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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Data for High Yield Production of 3-Hydroxypropionic Acid Using Issatchenkia orientalis

Biomanufacturing provides a more sustainable alternative to fossil-based chemical manufacturing. 3-Hydroxypropionic acid (3HP) is a top Department of Energy value-added chemical and precursor to bioplastics, yet cost-effective microbial production remains elusive. Here, we establish the acid-tolerant yeast Issatchenkia orientalis as a robust host for low-pH 3HP biosynthesis. Genome-scale modeling identifies the β-alanine pathway as optimal, offering the highest theoretical yield and lowest oxygen requirement. Thermodynamic analysis confirms its favorability under acidic conditions. Using sequence similarity network analysis, we discover highly active aspartate 1-decarboxylase (PAND), β-alanine-pyruvate aminotransferase (BAPAT), and 3HP dehydrogenase (YDFG), which significantly improve the pathway efficiency. Next, to further elevate the production, pathway optimization through multi-copy PAND integration, byproduct elimination (knockouts of pyruvate decarboxylase and glycerol-3-phosphate dehydrogenase), and reinforcement of aspartate flux by overexpression of pyruvate carboxylase and aspartate amino transferase improves the titer to 29 g/L in shake flasks. Fed-batch fermentation at pH 4 with low-cost corn steep liquor medium further increases the production to 92 g/L with 0.7 g/g yield and 0.55 g/L/h productivity. Techno-economic analysis indicates that such performance could potentially enable a financially viable process for sustainable acrylic acid production. This work establishes I. orientalis as a next-generation platform for cost-effective 3HP production and paves the way toward industrial commercialization.

Bioproducts↗
DOE OSTI2022

Cloud-Control of Legacy Building Automation System: A case study

As Internet of Things devices and cloud-based platforms become more mature, Energy Management and Information Systems (EMIS) are increasingly gaining momentum in the building industry. In large commercial buildings, Fault-Detection and Diagnostic (FDD) and energy information systems (EIS) are now established technologies with tens of providers and thousands of deployment sites across North America. The new frontier for the EMIS technology is now represented by control systems that use advanced system optimization (ASO) methods to improve the operations of the HVAC system. Given the complexity of the integration of such systems with the existing building automation systems (BAS) and the higher risk involved with direct control of the HVAC, these systems are still emerging in the market. This paper presents the results of a project in which a start-up company partnered with a research institution to develop a cloud-based software EMIS solution and deployed it in a university campus in California. The software system included advanced sensing, data acquisition, storage and advanced control and analytics applications developed on top of the native BAS. The new platform controls ten buildings on the campus and the FDD and the ASO applications deployed on this platform were able to generate energy savings of up to 35% and 25% in certain buildings for each functionality respectively. Where the platform did not save energy, it improved building service (air quality). Lessons learned include the importance of collaborating with and training the building operators and evaluating whether the legacy system can work reliably with the new technology.

Prakash, Anand Krishnan↗
DOE OSTI2024

Untargeted Spatial Metabolomics and Spatial Proteomics on the Same Tissue Section

An increasing number of spatial multiomic workflows have been recently developed. Some of these approaches have leveraged initial mass spectrometry imaging (MSI)-based spatial metabolomics to inform region of interest (ROI) selection for downstream spatial proteomics. However, these workflows have been limited by varied substrate requirements between modalities or have required analyzing serial sections (i.e., one section per modality). To mitigate these issues, we present a novel multiomic workflow that uses desorption electrospray ionization (DESI)-MSI to identify representative spatial metabolite patterns on-tissue prior to spatial proteomic analyses on the same tissue section. Further, this workflow is demonstrated here with a model mammalian tissue (coronal rat brain section) mounted on a polyethylene naphthalate-membrane slide. Initial DESI-MSI resulted in 160 annotations (SwissLipids) within to the METASPACE platform (≤20% false discovery rate). A segmentation map from the annotated ion images informed downstream ROI selection for spatial proteomics characterization from the same sample. The unspecific substrate requirements and minimal sample disruption inherent to DESI-MSI allowed for an optimized, downstream spatial proteomics assay, resulting in 3888 ± 240 to 4717 ± 48 proteins being confidently directed per ROI (200 µm x 200 µm). Finally, we demonstrate the integration of multiomic information, where we found ceramide localization to be correlated with SMPD3 abundance (ceramide synthesis protein), and we also utilized protein abundance to resolve metabolite isomeric ambiguity. Overall, the integration of DESI-MSI into the multiomic workflow allows for complementary spatial and molecular-level information to be achieved from optimized implementations of each MS assay inherent to the workflow itself.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Ultralow-threshold, continuous-wave upconverting lasing from subwavelength plasmons

