Universality and Critical Behavior at the Critical-End-Point on Itinerant-Metamagnet UCoAl

We performed nuclear-magnetic-resonance (NMR) measurements on itinerant-electron metamagnet UCoAl in order to investigate the critical behavior of the magnetism near a metamagnetic (MM) critical endpoint (CEP). We derived c-axis magnetization $M_c$ and its fluctuation $S_c$ from the measurements of Knight shift and nuclear spin-lattice relaxation rate $1/T_1$ as a function of the c-axis external field ($H_c$) and temperature ($T$). We developed contour plots of $M_c$ and $S_c$ on the $H_c$ - $T$ phase diagram, and observed the strong divergence of $S_c$ at the CEP. The critical exponents of $M_c$ and $S_c$ near the CEP are estimated, and found to be close to the universal properties of a three-dimensional (3-D) Ising model. We indicate that the critical phenomena at the itinerant-electron MM CEP in UCoAl have a common feature as a gas-liquid transition.Comment: 8 Pages, 14 figure

Disordered skyrmion phase stabilized by magnetic frustration in a chiral magnet

Magnetic skyrmions are vortex-like topological spin textures often observed to form a triangular-lattice skyrmion crystal in structurally chiral magnets with Dzyaloshinskii-Moriya interaction. Recently $\beta$-Mn structure-type Co-Zn-Mn alloys were identified as a new class of chiral magnet to host such skyrmion crystal phases, while $\beta$-Mn itself is known as hosting an elemental geometrically frustrated spin liquid. Here we report the intermediate composition system Co$_7$Zn$_7$Mn$_6$ to be a unique host of two disconnected, thermal-equilibrium topological skyrmion phases; one is a conventional skyrmion crystal phase stabilized by thermal fluctuations and restricted to exist just below the magnetic transition temperature $T_\mathrm{c}$, and the other is a novel three-dimensionally disordered skyrmion phase that is stable well below $T_\mathrm{c}$. The stability of this new disordered skyrmion phase is due to a cooperative interplay between the chiral magnetism with Dzyaloshinskii-Moriya interaction and the frustrated magnetism inherent to $\beta$-Mn.Comment: 57 pages, 16 figure

Task-adaptive physical reservoir computing

Reservoir computing is a neuromorphic architecture that may offer viable solutions to the growing energy costs of machine learning. In software-based machine learning, computing performance can be readily reconfigured to suit different computational tasks by tuning hyperparameters. This critical functionality is missing in 'physical' reservoir computing schemes that exploit nonlinear and history-dependent responses of physical systems for data processing. Here we overcome this issue with a 'task-adaptive' approach to physical reservoir computing. By leveraging a thermodynamical phase space to reconfigure key reservoir properties, we optimize computational performance across a diverse task set. We use the spin-wave spectra of the chiral magnet Cu2OSeO3 that hosts skyrmion, conical and helical magnetic phases, providing on-demand access to different computational reservoir responses. The task-adaptive approach is applicable to a wide variety of physical systems, which we show in other chiral magnets via above (and near) room-temperature demonstrations in Co8.5Zn8.5Mn3 (and FeGe)