collaborators

14 papers

cond-mat.mtrl-sci2026

Towards a universal model for spin-orbit coupled Wannier Hamiltonians

Alexander C. Tyner

While machine learning interatomic potentials (MLiPs) have matured to revolutionize material science, deep learning models for electronic structure are just beginning to emerge and…

cond-mat.mes-hall2026

Revealing quantum metric multipoles in magnetic topological insulator MnBi2Te4

Lars Sjöström, Prasanna Rout, Shahid Sattar +9

Nonlinear electronic transport has emerged as a powerful probe of the quantum geometry in topological quantum materials, where the band topology and broken symmetries facilitate po…

cond-mat.mtrl-sci2026

Generation of magnetic metal-organic frameworks

Alexander C. Tyner, Avinash Pathapati, Alexander V. Balatsky

The potential to utilize metal-organic frameworks as a replacement for rare earth materials as well as in technological applications has prompted increased interested in this mater…

cond-mat.mes-hall2025

Simulating alternating bias assisted annealing of amorphous oxide tunnel junctions

Alexander C. Tyner, Alexander V. Balatsky

Amorphous oxide tunneling barriers, primarily formed from aluminum, represent one of the most widely adopted platforms for superconducting quantum bits (qubits). To overcome challe…

cond-mat.mes-hall2025

Machine learning assisted high throughput prediction of moiré materials

Daniel Kaplan, Alexander C. Tyner, Eva Y. Andrei +1

The world of 2D materials is rapidly expanding with new discoveries of stackable and twistable layered systems composed of lattices of different symmetries, orbital character, and…

cond-mat.supr-con2025

Tailoring Superconductivity with Two-Level Systems

Joshuah T. Heath, Alexander C. Tyner, S. Pamir Alpay +2

We investigate the impact of two-level systems (TLSs) on superconductivity, treating them as soft modes localised in real space. We show that these defects can either enhance or su…