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At least 1,495 records · Page 83

Exploring Parameter Redundancy in the Unitary Coupled-Cluster Ansätze for Hybrid Variational Quantum Computing

One of the commonly used chemical-inspired approaches in variational quantum computing is the unitary coupled-cluster (UCC) ansatze. Despite being a systematic way of approaching the exact limit, the number of parameters in the standard UCC ansatze exhibits unfavorable scaling with respect to the system size, hindering its practical use on near-term quantum devices. Efforts have been taken to propose some variants of UCC ansatze with better scaling. In this paper we explore the parameter redundancy in the preparation of unitary coupled-cluster singles and doubles (UCCSD) ansatze employing spin-adapted formulation, small amplitude filtration, and entropy-based orbital selection approaches. Numerical results of using our approach on some small molecules have exhibited a significant cost reduction in the number of parameters to be optimized and in the time to convergence compared with conventional UCCSD-VQE simulations. Further, we also discuss the potential application of some machine learning techniques in further exploring the parameter redundancy, providing a possible direction for future studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring Responses of Contact Kelvin Probe Force Microscopy in Triple-Cation Double-Halide Perovskites

Hybrid organic–inorganic perovskite (HOIP) solar cells have undergone unprecedentedly rapid improvement in power conversion efficiencies during the last decade, but controversy remains regarding the role of local phenomena and heterogeneity in grain by grain. These challenges in turn necessitate understanding the fundamental mechanisms operating at individual grains and exploring how these mechanisms give rise to the collective behaviors of the films. Although numerous efforts have targeted local phenomena in these materials using classical scanning probe microscopy modalities, the measurements remain difficult to interpret due to intrinsic coupling between possible ferroelectric, ion migration, bulk and surface electrochemical phenomena, and the effects of light on these behaviors. Here, we explore the electromechanical responses in (Cs 0.05 FA 0.85 MA 0.15 )Pb(I 0.85 Br 0.15 ) 3 perovskite thin film in the dark and under illumination using band excitation-piezoresponse force microscopy (BE-PFM). To identify and separate ferroic, electrostatic, and electrochemical responses, we utilize contact-Kelvin probe force microscopy (cKPFM). The cKPFM responses show weak variability with morphological features in the dark, while such variability significantly increases under illumination. Deconvolution of the cKPFM responses via principal component analysis (PCA) shows heterogeneity in grain to grain possibly due to variation in migration and segregation of halide ions in mixed perovskites at specific grains. Further, we propose an electrostatic mechanism based on the physics of semiconductors, which can directly link the observed cKPFM behaviors with the ionic and electronic density of states (DOS) and their time dynamics. Here, these findings suggest that cKPFM is a powerful probe of local ionic behaviors on the nanoscale, both in HOIPs and other materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ReaxFF Reactive Force Field for Exploring Electronically Switchable Polarization in Zn 1– x Mg x O Ferroelectric Semiconductors

Cation misfit in traditional ferroelectric crystals offers a new material platform that can drive electronic components toward structural miniaturization and high-density integration, enabling deviation from von-Neumann architectures. Here, we explore ferroelectricity in Zn 1–x Mg x O, a nontraditional ferroelectric material with tunable properties. Using data from density-functional theory calculations, we have developed a ReaxFF reactive force field to explore the ferroelectric properties of Zn 1–x Mg x O and reveal the hysteresis behavior. We discover that ferroelectric switching can be observed at a critical thickness of 10 nm with a residual polarization of ~100 μC/cm 2 . Our analysis indicates that an increase in Mg-substitution correlates with a decrease in the coercive field. We also observe a strong temperature dependence of the coercive field in Zn 1–x Mg x O, with values decreasing as the temperature increases. Additionally, we find that the distribution of Mg atoms significantly impacts the coercive field, with a clustered distribution leading to a substantial increase. In particular, a decrease in coercive field values is observed when Mg atoms are randomly distributed, compared to uniform distribution. Furthermore, leveraging tunable hysteresis behavior offered by varied percentages and distribution of Mg-substitution provides valuable insights into the design of next-generation functional devices and will inspire further investigations.

