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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Correlating Power Outage Spread with Infrastructure Interdependencies During Hurricanes

Power outages caused by extreme weather events, such as hurricanes, can significantly disrupt essential services and delay recovery efforts, underscoring the importance of enhancing our infrastructure's resilience. This study investigates the spread of power outages during hurricanes by analyzing the correlation between the network of critical infrastructure and outage propagation. We leveraged datasets from Hurricanemapping.com, the North American Energy Resilience Model Interdependency Analysis (NAERM-IA), and historical power outage data from the Oak Ridge National Laboratory (ORNL)'s EAGLE-I system. Our analysis reveals a consistent positive correlation between the extent of critical infrastructure components accessible within a certain number of steps (k-hop distance) from initial impact areas and the occurrence of power outages in broader regions. This insight suggests that understanding the interconnectedness among critical infrastructure elements is key to identifying areas indirectly affected by extreme weather events.

Bose, Avishek↗
DOE OSTI2023

Influences of Cloud Microphysics on the Components of Solar Irradiance in the WRF-Solar Model

An accurate forecast of Global Horizontal solar Irradiance (GHI) and Direct Normal Irradiance (DNI) in cloudy conditions remains a major challenge in the solar energy industry. This study focuses on the impact of cloud microphysics on GHI and its partition into DNI and Diffuse Horizontal Irradiance (DHI) using the Weather Research and Forecasting model specifically designed for solar radiation applications (WRF-Solar) and seven microphysical schemes. Three stratocumulus (Sc) and five shallow cumulus (Cu) cases are simulated and evaluated against measurements at the US Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility, Southern Great Plains (SGP) site. Results show that different microphysical schemes lead to spreads in simulated solar irradiance components up to 75% and 350% from their ensemble means in the Cu and Sc cases, respectively. The Cu cases have smaller microphysical sensitivity due to a limited cloud fraction and smaller domain-averaged cloud water mixing ratio compared to Sc cases. Cloud properties also influence the partition of GHI into DNI and DHI, and the model simulates better GHI than DNI and DHI due to a non-physical error compensation between DNI and DHI. The microphysical schemes that produce more accurate liquid water paths and effective radii of cloud droplets have a better overall performance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Non-ideal stoichiometry and thermochemistry of aqueous iridium oxide nanoparticles in proton-coupled electron transfer and oxygen-atom transfer

Reported here are reactions of aqueous colloidal IrO x nanoparticles (NPs) with proton-coupled electron transfer (PCET) and oxygen-atom transfer (OAT) organic reagents, determining the reaction stoichiometries and thermochemistry. IrO x NPs have attracted much attention for their high electrocatalytic activity, but understanding of their fundamental reaction chemistry is limited. This IrO x NP model system is simple, with UV-vis titrations demonstrating reversible interconversion between predominantly Ir IV and predominantly Ir III NPs. This simplicity allows studies that reveal their complex non-idealities. The NP redox chemistry has a “super-Nernstian” stoichiometry of ∼1.3H + per 1e − transferred during both PCET and OAT reactions, as measured with electrochemistry and chemical methods. Spectroelectrochemistry revealed a broad distribution of surface IrO x –H bond dissociation free energies (BDFEs), becoming weaker as more H is added. Such variation in binding strengths—a non-ideal binding isotherm—is common for surface adsorbates. For IrO x , the variation of BDFE(IrO–H)s is fit well to a Frumkin isotherm with a width of 6.5 kcal mol −1 . For OAT from the reactive oxygen atoms of IrO x NPs, bracketing experiments gave 93 ± 24 kcal mol −1 for the average BDFE(O x Ir–O), with a predicted spread much larger than that for the BDFE(IrO–H). Taken together, the results show the importance of non-ideal stoichiometry and thermochemistry for IrO x NPs, and they open a path to more complete models to understand catalytic redox reactions at such surfaces.

