Large-Scale VQE Simulations with Tensor Networks
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Urban Air Mobility (UAM) is set to transform transportation in densely populated regions like the San Francisco Bay Area. This paper introduces an innovative simulation approach to explore large-scale UAM scenarios, emphasizing the use of distributed sensing to enhance operational efficiency and safety. The Revolutionary Vertical Lift Technology (RVLT) model is employed as the framework for simulating complex interactions among multiple vehicles within urban landscapes. Strategically deployed ground sensor nodes enable distributed sensing, enhancing situational awareness and operational effectiveness. By integrating empirical data and geographical realism, the simulations provide a systematic analysis of the feasibility, efficiency, and safety considerations associated with UAM deployment in urban environments. Factors such as air traffic density and infrastructural requirements are thoroughly examined, offering actionable insights for policymakers and industry stakeholders. This paper aims to refine the structure and scenarios for large-scale simulations based on distributed sensing, thereby contributing to the advancement of UAM operations.
Urban Air Mobility (UAM) is set to transform transportation in densely populated regions like the San Francisco Bay Area. This paper introduces an innovative simulation approach to explore large-scale UAM scenarios, emphasizing the use of distributed sensing to enhance operational efficiency and safety. The Revolutionary Vertical Lift Technology (RVLT) model is employed as the framework for simulating complex interactions among multiple vehicles within urban landscapes. Strategically deployed ground sensor nodes enable distributed sensing, enhancing situational awareness and operational effectiveness. By integrating empirical data and geographical realism, the simulations provide a systematic analysis of the feasibility, efficiency, and safety considerations associated with UAM deployment in urban environments. Factors such as air traffic density and infrastructural requirements are thoroughly examined, offering actionable insights for policymakers and industry stakeholders. This paper aims to refine the structure and scenarios for large-scale simulations based on distributed sensing, thereby contributing to the advancement of UAM operations.
This presentation highlights communication congestion control in delay-tolerant networks (DTNs). Large-scale future space exploration will offer complex communication challenges that may be best addressed by establishing a network infrastructure. However, current internet techniques for congestion control are not well suited for operation of a network over interplanetary distances. An alternative, delay-tolerant technique for congestion control in a delay-tolerant network is presented. A simple DTN was constructed and an experimental congestion control mechanism was applied. The mechanism appeared to be effective and each router was able to make its bundle acceptance decisions autonomously. Future research will examine more complex topologies and alternative bundle acceptance rules that might enhance performance.
We review recent observations by the Yohkoh-SXT (Soft X-ray Telescope) in collaboration with other spacecraft and ground-based observatories of coronal loops and prominences. These new results point to problems that SoHO will be able to address. With a unique combination of rapid-cadence digital imaging (greater than or equal to 32 s full-disk and greater than or equal to 2 s partial-frame images), high spatial resolution (greater than or equal to 2.5 arcsec pixels), high sensitivity (EM less than or equal to 10(exp 42) cm(exp -3)), a low-scatter mirror, and large dynamic range, SXT can observe a vast range of targets on the Sun. Over the first 21 months of Yohkoh operations SXT has taken over one million images of the corona and so is building up an invaluable long-term database on the large-scale corona and loop geometry. The most striking thing about the SXT images is the range of loop sizes and shapes. The active regions are a bright tangle of magnetic field lines, surrounded by a network of large-scale quiet-Sun loops stretching over distances in excess of 105 km. The cross-section of most loops seems to be constant. Loops displaying significant Gamma's are the exception, not the rule, implying the presence of widespread currents in the corona. All magnetic structures show changes. Time scales range from seconds to months. The question of how these structures are formed, become filled with hot plasma, and are maintained is still open. While we see the propagation of brightenings along the length of active-region loops and in X-ray jets with velocities of several hundred km/s, much higher velocities are seen in the quiet Sun. In XBP flares, for example, velocities of over 1000 km/s are common. Active-region loops seem to be in constant motion, moving slowly outward, carrying plasma with them. During flares, loops often produce localized brightenings at the base and later at the apex of the loop. Quiescent filaments and prominences have been observed regularly. Their coronal manifestation seems to be an extended arcade of loops overlying the filament. Reliable alignment of the ground-based data with the X-ray images make it possible to make a detailed intercomparison of the hot and cold plasma structures over extended periods. Hence we are able to follow the long-term evolution of these structures and see how they become destabilized and erupt.
We present a simple algorithm based on linear programming, that combines Kirchoff's flux and potential laws and applies them to metabolic networks to predict thermodynamically feasible reaction fluxes. These law's represent mass conservation and energy feasibility that are widely used in electrical circuit analysis. Formulating the Kirchoff's potential law around a reaction loop in terms of the null space of the stoichiometric matrix leads to a simple representation of the law of entropy that can be readily incorporated into the traditional flux balance analysis without resorting to non-linear optimization. Our technique is new as it can easily check the fluxes got by applying flux balance analysis for thermodynamic feasibility and modify them if they are infeasible so that they satisfy the law of entropy. We illustrate our method by applying it to the network dealing with the central metabolism of Escherichia coli. Due to its simplicity this algorithm will be useful in studying large scale complex metabolic networks in the cell of different organisms.
