el2021★ 8 cited

Hydrodynamics of quantum spin liquids

Vir B. Bulchandani, Benjamin Hsu, Christopher P. Herzog +1

Quantum spin liquids are topological states of matter that arise in frustrated quantum magnets at low temperatures. At low energies, such states exhibit emergent gauge fields and f…

cond-mat.stat-mech2021★ 4 cited

Recursive contact tracing in Reed-Frost epidemic models

Saumya Shivam, Vir B. Bulchandani, S. L. Sondhi

We introduce a Reed-Frost epidemic model with recursive contact tracing and asymptomatic transmission. This generalizes the branching-process model introduced by the authors in a p…

cond-mat.stat-mech2021★ 127 cited

Superdiffusion in spin chains

Vir B. Bulchandani, Sarang Gopalakrishnan, Enej Ilievski

This review summarizes recent advances in our understanding of anomalous transport in spin chains, viewed through the lens of integrability. Numerical advances, based on tensor-net…