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Ne 21 energy levels approaching the α -particle threshold
Nuclei around Ne 20 exhibit an interplay of different excitations caused by different aspects of nuclear structure, including single-particle and multiparticle configurations and collective rotations. One-nucleon transfer reactions selectively probe single-particle structures in these nuclei. These nuclei are also important to astrophysics, with a number of important reactions proceeding through this mass region. Energy levels approaching the α -particle threshold in Ne 21 are of importance to nuclear structure. The Ne 20 ( d , p ) Ne 21 reaction was measured and the corresponding spectroscopic nuclear information was extracted. States in Ne 21 were populated using the Ne 20 ( d , p ) Ne 21 reaction in forward kinematics. Protons were identified in the Triangle Universities Nuclear Laboratory (TUNL) Enge split-pole spectrograph and angular distributions were extracted. Spin-party assignments were made and neutron partial widths were determined based on distorted-wave Born approximation (DWBA) analysis. Several new energy levels were observed at energies of 7176, 7235, 7250, and 7337 keV, and spin-parities are reported which generally agree with previous results where literature was available. Spin and parity assignments are reported for several energy levels along with estimated neutron widths for those states above the neutron threshold ( S n = 6761 keV ). Results from this study are placed in context with a review of the available literature on all known states in this energy region of Ne 21 . Published by the American Physical Society 2024
Non-Intrusive Appliance Identification with Appliance-Specific Networks
The problem of noninstrusive load monitoring (NILM) is usually formulated as a single-channel blind source separation task, whose successful solution enable fast and convenient load identification and energy disaggregation. When applied at test time, NILM algorithms aim to identify the operating characteristics of individual appliances from an aggregate power measurement of the entire house. Recent advances in deep learning gave rise to many methods that mostly focus on learning a direct mapping from aggregate measurement to individual appliance power. However, these methods are not only computationally expensive, but they often suffer from overfitting and do not generalize very well. In this article, we propose a novel NILM method that leverages advances in statistical learning that have not been properly applied in this domain before. The proposed method consists of three stages: first, a Bayesian nonparametric learning-based approach for appliance state extraction; second, synthetic minority oversampling technique for data augmentation and mitigating the heavy imbalance in switching events; and third, appliance-specific lightweight long short-term memory networks for status classification for each appliance. Here, we adopt a “differential” input (the difference before and after the switching event) to reduce the complexity of network training and make the proposed method robust to multiappliance switching events. Experiments are conducted to demonstrate the effectiveness of the proposed method, achieving superior performance when compared to recent methods. An ablation study is conducted to demonstrate the effectiveness of each module of our method. Finally, we investigate the quality of generated synthetic samples.
Time-resolved atomic-resolution Brownian tomography of single nanocrystals reveals size-dependent dynamics
Atomic-resolution structure identification of nanocrystals by graphene liquid cell electron microscopy (GLC-EM) has revealed that small, solubilized platinum nanocrystals consist of an ordered crystalline core surrounded by mobile surface atoms, which dissociate during oxidative etching, resulting in distinct temporal structural states. Requirements imposed by the 3D reconstruction algorithm limit the number of structural states that can be resolved. We introduce a regularized 3D reconstruction algorithm that exploits the redundancy inherent in the experimental data, allowing us to improve the time resolution. Our developments provide a comprehensive molecular picture at unprecedented spatial and temporal resolution of the nonlinear, linear, and fluctuating dynamic phenomena that single nanocrystals undergo during the GLC-EM experiment. We determined atomic structures of 66 temporal structural states, extracted from 15 time trajectories of individual nanocrystals. Large (478 to 698 atoms) and small (<300 atoms) nanocrystals show etching that preserves a stable core, whereas mid-sized (351 to 571 atoms) nanocrystals present dynamics that change the coordination of the core.
Complete Initial Evaluation of Novel Complexants for Tc Holdback for Simplified Single Cycle Separations.
