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At least 721 records · Page 40

Derivative-free optimization methods

In many optimization problems arising from scientific, engineering and artificial intelligence applications, objective and constraint functions are available only as the output of a black-box or simulation oracle that does not provide derivative information. Such settings necessitate the use of methods for derivative-free, or zeroth-order, optimization. We provide a review and perspectives on developments in these methods, with an emphasis on highlighting recent developments and on unifying treatment of such problems in the non-linear optimization and machine learning literature. We categorize methods based on assumed properties of the black-box functions, as well as features of the methods. We first overview the primary setting of deterministic methods applied to unconstrained, non-convex optimization problems where the objective function is defined by a deterministic black-box oracle. We then discuss developments in randomized methods, methods that assume some additional structure about the objective (including convexity, separability and general non-smooth compositions), methods for problems where the output of the black-box oracle is stochastic, and methods for handling different types of constraints.

97 MATHEMATICS AND COMPUTING↗

State Preparation of Antisymmetrized Geminal Power on a Quantum Computer without Number Projection

The antisymmetrized geminal power (AGP) is equivalent to the number projected Bardeen–Cooper–Schrieffer (PBCS) wave function. It is also an elementary symmetric polynomial (ESP) state. We generalize previous research on deterministically implementing the Dicke state to a state preparation algorithm for an ESP state, or equivalently AGP, on a quantum computer. Our method is deterministic and has polynomial cost, and it does not rely on number symmetry breaking and restoration. We also show that our circuit is equivalent to a disentangled unitary paired coupled cluster operator and a layer of unitary Jastrow operator acting on a single Slater determinant. Here, the method presented herein highlights the ability of disentangled unitary coupled cluster to capture nontrivial entanglement properties that are hardly accessible with traditional Hartree–Fock based electronic structure methods.

97 MATHEMATICS AND COMPUTING↗

Laser-Assisted Synthesis of Monolayer 2D MoSe 2 Crystals with Tunable Vacancy Concentrations: Implications for Gas and Biosensing

We report tuning the structural and electronic properties of atomically thin two-dimensional (2D) materials via defect and vacancy engineering is the key to enabling their potential use in various applications, including electronics, energy, and sensing devices. Vacancies are, for instance, becoming highly promising for the enhanced interaction of gases and biomolecules with 2D materials in energy and sensing applications. However, the deterministic generation of desirable vacancies with tunable concentrations remains a challenge in 2D materials due to the limitations in the current growth methods, such as the complex reaction chemistries and gas flow dynamics. Therefore, engineering defects and vacancies in 2D materials have been mainly limited to destructive top-down processes such as heating, ion bombardments, and laser postprocessing. Here, we introduce a single-step bottom-up synthesis approach for the growth of monolayer MoSe 2 crystals with tunable vacancy concentrations. This method utilizes the spatiotemporal properties and adjustable power densities of the lasers to control the vaporization dynamics of the stoichiometric MoSe 2 powders. Such a mechanism in the vaporization allows us to grow tunable stoichiometry monolayer MoSe 2–x crystals on the substrates. The localized and time-controlled (250 ms to 2 s) vaporization of the MoSe 2 powder by a CO 2 laser enables the formation of monolayer crystals with controlled vacancy concentrations ranging from ~1 to 20%. The effects of laser power, laser irradiation time, and background pressure on the tuning range and subsequent properties of the crystals are investigated and quantified using Raman and photoluminescence spectroscopy, scanning transmission electron microscopy (STEM), and time-correlated single-photon counting (TCSPC). This bottom-up synthesis is a promising approach that allows the deterministic vacancy tuning for future electronics and, in particular, gas and biosensing applications without the need for further postprocessing and potential structural disruption of the crystals.