36 MATERIALS SCIENCE↗

Exploring the Ion Solvation Environments in Solid-State Polymer Electrolytes through Free-Energy Sampling

The success of poly(ethylene oxide) (PEO) in solid-state polymer electrolytes for lithium-ion batteries is well established. Recently, in order to understand this success and to explore possible alternatives, we studied polyacetal electrolytes to deepen the understanding of the effect of the local chemical structure on ion transport. Advanced molecular dynamics techniques using newly developed, tailored interaction potentials have helped elucidate the various coordination environments of ions in these systems. In particular, the competition between cation-Anion pairing and coordination by the polymer has been explored using free-energy sampling (metadynamics). At equivalent reduced temperatures, with respect to the polymer-specific glass-Transition temperature, two-dimensional free-energy plots reveal the existence of multiple coordination environments for the lithium (Li) ions in these systems and their relative stabilities. Furthermore, we observe that the Li-ion movement in PEO follows a serial, stepwise pathway when moving from one coordination state to another, whereas this happens in a more continuous and concerted fashion in a polyacetal such as poly(1,3-dioxalane) [P(EO-MO)]. The implication is that interconversion between coordination states of the Li ions may be easier in P(EO-MO). However, the overarching observation from our free-energy analysis is that Li-ion coordination is dominated by the polymer (in either case) and contact-ion pairs are rare. We rationalize the observed higher increase in glass-Transition temperature (Tg) with salt loading in polyacetals as due to intermolecular Li-ion coordination involving multiple polymer chains, rather than just one chain for PEO-based electrolytes. This interchain coupling in the polyacetals, resulting in the higher Tg, works against any gains due to variations in Li-ion coordination that might enhance transport processes over PEO. Further research is required to overcome the interdependence between local coordination and macroscopic properties to compete with PEO electrolytes at the same absolute working temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Autonomous Experiments in Scanning Probe Microscopy and Spectroscopy: Choosing Where to Explore Polarization Dynamics in Ferroelectrics

Polarization dynamics in ferroelectric materials are explored via automated experiment in piezoresponse force microscopy/spectroscopy (PFM/S). A Bayesian optimization (BO) framework for imaging is developed, and its performance for a variety of acquisition and pathfinding functions is explored using previously acquired data. The optimized algorithm is then deployed on an operational scanning probe microscope (SPM) for finding areas of large electromechanical response in a thin film of PbTiO 3 , with results showing that, with just 20% of the area sampled, most high-response clusters were captured. Furthermore, this approach can allow performing more complex spectroscopies in SPM that were previously not possible due to time constraints and sample stability. Improvements to the framework to enable the incorporation of more prior information and improve efficiency further are modeled and discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring Causal Physical Mechanisms via Non-Gaussian Linear Models and Deep Kernel Learning: Applications for Ferroelectric Domain Structures

Rapid emergence of multimodal imaging in scanning probe, electron, and optical microscopies has brought forth the challenge of understanding the information contained in these complex data sets, targeting the intrinsic correlations between different channels, and further exploring the underpinning causal physical mechanisms. Here, we develop such an analysis framework for Piezoresponse Force Microscopy. We argue that under certain conditions, we can bootstrap experimental observations with the prior knowledge of materials structure to get information on certain nonobserved properties, and demonstrate linear causal analysis for PFM observables. We further demonstrate that the strength of individual causal links between complex descriptors can be ascertained using the deep kernel learning (DKL) model. In this DKL analysis, we use the prior information on domain structure within the image to predict the physical properties. This analysis demonstrates the correlative relationships between morphology, piezoresponse, elastic property, etc., at nanoscale. The prediction of morphology and other physical parameters illustrates a mutual interaction between surface condition and physical properties in ferroelectric materials. Overall, this analysis is universal and can be extended to explore the correlative relationships of other multichannel data sets, and allow for high-fidelity reconstruction of underpinning functionalities and physical mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring How Changing Monsoonal Dynamics and Human Pressures Challenge Multireservoir Management for Flood Protection, Hydropower Production, and Agricultural Water Supply

Abstract Multireservoir systems require robust and adaptive control policies capable of managing hydroclimatic variability and human demands across a range of time scales. This is especially true for river basins with high intraannual and interannual variability, such as monsoonal systems that need to buffer against seasonal droughts while also managing extreme floods. Moreover, the timing, intensity, duration, and frequency of these hydrologic extremes may evolve with deeply uncertain changes in socioeconomic and climatic pressures. This study contributes an innovative method for exploring how possible changes in the timing and magnitude of the monsoonal cycle impact the robustness of reservoir operating policies designed assuming stationary hydrologic and socioeconomic conditions. We illustrate this analysis on the Red River basin in Vietnam, where reservoirs and dams serve as important sources of hydropower production, multisectoral water supply, and flood protection for the capital city of Hanoi. Applying our scenario discovery approach, we find that reservoir operations designed assuming stationarity provide robust hydropower performance in the Red River but that increased mean streamflow, amplification of the within‐year monsoonal cycle, and increased interannual variability all threaten their ability to manage flood risk. Additionally, increased agricultural water demands can only be tolerated if they are accompanied by greater mean flow, exacerbating food‐flood trade‐offs in the basin. These findings highlight the importance of exploring the impacts of a wide range of deeply uncertain socioeconomic and hydrologic factors when evaluating system robustness in monsoonal river basins, considering in particular both lower‐order moments of annual streamflow and intraannual monsoonal behavior.

