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At least 289 records · Page 16

Distribution Feeder-Scale Fast Frequency Response via Optimal Coordination of Net-load Resources Part II: Large-Scale Demonstration

This work is the second of a two-part series in which we develop and experimentally demonstrate a hierarchical control solution for optimally coordinating thousands of deferrable loads and distributed energy resources (DERs) to provide fast frequency response (FFR) from an entire distribution feeder. In Part I, we developed and proved practical algorithms for fast, cost-based optimal dispatch and for determining the optimal amount of headroom to operate solar inverters with to support FFR dispatch while minimizing opportunity cost. Simulation results in Part I demonstrated the advantages of the hierarchical dispatch approach in being able to maintain fast solution times needed for FFR even when the problem size increases. In Part II, we implement the algorithms developed in Part I in a novel, large-scale power hardware-in-the-loop experiment including embedded controllers and more than 100 powered appliance loads and DER connected to a simulated real-world distribution system with more than 10,000 controlled devices. Experimental results from multiple scenarios confirm that the optimal FFR dispatch approach scales well and can optimally coordinate more than 10,000 net-load resources across a distribution network while achieving hardware response times within 500 ms, which is not possible using state-of-the-art optimal coordination approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Laser-driven, ion-scale magnetospheres in laboratory plasmas. II. Particle-in-cell simulations

Ion-scale magnetospheres have been observed around comets, weakly magnetized asteroids, and localized regions on the Moon and provide a unique environment to study kinetic-scale plasma physics, in particular in the collision-less regime. In this work, we present the results of particle-in-cell simulations that replicate recent experiments on the large plasma device at the University of California, Los Angeles. Using high-repetition rate lasers, ion-scale magnetospheres were created to drive a plasma flow into a dipolar magnetic field embedded in a uniform background magnetic field. The simulations are employed to evolve idealized 2D configurations of the experiments, study highly resolved, volumetric datasets, and determine the magnetospheric structure, magnetopause location, and kinetic-scale structures of the plasma current distribution. We show the formation of a magnetic cavity and a magnetic compression in the magnetospheric region, and two main current structures in the dayside of the magnetic obstacle: the diamagnetic current, supported by the driver plasma flow, and the current associated with the magnetopause, supported by both the background and driver plasmas with some time-dependence. From multiple parameter scans, we show a reflection of the magnetic compression, bounded by the length of the driver plasma, and a higher separation of the main current structures for lower dipolar magnetic moments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Enhanced upconversion and photoconductive nanocomposites of lanthanide-doped nanoparticles functionalized with low-vibrational-energy inorganic ligands

Upconverting nanoparticles (UCNPs) convert near-infrared (IR) light into higher-energy visible light, allowing them to be used in applications such as biological imaging, nano-thermometry, and photodetection. It is well known that the upconversion luminescent efficiency of UCNPs can be enhanced by using a host material with low phonon energies, but the use of low-vibrational-energy inorganic ligands and non-epitaxial shells has been relatively underexplored. Here, we investigate the functionalization of lanthanide-doped NaYF4 UCNPs with low-vibrational-energy Sn2S64- ligands. Raman spectroscopy and elemental mapping are employed to confirm the binding of Sn2S64- ligands to UCNPs. This binding enhances upconversion efficiencies up to a factor of 16, consistent with an increase in the luminescent lifetimes of the lanthanide ions. Annealing Sn2S64--capped UCNPs results in the formation of a nanocomposite comprised of UCNPs embedded within an interconnected matrix of SnS2, enabling each UCNP to be electrically accessible through the semiconducting SnS2 matrix. This facilitates the integration of UCNPs into electronic devices, which we demonstrate through the fabrication of a UCNP-SnS2 photodetector that detects UV and near-IR light. Our findings show the promise of using inorganic capping agents to enhance the properties of UCNPs while facilitating their integration into optoelectronic devices.

Pan, Jia-Ahn↗

Securing Solar for the Grid: Extreme Control Whitepaper

Emerging standards outlining desired behaviors for Distributed Energy Resources (DER), such as IEEE 1547-2018, define several device-level control functions to regulate DER power injections/consumptions in response to locally sensed grid conditions. The ability to adjust settings of aggregations of DER with standardized embedded control functionality constitutes a mechanism which can, potentially, create undesirable or deleterious effects on the power grid. The purpose of this white paper is to highlight unintended effects stemming from improperly tuned embedded control functions in Distributed Energy Resources (DER), which could be exploited by a malicious entity as a means to attack the power grid.

