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At least 631 records · Page 35

PiCAM: A Raspberry Pi-based open-source, low-power camera system for monitoring plant phenology in Arctic environments

Time-lapse cameras have been widely used as a tool to monitor the timing of seasonal vegetation growth. These simple, relatively inexpensive systems can provide high-frequency observations of leaf development and demography which are critical data sets needed to characterize plant phenology from species to landscapes. This is important for understanding how plants are responding to global changes, as well as for validating satellite-derived phenology products. However, in remote regions including the high-latitude Arctic, deploying time-lapse cameras could be challenging. The remoteness and lack of widespread power and telecommunications infrastructure limit options for the installation, maintenance and retrieval of data and equipment, and make it difficult for cameras to survive in extreme weather (e.g. long cold winters). To improve our understanding of Arctic phenology, new technologies are required to address these challenges. Here, we present a novel, low-power, compact, lightweight time-lapse camera system, called power-interval camera automation module (PiCAM). The PiCAM was designed with explicit consideration to simplify deployment (i.e. without a need for external power supplies) of camera systems and to address the challenges of camera survival in harsh Arctic environments. In this paper, we describe the design, setup and technical details of the PiCAM and provide a roadmap for how to build and operate these systems. As proof of concept, we deployed 26 PiCAMs at three low-Arctic tundra sites on the Seward Peninsula, Alaska in early August 2021 for characterizing Arctic plant phenology. Of the 26 PiCAMs, 70% remained active at the point of our revisit in late July 2022 despite the extreme winter temperatures they experienced (< –30°C, heavy snow cover). We extracted key plant phenology metrics from the PiCAMs and captured strong differences across key Arctic plant species. We showed that the PiCAM has the potential to be widely used for monitoring plant phenology across the broader Arctic region, addressing the need for ground-based understanding of Arctic phenological diversity to develop knowledge of plant response to climate change and to validate remote sensing products.

54 ENVIRONMENTAL SCIENCES↗

Ground state energy and magnetization curve of a frustrated magnetic system from real-time evolution on a digital quantum processor

Models of interacting many-body quantum systems that may realize new exotic phases of matter, notably quantum spin liquids, are challenging to study using even state-of-the-art classical methods such as tensor network simulations. Quantum computing provides a promising route for overcoming these difficulties to find ground states, dynamics, and more. In this paper, we argue that recently developed hybrid quantum-classical algorithms based on real-time evolution are promising methods for solving a particularly important model in the search for spin liquids, the antiferromagnetic Heisenberg model on the two-dimensional kagome lattice. We show how to construct efficient quantum circuits to implement time evolution for the model and to evaluate key observables on the quantum computer, and we argue that the method has favorable scaling with increasing system size. We then restrict to a 12-spin star plaquette from the kagome lattice and a related 8-spin system, and we give an empirical demonstration on these small systems that the hybrid algorithms can efficiently find the ground state energy and the magnetization curve. For these demonstrations, we use four levels of approximation: exact state vectors, exact state vectors with statistical noise from sampling, noisy classical emulators, and (for the 8-spin system only) real quantum hardware, specifically the Quantinuum H1-1 processor; for the noisy simulations and hardware demonstration, we also employ error mitigation strategies based on the symmetries of the Hamiltonian. Our results strongly suggest that these hybrid algorithms present a promising direction for studying quantum spin liquids and more generally for resolving important unsolved problems in condensed matter theory and beyond.

