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At least 1,099 records · Page 61

The impact of cold electrons and cold ions in magnetospheric physics

A review of the impact of the cold-ion and cold-electron populations in the Earth’s magnetosphere is presented in this paper. The cold populations are defined by total energy less than approximately 100 eV, i.e. in the energy range which is strongly affected by spacecraft charging and that often dominates the total plasma density. We also include the warm plasma cloak in the review, since it overlaps partially with the cold energy range and is a population that is still not well understood. The known impacts of cold ions and cold electrons that are discussed are: the source of magnetospheric plasma, solar-wind/magnetosphere coupling, magnetotail reconnection and substorms, Kelvin-Helmholtz instabilities at the magnetopause, chorus, hiss, electromagnetic-ion-cyclotron and ultra-low-frequency wave-particle interactions, aurora structuring and spacecraft charging. Other possible impacts are associated with refilling on open-drift trajectories, the remnant layer and plasmapause disruption. A discussion of the difficulty of cold-plasma measurements and the need for new measurement techniques that measure the full cold-ion and cold-electron distribution functions is also presented. There remain a lot of unknowns about the cold-ion and cold-electron populations, associated with their origin, properties, drivers and impacts. These populations will need to be fully understood before the magnetosphere-ionosphere system can be fully understood.

79 ASTRONOMY AND ASTROPHYSICS↗

Structure of a monomeric photosystem II core complex from a cyanobacterium acclimated to far-red light reveals the functions of chlorophylls $d$ and $f$

Far-red light (FRL) photoacclimation (FaRLiP) in cyanobacteria provides a selective growth advantage for some terrestrial cyanobacteria by expanding the range of photosynthetically active radiation to include far-red/near-infrared light (700 to 800 nm). During this photoacclimation process, photosystem II (PSII), the water:plastoquinone photooxidoreductase involved in oxygenic photosynthesis, is modified. The resulting FRL-PSII is comprised of FRL-specific core subunits and binds chlorophyll (Chl) d and Chl f molecules in place of several of the Chl a molecules found when cells are grown in visible light. These new Chls effectively lower the energy canonically thought to define the “red limit” for light required to drive photochemical catalysis of water oxidation. Changes to the architecture of FRL-PSII were previously unknown, and the positions of Chl d and Chl f molecules had only been proposed from indirect evidence. Here, we describe the 2.25-Å resolution cryo-EM structure of a monomeric FRL-PSII core complex from Synechococcus sp. PCC 7335 cells that were acclimated to FRL. We identify one Chl d molecule in the Chl D1 position of the electron transfer chain, and four Chl f molecules in the core antenna. We also make observations that enhance our understanding of PSII biogenesis, especially on the acceptor side of the complex where a bicarbonate molecule is replaced by a glutamate sidechain in the absence of the assembly factor Psb28. In conclusion, these results provide a structural basis for the lower energy limit required to drive water oxidation, which is the gateway for most solar energy utilization on Earth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identification of structural transitions in bacterial fatty acid binding proteins that permit ligand entry and exit at membranes

Fatty acid (FA) transfer proteins extract FA from membranes and sequester them to facilitate their movement through the cytosol. Detailed structural information is available for these soluble protein–FA complexes, but the structure of the protein conformation responsible for FA exchange at the membrane is unknown. Staphylococcus aureus FakB1 is a prototypical bacterial FA transfer protein that binds palmitate within a narrow, buried tunnel. Here, we define the conformational change from a “closed” FakB1 state to an “open” state that associates with the membrane and provides a path for entry and egress of the FA. Using NMR spectroscopy, we identified a conformationally flexible dynamic region in FakB1, and X-ray crystallography of FakB1 mutants captured the conformation of the open state. In addition, molecular dynamics simulations show that the new amphipathic α-helix formed in the open state inserts below the phosphate plane of the bilayer to create a diffusion channel for the hydrophobic FA tail to access the hydrocarbon core and place the carboxyl group at the phosphate layer. The membrane binding and catalytic properties of site-directed mutants were consistent with the proposed membrane docked structure predicted by our molecular dynamics simulations. Finally, the structure of the bilayer-associated conformation of FakB1 has local similarities with mammalian FA binding proteins and provides a conceptual framework for how these proteins interact with the membrane to create a diffusion channel from the FA location in the bilayer to the protein interior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fission yeast Duf89 and Duf8901 are cobalt/nickel-dependent phosphatase–pyrophosphatases that act via a covalent aspartyl–phosphate intermediate

