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At least 73 records · Page 4

Electrodynamic Shaker Capability Estimation Through Experimental Dynamic Substructuring [Thesis]

Electrodynamic shaker systems are an essential tool in shock and vibration testing of dynamic environments. However, the specific performance capability of these systems is difficult to characterize. The dynamics of the shaker itself, the device under test and the specific test configuration used all couple to create a dynamic response unique to each test. Poorly predicted limitations in shaker capability affect the ability to achieve test specifications, delay testing schedules, and create difficulties for choosing test equipment. To predict shaker capability for a specific test configuration prior to setup, a lumped parameter model of the shaker system and a modal model of a device under test was developed. These models were then analytically coupled using LaGrange multiplier frequency based substructuring to estimate their coupled frequency response functions. The coupled frequency response functions were used to predict electrical inputs required to meet a given test specification. These input requirements were finally compared to a validation test using the specification and setup. Input requirements estimated using the substructuring estimated frequency response functions showed significant error. However, results using an ideal frequency response function showed very little error. These results indicate that with a better method of experimental dynamic substructuring employed it would be possible to accurately predict shaker capability for a given test configuration prior to setup.

42 ENGINEERING↗

A Gaussian field approach to the planar electric double layer structures in electrolyte solutions

Here, in this work, the planar, electric, double-layer structures of non-polarizable electrodes in electrolyte solutions are studied with Gaussian field theory. A response function with two Yukawa functions is used to capture the electrostatic response of the electrolyte solution, from which the modified response function in the planar symmetry is derived analytically. The modified response function is further used to evaluate the induced charge density and the electrostatic potential near an electrode. The Gaussian field theory, combined with a two-Yukawa response function, can reproduce the oscillatory decay behavior of the electric potentials in concentrated electrolyte solutions. When the exact sum rules for the bulk electrolyte solutions and the electric double layers are used as constraints to determine the parameters of the response function, the Gaussian field theory could at least partly capture the nonlinear response effect of the surface charge density. Comparison with results for a planar electrode with fixed surface charge densities from molecular simulations demonstrates the validity of Gaussian field theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

G-Function Library for Modeling Vertical Bore Ground Heat Exchanger

This library contains g-functions (thermal response functions) for standard, regularly spaced vertical borehole ground heat exchangers. In total, it contains 34, 321 configurations. To permit interpolation, each configuration has g-functions for heights of 24, 48, 96, 192, and 384 m. All the g-functions were calculated with burial depths of 2m, and borehole diameters of 15 to 17.5 cm, depending on height. In configurations with uniform spacing, the spacing between the boreholes is set to 5m, though it can be scaled to other horizontal spacings.

15 GEOTHERMAL ENERGY↗

A Gaussian field approach to the solvation of spherical ions in electrolyte solutions

In this paper, the electrostatic response of an electrolyte solution to a spherical ion is studied with a Gaussian field theory. In order to capture the ionic correlation effect in concentrated solutions, the bulk dielectric response function is described by a two-Yukawa response function. The modified response function of the solution is solved analytically in the spherical geometry, from which the induced charge density and the electrostatic energy are also derived analytically. Comparisons with results for small ions in electrolyte solutions from the hyper-netted chain theory demonstrate the validity of the Gaussian field theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simplified spin dependence in dark matter direct detection

The interactions of dark matter with Standard Model particles can be systematically studied in the language of effective field theories. We investigate dark matter interactions with Standard Model particles, including spin-dependent interactions, for direct detection experiments and demonstrate that, although the scattering rate generally depends on multiple types of material response functions, certain linear combinations of these material response functions vanish if the initial and final electronic states share the same Hamiltonian. We also find that several other response functions vanish in parity-symmetric materials, making these systems as simple as isotropic detectors in some respects. Finally, we present the scattering rate for an anisotropic, possibly chiral detector, for generic dark matter-electron spin interactions. These relations reduce the number of independent response functions needed, thereby simplifying the computational complexity for a broad class of dark matter models. Our results provide a complete and efficient toolkit for analyzing electron recoil signals in diverse detector materials.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Machine-learning-based inversion of nuclear responses

A microscopic description of the interaction of atomic nuclei with external electroweak probes is required for elucidating aspects of short-range nuclear dynamics and for the correct interpretation of neutrino oscillation experiments. Nuclear quantum Monte Carlo methods infer the nuclear electroweak response functions from their Laplace transforms. Inverting the Laplace transform is a notoriously ill-posed problem; and Bayesian techniques, such as maximum entropy, are typically used to reconstruct the original response functions in the quasielastic region. In this work, we present a physics-informed artificial neural network architecture suitable for approximating the inverse of the Laplace transform. Utilizing simulated, albeit realistic, electromagnetic response functions, we show that this physics-informed artificial neural network outperforms maximum entropy in both the low-energy transfer and the quasielastic regions, thereby allowing for robust calculations of electron scattering and neutrino scattering on nuclei and inclusive muon capture rates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Gauge invariance and Ward identities in nonlinear response theory