2D materials↗

Strain-Induced Growth of Twisted Bilayers during the Coalescence of Monolayer MoS 2 Crystals

Tailoring the grain boundaries (GBs) and twist angles between two-dimensional (2D) crystals are two crucial synthetic challenges to deterministically enable envisioned applications such as moiré excitons, emerging magnetism, or single-photon emission. Here, we reveal how twisted 2D bilayers can be synthesized from the collision and coalescence of two growing monolayer MoS 2 crystals during chemical vapor deposition. The twisted bilayer (TB) moiré angles are found to preserve the misorientation angle (θ) of the colliding crystals. The shapes of the TB regions are rationalized by a kink propagation model that predicts the GB formed by the coalescing crystals. Optical spectroscopy measurements reveal a θ-dependent long-range strain in crystals with stitched grain boundaries and a sharp (θ > 20°) threshold for the appearance of TBs, which relieves this strain. Reactive molecular dynamics simulations explain this strain from the continued growth of the crystals during coalescence due to the insertion of atoms at unsaturated defects along the GB, a process that self-terminates when the defects become saturated. The simulations also reproduce atomic-resolution electron microscopy observations of faceting along the GB, which is shown to arise from the growth-induced long-range strain. These facets align with the axes of the colliding crystals to provide favorable nucleation sites for second-layer growth of a TB with twist angles that preserve the misorientation angle θ. This interplay between strain generation and aligned nucleation provides a synthetic pathway for the growth of TBs with deterministic angles.

2D materials↗

Representative elementary volume estimation for porosity, moisture saturation, and air-water interfacial areas in unsaturated porous media: Data quality implications

Achieving a representative elementary volume (REV) has become a de facto criterion for demonstrating the quality of {mu}CT measurements in porous media systems. However, the data quality implications of an REV requirement have not been previously examined. In this work, deterministic REVs for porosity, moisture saturation (S{sub W}), and air-water interfacial area (A{sub I}) were estimated using a set of 49 {mu}CT images of eight unsaturated homogeneous porous media with heterogeneity in moisture distributions present in varying degrees. Estimated porosity REVs were <8 mm{sup 3} for all cases, smaller than typical CT image sizes ({approx}100 mm{sup 3}). Estimated S{sub W} and A{sub I} REVs were <55 mm{sup 3} for cases with homogeneous moisture distributions but could not be estimated for cases with heterogeneous moisture distributions, due to the absence of a distinct 'REV plateau' within the maximum imaged volume. Conventionally, S{sub W} and A{sub I} data from such non-REV cases would be excluded. The implications of excluding data on the basis of REV were examined by comparing A{sub I}-S{sub W} data measured on image windows of increasing size against the expected linear A{sub I}-S{sub W} relationship. At measurement scales exceeding porosity REV, random fluctuations in A{sub I}-S{sub W} data were excluded, even for cases containing heterogeneous moisture distributions. In contrast, requiring measurement scales to exceed S{sub W} and A{sub I} REV appeared overly restrictive and resulted in visible loss of reliable A{sub I}-S{sub W} data. We attribute these findings to overestimation of REVs due to inherently problematic estimation of deterministic REVs in real systems. Implications of these findings for ensuring CT data quality and the efficient use of CT data are discussed.

99 GENERAL AND MISCELLANEOUS↗

Hydrological parameter estimations from a conservative tracer test with variable-density effects at the Boise Hydrogeophysical Research Site

Reliable predictions of groundwater flow and solute transport require an estimation of the detailed distribution of the parameters (e.g., hydraulic conductivity, effective porosity) controlling these processes. However, such parameters are difficult to estimate because of the inaccessibility and complexity of the subsurface. In this regard, developments in parameter estimation techniques and investigations of field experiments are still challenging and necessary to improve our understanding and the prediction of hydrological processes. Here we analyze a conservative tracer test conducted at the Boise Hydrogeophysical Research Site in 2001 in a heterogeneous unconfined fluvial aquifer. Some relevant characteristics of this test include: variable-density (sinking) effects because of the injection concentration of the bromide tracer, the relatively small size of the experiment, and the availability of various sources of geophysical and hydrological information. The information contained in this experiment is evaluated through several parameter estimation approaches, including a grid-search-based strategy, stochastic simulation of hydrological property distributions, and deterministic inversion using regularization and pilot-point techniques. Doing this allows us to investigate hydraulic conductivity and effective porosity distributions and to compare the effects of assumptions from several methods and parameterizations. Our results provide new insights into the understanding of variabledensity transport processes and the hydrological relevance of incorporating various sources of information in parameter estimation approaches. Among others, the variable-density effect and the effective porosity distribution, as well as their coupling with the hydraulic conductivity structure, are seen to be significant in the transport process. The results also show that assumed prior information can strongly influence the estimated distributions of hydrological properties.