97 MATHEMATICS AND COMPUTING↗

Motivation and Design of the OCPP Security Service

Pacific Northwest National Laboratory is conducting in-depth research aimed at exploring how zero trust security principles can be effectively applied to electric vehicle charging infrastructure. This investigation seeks to enhance the resilience and reliability of these systems against cyber threats, ensuring secure and uninterrupted access to charging services for electric vehicle users and electric supply. Zero trust is a security concept centered on the belief that system operators should not automatically trust users or systems based on their location, whether inside or outside the organization, but instead must verify everything trying to connect to their systems before granting access. A key aspect of the project is to demonstrate and validate zero trust approaches targeted to electric vehicle (EV) charging infrastructure. It has been observed that both open-source and commercial solutions often overlook the specific protocols employed in managing EV charging stations and proceeded with a general, protocol-agnostic approach. While these strategies effectively block non-authorized routes to the charging infrastructure, they do not tackle the situations where attackers may exploit legitimate access channels, such as the inattentive operator model posited by the Idaho National Laboratory. To address this gap, this paper proposes and discusses a new security service targeted to the Open Charge Point Protocol (OCPP), which is the de facto protocol for the management of charging stations and serves a critical role in the broader adoption of electric vehicles. The design and architecture of the proposed OCPP security service are discussed in detail, outlining how it aims to safeguard charging station management system (CSMS) functions. The service is particularly important in scenarios where the charging station operator (CSO), responsible for the maintenance and operation of charging stations, and the charging network provider (CNP), which manages the charging network's accessibility and billing, are separate entities. This distinction is crucial because CSOs and CNPs often have different priorities, objectives, and operational responsibilities, which may not always align perfectly. For instance, a CSO might prioritize uptime and customer satisfaction, while a CNP might focus on maximizing revenue and network utilization. Such misalignment can create security vulnerabilities, as each entity might implement different policies and standards, potentially leaving gaps in the overall security posture.

33 ADVANCED PROPULSION SYSTEMS↗

A Detailed Characterization of HR 8799's Debris Disk with ALMA in Band 7

The exoplanetary system of HR 8799 is one of the rare systems in which multiple planets have been directly imaged. Its architecture is strikingly similar to that of the solar system, with the four imaged giant planets surrounding a warm dust belt analogous to the Asteroid Belt, and themselves being surrounded by a cold dust belt analog to the Kuiper Belt. Previous observations of this cold belt with ALMA in Band 6 (1.3 mm) revealed its inner edge, but analyses of the data differ on its precise location. It was therefore unclear whether or not the outermost planet HR 8799 b was dynamically sculpting it. We present here new ALMA observations of this debris disk in Band 7 (340 GHz, 880 μm). These are the most detailed observations of this disk obtained so far, with a resolution of 1″ (40 au) and sensitivity of 9.8 μJy beam{sup −1}, which allowed us to recover the disk structure with high confidence. In order to constrain the disk morphology, we fit its emission using radiative transfer models combined with a Markov Chain Monte Carlo procedure. We find that this disk cannot be adequately represented by a single power law with sharp edges. It exhibits a smoothly rising inner edge and smoothly falling outer edge, with a peak in between, as expected from a disk that contains a high-eccentricity component, hence confirming previous findings. Whether this excited population and inner edge shape stem from the presence of an additional planet remains, however, an open question.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Time-Resolved Spectroscopy of Insulator-Metal Transitions: Exploring Low-Energy Dynamics in Strongly Correlated Systems. Final Report

