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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Probabilistic measures for biological adaptation and resilience

This paper introduces an approach to quantifying ecological resilience in biological systems, particularly focusing on noisy systems responding to episodic disturbances with sudden adaptations. Incorporating concepts from nonequilibrium statistical mechanics, we propose a measure termed “ecological resilience through adaptation,” specifically tailored to noisy, forced systems that undergo physiological adaptation in the face of stressful environmental changes. Randomness plays a key role, accounting for model uncertainty and the inherent variability in the dynamical response among components of biological systems. Our measure of resilience is rooted in the probabilistic description of states within these systems and is defined in terms of the dynamics of the ensemble average of a model-specific observable quantifying success or well-being. Our approach utilizes stochastic linear response theory to compute how the expected success of a system, originally in statistical equilibrium, dynamically changes in response to a environmental perturbation and a subsequent adaptation. Importantly, the resulting mathematical derivations allow for the estimation of resilience in terms of ensemble averages of simulated or experimental data. Finally, through a simple but clear conceptual example, we illustrate how our resilience measure can be interpreted and compared to other existing frameworks in the literature. The methodology is general but inspired by applications in plant systems, with the potential for broader application to complex biological processes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Social network structure and the spread of complex contagions from a population genetics perspective

Ideas, behaviors, and opinions spread through social networks. If the probability of spreading to a new individual is a non-linear function of the fraction of the individuals’ affected neighbors, such a spreading process becomes a “complex contagion”. This non-linearity does not typically appear with physically spreading infections, but instead can emerge when the concept that is spreading is subject to game theoretical considerations (e.g. for choices of strategy or behavior) or psychological effects such as social reinforcement and other forms of peer influence (e.g. for ideas, preferences, or opinions). Here we study how the stochastic dynamics of such complex contagions are affected by the underlying network structure. Motivated by simulations of complex contagions on real social networks, we present a framework for analyzing the statistics of contagions with arbitrary non-linear adoption probabilities based on the mathematical tools of population genetics. The central idea is to use an effective lower-dimensional diffusion process to approximate the statistics of the contagion. This leads to a tradeoff between the effects of ”selection” (microscopic tendencies for an idea to spread or die out), random drift, and network structure. Our framework illustrates intuitively several key properties of complex contagions: stronger community structure and network sparsity can significantly enhance the spread, while broad degree distributions dampen the effect of selection compared to random drift. Finally, we show that some structural features can exhibit critical values that demarcate regimes where global contagions become possible for networks of arbitrary size. Our results draw parallels between the competition of genes in a population and memes in a world of minds and ideas. Our tools provide insight into the spread of information, behaviors, and ideas via social influence, and highlight the role of macroscopic network structure in determining their fate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Harnessing the Second-Order Metal−Insulator Transition for Neuromorphic Computing

Vanadium oxides are widely studied phase change materials for brain-inspired computing architectures. Systems like VO 2 and V 2 O 3 exhibit first-order metal−insulator transitions (MITs) with hysteresis and percolative switching, increasing stochasticity and device variability. Here, we focus on the less explored Magnéli phase V 4 O 7 , which undergoes a continuous, non-hysteretic, second-order MIT. This surprisingly enables highly reproducible volatile resistive switching in spiking-neuron-type devices. We synthesize V 4 O 7 films, characterize their structural and transport properties, and demonstrate voltage and current-driven threshold switching with electrothermal feedback. In a Pearson–Anson oscillator, V 4 O 7 devices produce stable, tunable spiking across 20–200 kHz, with consistent operation among multiple devices. We introduce a numerical analog leaky-integrate-and-fire (aLIF) model that captures waveform shapes and their dependence on load resistance, temperature, and voltage. Furthermore, these findings suggest that second-order MIT materials like V 4 O 7 are promising for deterministic, scalable spiking neuron arrays for neuromorphic computing.

V4O7↗
DOE OSTI2025

Structured interactions drive abrupt transitions in the spatial organization of microbial communities

Bacteria possess diverse mechanisms to regulate their motility in response to environmental and physiological signals, enabling them to navigate complex habitats and adapt their behavior. Some of these mechanisms are species specific and enable cells to modulate their movement based on the ecological identity of neighboring species. Here, we introduce a model in which bacteria interact via local signals that either enhance or suppress the motility of neighboring cells depending on species type. Through large-scale simulations and a coarse-grained stochastic model, we demonstrate the emergence of a sharp transition driven by nucleation processes: increasing the density of motility-suppressing interactions drives the system from a fully mixed, motile phase to a state characterized by large, stationary bacterial clusters. Remarkably, in systems with a large number of interacting species, this transition can be triggered solely by altering the structure of the motility-regulation interaction matrix while maintaining species and interaction densities constant. In particular, we find that heterogeneous and modular interactions promote the transition more readily than homogeneous random ones. These findings add a dimension to the theory of motility-induced phase separation and contribute to the ongoing effort to understand microbial interactions, suggesting that structured, nonrandom ones may be key to reproducing commonly observed spatial patterns in microbial communities.

