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We unveil the impact of the $\theta$-angle on the QCD phase diagram at nonzero isospin and strangeness chemical potentials for three light flavors and different quark mass ratios. We establish the phase boundaries as well as the nature of the associated phase transitions. The order parameters and the physical spectrum in the different phases are determined. We further elucidate the physics around $\theta=\pi$ where we discover a novel parity-preserving superfluid phase. Finally, we comment on Dashen's phenomenon in the superfluid phases when varying the number of light flavors., Comment: 35 pages, 11 figures

With the advent of portable 360{\deg} cameras, panorama has gained significant attention in applications like virtual reality (VR), virtual tours, robotics, and autonomous driving. As a result, wide-baseline panorama view synthesis has emerged as a vital task, where high resolution, fast inference, and memory efficiency are essential. Nevertheless, existing methods are typically constrained to lower resolutions (512 $\times$ 1024) due to demanding memory and computational requirements. In this paper, we present PanSplat, a generalizable, feed-forward approach that efficiently supports resolution up to 4K (2048 $\times$ 4096). Our approach features a tailored spherical 3D Gaussian pyramid with a Fibonacci lattice arrangement, enhancing image quality while reducing information redundancy. To accommodate the demands of high resolution, we propose a pipeline that integrates a hierarchical spherical cost volume and Gaussian heads with local operations, enabling two-step deferred backpropagation for memory-efficient training on a single A100 GPU. Experiments demonstrate that PanSplat achieves state-of-the-art results with superior efficiency and image quality across both synthetic and real-world datasets. Code will be available at \url{https://github.com/chengzhag/PanSplat}., Comment: Project Page: https://chengzhag.github.io/publication/pansplat/ Code: https://github.com/chengzhag/PanSplat

This paper addresses the incorporation of problem decomposition skills as an important component of computational thinking (CT) in K-12 computer science (CS) education. Despite the growing integration of CS in schools, there is a lack of consensus on the precise definition of CT in general and decomposition in particular. While decomposition is commonly referred to as the starting point of (computational) problem-solving, algorithmic solution formulation often receives more attention in the classroom, while decomposition remains rather unexplored. This study presents "CTSKills", a web-based skill assessment tool developed to measure students' problem decomposition skills. With the data collected from 75 students in grades 4-9, this research aims to contribute to a baseline of students' decomposition proficiency in compulsory education. Furthermore, a thorough understanding of a given problem is becoming increasingly important with the advancement of generative artificial intelligence (AI) tools that can effectively support the process of formulating algorithms. This study highlights the importance of problem decomposition as a key skill in K-12 CS education to foster more adept problem solvers.

We present a comprehensive set of harmonic resistance measurements of the dampinglike (DL) and fieldlike (FL) torques in Pt/CoFeB, Pt/Co, W/CoFeB, W/Co, and YIG/Pt bilayers complemented by measurements of the DL torque using the magneto-optical Kerr effect and calibrated by nitrogen vacancy magnetometry on the same devices. The magnon creation-annihilation magnetoresistances depend strongly on temperature and on the magnetic and transport properties of each bilayer, affecting the estimate of both the DL and FL torque. The DL torque, the most important parameter for applications, is overestimated by a factor of 2 in W/CoFeB and by one order of magnitude in YIG/Pt when not accounting for the magnonic contribution to the planar Hall resistance. We further show that the magnonic contribution can be quantified by combining measurements of the nonlinear longitudinal and transverse magnetoresistances, thus providing a reliable method to measure the spin-orbit torques in different material systems.

Charge-spin conversion phenomena such as the spin Hall effect allow for the excitation of magnons in a magnetic layer by passing an electric current in an adjacent nonmagnetic conductor. We demonstrate that this current-induced modification of the magnon density generates an additional nonlinear longitudinal and transverse magnetoresistance for every magnetoresistance that depends on the magnetization. Using harmonic measurements, we evidence that these magnon creation-annihilation magnetoresistances dominate the second harmonic longitudinal and transverse resistance of thin Y$_{3}$Fe$_{5}$O$_{12}$/Pt bilayers. Our results apply to both insulating and metallic magnetic layers, elucidating the dependence of the magnetoresistance on applied current and magnetic field for a broad variety of systems excited by spin currents.

