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At least 343 records · Page 19

Resource-Optimized Fermionic Local-Hamiltonian Simulation on a Quantum Computer for Quantum Chemistry

The ability to simulate a fermionic system on a quantum computer is expected to revolutionize chemical engineering, materials design, nuclear physics, to name a few. Thus, optimizing the simulation circuits is of significance in harnessing the power of quantum computers. Here, we address this problem in two aspects. In the fault-tolerant regime, we optimize the R z and T gate counts along with the ancilla qubit counts required, assuming the use of a product-formula algorithm for implementation. We obtain a savings ratio of two in the gate counts and a savings ratio of eleven in the number of ancilla qubits required over the state of the art. In the pre-fault tolerant regime, we optimize the two-qubit gate counts, assuming the use of the variational quantum eigensolver (VQE) approach. Specific to the latter, we present a framework that enables bootstrapping the VQE progression towards the convergence of the ground-state energy of the fermionic system. This framework, based on perturbation theory, is capable of improving the energy estimate at each cycle of the VQE progression, by about a factor of three closer to the known ground-state energy compared to the standard VQE approach in the test-bed, classically-accessible system of the water molecule. The improved energy estimate in turn results in a commensurate level of savings of quantum resources, such as the number of qubits and quantum gates, required to be within a pre-specified tolerance from the known ground-state energy. We also explore a suite of generalized transformations of fermion to qubit operators and show that resource-requirement savings of up to more than 20 % , in small instances, is possible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interactively Assessing Disentanglement in GANs

Abstract Generative adversarial networks (GAN) have witnessed tremendous growth in recent years, demonstrating wide applicability in many domains. However, GANs remain notoriously difficult for people to interpret, particularly for modern GANs capable of generating photo‐realistic imagery. In this work we contribute a visual analytics approach for GAN interpretability, where we focus on the analysis and visualization of GAN disentanglement. Disentanglement is concerned with the ability to control content produced by a GAN along a small number of distinct, yet semantic, factors of variation. The goal of our approach is to shed insight on GAN disentanglement, above and beyond coarse summaries, instead permitting a deeper analysis of the data distribution modeled by a GAN. Our visualization allows one to assess a single factor of variation in terms of groupings and trends in the data distribution, where our analysis seeks to relate the learned representation space of GANs with attribute‐based semantic scoring of images produced by GANs. Through use‐cases, we show that our visualization is effective in assessing disentanglement, allowing one to quickly recognize a factor of variation and its overall quality. In addition, we show how our approach can highlight potential dataset biases learned by GANs.

Jeong, Sangwon↗

Nanoscale imaging of Gilbert damping using signal amplitude mapping

Ferromagnetic resonance force microscopy (FMRFM) is a powerful scanned probe technique that uses sub-micrometer-scale, spatially localized standing spin wave modes (LMs) to perform local ferromagnetic resonance (FMR) measurements. In this work, we show the spatially resolved imaging of Gilbert damping in a ferromagnetic material (FM) using FMRFM. Typically damping is measured from the FMR linewidth. We demonstrate an approach to image the spatial variation of Gilbert damping utilizing the LM resonance peak height to measure the LM resonance cone angle. This approach enables determination of damping through field-swept FMRFM at a single excitation frequency. The extreme force sensitivity of similar to 2 fN at room temperature can resolve changes of Gilbert damping as small as ~2 x 10 -4 at 2GHz, corresponding to ~0.16Oe in FMR linewidth resolution. This high sensitivity, high spatial resolution, and single frequency imaging of Gilbert damping creates the opportunity to study spin interactions at the interface between an insulating FM and a small volume of nonmagnetic material such as atomically thin two-dimensional materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Stronger field-emission science via coupling novel nanoscale imaging techniques