bacterial communities↗
NASA NTRS2014

Improving Sensorimotor Function Using Stochastic Vestibular Stimulation

Astronauts experience sensorimotor changes during spaceflight, particularly during G-transition phases. Post flight sensorimotor changes may include postural and gait instability, spatial disorientation, and visual performance decrements, all of which can degrade operational capabilities of the astronauts and endanger the crew. Crewmember safety would be improved if these detrimental effects of spaceflight could be mitigated by a sensorimotor countermeasure and even further if adaptation to baseline could be facilitated. The goal of this research is to investigate the potential use of stochastic vestibular stimulation (SVS) as a technology to improve sensorimotor function. We hypothesize that low levels of SVS will improve sensorimotor performance through stochastic resonance (SR). The SR phenomenon occurs when the response of a nonlinear system to a weak input signal is optimized by the application of a particular nonzero level of noise. Two studies have been initiated to investigate the beneficial effects and potential practical usage of SVS. In both studies, electrical vestibular stimulation is applied via electrodes on the mastoid processes using a constant current stimulator. The first study aims to determine the repeatability of the effect of vestibular stimulation on sensorimotor performance and perception in order to better understand the practical use of SVS. The beneficial effect of low levels of SVS on balance performance has been shown in the past. This research uses the same balance task repeated multiple times within a day and across days to study the repeatability of the stimulation effects. The balance test consists of 50 sec trials in which the subject stands with his or her feet together, arms crossed, and eyes closed on compliant foam. Varying levels of SVS, ranging from 0-700 micro A, are applied across different trials. The subject-specific optimal SVS level is that which results in the best balance performance as measured by inertial measurement units placed on the upper and lower torso of the subjects. Additionally, each individual’s threshold for illusory motion perception of suprasensory electrical vestibular stimulation is measured multiple times within and across days to better understand how multiple SVS test methods compare. The second study aims to demonstrate stochastic resonance in the vestibular system using a perception based motion recognition task. This task measures an individual’s velocity threshold of motion recognition using a 6-degree of freedom Stewart platform and a 3-down/1-up staircase procedure. For this study, thresholds are determined using 150 trials in the upright, head-centered roll tilt motion direction at a 0.2 Hz frequency. We aim to demonstrate the characteristic bell shaped curve associated with stochastic resonance with each subject’s motion recognition thresholds at varying SVS levels ranging from 0 to 1500 micro A. The curve includes the individual’s baseline threshold with no SVS, optimal or minimal threshold at some mid-level of SVS, and finally degraded or increased threshold at a high SVS level. An additional aim is to formally retest each subject at his or her individual optimal SVS level on a different day than the original testing for additional validity. The overall purpose of this research is to further quantify the effects of SVS on various sensorimotor tasks and investigate the practical implications of its use in the context of human space flight so that it may be implemented in the future as a component of a comprehensive countermeasure plan for adaptation to G-transitions.

Galvan, R. C.↗
DOE OSTI2022

Interplay between disorder and collective coherent response: Superradiance and spectral motional narrowing in the time domain

The interplay between static and dynamic disorder and collective optical response in molecular ensembles is an important characteristic of nanoplasmonic and nanophotonic molecular systems. Here we investigate the cooperative superradiant response of a molecular ensemble of quantum emitters under the influence of environmental disorder, including inhomogeneous broadening (as induced by a static random distribution of the molecular transition frequencies) and motional narrowing (as induced by stochastic modulation of these excitation energies). The effect of inhomogeneous broadening is to destroy the coherence of the collective molecular excitation and suppress superradiant emission. However, fast stochastic modulation of the molecular excitation energy can effectively restore the coherence of the quantum emitters and lead to a recovery of superradiant emission, which is an unexpected manifestation of motional narrowing. For a light-scattering process as induced by an off-resonant incident pulse, stochastic modulation leads to inelastic fluorescence emission at the average excitation energy at long times and suggests that dynamic disorder effects can actually lead to collective excitation of the molecular ensemble.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Laser Powder Bed Fusion Additive Manufacturing In-Process Monitoring and Optimization Using Thermionic Emission Detection