Domain of Unknown Function 89 (DUF89) proteins are metal-dependent phosphohydrolases. Exemplary DUF89 enzymes differ in their metal and phosphosubstrate preferences. Here, we interrogated the activities and structures of two DUF89 paralogs from fission yeast—Duf89 and Duf8901. We find that Duf89 and Duf8901 are cobalt/nickel-dependent phosphohydrolases adept at hydrolyzing p-nitrophenylphosphate and PP i . Crystal structures of metal-free Duf89 and Co 2+ -bound Duf8901 disclosed two enzyme conformations that differed with respect to the position of a three-helix module, which is either oriented away from the active site in Duf89 or forms a lid over the active site in Duf8901. Lid closure results in a 16 Å movement of Duf8901 Asp195, vis-à-vis Asp199 in Duf89, that brings Asp195 into contact with an octahedrally coordinated cobalt. Reaction of Duf8901 with BeCl 2 and NaF in the presence of divalent cations Co 2+ , Ni 2+ , or Zn 2+ generated covalent Duf8901-(Asp248)–beryllium trifluoride (BeF 3 )•Co 2+ , Duf8901-(Asp248)–BeF 3 •Ni 2+ , or Duf8901-(Asp248)–BeF 3 •Zn 2+ adducts, the structures of which suggest a two-step catalytic mechanism via formation and hydrolysis of an enzyme-(aspartyl)–phosphate intermediate. Alanine mutations of Duf8901 Asp248, Asn249, Lys401, Asp286, and Asp195 that interact with BeF 3 •Co 2+ squelched p-nitrophenylphosphatase activity. A 1.8 Å structure of a Duf8901-(Asp248)–AlF 4 –OH 2 •Co 2+ transition-state mimetic suggests an associative mechanism in which Asp195 and Asp363 orient and activate the water nucleophile. Whereas deletion of the duf89 gene elicited a phenotype in which expression of phosphate homeostasis gene pho1 was derepressed, deleting duf8901 did not, thereby hinting that the DUF89 paralogs have distinct functional repertoires in vivo.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Zinc dynamics regulate early ovarian follicle development

Zinc fluctuations regulate key steps in late oocyte and pre-implantation embryo development; however, roles for zinc in preceding stages in early ovarian follicle development, when cooperative interactions exist between the oocyte and somatic cells, are unknown. To understand the roles of zinc during early follicle development, we applied single cell X-ray fluorescence microscopy, a radioactive zinc tracer, and a labile zinc probe to measure zinc in individual mouse oocytes and associated somatic cells within early follicles. Here, we report a significant stage-specific increase and compartmental redistribution in oocyte zinc content upon the initiation of early follicle growth. The increase in zinc correlates with the increased expression of specific zinc transporters, including two that are essential in oocyte maturation. While oocytes in follicles exhibit high tolerance to pronounced changes in zinc availability, somatic survival and proliferation are significantly more sensitive to zinc chelation or supplementation. Finally, transcriptomic, proteomic, and zinc loading analyses reveal enrichment of zinc targets in the ubiquitination pathway. Overall, these results demonstrate that distinct cell type- specific zinc regulations are required for follicle growth and indicate that physiological fluctuation in the localization and availability of this inorganic cofactor has fundamental functions in early gamete development.

59 BASIC BIOLOGICAL SCIENCES↗

Human DNA polymerase η promotes RNA-templated error-free repair of DNA double-strand breaks

A growing body of evidence indicates that RNA plays a critical role in orchestrating DNA double-strand break repair (DSBR). Recently, we showed that homologous nascent RNA can be used as a template for error-free repair of double-strand breaks (DSBs) in the transcribed genome and to restore the missing sequence at the break site via the transcription-coupled classical nonhomologous end-joining (TC-NHEJ) pathway. TC-NHEJ is a complex multistep process in which a reverse transcriptase (RT) is essential for synthesizing the DNA strand from template RNA. However, the identity of the RT involved in the TC-NHEJ pathway remained unknown. Here, we report that DNA polymerase eta (Pol η), known to possess RT activity, plays a critical role in TC-NHEJ. We found that Pol η forms a multiprotein complex with RNAP II and other TC-NHEJ factors, while also associating with nascent RNA. Moreover, purified Pol η, along with DSBR proteins PNKP, XRCC4, and Ligase IV can fully repair RNA templated 3'-phosphate-containing gapped DNA substrate. In addition, we demonstrate here that Pol η deficiency leads to accumulation of R-loops and persistent strand breaks in the transcribed genes. Finally, we determined that, in Pol η depleted but not in control cells, TC-NHEJ-mediated repair was severely abrogated when a reporter plasmid containing a DSB with several nucleotide deletion within the E. coli lacZ gene was introduced for repair in lacZ-expressing mammalian cells. Thus, our data strongly suggest that RT activity of Pol η is required in error-free DSBR.

