activity
20132026
most citedZero-field superconducting diode effect in small-twist-angle trilayer graphene

295 citations · 3.3k across the 91 of their papers we have counts for

collaborators
Showing 2020Show all

13 papers · 1 filter

cond-mat.supr-con2020★ 28 cited

Time-reversal symmetry breaking and multigap superconductivity in the noncentrosymmetric superconductor LaNi

Arushi, D. Singh, A. D. Hillier +2

The ThFe family of superconductors provides a rich playground for unconventional superconductivity. LaNi is the latest member of this family, which we here inve…

cond-mat.str-el2020★ 2 cited

Learning crystal field parameters using convolutional neural networks

Noah F. Berthusen, Yuriy Sizyuk, Mathias S. Scheurer +1

We present a deep machine learning algorithm to extract crystal field (CF) Stevens parameters from thermodynamic data of rare-earth magnetic materials. The algorithm employs a two-…

cond-mat.str-el2020★ 100 cited

Universal moiré nematic phase in twisted graphitic systems

Carmen Rubio-Verdú, Simon Turkel, Larry Song +12

Graphene moiré superlattices display electronic flat bands. At integer fillings of these flat bands, energy gaps due to strong electron-electron interactions are generally observed…

cond-mat.str-el2020★ 37 cited

Anomalous mirror symmetry breaking in a model insulating cuprate SrCuOCl

A. de la Torre, K. L. Seyler, L. Zhao +8

Understanding the complex phase diagram of cuprate superconductors is an outstanding challenge. The most actively studied questions surround the nature of the pseudogap and strange…

cond-mat.str-el2020★ 95 cited

Superconductivity, correlated insulators, and Wess-Zumino-Witten terms in twisted bilayer graphene

Maine Christos, Subir Sachdev, Mathias S. Scheurer

Recent experiments on twisted bilayer graphene have shown a high-temperature parent state with massless Dirac fermions and broken electronic flavor symmetry; superconductivity and…

cond-mat.stat-mech2020★ 29 cited

Generative models for sampling and phase transition indication in spin systems

Japneet Singh, Vipul Arora, Vinay Gupta +1

Recently, generative machine-learning models have gained popularity in physics, driven by the goal of improving the efficiency of Markov chain Monte Carlo techniques and of explori…