Transition metal oxides (TMOs) have attracted much attention in recent years. The strong coupling between charge, spin, and orbital degrees of freedom creates novel functional properties. The research at the interplay between ferromagnetism, ferroelectricity and conductivity provides a promising way to the development of future spintronic devices. The interface characterization of multifunctional oxide heterostructures is crucial to understand deeply the magnetic response, spin injection and spin transport. In year one, we characterized optically the magnetic property with the method of magnetization-induced second-harmonic generation (MSHG), which is a sensitive technique to selectively probe the interface where the spatial inversion symmetry is broken. The interface of n-type BaTiO 3 (BTO)/La 0.67 Sr 0.33 MnO 3 (LSMO) forms a Schottky barrier and displays a good diode effect. By applying an external electric field across the sample, we observe the magnetoelectric (ME) coupling effect to modulate the interface magnetization. The voltage dependent magnetic contrast sharply vanishes at positive voltage (applied to LSMO contact) and reveals a ferromagnetic (FM)-to- antiferromagnetic (AFM) transition occurring at the interface, while the magneto-optic Kerr effect (MOKE) indicates that the bulk property is not affected. The strain mediated mechanism and ferroelectric (FE) polarization induced charge medicated mechanism are both discussed, but they do not play an important role in the observed magnetization transition. A new mechanism is proposed - the injected minority spins through strong Hund's interaction with the local magnetic moments at positive voltage weaken the double-exchange interaction of nearby Mn e g electrons, thereby reducing the ferromagnetic (FM) ordering. The dominant superexchange interaction of localized t 2g electrons finally leads to the AFM configuration. By reducing the electron carrier concentration of BTO, a positive voltage shift of the transition is observed. The oxygen richer sample with lower carrier concentration requires a higher voltage to increase the hole doping level of LSMO to induce the interfacial AFM phase. By inserting a thin (1nm) La 0.5 Ca 0.5 MnO 3 layer between BTO and LSMO, the interface magnetic response from LSMO is enhanced. In year two, a non-multiferroic heterostructure SrTiO 3 (STO)/ La 0.5 Ca 0.5 MnO 3 (LCMO)/La 0.67 Sr 0.33 MnO 3 (LSMO) was studied. In this system, the interface FM-AFM transition is observed at negative voltage. The STO layer may act as a hole-donating layer, which induces the hole transfer to LSMO making it overdoped, while the LCMO interlayer at the 0.5 hole doping level displays complicated CE type AFM phase. Thus the AFM phase is dominant at the interface and electron accumulation is required to induce the FM phase by applying a negative voltage. For oxygen rich sample, the magnetic MSHG loop reappears at high positive voltage (around +2.5 V). At high doping level (x > 0.5), LSMO exhibits A-type AFM order, consisting of AFM superexchange coupling between adjacent layers and intralayer FM double-exchange coupling. The less tensile strain of STO and LSMO due to a smaller lattice mismatch as compared to BTO would result in a weaker interlayer coupling . Thus, interfacial A-type AFM order can occur in STO/LCMO/LSMO heterostructure at high hole doping concentration. The study of ME coupling of multifunctional oxide heterostructures is definitely important to the development and performance of future spintronic devices. The results presented here regarding the interfacial magnetic transition controlled by an external electric field offer some new perspective to study the spin transport of magnetic tunnel junctions.

36 MATERIALS SCIENCE↗

From irregular to regular eutectic growth in the Al-Al 3 Ni system: In situ observations during directional solidification

Here we investigate the irregular eutectic growth dynamics of the Al-Al 3 Ni alloy, in which one of the solid phases (Al 3 Ni) grows faceted from the liquid. Leveraging in situ optical microscopy and synchrotron transmission x-ray microscopy, we address the question of the degree of coupling between Al and Al 3 Ni at the growth front and that of the shape of the microstructures left behind in the bulk solid during directional solidification. Real-time optical observations bring evidence for a morphological transition from a eutectic-grain dependent, irregular eutectic growth at low solidification velocity V (typically 1 μm s -1 ), to a weakly anisotropic, regular growth at higher V ( reaching 10 μm s -1 ). Unprecedented x-ray nano-imaging of the solid–liquid interface, and 3D characterization of the growth patterns, were made possible by a new DS setup at Brookhaven National Laboratory’s NSLS-II. At low V, the leading tips of partly faceted Al 3 Ni crystals are observed to grow not far ahead of the Al growth front. Correlating in situ images and postmortem 3D tomographic reconstructions reveals that the presence of faceted and non-faceted regions of Al 3 Ni crystals in the solid is a direct consequence of coupling and decoupling during DS, respectively. Upon increasing V, the lead distance of Al 3 Ni vanishes, and the shape of Al 3 Ni ceases to be governed by faceted growth. These observations cast light onto the basic mechanisms (faceted growth, diffusive coupling, and the dynamics of trijunctions) governing a faceted to rod-like transition upon increasing V in the Al 3 Ni system, with broad implications to a large class of irregular eutectics.