In this project, the emission of electrons during laser powder bed fusion additive manufacturing was identified and investigated to resolve the underlying dynamics driven by laser-material interactions. Laser powder bed fusion involves the selective laser melting of metal powder particles layer by layer which fuse together forming a larger 3D structure. Laser-based additive manufacturing approaches such as laser powder bed fusion hold the potential to revolutionize manufacturing of complex metal components in the aerospace, medical, and automotive industries. However, the difficulty in producing defect-free components by metal 3D printing is a major hurdle for widespread commercial adoption. This project resolved important dynamics in laser powder bed fusion including the identification of plasma formation mechanisms, transitions between laser-induced melting modes and stochastic precursors to defect formation. These findings were realized through implementation of electronic sensing diagnostics into an existing testbed system and harnessing capabilities developed for the time dependent analysis of laser powder bed fusion datasets. Importantly, the results advance our understanding of laser-material interactions and reveal that detection of thermionic emission can also resolve information critical to optimization of the laser powder bed fusion fabrication process. The findings are critical for advancing our fundamental understanding of the laser powder bed fusion process and can help assure the requisite fidelity of fabricated components.

36 MATERIALS SCIENCE↗
NASA NTRS1991

A distributed Petri Net controller for a dual arm testbed

This thesis describes the design and functionality of a Distributed Petri Net Controller (DPNC). The controller runs under X Windows to provide a graphical interface. The DPNC allows users to distribute a Petri Net across several host computers linked together via a TCP/IP interface. A sub-net executes on each host, interacting with the other sub-nets by passing a token vector from host to host. One host has a command window which monitors and controls the distributed controller. The input to the DPNC is a net definition file generated by Great SPN. Thus, a net may be designed, analyzed and verified using this package before implementation. The net is distributed to the hosts by tagging transitions that are host-critical with the appropriate host number. The controller will then distribute the remaining places and transitions to the hosts by generating the local nets, the local marking vectors and the global marking vector. Each transition can have one or more preconditions which must be fulfilled before the transition can fire, as well as one or more post-processes to be executed after the transition fires. These implement the actual input/output to the environment (machines, signals, etc.). The DPNC may also be used to simulate a Great SPN net since stochastic and deterministic firing rates are implemented in the controller for timed transitions.

Bjanes, Atle↗
DOE OSTI2023

A game-theoretic approach to nuclear fuel cycle transition analysis under uncertainty

We present a novel methodology for optimizing nuclear fuel cycle transitions that incorporates a game-theoretic approach and captures interactions among multiple decision makers. The methodology is demonstrated using a two-person sequential game with uncertainty, where the two players represent a policy maker and an electric utility company, though the method generalizes to any number and type of individual decision making entities. Coupled with a sophisticated nuclear fuel cycle simulator, rich transition scenarios may be analyzed to identify robust transition strategies. These strategies explicitly treat uncertainties using a stochastic programming approach, devising optimal near-term hedging strategies that simultaneously consider all possible states of the world, maintaining flexibility to allow for intelligent recourse decisions once uncertainties are resolved. In the demonstration game, reactor technology and fuel cycle scheme adopted by the electric utility are shown to depend on both the policy maker’s decisions and the distributions over uncertain technological and economic outcomes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRSDate not supplied

Monte Carlo simulations of neutrino and charged lepton propagation in the Earth with nuPyProp

An accurate modeling of neutrino flux attenuation and the distribution of leptons they produce in transit through the Earth is an essential component to determine neutrino flux sensitivities of underground, sub-orbital and space-based detectors. Through neutrino oscillations over cosmic distances, astrophysical neutrino sources are expected to produce nearly equal fluxes of electron, muon and tau neutrinos. Of particular interest are tau neutrinos that interact in the Earth at modest slant depths to produce leptons. Some leptons emerge from the Earth and decay in the atmosphere to produce extensive air showers. Future balloon-borne and satellite-based opticalCherenkov neutrino telescopes will be sensitive to upward air showers from tau neutrino induced lepton decays. We present nuPyProp, a python code that is part of the nuSpaceSim package. nuPyProp generates look-up tables for exit probabilities and energy distributions for (see paper for proper equation) propagation in the Earth. This flexible code runs with either stochastic or continuous electromagnetic energy losses for the lepton transit through the Earth. Current neutrino cross section models and energy loss models are included along with templates for user input of other models. Results from nuPyProp are compared with other recent simulation packages for neutrino and charged lepton propagation. Sources of modeling uncertainties are described and quantified.