Iridium Oxide Nanoparticles (NPs)↗
DOE OSTI2021

Transient disease dynamics across ecological scales

Analyses of transient dynamics are critical to understanding infectious disease transmission and persistence. Identifying and predicting transients across scales, from within-host to community-level patterns, plays an important role in combating ongoing epidemics and mitigating the risk of future outbreaks. Moreover, greater emphases on non-asymptotic processes will enable timely evaluations of wildlife and human diseases and lead to improved surveillance efforts, preventive responses, and intervention strategies. Here, we explore the contributions of transient analyses in recent models spanning the fields of epidemiology, movement ecology, and parasitology. In addition to their roles in predicting epidemic patterns and endemic outbreaks, we explore transients in the contexts of pathogen transmission, resistance, and avoidance at various scales of the ecological hierarchy. Examples illustrate how (i) transient movement dynamics at the individual host level can modify opportunities for transmission events over time; (ii) within-host energetic processes often lead to transient dynamics in immunity, pathogen load, and transmission potential; (iii) transient connectivity between discrete populations in response to environmental factors and outbreak dynamics can affect disease spread across spatial networks; and (iv) increasing species richness in a community can provide transient protection to individuals against infection. Ultimately, we suggest that transient analyses offer deeper insights and raise new, interdisciplinary questions for disease research, consequently broadening the applications of dynamical models for outbreak preparedness and management.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Differential contagiousness of respiratory disease across the United States

The initial contagiousness of a communicable disease within a given population is quantified by the basic reproduction number, $R_0$. This number depends on both pathogen and population properties. On the basis of compartmental models that reproduce Coronavirus Disease 2019 (COVID-19) surveillance data, we used Bayesian inference and the next-generation matrix approach to estimate region-specific $R_0$ values for 280 of 384 metropolitan statistical areas (MSAs) in the United States (US), which account for 95% of the US population living in urban areas and 82% of the total population. We focused on MSA populations after finding that these populations were more uniformly impacted by COVID-19 than state populations. Our maximum a posteriori (MAP) estimates for $R_0$ range from 1.9 to 7.7 and quantify the relative susceptibilities of regional populations to spread of respiratory diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Effective dissipation rate in a Liouvillian-graph picture of high-temperature quantum hydrodynamics

At high temperature, generic strongly interacting spin systems are expected to display hydrodynamics: local transport of conserved quantities, governed by classical partial differential equations like the diffusion equation. I argue that the emergence of this dissipative long-wavelength dynamics from the system's unitary microscopic dynamics is controlled by the structure of the Liouvillian graph of the system's Hamiltonian, that is, the graph induced on Pauli strings by commutation with that Hamiltonian. The Liouvillian graph decomposes naturally into subgraphs of Pauli strings of constant diameter, and the coherent dynamics of these subgraphs determines the rate at which operator weight spreads to long operators. In conclusion, this argument provides a quantitative theory of the emergence of a dissipative effective dynamics from unitary microscopic dynamics; it also leads to an effective model with Hilbert space dimension linear in system size and exponential in the UV cutoff for diffusion.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Improving probabilistic infectious disease forecasting through coherence

With an estimated $10.4 billion in medical costs and 31.4 million outpatient visits each year, influenza poses a serious burden of disease in the United States. To provide insights and advance warning into the spread of influenza, the U.S. Centers for Disease Control and Prevention (CDC) runs a challenge for forecasting weighted influenza-like illness (wILI) at the national and regional level. Many models produce independent forecasts for each geographical unit, ignoring the constraint that the national wILI is a weighted sum of regional wILI, where the weights correspond to the population size of the region. We propose a novel algorithm that transforms a set of independent forecast distributions to obey this constraint, which we refer to as probabilistically coherent. Enforcing probabilistic coherence led to an increase in forecast skill for 79% of the models we tested over multiple flu seasons, highlighting the importance of respecting the forecasting system’s geographical hierarchy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties With Deep Learning Multi‐Member and Stochastic Parameterizations

Abstract Deep learning is a powerful tool to represent subgrid processes in climate models, but many application cases have so far used idealized settings and deterministic approaches. Here, we develop stochastic parameterizations with calibrated uncertainty quantification to learn subgrid convective and turbulent processes and surface radiative fluxes of a superparameterization embedded in an Earth System Model (ESM). We explore three methods to construct stochastic parameterizations: (a) a single Deep Neural Network (DNN) with Monte Carlo Dropout; (b) a multi‐member parameterization; and (c) a Variational Encoder Decoder with latent space perturbation. We show that the multi‐member parameterization improves the representation of convective processes, especially in the planetary boundary layer, compared to individual DNNs. The respective uncertainty quantification illustrates that methods (b) and (c) are advantageous compared to a dropout‐based DNN parameterization regarding the spread of convective processes. Hybrid simulations with our best‐performing multi‐member parameterizations remained challenging and crash within the first days. Therefore, we develop a pragmatic partial coupling strategy relying on the superparameterization for condensate emulation. Partial coupling reduces the computational efficiency of hybrid Earth‐like simulations but enables model stability over 5 months with our multi‐member parameterizations. However, our hybrid simulations exhibit biases in thermodynamic fields and differences in precipitation patterns. Despite this, the multi‐member parameterizations enable improvements in reproducing tropical extreme precipitation compared to a traditional convection parameterization. Despite these challenges, our results indicate the potential of a new generation of multi‐member machine learning parameterizations leveraging uncertainty quantification to improve the representation of stochasticity of subgrid effects.