36 MATERIALS SCIENCE↗

SOMA: Observability, monitoring, and in situ analytics for exascale applications

With the rise of exascale systems and large, data-centric workflows, the need to observe and analyze high performance computing (HPC) applications during their execution is becoming increasingly important. HPC applications are typically not designed with online monitoring in mind, therefore, the observability challenge lies in being able to access and analyze interesting events with low overhead while seamlessly integrating such capabilities into existing and new applications. We explore how our service-based observation, monitoring, and analytics (SOMA) approach to collecting and aggregating both application-specific diagnostic data and performance data addresses these needs. Furthermore, we present our SOMA framework and demonstrate its viability with LULESH, a hydrodynamics proxy application. Then we focus on Astaroth, a multi-GPU library for stencil computations, highlighting the integration of the TAU and APEX performance tools and SOMA for application and performance data monitoring.

97 MATHEMATICS AND COMPUTING↗

Quantum liquid from strange frustration in the trimer magnet Ba4Ir3O10

Abstract Quantum spin systems such as magnetic insulators usually show magnetic order, but such classical states can give way to quantum liquids with exotic entanglement through two known mechanisms of frustration: geometric frustration in lattices with triangle motifs, and spin-orbit-coupling frustration in the exactly solvable quantum liquid of Kitaev’s honeycomb lattice. Here we present the experimental observation of a new kind of frustrated quantum liquid arising in an unlikely place: the magnetic insulator Ba 4 Ir 3 O 10 where Ir 3 O 12 trimers form an unfrustrated square lattice. The crystal structure shows no apparent spin chains. Experimentally we find a quantum liquid state persisting down to 0.2 K that is stabilized by strong antiferromagnetic interaction with Curie–Weiss temperature ranging from −766 to −169 K due to magnetic anisotropy. The anisotropy-averaged frustration parameter is 2000, seldom seen in iridates. Heat capacity and thermal conductivity are both linear at low temperatures, a familiar feature in metals but here in an insulator pointing to an exotic quantum liquid state; a mere 2% Sr substitution for Ba produces long-range order at 130 K and destroys the linear-T features. Although the Ir 4+ (5d 5 ) ions in Ba 4 Ir 3 O 10 appear to form Ir 3 O 12 trimers of face-sharing IrO 6 octahedra, we propose that intra-trimer exchange is reduced and the lattice recombines into an array of coupled 1D chains with additional spins. An extreme limit of decoupled 1D chains can explain most but not all of the striking experimental observations, indicating that the inter-chain coupling plays an important role in the frustration mechanism leading to this quantum liquid.

36 MATERIALS SCIENCE↗

Ideal conductor/dielectric model (ICDM): A generalized technique to correct for finite-size effects in molecular simulations of hindered ion transport

Molecular simulations serve as indispensable tools for investigating the kinetics and elucidating the mechanism of hindered ion transport across nanoporous membranes. In particular, recent advancements in advanced sampling techniques have made it possible to access translocation timescales spanning several orders of magnitude. In our prior study [Shoemaker et al., J. Chem. Theory Comput. 18, 7142 (2022)], we identified significant finite size artifacts in simulations of pressure-driven hindered ion transport through nanoporous graphitic membranes. We introduced the ideal conductor model, which effectively corrects for such artifacts by assuming the feed to be an ideal conductor. In the present work, we introduce the ideal conductor dielectric model (Icdm), a generalization of our earlier model, which accounts for the dielectric properties of both the membrane and the filtrate. Using the Icdm model substantially enhances the agreement among corrected free energy profiles obtained from systems of varying sizes, with notable improvements observed in regions proximate to the pore exit. Moreover, the model has the capability to consider secondary ion passage events, including the transport of a co-ion subsequent to the traversal of a counter-ion, a feature that is absent in our original model. We also investigate the sensitivity of the new model to various implementation details. The Icdm model offers a universally applicable framework for addressing finite size artifacts in molecular simulations of ion transport. It stands as a significant advancement in our quest to use molecular simulations to comprehensively understand and manipulate ion transport processes through nanoporous membranes.

