Over the past decades, superconducting qubits have emerged as one of the leading hardware platforms for realizing a quantum processor. Consequently, researchers have made significant effort to understand the loss channels that limit the coherence times of superconducting qubits. A major source of loss has been attributed to two level systems that are present at the material interfaces. It is recently shown that replacing the metal in the capacitor of a transmon with tantalum yields record relaxation and coherence times for superconducting qubits, motivating a detailed study of the tantalum surface. In this work, the chemical profile of the surface of tantalum films grown on c-plane sapphire using variable energy X-ray photoelectron spectroscopy (VEXPS) is studied. The different oxidation states of tantalum that are present in the native oxide resulting from exposure to air are identified, and their distribution through the depth of the film is measured. Furthermore, it is shown how the volume and depth distribution of these tantalum oxidation states can be altered by various chemical treatments. Correlating these measurements with detailed measurements of quantum devices may elucidate the underlying microscopic sources of loss.
Fluctuations and stochastic transitions are ubiquitous in nanometre-scale systems, especially in the presence of disorder. However, their direct observation has so far been impeded by a seemingly fundamental, signal-limited compromise between spatial and temporal resolution. Here we develop coherent correlation imaging (CCI) to overcome this dilemma. Our method begins by classifying recorded camera frames in Fourier space. Contrast and spatial resolution emerge by averaging selectively over same-state frames. Temporal resolution down to the acquisition time of a single frame arises independently from an exceptionally low misclassification rate, which we achieve by combining a correlation-based similarity metric1,2 with a modified, iterative hierarchical clustering algorithm3,4. We apply CCI to study previously inaccessible magnetic fluctuations in a highly degenerate magnetic stripe domain state with nanometre-scale resolution. We uncover an intricate network of transitions between more than 30 discrete states. Our spatiotemporal data enable us to reconstruct the pinning energy landscape and to thereby explain the dynamics observed on a microscopic level. CCI massively expands the potential of emerging high-coherence X-ray sources and paves the way for addressing large fundamental questions such as the contribution of pinning5-8 and topology9-12 in phase transitions and the role of spin and charge order fluctuations in high-temperature superconductivity13,14.
The detection and manipulation of antiferromagnetic domains and topological antiferromagnetic textures are of central interest to solid-state physics. A fundamental step is identifying tools to probe the mesoscopic texture of an antiferromagnetic order parameter. In this work, we demonstrate that Bragg coherent diffractive imaging can be extended to study the mesoscopic texture of an antiferromagnetic order parameter using resonant magnetic x-ray scattering. We study the onset of the antiferromagnet transition in PrNiO3, focusing on a temperature regime in which the antiferromagnetic domains are dilute in the beam spot and the coherent diffraction pattern modulating the antiferromagnetic peak is greatly simplified. We demonstrate that it is possible to extract the arrangements and sizes of these domains from single diffraction patterns and show that the approach could be extended to a time-structured light source to study the motion of dilute domains or the motion of topological defects in an antiferromagnetic spin texture.
Magnetic domains play a fundamental role in physics of magnetism and its technological applications. Dynamics of antiferromagnetic domains is poorly understood, although antiferromagnets are expected to be extensively used in future electronic devices wherein it determines the stability and operational speed. Dynamics of antiferromagnets also features prominently in the studies of topological quantum matter. Real-space imaging of fluctuating antiferromagnetic domains is therefore highly desired but has never been demonstrated. We use coherent x-ray diffraction to obtain videos of fluctuating micrometer-scale antiferromagnetic domains in Ni2MnTeO6 on time scales from 10-1 to 103 s. In the collinear phase, thermally activated domain wall motion is observed in the vicinity of the Néel temperature. Unexpectedly, the fluctuations persist through the full range of the higher-temperature helical phase. These observations illustrate the high potential significance of the dynamic domain imaging in phase transition studies and in magnetic device research.
Like other experimental techniques, X-ray photon correlation spectroscopy is subject to various kinds of noise. Random and correlated fluctuations and heterogeneities can be present in a two-time correlation function and obscure the information about the intrinsic dynamics of a sample. Simultaneously addressing the disparate origins of noise in the experimental data is challenging. We propose a computational approach for improving the signal-to-noise ratio in two-time correlation functions that is based on convolutional neural network encoder-decoder (CNN-ED) models. Such models extract features from an image via convolutional layers, project them to a low dimensional space and then reconstruct a clean image from this reduced representation via transposed convolutional layers. Not only are ED models a general tool for random noise removal, but their application to low signal-to-noise data can enhance the data's quantitative usage since they are able to learn the functional form of the signal. We demonstrate that the CNN-ED models trained on real-world experimental data help to effectively extract equilibrium dynamics' parameters from two-time correlation functions, containing statistical noise and dynamic heterogeneities. Strategies for optimizing the models' performance and their applicability limits are discussed.