Behrens, Gunnar [Deutsches Zentrum für Luft‐ und R↗
DOE OSTI2025

Sensitivities of Large Eddy Simulations of Aerosol Plume Transport and Cloud Response

Abstract Cloud responses to surface‐based sources of aerosol perturbation partially depend on how turbulent transport of the aerosol to cloud base affects the spatial and temporal distribution of aerosol. Here, scenarios of plume injection below a marine stratocumulus cloud are modeled using large eddy simulations coupled to a prognostic bulk aerosol and cloud microphysics scheme. Both passive plumes, consisting of an inert tracer, and active plumes are investigated, where the latter are representative of saltwater droplet plumes such as have been proposed for marine cloud brightening. Passive plume scenarios show higher in‐plume cloud brightness (relative to out‐of‐plume) due to the predominant transport of the passive plume tracer from the near‐surface to the cloud layer within updrafts. These updrafts rise into brighter areas within the cloud deck, even in the absence of an aerosol perturbation associated with an active plume. Comparing albedo at in‐plume to out‐of‐plume locations associates the inert plume with the brightest cloud locations, without any causal effect of the plume on the cloud. Numerical sensitivities are first assessed to establish a suitable model configuration. Then sensitivity to particle injection rate is investigated. Trade‐offs are identified between the number of injected particles and the suppressive effect of droplet evaporation on plume loft and spread. Furthermore, as the near‐field in‐plume brightening effect does not depend significantly on injection rate given a suitable definition of perturbed versus unperturbed regions of the flow, plume area is a key controlling factor on the overall cloud brightening effect of an aerosol perturbation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Higgs boson width and couplings at high energy muon colliders with forward muon detection

We propose a novel method using the ZZ-fusion channel and forward muon detection at high energy muon colliders to address the challenge of the Higgs coupling-width degeneracy. Our approach enables inclusive Higgs rate measurement to 0.75% at 10 TeV muon collider, breaking the coupling-width degeneracy. Results indicate the potential to refine Higgs coupling to subpercent levels and estimate its total width within (–0.41%, +2.1%). Key insights include the effectiveness of forward muon tagging in signal-background separation despite broad recoil mass distribution due to muon energy reconstruction and beam energy spread. The study emphasizes the significance of muon rapidity coverage up to |η⁡(μ)| < 6, enhancing measurement precision. Our findings highlight the unique capabilities of high energy lepton colliders for model-independent Higgs coupling determination and lay the groundwork for future advancements in muon collider technology and Higgs physics research.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Transition from susceptible-infected to susceptible-infected-recovered dynamics in a susceptible-cleric-zombie-recovered active matter model

The susceptible-infected (SI) and susceptible-infected-recovered (SIR) models provide two distinct representations of epidemic evolution, distinguished by whether or not the number of susceptibles always drops to zero at long times. Here, in this study, we introduce a new active matter epidemic model, the “susceptible-cleric-zombie-recovered” (SCZR) model, in which spontaneous recovery is absent but zombies can recover with probability γ via interaction with a cleric. Upon colliding with a zombie, both susceptibles and clerics enter the zombie state with probability β and α, respectively. By changing the initial fraction of clerics or their healing ability rate γ, we can tune the SCZR model between SI dynamics, in which no susceptibles or clerics remain at long times, and SIR dynamics, in which a finite number of clerics and susceptibles survive at long times. The model is relevant to certain real world diseases such as HIV where spontaneous recovery is impossible but where medical interventions by a limited number of caregivers can reduce or eliminate the spread of infection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Nanoporous weakly coordinating anionic frameworks (Final Technical Report)