Chemistry↗

Magnetic states of the quasi-one-dimensional iron chalcogenide Ba 2 FeS 3

Quasi-one-dimensional iron-based ladders and chains, with the 3d iron electronic density n=6, are attracting considerable attention. Recently, a new iron chain system Ba 2 FeS 3 , also with n=6, was prepared under high-pressure and high-temperature conditions. Here the magnetic and electronic phase diagrams are theoretically studied for this quasi-one-dimensional compound. Based on first-principles calculations, a strongly anisotropic one-dimensional electronic band behavior near the Fermi level was observed. In addition, a three-orbital electronic Hubbard model for this chain was constructed. Introducing the Hubbard and Hund couplings and studying the model via the density matrix renormalization group (DMRG) method, we studied the ground-state phase diagram. A robust staggered ↑-↓-↑-↓ AFM region was unveiled in the chain direction, consistent with our density functional theory (DFT) calculations. Furthermore, at intermediate Hubbard U coupling strengths, this system was found to display an orbital selective Mott phase (OSMP) with one localized orbital and two itinerant metallic orbitals. At very large U/W (W=bandwidth), the system displays Mott insulator characteristics, with two orbitals half-filled and one doubly occupied. Our results for high pressure Ba 2 FeS 3 provide guidance to experimentalists and theorists working on this one-dimensional iron chalcogenide chain material.

1-dimensional systems↗

Phase-Field Modeling of Materials Interfaces and Nanostructures

Nanostructured materials offer unique properties for a wide range of energy applications. Among various known processing methods, liquid metal dealloying (LMD)—the selective dissolution of a base alloy element into a metallic melt—has emerged as a powerful technique to produce a new class of nano-/meso-scale open porous and bicontinuous composite structures with ultra-high interfacial area. LMD has recently been complemented by the advent of vapor phase dealloying (VPD), a novel technique that exploits the selective evaporation of one element from a parent alloy containing elements with very different vapor pressures, thereby enabling to fabricate open nanoporous structures of various elements from less-noble metals to inorganic elements regardless of their chemical activity without requiring high LMD temperatures and chemical etching. Together LMD and VPD have greatly expanded the scope of dealloying techniques, limited by traditional electrochemical means to noble metals, and boosted the design of new functional and structural materials that combine a wide variety of elements. Topologically-connected open porous structures with ultra-high surface area allow mass transport within the structure while preserving structural integrity, enabling them to serve as catalysts, fuel cells, supercapacitors, or high-capacity battery materials. Bicontinuous composite structures in turn can display high strength and high ductility or superior radiation-damage resistance due to the ultra-high interface area between interpenetrating solid phases. This research program makes use of state-of-the-art computational methods to understand at a basic level the self-organizing dealloying process with main focus on dealloying kinetics and interfacial pattern formation at the dealloying front controlling initial structure size, topology, and phase compositions. Phase-field simulation studies of LMD focus on solid solutions, line compounds, and intermetallic systems that can form ternary composites by nucleation and growth of a new phase. Studies of VPD employ phase-field modeling and a hybrid method combining a kinetic Monte Carlo (KMC) model of evaporation and surface diffusion with molecular dynamics for vapor-phase transport inside nanopores. Simulations explore mechanisms of interface- and diffusion-controlled dealloying kinetics, both observed in VPD but not fundamentally understood. In addition, our newly developed multi-physics phase-field approach of large-volume-change phase transformations is being used to model novel 3D anode geometries based on dealloyed nanoporous structures including novel sandwiched graphene/Si/silica for highrate Li ion battery. Those studies are aimed at elucidating geometric design principles that improve mechanical stability. We expect this research to enhance the capability to tailor nano-/mesoscale structures for a wide range of energy-related materials applications and to yield further advances in computational methodologies that benefit a broad materials research community.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