Spin excitations of magnetic thin films are the founding element for magnetic devices in general. While spin dynamics have been extensively studied in bulk materials, the behaviour in mesoscopic films is less known due to experimental limitations. Here, we employ resonant inelastic X-ray scattering to investigate the spectrum of spin excitations in mesoscopic Fe films, from bulk-like films down to three unit cells. In bulk samples, we find isotropic, dispersive ferromagnons consistent with previous neutron scattering results for bulk single crystals. As the thickness is reduced, these ferromagnetic spin excitations renormalize to lower energies along the out-of-plane direction while retaining their dispersion in the in-plane direction. This thickness dependence is captured by simple Heisenberg model calculations accounting for the confinement in the out-of-plane direction through the loss of Fe bonds. Our findings highlight the effects of mesoscopic scaling on spin dynamics and identify thickness as a knob for fine tuning and controlling magnetic properties.
Understanding the formation and dynamics of charge and spin-ordered states in low-dimensional transition metal oxide materials is crucial to understanding unconventional high-temperature superconductivity. La_{2-x}Sr_{x}NiO_{4+δ} (LSNO) has attracted much attention due to its interesting spin dynamics. Recent x-ray photon correlation spectroscopy studies have revealed slow dynamics of the spin order (SO) stripes in LSNO. Here, we applied resonant soft x-ray ptychography to map the spatial distribution of the SO stripe domain inhomogeneity in real space. The reconstructed images show the SO domains are spatially anisotropic, in agreement with previous diffraction studies. For the SO stripe domains, it is found that the correlation lengths along different directions are strongly coupled in space. Surprisingly, fluctuations were observed in the real space amplitude signal, rather than the phase or position. We attribute the observed slow dynamics of the stripe domains in LSNO to thermal fluctuations of the SO domain boundaries.
Charge density waves (CDWs) in the cuprate high-temperature superconductors have evoked much interest, yet their typical short-range nature has raised questions regarding the role of disorder. Here we report a resonant X-ray diffraction study of ZrTe[Formula: see text], a model CDW system, with focus on the influence of disorder. Near the CDW transition temperature, we observe two independent signals that arise concomitantly, only to become clearly separated in momentum while developing very different correlation lengths in the well-ordered state that is reached at a distinctly lower temperature. Anomalously slow dynamics of mesoscopic charge domains are further found near the transition temperature, in spite of the expected strong thermal fluctuations. Our observations signify the presence of distinct experimental fingerprints of pristine and disorder-perturbed CDWs. We discuss the latter also in the context of Friedel oscillations, which we argue might promote CDW formation via a self-amplifying process.
Ru M3-edge resonant inelastic x-ray scattering (RIXS) measurements of [Formula: see text] with 27 meV resolution reveals a spin-orbit exciton without noticeable splitting. We extract values for the spin-orbit coupling constant ([Formula: see text] meV) and trigonal distortion field energy ([Formula: see text] meV) which support the [Formula: see text] nature of [Formula: see text]. We demonstrate the feasibility of M-edge RIXS for 4d systems, which allows ultra high-resolution RIXS of 4d systems until instrumentation for L-edge RIXS improves.
The metal-insulator phase transition in magnetite, known as the Verwey transition, is characterized by a charge-orbital ordering and a lattice transformation from a cubic to monoclinic structure. We use x-ray photon correlation spectroscopy to investigate the dynamics of this charge-orbitally ordered insulating phase undergoing the insulator-to-metal transition. By tuning to the Fe L_{3} edge at the (001/2) superlattice peak, we probe the evolution of the Fe t_{2g} orbitally ordered domains present in the low temperature insulating phase and forbidden in the high temperature metallic phase. We observe two distinct regimes below the Verwey transition. In the first regime, magnetite follows an Arrhenius behavior and the characteristic timescale for orbital fluctuations decreases as the temperature increases. In the second regime, magnetite phase separates into metallic and insulating domains, and the kinetics of the phase transition is dictated by metallic-insulating interfacial boundary conditions.
