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At least 19 records

Ab initio calculation of atomic solid hydrogen phases based on Gutzwiller many-body wave functions

We apply two ab initio many-body methods based on Gutzwiller wave functions, i.e., correlation matrix renormalization theory (CMRT) and Gutzwiller conjugate gradient minimization (GCGM), to the study of crystalline phases of atomic hydrogen. Both methods avoid empirical Hubbard U parameters and are free from double-counting issues. CMRT employs a Gutzwiller-type approximation that enables efficient calculations, while GCGM goes beyond this approximation to achieve higher accuracy at higher computational cost. By benchmarking against available quantum Monte Carlo (QMC) results, we demonstrate that while both methods are more accurate than the widely used density-functional theory, GCGM systematically captures additional correlation energy missing in CMRT, leading to significantly improved total energy predictions. We also show that by including the correlation energy Ec from local density approximation in the CMRT calculation, CMRT + E c produces energy in better agreement with the QMC results in these hydrogen lattice systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Geophysical measurements of a demolition at NRF

On May 31 st , 2025, at approximately 14:40:00 UTC, the former Submarine First Westinghouse (SW1) structure housing a large crane was demolished at the Naval Reactors Facility (NRF) located within the perimeter of the Idaho National Laboratory (INL). Several targeted explosives were used to facilitate this demolition. The INL Seismic Monitoring Program (SMP) installed four temporary seismic instrument suites around the site of the demolition in order to monitor ground motion including measuring peak ground acceleration (PGA), peak ground velocity (PGV), and to calculate peak ground displacement (PGD). The demolition produced three types of waves: body waves, surface waves, and acoustic waves. The acoustic wave represents the largest signal received. The PGA, measured on the eastern component of the instrument located approximately 95m away from the demolition site, was 0.187g. The PGV measured was 0.0004 m/s, and the PGD was approximately 0.000006m. Rayleigh waves incident on an instrument located at the Advanced Test Reactor, about 7.6km away, were used to estimate a magnitude of 0.3 at the ATR, representing a yield of energy equivalent to approximately 3 grams of TNT.

58 - GEOSCIENCES

Performance of wave function and Green's function methods for non-equilibrium many-body dynamics

Theoretical descriptions of the non-equilibrium dynamics of quantum many-body systems essentially employ either (i) explicit treatments, relying on the truncation of the expansion of the many-body wave function, (ii) compressed representations of the many-body wave function, or (iii) evolution of an effective (downfolded) representation through Green's functions. In this work, we select representative cases of each of the methods and address how these complementary approaches capture the dynamics driven by intense field perturbations to non-equilibrium states. Under strong driving, the systems are characterized by strong entanglement of the single-particle density matrix and natural populations approaching those of a strongly interacting equilibrium system. We generate a representative set of results that are numerically exact and form a basis for a critical comparison of the distinct families of methods. We demonstrate that the compressed formulation based on similarity-transformed Hamiltonians (coupled-cluster approach) is practically exact in weak fields and, hence, weakly or moderately correlated systems. Coupled cluster, however, struggles for strong driving fields, under which the system exhibits strongly correlated behavior, as measured by the von Neumann entropy of the single-particle density matrix. The dynamics predicted by Green's functions in the (widely popular) G W approximation are less accurate, but improve significantly upon the mean-field results in the strongly driven regime. Published by the American Physical Society 2025

Reeves, Cian C. (ORCID:0009000642581845)

Symmetrizing relativistic three-body partial wave amplitudes

S matrix principles and symmetries impose constraints on three-particle scattering amplitudes, which can be formulated as a class of integral equations for their partial wave projections. However, these amplitudes are typically expressed in an asymmetric basis, where one of the initial and final state particles is singled out, and all quantum numbers are defined relative to this spectator. In this work, we show how to construct symmetric partial wave amplitudes, which have been symmetrized over all possible spectator combinations, using their asymmetric counterparts and sets of recoupling coefficients. We derive these recoupling coefficients for arbitrary angular momentum and isospin for arbitrary systems of spinless particles with SU(2) flavor symmetry. We propose a simple intensity observable suitable for visualizing the structure of three-body dynamics in Dalitz distributions. Finally, we provide some numerical examples of Dalitz distributions relevant for future lattice QCD calculations of 3⁢𝜋 systems and provide numerical evidence that the symmetrization procedure is consistent with expected symmetries of Dalitz plots.