14 SOLAR ENERGY↗

Active Aerodynamic Load Control for Wind Turbines

The goal of this project was to develop and demonstrate an advanced dielectric barrier discharge (DBD) plasma actuator technology. We set out to demonstrate the efficacy and impact of the new actuator technology as a key component of an active load control system for wind turbines. A DBD plasma actuator consists of a thin layer of dielectric material separating a pair of offset electrodes. One of those electrodes is embedded between the dielectric layer and a non-conductive substrate, while the other is exposed to air. When driven by an appropriate high voltage waveform, the device ionizes the air near the surface of the dielectric and adjacent to the exposed electrode. Collisions between the ions in the plasma and neutral air molecules result in a wall-jet – a region of induced air velocity that can be used to modify the flow around a lifting body. Use of the device near the trailing edge of a wind turbine blade, designed in such a way as to amplify the effects of the flow-modifying device, can result in large changes to the global forces experienced by the blade. Because of the fast response time of the device, it can allow the turbine to react in real time to changes in the wind associated with turbulence, wind shear, gusts, and the like, when paired with appropriate sensors and control algorithms. The goal of this project was to increase the capacity of the device to induce velocity on its surface at the levels required by large, utility-scale wind turbines. The first technical goal was to increase the induced velocity from the current industry-best of about 4 m/s to 10 m/s by modifying the electrical waveform used to drive the device and by introducing a semi-conductive surface coating to control electrostatic charge build-up on the surface. The second goal was to use the device to modify the lift on a representative airfoil in a wind tunnel, demonstrating a reduction in lift coefficient of 0.2 or better. The third goal was to produce an actuator-induced velocity of 20 m/s. Alongside our partners at the University of Texas at Dallas, we also applied modern, advanced design methods to optimize the impact of the technology on the design of wind turbines. We also had planned to install a segmented, active load control system on a test turbine to demonstrate the ability to reduce unsteady aerodynamic forces on the turbine associated with changes in the wind. The highest induced velocity achieved during this research was 11 m/s. However, practical design constraints limited the change in lift coefficient to about 0.12 for a representative airfoil in the wind tunnel at a Reynolds number of 400,000. The primary conclusion is that the plasma actuator control authority remains insufficient for practical purposes when extrapolated to Reynolds numbers over 1 million. The potential impact of the active lift control concept was evaluated through detailed simulations for three wind turbine sizes: a 3.4MW onshore turbine, a 10MW offshore turbine, and a 15MW offshore turbine. A feedback control system was designed for each turbine within two scenarios: one where the active lift control is used as a retrofit capability on the baseline design, and the other where the designers were permitted to “upscale” the turbines in order increase annual energy production. The levelized cost of energy was then evaluated for the range of turbine sizes and design configuration. It was found that the LCOE reduction associated with active lift control fell in the range of 0.7% to 7.2%, with the highest reduction associated with upscaling the 3.4MW turbine.

17 WIND ENERGY↗

Filtering Water by Use of Ultrasonically Vibrated Nanotubes

Devices that could be characterized as acoustically driven molecular sieves have been proposed for filtering water to remove all biological contaminants and all molecules larger than water molecules. Originally intended for purifying wastewater for reuse aboard spacecraft, these devices could also be attractive for use on Earth in numerous settings in which there are requirements to obtain potable, medical-grade, or otherwise pure water from contaminated water supplies. These devices could also serve as efficient means of removing some or all water from chemical products . for example, they might be useful as adjuncts or substitutes for stills in the removal of water from alcohols and alcoholic beverages. These devices may be constructed using various materials, such as ceramics, metallics, or polymers, depending on end-use requirements. A representative device of this type (see figure) would include a polymeric disk, about 1 mm in diameter and between 1 and 40 microns thick, within which would be embedded single-wall carbon nanotubes aligned along the thickness axis. The polymeric disk would be part of a unitary polymeric ring assembly. An acoustic transducer in the form of a piezoelectric-film-and-electrode subassembly - typically 9 microns thick and made of poly(vinylidene fluoride) coated with copper 150 nm thick -. would be affixed to the outside of the outer polymeric ring by means of an electrically nonconductive epoxy. The nanotubes would be chosen to have diameters between about 8 and about 13.5 A because water molecules could fit into the nanotubes, but larger molecules could not. Water to be purified would be placed in contact with one face (typically, the upper face) of the filter disk. The surface tension of water is low enough that water molecules should enter and travel along the nanotubes, and computational simulations of molecular dynamics and experimental measurements have shown that the water molecules inside the nanotubes in this size range can be expected to become aligned into helical columns that exhibit properties of both hexagonal ice crystals and liquid water

