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At least 1,207 records · Page 67

A Process Model of Interpersonal Relationship Formation in Isolated and Confined Environments

Future space crews will face several challenges such as living and working in a confined environment, isolated from others. These circumstances increase the importance of interpersonal compatibility, teamwork, and team performance. The interpersonal compatibility of space crews has been and continues to be of interest to both NASA and the Institute of Biomedical Problems (IBMP), whose research informs operations for Roscosmos. In NASA-sponsored research, interpersonal compatibility has been examined in terms of how the combination of team members’ personality traits, values, and demographics shape team member relationships and team performance overtime. IBMP-sponsored research mostly has moved away from trait-based approaches toward an idiographic (in-depth, heavily descriptive) approach to researching crew interpersonal relations. This research uses software such as Personal Self-Perception and Attitudes (PSPA), network approaches to team member relations, and content analysis of interactions to assess interpersonal compatibility, and infer states and team dynamics. Our research program integrated these ideas. Our primary research aim was to develop and empirically test a process model of interpersonal relationship formation in isolated and confinement environments. We created a model, collected data from teams in an isolated and confined environment, and applied a novel analytical strategy that combines trait, state, and interaction data (i.e., relational events). We focused specifically on the formation of strained relationships in isolation and confinement—or with whom fellow crewmembers find it difficult to work.

S T Bell↗

Roles of Glutamates and Metal ions in a Rationally Designed Nitric Oxide Reductase Based on Myoglobin

A structural and functional model of bacterial nitric oxide reductase (NOR) has been designed by introducing two glutamates (Glu) and three histidines (His) in sperm whale myoglobin. X-ray structural data indicate that the three His and one Glu (V68E) residues bind iron, mimicking the putative FeB site in NOR, while the second Glu (I107E) interacts with a water molecule and forms a hydrogen bonding network in the designed protein. Unlike the first Glu (V68E), which lowered the heme reduction potential by {approx}110 mV, the second Glu has little effect on the heme potential, suggesting that the negatively charged Glu has a different role in redox tuning. More importantly, introducing the second Glu resulted in a {approx}100% increase in NOR activity, suggesting the importance of a hydrogen bonding network in facilitating proton delivery during NOR reactivity. In addition, EPR and X-ray structural studies indicate that the designed protein binds iron, copper, or zinc in the FeB site, each with different effects on the structures and NOR activities, suggesting that both redox activity and an intermediate five-coordinate heme-NO species are important for high NOR activity. The designed protein offers an excellent model for NOR and demonstrates the power of using designed proteins as a simpler and more well-defined system to address important chemical and biological issues.

08 HYDROGEN↗

Efficient Certificate Verification for Vehicle-to-Grid Communications

While public charging stations are typically used for Electric Vehicle (EV) such as charging, home microgrids that may act as private charging stations are also expected to be used for meeting the increased EV charging demands in the future. Such home microgrids can be accessible through their smart meters, which makes advanced metering infrastructure (AMI) a viable alternative for vehicle-to-grid (V2G) communications. However, to ensure secure V2G communications using public-keys, smart meters will need to maintain certificate revocation lists (CRLs) not just for the AMI network but also for large number of EVs that may interact with them. For resource-constrained smart meters, this will increase the storage requirements and introduce additional overhead in terms of delay and CRL maintenance. To eliminate this burden, we propose keeping merely non-revoked certificates that belong to EVs, which are usually driven within the vicinity of that particular microgrid. The motivation comes from the fact that it is inefficient to distribute and store a large CRL that has revocation information about all EVs in the whole system as most of these EVs will never come to the geographic vicinity of that home microgrid. The approach ensures that any status changes of these certificates are communicated to the smart meters. We implemented the proposed approach in a realistic V2G communication scenario by using IEEE 802.11s mesh as the underlying AMI infrastructure using ns-3 simulator. The results confirmed that the proposed approach significantly reduces the certificate verification time and the storage requirements on smart meters.

25 ENERGY STORAGE↗

Sensitivity-Based Reactive Power Dispatch of DERs to Support Transmission Grid During Emergency

This paper proposes a TSO-DSO framework including DER set-point dispatch using sensitivity analysis. We address all three steps of TSO-DSO integration stating by estimating the capability curve of an unbalanced distribution system and then modeling of capability curve on the transmission side grid and estimating the reactive power needed from DSO during emergencies, and ending by dispatching the requested reactive power from TSO. The proposed interaction framework is tested on an IEEE 37-node distribution network connected to IEEE 9 bus transmission system. The simulation shows that using sensitivity-based dispatch would reduce the number of communication signals between DERs and DSO and that can decrease the risk of communication contingency.

