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Projected Multi-Agent Consensus Equilibrium (PMACE) With Application to Ptychography

Multi-Agent Consensus Equilibrium (MACE) formulates an inverse imaging problem as a balance among multiple update agents such as data-fitting terms and denoisers. However, each such agent operates on a separate copy of the full image, leading to redundant memory use and slow convergence when each agent affects only a small subset of the full image. In this article, we extend MACE to Projected Multi-Agent Consensus Equilibrium (PMACE), in which each agent updates only a projected component of the full image, thus greatly reducing memory use for some applications. We describe PMACE in terms of an equilibrium problem and an equivalent fixed-point problem and show that in most cases the PMACE equilibrium is not the solution of an optimization problem. To demonstrate the value of PMACE, we apply it to the problem of ptychography, in which a sample is reconstructed from the diffraction patterns resulting from coherent X-ray illumination at multiple overlapping spots. In our PMACE formulation, each spot corresponds to a separate data-fitting agent, with the final solution found as an equilibrium among all the agents. In conclusion, our results demonstrate that the PMACE reconstruction algorithm generates more accurate reconstructions at a lower computational cost than existing ptychography algorithms when the spots are sparsely sampled.

97 MATHEMATICS AND COMPUTING↗

Ringing Artifact Reduction Method for Ultrasound Reconstruction Using Multi-Agent Consensus Equilibrium

Non-destructive characterization of multi-layered structures that can be accessed from only a single side is important for applications such as well-bore integrity inspection. Existing methods related to Synthetic Aperture Focusing Technique (SAFT) rapidly produce acceptable results but with significant artifacts. Recently, ultrasound model-based iterative reconstruction (UMBIR) approaches have shown significant improvements over SAFT. However, even these methods produce ringing artifacts due to the high fractional-bandwidth of the excitation signal.In this paper, we propose a ringing artifact reduction method for ultrasound image reconstruction that uses a multi-agent consensus equilibrium (RARE-MACE) framework. Our approach integrates a physics-based forward model that accounts for the propagation of a collimated ultrasonic beam in multi-layered media, a spatially varying image prior, and a denoiser designed to suppress the ringing artifacts that are characteristic of reconstructions from high-fractional bandwidth ultrasound sensor data. We test our method on simulated and experimental measurements and show substantial improvements in image quality compared to SAFT and UMBIR.

Alanazi, Abdulrahman M↗

Sparse measurement medical CT reconstruction using multi-fused block matching denoising priors

A major challenge for medical X-ray CT imaging is reducing the number of X-ray projections to lower radiation dosage and reduce scan times without compromising image quality. However these under-determined inverse imaging problems rely on the formulation of an expressive prior model to constrain the solution space while remaining computationally tractable. Traditional analytical reconstruction methods like Filtered Back Projection (FBP) often fail with sparse measurements, producing artifacts due to their reliance on the Shannon-Nyquist Sampling Theorem. Consensus Equilibrium, which is a generalization of Plug and Play, is a recent advancement in Model-Based Iterative Reconstruction (MBIR), has facilitated the use of multiple denoisers are prior models in an optimization free framework to capture complex, non-linear prior information. However, 3D prior modelling in a Plug and Play approach for volumetric image reconstruction requires long processing time due to high computing requirement. Instead of directly using a 3D prior, this work proposes a BM3D Multi Slice Fusion (BM3D-MSF) prior that uses multiple 2D image denoisers fused to act as a fully 3D prior model in Plug and Play reconstruction approach. Our approach does not require training and are thus able to circumvent ethical issues related with patient training data and are readily deployable in varying noise and measurement sparsity levels. In addition, reconstruction with the BM3D-MSF prior achieves similar reconstruction image quality as fully 3D image priors, but with significantly reduced computational complexity. We test our method on clinical CT data and demonstrate that our approach improves reconstructed image quality.