Gavalas, Lillian Susan↗

Energy efficient photonic memory based on electrically programmable embedded III-V/Si memristors: switches and filters

Abstract Over the past few years, extensive work on optical neural networks has been investigated in hopes of achieving orders of magnitude improvement in energy efficiency and compute density via all-optical matrix-vector multiplication. However, these solutions are limited by a lack of high-speed power power-efficient phase tuners, on-chip non-volatile memory, and a proper material platform that can heterogeneously integrate all the necessary components needed onto a single chip. We address these issues by demonstrating embedded multi-layer HfO 2 /Al 2 O 3 memristors with III-V/Si photonics which facilitate non-volatile optical functionality for a variety of devices such as Mach-Zehnder Interferometers, and (de-)interleaver filters. The Mach-Zehnder optical memristor exhibits non-volatile optical phase shifts > π with ~33 dB signal extinction while consuming 0 electrical power consumption. We demonstrate 6 non-volatile states each capable of 4 Gbps modulation. (De-) interleaver filters were demonstrated to exhibit memristive non-volatile passband transformation with full set/reset states. Time duration tests were performed on all devices and indicated non-volatility up to 24 hours and beyond. We demonstrate non-volatile III-V/Si optical memristors with large electric-field driven phase shifts and reconfigurable filters with true 0 static power consumption. As a result, co-integrated photonic memristors offer a pathway for in-memory optical computing and large-scale non-volatile photonic circuits.

Cheung, Stanley (ORCID:0000000248860013)↗

A Self-Sustained CPS Design for Reliable Wildfire Monitoring

Continuous monitoring of areas nearby the electric grid is critical for preventing and early detection of devastating wildfires. Existing wildfire monitoring systems are intermittent and oblivious to local ambient risk factors, resulting in poor wildfire awareness. Ambient sensor suites deployed near the gridlines can increase the monitoring granularity and detection accuracy. However, these sensors must address two challenging and competing objectives at the same time. First, they must remain powered for years without manual maintenance due to their remote locations. Second, they must provide and transmit reliable information if and when a wildfire starts. The first objective requires aggressive energy savings and ambient energy harvesting, while the second requires continuous operation of a range of sensors. To the best of our knowledge, this paper presents the first self-sustained cyber-physical system that dynamically co-optimizes the wildfire detection accuracy and active time of sensors. The proposed approach employs reinforcement learning to train a policy that controls the sensor operations as a function of the environment (i.e., current sensor readings), harvested energy, and battery level. Here, the proposed cyber-physical system is evaluated extensively using real-life temperature, wind, and solar energy harvesting datasets and an open-source wildfire simulator. In long-term (5 years) evaluations, the proposed framework achieves 89% uptime, which is 46% higher than a carefully tuned heuristic approach. At the same time, it averages a 2-minute initial response time, which is at least 2.5× faster than the same heuristic approach. Furthermore, the policy network consumes 0.6 mJ per day on the TI CC2652R microcontroller using TensorFlow Lite for Micro, which is negligible compared to the daily sensor suite energy consumption.

54 ENVIRONMENTAL SCIENCES↗

Configuration space representation in parallel coordinates

By means of a system of parallel coordinates, a nonprojective mapping from R exp N to R squared is obtained for any positive integer N. In this way multivariate data and relations can be represented in the Euclidean plane (embedded in the projective plane). Basically, R squared with Cartesian coordinates is augmented by N parallel axes, one for each variable. The N joint variables of a robotic device can be represented graphically by using parallel coordinates. It is pointed out that some properties of the relation are better perceived visually from the parallel coordinate representation, and that new algorithms and data structures can be obtained from this representation. The main features of parallel coordinates are described, and an example is presented of their use for configuration space representation of a mechanical arm (where Cartesian coordinates cannot be used).