Alkhonain, Ahmed↗

Inaugural Molten Salt Technologies Workshop Powering the Future

The inaugural “Molten Salt Technologies – Powering the Future” Workshop marked a significant convergence of minds from diverse industries, each harnessing molten-salt technologies in innovative ways. Participants from sectors such as solar, geothermal, and advanced nuclear energy, as well as those involved in cutting-edge applications like thermal transport and rare-earth metals extraction, gathered to discuss their shared technical challenges and opportunities. Industry leaders in metal extraction and recycling, alongside experts in high-temperature sensor technology and advanced material manufacturing, also brought their unique perspectives to the table. This workshop served as a crucial platform for these varied industries to delve into the engineering intricacies that molten salt technologies entail. Common challenges such as understanding the thermophysical properties of salts, tackling corrosion mechanisms in harsh environments, and enhancing material resilience under extreme conditions were at the forefront of discussions. These technical sessions highlighted the critical need for cross-industry collaboration to address issues like salt life-cycle process engineering, impurity mitigation, and the development of durable, high-performance materials. By bringing together academia, industry, and representatives from national laboratories and the U.S. Department of Energy (DOE), the workshop facilitated a rich exchange of knowledge and experiences. This interaction not only fostered new partnerships but also strengthened the network among existing collaborators, setting the stage for joint solutions to the complex problems faced by all sectors using molten salt technologies. The event underscored the importance of collaborative efforts in overcoming common engineering challenges and advancing the application of molten-salt technologies across various industries. The workshop not only provided an essential forum for networking and idea exchange but also highlighted the collective drive towards innovative solutions that could benefit multiple fields.

Department of Energy↗

Inaugural Molten Salt Technologies Workshop Powering the Future

The inaugural “Molten Salt Technologies – Powering the Future” Workshop marked a significant convergence of minds from diverse industries, each harnessing molten-salt technologies in innovative ways. Participants from sectors such as solar, geothermal, and advanced nuclear energy, as well as those involved in cutting-edge applications like thermal transport and rare-earth metals extraction, gathered to discuss their shared technical challenges and opportunities. Industry leaders in metal extraction and recycling, alongside experts in high-temperature sensor technology and advanced material manufacturing, also brought their unique perspectives to the table. This workshop served as a crucial platform for these varied industries to delve into the engineering intricacies that molten salt technologies entail. Common challenges such as understanding the thermophysical properties of salts, tackling corrosion mechanisms in harsh environments, and enhancing material resilience under extreme conditions were at the forefront of discussions. These technical sessions highlighted the critical need for cross-industry collaboration to address issues like salt life-cycle process engineering, impurity mitigation, and the development of durable, high-performance materials. By bringing together academia, industry, and representatives from national laboratories and the U.S. Department of Energy (DOE), the workshop facilitated a rich exchange of knowledge and experiences. This interaction not only fostered new partnerships but also strengthened the network among existing collaborators, setting the stage for joint solutions to the complex problems faced by all sectors using molten salt technologies. The event underscored the importance of collaborative efforts in overcoming common engineering challenges and advancing the application of molten-salt technologies across various industries. The workshop not only provided an essential forum for networking and idea exchange but also highlighted the collective drive towards innovative solutions that could benefit multiple fields.

Department of Energy↗

Atlas of putative minima and low-lying energy networks of water clusters n = 3 - 25

We report a database consisting of the putative minima and ~3.2 million local minima lying within 5 kcal/mol from the putative minima for water clusters of sizes n = 3 – 25 using an improved version of the Monte Carlo Temperature Basin Paving (MCTBP) global optimization procedure in conjunction with the ab-initio based, flexible, polarizable Thole-Type Model (TTM2.1-F, version 2.1) interaction potential for water. Several of the low-lying structures, as well as lowlying penta-coordinated water networks obtained with the TTM2.1-F potential, were further refined at the Møller-Plesset second order perturbation MP2/aug-cc-pVTZ level of theory. In total, we have identified 3,138,303 networks corresponding to local minima of the clusters n = 3 – 25, whose Cartesian coordinates and relative energies can be obtained from the webpage https://sites.uw.edu/wdbase/. Networks containing penta-coordinated water molecules start to appear at n = 11 and, quite surprisingly, are energetically close (within 1 – 3 kcal/mol) to the putative minima, a fact that has been confirmed from the MP2 calculations. This large database of water cluster minima spanning quite dissimilar hydrogen bonding networks is expected to influence the development and assessment of the accuracy of interaction potentials for water as well as lower scaling electronic structure methods (such as different density functionals). Furthermore, it can also be used in conjunction with data science approaches (including but no limited to neural networks, machine and deep learning) to understand the properties of water, nature’s most important substance.