N-port networks interconnection by NASAP-70 transfer function capability for large scale circuit problems, considering Laemmel and Cascade Parameter methods
This paper describes a technique for implementing scalable, reliable, multi-source multipoint data distribution in space flight communications -- Delay-Tolerant Reliable Multicast (DTRM) -- that is fully supported by the "Remote AMS" (RAMS) protocol of the Asynchronous Message Service (AMS) proposed for standardization within the Consultative Committee for Space Data Systems (CCSDS). The DTRM architecture enables applications to easily "publish" messages that will be reliably and efficiently delivered to an arbitrary number of "subscribing" applications residing anywhere in the space network, whether in the same subnet or in a subnet on a remote planet or vehicle separated by many light minutes of interplanetary space. The architecture comprises multiple levels of protocol, each included for a specific purpose and allocated specific responsibilities: "application AMS" traffic performs end-system data introduction and delivery subject to access control; underlying "remote AMS" directs this application traffic to populations of recipients at remote locations in a multicast distribution tree, enabling the architecture to scale up to large networks; further underlying Delay-Tolerant Networking (DTN) Bundle Protocol (BP) advances RAMS protocol data units through the distribution tree using delay-tolerant storeand- forward methods; and further underlying reliable "convergence-layer" protocols ensure successful data transfer over each segment of the end-to-end route. The result is scalable, reliable, delay-tolerant multi-source multicast that is largely self-configuring.
Architectures that would exploit the distinct characteristics of quantum-dot cellular automata (QCA) have been proposed for digital communication networks that connect advanced digital computing circuits. In comparison with networks of wires in conventional very-large-scale integrated (VLSI) circuitry, the networks according to the proposed architectures would be more compact. The proposed architectures would make it possible to implement complex interconnection schemes that are required for some advanced parallel-computing algorithms and that are difficult (and in many cases impractical) to implement in VLSI circuitry. The difficulty of implementation in VLSI and the major potential advantage afforded by QCA were described previously in Implementing Permutation Matrices by Use of Quantum Dots (NPO-20801), NASA Tech Briefs, Vol. 25, No. 10 (October 2001), page 42. To recapitulate: Wherever two wires in a conventional VLSI circuit cross each other and are required not to be in electrical contact with each other, there must be a layer of electrical insulation between them. This, in turn, makes it necessary to resort to a noncoplanar and possibly a multilayer design, which can be complex, expensive, and even impractical. As a result, much of the cost of designing VLSI circuits is associated with minimization of data routing and assignment of layers to minimize crossing of wires. Heretofore, these considerations have impeded the development of VLSI circuitry to implement complex, advanced interconnection schemes. On the other hand, with suitable design and under suitable operating conditions, QCA-based signal paths can be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes. The proposed architectures require two advances in QCA-based circuitry beyond basic QCA-based binary-signal wires described in the cited prior article. One of these advances would be the development of QCA-based wires capable of bidirectional transmission of signals. The other advance would be the development of QCA circuits capable of high-impedance state outputs. The high-impedance states would be utilized along with the 0- and 1-state outputs of QCA.
Basis functions for arbitrary time variable network symmetries for large scale integration, using group theory
In cooperation with scientists in the University of Washington Medical School, a microcomputer-based image processing system for quantitative microscopy, called DMD1 (Digital Microdensitometer 1) was constructed. In order to make DMD1 transportable to different hosts and image processors, we have been investigating the possibility of rewriting the lower level portions of DMD1 software using Transportable Applications Executive (TAE) libraries and subsystems. If successful, we hope to produce a newer version of DMD1, called DMD2, running on an IBM PC/AT under the SCO XENIX System 5 operating system, using any of seven target image processors available in our laboratory. Following this implementation, copies of the system will be transferred to other laboratories with biomedical imaging applications. By integrating those applications into DMD2, we hope to eventually expand our system into a low-cost general purpose biomedical imaging workstation. This workstation will be useful not only as a self-contained instrument for clinical or research applications, but also as part of a large scale Digital Imaging Network and Picture Archiving and Communication System, (DIN/PACS). Widespread application of these TAE-based image processing and analysis systems should facilitate software exchange and scientific cooperation not only within the medical community, but between the medical and remote sensing communities as well.
Adaptive, parallel, discrete-event-simulation-synchronization algorithm, Breathing Time Buckets, developed in Synchronous Parallel Environment for Emulation and Discrete Event Simulation (SPEEDES) operating system. Algorithm allows parallel simulations to process events optimistically in fluctuating time cycles that naturally adapt while simulation in progress. Combines best of optimistic and conservative synchronization strategies while avoiding major disadvantages. Algorithm processes events optimistically in time cycles adapting while simulation in progress. Well suited for modeling communication networks, for large-scale war games, for simulated flights of aircraft, for simulations of computer equipment, for mathematical modeling, for interactive engineering simulations, and for depictions of flows of information.