59 BASIC BIOLOGICAL SCIENCES↗

Designer molecules of the synaptic organizer MDGA1 reveal 3D conformational control of biological function

MDGAs (MAM domain-containing glycosylphosphatidylinositol anchors) are synaptic cell surface molecules that regulate the formation of trans-synaptic bridges between neurexins (NRXNs) and neuroligins (NLGNs), which promote synaptic development. Mutations in MDGAs are implicated in various neuropsychiatric diseases. MDGAs bind NLGNs in cis on the postsynaptic membrane and physically block NLGNs from binding to NRXNs. In crystal structures, the six immunoglobulin (Ig) and single fibronectin III domains of MDGA1 reveal a striking compact, triangular shape, both alone and in complex with NLGNs. Whether this unusual domain arrangement is required for biological function or other arrangements occur with different functional outcomes is unknown. Here, we show that WT MDGA1 can adopt both compact and extended 3D conformations that bind NLGN2. Designer mutants targeting strategic molecular elbows in MDGA1 alter the distribution of 3D conformations while leaving the binding affinity between soluble ectodomains of MDGA1 and NLGN2 intact. In contrast, in a cellular context, these mutants result in unique combinations of functional consequences, including altered binding to NLGN2, decreased capacity to conceal NLGN2 from NRXN1β, and/or suppressed NLGN2-mediated inhibitory presynaptic differentiation, despite the mutations being located far from the MDGA1-NLGN2 interaction site. Thus, the 3D conformation of the entire MDGA1 ectodomain appears critical for its function, and its NLGN-binding site on Ig1-Ig2 is not independent of the rest of the molecule. As a result, global 3D conformational changes to the MDGA1 ectodomain via strategic elbows may form a molecular mechanism to regulate MDGA1 action within the synaptic cleft.

MDGAs↗

Dirigent isoflavene-forming PsPTS2: 3D structure, stereochemical, and kinetic characterization comparison with pterocarpan-forming PsPTS1 homolog in pea

Pea (legume plant defense) phytoalexin pterocarpans (–)-maackiain and (+)-pisatin have opposite C6a and C11a configurations, but how this occurs biosynthetically is unknown. Herein, pea dirigent-protein (DP) PsPTS2, which generates 7,2'-dihydroxy-4',5'-methylenedioxyisoflav-3-ene (DMDIF), was investigated as regards stereoselectivity towards four possible 7,2'-dihydroxy-4',5'-methylenedioxyisoflavan-4-ol (DMDI) stereoisomers. Each DMDI stereoisomer configuration was determined using NMR spectroscopy, electronic circular dichroism, and molecular orbital analyses. PsPTS2 efficiently converted cis-(3R,4R)-DMDI into DMDIF, this being 20-fold faster than with the trans-(3R,4S)-isomer. The 4R-configured substrate’s near ß-axial OH orientation significantly enhanced its leaving group abilities in creating intermediate A-ring mono-quinone methide (QM), whereas the 4S-isomer’s 4-OH group α-equatorial orientation was a poorer leaving group. Substrate docking simulations also indicated that the 4R-configured ß-axial OH was closest to the Asp catalytic center, whereas the 4S-isomer’s α-equatorial OH was further away. Neither cis-(3S,4S)- nor trans-(3S, 4R)-DMDIs were substrates, even with the former having the same C3/C4 stereochemistry as (+)-pisatin. PsPTS2, assayed with cis-(3R,4R)-7,2'-dihydroxy-4'-methoxyisoflavan-4-ol [cis-(3R,4R)-DMI] and its C3/C4 stereoisomers, gave 2',7-dihydroxy-4'-methoxyisoflav-3-ene (DMIF), with the same substrate stereoselectivity. DP homologs may exist in licorice (Glycyrrhiza pallidiflora) and the tree legume Bolusanthus speciosus, as DMIF is found in both. PsPTS1 preferentially utilized cis-(3R,4R)-DMDI to give (–)-maackiain, this being 2200-fold more efficient than with cis-(3R,4R)-DMI. PsPTS1 also slowly converted trans-(3S,4R)-DMDI into (+)-maackiain, again reflecting the better 4R configured OH leaving group. Pea PsPTS2 and PsPTS1 provisionally provide a facile DP-engendered means to enable differing C6a and C11a configurations in (+)-pisatin and (–)-maackiain. Both DP transformations are considered to occur via DP-engendered generation of an identical mono-QM bound intermediate, which with PsPTS2 either re-aromatizes to give DMDIF or with PsPTS1 undergoes intramolecular cyclization to afford (–)-maackiain. Substrate docking simulations using PsPTS2 (2.5 Å resolution) and PsPTS1 (1.5 Å resolution) plausibly indicate that cis-(3R,4R)-DMDI binds in the anti-configuration in the PsPTS2 active site to afford DMDIF, and the syn-configuration in PsPTS1 to give maackiain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Functional roles of the [2Fe-2S] clusters in Synechocystis PCC 6803 Hox [NiFe]-hydrogenase reactivity with ferredoxins