A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making. This behavior, known as habituation, is universal among all forms of life with a central nervous system, and is also observed in single-cell organisms that do not possess a brain. Here, we report the discovery of habituation-based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by first-principles theory, synchrotron investigations, ab initio molecular dynamics simulations, and in situ environmental breathing studies. We implement a learning algorithm inspired by the conductance relaxation behavior of perovskites that naturally incorporates habituation, and demonstrate learning to forget: a key feature of animal and human brains. Incorporating this elementary skill in learning boosts the capability of neural computing in a sequential, dynamic environment.Habituation is a learning mechanism that enables control over forgetting and learning. Zuo, Panda et al., demonstrate adaptive synaptic plasticity in SmNiO3 perovskites to address catastrophic forgetting in a dynamic learning environment via hydrogen-induced electron localization.
The applied potential dependent rate of atomic step motion of the Ag(001) surface in weak NaF electrolyte has been measured using a new extension of the technique of X-ray Photon Correlation Spectroscopy (XPCS). For applied potentials between hydrogen evolution and oxidation, the surface configuration completely changes on timescales of 10(2)-10(4) seconds depending upon the applied potential. These dynamics, directly measured over large areas of the sample surface simultaneously, are related to the surface energy relative to over or under potential. Concurrent specular X-ray scattering measurements reveal how the ordering of the water layers at the interface correlates with the dynamics.
We developed a method for production of arrays of platinum nanocrystals of controlled size and shape using templates from ordered silica bead monolayers. Silica beads with nominal sizes of 150 and 450 nm were self-assembled into monolayers over strontium titanate single crystal substrates. The monolayers were used as shadow masks for platinum metal deposition on the substrate using the three-step evaporation technique. Produced arrays of epitaxial platinum islands were transformed into nanocrystals by annealing in a quartz tube in nitrogen flow. The shape of particles is determined by the substrate crystallography, while the size of the particles and their spacing are controlled by the size of the silica beads in the monolayer mask. As a proof of concept, arrays of platinum nanocrystals of cubooctahedral shape were prepared on (100) strontium titanate substrates. The nanocrystal arrays were characterized by atomic force microscopy, scanning electron microscopy, and synchrotron X-ray diffraction techniques.
We observed an epitaxial, air-stable, partially registered (2 × 1) oxide bilayer on Pt (001) nanofacets [V. Komanicky, A. Menzel, K.-C. Chang, and H. You, J. Phys. Chem. 109, 23543 (2005)]. The bilayer is made of two half Pt layers; the top layer has four oxygen bonds and the second layer two. The positions and oxidation states of the Pt atoms are determined by analyzing crystal truncation rods and resonance scattering data. The positions of oxygen atoms are determined by density functional theory (DFT) calculations. Partial registry on the nanofacets and the absence of such registry on the extended Pt (001) surface prepared similarly are explained in DFT calculations by strain relief that can be accommodated only by nanoscale facets.
The wetting behavior of ethylene adsorbed on MgO(100) was investigated from 83-135 K using high resolution volumetric adsorption isotherms. The results are compared to ethylene adsorption on graphite, a prototype adsorption system, in an effort to gain further insight into the forces that drive the observed film growth. Layering transitions for ethylene on MgO(100) are observed below the bulk triple point of ethylene (T = 104.0 K). The formation of three discrete adlayers is observed on the MgO(100) surface; onset of the second and third layers occurs at 79.2 +/- 1.3 K and 98.3 +/- 0.9 K, respectively. Thermodynamic quantities such as differential enthalpy and entropy, heat of adsorption, and isosteric heat of adsorption are determined and compared to the previously published values for ethylene on graphite. The average area occupied by a ethylene molecule on MgO(100) is 22.6 +/- 1.1 A2 molecule(-1). The locations of two phase transitions are identified (i.e., layer critical temperatures at T(c2)(n=1) at 108.6 +/- 1.7 K and T(c2)(n=2) at 116.5 +/- 1.2 K) and a phase diagram is proposed. Preliminary neutron diffraction measurements reveal evidence of a monolayer solid with a lattice constant of approximately 4.2 A. High resolution INS measurements show that the onset to dynamical motion and monolayer melting take place at approximately 35 K and approximately 65 K, respectively. The data reported here exhibit a striking similarity to ethylene on graphite which suggests that molecule-molecule interactions play an important role in determining the physical properties and growth of molecularly thin ethylene films.