54 ENVIRONMENTAL SCIENCES↗

Ecosystem carbon storage capacity as affected by disturbance regimes: A general theoretical model

Disturbances have been recognized as a key factor shaping terrestrial ecosystem states and dynamics. A general model that quantitatively describes the relationship between carbon storage and disturbance regime is critical for better understanding large scale terrestrial ecosystem carbon dynamics. We developed a model (REGIME) to quantify ecosystem carbon storage capacities (E[x]) under varying disturbance regimes with an analytical solution E[x] = U {center_dot} {tau}{sub E} {center_dot} {lambda}{lambda} + s {tau} 1, where U is ecosystem carbon influx, {tau}{sub E} is ecosystem carbon residence time, and {tau}{sub 1} is the residence time of the carbon pool affected by disturbances (biomass pool in this study). The disturbance regime is characterized by the mean disturbance interval ({lambda}) and the mean disturbance severity (s). It is a Michaelis-Menten-type equation illustrating the saturation of carbon content with mean disturbance interval. This model analytically integrates the deterministic ecosystem carbon processes with stochastic disturbance events to reveal a general pattern of terrestrial carbon dynamics at large scales. The model allows us to get a sense of the sensitivity of ecosystems to future environmental changes just by a few calculations. According to the REGIME model, for example, approximately 1.8 Pg C will be lost in the high-latitude regions of North America (>45{sup o} N) if fire disturbance intensity increases around 5.7 time the current intensity to the end of the twenty-first century, which will require around 12% increases in net primary productivity (NPP) to maintain stable carbon stocks. If the residence time decreased 10% at the same time additional 12.5% increases in NPP are required to keep current C stocks. The REGIME model also lays the foundation for analytically modeling the interactions between deterministic biogeochemical processes and stochastic disturbance events.

09 BIOMASS FUELS↗

Assessing microbial community patterns under incipient soil formation from basalt

Microbial dynamics drive the biotic machinery of early soil evolution. However, integrated knowledge of microbial community establishment, functional associations, and community assembly processes in incipient soil is lacking. This study presents a novel approach of combining microbial phylogenetic profiling, functional predictions, and community assembly processes to analyze drivers of microbial community establishment in an emerging soil system. Rigorous sub-meter sampling of a basalt-soil lysimeter after two years of irrigation revealed the contrasting depth-dependent distribution patterns of soil parameters and community diversity. Phylogenetic analysis of 16S rRNA gene indicated the presence of diverse bacterial and archaeal phyla, with high relative abundance of Actinobacteria on the surface and a consistently high abundance of Proteobacteria at all depths. Predicted functional gene analysis suggested dominant autotrophy signatures, evidence of an incomplete nitrogen cycle, and predicted enzymes of iron (III) to iron (II) conversion followed by intracellular uptake, transport, and regulation. Null modeling revealed microbial community assembly predominantly governed by variable selection. The relative influence of the variable selection decreased with depth, indicating unique and relatively harsh environmental conditions near the surface and more benign conditions with depth. Additionally, high levels of dispersal influenced community composition near the center of the domain, suggesting that spatial processes interact with deterministic selection imposed by the environment. Characterizing the complexity in incipient soils can advance research insights about microbial community diversity and assembly in other incipient systems (e.g., transformation of marginal soils, or soils recovering from disturbances such as fire, erosion, intensive agricultural practices, or contamination).

