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DOE OSTI2017

Sampling and Analysis Plan for Supplemental Environmental Project: Aquatic Life Surveys

As part of a settlement agreement for nuclear waste incidents in 2014, several supplemental environment projects (SEPs) were initiated at Los Alamos National Laboratory (LANL or the Laboratory) between the U.S. Department of Energy and the state of New Mexico. One SEP from this agreement consists of performing aquatic life surveys and will be used to assess the applicability of using generic ambient water-quality criteria (AWQC) for aquatic life. AWQC are generic criteria developed by the U.S. Environmental Protection Agency (EPA) to cover a broad range of aquatic species and are not unique to a specific region or state. AWQC are established by a composition of toxicity data, called species sensitivity distributions (SSDs), and are determined by LC50 (lethal concentration of 50% of the organisms studied) acute toxicity experiments for chemicals of interest. It is of interest to determine whether aquatic species inhabiting waters on the Pajarito Plateau are adequately protected using the current generic AWQC. The focus of this study will determine which aquatic species are present in ephemeral, intermittent, and perennial waters within LANL boundaries and from reference waters adjacent to LANL. If the species identified from these waters do not generally represent species used in the SSDs, then SSDs may need to be modified and AWQC may need to be updated. This sampling and analysis plan details the sampling methodology, surveillance locations, temporal scheduling, and analytical approaches that will be used to complete aquatic life surveys. A significant portion of this sampling and analysis plan was formalized by referring to Appendix E: SEP Aquatic Life Surveys DQO (Data Quality Objectives).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Unraveling the 2021 Central Tennessee flood event using a hierarchical multi-model inundation modeling framework

Flood prediction systems need hierarchical atmospheric, hydrologic, and hydraulic models to predict rainfall, runoff, streamflow, and floodplain inundation. The accuracy of such systems depends on the error propagation through the modeling chain, sensitivity to input data, and choice of models. In this study, we used multiple precipitation forcings (hindcast and forecast) to drive hydrologic and hydrodynamic models to analyze the impacts of various drivers on the estimates of flood inundation depth and extent. We implement this framework to unravel the August 2021 extreme flooding event that occurred in Central Tennessee, USA. We used two radar-based quantitative precipitation estimates (STAGE4 and MRMS) as well as quantitative precipitation forecasts (QPF) from the National Weather Service Weather Prediction Center (WPC) to drive a series of models in the hierarchical framework, including the Variable Infiltration Capacity (VIC) land surface model, the Routing Application for Parallel Computation of Discharge (RAPID) river routing model, and the AutoRoute and TRITON inundation models. An evaluation with observed high-water marks demonstrates that the framework can reasonably simulate flood inundation. Despite the complex error propagation mechanism of the modeling chain, we show that inundation estimates are most sensitive to rainfall estimates. Most notably, QPF significantly underestimates flood magnitudes and inundations leading to unanticipated severe flooding for all stakeholders involved in the event. Finally, we discuss the implications of the hydrodynamic modeling framework for real-time flood forecasting.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1992

Deep-space navigation with differenced data types. Part 3: An expanded information content and sensitivity analysis

An approximate six-parameter analytic model for Earth-based differential range measurements is presented and is used to derive a representative analytic approximation for differenced Doppler measurements. The analytical models are tasked to investigate the ability of these data types to estimate spacecraft geocentric angular motion, Deep Space Network station oscillator (clock/frequency) offsets, and signal-path calibration errors over a period of a few days, in the presence of systematic station location and transmission media calibration errors. Quantitative results indicate that a few differenced Doppler plus ranging passes yield angular position estimates with a precision on the order of 0.1 to 0.4 micro-rad, and angular rate precision on the order of 10 to 25 x 10(exp -12) rad/sec, assuming no a priori information on the coordinate parameters. Sensitivity analyses suggest that troposphere zenith delay calibration error is the dominant systematic error source in most of the tracking scenarios investigated; as expected, the differenced Doppler data were found to be much more sensitive to troposphere calibration errors than differenced range. By comparison, results computed using wideband and narrowband (delta) VLBI under similar circumstances yielded angular precisions of 0.07 to 0.4 micro-rad, and angular rate precisions of 0.5 to 1.0 x 10(exp -12) rad/sec.