We present a formal analysis of nonlinear response functions in terms of correlation functions in real- and imaginary-time domains. In particular, we show that causal nonlinear response functions, expressed in terms of nested commutators in real time, can be obtained from the analytic continuation of time-ordered response functions, which are more easily amenable to diagrammatic calculation. This generalizes the well-known result of linear response theory. We then use gauge invariance arguments to derive exact relations between second-order response functions in density and current channels. These identities, which are non-perturbative in the strength of inter-particle interactions, allow us to establish exact connections between nonlinear optics calculations done in different electromagnetic gauges.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Nuclear two point correlation functions on a quantum computer

The calculation of dynamic response functions is expected to be an early application benefiting from rapidly developing quantum hardware resources. The ability to calculate real-time quantities of strongly correlated quantum systems is one of the most exciting applications that can easily reach beyond the capabilities of traditional classical hardware. Response functions of fermionic systems at moderate momenta and energies corresponding roughly to the Fermi energy of the system are a potential early application because the relevant operators are nearly local, and the energies can be resolved in moderately short real time, reducing the spatial resolution and gate depth required. This is particularly the case in quasielastic electron and neutrino scattering from nuclei, a topic of great interest in the nuclear and particle physics communities and directly related to experiments designed to probe neutrino properties. In this paper we use current quantum hardware and error mitigation protocols to calculate response functions for a highly simplified nuclear model through calculations of a 2-point real time correlation function for a modified Fermi-Hubbard model in two dimensions with three distinguishable nucleons on four lattice sites.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Static and dynamic properties of atomic nuclei with high-resolution potentials

Here, we compute ground-state and dynamical properties of 4 He and 16 O nuclei using as input high-resolution, phenomenological nucleon-nucleon and three-nucleon forces that are local in coordinate space. The nuclear Schrodinger equation for both nuclei is accurately solved employing the auxiliary-field diffusion Monte Carlo approach. For the 4 He nucleus, detailed benchmarks are carried out with the hyperspherical harmonics method. In addition to presenting results for the binding energies and radii, we also analyze the momentum distributions of these nuclei and their Euclidean response function corresponding to the isoscalar density transition. The latter quantity is particularly relevant for lepton-nucleus scattering experiments, as it paves the way to quantum Monte Carlo calculations of electroweak response functions of 16 O.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Nuclear-level effective theory of 𝜇→𝑒 conversion: Formalism and applications