A seamless approach for evaluating climate models across spatial scales

In regions of the world where topography varies significantly with distance, most global climate models (GCMs) have spatial resolutions that are too coarse to accurately simulate key meteorological variables that are influenced by topography, such as clouds, precipitation, and surface temperatures. One approach to tackle this challenge is to run climate models of sufficiently high resolution in those topographically complex regions such as the North American Regionally Refined Model (NARRM) subset of the Department of Energy’s (DOE) Energy Exascale Earth System Model version 2 (E3SM v2). Although high-resolution simulations are expected to provide unprecedented details of atmospheric processes, running models at such high resolutions remains computationally expensive compared to lower-resolution models such as the E3SM Low Resolution (LR). Moreover, because regionally refined and high-resolution GCMs are relatively new, there are a limited number of observational datasets and frameworks available for evaluating climate models with regionally varying spatial resolutions. As such, we developed a new framework to quantify the added value of high spatial resolution in simulating precipitation over the contiguous United States (CONUS). To determine its viability, we applied the framework to two model simulations and an observational dataset. We first remapped all the data into Hierarchical Equal-Area Iso-Latitude Pixelization (HEALPix) pixels. HEALPix offers several mathematical properties that enable seamless evaluation of climate models across different spatial resolutions including its equal-area and partitioning properties. The remapped HEALPix-based data are used to show how the spatial variability of both observed and simulated precipitation changes with resolution increases. This study provides valuable insights into the requirements for achieving accurate simulations of precipitation patterns over the CONUS. It highlights the importance of allocating sufficient computational resources to run climate models at higher temporal and spatial resolutions to capture spatial patterns effectively. Furthermore, the study demonstrates the effectiveness of the HEALPix framework in evaluating precipitation simulations across different spatial resolutions. This framework offers a viable approach for comparing observed and simulated data when dealing with datasets of varying spatial resolutions. By employing this framework, researchers can extend its usage to other climate variables, datasets, and disciplines that require comparing datasets with different spatial resolutions.

54 ENVIRONMENTAL SCIENCES↗

Lambda baryon production in neutrino-nucleus interactions and light signals reconstruction in the Short-Baseline Near Detector

The field of neutrino physics is nowadays entering the era of precision measurements, with new detectors capable of capturing neutrino interactions with unprecedented detail and high intensity neutrino beams. Liquid Argon Time Projection Chambers (LArTPCs) have become one of the main neutrino detection technologies, providing excellent imaging capabilities and particle identification. The Short-Baseline Near Detector (SBND) at Fermilab is a LArTPC experiment designed to capture neutrinos from the Booster Neutrino Beam (BNB). Its proximity to the beam target (110\,m) and large size (112\,ton) enable the recording of millions of neutrino interactions annually. SBND provides the highest statistics worldwide for neutrino-argon cross-section measurements, facilitating the study of rare channels like Cabibbo-suppressed quasielastic hyperon production. Specifically, this thesis focuses on neutral $\Lambda$ baryon production for which only tens of events have been observed up to date. Our work introduces a novel selection strategy leveraging LArTPC imaging capabilities to identify the distinctive decay signatures of $\Lambda$ baryons, enhancing sensitivity to this channel. Besides being a very mature technology, LArTPCs are an evolving technology. Part of the focus of the new developments lies in harnessing the potential of scintillation light signals. The Photon Detection System (PDS) in SBND has been designed to provide an efficient detection of the scintillation light, representing a major R\&D opportunity in the LArTPC community. Its design provides a high and more uniform light yield, an excellent timing resolution and an independent 3D reconstruction of the events, including the drift coordinate, using exclusively the light signals. This work presents the first comprehensive study of the SBND PDS capabilities. The new developments in the simulation and reconstruction of the light signals in SBND are presented. The whole chain is applied to accurately tag neutrino events through timing information, with a predicted resolution $\mathcal{O}$(2\,ns), and ultimately retrieve the pulse structure of the BNB.

