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Chromium trihalides (CrX3, with X=I,Br,Cl) are layered ferromagnetic materials with rich physics and possible applications. Their structure consists of magnetic Cr atoms positioned between two layers of halide atoms. The choice of halide results in distinct magnetic properties, but their effect on spin-wave (magnon) excitations is not fully understood. Here we present first-principles calculations of magnon dispersions and wave functions for monolayer Cr trihalides using the finite-momentum Bethe-Salpeter equation (BSE) to describe collective spin-flip excitations. We study the dependence of magnon dispersions on the halide species and resolve the small topological gap at the Dirac point in the magnon spectrum by including spin-orbit coupling. Analysis of magnon wave functions reveals that magnons are made up of electronic transitions with a wider energy range than excitons in CrX3 monolayers, providing insight into magnon states in real and reciprocal space. We discuss Heisenberg exchange parameters extracted from the BSE and discuss the convergence of BSE magnon calculations. Our work advances the quantitative modeling of magnons in two-dimensional materials, providing the starting point for studying magnon interactions in a first-principles BSE framework. 

Modeling spin-wave (magnon) dynamics in novel materials is important to advance spintronics and spin-based quantum technologies. The interactions between magnons and lattice vibrations (phonons) limit the length scale for magnon transport. However, quantifying these interactions remains challenging. Here we show many-body calculations of magnon-phonon (mag-ph) coupling based on the ab initio Bethe-Salpeter equation. We derive expressions for mag-ph coupling matrices and compute them in 2D ferromagnets, focusing on hydrogenated graphene and monolayer CrI3. Our analysis shows that electron-phonon (e-ph) and mag-ph interactions differ significantly, where modes with weak e-ph coupling can exhibit strong mag-ph coupling (and vice versa), and reveals which phonon modes couple more strongly with magnons. In both materials studied here, the inelastic magnon relaxation time is found to decrease abruptly above the threshold for emission of strongly coupled phonons, thereby defining a low-energy window for efficient magnon transport. By averaging in this window, we compute the temperature-dependent magnon mean-free path, a key figure of merit for spintronics, entirely from first principles. The theory and computational tools shown in this work enable studies of magnon interactions, scattering, and dynamics in generic materials, advancing the design of magnetic systems and magnon- and spin-based devices. 

Abstract A three‐stage rail‐to‐rail bulk‐driven class AB OTA that operates with ±0.15 V supplies and a power dissipation of 90 nW is introduced. The first two stages use resistive local common mode feedback. The OTA uses simple phase lead compensation. It has a 36 MHz.pF/μW small signal figure of merit and a 55(V/μs) pF/μW large signal figure of merit. 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.