Over the next decade new 𝜇→𝑒 conversion searches at Fermilab (Mu2e) and J-PARC (COMET, DeeMe) are expected to advance limits on charged lepton flavor violation (CLFV) by more than four orders of magnitude. Here, by considering the consequence of 𝑃 and 𝐶⁢𝑃 on elastic 𝜇→𝑒 conversion and the structure of possible charge and current densities, we show that rates are governed by six nuclear responses and a single scale, 𝑞/𝑚 𝑁 , where 𝑞 ≈ 𝑚 𝜇 is the momentum transferred from the leptons to the nucleus. To relate this result to microscopic formulations of CLFV, we construct in nonrelativistic effective theory (NRET) the CLFV nucleon-level interaction, pointing out the relevance of the dimensionless scales 𝑦=($^{𝑞⁢𝑏}_2$) 2 ⁢ > |$\overrightarrow{𝑣}_N$⁢|>|$\overrightarrow{𝑣}_μ$⁢|>|$\overrightarrow{𝑣}_T$| , where 𝑏 is the nuclear size, $\overrightarrow{𝑣}_N$ and $\overrightarrow{𝑣}_μ$ are the nucleon and muon intrinsic velocities, and $\overrightarrow{𝑣}_T$ is the target recoil velocity. We discuss previous work, noting the lack of a systematic treatment of the various small parameters. Because the parameter 𝑦 is not small, a proper calculation of 𝜇→𝑒 conversion requires a full multipole expansion of the nuclear response functions, an apparently daunting task with Coulomb-distorted electron partial waves. We demonstrate that the multipole expansion can be carried out to high precision by introducing a simplifying local momentum 𝑞 eff for the electron. Previous work has been limited to simple charge or spin interactions, thereby treating the nucleus effectively as a point particle. We show that such formulations are not compatible with the general form of the 𝜇→𝑒 conversion rate, failing to generate three of the six allowed nuclear response functions. The inclusion of the nucleon velocity $\overrightarrow{𝑣}_N$ yields an NRET with 16 operators and a rate of the general form. Consequently, in the current discovery era for CLFV, it provides the most sensible starting point for experimental analysis, defining what can and cannot be determined about CLFV from the highly exclusive process of 𝜇→𝑒 conversion. Finally, we expand the NRET operator basis to account for the effects of $\overrightarrow{𝑣}_μ$, associated with the muon's lower component, generating corrections to the CLFV coefficients of the point-nucleus response functions. Using advanced shell-model methods, we compute 𝜇→𝑒 conversion rates for a series of experimental targets, deriving bounds on the coefficients of the CLFV operators. These calculations are the first to include a general basis of CLFV operators, full evaluation of the associated nuclear response functions, and an accurate treatment of electron and muon Coulomb effects. We discuss target selection as an experimental “knob” that can be turned to probe the microscopic origins of CLFV. We describe two types of coherence that enhance certain CLFV operators and selection rules that blind elastic 𝜇→𝑒 conversion to others. We discuss the matching of the NRET onto higher level effective field theories, such as those constructed at the light quark level, noting opportunities to build on existing work in direct detection of dark matter. We discuss the relation of 𝜇→𝑒 conversion to 𝜇→𝑒+𝛾 and 𝜇→3⁢𝑒, showing how MEG II and Mu3e results will complement those of Mu2e and COMET. Finally we describe a accompanying script—in Mathematica and Python versions—that can be used to compute 𝜇→𝑒 conversion rates in various nuclear targets for the full set of NRET operators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Modeling inclusive electron-nucleus scattering with Bayesian artificial neural networks

We introduce a Bayesian protocol based on artificial neural networks that is suitable for modeling inclusive electron-nucleus scattering on a variety of nuclear targets with quantified uncertainties. Unlike previous applications in the field, which directly parameterize the cross sections, our approach employs artificial neural networks to represent the longitudinal and transverse response functions. In contrast to cross sections, which depend on the incoming energy, scattering angle, and energy transfer, the response functions are determined solely by the energy and momentum transfer to the system, allowing the angular component to be treated analytically. We assess the accuracy and predictive power of our framework against the extensive data in the quasielastic inclusive electron-scattering database. Additionally, we present novel extractions of the longitudinal and transverse response functions and compare them with previous experimental analysis and nuclear ab-initio calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Transverse Enhancement, Longitudinal Quenching and Coulomb Sum Rule in e-$^{12}$C and e-$^{16}$O Scattering

We present a short summary of a phenomenological analysis of all available electron scattering data on 12 C 12 C (about 6600 differential cross section measurements) and on 16 O 16 O (about 250 measurements) within the framework of the quasielastic superscaling model (including Pauli blocking). All quasielastic and inelastic cross section measurements are included down to the lowest momentum transfer ? q (including photo-production data). We find that there is enhancement of the transverse quasielastic response function and quenching of the longitudinal response function at low ? q (in addition to Pauli blocking). We extract parameterizations of a ? ? ? ? ? ? ? ? ? ? ? ? ? ? multiplicative low ? q "Longitudinal Quenching Factor" and an ? ? ? ? ? ? ? ? additive "Transverse Enhancement" contribution. Additionally, we find that the excitation of nuclear states contribute significantly (up to 30\%) to the Coulomb Sum Rule. We extract the most accurate determination of the sum rule to date and find it to be in disagreement with random phase approximation based calculations but in reasonable agreement with recent theoretical calculations such as "First Principle Green's Function Monte Carlo".

Bodek, Arie↗

Low Peripheral Blood Counts and Elevated Proinflammatory Cytokines Signal a Poor CD19 Chimeric Antigen Receptor T-cell Response in Acute Lymphoblastic Leukemia