Rakshit, Avijit↗

Complex water networks visualized by cryogenic electron microscopy of RNA

The stability and function of biomolecules are directly influenced by their myriad interactions with water. Here we investigated water through cryogenic electron microscopy (cryo-EM) on a highly solvated molecule: the Tetrahymena ribozyme. By using segmentation-guided water and ion modelling (SWIM), an approach combining resolvability and chemical parameters, we automatically modelled and cross-validated water molecules and Mg 2+ ions in the ribozyme core, revealing the extensive involvement of water in mediating RNA non-canonical interactions. Unexpectedly, in regions where SWIM does not model ordered water, we observed highly similar densities in both cryo-EM maps. In many of these regions, the cryo-EM densities superimpose with complex water networks predicted by molecular dynamics, supporting their assignment as water and suggesting a biophysical explanation for their elusiveness to conventional atomic coordinate modelling. Our study demonstrates an approach to unveil both rigid and flexible waters that surround biomolecules through cryo-EM map densities, statistical and chemical metrics, and molecular dynamics simulations.

59 BASIC BIOLOGICAL SCIENCES↗

Communicate and Fuse: How Filamentous Fungi Establish and Maintain an Interconnected Mycelial Network

Cell-to-cell communication and cell fusion are fundamental biological processes across the tree of life. Survival is often dependent upon being able to identify nearby individuals and respond appropriately. Communication between genetically different individuals allows for the identification of potential mating partners, symbionts, prey, or predators. In contrast, communication between genetically similar (or identical) individuals is important for mediating the development of multicellular organisms or for coordinating density-dependent behaviors (i.e., quorum sensing). This review describes the molecular and genetic mechanisms that mediate cell-to-cell communication and cell fusion between cells of Ascomycete filamentous fungi, with a focus on Neurospora crassa . Filamentous fungi exist as a multicellular, multinuclear network of hyphae, and communication-mediated cell fusion is an important aspect of colony development at each stage of the life cycle. Asexual spore germination occurs in a density-dependent manner. Germinated spores (germlings) avoid cells that are genetically different at specific loci, while chemotropically engaging with cells that share identity at these recognition loci. Germlings with genetic identity at recognition loci undergo cell fusion when in close proximity, a fitness attribute that contributes to more rapid colony establishment. Communication and cell fusion also occur between hyphae in a colony, which are important for reinforcing colony architecture and supporting the development of complex structures such as aerial hyphae and sexual reproductive structures. Over 70 genes have been identified in filamentous fungi (primarily N. crassa ) that are involved in kind recognition, chemotropic interactions, and cell fusion. While the hypothetical signal(s) and receptor(s) remain to be described, a dynamic molecular signaling network that regulates cell-cell interactions has been revealed, including two conserved MAP-Kinase cascades, a conserved STRIPAK complex, transcription factors, a NOX complex involved in the generation of reactive oxygen species, cell-integrity sensors, actin, components of the secretory pathway, and several other proteins. Together these pathways facilitate the integration of extracellular signals, direct polarized growth, and initiate a transcriptional program that reinforces signaling and prepares cells for downstream processes, such as membrane merger, cell fusion and adaptation to heterokaryon formation.