Miniaturized lasers are an emerging platform for generating coherent light for quantum photonics, in vivo cellular imaging, solid-state lighting and fast three-dimensional sensing in smartphones. Continuous-wave lasing at room temperature is critical for integration with opto-electronic devices and optimal modulation of optical interactions. Plasmonic nanocavities integrated with gain can generate coherent light at subwavelength scales, beyond the diffraction limit that constrains mode volumes in dielectric cavities such as semiconducting nanowires. However, insufficient gain with respect to losses and thermal instabilities in nanocavities has limited all nanoscale lasers to pulsed pump sources and/or low-temperature operation. Here, we show continuous-wave upconverting lasing at room temperature with record-low thresholds and high photostability from subwavelength plasmons. We achieve selective, single-mode lasing from Yb 3+ /Er 3+ -co-doped upconverting nanoparticles conformally coated on Ag nanopillar arrays that support a single, sharp lattice plasmon cavity mode and greater than wavelength λ/20 field confinement in the vertical dimension. The intense electromagnetic near-fields localized in the vicinity of the nanopillars result in a threshold of 70 W cm -2 , orders of magnitude lower than other small lasers. Our plasmon-nanoarray upconverting lasers provide directional, ultra-stable output at visible frequencies under near-infrared pumping, even after six hours of constant operation, which offers prospects in previously unrealizable applications of coherent nanoscale light.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Benchmarking Quantum Simulators Using Ergodic Quantum Dynamics

Here we propose and analyze a sample-efficient protocol to estimate the fidelity between an experimentally prepared state and an ideal target state, applicable to a wide class of analog quantum simulators without advanced spatiotemporal control. Our protocol relies on universal fluctuations emerging from generic Hamiltonian dynamics, which we discover in the present work. It does not require fine-tuned control over state preparation, quantum evolution, or readout capability, while achieving near optimal sample complexity: a percent-level precision is obtained with ~103 measurements, independent of system size. Furthermore, the accuracy of our fidelity estimation improves exponentially with increasing system size. We numerically demonstrate our protocol in a variety of quantum simulator platforms, including quantum gas microscopes, trapped ions, and Rydberg atom arrays. We discuss applications of our method for tasks such as multiparameter estimation of quantum states and processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Big Data Analysis of Massive PMU Datasets: A Data Platform Perspective

The discovery of `event signatures' and useful insights from very large historical Phasor Measurement Unit (PMU) datasets is predicated on offline Big Data analysis approaches that rely on the generation of predictive features on a massive scale. This paper presents lessons learned from a data platform perspective towards reducing barriers to adoption of Big Data analytics against a real dataset of almost half a trillion data points drawn from over 400 PMUs distributed across the North American power grid. We demonstrate software abstractions and targeted performance optimizations that can lead to significant productivity gains for power systems researchers seeking to perform offline exploratory temporal analysis and modeling tasks, with a focus on feature generation. We describe how our optimized approach goes beyond a naive application of mainstream Big Data technologies, enabling feature generation tasks, that previously took days or even weeks, to now be completed in just a few hours.

Kumar, Vijay S.↗
DOE OSTI2014

SU-E-T-279: Realization of Three-Dimensional Conformal Dose Planning in Prostate Brachytherapy