Estefan, J. A.↗

DOE OSTI2022

My Virtual Cancer

Since each cancer has its own unique characteristics, each one can respond differently to the same treatments. Therefore, the creation of a digital twin (DT) of cancer can assist us in predicting the evolution of an individual's cancer through modeling each tumor's characteristics and response to treatment. Hence, we propose to take advantage of new advances in computational approaches and combine mechanistic, machine learning, and stochastic modeling approaches to create “My Virtual Cancer", a DT platform. To establish a personalized DT, we use patient-specific data for parameter estimations, sensitivity analysis, and uncertainty quantification. For each patient, we will estimate the values of parameters of their QSP model using the patient's data. We perform a multi-dimensional sensitivity analysis and uncertainty quantification on the mechanistic model to find a set of critical interactions and predict the intervals of confidence. Since this QSP model includes the data-driven mechanistic model of cells and molecules' interaction networks, one of the ultimate results of this DT would be the prediction of evolution of tumors.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1995

Star formation activity in spiral galaxy disks and the properties of radio halos: Observational evidence for a direct dependence

In this article we address observationally the questions: how does star formation (SF) in the disks of galaxies lead to the creation of radio halos, and what minimum energy input into the interstellar medium (ISM) is needed to facilitate this? For the investigation we use a sample of five edge-on galaxies exhibiting radio continuum emmission in their halos and enhanced SF spread over large parts of their disks. In a detailed study of the two galaxies in our sample for which we have the best data, NGC 891 and NGC 4631, we show that the radio halos cut off abruptly at galactocentric radii smaller than those of the underlying thin radio disks. Our most important result is that the halo cutoffs are spatially coincident with the radii where the SF activity in the underlying disks drops sharply. The difference in radius of the emission distributions tracing ongoing SF in the disks (IRAS 50 micrometers, H alpha) versus that of the nonthermal radio continuum thin disks (tracing the distribution of cosmic-ray (CR) electrons) is typically a few kpc. This difference in extent is caused by CR diffusion. We have measured the CR diffusion coefficients in the thin disks of both NGC 891 and NGC 4631. For radial diffusion of CR electrons within the galactic disks the values are D(sub r) = 1.1-2.5 x 10 (exp 29) sq cm/s (NGC 4631) and D(sub r) = 1.2 x 10(exp 29) sq cm/s (NGC 891). For motions in the z-direction in areas within the thin disks where no outflows occur, we derive a firm upper limit of D(sub z) less than or equal to 0.2 x 10(exp 28) sq cm/s for NGC 891. The value for NGC 4631 is D(sub z = 1.4 x 10 (exp 28) sq cm/s. The other three galaxies in our sample, NGC 3044, NGC 4666, and NGC 5775 show (at the sensitivity of our data) less extended, more filamentary radio halos. Isolates spurs or filaments of nonthermal radio continuum emission in their halos are traced only above the most actively star-forming regions in the disks. This, in conjuction with the results obtained for NGC 891 and NGC 4631, suggests a direct connection between the shapes and radial extents of radio halos of normal galaxies and the level and the spatial distribution of the current SF in their disks. The existence of filamentary structures implies that expansion and convection of CR-heated plasma plays an important role even at low z-distances above the plane. Based on radio data we derive the disk-averaged mean energy input rates into the ISM due to supernova explosions per unit surface area in nine galaxies, including the ones in our sample. We find a clear trend in the sense that the galaxies with the highest mean energy input rates in the underlying disks have the most extended and pervasisve radio halos. Below a certain threshohld, outflows are inhibited. As a lower limit for this threshhold we derive an energy input rate of approximately 10 (exp -4) erg/s sq cm. The fact that radio halo emission is found only above the most luminous giant H 2 regions in late-type 'normal' galaxies (of type Sbc or later) indicates that only these are capable of initiating disk-halo interactions by locally exceeding the threshold. The distribution of the local outflows determines the overall shapes of the CR halos and leads to the observed filamentary structures.