Lattice QCD

Five-point functions and the permutation group 𝑆 5

Five-point functions and five-body wave functions play an important role in many areas of nuclear and particle physics, e.g., in 2 →3 scattering processes, in the five-gluon vertex, or in the study of pentaquarks. In this work we consider the permutation group 𝑆 5 to facilitate the description of such objects. We work out the multiplets transforming under irreducible representations of 𝑆 5 and provide compact formulas allowing one to cast the permutations of an object 𝑓 12345 into combinations with definite permutation symmetry. We also give the explicit expressions for the irreducible multiplet products. We consider several practical applications as examples: We arrange the four-momenta and Lorentz invariants of a five-point function into the multiplet structure, we work out the color tensors of the five-gluon vertex in the multiplet notation, and we discuss applications for five-body wave functions like those of pentaquarks.

Bethe-Salpeter equation

Bayesian Inference for the Seismic Moment Tensor Using Regional Waveforms and Teleseismic- P Polarities with a Data-Derived Distribution of Velocity Models and Source Locations

The largest source of uncertainty in any source inversion is the velocity model used in the transfer function that relates observed ground motion to the seismic moment tensor. However, standard inverse procedure often does not quantify uncertainty in the seismic moment tensor due to error in the Green’s functions from uncertain event location and Earth structure. Here, we incorporate this uncertainty into an estimation of the seismic moment tensor using a data-derived distribution of velocity models based on complementary geophysical data sets, including thickness constraints, velocity profiles, gravity data, surface-wave group velocities, and regional body-wave travel times. The data-derived distribution of velocity models is then used as a prior distribution of Green’s functions for use in Bayesian inference of an unknown seismic moment tensor using regional and teleseismic-P waveforms. The use of multiple data sets is important for gaining resolution to different components of the moment tensor. The combined likelihood is estimated using data-specific error models and the posterior of the seismic moment tensor is estimated and interpreted in terms of the most probable source type.

58 GEOSCIENCES

A Pn magnitude scale m b ( Pn ) for earthquakes along the equatorial Mid-Atlantic Ridge

We developed a short-period Pn magnitude scale m b (Pn) for earthquakes along the equatorial Mid-Atlantic Ridge. Due to low signal-to-noise ratios, teleseismic body wave magnitude and long-period surface wave magnitude cannot be confidently determined for small earthquakes of m b < 4. Local magnitude scales are also not useful for these events because the oceanic environment does not allow the propagation of crustal phases. However, regional high-frequency Pn waves from these small- to moderate-size (m b 3–6) earthquakes are well recorded in the equatorial Atlantic region and can be used to assign magnitudes. We measured over 2041 Pn peak amplitudes on vertical records from about 21 stations in northeastern Brazil and 11 stations in western Africa in the distance range of 700–3700 km. We analysed data from 189 events from the global centroid moment tensor catalogue to tie our m b (Pn) scale to M w so that seismic moments can be readily estimated. Pn arrivals show apparent group velocity between 7.9 km s –1 at short ranges (~1000 km) and up to 9.1 km s –1 at 3500 km. The measured peak amplitudes have a frequency between 0.8 and 3 Hz at 1000–1800 km, but at greater distances, 1800–3700 km, they show a remarkably consistent frequency of about 0.8 Hz. The peak amplitude attenuates at a higher rate at short distances (~0.65 magnitude units between 700 and 2000 km) but attenuates at a lower rate at long distances (~0.35 magnitude units between 2000 and 3700 km). The low rate of amplitude decay with distance and nearly constant frequency content of the peak amplitudes suggest that Pn waves propagate efficiently in the lower part of the upper mantle in the equatorial Atlantic Ocean basins. Furthermore, these are important attributes of oceanic Pn waves that can be used to assign magnitude for small- to moderate-size earthquakes in the equatorial mid-Atlantic region. The estimated station corrections correlate well with upper mantle low-velocity anomalies, especially in Brazil.