We implemented a vacuum field emission electron microscope (FEM) using the electron optics of a low-energy /photoemission electron microscope (LEEM/PEEM). Historically, there have been other FEM hardware platforms, and the distinctive feature of our method is that it integrates with the LEEM/PEEM and associated techniques, enabling a powerful multi-capability toolset for studying fundamental materials properties underpinning field emission (FE) and vacuum arc initiation. Typically, LEEM is used to image surface structure, which influences both work function and electric field distribution near a surface, while PEEM is used to map photoelectric work function across a surface. Our FEM adds the capability for spatially-correlated coincident-site measurements of FE currents to go-along with structure and work function. LEEM, PEEM, and our FEM implementation achieve nanoscale spatial resolution relevant for materials studies in nanoscience/engineering. Our approach requires a straightforward calibration of the electron optics to enable focused FEM imaging under intentional electric field variation. We demonstrate the FEM approach by imaging field emitter arrays relevant for vacuum nanoelectronics. We demonstrate submicron spatial resolution and dynamic measurement of FE versus applied electric field. We anticipate this capability will enable fundamental structure-function studies of FE and arc initiation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Hybrid Data Assimilation without Ensemble Filtering

The Global Modeling and Assimilation Office is preparing to upgrade its three-dimensional variational system to a hybrid approach in which the ensemble is generated using a square-root ensemble Kalman filter (EnKF) and the variational problem is solved using the Grid-point Statistical Interpolation system. As in most EnKF applications, we found it necessary to employ a combination of multiplicative and additive inflations, to compensate for sampling and modeling errors, respectively and, to maintain the small-member ensemble solution close to the variational solution; we also found it necessary to re-center the members of the ensemble about the variational analysis. During tuning of the filter we have found re-centering and additive inflation to play a considerably larger role than expected, particularly in a dual-resolution context when the variational analysis is ran at larger resolution than the ensemble. This led us to consider a hybrid strategy in which the members of the ensemble are generated by simply converting the variational analysis to the resolution of the ensemble and applying additive inflation, thus bypassing the EnKF. Comparisons of this, so-called, filter-free hybrid procedure with an EnKF-based hybrid procedure and a control non-hybrid, traditional, scheme show both hybrid strategies to provide equally significant improvement over the control; more interestingly, the filter-free procedure was found to give qualitatively similar results to the EnKF-based procedure.

Kalman Filter↗

Spatial and temporal patterns of biotic exchange of CO2

Our research is focused on a better quantification of the variations in C02(sub) exchanges between the atmosphere and biosphere and the factors responsible for these exchanges. The principal approach is to infer the variations in the exchanges from variations in the atmospheric C02(sub) distribution.

Fung, Inez↗

A Scalable Space-Time Domain Decomposition Approach for Solving Large Scale Nonlinear Regularized Inverse Ill Posed Problems in 4D Variational Data Assimilation

We address the development of innovative algorithms designed to solve the strong-constraint Four Dimensional Variational Data Assimilation (4DVar DA) problems in large scale applications. We present a space-time decomposition approach which employs the whole domain decomposition, i.e. both along the spacial and temporal direction in the overlapping case, and the partitioning of both the solution and the operator. Starting from the global functional defined on the entire domain, we get to a sort of regularized local functionals on the set of sub domains providing the order reduction of both the predictive and the Data Assimilation models. The algorithm convergence is developed. Performance in terms of reduction of time complexity and algorithmic scalability is discussed on the Shallow Water Equations on the sphere. The number of state variables in the model, the number of observations in an assimilation cycle, as well as numerical parameters as the discretization step in time and in space domain are defined on the basis of discretization grid used by data available at repository Ocean Synthesis/Reanalysis Directory of Hamburg University.