Quantum magnetometers based on spin defects in solids enable sensitive imaging of various magnetic phenomena, such as ferro- and antiferromagnetism, superconductivity, and current-induced fields. Existing protocols primarily focus on static fields or narrow-band dynamical signals, and are optimized for high sensitivity rather than fast time resolution. Here, we report detection of fast signal transients, providing a perspective for investigating the rich dynamics of magnetic systems. We experimentally demonstrate our technique using a single nitrogen-vacancy (NV) center magnetometer at room temperature, reaching a best-effort time resolution of 1.1 ns, an instantaneous bandwidth of 0.9 GHz, and a time-of-flight precision better than 20 ps. The time resolution can be extended to the picosecond range by use of on-chip waveguides. At these speeds, NV quantum magnetometers will become competitive with time-resolved synchrotron X-ray techniques. Looking forward, adding fast temporal resolution to the spatial imaging capability further promotes single-spin probes as powerful research tools in spintronics, mesoscopic physics, and nanoscale device metrology., Comment: 11 pages including methods

Spin chirality in antiferromagnets offers new opportunities for spintronics. The kagome antiferromagnet Mn3Sn is a paradigmatic material in which the antiferromagnetic order parameter can be detected and controlled by electrical means. However, direct investigation of the magnetic texture of Mn3Sn has been challenging because of the tiny moment hosted in its magnetic octupole, hindering further clarification of this unique material. Here, we address this issue by observing the stray magnetic field from Mn3Sn using a diamond quantum scanning magnetometer. The spatially-resolved intrinsic domains and domain walls in a high-quality single-crystalline Mn3Sn film quantitatively reveal the polarization angle of the magnetic octupole in the kagome plane, the domain's local magnetization, the domain wall's width and chirality, and the octupole order in domain walls. Our nanoscale investigation of Mn3Sn, a powerful complement to macroscopic measurements, paves the road for developing chiral antiferromagnetism and its potential for spintronic applications., Comment: 17 pages, 4 figures

Recent large language models (LLMs) have demonstrated remarkable generalization abilities in mathematics and logical reasoning tasks. Prior research indicates that LLMs pre-trained with programming language data exhibit high mathematical and reasoning abilities; however, this causal relationship has not been rigorously tested. Our research aims to verify which programming languages and features during pre-training affect logical inference performance. Specifically, we pre-trained decoder-based language models from scratch using datasets from ten programming languages (e.g., Python, C, Java) and three natural language datasets (Wikipedia, Fineweb, C4) under identical conditions. Thereafter, we evaluated the trained models in a few-shot in-context learning setting on logical reasoning tasks: FLD and bAbi, which do not require commonsense or world knowledge. The results demonstrate that nearly all models trained with programming languages consistently outperform those trained with natural languages, indicating that programming languages contain factors that elicit logic inference performance. In addition, we found that models trained with programming languages exhibit a better ability to follow instructions compared to those trained with natural languages. Further analysis reveals that the depth of Abstract Syntax Trees representing parsed results of programs also affects logical reasoning performance. These findings will offer insights into the essential elements of pre-training for acquiring the foundational abilities of LLMs.

As large language models (LLMs) are applied across diverse domains, the ability to selectively unlearn specific information has become increasingly essential. For instance, LLMs are expected to provide confidential information to authorized internal users, such as employees or trusted partners, while withholding it from external users, including the general public and unauthorized entities. In response to this challenge, we propose a novel method termed ``in-context knowledge unlearning'', which enables the model to selectively forget information in test-time based on the context of the query. Our method fine-tunes pre-trained LLMs to enable prompt unlearning of target knowledge within the context, while preserving other knowledge. Experiments on the TOFU and AGE datasets using Llama2-7B/13B and Mistral-7B models show our method achieves up to 95% forgetting accuracy while retaining 80% of unrelated knowledge, significantly outperforming baselines in both in-domain and out-of-domain scenarios. Further investigation into the model's internal behavior revealed that while fine-tuned LLMs generate correct predictions in the middle layers and maintain them up to the final layer, they make the decision to forget at the last layer, i.e., ``LLMs pretend to forget''. Our findings offer valuable insights into enhancing the robustness of unlearning mechanisms in LLMs, setting a foundation for future research in the field.