Quinn, J. D.↗

Exploring Hydrologic Model Process Connectivity at the Continental Scale Through an Information Theory Approach

Exploring water fluxes between hydrological model (HM) components is essential to assess and improve model realism. Many classical metrics for HM diagnosis rely solely on streamflow and hence provide limited insights into model performance across processes. This study applies an information theory measure known as “transfer entropy” (TE) to systematically quantify the transfer of information among major HM components. To test and demonstrate the benefits of TE, we use the Framework for Understanding Structural Errors (FUSE) model to mimic and compare four commonly used HM structures, VIC, PRMS, SACRAMENTO, and TOPMODEL, across 671 catchments spanning a variety of hydrologic regimes in the conterminous United States. We explore connections between HM components and catchment landscape characteristics (e.g., climate, topography, soil, and vegetation) and characterize their nonlinear associations using distance correlation and Spearman correlation coefficients. Our results indicate that while the information transferred from precipitation to runoff is similar across model structures (likely as a result of calibration), the information transferred among other components can vary significantly from a FUSE structure to another. We find that aridity, precipitation duration and frequency, snow fraction, mean elevation, forest area, and leaf area index are often significantly associated with TE between the main HM components. Here, we propose that the presence of meaningful nonlinear associations can be used to diagnose process representation in HMs. Our results highlight the necessity to enhance the conventional streamflow-only calibration approach for a more realistic representation of water dynamics in the models.

large-sample hydrology↗

Exploring Western North Pacific Tropical Cyclone Activity in the High‐Resolution Community Atmosphere Model

Abstract High‐resolution climate models (∼28 km grid spacing) can permit realistic simulations of tropical cyclones (TCs), thus enabling their investigation in relation to the climate system. On the global scale, previous works have demonstrated that the Community Atmosphere Model (CAM) version 5 presents a reasonable TC climatology under prescribed present‐day (1980–2005) forcing. However, for the Western North Pacific (WNP) region, known biases in simulated TC genesis frequency and location under‐represent the basin's dominant share in observations. This study addresses these model biases in WNP by evaluating WNP TCs in a decadal simulation, and exploring potential improvements through nudging experiments. Among the major environmental controls of TC genesis, the lack of mid‐level moisture is identified as the leading cause of the deficit in simulated WNP TC genesis over the Pacific Warm Pool. Subsequent seasonal experiments explore the effect of constraining the large‐scale environment on TC development by nudging WNP temperature field toward reanalysis at various strengths. Temperature nudging elicits a significant response in TC genesis and intensity development, as well as in moisture and convection over the Warm Pool. These responses are sensitive to the choice of nudging timescale. Overall, the nudging experiments demonstrate that improvements in the large‐scale environment can lead to improvements in simulated TCs, suggesting future model developments in relation to model physics. In this way, the potential improvements in model fidelity will contribute to the understanding of how the mean state of current or future climates may give rise to extremes such as TCs.

58 GEOSCIENCES↗

Using Radiative Convective Equilibrium to Explore Clouds and Climate in the Community Atmosphere Model

Abstract Characteristics of, and fundamental differences between, the radiative‐convective equilibrium (RCE) climate states following the Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) protocols in the Community Atmosphere Model version 5 (CAM5) and version 6 (CAM6) are presented. This paper explores the characteristics of clouds, moisture, precipitation and circulation in the RCE state, as well as the tropical response to surface warming, in CAM5 and CAM6 with different parameterizations. Overall, CAM5 simulates higher precipitation rates that result in larger global average precipitation, despite lower outgoing longwave radiation compared to CAM6. Differences in the structure of clouds, particularly the amount and vertical location of cloud liquid, exist between the CAM versions and can, in part, be related to distinct representations of shallow convection and boundary layer processes. Both CAM5 and CAM6 simulate similar peaks in cloud fraction, relative humidity, and cloud ice, linked to the usage of a similar deep convection parameterization. These anvil clouds rise and decrease in extent in response to surface warming. More generally, extreme precipitation, aggregation of convection, and climate sensitivity increase with warming in both CAM5 and CAM6. This analysis provides a benchmark for future studies that explore clouds, convection, and climate in CAM with the RCEMIP protocols now available in the Community Earth System Model. These results are discussed within the context of realistic climate simulations using CAM5 and CAM6, highlighting the usefulness of a hierarchical modeling approach to understanding model and parameterization sensitivities to inform model development efforts.