43 PARTICLE ACCELERATORS↗

In Situ Neutron Reflectometry Reveals the Interfacial Microenvironment Driving Electrochemical Ammonia Synthesis

Electrified interfaces are critical to the performance of energy systems and often demonstrate substantial complexity under operating conditions. A nanoscale understanding of the interfacial microenvironment, i.e., the solid-electrolyte interphase (SEI), in lithium-mediated nitrogen reduction (Li–N 2 R) is key for realizing efficient ammonia (NH 3 ) production. Herein, we used time-resolved neutron reflectometry (NR) to observe SEI formation under Li–N 2 R conditions. We found that the LiBF 4 -based electrolyte provided a substantially more well-defined SEI layer than previous SEI NR interrogations that used LiClO 4 , highlighting the underlying chemistry that dictates electrolyte design and enabling new NR-based studies. Using in situ NR, we found that the LiBF 4 -derived SEI under Li–N 2 R conditions comprises a thick, diffuse outer layer and a thin, compact inner layer at low current cycling (<2 mA/cm 2 ), revealing a structure which ex situ studies have not been able to probe. Increased current cycling and sustained current cycling led to the merging of the layers into a single-layer SEI. Here, we used isotope contrast methods with d 6 -EtOH and d 8 -THF to drive time-resolved tracking of SEI growth at low current cycling, revealing that the proton donor modifies the inner layer, and the solvent modifies the outer layer. Li dendritic growth was observed in the absence of a proton donor. Neutron absorption also indicated the presence of boron in the SEI, underscoring the value of neutron-based interrogation. Our results inform Li-based systems and reaction microenvironments, and these methods can be applied broadly to interfacial energy technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Studying Open Quantum Systems Relevant to Chemistry on a Trapped-Ion Quantum Simulator (Final Technical Report)

This project advances the trapped-ion quantum simulator as a versatile platform for studying open quantum system phenomena. We aim to contribute to the emerging quantum simulation toolkits and enable simulation of nanoscale energy processes. Trapped-ion platforms offer unique capabilities: their vibrational motion can be precisely manipulated, measured, and coherently coupled to auxiliary qubits. The vibrational mode can function both as a highly sensitive quantum sensor and a programmable environment bath. Using this platform, we achieved three major outcomes. First, we demonstrated using the vibrational mode as an ultrasensitive probe for testing fundamental physics, including possible nonlinear quantum mechanics effects. Second, we established that these modes can act as controllable baths in which tunable noise and loss can enhance or modify energy-transfer dynamics, providing the experimental preparation toward studying mechanisms relevant to chemical reactions and light-harvesting systems. Third, by introducing controllable nonlinear gain and loss, we showed theoretically how simulations using trapped ions can model vibrationally-assisted energy transport in a non‐Hermitian quantum system comprising a chromophore dimer weakly coupled to a vibrational mode. Exploring the non‐Hermitian dynamics of the whole system including vibrations, we found that energy transfer accompanied by absorption of phonons from a vibrational mode can be significantly enhanced near an exceptional point. This theoretical work on simulation of energy transfer processes in driven non‐Hermitian quantum systems revealed an interesting novel path to study open quantum systems dynamics under conditions of gain and loss. We then further explored the benefits of controllable gain and loss with an experimental realization of quantum analogs of nonlinear oscillators, namely, the van der Pol oscillator. Here we observed mutual synchronization mediated by collective dissipation between two oscillators. In parallel, we explored related quantum networking protocols using the same trapped-ion platform, developing fast, high-fidelity schemes for distributing entanglement. Together, these achievements show that trapped-ion vibrational modes provide a highly programmable and high-fidelity platform for investigating complex dissipative quantum behavior, while enabling new approaches to remote quantum sensing, energy science, and nonlinear quantum dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Bifurcation of equilibrium positions for ellipsoidal particles in inertial shear flows between two walls