Under this award, we synthesized and characterized new weakly coordinating, anionic covalent organic frameworks. The motivation was to expand the class of covalent organic frameworks though the introduction of the first weakly coordinating anionic ones. The significance of the weakly coordinating anionic character of these frameworks is associated with the character of the counter (metal) cations in their pores. Those counter-cations, due to the inability to effectively coordinate to the pore walls, have a “naked”, and thus highly electrophilic, Lewis acidic character. Such properties are expected to translate to a number of interesting physical properties that can be potentially used for a range of energy-relevant applications. One of these applications is gas adsorption, separation, and storage. The electrophilic, Lewis acidic character of the counter-cations are expected to strongly bind to gas molecules entering the pores leading to higher gas sorption capacities. Other applications include heterogeneous catalysis, ion exchange, and solid state ion conduction. Within the project we explored a range of chemical blocks, and tested synthesis conditions to polymerize these building blocks to form the target materials. In particular, we focused on materials with group 15 elements like phosphorus in the oxidation state +5 and the coordination number 6, that have a formal -1 charge. The synthesis of such materials is challenging because its success depends on the absence of residual monomeric and oligomeric side-products in the pores, and the absence of significant framework interpenetration. Crystalline forms of these materials require sufficient reversibility of the polymerization reaction (which is difficult to achieve because group 15 elements like P tend to make strong covalent bonds with neighbored elements), as well as suitable polymerization rates that prevent the formation of kinetically controlled products. We had success with the preparation of anionic porous organic frameworks with anionic building blocks containing P(V)O6 octahedra synthesized through Yamamoto coupling reactions. These materials are non-crystalline because of the irreversible nature of the Yamamoto coupling reaction, but show porosity. The porosity and surface area can be significantly increased by co-reaction with electrostatically neutral co-reactants. Very high porosity and surface areas can be achieved when the materials are washed with hydrochloric acid. This method is commonly used to free products from Yamamoto coupling reactions from by-products. Indeed, this method removed by products from the pores of our materials, however it also led to the hydrolysis of the PO6 octahedra to form pending phosphonic acid groups (-PO3H)-groups in the frameworks (PA-POFs) which was actually not desired. Nonetheless, these materials showed high CO2 sorption capacities. In addition, they show extremely high (actually record) sorption capacities for the removal of a range of common micropollutants such as bisphenol A (BPA) and 4-nitrophenol in water. BPA is a wide-spread organic pollutant and a known endocrine disruptor. The maximum adsorption capacity of BPA at equilibrium is found to be as high as 3,366 mg g-1 by Langmuir adsorption model, which is more than 10 times greater than peer materials. The polymer also rapidly removes various other organic micropollutants with more than 90% removal efficiencies. In addition, the PA-POF material can be regenerated at least five times by mild washing using methanol without significant loss in removal efficiency. This is significant advantage over commonly used activated carbon materials (that are in Brita water faucet filters, for example). Comparison studies showed that only materials with the phosphonate groups show extreme sorption although the number of PA group is actually small according to solid state NMR and EDX data. More research would be needed to investigate why this is (a possibility is that the phosphonate groups have a multiplying effect in which a PA-induced initial adsorption leads to the adsorption of much more adsorbate). The extreme sorption capabilities can also be visually seen when colored adsorbates such as 4-nitrophenol are used, as the adsorption of the nitrobenzene leads to the decoloration of the solution. We have produced three short videos that illustrate the sorption capabilities compared to two peer materials (activated carbon from dismantled Brita water filters, and a electrostatically neutral, chemically related, porous organic polymer, respectively).

36 MATERIALS SCIENCE↗
DOE OSTI2024

Reducing uncertainty of polar to midlatitude linkages using DOE’s E3SM in a coordinated model-experiment setting