Dahlem, Michael↗

NASA NTRS2014

Cloud Thermodynamic Phase Detection with Polarimetrically Sensitive Passive Sky Radiometers

The primary goal of this project has been to investigate if ground-based visible and near-infrared passive radiometers that have polarization sensitivity can determine the thermodynamic phase of overlying clouds, i.e. if they are comprised of liquid droplets or ice particles. While this knowledge is important by itself for our understanding of the global climate, it can also help improve cloud property retrieval algorithms that use total (unpolarized) radiance to determine Cloud Optical Depth (COD). This is a potentially unexploited capability of some instruments in the NASA Aerosol Robotic Network (AERONET), which, if practical, could expand the products of that global instrument network at minimal additional cost. We performed simulations that found, for zenith observations, cloud thermodynamic phase is often expressed in the sign of the Q component of the Stokes polarization vector. We chose our reference frame as the plane containing solar and observation vectors, so the sign of Q indicates the polarization direction, parallel (negative) or perpendicular (positive) to that plane. Since the quantity of polarization is inversely proportional to COD, optically thin clouds are most likely to create a signal greater than instrument noise. Besides COD and instrument accuracy, other important factors for the determination of cloud thermodynamic phase are the solar and observation geometry (scattering angles between 40 and 60 degrees are best), and the properties of ice particles (pristine particles may have halos or other features that make them difficult to distinguish from water droplets at specific scattering angles, while extreme ice crystal aspect ratios polarize more than compact particles). We tested the conclusions of our simulations using data from polarimetrically sensitive versions of the Cimel 318 sun photometerradiometer that comprise AERONET. Most algorithms that exploit Cimel polarized observations use the Degree of Linear Polarization (DoLP), not the individual Stokes vector elements (such as Q). For this reason, we had no information about the accuracy of Cimel observed Q and the potential for cloud phase determination. Indeed, comparisons to ceilometer observations with a single polarized spectral channel version of the Cimel at a site in the Netherlands showed little correlation. Comparisons to Lidar observations with a more recently developed, multi-wavelength polarized Cimel in Maryland, USA, show more promise. This divergence between simulations and observations has prompted us to begin the development of a small test instrument called the Sky Polarization Radiometric Instrument for Test and Evaluation (SPRITE). This instrument is specifically devoted to the accurate observation of Q, and the testing of calibration and uncertainty assessment techniques, with the ultimate goal of understanding the practical feasibility of these measurements.

Knobelspiesse, Kirk D.↗

NASA NTRS2002

Phylogeny and systematic position of Opiliones: a combined analysis of chelicerate relationships using morphological and molecular data

The ordinal level phylogeny of the Arachnida and the suprafamilial level phylogeny of the Opiliones were studied on the basis of a combined analysis of 253 morphological characters, the complete sequence of the 18S rRNA gene, and the D3 region of the 28S rRNA gene. Molecular data were collected for 63 terminal taxa. Morphological data were collected for 35 exemplar taxa of Opiliones, but groundplans were applied to some of the remaining chelicerate groups. Six extinct terminals, including Paleozoic scorpions, are scored for morphological characters. The data were analyzed using strict parsimony for the morphological data matrix and via direct optimization for the molecular and combined data matrices. A sensitivity analysis of 15 parameter sets was undertaken, and character congruence was used as the optimality criterion to choose among competing hypotheses. The results obtained are unstable for the high-level chelicerate relationships (except for Tetrapulmonata, Pedipalpi, and Camarostomata), and the sister group of the Opiliones is not clearly established, although the monophyly of Dromopoda is supported under many parameter sets. However, the internal phylogeny of the Opiliones is robust to parameter choice and allows the discarding of previous hypotheses of opilionid phylogeny such as the "Cyphopalpatores" or "Palpatores." The topology obtained is congruent with the previous hypothesis of "Palpatores" paraphyly as follows: (Cyphophthalmi (Eupnoi (Dyspnoi + Laniatores))). Resolution within the Eupnoi, Dyspnoi, and Laniatores (the latter two united as Dyspnolaniatores nov.) is also stable to the superfamily level, permitting a new classification system for the Opiliones. c2002 The Willi Hennig Society.