Hossain, Maliha [ORNL]↗

Super Resolving Unrolled Neural Networks for Remote Sensing

In remote sensing systems, the capabilities of the system are constrained by the complex interactions between size, weight, and power (SWAP) of potential designs. In electro-optical (EO) systems, examples of these critical parameters include the system’s sensitivity and resolution. Those parameters can be increased by ever larger optical apertures and focal planes but at the cost of more SWAP. Multi-image super resolution (MISR) techniques allow resolution to be enhanced via computation rather than more sophisticated optical hardware. These algorithms combine multiple images together into a single, higher resolution image, trading temporal resolution and computation for spatial resolution. Fielded MISR techniques, such as Drizzle, can require several hundred images to create a single super resolved image, implying reduced temporal resolution, increased data acquisition load, and limiting mission applications. Iterative techniques, such as model-based image reconstruction and compressive sensing, have been shown to create super resolved images using fewer images than Drizzle. They do this by posing an optimization problem that balances accuracy between a highly accurate physical model and an image model. In the case of super resolution, the physical model is defined by the relation between low resolution input images and the desired high resolution output image. The image model encodes some assumptions about the super resolved image. These assumptions are meant to suppress reconstruction artifacts that arise due to deterministic physical model error, stochastic measurement noise, and potential undersampling. In practice, the performance of iterative methods are limited by imaging models compatible with optimization. Deep learning-based methods can effectively learn image models of arbitrary complexity, but lack the theoretical explainability and robustness of iterative techniques. Consensus equilibrium (CE) generalizes the iterative techniques beyond optimization, enabling blackbox algorithms such as traditional and neural image denoisers to be used as the image model. CE-based approaches retain much of the explainability and robustness of iterative techniques while allowing the expressiveness of machine learning image models to be used. Additionally, by unrolling iterations of CE with an embedded image denoiser, the image denoiser can be further trained and specialized to the specific application with potentially higher quality reconstructions. Under this project, we demonstrated the feasibility of training an unrolled neural network based upon CE. While we didn’t train one, we showed that the CE process is differentiable and its gradient can be tractably computed. We also explored the usage of a variants of CE akin to generative neural works. Most importantly, we applied the CE framework to a number of problems including non-blind deconvolution, upsampling, single-image super resolution, MISR, event-based sensing, and saturated deconvolution. Our MISR prototype creates high quality reconstructions with an order of magnitude fewer images than previous approaches and, critically, produces these reconstructions fast enough for practical usage.

47 OTHER INSTRUMENTATION↗

Phase compatibilities of YBa2Cu3O(9-delta) type structure in quintenary systems Y-Ba-Cu-O-X (impurity)

Electrical transport properties of the oxidic high T(sub c) superconductors are significantly affected by the presence of minor amounts of various elements adventing as impurities, e.g., from the chemical environment during manufacturing. YBa2Cu3O(9-delta) is prone to an extinction of the superconductivity on (partial) substitution of all four elemental components. E.g., Pr (for Y), La (for Ba), Zn (for Cu) or peroxygroup (for O) substituents will alter some of the superconductivity preconditions, like mixed valence state in Cu3O7/O(9-delta) network or structural distortion of the network. Although various pseudoternary chemical equilibrium phase diagrams of the Y(O)-Ba(O)-Cu(O) system now are available, no consensus is generally shown, however, this is partly due to lack of compatible definitions of the equilibrium conditions. Less information is available about the phase compatibilities in the appropriate quaternary phase diagram (including oxygen) and virtually no information exists about any pentenary phase diagrams (including one impurity). Unfortunately, complexity of such systems, stemming both from number of quaternary or pentenary compounds and from visualizing the five-component phase system, limits this presentation to more or less close surroundings of the YBa2Cu3O(9-delta) type phase in appropriate pseudoquaternary or pseudopseudoternary diagrams, involving Y-Ba-Cu and O, O-CO2, alkaline metals, Mg and alkaline earths, and Sc and most of the 3-d and 4-f elements. The systems were investigated by means of x ray diffraction, neutron diffraction and chemical analytical methods on samples prepared by sol-gel technique from citrates. The superconductivity was characterized by measuring the diamagnetic susceptibility by SQUID.

Karen, P.↗

Tests of the DFT Ladder for the Fulminic Acid Challenge

Properties of the historically pivotal fulminic acid (HCNO) molecule have been computed with a panoply of 473 density functionals of all varieties, providing a snapshot of the performance of contemporary density functional theory (DFT) for a challenging chemical system. Exhaustive tabulations and statistical analyses have been carried out for geometric parameters, vibrational frequencies, barriers to linearity, and the HCN–O dissociation energy. As the DFT ladder is climbed, confusion rather than consensus ensues regarding the details of the distinctive, extremely flat H–C–N bending potential of fulminic acid and whether the equilibrium structure is linear or bent. While high-ranking DFT functionals produce the smallest errors for the HCN + O( 3 P) → HCNO reaction energy, lower rungs emerge as the best performers for many of the bond distances and harmonic vibrational frequencies. This research shows that the current DFT zoo of approximations does not constitute a transparent ladder of increasingly accurate methods that consistently converges on definitive predictions for various properties of HCNO. Additional analyses are performed on the side effects of popular dispersion corrections on the covalently bonded properties and thermochemistry of HCNO.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Dynamics of Debris Disk Creation in Neutron Star Mergers