The interfacial Dzyaloshinskii-Moriya interaction (DMI) can be exploited in magnetic thin films to realize lateral chirally coupled systems, providing a way to couple different sections of a magnetic racetrack and realize interconnected networks of magnetic logic gates. Here, we systematically investigate the interplay between spin-orbit torques, chiral coupling and the device design in domain wall racetracks. We show that the current-induced domain nucleation process can be tuned between single-domain nucleation and repeated nucleation of alternate domains by changing the orientation of an in-plane patterned magnetic region within an out-of-plane magnetic racetrack. Furthermore, by combining experiments and micromagnetic simulations, we show that the combination of damping-like and field-like spin-orbit torques with DMI results in selective domain wall injection in one of two arms of a Y-shaped devices depending on the current density. Such an element constitutes the basis of domain wall based demultiplexer, which is essential for distributing a single input to any one of the multiple outputs in logic circuits. Our results provide input for the design of reliable and multifunctional domain-wall circuits based on chirally coupled interfaces.

One of the key elements in spintronics research is the spin Hall effect, allowing to generate spin currents from charge currents. A large spin Hall effect is observed in materials with strong spin orbit coupling, e.g., Pt. Recent research suggests the existence of an orbital Hall effect, the orbital analogue to the spin Hall effect, which also arises in weakly spin orbit coupled materials like Ti, Mn or Cr. In Pt both effects are predicted to coexist. In any of these materials, a magnetic field perpendicular to the spin or orbital accumulation leads to additional Hanle dephasing and thereby the Hanle magnetoresistance (MR). To reveal the MR behavior of a material with both spin and orbital Hall effect, we thus study the MR of Pt thin films over a wide range of thicknesses. Careful evaluation shows that the MR of our textured samples is dominated by the ordinary MR rather than by the Hanle effect. We analyze the intrinsic properties of Pt films deposited by different groups and show that next to the resistivity also the structural properties of the film influence which MR dominates. We further show that this correlation can be found in both spin Hall active materials like Pt and orbital Hall active materials, like Ti. For both materials, the crystalline samples shows a MR attributed to the ordinary MR, whereas we find a large Hanle MR for the samples without apparent structural order. We then provide a set of rules to distinguish between the ordinary and the Hanle MR. We conclude that in all materials with a spin or orbital Hall effect the Hanle MR and the ordinary MR coexist and the purity and crystallinity of the thin film determine the dominating effect.

The writing energy for reversing the magnetization of the free layer in a magnetic tunnel junction (MTJ) is a key figure of merit for comparing the performances of magnetic random access memories with competing technologies. Magnetization switching of MTJs induced by spin torques typically relies on square voltage pulses. Here, we focus on the switching of perpendicular MTJs driven by spin-orbit torque (SOT), for which the magnetization reversal process consists of sequential domain nucleation and domain wall propagation. By performing a systematic study of the switching efficiency and speed as a function of pulse shape, we show that shaped pulses achieve up to 50% reduction of writing energy compared to square pulses without compromising the switching probability and speed. Time-resolved measurements of the tunneling magnetoresistance reveal how the switching times are strongly impacted by the pulse shape and temperature rise during the pulse. The optimal pulse shape consists of a preheating phase, a maximum amplitude to induce domain nucleation, and a lower amplitude phase to complete the reversal. Our experimental results, corroborated by micromagnetic simulations, provide diverse options to reduce the energy footprint of SOT devices in magnetic memory applications., Comment: 10 pages, 7 figures