Fiorini, Paolo↗

USDC based rapid penetrator of packed soil

Environment protection requires more testing and analysis tools. To detect buried chemical containers or other objects embedded in soil and avoid possible damages of them, a penetrator of packed soil operated using low pushing force was developed. The design was based on a novel driving mechanism of the ultrasonic/sonic driller/corer (USDC) device developed in the NDEAA lab at JPL [Bar-Cohen et al 2001, Bao et al 2003]. In the penetrator, a small free-flying mass is energized by a piezoelectric transducer and impacts a rod probe on its shoulder at frequencies of hundreds times per second. The impacts help the probe to penetrate the packed soil rapidly. A great reduction of the needed pushing force for penetration was achieved. The details of the design of the prototype penetrator and the results of performance tests are presented.

sampling↗

Complex permittivity measurements during high temperature recycling of space shuttle antenna window and dielectric heat shield materials

The research performed and the data obtained on candidate space shuttle antenna window and heat shield materials are presented. The measurement technique employs a free-space focused beam microwave bridge for obtaining RF transmission data, and a device which rotates a sample holder which is heated on one side by natural gas-air flames. The surface temperature of each sample is monitored by IR pyrometry; embedded and rear surface thermocouples are also used in obtaining temperature data. The surface of the sample undergoing test is subjected to approximately the same temperature/time profile that occurs at a proposed antenna position on the space shuttle as it re-enters. The samples are cycled through ten of these temperature profiles to determine the recycling effects. Very little change was noted in the materials due to the recycling.

Bassett, H. L.↗

Gel stretch method: a new method to measure constitutive properties of cardiac muscle cells

Diastolic dysfunction is an important cause of congestive heart failure; however, the basic mechanisms causing diastolic congestive heart failure are not fully understood, especially the role of the cardiac muscle cell, or cardiocyte, in this process. Before the role of the cardiocyte in this pathophysiology can be defined, methods for measuring cardiocyte constitutive properties must be developed and validated. Thus this study was designed to evaluate a new method to characterize cardiocyte constitutive properties, the gel stretch method. Cardiocytes were isolated enzymatically from normal feline hearts and embedded in a 2% agarose gel containing HEPES-Krebs buffer and laminin. This gel was cast in a shape that allowed it to be placed in a stretching device. The ends of the gel were held between a movable roller and fixed plates that acted as mandibles. Distance between the right and left mandibles was increased using a stepper motor system. The force applied to the gel was measured by a force transducer. The resultant cardiocyte strain was determined by imaging the cells with a microscope, capturing the images with a CCD camera, and measuring cardiocyte and sarcomere length changes. Cardiocyte stress was characterized with a finite-element method. These measurements of cardiocyte stress and strain were used to determine cardiocyte stiffness. Two variables affecting cardiocyte stiffness were measured, the passive elastic spring and viscous damping. The passive spring was assessed by increasing the force on the gel at 1 g/min, modeling the resultant stress vs. strain relationship as an exponential [sigma = A/k(ekepsilon - 1)]. In normal cardiocytes, A = 23.0 kN/m2 and k = 16. Viscous damping was assessed by examining the loop area between the stress vs. strain relationship during 1 g/min increases and decreases in force. Normal cardiocytes had a finite loop area = 1.39 kN/m2, indicating the presence of viscous damping. Thus the gel stretch method provided accurate measurements of cardiocyte constitutive properties. These measurements have allowed the first quantitative assessment of passive elastic spring properties and viscous damping in normal mammalian cardiocytes.

Non-NASA Center↗

Flow Boiling in Microgap Coolers - Suborbital Flight Results

Flow Boiling in Microgap Coolers (FBMC) is a thermal management technique that provides embedded, on-site heat removal for power dense electronic components and systems. The dielectric coolant undergoes liquid-to-vapor phase change as it passes through channels integrated within or between devices. By facilitating direct contact between the coolant and heat-generating devices and relying on phase change, the system provides tight temperature control, hot spot mitigation, very high heat transfer coefficients, and low pumping power. Ground tests demonstrated removal of high heat fluxes (up to 500 kW/m2), very high coefficients of performance (up to 40 W of heat transferred per W of pumping power), and consistent performance across five evaporator orientations under the appropriate conditions. As a follow-on study and to better assess the role of gravity on such two-phase systems, the FBMC payload was developed and flown twice aboard the Blue Origin New Shepard space vehicle in January and May 2019. Each flight exposed the payload to weightlessness (150 seconds below 0.01 g) and shorter periods of high-g during ascent (up to 3 g) and descent (up to 5 g). The flow boiling performance was consistent independent of the acceleration levels, which provides confidence that such systems will provide consistent performance when tested on the ground, orbiting or traveling through weightlessness, and operating on the surface of the Moon, Mars, and other planetary bodies. Details of the flight results, payload development, flight environment, and planned future testing will be presented.