The HoxEFUYH complex of Synechocystis PCC 6803 (S. 6803) consists of a HoxEFU ferredoxin:NAD(P)H oxidoreductase subcomplex and a HoxYH [NiFe]-hydrogenase subcomplex that catalyzes reversible H2 oxidation. Prior studies have suggested that the presence of HoxE is required for reactivity with ferredoxin; however, it is unknown how HoxE is functionally integrated into the electron transfer network of the HoxEFU:ferredoxin complex. Deciphering electron transfer pathways is challenged by the rich iron-sulfur cluster content of HoxEFU, which includes a [2Fe-2S] cluster in each subunit, along with multiple [4Fe-4S] clusters and a flavin cofactor. To resolve the role of HoxE, we determined the biophysical and thermodynamic properties of each [2Fe-2S] cluster in HoxEFU using steady-state and potentiometric EPR analysis in combination with square wave voltammetry (SWV). The temperature-dependence of the EPR signal for HoxE confirmed the coordination of a single [2Fe-2S] cluster that was shown by SWV to have an E m = -424 mV (versus SHE). Strikingly, when the E m of the HoxE [2Fe-2S] cluster was analyzed in HoxEFU titrations, it was shifted by >100 mV to an E m < -525 mV (versus SHE). EPR titrations of HoxEFU gave an E m value for the [2Fe-2S] cluster of HoxF, E m = -419 mV and HoxU, E m = -349 mV. These values were used to re-analyze the diaphorase kinetics in reactions performed with ferredoxins with varying E m 's. The results are formulated into a model of HoxEFU:ferredoxin reactivity and the role of HoxE in mediating electron transfer within the HoxEFU:ferredoxin complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the effect of organic coatings on 4-nitrostyrene hydrogenation selectivity over Pt/TiO 2 catalysts

The hydrogenation of 4-nitrostyrene was investigated over Pt/TiO 2 catalysts to understand the effects of different catalyst coatings on product selectivity and reaction rates. This reaction is a much-investigated selectivity probe due to difficulty in controlling reactivity between the nitro and vinyl groups of 4-nitrostyrene, with C=C reduction generally being more favorable. 4-Nitrostyrene hydrogenation reactions were carried out in a batch reactor using uncoated, organothiol coated, phosphonic acid (PA) coated, and ion-conducting polymer (ionomer) coated catalysts. Thiols form dense coatings on Pt surfaces, whereas PAs preferentially accumulate on TiO 2 ; ionomer binding preference is unknown for this type of catalyst. The coating densities of the thiols and PAs were varied to observe the effects of loading on catalytic activity and reaction selectivity relative to the uncoated catalyst. Changes in selectivity were observed for catalysts with all coatings, with thiol coatings shifting selectivity towards the nitro reduction product, 4-vinylaniline (4-VA), and both ionomer and PA coatings shifting towards 4-ethylnitrobenzene, the olefin hydrogenation product. It was observed that selectivity toward 4-VA increased with thiol coating density, where 1,2-benzenedithiol (BDT) coated catalysts exhibited a selectivity of >99%. These changes were attributed to the identity of the adsorption sites blocked by the different coatings: blocking of metal sites via thiols decreased the rate of C=C hydrogenation, whereas blocking of TiO 2 sites by PAs decreased the rate of nitro group hydrogenation. The changes observed for ionomer and PA coatings suggested that ionomers, like PAs, bind preferentially to the metal oxide support rather than the active metal. This work provides new support to the proposal that nitro group hydrogenation preferentially occurs on TiO 2 sites after hydrogen spillover and underscores how selection of ligand functionality can be used to tune catalyst selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Topological origin of phase separation in hydrated gels