97 MATHEMATICS AND COMPUTING↗

Impact of storage and blending of algae and forest product residue on fuel blendstock production

Seasonal impacts on the production of algae biomass require blending with other feedstocks such as wood to maintain consistent annual conversion capacity. Idaho National Laboratory (INL) has developed a long-term storage strategy for algae biomass using ensiling, or anaerobic wet storage, that was tested for blends of algae and wood to stabilize the feedstock supply for processing to fuels. Additionally, blending biomass (algae and wood) leverages existing biomass storage approaches commonly used by the feed and forage industry. Earlier research also has demonstrated positive results that indicate ensiling is more effective and economical in normalizing biomass feedstock supply prior to conversions such as HTL (hydrothermal liquefaction) than preserving biomass by drying. By assessing impacts beginning with upstream logistic operations and proceeding through each conversion step, this work focuses on conversion of ensiled and blended biomass to fungible liquid transportation fuel blendstocks. This is accomplished by conversion of the blended biomass (62% Chlorella sp. blended with 38% loblolly pine forest product residues [FPR]) to bio-crude through HTL and subsequent upgrading through HT (hydrotreating) with a commercial refinery catalyst analogous to a refinery process to produce hydrocarbon fuel. In this work, results indicate that carbon retention and quality are preserved in both the bio-crude and upgraded fuel from the ensiled blend, indicating the potential of this approach for managing seasonal variations in algae biomass productivity.

09 BIOMASS FUELS↗

Uniformity and volume-representativity of consecutive submillimetre wafers of shale for SANS and USANS investigations

(Ultra) Small Angle Neutron Scattering (SANS/USANS) is a non-destructive technique suitable for characterization of porous structures from nano- to micro-pore size (1 nm to 20 μm), which has been widely used to characterize accessible and inaccessible porosity in tight unconventional hydrocarbon reservoirs (e.g., shales). Here, in this study, SANS and USANS are used to examine the degree of nano- to micropore uniformity of the rock body on sub-millimetre to centimetre scale. This study presents a test of the hypothesis of volume representativity of pore structure information measured by SANS and USANS for shale wafers (0.22–1 mm) cut from six North American unconventional shale cores of different maturities (New Albany Shale and Marcellus Shale). Experimental reproducibility of USANS is further investigated for two wafers measured using various acquisition times. All samples show that fluctuations of the relative intensity generally decrease from the USANS Q-range (pore size from around 200 nm to 20 μm) to most of the SANS Q-range (pore size from around 5 nm to 700 nm), and peaks in the SANS large-Q region (for pores smaller than about 5 nm). There is a positive correlation between the spatial fluctuation of the relative SANS intensity and the scattering power of shales. In addition, the scattering intensity and its fluctuations is larger for the less mature shale cores. Shale is known to be highly heterogenous and the hypothesis of uniformity does not apply at sub-millimetre scale even for samples that appear homogeneous at visual inspection. This study presents an approach to minimise the variation through sample selection, data interpretation methodology and instrumental reproducibility tests. The best values of the microstructural spatial uniformity for the apparently homogeneous sections of a core (i.e., the SANS and USANS intensity variation) is less than ±10%.

01 COAL, LIGNITE, AND PEAT↗

Influences on hydrogen production at a wind farm

If an affordable infrastructure for low-carbon-intensity hydrogen can be developed, then hydrogen is expected to become a key factor in decarbonizing the atmosphere. This research focuses on factors an existing wind farm operator would consider when weighing participating in the electricity market, the hydrogen market, or both. The solutions depend on the state of technology, which is changing rapidly, the local market structures, the local natural resources, and the local pre-existing infrastructure. Consequently, this investigation used an assessment approach that examined the variation of net present value. The investigation identified profitability conditions under three different scenarios: 1) Make and sell what makes economic sense at the time of production, 2) Use electrolyzer and fuel cell to consume power from the grid at times of low net demand and to produce electricity at times of high net demand, 3) Same as #2 but also market hydrogen directly when profitable.

