activity
19962026
most citedMagnetic Monopoles in Spin Ice

1.5k citations · 27.2k across the 426 of their papers we have counts for

collaborators

429 papers

cond-mat.mes-hall2026

Gentle Floquet control of orbital Hall effect and orbital inverse Faraday effect

Pei-Han Lin, Roderich Moessner, Egor I. Kiselev

Floquet engineering controls material responses via a time-periodic electromagnetic drive. An important task in practice is to reduce the driving strengths required to implement Fl…

cond-mat.str-el2026

Berry-Landau Fermi-liquid theory: transport in presence of quantum geometry

Shuai A. Chen, Roderich Moessner

Landau Fermi-liquid theory characterizes interacting metals through quasiparticles and their residual interactions. It is a challenge to incorporate non-trivial quantum geometry --…

cond-mat.stat-mech2026

Breakdown of Multipole Expansion in Emergent Electromagnetism

Tom Ben-Ami, Markus Heyl, Roderich Moessner

We find a striking departure from simple electrostatics in a family of two-dimensional lattice models whose effective description takes the form of an emergent electromagnetism: a…

cond-mat.stat-mech2026

Transient and universal regimes in quantum reaction-transport kinetics

Hossein Hosseinabadi, Roderich Moessner

Quantum reaction-transport systems consist of coherently propagating particles that irreversibly react upon encounter. Their relaxation is commonly classified as reaction-limited o…

cond-mat.str-el2026

Exact quantum spin liquids with topological order on maple-leaf and trellis lattices

Li Ern Chern, Roderich Moessner, Claudio Castelnovo

We construct spin models with bond-dependent anisotropic interactions on the penta-coordinated maple-leaf and trellis lattices, which yield exact quantum spin liquid…

quant-ph2026

Reinforcement Learning to Harness Approximation Errors for Long-Time Quantum Simulation

Yu-Bo Shi, Markus Heyl, Roderich Moessner +2

Accurate digital quantum simulation at long times is limited by the accumulation of errors inherent to approximate simulation. Here we introduce RL-Trotter, a reinforcement-learnin…