Flow boiling↗

B—N–Bond–Embedded Triplet Terpolymers with Small Singlet–Triplet Energy Gaps for Suppressing Non–Radiative Recombination and Improving Blend Morphology in Organic Solar Cells

Suppressing the photon energy loss (E loss ), especially the non-radiative loss, is of importance to further improve the device performance of organic solar cells (OSCs). However, typical π-conjugated semiconductors possess a large singlet–triplet energy gap (ΔE ST ), leading to a lower triplet state than charge transfer state and contributing to a non-radiative loss channel of the photocurrent by the triplet state. Herein, a series of triplet polymer donors are developed by introducing a BNIDT block into the PM6 polymer backbone. Further, the high electron affinity of BNIDT and the opposite resonance effect of the B—N bond in BNIDT results in a lowered highest occupied molecular orbital (HOMO) and a largely reduced ΔE ST . Moreover, the morphology of the active blends is also optimized by fine-tuning the BNIDT content. Therefore, non-radiative recombination via the terminal triplet loss channels and morphology traps is effectively suppressed. The PNB-3 (with 3% BNIDT):L8-BO device exhibits both small ΔE ST and optimized morphology, favoring more efficient charge transfer and transport. Finally, the simultaneously enhanced V oc of 0.907 V, J sc of 26.59 mA cm –2 , and FF of 78.86% contribute to a champion PCE of 19.02%. Therefore, introducing B—N bonds into benchmark polymers is a possible avenue toward higher-performance of OSCs.

36 MATERIALS SCIENCE↗

Even Higher-Level Synthesis: An Exploration of AI Hardware Accelerators using HLS4ML

With the rise of artificial intelligence, the popularization of deep learning, and a constantly evolving industry, the demand for flexible and efficient tools has never been greater. As algorithms grow more complex, their runtime and energy consumption increase exponentially. Customized hardware accelerators, long used for specific mathematical operations, remain essential for managing modern applications' computational and power demands. Hardware accelerators can speed up complex computations by orders of magnitude, but their manual design and verification processes are often challenging and time-consuming. High-Level Synthesis (HLS) provides a solution by transforming high-level algorithm descriptions, typically written in C++ or SystemC, into synthesizable RTL suitable for hardware implementation. This approach reduces development time for RTL engineers while offering flexibility beyond what traditional handwritten RTL can provide. We extended this capability to the machine-learning domain with the open-source framework hls4ml, which allows neural networks trained in Python frameworks like Tensorflow or PyTorch to be synthesized into efficient hardware representations for the traditional FPGA and ASIC flows. This breakthrough addresses the growing need for reduced design turnaround and easy verification of ML hardware accelerators with low latency and power efficiency constraints. During this tutorial, we will demonstrate how Python complements HLS by simplifying the ML design process, bridging the gap between software and hardware development. Attendees will explore how we translate neural networks modeled in Python into fixed-point C++ models suitable for HLS workflows. We will dive into strategies like Value-Range Analysis and Quantization-Aware Training, which optimize these designs for deployment and evaluate their accuracy, power consumption, and energy efficiency. To exemplify these concepts, experts from Fermilab will share their experiences applying this technology to high-energy physics experiments, where real-time, low-latency processing is critical. Over the years, Fermilab engineers have demonstrated how deep neural networks, optimized for hardware using hls4ml, can meet the stringent requirements of trigger systems at the CERN Large Hadron Collider. These systems rely on rapid decision-making to process immense data volumes while retaining only the most relevant events for further analysis. The application of hls4ml has also been extended to innovative technologies like smart pixel arrays. These smart pixels integrate ML inference capabilities directly into sensor devices, enabling localized data processing at the pixel level. This approach drastically reduces the need to transmit raw data to external processing units, significantly decreasing power consumption and latency. By embedding neural networks within the pixel architecture, the smart pixels can identify and prioritize relevant data in real time, providing a highly efficient solution for edge computing in scenarios such as particle detectors and imaging systems. Fermilab's work highlights the potential of hardware-accelerated ML in scenarios where both speed and power efficiency are mission-critical. Through this tutorial, attendees will gain valuable insights into the challenges and solutions of deploying ML in hardware. Understanding how HLS and hls4ml streamline the development of neural network-based hardware accelerators is fundamental for the industry's future. Participants will learn how these technologies are shaping the future of AI and scientific computing.