Microbiology↗

The individual and collective effects of exact exchange and dispersion interactions on the ab initio structure of liquid water

In this work, we report the results of a series of density functional theory (DFT) based ab initio molecular dynamics (AIMD) simulations of ambient liquid water using a hierarchy of exchange-correlation (XC) functionals to investigate the individual and collective effects of exact exchange (Exx), via the PBE0 hybrid functional, non-local van der Waals/dispersion (vdW) interactions, via a fully self-consistent density-dependent dispersion correction, and an approximate treatment of nuclear quantum effects, via a 30 K increase in the simulation temperature, on the microscopic structure of liquid water. Based on these AIMD simulations, we found that the collective inclusion of Exx and vdW as resulting from a large-scale AIMD simulation of (H{sub 2}O){sub 128} significantly softens the structure of ambient liquid water and yields an oxygen-oxygen structure factor, S{sub OO}(Q), and corresponding oxygen-oxygen radial distribution function, g{sub OO}(r), that are now in quantitative agreement with the best available experimental data. This level of agreement between simulation and experiment demonstrated herein originates from an increase in the relative population of water molecules in the interstitial region between the first and second coordination shells, a collective reorganization in the liquid phase which is facilitated by a weakening of the hydrogen bond strength by the use of a hybrid XC functional, coupled with a relative stabilization of the resultant disordered liquid water configurations by the inclusion of non-local vdW/dispersion interactions. This increasingly more accurate description of the underlying hydrogen bond network in liquid water also yields higher-order correlation functions, such as the oxygen-oxygen-oxygen triplet angular distribution, P{sub OOO}(θ), and therefore the degree of local tetrahedrality, as well as electrostatic properties, such as the effective molecular dipole moment, that are in much better agreement with experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Scale-Dependent Fracture-Matrix Interactions and Their Impact on Radionuclide Transport: Development of efficient particle-tracking methods

Matrix Diffusion and Adsorption within a rock matrix are important mechanisms for retarding transport of radionuclides in fractured rock. Due to computational limitations and difficulties in characterizing complex subsurface systems, diffusive exchange between a fracture network and surrounding rock matrix is often modeled using simplified conceptual representations. There is significant uncertainty in “effective” parameters used in these models, such as the “effective matrix diffusivity”. Often, these parameters are estimated by fitting sparse breakthrough data, and estimated values fall outside meaningful ranges, because simplified interpretive models do not consider complex three-dimensional flow. There is limited understanding of the relationship between the effective parameters and rock mass characteristics including network structure and matrix properties. There is also evidence for an apparent scale-dependence in “effective matrix diffusion” coefficients. These observations raise questions on whether fracture-matrix interaction parameters estimated from small-scale tracer tests can be used for predicting radionuclide fate and transport at the scale of DOE field sites. High-resolution three-dimensional Discrete-Fracture-Network-Matrix (DFNM) models based on well-defined local scale transport equations can help to address some of these questions. Due to tremendous advances in computational technology over the last 10 years, DFNM modeling in relatively large domains is now feasible. The overarching objective of our research is to use DFNM modeling to improve fundamental understanding of how effective parameters in conceptual models are related to fracture network structure and matrix properties. An advanced three-dimensional DFNM model is being developed, which combines upscaled particle-tracking algorithms for fracture-matrix interaction and a parallel fracture-network flow simulator. The particle-tracking algorithms allow complexity in flow fields at different scales, and track transport across fracture-matrix interfaces based on rigorous local approximations to the transport equations. This modeling approach can incorporate aperture variability, multi-scale preferential flow and matrix heterogeneity. We developed efficient particle-tracking methods for handling matrix diffusion and adsorption on fracture walls and demonstrated their efficiency for use within the context of large-scale complex fracture network models with variability in apertures across a network of fractures and within individual fractures.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The Odd Power of Dispersion

In ancient China, water has been regarded as one of the five vital components of life. It has been observed that water has many fascinating properties: water is ‘soft’ yet it can penetrate a hard rock; water is ‘pure’ yet it can tolerate other beings. Because of its unique properties, water is often associated with good quality and has been given the highest praise by Laozi in his book Tao Te Ching saying: the highest/best quality that one can have is being like water. However, little did people understand why and how water possesses such fascinating properties. Modern scientific developments made people realize that the macroscopic liquid water is made of a large number of water molecules held together via a network of hydrogen bonds. And those wonderful properties of water are merely the macroscopic manifestations of the interactions between water molecules and other molecules. For example, the dissolving ability of water is due to the fact that the interaction between a water molecule and the other molecular species is stronger than the interactions among their own molecular species. In fact the interactions between any two molecules are governed by the same physics and are termed intermolecular interaction (or intermolecular forces in some literature, although technically ‘force’ is incorrect usage here). Although the very existence of the intermolecular interactions is easily proved, e.g. the mere presence of the solid phase of matter, and scientists today have recognized that the seemingly weak intermolecular interactions essentially hold the world together through a delicate and cooperative process, the theoretical understanding of various intermolecular interactions is still far from satisfactory. On the practical side, theoreticians need to balance computational cost and accuracy. Because of the relatively small magnitudes of the intermolecular interactions, errors that appear tiny compared to the usual chemical (covalent) bonding may change conclusions qualitatively. High-level ab initio methods including explicit description of electron correlation can achieve the desired accuracy at very high computational cost. (Chapter 5 and 6) However the cooperative network of hundreds of thousands of molecules that reflects the true power of intermolecular interactions cannot be modeled easily by ab initio methods. Deeper understanding of intermolecular interactions yields better theoretical models; better theoretical models facilitate and even deepen the understanding of intermolecular interactions. With the aforementioned motivation in mind, a significant portion of this dissertation is dedicated to developing a method to describe the intermolecular interactions accurately with affordable computational resources.