Sengupta, Aditi↗

The Leading Modes of Asian Summer Monsoon Variability as Pulses of Atmospheric Energy Flow

Monsoon rainfall anomalies are often organized into dynamical modes that are more predictable than rainfall at specific locations. Here a linear response function (LRF) is constructed to extract the neutral modes (NM) of the dynamical atmospheric system and their optimal forcing that govern precipitation variability, providing a dynamical underpinning for the empirically derived, recurrent rainfall patterns. The leading mode (NM1) features a shift in the Atlantic ITCZ, a drying over the Indian Ocean and Indian subcontinent, and a “South-Flood-North Drought (SFND)” pattern over eastern China, a pattern inferable from changes in the atmospheric energy flow forced by the corresponding optimal forcing and further enhanced by the water vapor and cloud feedbacks. Moreover, the slow evolving component of the NM1 in response to CO2 forcing can be skillfully predicted by running the ocean heat uptake through the LRF, implicating a deterministic ocean dynamic source for the NM1-like trend under climate warming.

monsoon mode of variability, EBM, climate change, ↗

QRF4P-NRT: Probabilistic Post-Processing of Near-Real-Time Satellite Precipitation Estimates Using Quantile Regression Forests

Accurate and reliable near-real-time satellite precipitation estimation is of great importance for operational large-scale flood forecasting and drought monitoring. The state-of-the-art precipitation post-processing model is based on a deterministic approach to construct relationships between satellites estimates and ground observations. We propose a probabilistic postprocessor, the Probabilistic Post-Processing of Near-Real-Time Satellite Precipitation Estimates using Quantile Regression Forests (QRF4P-NRT), based on quantile modeling, yielding both deterministic and probabilistic predictions. The experimental design incorporates different solutions of near-real-time predictors to further improve the model performance. Using the Integrated Multi-satellitE Retrievals Early Run for Global Precipitation Measurement Mission (IMERG-E) product as an example, we illustrate that the proposed method significantly improves the overall quality of the raw IMERG-E and is also superior to the bias-corrected product (IMERG Final Run, IMERG-F) at daily scale in a complex mountain basin. Evaluations of the corrected IMERG-E, raw IMERG-E, and IMERG-F using ground observation show that the corrected IMERG-E improves correlation coefficients (0.7), mean error (-0.14 mm/day) and root mean square error (3.3 mm/day) relative to the raw IMERG-E (0.31, -0.72 and 5.5 mm/day) and IMERG-F (0.34, -0.09 and 6.0 mm/day). The error decomposition further confirms that the QRF4P-NRT improves on the various deficiencies of the raw IMERG-E product. The ensemble assessment also demonstrates that the quantile outputs provide reliable prediction spread and sharp prediction intervals. The promising results indicate the great potential of the proposed method for probabilistic post-processing for near-real-time satellite precipitation estimates, and for further applications such as hydrological ensemble forecasting.

54 ENVIRONMENTAL SCIENCES↗

Method of Distributions for Two‐Phase Flow in Heterogeneous Porous Media

Abstract Multiscale heterogeneity and insufficient characterization data for a specific subsurface formation of interest render predictions of multi‐phase fluid flow in geologic formations highly uncertain. Quantification of the uncertainty propagation from the geomodel to the fluid‐flow response is typically done within a probabilistic framework. This task is computationally demanding due to, for example, the slow convergence of Monte Carlo simulations (MCS), especially when computing the tails of a distribution that are necessary for risk assessment and decision‐making under uncertainty. The frozen streamlines method (FROST) accelerates probabilistic predictions of immiscible two‐phase fluid flow problems; however, FROST relies on MCS to compute the travel‐time distribution, which is then used to perform the transport (phase saturation) computations. To alleviate this computational bottleneck, we replace MCS with a deterministic equation for the cumulative distribution function (CDF) of travel time. The resulting CDF‐FROST approach yields the CDF of the saturation field without resorting to sampling‐based strategies. Our numerical experiments demonstrate the high accuracy of CDF‐FROST in computing the CDFs of both saturation and travel time. For the same accuracy, it is about 5 and 10 times faster than FROST and MCS, respectively.