Di Guglielmo, Giuseppe [Fermilab]↗

Badger COMET Compartmentalized Onboard Material Extrusion Technology

In response to the 2014 NASA Academic Innovation Challenge, the University of Wisconsin – Madison team presents the design of a collapsible Fused Deposition Modeling (FDM) system for in situ manufacturing in a space habitat environment, the Badger Compartmentalized Onboard Material Extrusion Technology (COMET). The proposed mechanism incorporates one year of design and testing on an array of current additive manufacturing techniques, with the goal of providing a reliable and maintainable manufacturing solution. Seven Level 1 requirements were employed to guide the design process, based on information in the challenge, communications with NASA, and the evolving systems feedback of project work groups. These requirements provided a baseline for the development of the System Requirements Document (SRD, Appendix I), which framed the design of the system. The design requirements deemed critical to the success of the systems are as follows: - The system shall compose an FDM workstation capable of producing parts within industry standard tolerances. - The system shall reduce to a minimum of 50 percent or less of its deployed volume when not in use, and must collapse without the need for disassembly. - The system shall meet all relevant NASA safety and functional standards. The final design for the Badger COMET was selected from multiple design iterations, which balanced the critical design requirements listed above with system reliability, with the final goal of providing a minimal system weight. The system collapses in the vertical direction, allowing for a maximum reduction in volume. Guide rods and precision, anti-backlash lead screws provide all linear movement in the device. Stepper motors were chosen to actuate each system axis, due to their high precision and repeatable accuracy. The system is controlled through an on-board computer system and embedded electronics package.

Frederick T. Elder↗

Space Networking Implementation for Lunar Operations

The High-Rate Delay Tolerant Networking (HDTN) project at NASA has developed a performance optimized and open-source Delay Tolerant Networking (DTN) implementation. The primary goal is to create a scalable networking solution to increase the scientific data return rate of space missions. To reach this goal, HDTN must span multiple edge cases in space networking by including tools and configurations to accommodate a wide range of space systems. Typically, HDTN evaluations are conducted on a laboratory emulation test bed, made up of hardware accelerated x86 based systems capable of data rates over 10 Gbps. HDTN must have an effective implementation process on a wide range of systems to increase the sustainability of the design. One important implementation option is with low-level embedded systems which could be used on small robotic missions. This paper details the implementation process, benchmark testing, and performance results of HDTN in multiple configurations on Raspberry Pi 4 devices. By implementing HDTN on a Raspberry Pi 4, a process for building HDTN onto ARM processors was developed and utilized to conduct benchmark tests in multiple network configurations, achieving a data rate performance exceeding 600 Mbps. Based on these results, HDTN proved to run on small ARM based systems with slight modifications to the build procedure. These results were then extended to evaluating an implementation of the HDTN software parsed across several Raspberry Pi 4 nodes. To test this capability, HDTN was configured in a simplified cut-through setup and distributed among multiple Raspberry Pi 4 processors. This distributed architecture was benchmark tested in a similar fashion to the testing of a singular HDTN implementation. The results from the benchmark testing are used to examine how these implementation options and capabilities can expand the use cases for DTN, and particularly with small robotic missions.

Space Networking↗

Commuting embeddings for parallel strategies in non-local games

Non-local games provide a versatile framework for probing quantum correlations and for benchmarking the power of entanglement. In finite dimensions, the standard method for playing several games in parallel requires a tensor product of the local Hilbert spaces, which scales additively in the number of qubits. In this work, we show that this additive cost can be reduced by exploiting algebraic embeddings. We introduce two forms of compressions. First, when a referee selects one game from a finite collection of games at random, the game quantum strategy can be implemented using a maximally entangled state of dimension equal to the largest individual game, thereby eliminating the need for repeated state preparations. Second, we establish conditions under which several games can be played simultaneously in parallel on fewer qubits than the tensor product baseline. These conditions are expressed in terms of commuting embeddings of the game algebras. Moreover, we provide a constructive framework for building such embeddings. Using tools from Lie theory, we show that aligning the various game algebras into a common Cartan decomposition enables such a qubit reduction. Beyond the theoretical contribution, our framework casts NLGs as algebraic primitives for distributed and resource-constrained quantum computations and suggested NLGs as a comparable device-independent dimension witness.

Commuting embeddings↗