08 HYDROGEN↗

Diffused trenches for high fill-factor Low-Gain Avalanche Diodes

Low-Gain Avalanche Diodes (LGADs) are a class of silicon detectors that have been specifically designed for the fast detection of minimum ionizing particles (mips) in High-Energy Physics experiments. While they provide timing resolution on the order of a few tens of picoseconds, they cannot achieve high spatial resolution due to the intrinsic characteristics of their structures. Thus, active R&D is on-going to develop detectors based on LGADs to improve their spatial resolution while maintaining the timing performance of the LGADs. Such devices are, for example, AC-coupled LGADs and Deep-Junction LGADs. Another device option is the Trench-Isolated LGAD (TI LGAD), where trenches etched at the periphery of the pixels isolate them while providing a high fill-factor. Here, in this paper, we present a variation of this latter approach, demonstrating its feasibility by means of 2-dimensional TCAD simulations.

47 OTHER INSTRUMENTATION↗

In Situ Analysis of Electron-Induced Chemical Transformations in Vapor-Phase-Synthesized Al-Based Inorganic–Organic Hybrid Thin Films for EUV Resist Platform

The rapid advancement and stringent requirements of extreme ultraviolet (EUV) lithography technology necessitate the development of advanced photoresist systems for next-generation microelectronics. Recent studies have demonstrated that inorganic-based hybrid photoresists offer notable improvements in EUV sensitivity, etch resistance, and greater insusceptibility to pattern collapse compared to their purely organic counterparts. However, variations in the synthesis/coating approaches and chemistry of inorganic–organic photoresists can result in distinct exposure mechanisms. In this work, an Al-based hybrid thin film resist system synthesized via molecular (atomic) layer deposition (MLD or MALD) is explored, focusing on its electron-beam and EUV patterning mechanisms. The Al-based hybrid thin films are deposited using trimethylaluminum (TMA) and the organic precursor hydroquinone, exhibiting a saturated growth rate within the temperature range of 150–200°C. In diluted tetramethylammonium hydroxide (TMAH)-based developer solutions, the electron-irradiated Al-based hybrid thin film system behaves as a negative tone resist, achieving a sensitivity of 10.4 mC/cm 2 at 0.1 kV electron beam lithography (EBL). Chemical changes induced by electron exposure are also analyzed in this study using X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and a unique infrared spectroscopy setup, revealing the potential cross-linking pathways. To further correlate the electron-induced chemical transformations with those mediated by EUV irradiations, a combination of X-ray photoemission electron microscopy/low-energy electron microscopy (XPEEM/LEEM) system is also employed. In conclusion, this study provides critical insights into the mechanisms underlying solubility switching and contributes to the design of advanced resist materials for EUV lithography.

36 MATERIALS SCIENCE↗

A Facile Approach to High Precision Detection of Cell-to-Cell Variation for Li-ion Batteries

Abstract Over the past decade, it has been repeatedly demonstrated that homogeneity in electrochemical performance of lithium-ion cells plays a major role in determining the life and safety of lithium-ion battery modules or packs. Generally, the homogeneity of a battery pack is evaluated by characterizing the cells individually in terms of capacity, mass, impedance. Particularly, high quality electrochemical data heavily relies on the availability of high precision current source to minimize the discrepancy induced by the channel-to-channel variation. Here, a facile and precise measurement method is reported for screening cell-to-cell variations, in which voltage is the only indicator parameter independent of high precision current source. In detail, by connecting the cells in series (CiS), the measurement error of electrochemical data caused by stability and discrepancy of current sources among different charge/discharge equipment can be effectively avoided. The findings of this work showed that the cell-to-cell variations can be simply and sensitively detected with CiS configuration. For example, the relative standard deviation, which is the evaluation criterion of battery homogeneity, was 2.14% based on CiS while it was 0.43% based on individual measurements. The simple and precise CiS measurement is promising for evaluation of cell quality or module integration quality. In addition, this work can also provide a solid foundation for the development of detection algorithms for battery management systems to rapidly monitor battery homogeneity.