58 GEOSCIENCES

Observable measurement-induced transitions

One of the main postulates of quantum mechanics is that measurements destroy quantum coherence (wave function collapse). Recently it was discovered that in a many-body system dilute local measurements still preserve some coherence across the entire system. As the measurement density is increased, a phase transition occurs that is characterized by the disentanglement of different parts of the system. Unfortunately, this transition is impossible to observe experimentally for macroscopic systems because it requires an exponentially costly full tomography of the many-body wave function or a comparison with the simulation on an oracle classical computer. In this work we report the discovery of another measurement-induced phase transition that can be observed experimentally if quantum dynamics can be reversed. On one side of this phase transition the quantum information encoded in some part of the Hilbert space is fully recovered after the time inversion. On the other side, all quantum information is corrupted. This transition also manifests itself as the change in the behavior of the probability to observe the same measurement outcome in the process that consists of identical blocks repeated many times. In each block the unitary evolution is followed by the measurement. On one side of the transition the probability decreases exponentially with the number of repetitions, on the other it tends to a constant as the number of repetitions is increased. We confirm the existence of the proposed phase transition through numerical simulations of realistic quantum circuits and analytical calculations using an effective random-matrix theory model.

Measurement-induced phase transitions

Downfolding from ab initio to interacting model Hamiltonians: comprehensive analysis and benchmarking of the DFT+cRPA approach

Abstract Model Hamiltonians are regularly derived from first principles to describe correlated matter. However, the standard methods for this contain a number of largely unexplored approximations. For a strongly correlated impurity model system, here we carefully compare a standard downfolding technique with the best possible ground-truth estimates for charge-neutral excited-state energies and wave functions using state-of-the-art first-principles many-body wave function approaches. To this end, we use the vanadocene molecule and analyze all downfolding aspects, including the Hamiltonian form, target basis, double-counting correction, and Coulomb interaction screening models. We find that the choice of target-space basis functions emerges as a key factor for the quality of the downfolded results, while orbital-dependent double-counting corrections diminish the quality. Background screening of the Coulomb interaction matrix elements primarily affects crystal-field excitations. Our benchmark uncovers the relative importance of each downfolding step and offers insights into the potential accuracy of minimal downfolded model Hamiltonians.

Chemistry

Powering the Woods Hole X-Spar Buoy with Ocean Wave Energy—A Control Co-Design Feasibility Study

Despite its success in measuring air–sea exchange, the Woods Hole Oceanographic Institution’s (WHOI) X-Spar Buoy faces operational limitations due to energy constraints, motivating the integration of an energy harvesting apparatus to improve its deployment duration and capabilities. This work explores the feasibility of an augmented, self-powered system in two parts. Part 1 presents the collaborative design between X-Spar developers and wave energy researchers translating user needs into specific functional requirements. Based on requirements like desired power levels, deployability, survivability, and minimal interference with environmental data collection, unsuitable concepts are pre-eliminated from further feasibility study consideration. In part 2, we focus on one of the promising concepts: an internal rigid body wave energy converter. We apply control co-design methods to consider commercial of the shelf hardware components in the dynamic models and investigate the concept’s power conversion capabilities using linear 2-port wave-to-wire models with concurrently optimized control algorithms that are distinct for every considered hardware configuration. During this feasibility study we utilize two different control algorithms, the numerically optimal (but acausal) benchmark and the optimized damping feedback. We assess the sensitivity of average power to variations in drive-train friction, a parameter with high uncertainty, and analyze stroke limitations to ensure operational constraints are met. Our results indicate that a well-designed power take-off (PTO) system could significantly extend the WEC-Spar’s mission by providing additional electrical power without compromising data quality.

autonomous systems

Rotational Millimeter-Wave Shoe Scanner Using the Discrete Fourier Transform for Backprojection-Based Image Reconstruction

An active 3D microwave / millimeter-wave shoe scanner was previously developed at the Pacific Northwest National Laboratory (PNNL) using two linear arrays scanned over a rectilinear aperture. The radar system chirps a frequency sweep from 10-40 GHz. These frequencies allow imaging through optically opaque material such as leather, rubber, plastics, and other dielectrics. The system was designed to detect concealed items in the soles of shoes while allowing people to leave their shoes on through a security checkpoint. To shrink the footprint of the system, a new iteration of the design has been developed that scans the two linear arrays over a circular aperture. This new footprint opens the possibility of it being installed in the floor of a cylindrical millimeter-wave body scanner. The backprojection-based multilayer dielectric image reconstruction developed at PNNL can easily handle arbitrary spatial sampling, accommodating the new rotational shoe scanner design. Commonly, the fast Fourier transform (FFT) is used to efficiently compute the range response from the data collected by the system as a preprocessing step to the backprojection algorithm. It was found that converting to range using the discrete Fourier transform (DFT) directly has some advantages over the FFT. For example, nonlinear and non-uniform frequency sweeps can easily be compensated for during the computation of the DFT and only the range bins of interest need to be computed and their spacing can be chosen arbitrarily. Because the range conversion step of the image reconstruction is the fastest part of the process there is very little speed penalty for using the DFT over the FFT and it can even increase the speed of image reconstruction when the ranges of interest are fewer than the total span that is calculated in the FFT.