Yosui Akaike↗
DOE OSTI2026

Stochastic Microgrid Scheduling With Chance‐Constrained Resilience Consideration

Traditionally, it is assumed that microgrids transition seamlessly from grid‐connected operation to islanded mode in the event of sudden main grid outages. In reality, the islanding process, especially unintentional islanding, is rarely seamless. Instead, it is subject to voltage and frequency fluctuations caused by the instantaneous disconnection of the point of common coupling (PCC) switch, variations in loads and renewable generation output and even the protection tripping of distributed energy resources (DERs). To mitigate these fluctuations and facilitate a smooth islanding process, we propose a stochastic microgrid scheduling model that incorporates chance‐constrained resilience measures. Specifically, the resilience measure is defined as the probability of successful islanding (PSI), that is, the probability that a microgrid can mitigate the generation‐demand imbalance caused by the disconnection of the PCC switch, variations in load and renewable generation and DER tripping. This measure is modelled using chance constraints. Unlike existing reliability and resilience indices, which typically neglect the possibility of microgrid/DER failure under extreme events and assume their survival while primarily focussing on reducing impact duration or magnitude, the proposed PSI‐based framework explicitly addresses microgrid and DER survival during the islanding transition. The formulated nonlinear chance constraints are approximated using a multiinterval approach and equivalently represented as a mixed‐integer linear programming (MILP) formulation. Case study results validate the proposed method, showing that the PSI estimation error is reduced to less than 8%, compared to approximately 28% with existing methods. Various sensitivity analyses on the DER tripping rate and PSI settings were performed to validate the robustness of the proposed method. In particular, the necessity of accounting for DER tripping in the PSI calculation was demonstrated.

chance constrained optimization↗
NASA NTRS2016

Exhibition of Stochastic Resonance in Vestibular Perception

Astronauts experience sensorimotor changes during spaceflight, particularly during G-transitions. Post flight sensorimotor changes include spatial disorientation, along with postural and gait instability that may degrade operational capabilities of the astronauts and endanger the crew. A sensorimotor countermeasure that mitigates these effects would improve crewmember safety and decrease risk. The goal of this research is to investigate the potential use of stochastic vestibular stimulation (SVS) as a technology to improve sensorimotor function. We hypothesize that low levels of SVS will improve sensorimotor perception through the phenomenon of stochastic resonance (SR), when the response of a nonlinear system to a weak input signal is enhanced by the application of a particular nonzero level of noise. This study aims to advance the development of SVS as a potential countermeasure by 1) demonstrating the exhibition of stochastic resonance in vestibular perception, a vital component of sensorimotor function, 2) investigating the repeatability of SR exhibition, and 3) determining the relative contribution of the semicircular canals (SCC) and otolith (OTO) organs to vestibular perceptual SR. A constant current stimulator was used to deliver bilateral bipolar SVS via electrodes placed on each of the mastoid processes, as previously done. Vestibular perceptual motion recognition thresholds were measured using a 6-degree of freedom MOOG platform and a 150 trial 3-down/1-up staircase procedure. In the first test session, we measured vestibular perceptual thresholds in upright roll-tilt at 0.2 Hz (SCC+OTO) with SVS ranging from 0-700 μA. In a second test session a week later, we re-measured roll-tilt thresholds with 0, optimal (from test session 1), and 1500 μA SVS levels. A subset of these subjects, plus naive subjects, participated in two additional test sessions in which we measured thresholds in supine roll-rotation at 0.2 Hz (SCC) and upright y-translation at 1 Hz (OTO) with SVS up to 700 μA. A sinusoidal galvanic vestibular stimulation (GVS) perceptual threshold was also measured on each test day and used to normalize the SVS levels across subjects. In roll-tilt thresholds with SVS, the characteristic SR curve was qualitatively exhibited in 10 of 12 subjects, and the improvement in motion threshold was significant in 6 subjects, indicating that optimal SVS improved passive body motion perception in a way that is consistent with classical SR theory. A probabilistic comparison to numeric simulations further validated these experimental results. On the second test session, 4 out of the 10 SR exhibitors showed repeated improvement with SVS compared to the no SVS condition. Data collection is ongoing for the last two test sessions in which SCC and OTO only perceptual motion recognition thresholds are being measured with SVS. The final results of these test sessions will give insight into whether vestibular perceptual SR can occur when only one type of vestibular sensor is sensing motion or if it is more evident when sensory integration between the SCC and OTO is occurring during the motion. The overall purpose of this research is to further quantify the effects of SVS on various sensorimotor tasks and to gain a more fundamental understanding of how SVS causes SR in the vestibular system. In the context of human space flight, results from this research will help in understanding how SVS may be practically implemented in the future as a component of a comprehensive countermeasure plan for G-transition adaptation.

