Neural-Inspired Computation for Efficient Scientific Computing via Random Walks and Surrogate Models.
Abstract not provided.
Severa, William Mark↗
SEARCH · Search NASA
Results for “Random walk”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Leveraging Random Walks to Solve IPDEs on Spiking Neuromorphic Hardware.
Abstract not provided.
Smith, John Darby↗
A Comparison of Custom and Standard Neuron Model Random Walks on the Ornstein-Uhlenbeck Equation for Simplified Turbulence
An initial investigation into neuron models aimed at efficient stochastic simulation of turbulent flows.
Smith, John Darby [Sandia National Laboratories (S↗
Systems Characterization of Combustor Instabilities With Controls Design Emphasis
This effort performed test data analysis in order to characterize the general behavior of combustor instabilities with emphasis on controls design. The analysis is performed on data obtained from two configurations of a laboratory combustor rig and from a developmental aero-engine combustor. The study has characterized several dynamic behaviors associated with combustor instabilities. These are: frequency and phase randomness, amplitude modulations, net random phase walks, random noise, exponential growth and intra-harmonic couplings. Finally, the very cause of combustor instabilities was explored and it could be attributed to a more general source-load type impedance interaction that includes the thermo-acoustic coupling. Performing these characterizations on different combustors allows for more accurate identification of the cause of these phenomena and their effect on instability.
Kopasakis, George↗
Attentional Modulation of Eye Torsion Responses
Eye movements generally have both reflexive and voluntary aspects, but torsional eye movements are usually thought of as a reflexive response to image rotation around the line of sight (torsional OKN) or to head roll (torsional VOR). In this study we asked whether torsional responses could be modulated by attention in a case where two stimuli rotated independently, and whether attention would influence the latency of responses. The display consisted of rear-projected radial "pinwheel" gratings, with an inner annulus segment extending from the center to 22 degrees eccentricity, and an outer annulus segment extending from 22 degrees out to 45 degrees eccentricity. The two segments rotated around the center in independent random walks, stepping randomly 4 degrees clockwise or counterclockwise at 60 Hz. Subjects were asked to attend to one or the other while keeping fixation steady at the center of the display. To encourage attention on one or the other segment of the display, subjects were asked to move a joystick in synchrony with the back and forth rotations of one part of the image while ignoring the other. Eye torsion was recorded with the scleral search coil technique, sampled at 500 Hz. All four subjects showed roughly 50% stronger torsion responses to the attended compared to unattended segments. Latency varied from 100 to 150 msec across subjects and was unchanged by attention. These findings suggest that attention can influence eye movement responses that are not typically under voluntary control.
attention↗
Attentional Modulation of Eye Torsion Responses
Eye movements generally have both reflexive and voluntary aspects, but torsional eye movements are usually thought of as a reflexive response to image rotation around the line of sight (torsional OKN) or to head roll (torsional VOR). In this study we asked whether torsional responses could be modulated by attention in a case where two stimuli rotated independently, and whether attention would influence the latency of responses. The display consisted of rear-projected radial pinwheel gratings, with an inner annulus segment extending from the center to 22 degrees eccentricity, and an outer annulus segment extending from 22 degrees out to 45 degrees eccentricity. The two segments rotated around the center in independent random walks, stepping randomly 4 degrees clockwise or counterclockwise at 60 Hz. Subjects were asked to attend to one or the other while keeping fixation steady at the center of the display. To encourage attention on one or the other segment of the display, subjects were asked to move a joystick in synchrony with the back and forth rotations of one part of the image while ignoring the other. Eye torsion was recorded with the scleral search coil technique, sampled at 500 Hz. All four subjects showed roughly 50 stronger torsion responses to the attended compared to unattended segments. Latency varied from 100 to 150 msec across subjects and was unchanged by attention. These findings suggest that attention can influence eye movement responses that are not typically under voluntary control.