25 ENERGY STORAGE↗

Case study on climate change effects and food security in Southeast Asia

Agriculture, a cornerstone of human civilization, faces rising challenges from climate change, resource limitations, and stagnating yields. Precise crop production forecasts are crucial for shaping trade policies, development strategies, and humanitarian initiatives. This study introduces a comprehensive machine learning framework designed to predict crop production. We leverage CMIP5 climate projections under a moderate carbon emission scenario to evaluate the future suitability of agricultural lands and incorporate climatic data, historical agricultural trends, and fertilizer usage to project yield changes. Our integrated approach forecasts significant regional variations in crop production across Southeast Asia by 2028, identifying potential cropland utilization. Specifically, the cropland area in Indonesia, Malaysia, Philippines, and Viet Nam is projected to decline by more than 10% if no action is taken, and there is potential to mitigate that loss. Moreover, rice production is projected to decline by 19% in Viet Nam and 7% in Thailand, while the Philippines may see a 5% increase compared to 2021 levels. Our findings underscore the critical impacts of climate change and human activities on agricultural productivity, offering essential insights for policy-making and fostering international cooperation.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of the excitation spectra with diffusion Monte Carlo on an auxiliary bosonic ground state

We aim to improve upon the variational Monte Carlo (VMC) approach for excitations replacing the Jastrow factor by an auxiliary bosonic (AB) ground state and multiplying it by a fermionic component factor. The instantaneous change in imaginary time of an arbitrary excitation in the original interacting fermionic system is obtained by measuring observables via the ground-state distribution of walkers of an AB system that is subject to an auxiliary effective potential. The effective potential is used to (i) drive the AB system’s ground-state configuration space toward the configuration space of the excitations of the original fermionic system and (ii) subtract from a diffusion Monte Carlo (DMC) calculation contributions that can be included in conventional approximations, such as mean-field and configuration interaction (CI) methods. In this novel approach, the AB ground state is treated statistically in DMC, whereas the fermionic component of the original system is expanded in a basis. The excitation energies of the fermionic eigenstates are obtained by sampling a fermion–boson coupling term on the AB ground state. We show that this approach can take advantage of and correct for approximate eigenstates obtained via mean-field calculations or truncated interactions. We demonstrate that the AB ground-state factor incorporates the correlations missed by standard Jastrow factors, further reducing basis truncation errors. Relevant parts of the theory have been tested in soluble model systems and exhibit excellent agreement with exact analytical data and CI and VMC approaches. In particular, for limited basis set expansions and sufficient statistics, AB approaches outperform CI and VMC in terms of basis size for the same systems. The implementation of this method in current codes, despite being demanding, will be facilitated by reusing procedures already developed for calculating ground-state properties with DMC and excitations with VMC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum computing for heavy quarkonium spectroscopy

Here, we report a first demonstration for the application of quantum computing to heavy quarkonium spectroscopy study. Based on a Cornell-potential model for the heavy quark and antiquark system, we show how this Hamiltonian problem can be formulated and solved with the variational quantum eigensolver (VQE) approach on the IBM cloud quantum computing platform. Errors due to a global depolarizing noise channel are corrected with a zero-noise extrapolation method, resulting in good agreement with the expected value. We also generalize the VQE method for solving excited states by orthogonalization with respect to the ground state. This new approach is demonstrated to be successful for the quarkonium system on a noiseless quantum simulator and can easily be adapted for solving similar excited state problems in many other physical systems.

79 ASTRONOMY AND ASTROPHYSICS↗

Metabolic and evolutionary responses of Clostridium thermocellum to genetic interventions aimed at improving ethanol production

Engineering efforts targeted at increasing ethanol by modifying the central fermentative metabolism of Clostridium thermocellum have been variably successful. Here, we aim to understand this variation by a multifaceted approach including genomic and transcriptomic analysis combined with chemostat cultivation and high solids cellulose fermentation. Three strain lineages comprising 16 strains total were examined. Two strain lineages in which genes involved in pathways leading to organic acids and/or sporulation had been knocked out resulted in four end-strains after adaptive laboratory evolution (ALE). A third strain lineage recapitulated mutations involving adhE that occurred spontaneously in some of the engineered strains.

Biotechnology & Applied Microbiology↗