Charge-spin interconversion processes underpin the generation of spin-orbit torques in magnetic/nonmagnetic bilayers. However, efficient sources of spin currents such as 5d metals are also efficient spin sinks, resulting in a large increase of magnetic damping. Here we show that a partially-oxidized 3d metal can generate a strong orbital torque without a significant increase in damping. Measurements of the torque efficiency {\xi} and Gilbert damping {\alpha} in CoFe/CuOx and CoFe/Pt indicate that {\xi} is comparable. The increase in damping relative to a single CoFe layer is {\Delta}{\alpha}<0.002 in CoFe/CuOx and {\Delta}{\alpha} ~ 0.005 - 0.02 in CoFe/Pt, depending on CoFe thickness. We ascribe the nonreciprocal relationship between {\Delta}{\alpha} and {\xi} in CoFe/CuOx to the small orbital-to-spin current ratio generated by magnetic resonance in CoFe and the lack of an efficient spin sink in CuOx. Our findings provide new perspectives on the efficient excitation of magnetization dynamics via the orbital torque.

The magnetic resonance of iron garnets is at the heart of rich physics and provides a crucial technology used inside microwave components. A barrier still stands in the way of integrated cryogenic devices with iron garnets, because their epitaxy requires paramagnetic substrates that cause large microwave losses at low temperatures. Finding alternative combinations of substrates and magnetic garnets is thus essential to enabling cryogenic integrated magnonics. With this motivation, we develop a new approach to the synthesis of epitaxial garnet films, based on the co-sputtering of binary oxides, enabling a precise and continuous tuning of the iron garnet composition. By substituting a controlled proportion of the iron with additional yttrium, we obtain Y$_{3}$(Y$_{x}$Fe$_{5-x}$)O$_{12}$ films of high crystalline quality that can be lattice-matched to yttrium scandium gallium garnet (YSGG), a diamagnetic substrate suitable for low-temperature applications. Ferromagnetic resonance performed at low temperatures confirms the elimination of substrate paramagnetism losses on YSGG. We also show that the Y$_{3}$(Y$_{x}$Fe$_{5-x}$)O$_{12}$ system can be matched to other substrates, such as gadolinium yttrium scandium gallium garnet and gadolinium scandium gallium garnet. Additionally, we demonstrate that Bi-substituted films of (Bi$_{0.8}$Y$_{2.2}$)Fe$_{5}$O$_{12}$ also offer ideal lattice matching to YSGG for low-temperature magnetic resonance. The present approach of controlled substitutions in iron garnets to obtain ideal lattice matching with diamagnetic substrates opens a very promising pathway to magnonic devices operating in low-temperature environments., Comment: Main: 18 pages, 6 figures; Supplement: 9 pages, 6 figures

Orbital currents have recently emerged as a promising tool to achieve electrical control of the magnetization in thin-film ferromagnets. Efficient orbital-to-spin conversion is required in order to torque the magnetization. Here we show that the injection of an orbital current in a ferrimagnetic GdyCo100-y alloy generates strong orbital torques whose sign and magnitude can be tuned by changing the Gd content and temperature. The effective spin-orbital Hall angle reaches up to -0.25 in a GdyCo100-y/CuOx bilayer compared to +0.03 in Co/CuOx and +0.13 in GdyCo100-y/Pt. This behavior is attributed to the local orbital-to-spin conversion taking place at the Gd sites, which is about five times stronger and of the opposite sign relative to Co. Furthermore, we observe a manyfold increase in the net orbital torque at low temperature, which we attribute to the improved conversion efficiency following the magnetic ordering of the Gd and Co sublattices.

Control over quantum systems is typically achieved by time-dependent electric or magnetic fields. Alternatively, electronic spins can be controlled by spin-polarized currents. Here we demonstrate coherent driving of a single spin by a radiofrequency spin-polarized current injected from the tip of a scanning tunneling microscope into an organic molecule. With the excitation of electron paramagnetic resonance, we established dynamic control of single spins by spin torque using a local electric current. In addition our work highlights the dissipative action of the spin-transfer torque, in contrast to the nondissipative action of the magnetic field, which allows for the manipulation of individual spins based on controlled decoherence.