ocular torsion↗
Dark matter halo mass functions and density profiles from mass and energy cascade
Abstract Halo abundance and structure play a central role for modeling structure formation and evolution. Without relying on a spherical or ellipsoidal collapse model, we analytically derive the halo mass function and cuspy halo density (inner slope of −4/3) based on the mass and energy cascade theory in dark matter flow. The hierarchical halo structure formation leads to halo or particle random walk with a position-dependent waiting time $$\tau _g$$ τ g . First, the inverse mass cascade from small to large scales leads to the halo random walk in mass space with $$\tau _g\propto m_h^{-\lambda }$$ τ g ∝ m h - λ , where $$m_h$$ m h is the halo mass and $$\lambda$$ λ is a halo geometry parameter with predicted value of 2/3. The corresponding Fokker-Planck solution for halo random walk in mass space gives rise to the halo mass function with a power-law behavior on small scale and exponential decay on large scale. This can be further improved by considering two different $$\lambda$$ λ for haloes below and above a critical mass scale $$m_h^*$$ m h ∗ , i.e. a double- $$\lambda$$ λ halo mass function. Second, a double- $$\gamma$$ γ density profile can be derived based on the particle random walk in 3D space with a position-dependent waiting time $$\tau _g \propto \Phi (r)^{-1} \propto r^{-\gamma }$$ τ g ∝ Φ ( r ) - 1 ∝ r - γ , where $$\Phi$$ Φ is the gravitational potential and r is the particle distance to halo center. Theory predicts $$\gamma =2/3$$ γ = 2 / 3 that leads to a cuspy density profile with an inner slope of −4/3, consistent with the predicted scaling laws from energy cascade. The Press-Schechter mass function and Einasto density profile are just special cases of proposed models. The small scale permanence can be identified due to the scale-independent rate of mass and energy cascade, where density profiles of different halo masses and redshifts converge to the $$-4/3$$ - 4 / 3 scaling law ( $$\rho _h \propto r^{-4/3}$$ ρ h ∝ r - 4 / 3 ) on small scales. Theory predicts the halo number density scales with halo mass as $$\propto m_h^{-1.9}$$ ∝ m h - 1.9 , while the halo mass density scales as $$\propto m_h^{4/9}$$ ∝ m h 4 / 9 . Results were compared against the Illustris simulations. This new perspective provides a theory for nearly universal halo mass functions and density profiles.
79 ASTRONOMY AND ASTROPHYSICS↗
Dynamical Signatures of Living Systems
One of the main challenges in modeling living systems is to distinguish a random walk of physical origin (for instance, Brownian motions) from those of biological origin and that will constitute the starting point of the proposed approach. As conjectured, the biological random walk must be nonlinear. Indeed, any stochastic Markov process can be described by linear Fokker-Planck equation (or its discretized version), only that type of process has been observed in the inanimate world. However, all such processes always converge to a stable (ergodic or periodic) state, i.e., to the states of a lower complexity and high entropy. At the same time, the evolution of living systems directed toward a higher level of complexity if complexity is associated with a number of structural variations. The simplest way to mimic such a tendency is to incorporate a nonlinearity into the random walk; then the probability evolution will attain the features of diffusion equation: the formation and dissipation of shock waves initiated by small shallow wave disturbances. As a result, the evolution never "dies:" it produces new different configurations which are accompanied by an increase or decrease of entropy (the decrease takes place during formation of shock waves, the increase-during their dissipation). In other words, the evolution can be directed "against the second law of thermodynamics" by forming patterns outside of equilibrium in the probability space. Due to that, a specie is not locked up in a certain pattern of behavior: it still can perform a variety of motions, and only the statistics of these motions is constrained by this pattern. It should be emphasized that such a "twist" is based upon the concept of reflection, i.e., the existence of the self-image (adopted from psychology). The model consists of a generator of stochastic processes which represents the motor dynamics in the form of nonlinear random walks, and a simulator of the nonlinear version of the diffusion equation which represents the mental dynamics. It has been demonstrated that coupled mental-motor dynamics can simulate emerging self-organization, prey-predator games, collaboration and competition, "collective brain," etc.
Zak, M.↗
Stationary Spatial Charging Demand Distribution for Commercial Electric Vehicles in Urban Area
The electric vehicle (EV) is an increasingly popu- lar mobility solution today. It is especially appealing for urban commercial usage including serving commuters and delivering goods. Commercial EVs, defined as electric taxi fleets in this paper, contribute a lot to the energy consumption and emission. One critical component to facilitate the adoption of EVs is to provide sufficient charging infrastructures for road users to alleviate the range anxiety. In this study, we develop an analytical model to profile the stationary spatial distribution of charging demand for any given fleet of commercial EVs, which serves as the necessary input for planning the location of charging infrastructures. Our model considers the movement of EVs as a random walk, with the underlying Markov process driven by the spatial demand that the commercial EV fleet needs to serve. We then define the electricity consumption and charging models and develop the probability distribution that an EV may need to recharge its battery at any given location in the city, based on the stationary distribution of the random walk process. We calibrate the performance parameters of EVs from the trip record and present numerical experiments based on New York City taxi trip data and compare the solution from simulation with our analytical solution. The result shows that analytical solution is quite close to the simulation result. This paper provides insights to the city agencies and private companies to make charging infrastructure location planning.