NASA Discipline Evolutionary Biology↗

DOE OSTI2021

Application of Machine Learning Algorithms to Identify Problematic Nuclear Data

In this work we aim to show that Machine learning algorithms are promising tools for the identification of nuclear data that contribute to increased errors in transport simulations. We demonstrate this through an application of a machine learning algorithm (Random Forest) to the Whisper/MCNP6 criticality validation library to identify nuclear data that are associated with an increase of the bias (simulated - experimental $k_{eff}$) in the calculations. Specifically, the $k_{eff}$ sensitivity profiles (w.r.t. nuclear data) of 233 U solution benchmarks are used to predict the bias and Shapley Additive Explanations (SHAP) are used to explain how the sensitivities are related to the predicted bias. The SHAP values can be interpreted as sensitivity coefficients of the machine learning model to the $k_{eff}$ sensitivities which are used to make predictions of bias. Using the SHAP values we can identify specific subsets of nuclear data which have the highest probability of influencing bias. We demonstrate the utility of this method by showing how SHAP values were used to identify an inconsistency in the 19 F inelastic scattering nuclear data. The methodology presented here is not limited to transport problems and can be applied to other simulations if there are experimental measurements to compare against, simulations of those experimental measurements, and the ability to calculate sensitivities of the model output with respect to the data inputs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2003

Transonic Experimental Observations of Abrupt Wing Stall on an F/A-18E Model (Invited)

A transonic wind tunnel test of an 8% F/A-18E model was conducted in the NASA Langley Research Center (LaRC) 16 ft Transonic Tunnel (16-ft TT) to investigate on-surface flow physics during stall. The technical approach employed focused on correlating static (or time-averaged) and unsteady wind-tunnel test data to the unsteady wing-stall events using force, moment, pressure, and pressure-sensitive-paint measurements. This paper focuses on data obtained on the pre-production configuration of the F/A-18E aircraft at Mach number of 0.90. The flow unsteadiness occurring on the wing as the wing went through the stall process was captured using the time history of balance and pressure measurements and by calculating the root mean square (RMS) for a number of instrument signals. The second step was to gather global perspectives on the pressures influencing the wing stall process. The abrupt wing stall experienced by the 8% F/A-18E Model was observed to be an unsteady event triggered by the rapid advancement of separation, which had migrated forward from the trailing edge, to the leading-edge flap hingeline over a very small increment in angle of attack. The angle of attack at which this stall occurred varied, from run to run, over an 1 deg increment. The abrupt wing stall was observed, using pressure-sensitive-paint, to occur simultaneously on both wing panels or asymmetrically. The pressure-sensitive paint data and wingroot bending moment data were essential in providing insight to the flow structures occurring over the wing and the possible asymmetry of those flow structures. A repeatability analysis conducted on eight runs of static data provided a quick and inexpensive examination of the unsteady aerodynamic characteristics of abrupt wing stall. The results of the repeatability analysis agreed extremely well with data obtained using unsteady measurement techniques. This approach could be used to identify test conditions for more complex unsteady data measurements using special instrumentation.

McMillin, S. Naomi↗

NASA NTRS2003

Transonic Experimental Observations of Abrupt Wing Stall on an F/A-l8E Model

A transonic wind tunnel test of an 8% F/A-18E model was conducted in the NASA Langley Research Center (LaRC) 16 ft Transonic Tunnel (16-ft TT) to investigate on-surface flow physics during stall. The technical approach employed focused on correlating static (or time-averaged) and unsteady wind-tunnel test data to the unsteady wing-stall events using force, moment, pressure, and pressure-sensitive-paint measurements. This paper focuses on data obtained on the pre-production configuration of the F/A-18E aircraft at Mach number of 0.90. The flow unsteadiness occurring on the wing as the wing went through the stall process was captured using the time history of balance and pressure measurements and by calculating the root mean square (RMS) for a number of instrument signals. The second step was to gather global perspectives on the pressures influencing the wing stall process. The abrupt wing stall experienced by the 8% F/A-18E Model was observed to be an unsteady event triggered by the rapid advancement of separation, which had migrated forward from the trailing edge, to the leading-edge flap hingeline over a very small increment in angle of attack. The angle of attack at which this stall occurred varied, from run to run, over an 1 degree increment. The abrupt wing stall was observed, using pressure-sensitive-paint, to occur simultaneously on both wing panels or asymmetrically. The pressure-sensitive paint data and wing-root bending moment data were essential in providing insight to the flow structures occurring over the wing and the possible asymmetry of those flow structures. A repeatability analysis conducted on eight runs of static data provided a quick and inexpensive examination of the unsteady aerodynamic characteristics of abrupt wing stall. The results of the repeatability analysis agreed extremely well with data obtained using unsteady measurement techniques. This approach could be used to identify test conditions for more complex unsteady data measurements using special instrumentation.