Yang, Hyung Jun↗

Forfeiting the priority effect: turnover defines biofilm community succession

Microbial community succession is a fundamental process that affects underlying functions of almost all ecosystems; yet the roles and fates of the most abundant colonizers are often poorly understood. Does early abundance spur long term persistence? How do deterministic and stochastic processes influence the ecological contribution of colonizers? We performed a succession experiment within a hypersaline ecosystem to investigate how different processes contributed to the turnover of founder species. Bacterial and eukaryotic colonizers were identified during primary succession and tracked through a defined, 79-day biofilm maturation period using 16S and 18S rRNA gene sequencing in combination with high resolution imaging that utilized stable isotope tracers to evaluate successional patterns of primary producers and nitrogen fixers. The majority of the founder species did not maintain high abundance throughout succession. Species replacement (versus loss) was the dominant process shaping community succession. We also asked if different ecological processes acted on bacteria versus Eukaryotes during succession and found deterministic and stochastic forces corresponded more with microeukaryote and bacterial colonization, respectively. Our results show that taxa and functions belonging to different kingdoms, which share habitat in the tight spatial confines of a biofilm, were influenced by different ecological processes and time scales of succession.

Brislawn, Colin J.↗

Kinetic control of tunable multi-state switching in ferroelectric thin films

Deterministic creation of multiple ferroelectric states with intermediate values of polarization remains challenging due to the inherent bi-stability of ferroelectric switching. In this work we show the ability to select any desired intermediate polarization value via control of the switching pathway in (111)-oriented PbZr 0.2 Ti 0.8 O 3 films. Such switching phenomena are driven by kinetic control of the volume fraction of two geometrically different domain structures which are generated by two distinct switching pathways: one direct, bipolar-like switching and another multi-step switching process with the formation of a thermodynamically-stable intermediate twinning structure. Such control of switching pathways is enabled by the competition between elastic and electrostatic energies which favors different types of ferroelastic switching that can occur. As a whole, our work reflects an alternative approach that transcends the inherent bi-stability of ferroelectrics to create non-volatile, deterministic, and repeatedly obtainable multi-state polarization without compromising other important properties, and holds promise for non-volatile multi-state functional applications.

36 MATERIALS SCIENCE↗

Using metacommunity ecology to understand environmental metabolomes

Abstract Environmental metabolomes are fundamentally coupled to microbially-linked biogeochemical processes within ecosystems. However, significant gaps exist in our understanding of their spatiotemporal organization, limiting our ability to uncover transferrable principles and predict ecosystem function. We propose that a theoretical paradigm, which integrates concepts from metacommunity ecology, is necessary to reveal underlying mechanisms governing metabolomes. We call this synthesis between ecology and metabolomics ‘meta-metabolome ecology’ and demonstrate its utility using a mass spectrometry dataset. We developed three relational metabolite dendrograms using molecular properties and putative biochemical transformations and performed ecological null modeling. Based upon null modeling results, we show that stochastic processes drove molecular properties while biochemical transformations were structured deterministically. We further suggest that potentially biochemically active metabolites were more deterministically assembled than less active metabolites. Understanding variation in the influences of stochasticity and determinism provides a way to focus attention on which meta-metabolomes and which parts of meta-metabolomes are most likely to be important to consider in mechanistic models. We propose that this paradigm will allow researchers to study the connections between ecological systems and their molecular processes in previously inaccessible detail.