Reed, Kevin A.↗

Exploring physics of ferroelectric domain walls via Bayesian analysis of atomically resolved STEM data

The physics of ferroelectric domain walls is explored using the Bayesian inference analysis of atomically resolved STEM data. We demonstrate that domain wall profile shapes are ultimately sensitive to the nature of the order parameter in the material, including the functional form of Ginzburg-Landau-Devonshire expansion, and numerical value of the corresponding parameters. The preexisting materials knowledge naturally folds in the Bayesian framework in the form of prior distributions, with the different order parameters forming competing (or hierarchical) models. Here, we explore the physics of the ferroelectric domain walls in BiFeO 3 using this method, and derive the posterior estimates of relevant parameters. More generally, this inference approach both allows learning materials physics from experimental data with associated uncertainty quantification, and establishing guidelines for instrumental development answering questions on what resolution and information limits are necessary for reliable observation of specific physical mechanisms of interest.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Turn-key constrained parameter space exploration for particle accelerators using Bayesian active learning

Abstract Particle accelerators are invaluable discovery engines in the chemical, biological and physical sciences. Characterization of the accelerated beam response to accelerator input parameters is often the first step when conducting accelerator-based experiments. Currently used techniques for characterization, such as grid-like parameter sampling scans, become impractical when extended to higher dimensional input spaces, when complicated measurement constraints are present, or prior information known about the beam response is scarce. Here in this work, we describe an adaptation of the popular Bayesian optimization algorithm, which enables a turn-key exploration of input parameter spaces. Our algorithm replaces the need for parameter scans while minimizing prior information needed about the measurement’s behavior and associated measurement constraints. We experimentally demonstrate that our algorithm autonomously conducts an adaptive, multi-parameter exploration of input parameter space, potentially orders of magnitude faster than conventional grid-like parameter scans, while making highly constrained, single-shot beam phase-space measurements and accounts for costs associated with changing input parameters. In addition to applications in accelerator-based scientific experiments, this algorithm addresses challenges shared by many scientific disciplines, and is thus applicable to autonomously conducting experiments over a broad range of research topics.

43 PARTICLE ACCELERATORS↗

Oblique and rippled heliosphere structures from the Interstellar Boundary Explorer

Abstract Past analysis has shown that the heliosphere structure can be deduced from correlations between long-scale solar wind pressure evolution and energetic neutral atom emissions. However, this required spatial and temporal averaging that smoothed out small or dynamic features of the heliosphere. In late 2014, the solar wind dynamic pressure increased by roughly 50% over a period of 6 months, causing a time and directional-dependent rise in around 2–6 keV energetic neutral atom fluxes from the heliosphere observed by the Interstellar Boundary Explorer. Here, we use the 2014 pressure enhancement to provide a simultaneous derivation of the three-dimensional heliospheric termination shock (HTS) and heliopause (HP) distances at high resolution from Interstellar Boundary Explorer measurements. The analysis reveals rippled HTS and HP surfaces that are oblique with respect to the local interstellar medium upwind direction, with significant asymmetries in the heliosphere structure compared to steady-state heliosphere models. We estimate that the heliosphere boundaries contain roughly ten astronomical unit-sized spatial variations, with slightly larger variations on the HTS surface than the HP and a large-scale, southwards-directed obliquity of the surfaces in the meridional plane. Comparisons of the derived HTS and HP distances with Voyager observations indicate substantial differences in the heliosphere boundaries in the northern versus southern hemispheres and their motion over time.

79 ASTRONOMY AND ASTROPHYSICS↗

Habitat quality influences trade-offs in animal movement along the exploration–exploitation continuum

Abstract To successfully establish itself in a novel environment, an animal must make an inherent trade-off between knowledge accumulation and exploitation of knowledge gained (i.e., the exploration–exploitation dilemma). To evaluate how habitat quality affects the spatio-temporal scale of switching between exploration and exploitation during home range establishment, we conducted experimental trials comparing resource selection and space-use of translocated animals to those of reference individuals using reciprocal translocations between habitat types of differing quality. We selected wild pigs ( Sus scrofa ) as a model species to investigate hypotheses related to the movement behavior of translocated individuals because they are globally distributed large mammals that are often translocated within their introduced range to facilitate recreational hunting. Individuals translocated to higher quality habitat (i.e. higher proportions of bottomland hardwood habitats) exhibited smaller exploratory movements and began exploiting resources more quickly than those introduced to lower quality areas, although those in lower-quality areas demonstrated an increased rate of selection for preferred habitat as they gained knowledge of the landscape. Our data demonstrate that habitat quality mediates the spatial and temporal scale at which animals respond behaviorally to novel environments, and how these processes may determine the success of population establishment.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring toroidal anvil profiles for larger sample volumes above 4 Mbar