McMillin, S. Naomi↗

DOE OSTI2018

Mapping canopy defoliation by herbivorous insects at the individual tree level using bi-temporal airborne imaging spectroscopy and LiDAR measurements

Defoliation by herbivorous insects is a widespread forest disturbance driver, affecting global forest health and ecosystem dynamics. Additionally, compared with time- and labor-intensive field surveys, remote sensing provides the only realistic approach to mapping canopy defoliation by herbivorous insects over large spatial and temporal scales. However, the spectral and structural signatures of defoliation by insects at the individual tree level have not been well studied. Additionally, the predictive power of spectral and structural metrics for mapping canopy defoliation has seldom been compared. These critical knowledge gaps prevent us from consistently detecting and mapping canopy defoliation by herbivorous insects across multiple scales. During the peak of a gypsy moth outbreak in Long Island, New York in summer 2016, we leveraged bi-temporal airborne imaging spectroscopy (IS, i.e., hyperspectral imaging) and LiDAR measurements at 1m spatial resolution to explore the spectral and structural signatures of canopy defoliation in a mixed oak-pine forest. We determined that red edge and near-infrared spectral regions within the IS data were most sensitive to crown-scale defoliation severity. LiDAR measurements including B70 (i.e., 70th bincentile height), intensity skewness, and kurtosis were effectively able to detect structural changes caused by herbivorous insects. In addition to canopy leaf loss, increased exposure of understory and non-photosynthetic materials contributed to the detected spectral and structural signatures. Comparing the ability of individual sensors to map canopy defoliation, the LiDAR-only Ordinary Least-Square (OLS) model performed better than the IS-only model (Adj. R-squared = 0.77, RMSE = 15.37% vs. Adj. R- squared = 0.63, RMSE = 19.11%). The IS+LiDAR model improved on performance of the individual sensors (Adj. R-squared = 0.81, RMSE = 14.46%). Our study improves our understanding of spectral and structural signatures of defoliation by herbivorous insects and presents a novel approach for mapping insect defoliation at the individual tree level. Furthermore, with the current and next generation of spaceborne sensors (e.g., WorldView-3, Landsat, Sentinel-2, HyspIRI, and GEDI), higher accuracy and frequent monitoring of insect defoliation may become more feasible across a range of spatial scales, which are critical for ecological research and management of forest resources including the economic consequences of forest insect infestations (e.g., reduced growth and increased mortality), as well as for informing and testing of carbon cycle models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Introduction to the Bioproduct Transition Dynamics Model

The U.S. Department of Energy, Bioenergy Technologies Office has a broad understanding of different conversion processes that produce bioproducts (chemicals derived from biomass feedstocks) and the market attributes of those processes. However, bioproducts have in many cases proven to be difficult to scale up to commercial production and bring to market, and there is currently a need for greater understanding around the possible successful scenarios for advancing the bioproducts industry. Insight into the myriad factors that impact the success of individual bioproducts and the growth of the bioproducts industry will enable bioproduct stakeholders to evaluate strategies for development and investment that could achieve the greatest impact. An understanding of these factors will also enable the identification of synergies between the bioproducts and biofuels industries that occur through shared learning and co-production. The Bioproduct Transition Dynamics (BTD) model explores questions such as the following: what are the factors that separate a successful, commercially produced bioproduct like succinic acid from one that never progresses beyond bench-scale lab research? Can these factors be influenced by stakeholders, and to what extent? The BTD model uses system dynamics to capture the impacts of investor decision-making, bioproduct techno-economics, and market factors during the early stages of bioproduct development. Key components of the BTD model include techno-economic benchmarks that inform the investor decision-making process, failures and setbacks in development and the resulting need for additional work, and the impacts of effective or ineffective management during each development stage. These factors and their interactions are tracked through bench-scale laboratory research, piloting, demoing, and the construction and operation of the first commercial-scale plant. Bioproduct development is linked to the biofuels industry through a shared-learning model, enabling the benefit to biofuels from bioproduct technology and feedstock supply chain development to be quantified. A wide variety of bioproducts can be analyzed using the BTD model, including bioproducts that have been developed through economic or policy-driven mechanisms, and those with either niche (low volume) or scalable (high volume) markets. The BTD model also has the potential to apply to technology development processes outside the bioproducts industry; background research performed for this project has shown that the early stages of technology development are similar, and impacted by similar factors, regardless of the exact industry. This presentation will cover the BTD model logic, input data, validation process, and results of a sensitivity analysis based on techno-economic data for succinic acid. The sensitivity analysis was performed to identify factors with the largest impact on the eventual success or failure of a bioproduct. Results indicate that management effectiveness, which affects how efficiently money spent is converted into technological advancements, is the single most important factor in determining whether a bioproduct reaches commercial-scale production. The capacity of the first commercial plant and the type of biomass feedstock used, as well as the presence of government support in the form of cost-sharing, were also identified as significant factors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2018