Management of technetium at the back end of nuclear fuel cycle is complicated by its unique physico-chemical character, but must be addressed to due to the environmental, storage and reprocessing challenges of this fission product. In a single-cycle scenario, the recovery and purification of uranium is particularly challenging due to the tendency of a pertechnetate anion to follow uranyl cation. This report summarizes initial studies directed towards finding the solution for technetium management. Two options for controlling technetium’s chemistry in solvent extraction scenarios were studied. Molecular recognition of pertechnetate by aqueous complexants based on guanidinium moieties was compared to redox manipulation of technetium using dihydrazide reagents. Solvent extraction, potentiometric and nuclear magnetic resonance spectroscopy studies were performed. The influence of guanidinium reagents on the liquid-liquid partitioning of technetium is less pronounced, relative to dihydrazides. Strong impact exerted by dihydrazides originates from the technetium-catalyzed decomposition of such compounds which reduces technetium to a tetravalent, non-extractable state. Although this route of technetium management is very effective the destruction of dihydrazides is undesirable. Guanidinium complexants show a more tempered influence on technetium. The effect on the liquid-liquid partitioning of pertechnetate is evident and likely guided by anion recognition due to ion-pair and hydrogen bond formation. Guanidiniums are stable in presence of technetium as evidenced by nuclear magnetic resonance studies. The steady state chemistry of guanidiniums identify this class of aqueous complexants as solid candidates for structure-function pertechnetate recognition studies.
Extracting doubly excited state lifetimes in helium directly in the time domain with attosecond noncollinear four-wave-mixing spectroscopy
The helium atom, with one nucleus and two electrons, is a prototypical system to study quantum many-body dynamics. Doubly excited states, or quantum states in which both electrons are excited by one photon, showcase electronic-correlation mediated effects. In this paper, the natural lifetimes of the doubly excited 1 P o 2 s n p Rydberg series and the 1 S e 2 p 2 dark state in helium in the 60–65 eV region are measured directly in the time domain with extreme-ultraviolet/near-infrared noncollinear attosecond four-wave-mixing (FWM) spectroscopy. The measured lifetimes agree with lifetimes deduced from spectral linewidths and theoretical predictions, and the roles of specific decay mechanisms are considered. While complex spectral line shapes in the form of Fano resonances are common in absorption spectroscopy of autoionizing states, the background-free and thus homodyned character of noncollinear FWM results exclusively in Lorentzian spectral features in the absence of strong-field effects. The onset of strong-field effects that would affect the extraction of accurate natural lifetimes in helium by FWM is determined to be approximately 0.3 Rabi cycles. This study provides a systematic understanding of the FWM parameters necessary to enable accurate lifetime extractions, which can be utilized in more complex quantum systems in the future. Published by the American Physical Society 2024
Addressing quantum’s “fine print” with efficient state preparation and information extraction for quantum algorithms and geologic fracture networks
Abstract Quantum algorithms provide an exponential speedup for solving certain classes of linear systems, including those that model geologic fracture flow. However, this revolutionary gain in efficiency does not come without difficulty. Quantum algorithms require that problems satisfy not only algorithm-specific constraints, but also application-specific ones. Otherwise, the quantum advantage carefully attained through algorithmic ingenuity can be entirely negated. Previous work addressing quantum algorithms for geologic fracture flow has illustrated core algorithmic approaches while incrementally removing assumptions. This work addresses two further requirements for solving geologic fracture flow systems with quantum algorithms: efficient system state preparation and efficient information extraction. Our approach to addressing each is consistent with an overall exponential speed-up.