Abstract The detection of GW170817/AT2017gfo inaugurated an era of multimessenger astrophysics, in which gravitational-wave and multiwavelength photon observations complement one another to provide unique insight into astrophysical systems. A broad theoretical consensus exists, in which the photon phenomenology of neutron star mergers largely rests upon the evolution of the small amount of matter left on bound orbits around the black hole or massive neutron star remaining after the merger. Because this accretion disk is far from inflow equilibrium, its subsequent evolution depends very strongly on its initial state, yet very little is known about how this state is determined. Using both snapshot and tracer particle data from a numerical relativity/MHD simulation of an equal-mass neutron star merger that collapses to a black hole, we show how gravitational forces arising in a nonaxisymmetric, dynamical spacetime supplement hydrodynamical effects in shaping the initial structure of the bound debris disk. The work done by hydrodynamical forces is ∼10 times greater than that due to time-dependent gravity. Although gravitational torques prior to remnant relaxation are an order of magnitude larger than hydrodynamical torques, their intrinsic sign symmetry leads to strong cancellation; as a result, hydrodynamical and gravitational torques have a comparable effect. We also show that the debris disk’s initial specific angular momentum distribution is sharply peaked at roughly the specific angular momentum of the merged neutron star’s outer layers, a fewr g c, and identify the regulating mechanism.

Astronomy & Astrophysics↗

Modeling active nematics via the nematic locking principle

Active nematic systems consist of rod-like internally driven subunits that interact with one another to form large-scale coherent flows. They are important examples of far-from-equilibrium fluids, which exhibit a wealth of nonlinear behavior. This includes active turbulence, in which topological defects in the nematic order braid around one another in a chaotic fashion. One of the most studied examples of active nematics consists of a dense two-dimensional layer of microtubules, crosslinked by kinesin molecular motors that inject extensile deformations into the fluid. Though numerous theoretical studies have modeled microtubule-based active nematics, no consensus has emerged on how to fully and quantitatively capture the features of the experimental system. Here, to better understand the theoretical foundations for modeling this system, we propose a fundamental principle we call the nematic locking principle—individual microtubules cannot rotate without all neighboring microtubules also rotating. Physically, this is justified by the high density of the microtubules, their elongated nature, and their corresponding steric interactions. We assert that the nematic locking principle holds throughout the majority of the material, but breaks down in the neighborhood of topological defects and other regions of low density. We derive the most general nematic transport equation consistent with this principle and also derive the most general term that violates it, introducing fracturing into the material. We then examine the standard Beris–Edwards approach, commonly used to model this system, and show that it violates the nematic locking principle throughout the majority of the material due to fracturing. We then propose a modification to the Beris–Edwards model that enforces nematic locking nearly everywhere. This modification shuts off fracturing except in regions where the order parameter (a proxy for density) is reduced. In these regions fracturing is turned on. The resulting simulations in turn show strong nematic locking throughout the bulk of the material, with narrow bands of fracturing, consistent with experimental observation. One additional advantage of enforcing nematic locking is that nontrivial stationary state solutions, common in Beris–Edwards simulations but not seen in experiments, are eliminated.

Mitchell, Kevin A. [Univ. of California, Merced, C↗

RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project

Abstract. The radiative–convective equilibrium (RCE) model intercomparison project (RCEMIP) leveraged the simplicity of RCE to focus attention on moist convective processes and their interactions with radiation and circulation across a wide range of model types including cloud-resolving models (CRMs), general circulation models (GCMs), single-column models, global cloud-resolving models, and large-eddy simulations. While several robust results emerged across the spectrum of models that participated in the first phase of RCEMIP (RCEMIP-I), two points that stand out are (1) the strikingly large diversity in simulated climate states and (2) the strong imprint of convective self-aggregation on the climate state. However, the lack of consensus in the structure of self-aggregation and its response to warming is a barrier to understanding. Gaining a deeper understanding of convective aggregation and tropical climate will require reducing the degrees of freedom with which convection can vary. Therefore, we propose phase II of RCEMIP (RCEMIP-II) that utilizes a prescribed sinusoidal sea surface temperature (SST) pattern to provide a constraint on the structure of convection and move one critical step up the model hierarchy. This so-called “mock-Walker” configuration generates features that resemble observed tropical circulations. The specification of the mock-Walker protocol for RCEMIP-II is described, along with example results from one CRM and one GCM. RCEMIP-II will consist of five required simulations: three simulations with the same three mean SSTs as in RCEMIP-I but with an SST gradient and two additional simulations at one of the mean SSTs with different values of the SST gradients. We also test the sensitivity to the imposed SST gradient and the domain size. Under weak SST gradients, unforced self-aggregation emerges across the entire domain, similar to what was found in RCEMIP. As the SST gradient increases, the convective region narrows and is more confined to the warmest SSTs. At warmer mean SSTs and stronger SST gradients, low-frequency variability in the convective aggregation emerges, suggesting that simulations of at least 200 d may be needed to achieve robust equilibrium statistics in this configuration. Simulations with different domain sizes generally have similar mean statistics and convective structures, depending on the value of the SST gradient. The prescribed SST boundary condition is the only difference in the set-up between RCEMIP-II and RCEMIP-I, which enables comparison between the two; however, we also welcome participation in RCEMIP-II from models that did not participate in RCEMIP-I.