CD19 chimeric antigen receptor T-cell (CAR-T) therapy has significantly improved outcomes for patients with relapsed/refractory B-cell acute lymphoblastic leukemia (R/R B-ALL). However, approximately 20% of patients fail to achieve a complete remission (CR), and some develop severe, life-threatening toxicities. Understanding the biological mechanisms underlying both dysfunctional responses and severe toxicity is essential for optimizing patient management and improving therapeutic efficacy. This study aimed to (1) characterize cytokine profiles associated with dysfunctional responses and severe toxicity following CAR-T infusion, (2) examine the timing and trajectory of cytokine changes in relation to treatment outcomes, and evaluate potential strategies for mitigating toxicity and treatment failure. We conducted a comprehensive analysis of serum cytokine profiles in 86 adult and pediatric patients undergoing autologous CD19 CAR-T therapy for B-ALL. Patients were categorized into three groups: (1) Dysfunctional response—Patients who failed to achieve a minimal residual disease-negative CR (MRD-CR) by Day 63 or who experienced recurrence of CD19+ disease in the setting ongoing CAR-T cell detection before Day 63. (2) Functional response with severe cytokine release syndrome (CRS) and/or neurotoxicity (NTX)—Patients with best response of MRD-CR by Day 63 who experienced grade 3 or higher CRS or NTX. (3) Functional response without severe CRS or NTX—Patients with best response of MRD-CR by Day 63 who did not experience grade =3 CRS or NTX. Cytokine levels were measured during the first-week postinfusion and correlated with treatment efficacy, toxicity outcomes, complete blood counts, and CAR-T expansion dynamics. This analysis aimed to better understand how cytokine profiles relate to patient outcomes and immune responses in CAR-T therapy. Patients with dysfunctional response exhibited decreased neutrophils, platelets, and levels of granulocytic cytokines (suggestive of low bone marrow reserve) alongside elevated pro-inflammatory cytokines by Day 1. Functional response with severe toxicity patients showed a progressive rise in proinflammatory cytokines, reaching similar levels to dysfunctional response patients by Day 7. We observed that high cytokines at both the Day 1 and Day 7 time points were associated with poor survival. These findings remained significant when adjusting for high disease burden, a known predictor of severe inflammatory toxicity and lack of response. Early post-CAR-T infusion inflammation is associated with both dysfunctional response and severe toxicity—even after adjusting for disease burden. This suggests that inflammation, in addition to disease burden, plays a role in determining patient outcome. Therefore, strategies aimed at reducing the pro-inflammatory state prior to or early after CAR-T cell infusion may improve outcomes for R/R B-ALL patients.

Serum cytokines↗

Species interactions amplify functional group responses to elevated CO 2 and N enrichment in a 24‐year grassland experiment

Abstract Plant functional groups (FGs) differ in their response to global changes, although species within those groups also vary in such responses. Both species and FG responses to global change are likely influenced by species interactions such as inter‐specific competition and facilitation, which are prevalent in species mixtures but not monocultures. As most studies focus on responses of plants growing in either monocultures or mixtures, but rarely both, it remains unclear how interspecific interactions in diverse ecological communities, especially among species in different FGs, modify FG responses to global changes. To address these issues, we leveraged data from a 16‐species, 24‐year perennial grassland experiment to examine plant FG biomass responses to atmospheric CO 2 , and N inputs at different planted diversity. FGs differed in their responses to N and CO 2 treatments in monocultures. Such differences were amplified in mixtures, where N enrichment strongly increased C3 grass success at ambient CO 2 and C4 grass success at elevated CO 2 . Legumes declined with N enrichment in mixtures at both CO 2 levels and increased with elevated CO 2 in the initial years of the experiment. Our results suggest that previous studies that considered responses to global changes in monocultures may underestimate biomass changes in diverse communities where interspecific interactions can amplify responses. Such effects of interspecific interactions on responses of FGs to global change may impact community composition over time and consequently influence ecosystem functions.

Mohanbabu, Neha↗

Towards Realistic and High Fidelity Models for Nuclear Reactor Power Synthesis Simulation with Self-Powered Neutron Detectors