74 ATOMIC AND MOLECULAR PHYSICS↗

MO-DE-BRA-05: Developing Effective Medical Physics Knowledge Structures: Models and Methods

Purpose: Develop a method and supporting online resources to be used by medical physics educators for teaching medical imaging professionals and trainees so they develop highly-effective physics knowledge structures that can contribute to improved diagnostic image quality on a global basis. Methods: The different types of mental knowledge structures were analyzed and modeled with respect to both the learning and teaching process for their development and the functions or tasks that can be performed with the knowledge. While symbolic verbal and mathematical knowledge structures are very important in medical physics for many purposes, the tasks of applying physics in clinical imaging--especially to optimize image quality and diagnostic accuracy--requires a sensory conceptual knowledge structure, specifically, an interconnected network of visually based concepts. This type of knowledge supports tasks such as analysis, evaluation, problem solving, interacting, and creating solutions. Traditional educational methods including lectures, online modules, and many texts are serial procedures and limited with respect to developing interconnected conceptual networks. A method consisting of the synergistic combination of on-site medical physics teachers and the online resource, CONET (Concept network developer), has been developed and made available for the topic Radiographic Image Quality. This was selected as the inaugural topic, others to follow, because it can be used by medical physicists teaching the large population of medical imaging professionals, such as radiology residents, who can apply the knowledge. Results: Tutorials for medical physics educators on developing effective knowledge structures are being presented and published and CONET is available with open access for all to use. Conclusion: An adjunct to traditional medical physics educational methods with the added focus on sensory concept development provides opportunities for medical physics teachers to share their knowledge and experience at a higher cognitive level and produce medical professionals with the enhanced ability to apply physics to clinical procedures.

60 APPLIED LIFE SCIENCES↗

Improving Physics Based Electron Neutrino Appearance Identication with a Long Short-Term Memory Network

The NOvA experiment is a long baseline neutrino oscillation experiment with the objective to measure the oscillation probability of muon type neutrinos ($\nu_{\mu}$) into electron type neutrinos ($\nu_e$). NOvA measures the interactions of neutrinos from the NuMI beam in two functionally identical liquid scintillator detectors. The far detector detects the appearance of electron neutrinos, leading to measurement of the oscillation parameters under study. Using an off -axis beam with an 810 km baseline length, NOvA is sensitive to measuring the neutrino mass hierarchy, the CP violating parameter, and the octant of the mixing angle, $\theta_{23}$. The data presented in this thesis has been collected from October 2013 until May 2018. The first NOvA $\nu_e$ charged current identifier utilized an artificial neural network with the physical features of the highest energy reconstructed shower as inputs. The $\nu_ e$ charged current identifier in this thesis utilizes a Long Short-Term Memory network with the physical features of every reconstructed shower in a particular interaction. In addition to the Long Short-Term Memory network, there are two Boosted Decision Trees to assist in event level selection. In the analysis of the data, 54 $\nu_e$ candidate events were detected with an expected background of 15 events. The results of this analysis prefer the normal mass hierarchy with maximal mixing and $\frac{\delta_{CP}}{\pi}=1.92_{-1.19}^{0.08}$. Results from this analysis differ from the published NOvA analysis, due to the differences of electron identification techniques.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Interactive Visual Study of Multiple Attributes Learning Model of X-Ray Scattering Images