The ability (and inability) of large language models (LLMs) to perform arithmetic tasks has been the subject of much theoretical and practical debate. We show that LLMs are frequently able to correctly and confidently predict the first digit of n-digit by m-digit multiplication tasks without using chain of thought reasoning, despite these tasks require compounding operations to solve. Simultaneously, LLMs in practice often fail to correctly or confidently predict the last digit of an n-digit by m-digit multiplication, a task equivalent to 1-digit by 1-digit multiplication which can be easily learned or memorized. We show that the latter task can be solved more robustly when the LLM is conditioned on all of the correct higher-order digits, which on average increases the confidence of the correct last digit on 5-digit by 5-digit multiplication tasks using Llama 2-13B by over 230% (0.13 to 0.43) and Mistral-7B by 150% (0.22 to 0.55)., Comment: In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

In this work, we study the metric Steiner Tree problem on graphs focusing on computing lower bounds for the integrality gap of the bi-directed cut (DCUT) formulation and introducing a novel formulation, the Complete Metric (CM) model, specifically designed to address the weakness of the DCUT formulation on metric instances. A key contribution of our work is extending of the Gap problem, previously explored in the context of the Traveling Salesman problems, to the metric Steiner Tree problem. To tackle the Gap problem for Steiner Tree instances, we first establish several structural properties of the CM formulation. We then classify the isomorphism classes of the vertices within the CM polytope, revealing a correspondence between the vertices of the DCUT and CM polytopes. Computationally, we exploit these structural properties to design two complementary heuristics for finding nontrivial small metric Steiner instances with a large integrality gap. We present several vertices for graphs with a number of nodes $\leq 10$, which realize the best-known lower bounds on the integrality gap for the CM and the DCUT formulations. We conclude the paper by presenting three new conjectures on the integrality gap of the DCUT and CM formulations for small graphs., Comment: 27 pages, 4 figures

Generative models, e.g., Stable Diffusion, have enabled the creation of photorealistic images from text prompts. Yet, the generation of 360-degree panorama images from text remains a challenge, particularly due to the dearth of paired text-panorama data and the domain gap between panorama and perspective images. In this paper, we introduce a novel dual-branch diffusion model named PanFusion to generate a 360-degree image from a text prompt. We leverage the stable diffusion model as one branch to provide prior knowledge in natural image generation and register it to another panorama branch for holistic image generation. We propose a unique cross-attention mechanism with projection awareness to minimize distortion during the collaborative denoising process. Our experiments validate that PanFusion surpasses existing methods and, thanks to its dual-branch structure, can integrate additional constraints like room layout for customized panorama outputs. Code is available at https://chengzhag.github.io/publication/panfusion., Comment: CVPR 2024. Project Page: https://chengzhag.github.io/publication/panfusion Code: https://github.com/chengzhag/PanFusion

In recent years, the emphasis on computational thinking (CT) has intensified as an effect of accelerated digitalisation. While most researchers are concentrating on defining CT and developing tools for its instruction and assessment, we focus on the characteristics of computational thinking problems (CTPs) - activities requiring CT to be solved - and how they influence the skills students can develop. In this paper, we present a comprehensive framework for systematically profiling CTPs by identifying specific components and characteristics, while establishing a link between these attributes and a structured catalogue of CT competencies. The purposes of this framework are (i) facilitating the analysis of existing CTPs to identify which abilities can be developed or measured based on their inherent characteristics, and (ii) guiding the design of new CTPs targeted at specific skills by outlining the necessary characteristics required for CT activation. To illustrate the framework functionalities, we begin by analysing prototypical activities in the literature, a process that leads to the definition of a taxonomy of CTPs across various domains, and we conclude with a case study on the design of a different version of one of these activities, the Cross Array Task (CAT), set in different cognitive environments. This approach allows an understanding of how CTPs in different contexts display unique and recurring characteristics that promote the development of distinct skills. In conclusion, this framework can inform the development of assessment tools, improve teacher training, and facilitate the analysis and comparison of existing CT activities, contributing to a deeper understanding of competency activation and guiding curriculum design in CT education.