Purpose: Successful clinical treatment in prostate brachytherapy is largely dependent on the effectiveness of pre-surgery dose planning. Conventional dose planning method could hardly arrive at a satisfy result. In this abstract, a three-dimensional conformal localized dose planning method is put forward to ensure the accuracy and effectiveness of pre-implantation dose planning. Methods: Using Monte Carlo method, the pre-calculated 3-D dose map for single source is obtained. As for multiple seeds dose distribution, the maps are combined linearly to acquire the 3-D distribution. The 3-D dose distribution is exhibited in the form of isodose surface together with reconstructed 3-D organs group real-timely. Then it is possible to observe the dose exposure to target volume and normal tissues intuitively, thus achieving maximum dose irradiation to treatment target and minimum healthy tissues damage. In addition, the exfoliation display of different isodose surfaces can be realized applying multi-values contour extraction algorithm based on voxels. The needles could be displayed in the system by tracking the position of the implanted seeds in real time to conduct block research in optimizing insertion trajectory. Results: This study extends dose planning from two-dimensional to three-dimensional, realizing the three-dimensional conformal irradiation, which could eliminate the limitations of 2-D images and two-dimensional dose planning. A software platform is developed using VC++ and Visualization Toolkit (VTK) to perform dose planning. The 3-D model reconstruction time is within three seconds (on a Intel Core i5 PC). Block research could be conducted to avoid inaccurate insertion into sensitive organs or internal obstructions. Experiments on eight prostate cancer cases prove that this study could make the dose planning results more reasonable. Conclusion: The three-dimensional conformal dose planning method could improve the rationality of dose planning by safely reducing the large target margin and avoiding dose dead zones for prostate cancer treatment. 1) National Natural Science Foundation of People's Republic of China (No. 51175373); 2) New Century Educational Talents Plan of Chinese Education Ministry (NCET-10-0625); 3) Scientific and Technological Major Project, Tianjin (No. 12ZCDZSY10600)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]

The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.

Guerra Fernandez, Omar Jose↗
DOE OSTI2016

Novus: An Unmanned Aerial System and Virtual Reality Flight Deck for Data Collection and Visualization

Many emerging technologies offer tremendous new capabilities that will, without question, redefine how we interact with, utilize, understand, and optimize the energy systems around us. Drones offer a new ability to remotely capture data in ways that have previously been impractical. However, their flight control systems remain rudimentary and limit the ability of researchers to fully take advantage of these platforms as remote sensing devices. In this project, we constructed a hexarotor drone and outfitted it with advanced (yet inexpensive) sensors as well as a telemetry data management and control package. We then created a virtual reality flight deck that allows a drone operator to define waypoints "on-the-fly" or take manual control over flight operations. The flight deck provides a live on-board video stream display, a 3-dimensional topographic map with the drone’s position in space overlaid onto it, as well as a data visualization framework that keeps critical information immediately available to the operator. These advances provide a new platform for scientific data collection such as thermography of building envelopes or solar arrays. As the drone is in flight and data are being collected, these data are relayed to the virtual reality environment where they can be inspected for integrity and the flight plan altered if necessary to collect higher quality data. Future work will focus on implementing 3-dimensional mapping using both visible and thermal imagery collected from the drone, and streaming those into the virtual reality flight deck in real time.

Source record↗
DOE OSTI2022

NREL's Advanced Distribution Management System (ADMS) Test Bed

Transform utility electric distribution management systems to enable the integration and management of all assets and functions across the utility enterprise regardless of vendor or technology. Four program areas: Platform: Develop an open-source platform; evaluate advanced applications. Test bed: Build a vendor-neutral test bed to evaluate existing and future advanced distribution management system (ADMS) functionalities in a realistic setting. Applications: Develop an initial suite of ADMS applications. Advanced control: Develop new integrated optimization and control solutions.

ADMS test bed↗
DOE OSTI2020

Accelerating Parallel Applications in Cloud Platforms via Adaptive Time-Slice Control

Cloud platforms can provide flexible and cost-effective environments for parallel applications. However, the resource over-commitment issues, i.e., cloud providers often provide much more executable virtual CPUs than available physical CPUs, still impede the synchronization operations of parallel applications, causing severe performance degradation. Existing methods optimize parallel applications by promoting the priorities of involved VMs. They cannot fully explore the performance of parallel applications, because they ignore the time-slice requirements of different phases of parallel applications. Furthermore, non-parallel applications experience unsatisfied performance because of low scheduling priorities. Given empirical analysis on time-slices of virtual machines (VMs), we find that shortening time-slices can mitigate synchronization overhead which incurs during communication phases, while over-short time-slices cause frequent cache misses in computation phases. Accordingly, we propose an Adaptive Time-slice Control (ATC) mechanism. ATC first detects the phases of parallel applications based on lock latency or cache misses. Then, ATC shortens time-slices during communication phases and prolongs time-slices during computation phases for parallel applications, and sets a uniform time-slice for non-parallel applications. Finally, we evaluate ATC using seven well-known benchmarks with 25+ applications. Experiments show that ATC obtains 1.5-75x performance gain for running parallel applications than state-of-the-art solutions, with nearly unaffected impact on non-parallel applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Investigation of Portable Event-Based Monte Carlo Transport Using the NVIDIA Thrust Library