This project brought DOE’s climate modeling effort with the Energy Exascale Earth System Model into the Polar Amplification Model Intercomparison Project (PAMIP), which is part of the sixth and latest Coupled Model Intercomparison Project, CMIP6. PAMIP examines the causes and consequences of polar amplification, when external forcing results in a larger temperature increase in high latitudes than the global average, in a coordinated set of model experiments with a common modeling protocol. Our teams from UC Irvine and the University of Toronto have designed, carried out, analyzed, and disseminated PAMIP output from the Energy Exascale Earth System Model (E3SM) and the Community Earth System Model (CESM). PAMIP’s ongoing stream of significant new results have advanced progress in the community’s understanding and led to new outstanding research questions that have motivated further work. PAMIP has led to improved consensus on the atmospheric response to sea ice loss. The important finding is that for a similar sea ice anomaly forcing, the simulated atmospheric response in the troposphere is remarkably consistent among the 16 models’ runs analyzed. The zonal-mean tropospheric response consists of a very robust equatorward shift of the westerly flow in mid-latitudes. However, while the multi-model mean response is robust, it has a weak amplitude relative to internal variability. We identified a weakness in the models (including E3SM) in terms of their response to sea-ice forcing that is related to eddy forcing (or nonlinear dynamical effects) at mid- to high latitudes. In fact, E3SM is an outlier in terms of the models participating, and in that sense, it turned out to be a vital participant model. We found that reductions in energy transport due sea-ice loss and involving dry air only are compensated by increases in moist energy transport from warmer sea surface temperature in midlatitudes. This leads to a large spread in energy transport into the Arctic and is a potential source of spread in Arctic amplification. We identified an important role that climate modes, including tropical modes of variability (El Nino and the Southern Oscillation (ENSO); the Quasi-biennial Oscillation (QBO)) play in the response to sea-ice anomalies, including in ocean coupled experiments. Similarly, we identified and quantified the contribution of sea-ice thickness to the atmospheric response compared to the response to sea-ice extent only. We found that it is important to run large ensembles and even with an ensemble size of 100 simulations the response is largely influenced by internal variability. We demonstrated convincingly that Ural blocking, not sea-ice loss, provides the weakening of the stratospheric polar vortex in fall/early winter and a negative phase of the North Atlantic Oscillation that can last for up to two months. However, sea-ice anomalies can influence the background flow so that the response to Ural blocking is more persistent under low sea-ice conditions in the Barents/Kara Sea than high sea ice Atmospheric model hierarchies that progressively add individual processes have a long history in providing dynamical insight for modeling the atmosphere. Similarly, coupled model hierarchies that progressively add individual ocean processes can provide insights into the workings of the coupled climate system, however such hierarchies have not been available except for a non-dynamical slab ocean model. Because of the missing processes, surface flux corrections must be added to produce a target climate. In this project, we managed to overcome this problem and develop a globally coupled ocean model hierarchy in CESM that can turn on and off the processes of mixed-layer entrainment and Ekman flow. We used the hierarchy to study the impact of Arctic sea-ice loss on the climate system. We find that the effect of mixed-layer entrainment on ocean heat uptake influences the atmospheric circulation by shifting the latitudinal positions of the mid-latitude westerly jet and the Intertropical Convergence Zone (ITCZ). In quadrupled CO 2 experiments, we studied how air-sea coupling affects the response of tropical rainfall under global warming. In order to identify the importance of individual ocean processes, we used the hierarchy of ocean models to separate the effects of seasonal mixed-layer entrainment, wind-driven Ekman flows, and frictional flows. We showed that including Ekman and frictional flows allows our simulation to produce the Pacific Ocean's enhanced equatorial warming pattern and equatorward ITCZ contraction noted in previous climate simulations. We also showed that the frictional flow, which has yet to receive much attention, is as important as the Ekman flow in generating equatorial heat convergence.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Blanco DECam Bulge Survey (BDBS) II: project performance, data analysis, and early science results

ABSTRACT The Blanco DECam Bulge Survey (BDBS) imaged more than 200 sq deg of the Southern Galactic bulge using the ugrizY filters of the Dark Energy Camera, and produced point spread function photometry of approximately 250 million unique sources. In this paper, we present details regarding the construction and collation of survey catalogues, and also discuss the adopted calibration and dereddening procedures. Early science results are presented with a particular emphasis on the bulge metallicity distribution function and globular clusters. A key result is the strong correlation (σ ∼ 0.2 dex) between (u − i)o and [Fe/H] for bulge red clump giants. We utilized this relation to find that interior bulge fields may be well described by simple closed box enrichment models, but fields exterior to b ∼ −6° seem to require a secondary metal-poor component. Applying scaled versions of the closed box model to the outer bulge fields is shown to significantly reduce the strengths of any additional metal-poor components when compared to Gaussian mixture models. Additional results include: a confirmation that the u band splits the subgiant branch in M22 as a function of metallicity, the detection of possible extratidal stars along the orbits of M 22 and FSR 1758, and additional evidence that NGC 6569 may have a small but discrete He spread, as evidenced by red clump luminosity variations in the reddest bands. We do not confirm previous claims that FSR 1758 is part of a larger extended structure.