A System Dynamics Model of Early-Stage Transition Dynamics in the Bioproducts Industry

The U.S. Department of Energy, Bioenergy Technologies Office has a broad understanding of different conversion processes that produce bioproducts (chemicals derived from biomass feedstocks) and the techno-economic attributes of those processes. However, bioproducts have in many cases proven to be difficult to scale up to commercial production, and there is currently a need for greater understanding around the possible successful scenarios for advancing the bioproducts industry. Insight into the myriad factors that impact the success of individual bioproducts and the growth of the bioproducts industry will enable bioproduct stakeholders to evaluate strategies for development and investment that could achieve the greatest impact. An understanding of these factors will also enable the identification of synergies between the bioproducts and biofuels industries that occur through shared learning and co-production. The Bioproduct Transition Dynamics (BTD) model explores questions such as the following: what are the factors that separate a successful, commercially produced bioproduct like succinic acid from one that never progresses beyond bench-scale lab research? Can these factors be influenced by stakeholders, and to what extent? The BTD model uses system dynamics to capture the impacts of investor decision-making, bioproduct techno-economics, and end use factors during the early stages of bioproduct development. Key components of the BTD model include techno-economic benchmarks that inform the investor decision-making process, failures and setbacks in development and the resulting need for additional work, and the impacts of effective or ineffective management during each development stage. These factors and their interactions are tracked through bench-scale laboratory research, piloting, demoing, and the construction and operation of the first commercial-scale plant. Bioproduct development is linked to the biofuels industry through a shared-learning model, enabling the benefit to biofuels from bioproduct technology and feedstock supply chain development to be quantified. A wide variety of bioproducts can be analyzed using the BTD model, including bioproducts that have been developed through economic or policy-driven mechanisms, and those with either niche (low volume) or scalable (high volume) demand. The BTD model also has the potential to apply to technology development processes outside the bioproducts industry; background research performed for this project has shown that the early stages of technology development are similar, and impacted by similar factors, regardless of the exact industry. This presentation will cover the BTD model logic, input data, validation process, and results of a sensitivity analysis based on techno-economic data for succinic acid. The sensitivity analysis was performed to identify factors with the largest impact on the eventual success or failure of a bioproduct. Results indicate that management effectiveness, which affects how efficiently money spent is converted into technological advancements, is the single most important factor in determining whether a bioproduct reaches commercial-scale production. The capacity of the first commercial plant and the type of biomass feedstock used, as well as the presence of government support in the form of cost-sharing, were also identified as significant factors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Nearest neighbour distributions: New statistical measures for cosmological clustering

ABSTRACT The use of summary statistics beyond the two-point correlation function to analyse the non-Gaussian clustering on small scales, and thereby, increasing the sensitivity to the underlying cosmological parameters, is an active field of research in cosmology. In this paper, we explore a set of new summary statistics – the k-Nearest Neighbour Cumulative Distribution Functions (kNN-CDF). This is the empirical cumulative distribution function of distances from a set of volume-filling, Poisson distributed random points to the k-nearest data points, and is sensitive to all connected N-point correlations in the data. The kNN-CDF can be used to measure counts in cell, void probability distributions, and higher N-point correlation functions, all using the same formalism exploiting fast searches with spatial tree data structures. We demonstrate how it can be computed efficiently from various data sets – both discrete points, and the generalization for continuous fields. We use data from a large suite of N-body simulations to explore the sensitivity of this new statistic to various cosmological parameters, compared to the two-point correlation function, while using the same range of scales. We demonstrate that the use of kNN-CDF improves the constraints on the cosmological parameters by more than a factor of 2 when applied to the clustering of dark matter in the range of scales between 10 and $40\, h^{-1}\, {\rm Mpc}$. We also show that relative improvement is even greater when applied on the same scales to the clustering of haloes in the simulations at a fixed number density, both in real space, as well as in redshift space. Since the kNN-CDF are sensitive to all higher order connected correlation functions in the data, the gains over traditional two-point analyses are expected to grow as progressively smaller scales are included in the analysis of cosmological data, provided the higher order correlation functions are sensitive to cosmology on the scales of interest.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

