activity
20232026
most citedCharacterization of Magnetic Labyrinthine Structures Through Junctions and Terminals Detection Using Template Matching and CNN

3 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cond-mat.soft2026

Coarsening dynamics of fingerprint labyrinthine patterns: Machine learning assisted characterization

Supriyo Ghosh, Vinicius Yu Okubo, Kotaro Shimizu +3

Fingerprint labyrinthine patterns exhibit a level of structural complexity beyond simple stripe phases, combining local stripe order with a dense network of point-like defects. Unl…

cond-mat.str-el2024★ 1 cited

Disorder-induced spin-cluster magnetism in a doped kagome spin liquid candidate

Arnab Seth, Joseph C. Prestigiacomo, Aini Xu +6

The search for new quantum spin liquid materials relies on systems with strong frustration such as spins on an ideal kagome lattice. However, lattice imperfections can have substan…

cond-mat.str-el2024

Magnetic Nonlinear Response of UPt: An augmented Landau approach

Trevor D. Ford, K. Matsumoto, B. S. Shivaram

Several heavy fermion materials, including UPt, exhibit a rapid but gradual rise in the magnetization at a critical field, without an apparent phase transition at any temperatu…

cond-mat.str-el2024

Non-Analytic Magnetic Response and Intrinsic Ferromagnetic Clusters in a Dirac Spin Liquid Candidate

B. S. Shivaram, J. Prestigiacomo, Aini Xu +5

Finding distinct signatures of a quantum spin liquid (QSL) is an ongoing quest in condensed matter physics, invariably complicated by the presence of disorder in real materials. In…

cs.CV2024★ 3 cited

Characterization of Magnetic Labyrinthine Structures Through Junctions and Terminals Detection Using Template Matching and CNN

Vinícius Yu Okubo, Kotaro Shimizu, B. S. Shivaram +1

Defects influence diverse properties of materials, shaping their structural, mechanical, and electronic characteristics. Among a variety of materials exhibiting unique defects, mag…

cond-mat.soft2023

Machine Learning Assisted Characterization of Labyrinthine Pattern Transitions

Kotaro Shimizu, Vinicius Yu Okubo, Rose Knight +5

We present a comprehensive approach to characterizing labyrinthine structures that often emerge as a final steady state in pattern forming systems. We employ advanced machine learn…