We conducted a systematic numerical investigation of spherical, prolate and oblate particles in an inertial shear flow between two parallel walls, using smoothed particle hydrodynamics (SPH). It was previously shown that above a critical Reynolds number, spherical particles experience a supercritical pitchfork bifurcation of the equilibrium position in shear flow between two parallel walls, namely that the central equilibrium position becomes unstable, leading to the emergence of two new off-centre stable positions (Foxet al.,J. Fluid Mech., vol. 915, 2021). This phenomenon was unexpected given the symmetry of the system. In addition to confirming this finding, we found, surprisingly, that ellipsoidal particles can also return to the centre position from the off-centre positions when the particle Reynolds number is further increased, while spherical particles become unstable under this increased Reynolds number. By utilizing both SPH and the finite element method for flow visualization, we explained the underlining mechanism of this reverse of bifurcation by altered streamwise vorticity and symmetry breaking of pressure. Furthermore, we expanded our investigation to include asymmetric particles, a novel aspect that had not been previously modelled, and we observed similar trends in particle dynamics for both symmetric and asymmetric ellipsoidal particles. While further validation through laboratory experiments is necessary, our research paves the road for development of new focusing and separation methods for shaped particles.

Mechanics↗

Closure of Earth’s Global Seasonal Cycle of Energy Storage

Abstract The global seasonal cycle of energy in Earth’s climate system is quantified using observations and reanalyses. After removing long-term trends, net energy entering and exiting the climate system at the top of the atmosphere (TOA) should agree with the sum of energy entering and exiting the ocean, atmosphere, land, and ice over the course of an average year. Achieving such a balanced budget with observations has been challenging. Disagreements have been attributed previously to sparse observations in the high-latitude oceans. However, limiting the local vertical integration of new global ocean heat content estimates to the depth to which seasonal heat energy is stored, rather than integrating to 2000 m everywhere as done previously, allows closure of the global seasonal energy budget within statistical uncertainties. The seasonal cycle of energy storage is largest in the ocean, peaking in April because ocean area is largest in the Southern Hemisphere and the ocean’s thermal inertia causes a lag with respect to the austral summer solstice. Seasonal cycles in energy storage in the atmosphere and land are smaller, but peak in July and September, respectively, because there is more land in the Northern Hemisphere, and the land has more thermal inertia than the atmosphere. Global seasonal energy storage by ice is small, so the atmosphere and land partially offset ocean energy storage in the global integral, with their sum matching time-integrated net global TOA energy fluxes over the seasonal cycle within uncertainties, and both peaking in April.

54 ENVIRONMENTAL SCIENCES↗

Learning generative neural networks with physics knowledge

Deep generative neural networks have enabled modeling complex distributions, but incorporating physics knowledge into the neural networks is still challenging and is at the core of current physics-based machine learning research. To this end, we propose a physics generative neural network (PhysGNN), a new class of generative neural networks for learning unknown distributions in a physical system described by partial differential equations (PDE). PhysGNN couples PDE systems with generative neural networks. It is a fully differentiable model that allows back-propagation of gradients through both numerical PDE solvers and generative neural networks, and is trained by minimizing the discrete Wasserstein distance between generated and observed probability distributions of the PDE outputs using the stochastic gradient descent method. Moreover, PhysGNN does not require adversarial training like standard generative neural networks, which offers better stability than adversarial training. We show that PhysGNN can learn complex distributions in stochastic inverse problems, where conventional methods such as maximum likelihood estimation and momentum matching methods may be inapplicable when little knowledge is known about the form of unknown distributions or the physical model is too complex. Furthermore, our method allows physics-based generative neural network training for learning complex distributions in the context of differential equations.

97 MATHEMATICS AND COMPUTING↗