Power consumption considerations are driving future high performance computing platforms toward many-core computing architectures. Los Alamos National Laboratory's Trinity machine, available in 2016, will use both Intel Xeon Haswell processors and Intel Xeon Phi Knights Landing many integrated core (MIC) architecture coprocessors. Lawrence Livermore National Laboratory's Sierra machine, available in 2018, will use an IBM PowerPC architecture along with Nvidia graphics processing unit (GPU) architecture accelerators. These different advanced architectures make the computing landscape in upcoming years complex. Traditional approaches to Monte Carlo transport do not work efficiently on these new computing platforms. MIC architectures require vectorization to operate efficiently, and vectorization is difficult to achieve in Monte Carlo transport. GPU architectures require additional code to explicitly use the hardware, requiring significant code changes or hardware specific branches in the source code. A significant challenge for Monte Carlo transport projects is to simultaneously support within a single source code base efficient simulations for both the current generation of architectures and the different advanced computing architectures. In order to address these challenges, two important changes are typically required: a new algorithmic approach for solving Monte Carlo transport, and explicit use of hardware specific software. In this paper, we describe initial research investigations of an event-based Monte Carlo transport algorithm implemented using the Nvidia Thrust library on a GPU for a Monte Carlo test code. The event-based algorithm targets many-core architectures by increasing SIMD (single instruction multiple data) parallelism, while Thrust potentially provides portable performance by allowing one source code base to compile code targeted for both CPUs and GPUs. We described preliminary investigations of portable event-based Monte Carlo algorithms implemented using the Nvidia Thrust library in a research Monte Carlo test code. We found that an explicit CUDA implementation of an event-based Monte Carlo algorithm performed significantly more efficiently than a Thrust implementation on GPU platforms, most likely as a result of additional flexibility in access to different memory spaces on the GPU. Additionally, we showed that on GPU platforms and at large enough problem sizes the event-based implementations perform more efficiently than the serial history-based implementation running on the host CPU. While investigating this problem, we also discovered that the performance of the event-based algorithm is affected by what tallies are being used. A zonal scalar flux tally requires atomic operations that significantly impacted the performance of the code, in some cases producing slowdowns instead of speedups. We decided to remove the tally in order to focus on the effectiveness of the event-based algorithm. Future work will be required to research more effective ways of handling such tallies. Additionally, we would like to consider new ways for optimizing both the Thrust and CUDA versions, in order to see how much performance we have yet to achieve. The potential trade-off between portability and performance was demonstrated in this investigation. Thrust provides both CPU and GPU versions of the code in one code base, but it does so at a cost. We discovered approximately a factor of 2-5 performance difference between Thrust and CUDA on each GPU platform we tested. Thrust provides a tool to access the GPUs with less effort and specialization, but it does so by giving up fine grained control where extra performance can be found for this application. Future work will be required to determine whether this performance differential between Thrust and CUDA can be reduced for event-based Monte Carlo transport. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Evolutionary Optimization of a Charge Transfer Ionic Potential Model for Ta/Ta-Oxide Heterointerfaces