Abstract With the advent of toroidal and double-stage diamond anvil cells (DACs), pressures between 4 and 10 Mbar can be achieved under static compression, however, the ability to explore diverse sample assemblies is limited on these micron-scale anvils. Adapting the toroidal DAC to support larger sample volumes offers expanded capabilities in physics, chemistry, and planetary science: including, characterizing materials in soft pressure media to multi-megabar pressures, synthesizing novel phases, and probing planetary assemblages at the interior pressures and temperatures of super-Earths and sub-Neptunes. Here we have continued the exploration of larger toroidal DAC profiles by iteratively testing various torus and shoulder depths with central culet diameters in the 30–50 µm range. We present a 30 µm culet profile that reached a maximum pressure of 414(1) GPa based on a Pt scale. The 300 K equations of state fit to our P–V data collected on gold and rhenium are compatible with extrapolated hydrostatic equations of state within 1% up to 4 Mbar. This work validates the performance of these large-culet toroidal anvils to > 4 Mbar and provides a promising foundation to develop toroidal DACs for diverse sample loading and laser heating.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Exploring the phase diagram of 3D artificial spin-ice

Artificial spin-ices consist of lithographic arrays of single-domain magnetic nanowires organised into frustrated lattices. These geometries are usually two-dimensional, allowing a direct exploration of physics associated with frustration, topology and emergence. Recently, three-dimensional geometries have been realised, in which transport of emergent monopoles can be directly visualised upon the surface. Here we carry out an exploration of the three-dimensional artificial spin-ice phase diagram, whereby dipoles are placed within a diamond-bond lattice geometry. We find a rich phase diagram, consisting of a double-charged monopole crystal, a single-charged monopole crystal and conventional spin-ice with pinch points associated with a Coulomb phase. In experimental demagnetised systems, broken symmetry forces formation of ferromagnetic stripes upon the surface, forbidding the lower energy double-charged monopole crystal. Instead, we observe crystallites of single magnetic charge, superimposed upon an ice background. The crystallites are found to form due to the distribution of magnetic charge around the 3D vertex, which locally favours monopole formation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Higher order harmonic detection for exploring nonlinear interactions with nanoscale resolution

Nonlinear dynamics underpin a vast array of physical phenomena ranging from interfacial motion to jamming transitions. In many cases, insight into the nonlinear behavior can be gleaned through exploration of higher order harmonics. Here, a method using band excitation scanning probe microscopy (SPM) to investigate higher order harmonics of the electromechanical response, with nanometer scale spatial resolution is presented. The technique is demonstrated by probing the first three harmonics of strain for a Pb(Zr 1-x Ti x )O 3 (PZT) ferroelectric capacitor. It is shown that the second order harmonic response is correlated with the first harmonic response, whereas the third harmonic is not. Additionally, measurements of the second harmonic reveal significant deviations from Rayleigh-type models in the form of a much more complicated field dependence than is observed in the spatially averaged data. These results illustrate the versatility of n th order harmonic SPM detection methods in exploring nonlinear phenomena in nanoscale materials.

36 MATERIALS SCIENCE↗

Exploring the phase space of Zn 2 SbN 3 , a novel semiconducting nitride

The novel semiconductor Zn 2 SbN 3 is one of a growing list of ternary nitrides with promise for optoelectronic and energy applications. Previous work by Arca et al. [Materials Horizons, 2019, 6, 1669–1974] first reported synthesis of this material, but did not explore the effects of growth conditions on material formation. In this work, we present a semi-automated study of the relationship between growth conditions and crystallinity via high-throughput RF sputtering and a custom X-ray diffraction analysis routine. Zn 2 SbN 3 is found to crystallize in a wide range of growth conditions, and the formation of several contaminant phases is examined. Electron microscopy of these secondary phases, caused both by off-stoichiometry and by growth conditions, provides insight into the growth mechanisms of Zn 2 SbN 3 . Furthermore, computational work relates this material to other Zn-based ternary nitrides and offers an explanation for the difficulty of growing cation-ordered material despite the wide range of growth conditions explored.

36 MATERIALS SCIENCE↗