We report an axion dark matter search with a haloscope equipped with a microwave photon counter. The haloscope is a tunable high quality factor 3-dimensional microwave cavity placed in a magnetic field. The photon counter, operated cyclically, maps an incoming microwave photon onto the state of a superconducting transmon qubit. The measurement protocol continuously monitors the power emitted by the haloscope cavity as well as the dark count background, and enables tuning of the cavity frequency to probe different axion masses. With this apparatus we enhance by a factor 20 the search speed that can be reached with quantum-limited linear amplifiers, and set a new standard for probing the existence of axions with resonant detectors.

We report the first experimental results obtained with the new haloscope of the QUAX experiment located at Laboratori Nazionali di Frascati of INFN (LNF). The haloscope is composed of a OFHC Cu resonant cavity cooled down to about 30 mK and immersed in a magnetic field of 8 T. The cavity frequency was varied in a 6 MHz range between 8.831496 and 8.83803 GHz. This corresponds to a previously unprobed mass range between 36.52413 and 36.5511 $\mu$eV. We don't observe any excess in the power spectrum and set limits on the axion-photon coupling in this mass range down to $g_{a\gamma\gamma} < 0.861 \times 10^{-13}$ GeV$^{-1}$ with the confidence level set at $90\%$., Comment: Submitted to Physical Review D (https://journals.aps.org/prd/)

Recent developments in foundation models, like Large Language Models (LLMs) and Vision-Language Models (VLMs), trained on extensive data, facilitate flexible application across different tasks and modalities. Their impact spans various fields, including healthcare, education, and robotics. This paper provides an overview of the practical application of foundation models in real-world robotics, with a primary emphasis on the replacement of specific components within existing robot systems. The summary encompasses the perspective of input-output relationships in foundation models, as well as their role in perception, motion planning, and control within the field of robotics. This paper concludes with a discussion of future challenges and implications for practical robot applications.

We study the incubation and transition times that characterize the magnetization switching induced by spin-orbit torques in nanomagnets with perpendicular anisotropy. We present a phenomenological model to interpret the dependence of the incubation time on the amplitude of the voltage pulse and assisting magnetic field and estimate the volume of the seed domain that triggers the switching. Our measurements evidence a correlation between the incubation and transition times that is mediated by the temperature variation during the electric pulse. In addition, we discuss the stochastic distributions of the two times in terms of the energy barriers opposing the nucleation and expansion of the seed domain. We propose two models based on the log-normal and gamma functions to account for the different origin of the variability of the incubation and transition times, which are associated with a single nucleation barrier and multiple pinning sites, respectively.

The Hanle magnetoresistance is a telltale signature of spin precession in nonmagnetic conductors, in which strong spin-orbit coupling generates edge spin accumulation via the spin Hall effect. Here, we report the existence of a large Hanle magnetoresistance in single layers of Mn with weak spin-orbit coupling, which we attribute to the orbital Hall effect. The simultaneous observation of a sizable Hanle magnetoresistance and vanishing small spin Hall magnetoresistance in BiYIG/Mn bilayers corroborates the orbital origin of both effects. We estimate an orbital Hall angle of 0.016, an orbital relaxation time of 2 ps and diffusion length of the order of 2 nm in disordered Mn. Our findings indicate that current-induced orbital moments are responsible for magnetoresistance effects comparable to or even larger than those determined by spin moments, and provide a tool to investigate nonequilibrium orbital transport phenomena.

Light transition metals have recently emerged as a sustainable material class for efficient spin-charge interconversion. We report measurements of current-induced spin-orbit torques generated by Ni$_{1-x}$Cu$_{x}$ alloys in perpendicularly magnetized ferrimagnetic Gd/Fe multilayers. We show that the spin-orbit torque efficiency of Ni$_{1-x}$Cu$_{x}$ increases with the Ni/Cu atomic ratio, reaching values comparable to those of Pt for Ni$_{55}$Cu$_{45}$. Furthermore, we demonstrate magnetization switching of a 20-nm-thick Gd/Fe multilayer with a threshold current that decreases with increasing Ni concentration, similar to the spin-orbit torque efficiency. Our findings show that Ni$_{1-x}$Cu$_{x}$$-$based magnetic heterostructures allow for efficient control of the magnetization by electric currents.