Heterostructures of tantalum and its oxide are of tremendous technological interest for a myriad of technological applications, including electronics, thermal management, catalysis and biochemistry. In particular, local oxygen stoichiometry variation in TaO x memristors comprising of thermodynamically stable metallic (Ta) and insulating oxide (Ta 2 O 5 ) have been shown to result in fast switching on the subnanosecond timescale over a billion cycles. This rapid switching opens up the potential for advanced functional platforms such as stateful logic operations and neuromorphic computation. Despite its broad importance, an atomistic scale understanding of oxygen stoichiometry variation across Ta/TaO x heterointerfaces, such as during early stages of oxidation and oxide growth, is not well understood. This is mainly due to the lack of a unified interatomic potential model for tantalum oxides that can accurately describe metallic (Ta), ionic (TaO x ) as well as mixed (Ta/TaO x interfaces) bonding environments simultaneously. To address this challenge, we introduce a Charge Transfer Ionic Potential (CTIP) model for Ta/Ta-oxide system by training against lattice parameters, cohesive energies, equations of state (EOS), elastic properties, and surface energies of the various experimentally observed Ta 2 O 5 polymorphs (hexagonal, orthorhombic and monoclinic) obtained from density functional theory (DFT) calculations. The best CTIP parameters are determined by employing a global optimization scheme driven by genetic algorithms followed by local Simplex optimization. Our newly developed CTIP potential accurately predicts structure, thermodynamics, energetic ordering of polymorphs, as well as elastic and surface properties of both Ta and Ta 2 O 5 , in excellent agreement with DFT calculations and experiments. We employ our newly parameterized CTIP potential to investigate the early stages of oxidation and atomic scale mechanisms associated with oxide growth on Ta surface at various temperatures. Furthermore, the CTIP potential developed in this work is an invaluable tool to investigate atomic-scale mechanisms and transport phenomena underlying the response of Ta/TaO x interfaces to external stimuli (e.g, temperature, pressure, strain, electric field etc.), as well as other interesting dynamical phenomena including the physics of switching dynamics in TaO x based memristors and neuromorphic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

SU-E-T-500: Initial Implementation of GPU-Based Particle Swarm Optimization for 4D IMRT Planning in Lung SBRT

Purpose 4D-IMRT planning, combined with dynamic MLC tracking delivery, utilizes the temporal dimension as an additional degree of freedom to achieve improved OAR-sparing. The computational complexity for such optimization increases exponentially with increase in dimensionality. In order to accomplish this task in a clinically-feasible time frame, we present an initial implementation of GPU-based 4D-IMRT planning based on particle swarm optimization (PSO). Methods The target and normal structures were manually contoured on ten phases of a 4DCT scan of a NSCLC patient with a 54cm3 right-lower-lobe tumor (1.5cm motion). Corresponding ten 3D-IMRT plans were created in the Eclipse treatment planning system (Ver-13.6). A vendor-provided scripting interface was used to export 3D-dose matrices corresponding to each control point (10 phases × 9 beams × 166 control points = 14,940), which served as input to PSO. The optimization task was to iteratively adjust the weights of each control point and scale the corresponding dose matrices. In order to handle the large amount of data in GPU memory, dose matrices were sparsified and placed in contiguous memory blocks with the 14,940 weight-variables. PSO was implemented on CPU (dual-Xeon, 3.1GHz) and GPU (dual-K20 Tesla, 2496 cores, 3.52Tflops, each) platforms. NiftyReg, an open-source deformable image registration package, was used to calculate the summed dose. Results The 4D-PSO plan yielded PTV coverage comparable to the clinical ITV-based plan and significantly higher OAR-sparing, as follows: lung Dmean=33%; lung V20=27%; spinal cord Dmax=26%; esophagus Dmax=42%; heart Dmax=0%; heart Dmean=47%. The GPU-PSO processing time for 14940 variables and 7 PSO-particles was 41% that of CPU-PSO (199 vs. 488 minutes). Conclusion Truly 4D-IMRT planning can yield significant OAR dose-sparing while preserving PTV coverage. The corresponding optimization problem is large-scale, non-convex and computationally rigorous. Our initial results indicate that GPU-based PSO with further software optimization can make such planning clinically feasible. This work was supported through funding from the National Institutes of Health and Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Overview of the KSTAR experiments and future plan