Johnson, Christian I.↗
DOE OSTI2021

Aerodynamic effects on outer ash deposition rates in second generation atmospheric pressure oxy-coal combustion systems

Recent measurements in scenarios representative of second generation atmospheric pressure oxy-coal combustion systems have shown a significant increase in ash deposition rates in comparison to combustion in air. However, the causative mechanisms behind this increase have not been well understood. To fill this void, well-characterized experiments including fuel and deposit particle size distributions (PSDs) were coupled with highly resolved numerical simulations to isolate the aerodynamic effects impacting the deposition process such that mechanisms could be hypothesized. Three combustion scenarios (AIR, OXY27, OXY70) spanning a factor of three variation in flue gas volumetric flow rates were simulated and the deposition characteristics (impaction rates, deposit PSD, temperature, residence times, capture rates) tracked/predicted using a customized deposition module. The measured deposit PSD was significantly different from the PSD of the parent fuel indicating significant physio-chemical transformations (coalescence and particle growth in particular) at play. The use of simplistic modeling approaches (swelling parameter variations) to model particle growth led to inaccurate deposit ash PSD and rate predictions. A more satisfactory agreement between the measurements and simulations was obtained when the functional form of the parent fuel PSD (spread parameter) was modified to conform closely to the deposit PSD while still ensuring the fidelity of temperature and velocity predictions. Based on the measured ash compositions, identical capture criteria were employed across all three scenarios. Here this study further supports the theory that the ash deposition rates in these systems are dominated by aerodynamic effects with the ash PSD playing a dominant role.

42 ENGINEERING↗
DOE OSTI2026

A Panspermia Origin for Venus Cloud Life

Decades of study have hinted at the astrobiological potential of Venus's cloud layers. This potential is often cast as stemming from the idea that the Venusian surface was clement in the past. As the climate changed, life then remained in, or perhaps evolved and migrated to, the last habitable niche: the altitudes above ∼50 km with Earth-like temperatures and pressures today. Here we explore an alternative scenario where life was delivered to Venus' clouds from Earth or Mars (“panspermia”). This process requires a life-containing bolide to enter the atmosphere, without experiencing complete sterilization, and then be dispersed at high altitude in fragments small enough to dwell in the clouds. We adapt a widely used model of bolide-atmosphere interaction to investigate the fate of bolides delivered to Venus from Earth and Mars. Starting at the top of the atmosphere, bolides ablate and fragment. Aerodynamic drag spreads these fragments horizontally, forming a “pancake” with an increased effective cross-section, causing rapid deceleration. An airburst occurs when the bolide deposits its highest amount of kinetic energy in the atmosphere. Observations of terrestrial meteorites provide a scaling law for the distribution of post-airburst fragment sizes. Inspired by the “Venus Life Equation,” we present a framework for calculating the rate at which panspermia delivers microbial life to the clouds of Venus. Our best estimate is an average of ∼100 cells dispersed in the clouds per Earth-year. Whether this life can survive and thrive in its new home remains an open question.

Guinan, Emma [Arizona State Univ., Tempe, AZ (Unit↗
DOE OSTI2020

Entanglement Hamiltonian of Many-Body Dynamics in Strongly Correlated Systems

A powerful perspective in understanding nonequilibrium quantum dynamics is through the time evolution of its entanglement content. Yet apart from a few guiding principles for the entanglement entropy,to date, much less is known about the refined characteristics of entanglement propagation. In this paper we unveil signatures of the entanglement evolving and information propagating out of equilibrium, from the view of the entanglement Hamiltonian. We investigate quantum quench dynamics of prototypical Bose-Hubbard model using state-of-the-art numerical technique combined with conformal field theory. Before reaching equilibrium, it is found that a current operator emerges in the entanglement Hamiltonian, implying that entanglement spreading is carried by particle flow. In the long-time limit the subsystem enters a steady phase, evidenced by the dynamic convergence of the entanglement Hamiltonian to the expectation of a thermal ensemble. Importantly, the entanglement temperature in steady state is spatially independent,which provides an intuitive trait of equilibrium. These findings not only provide crucial information on how equilibrium statistical mechanics emerges in many-body dynamics, but also add a tool to exploring quantum dynamics from the perspective of the entanglement Hamiltonian.

36 MATERIALS SCIENCE↗