Qian, Xinwu↗
Continuous-Time Multidimensional Walks as an Integrable Model
We consider continuous-time random walks on multidimensional symplectic lattices. It is shown that the generating functions of random walks and the transition amplitudes of continuous-time quantum walks can be expressed through dynamical correlation functions of an exactly solvable model describing strongly correlated bosons on a chain, the so-called phase model. The number of random lattice paths with a fixed number of steps connecting the starting and ending points on the multidimensional lattice is expressed through solutions of the Bethe equations of the phase model. Its asymptotics is obtained in the limit of a large number of steps.
97 MATHEMATICS AND COMPUTING↗
NeuralRW-Loihi: Spiking Discrete Time Markov Chain Simulator for Intel Loihi v
SAND2024-01302O NeuralRW-Loihi: Spiking Discrete Time Markov Chain Simulator for Intel Loihi is a neuromorphic script that generates a random walk simulation of a discrete-time Markov Chain for the Loihi neuromorphic hardware. The code was used to produce the paper "Neuromorphic scaling advantages for energy-efficient random walk computations" by Smith et al., 2021. It was published in Nature Electronics. The software provides code for implementing the discrete time Markov chain random walks on Intel's Loihi Neuromorphic platform. In addition, it provides an example problem through a mini app.
Aimone, James↗
Simulation of the Formation of DNA Double Strand Breaks and Chromosome Aberrations in Irradiated Cells
The formation of DNA double-strand breaks (DSBs) and chromosome aberrations is an important consequence of ionizing radiation. To simulate DNA double-strand breaks and the formation of chromosome aberrations, we have recently merged the codes RITRACKS (Relativistic Ion Tracks) and NASARTI (NASA Radiation Track Image). The program RITRACKS is a stochastic code developed to simulate detailed event-by-event radiation track structure: [1] This code is used to calculate the dose in voxels of 20 nm, in a volume containing simulated chromosomes, [2] The number of tracks in the volume is calculated for each simulation by sampling a Poisson distribution, with the distribution parameter obtained from the irradiation dose, ion type and energy. The program NASARTI generates the chromosomes present in a cell nucleus by random walks of 20 nm, corresponding to the size of the dose voxels, [3] The generated chromosomes are located within domains which may intertwine, and [4] Each segment of the random walks corresponds to approx. 2,000 DNA base pairs. NASARTI uses pre-calculated dose at each voxel to calculate the probability of DNA damage at each random walk segment. Using the location of double-strand breaks, possible rejoining between damaged segments is evaluated. This yields various types of chromosomes aberrations, including deletions, inversions, exchanges, etc. By performing the calculations using various types of radiations, it will be possible to obtain relative biological effectiveness (RBE) values for several types of chromosome aberrations.
Plante, Ianik↗
Approximate scaling properties of RNA free energy landscapes
RNA free energy landscapes are analysed by means of "time-series" that are obtained from random walks restricted to excursion sets. The power spectra, the scaling of the jump size distribution, and the scaling of the curve length measured with different yard stick lengths are used to describe the structure of these "time series". Although they are stationary by construction, we find that their local behavior is consistent with both AR(1) and self-affine processes. Random walks confined to excursion sets (i.e., with the restriction that the fitness value exceeds a certain threshold at each step) exhibit essentially the same statistics as free random walks. We find that an AR(1) time series is in general approximately self-affine on timescales up to approximately the correlation length. We present an empirical relation between the correlation parameter rho of the AR(1) model and the exponents characterizing self-affinity.
Signal Processing, Computer-Assisted↗
Node-degree aware edge sampling mitigates inflated classification performance in biomedical random walk-based graph representation learning
Motivation: Graph representation learning is a family of related approaches that learn low-dimensional vector representations of nodes and other graph elements called embeddings. Embeddings approximate characteristics of the graph and can be used for a variety of machine-learning tasks such as novel edge prediction. For many biomedical applications, partial knowledge exists about positive edges that represent relationships between pairs of entities, but little to no knowledge is available about negative edges that represent the explicit lack of a relationship between two nodes. For this reason, classification procedures are forced to assume that the vast majority of unlabeled edges are negative. Existing approaches to sampling negative edges for training and evaluating classifiers do so by uniformly sampling pairs of nodes. Results: We show here that this sampling strategy typically leads to sets of positive and negative examples with imbalanced node degree distributions. Using representative heterogeneous biomedical knowledge graph and random walk-based graph machine learning, we show that this strategy substantially impacts classification performance. If users of graph machine-learning models apply the models to prioritize examples that are drawn from approximately the same distribution as the positive examples are, then performance of models as estimated in the validation phase may be artificially inflated. We present a degree-aware node sampling approach that mitigates this effect and is simple to implement. Availability and implementation: Our code and data are publicly available at https://github.com/monarch-initiative/negativeExampleSelection.