Variational quantum state eigensolver
Extracting eigenvalues and eigenvectors of exponentially large matrices will be an important application of near-term quantum computers. The variational quantum eigensolver (VQE) treats the case when the matrix is a Hamiltonian. Here, we address the case when the matrix is a density matrix ρ. We introduce the variational quantum state eigensolver (VQSE), which is analogous to VQE in that it variationally learns the largest eigenvalues of ρ as well as a gate sequence V that prepares the corresponding eigenvectors. VQSE exploits the connection between diagonalization and majorization to define a cost function C=Tr(ρ~H) where H is a non-degenerate Hamiltonian. Due to Schur-concavity, C is minimized when ρ~=VρV† is diagonal in the eigenbasis of H. VQSE only requires a single copy of ρ (only n qubits) per iteration of the VQSE algorithm, making it amenable for near-term implementation. We heuristically demonstrate two applications of VQSE: (1) Principal component analysis, and (2) Error mitigation.
Automated label flows for excited states of correlation functions in lattice gauge theory
Extracting excited states from lattice gauge theory correlation functions can be achieved through $χ^2$ minimization fits or algebraic approaches such as the variational method and Prony's method. Performing any kind of error analysis often leads to overlapping confidence regions of model parameters, even when the spectrum is not particularly dense. To correctly estimate errors, one must beware of mislabeling the states. In this work, we provide an algorithm that we call automated label flows which consistently and systematically identifies a deterministic labeling of states. This is a black-box approach in the sense that it gives a sensible set of labels without user guidance. Further, as an example, we pair one black box method with another, analyzing a lattice correlation function from real data using automated label flows in the context of Prony's method.
Extraction of ground-state nuclear deformations from ultrarelativistic heavy-ion collisions: Nuclear structure physics context
The collective-flow-assisted nuclear shape-imaging method in ultrarelativistic heavy-ion collisions (UHICs) has recently been used to characterize nuclear collective states. In this paper, we assess the foundations of the shape-imaging technique employed in these studies. We argue that some current UHIC nuclear imaging techniques neglect fundamental aspects of spontaneous symmetry breaking and symmetry restoration in colliding ions and incorrectly infer one-body multipole moments from studies of nucleonic correlations. Therefore, the impact of this approach on nuclear structure research has been overstated. Conversely, efforts to incorporate existing knowledge on nuclear shapes into analysis pipelines can be beneficial for benchmarking tools and calibrating models used to extract information from ultrarelativistic heavy-ion experiments.
The proton charge radius extracted from the initial-state radiation experiment at MAMI
Abstract We report on a comprehensive reinterpretation of the existing cross-section data for elastic electron-proton scattering obtained by the initial-state radiation technique, resulting in a significantly improved accuracy of the extracted proton charge radius. By refining the external energy corrections we have achieved an outstanding description of the radiative tail, essential for a detailed investigation of the proton finite-size effects on the measured cross sections. This development, together with a novel framework for determining the radius, based on a regression analysis of the cross sections employing a polynomial model for the form factor, led us to a new value for the charge radius, which is $$(0.878 \pm 0.011_\mathrm {stat.}\pm 0.031_\mathrm {sys.}\pm 0.002_\mathrm {mod.})\,\mathrm {fm}$$ ( 0.878 ± 0 . 011 stat . ± 0 . 031 sys . ± 0 . 002 mod . ) fm
The 1 S 0 Pairing Gap in Neutron Matter
We report ab initio calculations of the S wave pairing gap in neutron matter calculated using realistic nuclear Hamiltonians that include two- and three-body interactions. We use a trial state, properly optimized to capture the essential pairing correlations, from which we extract ground state properties by means of auxiliary field diffusion Monte Carlo simulations. We extrapolate our results to the thermodynamic limit by studying the finite-size effects in the symmetry-restored projected Bardeen-Cooper-Schrieffer (PBCS) theory and compare our results to other ab initio studies done in the past. Our quantum Monte Carlo results for the pairing gap show a modest suppression with respect to the mean-field BCS values. These results can be connected to cold atom experiments, via the unitarity regime where fermionic superfluidity assumes a unified description, and they are important in the prediction of thermal properties and the cooling of neutron stars.