Millimeter-wave imaging, microwave imaging, shoe s

MTUQ: a framework for estimating moment tensors, point forces, and their uncertainties

SUMMARY We introduce MTUQ, an open-source Python package for seismic source estimation and uncertainty quantification, emphasizing flexibility and operational scalability. MTUQ provides MPI-parallelized grid search and global optimization capabilities, compatibility with 1-D and 3-D Green’s function database formats, customizable data processing, C-accelerated waveform and first-motion polarity misfit functions, and utilities for plotting seismic waveforms and visualizing misfit and likelihood surfaces. Applicability to a range of full- and constrained-moment tensor, point force, and centroid inversion problems is possible via a documented application programming interface, accompanied by example scripts and integration tests. We demonstrate the software using three different types of seismic events: (1) a 2009 intraslab earthquake near Anchorage, Alaska; (2) an episode of the 2021 Barry Arm landslide in Alaska; and (3) the 2017 Democratic People’s Republic of Korea underground nuclear test. With these events, we illustrate the well-known complementary character of body waves, surface waves, and polarities for constraining source parameters. We also convey the distinct misfit patterns that arise from each individual data type, the importance of uncertainty quantification for detecting multimodal or otherwise poorly constrained solutions, and the software’s flexible, modular design.

58 GEOSCIENCES

Majorana Edge Modes in Isolated Wires

Topological superconductors are believed to host exotic quasiparticle excitations known as Majorana zero modes (MZMs), with much of the evidence based on BCS mean-field theory. The direct application of mean-field arguments is tenuous in finite, isolated systems relevant in some experiments. Here, we develop a new correlation-based method for identifying MZMs in interacting, number-conserving systems. Using the density matrix renormalization group, we study fermion number-conserving models with long-range interactions, which under periodic boundary conditions exhibit robust topological and nontopological superconductivity, tuned by the strength of interaction [Ortiz et al., Phys. Rev. Lett. 113, 267002 (2014)]. We find evidence that, on the topological side, Majorana edge modes appear in open chains, manifesting as the vanishing of the energy splitting between odd- and even-parity ground states with increasing system size. Additionally, off-diagonal two-point correlation functions show nonlocal, parity-dependent edge effects. These correlations reveal the spatial structure of Majorana modes in the many-body wave function. We show that the correlation diagnostic applies broadly, including to short-range interacting models, where topological superconductivity is more fragile due to the absence of a bulk excitation gap.

Thomas-Markarian, Jaden

Quantum Criticality Under Imperfect Teleportation

Entanglement, measurement, and classical communication together enable teleportation of quantum states between distant parties, in principle, with perfect fidelity. To what extent do correlations and entanglement of a many-body wave function transfer under teleportation protocols? We address this question for the case of an imperfectly teleported quantum critical wave function, focusing on the ground state of a critical Ising chain. We demonstrate that imperfections, e.g., in the entangling gate adopted for a given protocol, effectively manifest as weak measurements acting on the otherwise pristinely teleported critical state. Armed with this perspective, we leverage and further develop the theory of measurement-altered quantum criticality to quantify the resilience of critical-state teleportation. We identify classes of teleportation protocols for which imperfection (i) preserves both the universal long-range entanglement and correlations of the original quantum critical state, (ii) weakly modifies these quantities away from their universal values, and (iii) obliterates long-range entanglement altogether while preserving power-law correlations, albeit with a new set of exponents. We also show that mixed states describing the average over a series of sequential imperfect teleportation events retain pristine power-law correlations due to a “built-in” decoding algorithm, though their entanglement structure measured by the negativity depends on errors similarly to individual protocol runs. These results may allow one to design teleportation protocols that optimize against errors—highlighting a potential practical application of measurement-altered criticality. Published by the American Physical Society 2024

Physics

UMass 2-Body WEC Techno-Economic Assessment

The University of Massachusetts (UMass) is developing a 2-body wave energy converter (WEC) device that is converting mechanical power into electricity using a mechanical motion rectifier that allows the system to couple to a flywheel. UMass has completed numerical modeling, wave tank testing, and PTO sub-system testing and needed assistance in developing a techno-economic model to enable optimization of their topology, comparison to a generic heaving point absorber topology, and guide the next steps in their development efforts. The core objective was to develop a techno-economic approach and modeling tool that allows benchmarking of the two topologies across a wide range of scales to evaluate their respective competitiveness in different application spaces. This data includes the final report as well as a supporting spreadsheet containing the data produced for this report.