Depending on their composition, hydrated gels can be homogeneous or phase-separated, which, in turn, affects their dynamical and mechanical properties. However, the nature of the structural features, if any, that govern the propensity for a given gel to phase-separate remains largely unknown. Here, we argue that the propensity for hydrated gels to phase-separate is topological in nature. We employ reactive molecular dynamics simulations to model the early-age precipitation of calcium–alumino–silicate–hydrate (Csingle bondAsingle bondSsingle bondH) gels with varying compositions, i.e., (CaO) 1.7 (Al 2 O 3 ) x (SiO 2 ) 1 – x (H 2 O) 3.7 + x . By adopting topological constraint theory, we investigate the structural origin of phase separation in hydrated gels. We report the existence of a homogeneous-to-phase-separated transition, wherein Si-rich (x ≤ 0.10) Csingle bondAsingle bondSsingle bondH gels are homogeneous, whereas Al-rich (x > 0.10) Csingle bondAsingle bondSsingle bondH gels tend to phase-separate. Furthermore, we demonstrate that this transition is correlated to a topological flexible-to-rigid transition within the atomic network. Finally, we reveal that the propensity for topologically-overconstrained gels to phase-separate arises from the existence of some internal stress within their atomic network, which acts as an energy penalty that drives phase separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-stage preconditioners for thermal–compositional–reactive flow in porous media

We present a family of multi-stage preconditioners for coupled thermal-compositional-reactive reservoir simulation problems. The most common preconditioner used in industrial practice, the Constrained Pressure Residual (CPR) method, was designed for isothermal models and does not offer a specific strategy for the energy equation. For thermal simulations, inadequate treatment of the temperature unknown can cause severe conver-gence degradation. When strong thermal diffusion is present, the energy equation exhibits significant elliptic behavior that cannot be accurately corrected by CPR's second stage. In this work, we use Schur-complement decompositions to extract a temperature subsystem and apply an Algebraic MultiGrid (AMG) approximation as an additional preconditioning stage to improve the treatment of the energy equation. We present results for several two-dimensional hot air injection problems using an extra heavy oil, including challenging reactive In-Situ Combustion (ISC) cases. We show improved performance and robustness across different thermal regimes, from advection dominated (high Péclet number) to diffusion dominated (low Péclet number). The number of linear iterations is reduced by 40–85% compared to standard CPR for both homogeneous and heterogeneous media, and the new methods exhibit almost no sensitivity to the thermal regime.

42 ENGINEERING↗

Nonlinear sparse Bayesian learning for physics-based models

This paper addresses the issue of overfitting while calibrating unknown parameters of over-parameterized physics-based models with noisy and incomplete observations. Here, a semi-analytical Bayesian framework of nonlinear sparse Bayesian learning (NSBL) is proposed to identify sparsity among model parameters during Bayesian inversion. NSBL offers significant advantages over machine learning algorithm of sparse Bayesian learning (SBL) for physics-based models, such as 1) the likelihood function or the posterior parameter distribution is not required to be Gaussian, and 2) prior parameter knowledge is incorporated into sparse learning (i.e. not all parameters are treated as questionable). NSBL employs the concept of automatic relevance determination (ARD) to facilitate sparsity among questionable parameters through parameterized prior distributions. The analytical tractability of NSBL is enabled by employing Gaussian ARD priors and by building a Gaussian mixture-model approximation of the posterior parameter distribution that excludes the contribution of ARD priors. Subsequently, type-II maximum likelihood is executed using Newton's method whereby the evidence and its gradient and Hessian information are computed in a semi-analytical fashion. We show numerically and analytically that SBL is a special case of NSBL for linear regression models. Subsequently, a linear regression example involving multimodality in both parameter posterior pdf and model evidence is considered to demonstrate the performance of NSBL in cases where SBL is inapplicable. Next, NSBL is applied to identify sparsity among the damping coefficients of a mass-spring-damper model of a shear building frame. These numerical studies demonstrate the robustness and efficiency of NSBL in alleviating overfitting during Bayesian inversion of nonlinear physics-based models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Massively parallel transport sweeps on meshes with cyclic dependencies