Geology↗

Reverse Energy Cascade in Turbulent Weakly Ionized Plasmas

For systems far from equilibrium, the neglect of a role for viscous effects in turbulence may be generally inappropriate when the relaxation time for the molecular process approaches the local flow time (Orou et al. (1996)). Furthermore, for stationary collisional plasmas, the conventional Reynolds number is irrelevant under circumstances where the standard features of turbulence in ordinary gases are observed in the plasma (Johnson et al. (1987)). The current theoretical understanding of these turbulent phenomenon is particularly inadequate for turbulence associated with ionizing shock waves; generally speaking, thermodynamic, acoustic and pressure fluctuations are all seen as amplified across the shock wave followed by a dramatic decay (relaminarization) usually attributed to a lack of importance of viscosity in the turbulent regions. This decay would be accelerated when the flow speed is also reduced due to the importance usually given to the conventional Reynolds number (which is directly proportional to velocity) as a quality of turbulence index. However, evidence supporting this consensus is lacking. By contrast, recent evidence of vanishing triple correlations form De Silva et al. (1996) provides strong support for early theoretical speculation of inherently molecular effects in macroscopic turbulence in Tsuge (1974). This specifically suggests that the role of compressive effects ordinarily associated with the shock wave could be significantly muted by the existence of a strongly turbulent local environment. There is also more recent theoretical speculation (Frisch et al. (1984)) of an inherently and previously unsuspected non-dissipative nature to turbulence, with energy conservation being nurtured by reverse energy cascades in the turbulent fluctuation spectra. Furthermore, the role which might be played by fluctuations on quantum mechanical phenomena and variations in molecular parameters is completely unknown, especially of the sort which might be found in optical spectra. A determination of the role which changing turbulent parameters might play on optical signatures behind a reflected shock wave should therefore provide a useful tool for the evolution of theoretical models for turbulence.

Williams, Kyron↗

Operando Characterization of Fe in Doped Ni x (Fe 1– x )O y H z Catalysts for Electrochemical Oxygen Evolution

Iron-doped nickel oxyhydroxides, Ni x (Fe 1– x )O y H z , are among the most promising oxygen evolution reaction (OER) electrocatalysts in alkaline environments. Although iron (Fe) significantly enhances the catalytic activity, there is still no clear consensus on whether Fe directly participates in the reaction or merely acts as a promoter. To elucidate the Fe’s role, we performed operando X-ray spectroscopy studies supported by DFT on Ni x (Fe 1– x )O y H z electrocatalysts. We probed the reversible changes in the structure and electronic character of Ni x (Fe 1– x )O y H z as the electrode potential is cycled between the resting (here at 1.10 V RHE ) and operational states (1.66 V RHE ). DFT calculations and XAS simulations on a library of Fe structures in various NiO y H z environments are in favor of a distorted local octahedral Fe(III)O 3 (OH) 3 configuration at the resting state with the NiO y H z scaffold going from α-Ni(OH) 2 to γ-NiOOH as the potential is increased. Under catalytic conditions, EXAFS and HERFD spectra reveal changes in p-d mixing (covalency) relative to the resting state between O/OH ligands and Fe leading to a shift from octahedral to square pyramidal coordination at the Fe site. XES measurements and theoretical simulations further support that the Fe equilibrium structure remains in a formal Fe(III) state under both resting and operational conditions. These spectral changes are attributed to potential dependent structural rearrangements around Fe. The results suggest that ligand dissociation leads to the C 4v symmetry as the most stable intermediate of the Fe during OER. This implies that Fe has a weakly coordinated or easily dissociable ligand that could serve to coordinate the O–O bond formation and, tentatively, play an active role in the Ni x (Fe 1– x )O y H z electrocatalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