Galvan-Garza, R. C.↗
DOE OSTI2026

Gamma rays and gravitational waves from inelastic Higgs portal dark matter

We explore a simple and predictive dark matter scenario involving a complex scalar field, ϕ , coupled to the Higgs portal with no additional field content. In the UV, the field possesses a global U ( 1 ) symmetry which is broken by mass terms and Higgs portal interactions. In the mass basis, the complex field splits into a pair of real scalars with a small mass splitting (in analogy to pseudo-Dirac fermions), such that the Higgs portal acquires both diagonal and off-diagonal terms with respect to these eigenstates. In the parameter space where the off-diagonal interaction predominates, this scenario is safe from direct detection constraints. Moreover, this model provides a viable explanation for the longstanding Galactic Center γ -ray excess. Additionally, this model influences the Higgs potential in a way that could facilitate a strong first-order electroweak phase transition in the early Universe, potentially leading to a stochastic gravitational wave background that could fall within the reach of upcoming space-based detectors.

Hooper, Dan [Wisconsin U., Madison] (ORCID:0009000↗
NASA NTRS1988

Electronic excitation and quenching of atoms at insulator surfaces

A trajectory-based semiclassical method is used to study electronically inelastic collisions of gas atoms with insulator surfaces. The method provides for quantum-mechanical treatment of the internal electronic dynamics of a localized region involving the gas/surface collision, and a classical treatment of all the nuclear degrees of freedom (self-consistently and in terms of stochastic trajectories), and includes accurate simulation of the bath-temperature effects. The method is easy to implement and has a generality that holds promise for many practical applications. The problem of electronically inelastic dynamics is solved by computing a set of stochastic trajectories that on thermal averaging directly provide electronic transition probabilities at a given temperature. The theory is illustrated by a simple model of a two-state gas/surface interaction.

Swaminathan, P. K.↗
DOE OSTI2022

Snowmass2021 Cosmic Frontier White Paper: Future Gravitational-Wave Detector Facilities

The next generation of gravitational-wave observatories can explore a wide range of fundamental physics phenomena throughout the history of the universe. These phenomena include access to the universe's binary black hole population throughout cosmic time, to the universe's expansion history independent of the cosmic distance ladders, to stochastic gravitational-waves from early-universe phase transitions, to warped space-time in the strong-field and high-velocity limit, to the equation of state of nuclear matter at neutron star and post-merger densities, and to dark matter candidates through their interaction in extreme astrophysical environments or their interaction with the detector itself. We present the gravitational-wave detector concepts than can drive the future of gravitational-wave astrophysics. We summarize the status of the necessary technology, and the research needed to be able to build these observatories in the 2030s.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

A control-inspired approach for energy transition planning under uncertainty

As the global carbon footprint continues to grow, many countries are implementing carbon emission reduction policies which have incentivized the expansion of low-carbon and renewable technologies. However, the speed and scale of deployment falls short of that needed to meet climate goals. Energy system models serve as key tools for guiding investment decisions and helping policymakers evaluate the effects of various policies on the development of an energy system. This study focuses on the energy system of the United States and builds upon prior work by incorporating more geographic granularity to account for the trade of commodities and addresses transmission congestion through electricity price adjustments. Furthermore, real-world characteristics, such as delays in constructing new liquid fuel production and electricity generation facilities, are integrated using a sequential decision-making approach that better reflects how decisions can be updated as uncertainties unfold. Results demonstrate that stochastic programming combined with sequential decision-making produces energy transition pathways that are robust to multiple uncertain futures. Additionally, considering real-world characteristics significantly impacts the deployment of renewable technologies and the ability to meet carbon emission reduction goals while also reliably meeting demand. These findings highlight the importance of accounting for uncertainty and real-world characteristics to avoid overly optimistic projections in energy system planning.

energy systems↗
NASA NTRS1989

Gravitational radiation from primordial solitons and soliton-star binaries

The possibility that both the formation of nontopological solitons in a primordial second-order phase transition and binary systems of soliton stars could generate a stochastic gravitational-wave background is examined. The present contribution of gravitational radiation to the energy density of the universe from these processes is estimated for a number of different models. The detectability of such contributions from the timing measurements of the millisecond pulsar and spaceborne laser interferometry is briefly discussed and compared to other cosmological and local sources of background gravitational waves.

Gleiser, Marcelo↗