When solving the first-order form of the linear Boltzmann equation, a common misconception is that the matrix-free computational method of “sweeping the mesh”, used in conjunction with the Discrete Ordinates method, is too complex or does not scale well enough to be implemented in modern high performance computing codes. This has led to considerable efforts in the development of matrix-based methods that are computationally expensive and is partly driven by the requirements placed on modern spatial discretizations. In particular, modern transport codes are required to support higher order elements, a concept that invariably adds a lot of complexity to sweeps because of the introduction of cyclic dependencies with curved mesh cells. In this article we will present a comprehensive implementation of sweeping, to a piecewise-linear DFEM spatial discretization with particular focus on handling cyclic dependencies and possible extensions to higher order spatial discretizations. We find that these methods are implemented in a new C++ simulation framework called Chi-Tech (). We present some typical simulation results with some performance aspects that one can expect during real world simulations, we also present a scaling study to >100k processes where Chi-Tech maintains greater than 80% efficiency solving a total of 87.7 trillion angular flux unknowns for a 116 group simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Deep learning of free boundary and Stefan problems

Free boundary problems appear naturally in numerous areas of mathematics, science and engineering. These problems present a great computational challenge because they necessitate numerical methods that can yield an accurate approximation of free boundaries and complex dynamic interfaces. In this work, we propose a multi-network model based on physics-informed neural networks to tackle a general class of forward and inverse free boundary problems called Stefan problems. Specifically, we approximate the unknown solution as well as any moving boundaries by two deep neural networks. Besides, we formulate a new type of inverse Stefan problems that aim to reconstruct the solution and free boundaries directly from sparse and noisy measurements. We demonstrate the effectiveness of our approach in a series of benchmarks spanning different types of Stefan problems, and illustrate how the proposed framework can accurately recover solutions of partial differential equations with moving boundaries and dynamic interfaces. All code and data accompanying this manuscript are publicly available at https://github.com/PredictiveIntelligenceLab/DeepStefan.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Multi-fidelity Bayesian neural networks: Algorithms and applications

Here we propose a new class of Bayesian neural networks (BNNs) that can be trained using noisy data of variable fidelity, and we apply them to learn function approximations as well as to solve inverse problems based on partial differential equations (PDEs). These multi-fidelity BNNs consist of three neural networks: The first is a fully connected neural network, which is trained following the maximum a posteriori probability (MAP) method to fit the low-fidelity data; the second is a Bayesian neural network employed to capture the cross-correlation with uncertainty quantification between the low- and high-fidelity data; and the last one is the physics-informed neural network, which encodes the physical laws described by PDEs. For the training of the last two neural networks, we first employ the mean-field variational inference (VI) to maximize the evidence lower bound (ELBO) to obtain informative prior distributions for the hyperparameters in the BNNs, and subsequently we use the Hamiltonian Monte Carlo (HMC) method to estimate accurately the posterior distributions for the corresponding hyperparameters. We demonstrate the accuracy of the present method using synthetic data as well as real measurements. Specifically, we first approximate a one- and four-dimensional function, and then infer the reaction rates in one- and two-dimensional diffusion-reaction systems. Moreover, we infer the sea surface temperature (SST) in the Massachusetts and Cape Cod Bays using satellite images and in-situ measurements. Taken together, our results demonstrate that the present method can capture both linear and nonlinear correlation between the low- and high-fidelity data adaptively, identify unknown parameters in PDEs, and quantify uncertainties in predictions, given a few scattered noisy high-fidelity data. Finally, we demonstrate that we can effectively and efficiently reduce the uncertainties and hence enhance the prediction accuracy with an active learning approach, using as examples a specific one-dimensional function approximation and an inverse PDE problem.

97 MATHEMATICS AND COMPUTING↗

Adjoint DSMC for nonlinear Boltzmann equation constrained optimization

Applications for kinetic equations such as optimal design and inverse problems often involve finding unknown parameters through gradient-based optimization algorithms. Based on the adjoint-state method, we derive two different frameworks for approximating the gradient of an objective functional constrained by the nonlinear Boltzmann equation. While the forward problem can be solved by the DSMC method, it is difficult to efficiently solve the high-dimensional continuous adjoint equation obtained by the “optimize-then-discretize” approach. This challenge motivates us to propose an adjoint DSMC method following the “discretize-then-optimize” approach for Boltzmann-constrained optimization. We also analyze the properties of the two frameworks and their connections. Here, several numerical examples are presented to demonstrate their accuracy and efficiency.

97 MATHEMATICS AND COMPUTING↗