16 TIDAL AND WAVE POWER

Neural-network quantum states for the nuclear many-body problem

A long-standing goal of nuclear theory is to explain how the structure and dynamics of atomic nuclei and neutron-star matter emerge from the underlying interactions among protons and neutrons. Achieving this goal requires solving the nuclear quantum many-body problem with high accuracy across a wide range of length scales and density regimes. In this review, we discuss how artificial neural network representations of the nuclear many-body wave function have significantly extended the capabilities of continuum quantum Monte Carlo methods. In particular, neural network quantum states enable calculations of larger systems than were previously accessible and provide a flexible framework for capturing phenomena that challenge conventional approaches, including the emergence of nuclear clusters and superfluid phases in dense matter. We highlight recent applications to finite nuclei, infinite nuclear and neutron matter, and dynamical processes relevant to lepton-nucleus and nucleus-nucleus scattering. We also discuss conceptual and methodological connections with condensed matter physics, emphasizing developments in neural network quantum states that bridge strongly correlated systems across disciplines. Together, these developments demonstrate how neural-network methods open new avenues toward unified and accurate descriptions of nuclear structure, matter, and reactions.

Lovato, Alessandro [Argonne; TIFPA-INFN, Trento; V

RidgeAlloy: A high pressure die casting alloy that captures the approaching wave of automotive body sheet scrap

Oak Ridge National Laboratory (ORNL) has recently launched an effort to economically expand the North American aluminum supply chain by designing and developing a new family of Al-Mg-Si-Fe-Mn structural die cast aluminum alloys that can be made from up to 100% mixed 5xxx and 6xxx series automotive post-consumer sheet scrap and do not require heat treatment. The goal is to develop an alloy capable of capturing the approaching scrap wave of aluminum sheet intensive vehicles (in the 2030’s) into integrated structural high pressure die castings, rather than down-cycling these high-grade sheet alloys into non-structural castings. ORNL discovered a significant gap in the commercial thermodynamic databases that were unable to predict the trends of a key primary intermetallic phase as a function of composition. Experiments were performed to correct this gap and to create a unique, corrected quaternary database for Al-Mg-Si-Fe. High throughput computational methods, including solidification simulations, were used to identify a composition volume capable of avoiding this embrittling primary intermetallic phase, even at higher Fe + Si contents. Laboratory scale castings validated the thermodynamic and solidification predictions and resulted in lab-cast alloys with little primary intermetallic, and which met or exceeded structural casting properties requirements for yield strength and ductility. An accelerated demonstration of an HPDC automotive part was conducted in collaboration with two U.S. small businesses. Ingots made from 100% recycled 5xxx and 6xxx series scrap (plus Fe) were used to die cast one variant of this new family of Al-Mg-Si-Fe-Mn alloys (with high Si + Fe content) into a mid-sized HPDC structural-type automotive component. The HPDC alloy demonstration part showed good properties (especially ductility) and good castability for a complex component.

Plotkowski, Alex [ORNL] (ORCID:0000000154718681)

Evaluating Physics-Informed Neural Network Performance for Seismic Discrimination between Earthquakes and Explosions

In this article, we evaluate adding a weak physics constraint, that is, a physics‐based empirical relationship, to the loss function with a physics‐informed manner in local distance explosion discrimination in the hope of improving the generalization capability of the machine learning (ML) model. We compare the proposed model with the two‐branch model we previously developed, as well as with a pure data‐driven model. Unexpectedly, the proposed model did not consistently outperform the pure data‐driven model. By varying the level of inconsistency in the training data, we find this approach is modulated by the strength of the physics relationship. In conclusion, this result has important implications for how to best incorporate physical constraints in ML models.

58 GEOSCIENCES