In search of large signals at the cosmological collider

We look for oscillating signals in the primordial bispectrum from new physics heavy particles which are visibly large for next generation large scale structures (LSS) survey. We show that in ordinary inflation scenarios where a slow-rolling inflaton generates density fluctuations and with no breaking of scale invariance or spacetime symmetry, there exist no naturally large signals unless the rolling inflaton generates a parity-odd chemical potential for the heavy particles. We estimate the accessibility of this signal through observations. While current CMB data are already sensitive in the most optimistic scenario, future probes, including LSS survey and 21 cm observation, can cover interesting regions of the model space.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Constraining non-standard neutrino interactions with neutral current events at long-baseline oscillation experiments

We explore, for the first time, neutral-curren t events at long-baseline experiments to constrain vector and axial-vector neutrino non-standard interactions (NSI) with quarks. We leverage the flavor dependence of NSIs to perform an oscillation analysis in the neutral- current channel. We first introduce a framework to parametrize the effect of NSI on the cross section. Then, as an example, we analyze NOvA neutral-current data which provides significantly improved constraints on the axial-vector NSI parameters ${\varepsilon}_{\mu \mu}^A$, ${\varepsilon}_{\tau \tau}^A$ and ${\varepsilon}_{e\mu}^A$. This is highly complementary to constraints from SNO data, which, differently from long-baseline neutral current data, is not sensitive to isospin conserving NSIs ${\varepsilon}_u^A$ = ${\varepsilon}_d^A$. Additionally, we disfavor large values of the diagonal vectorial NSI ${\varepsilon}_{\mu \mu}^{VV}$ and ${\varepsilon}_{\tau \tau}^V$ which originate from the LMA-Dark solution. We also highlight the complementarity between NSI searches at oscillation experiments using charged current and neutral current channels.

neutrino interactions↗

DOE OSTI2020

The second Higgs at the lifetime frontier

We assess the current coverage and the future discovery potential of LHC searches for heavy Higgs bosons decaying into long-lived particles (LLPs), focusing primarily on the production of pairs of LLPs with hadronic final states. These signatures are generic in dark sectors where a heavy scalar decays into pairs of lighter states which subsequently mix with the Standard Model Higgs. We show that a handful of existing analyses provide broad coverage of LLP decay lengths ranging from millimeters to tens of meters, and explore the complementarity between searches for displaced and prompt final states in several simplified models. For both heavy singlet and heavy doublet scalars, LLP searches typically provide the leading sensitivity in current data and exhibit the strongest discovery potential in future LHC runs. We further translate the impact of these searches into the parameter space of various Twin Higgs models, demonstrating that LLP searches are a promising avenue for discovering a Twin Higgs with displaced decays. Finally, we propose a variety of additional search channels that would improve coverage of the second Higgs at the lifetime frontier.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Exotic field theories for (hybrid) fracton phases from imposing constraints in foliated field theory

Fracton phases of matter are gapped phases of matter that, by dint of their sensitivity to UV data, demand non-standard quantum field theories to describe them in the IR. Two such approaches are foliated quantum theory and exotic field theory. In this paper, we explicitly construct a map from one to the other and work out several examples. In particular, we recover the equivalence between the foliated and exotic fractonic BF theories recently demonstrated at the level of operator correspondence. We also demonstrate the equivalence of toric code layers and the anisotropic model with lineons and planons to the foliated BF theory with one and two foliations, respectively. Finally, we derive new exotic field theories that provide simple descriptions of hybrid fracton phases from foliated field theries known to do so. Our results both provide new examples of exotic field theories and pave the way toward their systematic construction from foliated field theories.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