We developed an identification method to find the strength of the connections between neurons from their behavior in small biologically-inspired artificial neural networks. That is, given the network external inputs and the temporal firing pattern of the neurons, we can calculate a solution for the strengths of the connections between neurons and the initial neuron activations if a solution exists. The method determines directly if there is a solution to a particular neural network problem. No training of the network is required. It should be noted that this is a first pass at the solution of a difficult problem. The neuron and network models chosen are related to biology but do not contain all of its complexities, some of which we hope to add to the model in future work. A variety of new results have been obtained. First, the method has been tailored to produce connection weight matrix solutions for networks with important features of biological neural (bioneural) networks. Second, a computationally efficient method of finding a robust central solution has been developed. This later method also enables us to find the most consistent solution in the presence of noisy data. Prospects of applying our method to identify bioneural network connections are exciting because such connections are almost impossible to measure in the laboratory. Knowledge of such connections would facilitate an understanding of bioneural networks and would allow the construction of the electronic counterparts of bioneural networks on very large scale integrated (VLSI) circuits.
A system is presented for optically providing one-to-many irregular interconnections, and strength-adjustable many-to-many irregular interconnections which may be provided with strengths (weights) w(sub ij) using multiple laser beams which address multiple holograms and means for combining the beams modified by the holograms to form multiple interconnections, such as a cross-bar switching network. The optical means for interconnection is based on entering a series of complex computer-generated holograms on an electrically addressed spatial light modulator for real-time reconfigurations, thus providing flexibility for interconnection networks for large-scale practical use. By employing multiple sources and holograms, the number of interconnection patterns achieved is increased greatly.
The NASA sponsored Hyper-Spectral Communications and Networking for Air Traffic Management (ATM) (HSCNA) project is conducting research to improve the operational efficiency of the future National Airspace System (NAS) through diverse and secure multi-band, multi-mode, and millimeter-wave (mmWave) wireless links. Worldwide growth of air transportation and the coming of unmanned aircraft systems (UAS) will increase air traffic density and complexity. Safe coordination of aircraft will require more capable technologies for communications, navigation, and surveillance (CNS). The HSCNA project will provide a foundation for technology and operational concepts to accommodate a significantly greater number of networked aircraft. This paper describes two of the HSCNA projects technical challenges. The first technical challenge is to develop a multi-band networking concept of operations (ConOps) for use in multiple phases of flight and all communication link types. This ConOps will integrate the advanced technologies explored by the HSCNA project and future operational concepts into a harmonized vision of future NAS communications and networking. The second technical challenge discussed is to conduct simulations of future ATM operations using multi-bandmulti-mode networking and technologies. Large-scale simulations will assess the impact, compared to todays system, of the new and integrated networks and technologies under future air traffic demand.
We have developed and deployed a distributed-parallel storage system (DPSS) in several high speed asynchronous transfer mode (ATM) wide area networks (WAN) testbeds to support several different types of data-intensive applications. Architecturally, the DPSS is a network striped disk array, but is fairly unique in that its implementation allows applications complete freedom to determine optimal data layout, replication and/or coding redundancy strategy, security policy, and dynamic reconfiguration. In conjunction with the DPSS, we have developed a 'top-to-bottom, end-to-end' performance monitoring and analysis methodology that has allowed us to characterize all aspects of the DPSS operating in high speed ATM networks. In particular, we have run a variety of performance monitoring experiments involving the DPSS in the MAGIC testbed, which is a large scale, high speed, ATM network and we describe our experience using the monitoring methodology to identify and correct problems that limit the performance of high speed distributed applications. Finally, the DPSS is part of an overall architecture for using high speed, WAN's for enabling the routine, location independent use of large data-objects. Since this is part of the motivation for a distributed storage system, we describe this architecture.
We provide preliminary evidence that existing algorithms for inferring small-scale gene regulation networks from gene expression data can be adapted to large-scale gene expression data coming from hybridization microarrays.
One of the outstanding problems in modern meterology is that of describing in detail the manner in which larger scales of motion interact with, influence and are influenced by successively smaller scales of motion. The present investigation is concerned with a study of the diurnal evolution of convection, the interaction between the peninsular-scale convergence and convection, and the role of the feedback produced by the cloud-scale downdrafts in the maintenance of the convection. Attention is given to the analysis, the diurnal cycle of the network area-averaged divergence, convective-scale divergence, convective mass transports, and the peninsular scale divergence. The links established in the investigation between the large scale (peninsular), the mesoscale (network), and the convective scale (cloud) are found to be of fundamental importance to the understanding of the initiation, maintenance, and decay of deep precipitating convection and to its theoretical parameterization.