59 BASIC BIOLOGICAL SCIENCES↗
Delocalization of a non-Hermitian quantum walk on random media in one dimension
Highlights: • We study the localization-delocalization transition of a non-Hermitian quantum walk. • We find that the phase transition is similar to the one in the Hatano-Nelson model. • All eigenvectors get extended and all eigenvalues become complex at the transition. • This implies that the localization lengths of all eigenvectors are the same. We first review the localization–delocalization transition of a non-Hermitian random tight-binding Anderson model, called the Hatano–Nelson model. We then report a new result for a non-Hermitian extension of a discrete-time quantum walk on a one-dimensional random medium; we numerically find a delocalization transition similar to one of the Hatano–Nelson model. As a common feature to both models, at the transition point, an eigenvector gets delocalized and at the same time the corresponding energy eigenvalue (for the latter quantum-walk model, the imaginary unit times the phase of the eigenvalue of the time-evolution operator) becomes complex. One of the unique properties of the present non-Hermitian quantum walk is that the localization length of all eigenvectors is the same, and thereby all eigenstates simultaneously undergo the delocalization transition and all energy eigenvalues become complex at the same time when we turn up a non-Hermitian parameter.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Simulations of the mean solar magnetic field during sunspot cycle 21
Regarding new bipolar magnetic regions as sources of flux, the evolution of the photospheric magnetic field during 1976-1984 was computed and the corresponding evolution of the mean line-of-sight field as seen from earth was derived. A good, but imperfect, agreement was obtained between the observed mean field and the field computed for a nominal choice of flux transport parameters. The response of the computed mean field to variations in the transport parameters and the source properties was determined. The results suggest that the mean-field evolution is a random-walk process with dissipation. New eruptions of flux produce the random walk, and together differential rotation, meridional flow, and diffusion provide the dissipation. The net effect of each new source depends on its strength and orientation and on the time elapsed before the next eruption.
Sheeley, N. R., Jr.↗
A finite difference informed random walker (FDiRW) solver for strongly inhomogeneous diffusion problems
In nature, many complex multi-physics coupling problems exhibit strong diffusivity inhomogeneity. For instance, in the context of radionuclide absorption by porous wasteform materials within a flowing waste stream, the difference of species’ diffusivity in solid and liquid phases spans by 3~8 orders of magnitude. To solve the diffusion equations with strongly inhomogeneous diffusivity, traditional discretization-based methods, such as the Finite Difference Method (FDM), require infinitesimally small time steps (<10 -10 ) as high spatial resolutions are employed in most microstructure evolution processes, leading to prohibitively high computational costs. Here, this work developed an integrated numerical approach (FDiRW: Finite Difference informed Random Walk) to tackle this challenge. The idea is that utilizing the Random Walk concept, the fast diffusion is modeled as a superposition of point source’s solution for a concentration distribution while FDM is used to obtain the point source’s solution at each node. A mesh-coarsening algorithm is developed to generate an exclusive coarse mesh for FDiRW approach to maximize its efficiency. The effectiveness of the coarse mesh-based FDiRW approach is validated by benchmarking Finite Difference solutions. Numerical results demonstrated that FDiRW achieves a remarkable 1000x computational efficiency improvement over FDM while preserving desired accuracy for a medium-sized model of 192 × 192 × 192 grids. Finally, as models scale up, a floating-point operations (PLOPs) analysis of the FDiRW algorithm reveals that its computational complexity grows quadratically in terms of the number of nodes employed in computation.
36 MATERIALS SCIENCE↗
Migration of lymphocytes on fibronectin-coated surfaces: temporal evolution of migratory parameters
Lymphocytes typically interact with implanted biomaterials through adsorbed exogenous proteins. To provide a more complete characterization of these interactions, analysis of lymphocyte migration on adsorbed extracellular matrix proteins must accompany the commonly performed adhesion studies. We report here a comparison of the migratory and adhesion behavior of Jurkat cells (a T lymphoblastoid cell line) on tissue culture treated and untreated polystyrene surfaces coated with various concentrations of fibronectin. The average speed of cell locomotion showed a biphasic response to substrate adhesiveness for cells migrating on untreated polystyrene and a monotonic decrease for cells migrating on tissue culture-treated polystyrene. A modified approach to the persistent random walk model was implemented to determine the time dependence of cell migration parameters. The random motility coefficient showed significant increases with time when cells migrated on tissue culture-treated polystyrene surfaces, while it remained relatively constant for experiments with untreated polystyrene plates. Finally, a cell migration computer model was developed to verify our modified persistent random walk analysis. Simulation results suggest that our experimental data were consistent with temporally increasing random motility coefficients.
NASA Program Fundamental Space Biology↗