As presented in this report, a weighting function–based inferencing method is being applied to synthesize the power distribution in next-generation and university research reactors based on simulated self power neutron detector (SPND) responses. The overall goal is to assess the impacts of sensor uncertainty and true power distribution perturbations on the error in the synthesized power distribution. Regarding sensor uncertainty, the NuScale Small Modular Reactor (SMR) and the Westinghouse AP1000 serve as testbeds for analyzing the impact of varying the sensor uncertainty, as well as varying the number of sensors per sensor string in the reactor core. The reactor models are informed by Monte Carlo N-Particle (MCNP) neutron flux tallies. For the NuScale SMR and Westinghouse AP1000, the SPND response functions (i.e., the response of the SPNDs to individual segments of fuel) were determined homogeneously. Regarding an analysis of power distribution perturbation detection, the Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor was used as a demonstration case with one particular arrangement of SPNDs; the response functions for this reactor model were determined heterogeneously, making this a uniquely high-fidelity demonstration of perturbation detection. Finally, SPND models generated in the Geometry and Tracking 4 (Geant4) code have been generated and tested for comparison with traditionally implemented analytical SPND models, with the intent for Geant4 integration with the full methodological framework. SPND current outputs as a function of distance from some fuel assembly segment in the NuScale SMR are compared with the analytically determined currents. Results from the sensor uncertainty simulations for the NuScale SMR and AP1000 indicate that the average error in the inferred power distribution on the fuel assembly segment level is reasonably low, being slightly less than the random uncertainty applied to all respective SPNDs in both cores. For example, if all SPNDs in the core have a random uncertainty of 5%, then the corresponding fuel assembly segment level error (i.e. difference between the true and inferred local power) is ~2–3%. However, the maximum error in the inferred power distribution on the fuel assembly segment level can be considerably high (>15%) when SPND random uncertainties start to exceed ~3%. In general, the average and maximum errors in the inferred power distribution were slightly higher in the AP1000 as opposed to the NuScale SMR for the sensor string configurations considered herein. Another result determined from analysis of the sensor uncertainty simulations was that increasing the number of SPNDs per string does not clearly reduce inferred power distribution error and can in fact make the error large in some cases; however, this assessment may skewed due to imposed iteration limits. Results from the perturbation detection demonstration using the high-fidelity TAMU TRIGA model indicate that, given the arrangement of 17 SPND strings and 4 SPNDs per string considered herein, there is a clear, provable ability to infer a localized Gaussian-type peak perturbation in the 3D power distribution. Such a perturbation was detected with an average fuel assembly segment level error of 0.19%, and the general visualization of the detected perturbation clearly indicates that the magnitude and shape were appropriately resolved. Finally, the electrical current output generated by the Geant4 modeled SPND indicates significant magnitude differences than the analytically modeled SPND, demonstrating the need for accurate SPND models which account for finite sensor geometry effects to inform the power synthesis work described herein.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Fine-root functional trait responses to experimental warming: a global meta-analysis

Whether and how warming alters functional traits of absorptive plant roots remains to be answered across the globe. Tackling this question is crucial to better understanding terrestrial responses to climate change as fine-root traits drive many ecosystem processes. In this work, we carried out a detailed synthesis of fine-root trait responses to experimental warming by performing a meta-analysis of 964 paired observations from 177 publications. Warming increased fine-root biomass, production, respiration and nitrogen concentration as well as decreased root carbon : nitrogen ratio and nonstructural carbohydrates. Warming effects on fine-root biomass decreased with greater warming magnitude, especially in short-term experiments. Furthermore, the positive effect of warming on fine-root biomass was strongest in deeper soil horizons and in colder and drier regions. Total fine-root length, morphology, mortality, life span and turnover were unresponsive to warming. Our results highlight the significant changes in fine-root traits in response to warming as well as the importance of warming magnitude and duration in understanding fine-root responses. These changes have strong implications for global soil carbon stocks in a warmer world associated with increased root-derived carbon inputs into deeper soil horizons and increases in fine-root respiration.

59 BASIC BIOLOGICAL SCIENCES↗

Solving reaction dynamics with quantum computing algorithms

The description of quantum many-body dynamics is extremely challenging on classical computers, as it can involve many degrees of freedom. However, the time evolution of quantum states is a natural application for quantum computers that are designed to efficiently perform unitary transformations. Here, in this paper, we study quantum algorithms for response functions, relevant for describing different reactions governed by linear response. We focus on nuclear-physics applications and consider a qubit-efficient mapping on the lattice, which can efficiently represent the large volumes required for realistic scattering simulations. For the case of a contact interaction, we develop an algorithm for time evolution based on the Trotter approximation that scales logarithmically with the lattice size and is combined with quantum phase estimation. We eventually focus on the nuclear two-body system and a typical response function relevant for electron scattering as an example. We also investigate ground-state preparation and examine the total circuit depth required for a realistic calculation and the hardware noise level required to interpret the signal.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Uncertainty-quantification-enabled inversion of nuclear responses

Nuclear quantum many-body methods rely on integral transform techniques to infer properties of electroweak response functions from ground-state expectation values. Retrieving the energy dependence of these responses is highly nontrivial, especially for quantum Monte Carlo methods, as it requires inverting the Laplace transform, a notoriously ill-posed problem. Here, in this work, we propose an artificial neural network architecture suitable for accurate response function reconstruction with precise estimation of the uncertainty of the inversion. We demonstrate the capabilities of this new architecture benchmarking it against maximum entropy and previously developed neural network methods designed for a similar task, paying particular attention to its robustness noise in the Euclidean

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