Existing interactive visualization tools for deep learning are mostly applied to the training, debugging, and refinement of neural network models working on natural images. However, visual analytics tools are lacking for the specific application of x-ray image classification with multiple structural attributes. In this paper, we present an interactive system for domain scientists to visually study the multiple attributes learning models applied to x-ray scattering images. It allows domain scientists to interactively explore this important type of scientific images in embedded spaces that are defined on the model prediction output, the actual labels, and the discovered feature space of neural networks. Users are allowed to flexibly select instance images, their clusters, and compare them regarding the specified visual representation of attributes. The exploration is guided by the manifestation of model performance related to mutual relationships among attributes, which often affect the learning accuracy and effectiveness. The system thus supports domain scientists to improve the training dataset and model, find questionable attributes labels, and identify outlier images or spurious data clusters. Case studies and scientists feedback demonstrate its functionalities and usefulness.

97 MATHEMATICS AND COMPUTING↗

Investigation of structural changes in chiral magnet Cr{sub 1∕3}NbS{sub 2} under application of pressure

We perform structural analysis experiments on the chiral magnet Cr{sub 1∕3}NbS{sub 2}, in which Cr{sup 3+} ions are inserted between hexagonal NbS{sub 2} layers. The noncentrosymmetrical nature of the inserted Cr{sup 3+} appears as a distorted CrS{sub 6} octahedron. Under the application of hydrostatic pressure, the lattice shrinks significantly along the c-axis rather than the a-axis. However, at a pressure P of approximately 3–4 GPa, a kink in the rate of decrease in the lattice parameters is observed, and the slight movement of a Nb atom along the c-axis brings about a decrease in the distortion of the CrS{sub 6} octahedron. This structural change qualitatively suggests a decrease in the strength of the Dzyaloshinskii-Moriya (D-M) interaction. Under hydrostatic pressure, the magnetic ordering temperature T{sub C} decreases, and dT{sub C}/dP exhibits a slight change at around 3 GPa. A series of experiments indicates that the change in the structural symmetry of the CrS{sub 6} octahedron influences the exchange network between Cr{sup 3+} ions as well as the D-M interaction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Plant–microbe networks in soil are weakened by century-long use of inorganic fertilizers

Understanding the changes in plant-microbe interactions is critically important for predicting ecosystem functioning in response to human-induced environmental changes such as nitrogen (N) addition. In this study, the effects of a century-long fertilization treatment (> 150 years) on the networks between plants and soil microbial functional communities, detected by GeoChip, in grassland were determined in the Park Grass Experiment at Rothamsted Research, UK. Our results showed that plants and soil microbes have a consistent response to long-term fertilization-both richness and diversity of plants and soil microbes are significantly decreased, as well as microbial functional genes involved in soil carbon (C), nitrogen (N) and phosphorus (P) cycling. The network-based analyses showed that long-term fertilization decreased the complexity of networks between plant and microbial functional communities in terms of node numbers, connectivity, network density and the clustering coefficient. Similarly, within the soil microbial community, the strength of microbial associations was also weakened in response to long-term fertilization. Mantel path analysis showed that soil C and N contents were the main factors affecting the network between plants and microbes. Our results indicate that century-long fertilization weakens the plant-microbe networks, which is important in improving our understanding of grassland ecosystem functions and stability under long-term agriculture management.

59 BASIC BIOLOGICAL SCIENCES↗

NoRA: A Tensor Network Ansatz for Volume-Law Entangled Equilibrium States of Highly Connected Hamiltonians

Motivated by the ground state structure of quantum models with all-to-all interactions such as mean-field quantum spin glass models and the Sachdev-Ye-Kitaev (SYK) model, we propose a tensor network architecture which can accomodate volume law entanglement and a large ground state degeneracy. We call this architecture the non-local renormalization ansatz (NoRA) because it can be viewed as a generalization of MERA, DMERA, and branching MERA networks with the constraints of spatial locality removed. We argue that the architecture is potentially expressive enough to capture the entanglement and complexity of the ground space of the SYK model, thus making it a suitable variational ansatz, but we leave a detailed study of SYK to future work. We further explore the architecture in the special case in which the tensors are random Clifford gates. Here the architecture can be viewed as the encoding map of a random stabilizer code. We introduce a family of codes inspired by the SYK model which can be chosen to have constant rate and linear distance at the cost of some high weight stabilizers. We also comment on potential similarities between this code family and the approximate code formed from the SYK ground space.

Physics↗