54 ENVIRONMENTAL SCIENCES↗

SiGe quantum wells with oscillating Ge concentrations for quantum dot qubits

Large-scale arrays of quantum-dot spin qubits in Si/SiGe quantum wells require large or tunable energy splittings of the valley states associated with degenerate conduction band minima. Existing proposals to deterministically enhance the valley splitting rely on sharp interfaces or modifications in the quantum well barriers that can be difficult to grow. Here, we propose and demonstrate a new heterostructure, the “Wiggle Well”, whose key feature is Ge concentration oscillations inside the quantum well. Experimentally, we show that placing Ge in the quantum well does not significantly impact our ability to form and manipulate single-electron quantum dots. We further observe large and widely tunable valley splittings, from 54 to 239 μ eV. Tight-binding calculations, and the tunability of the valley splitting, indicate that these results can mainly be attributed to random concentration fluctuations that are amplified by the presence of Ge alloy in the heterostructure, as opposed to a deterministic enhancement due to the concentration oscillations. Quantitative predictions for several other heterostructures point to the Wiggle Well as a robust method for reliably enhancing the valley splitting in future qubit devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Imaging of a van der Waals spin-orbit torque system using spin ensembles in hBN

Recently, optically active spin defects embedded in two-dimensional (2D) van der Waals (vdW) crystals have emerged as a transformative quantum sensing platform to explore cutting-edge materials science. Taking advantage of excellent solid-state integrability, this new class of spin defects can be readily arranged in nanoscale proximity to target materials, showing great promise for realizing in-situ quantum sensing of microscopic spin and charge behaviors in vdW heterostructures. Here we report hexagonal boron nitride-based quantum imaging of field-free deterministic magnetic switching and electric current distributions in an all-vdW spin-orbit torque (SOT) system. By visualizing variations of nanoscale magnetic stray field profile of room-temperature 2D magnet Fe 3 GaTe 2 under different SOT conditions, we show how the magnetic switching evolves from deterministic to stochastic behavior due to the interplay between spin orientations, anisotropy and Joule heating. Micromagnetic simulations rationalize our results well, revealing the role of field-like SOT in inhibiting thermal fluctuation driven stochastic switching and chaotic multi-domain competition. This understanding, which is otherwise difficult to access by conventional transport measurements, offers valuable insights into material design, testing, and performance evaluation of next-generation vdW spintronic devices.

Imaging techniques↗

High-dimensional optical quantum logic in large operational spaces

The probabilistic nature of single-photon sources and photon–photon interactions encourages encoding as much quantum information as possible in every photon for the purpose of photonic quantum information processing. Here, by encoding high-dimensional units of information (qudits) in time and frequency degrees of freedom using on-chip sources, we report deterministic two-qudit gates in a single photon with fidelities exceeding 0.90 in the computational basis. Constructing a two-qudit modulo SUM gate, we generate and measure a single-photon state with nonseparability between time and frequency qudits. We then employ this SUM operation on two frequency-bin entangled photons—each carrying two 32-dimensional qudits—to realize a four-party high-dimensional Greenberger–Horne–Zeilinger state, occupying a Hilbert space equivalent to that of 20 qubits. Although high-dimensional coding alone is ultimately not scalable for universal quantum computing, our design shows the potential of deterministic optical quantum operations in large encoding spaces for practical and compact quantum information processing protocols.

97 MATHEMATICS AND COMPUTING↗

Violating Bell’s inequality with remotely connected superconducting qubits

Quantum communication relies on the efficient generation of entanglement between remote quantum nodes, as entanglement is required to achieve and verify secure communications. Remote entanglement has been realized using a number of different probabilistic schemes, but deterministic remote entanglement has only been demonstrated recently, using a variety of superconducting circuit approaches. However, the deterministic violation of a Bell inequality, a strong measure of quantum correlation, has not been demonstrated so far in a superconducting quantum communication architecture, in part because achieving sufficiently strong correlation requires fast and accurate control of the emission and capture of the entangling photons. We present a simple and robust architecture for achieving this benchmark result in a superconducting system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