The Korea Superconducting Tokamak Advanced Research (KSTAR) device has recently entered a new phase of operation following the installation of a tungsten mono-block divertor, providing a unique platform to investigate high-performance, long-pulse plasma scenarios for future reactors. The 2023–2024 experimental campaigns demonstrated significant progress in commissioning the tungsten divertor, developing plasma operation scenarios, and achieving real-time control. Comparative studies revealed increased core radiation losses and associated performance degradation relative to the carbon divertor environment. Alleviation strategies, such as optimized neutral beam injection timing, boron powder seeding, and impurity control through gas puffing, were shown to reduce tungsten accumulation and extend high-performance phases, including record H-mode operation exceeding 100 s. International collaboration enabled the first demonstration of high poloidal beta scenarios with an internal transport barrier on KSTAR. Advances in control included upgraded real-time resonant magnetic perturbation schemes and disruption forecasting. Furthermore, divertor detachment control using a new surrogate-model-based approach with real-time radiation imaging demonstrated active impurity and heat flux management. Supported by enhanced heating, current drive, and diagnostic systems, these achievements offer valuable insights into tungsten impurity behavior, transport physics, and control strategies for future reactors including ITER. Planned upgrades toward a full-tungsten wall and ITER-aligned real-time plasma control will further establish KSTAR as a leading experimental platform for developing operational scenarios required to achieve steady-state, burning plasma conditions.

KSTAR↗
DOE OSTI2020

PLATFORM for Product Launch

Pecan Street Inc. (PSI) and its partners set out in 2017 to validate the PLATFORM for Product Launch, a new model for improving the effectiveness of investments in clean energy technologies and accelerating market entry of disruptive technologies. In partnership with a newly formed Innovation Advisory Council, PSI recruited fourteen companies with new hardware-based technologies that enable or create clean energy opportunities. Pecan Street carried out product evaluations and conducted market research with stakeholders and target customers to develop recommendations on product optimization opportunities for all companies, and created third party performance evaluation reports that include environmental metrics, such as water and energy savings potential, to assist in creating investment confidence and to unlock additional sources of funding, such as impact investments. Pecan Street set-up the product testing environment, performed small-batch field testing, and provided a verified third-party performance report on the product of twelve companies. PSI Street and its partners leveraged the performance evaluations and insights from the newly formed PRI toolkit to raise over $1.5M across five companies, and garner interest for private sector adoption of the PLATFORM for Product Launch.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Study of an Integration Platform Based on an Adiabatic Active-Layer Waveguide Connection for InP Photonic Device Integration Mirroring That of Heterogeneous Integration on Silicon

In this work, a photonic device integration platform capable of integration of active-passive InP-based photonic devices without the use of material regrowth is introduced. The platform makes use of an adiabatic active-layer waveguide connection (ALWC) to move an optical beam between active and passive devices. The performance of this platform is analyzed using an example made up of four main sections: (1) a fiber coupling section for enabling vertical beam coupling from optical fiber into the photonic chip using a mode-matched surface grating with apodized duty cycles; (2) a transparent waveguide section for realizing passive photonic devices; (3) an adiabatic mode connection structure for moving the optical beam between passive and active device sections; and (4) an active device section for realizing active photonic devices. It is shown that the coupled surface grating, when added with a bottom gold reflector, can achieve a high chip-to-fiber coupling efficiency (CE) of 88.3% at 1550 nm. The adiabatic active-layer mode connection structure has an optical loss of lower than 1% (CE > 99%). The active device section can achieve an optical gain of 20 dB/mm with the use of only 3 quantum wells. The optimized structural parameters of the entire waveguide module are analyzed and discussed.

42 ENGINEERING↗
DOE OSTI2017

Forward Modeling of Large-scale Structure: An Open-source Approach with Halotools

Here, we present the first stable release of Halotools (v0.2), a community-driven Python package designed to build and test models of the galaxy-halo connection. Halotools provides a modular platform for creating mock universes of galaxies starting from a catalog of dark matter halos obtained from a cosmological simulation. The package supports many of the common forms used to describe galaxy-halo models: the halo occupation distribution (HOD), the conditional luminosity function (CLF), abundance matching, and alternatives to these models that include effects such as environmental quenching or variable galaxy assembly bias. Satellite galaxies can be modeled to live in subhalos, or to follow custom number density profiles within their halos, including spatial and/or velocity bias with respect to the dark matter profile. Here, the package has an optimized toolkit to make mock observations on a synthetic galaxy population, including galaxy clustering, galaxy-galaxy lensing, galaxy group identification, RSD multipoles, void statistics, pairwise velocities and others, allowing direct comparison to observations. Halotools is object-oriented, enabling complex models to be built from a set of simple, interchangeable components, including those of your own creation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