We explore the reach of analytical models at one-loop in Perturbation Theory (PT) to accurately describe measurements of the galaxy power spectrum from numerical simulations in redshift space. We consider the validity range in terms of three different diagnostics: 1) the goodness of fit; 2) a figure-of-bias quantifying the error in recovering the fiducial value of a cosmological parameter; 3) an internal consistency check of the theoretical model quantifying the running of the model parameters with the scale cut. We consider different sets of measurements corresponding to an increasing cumulative simulation volume in redshift space. For each volume we define a median value and the associated scatter for the largest wavenumber where the model is valid (the $k$-reach of the model). We find, as a rather general result, that the median value of the reach decreases with the simulation volume, as expected since the smaller statistical errors provide a more stringent test for the model. This is true for all the three definitions considered, with the one given in terms of the figure-of-bias providing the most stringent scale cut. More interestingly, we find as well that the error associated with the $k$-reach value is quite large, with a significant probability of being as low as 0.1$\, h \, {\rm Mpc}^{-1}$ (or, more generally, up to 40% smaller than the median) for all the simulation volumes considered. We explore as well the additional information on the growth rate parameter encoded in the power spectrum hexadecapole, compared to the analysis of monopole and quadrupole, as a function of simulation volume. While our analysis is, in many ways, rather simplified, we find that the gain in the determination of the growth rate is quite small in absolute value and well within the statistical error on the corresponding figure of merit., Comment: 7 pages, 3 figures

Topological insulators have attracted great interest as generators of spin-orbit torques (SOTs) in spintronic devices. Bi\textsubscript{1-x}Sb\textsubscript{x} is a prominent topological insulator that has a high charge-to-spin conversion efficiency. However, the origin and magnitude of the SOTs induced by current-injection in Bi\textsubscript{1-x}Sb\textsubscript{x} remain controversial. Here we report the investigation of the SOTs and spin Hall magnetoresistance resulting from charge-to-spin conversion in twin-free epitaxial layers of Bi\textsubscript{0.9}Sb\textsubscript{0.1}(0001) coupled to FeCo, and compare it with that of amorphous Bi\textsubscript{0.9}Sb\textsubscript{0.1}. We find a large charge-to-spin conversion efficiency of 1 in the first case and less than 0.1 in the second, confirming crystalline Bi\textsubscript{0.9}Sb\textsubscript{0.1} as a strong spin injector material. The SOTs and spin Hall magnetoresistance are independent of the direction of the electric current, indicating that charge-to-spin conversion in single-crystal Bi\textsubscript{0.9}Sb\textsubscript{0.1}(0001) is isotropic despite the strong anisotropy of the topological surface states. Further, we find that the damping-like SOT has a non-monotonic temperature dependence with a minimum at 20~K. By correlating the SOT with resistivity and weak antilocalization measurements, we conclude that charge-spin conversion occurs via thermally-excited holes from the bulk states above 20~K, and conduction through the isotropic surface states with increasing spin polarization due to decreasing electron-electron scattering below 20~K., Comment: Supporting information at https://doi.org/10.1002/adma.202304905

In this article, we prove a Reocurrence Theorem over function fields of curves over $\mathbf{C}(\! (t)\! )$ and over finite extensions of the Laurent series field $\mathbf{C}(\! (x,y)\! )$. This provides a partial replacement to Chebotarev's Theorem over such fields. A concrete application to the study of weak approximation for homogeneous spaces under $\mathrm{SL}_n$ and with finite stabilizers is given at the end of the article.

X-ray absorption spectroscopy (XAS) and x-ray magnetic circular dichroism (XMCD) have been used to study transition metal impurities on K and Na films. The multiplet structure of the XAS spectra indicates that Fe, Co, and Ni have localized atomic ground states with predominantly d7, d8, and d9 character, respectively. XMCD shows that the localized impurity states possess large, atomiclike, magnetic orbital moments that are progressively quenched as clusters are formed. Ni impurities on Na films are found to be nonmagnetic, with a strongly increased d10 character of the impurity state. The results show that the high magnetic moments of transition metals in alkali hosts originate from electron localization.