Anomalous Hall crystals in rhombohedral multilayer graphene. II. General mechanism and a minimal model
Here we propose a minimal "three-patch model"for the anomalous Hall crystal (AHC), a topological electronic state that spontaneously breaks both time-reversal symmetry and continuous translation symmetry. The proposal for this state is inspired by the recently observed integer and fractional quantum Hall states in rhombohedral multilayer graphene at zero magnetic field. There, interaction effects appear to amplify the effects of a weak moiré potential, leading to the formation of stable, isolated Chern bands. It has been further shown that Chern bands are stabilized in mean-field calculations even without a moiré potential, enabling a realization of the AHC state. Our model is built on the dissection of the Brillouin zone into patches centered around high-symmetry points. Within this model, the wave functions at high-symmetry points fully determine the topology and energetics of the state. We extract two quantum geometrical phases of the noninteracting wave functions that control the stability of the topologically nontrivial AHC state. The model predicts that the AHC state wins over the topological trivial Wigner crystal in a wide range of parameters, and agrees very well with the results of full self-consistent Hartree-Fock calculations of the rhombohedral multilayer graphene Hamiltonian.
Some entanglement survives most measurements
To prepare quantum states and extract information, it is often assumed that one can perform a perfectly projective measurement. Such measurements can achieve an uncorrelated system and environment state. However, perfectly projective measurements can be difficult or impossible to perform in practice. Here, we investigate the limitations of repeated nonprojective measurements in preparing a quantum system. For an n-qubit system initially entangled with its environment and subsequently prepared with measurements, using a sequence of weak measurements, we show that some entanglement remains unless one of the measurement operators becomes perfectly projective through an extreme limiting process. Removing initial (unentangled) correlations between a system and its environment and the scenario where measurement outcomes are not tracked are also discussed. We present results for n-qubit and n-dimensional input states.
Life cycle greenhouse gas emissions of ethanol produced via fermentation of sugars derived from shrub willow (Salix ssp.) hot water extraction in the Northeast United States
Abstract Background The amount of carbon dioxide in the atmosphere has been on the rise for more than a century. Bioenergy crops are seen by the Intergovernmental Panel on Climate Change as an essential part of the solution to addressing climate change. To understand the potential impact of shrub willow ( Salix spp . ) crop in the northeast United States, effective and transparent life cycle assessment of these systems needs to occur. Results Here we show, ethanol produced from the fermentation of sugars from hot water extract of willow grown on cropland can sequester 0.012 ± 0.003 kg CO 2eq MJ −1 for a supply system incorporating summer harvest and storage. Despite decreases in soil organic carbon when willow is instead grown on grassland, the produced fuel still can provide significant climate benefits compared to gasoline. Conclusions Shrub willow converted to ethanol can be a carbon negative source of transportation fuel when the electricity and heat required for the conversion process are generated from renewable biomass. The sequestration of carbon in the belowground portion of the plants is essential for the negative GHG balance for cropland and low GHG emissions in grassland.
Plasma confinement state classification in fusion power plants: Profile reflectometer and ensemble diagnostics
As Fusion Pilot Plants (FPPs) are increasingly viewed as within reach, many engineering challenges remain. Not many diagnostics are expected to be available in a reactor environment. Survivability, maintainability, and limited port space substantially restrict the number of FPP-relevant diagnostics. One remaining challenge is developing tools and devices to extract plasma state information necessary for controlling an FPP from a limited subset of diagnostics. This work is part of an overarching project to address this challenge. The specific diagnostic subset to be used in FPPs is still under debate. We take the approach of developing machine-learning-based tools for different significant plasma state parameters, using already known FPP-viable diagnostics. Previously we developed a plasma confinement mode classifier utilizing the Electron Cyclotron Emission (ECE) diagnostic. Here, we expand on this by developing a Profile Reflectometer (PR) based classifier with 97% test accuracy, and an ensemble model that combines the ECE and PR models into a single model, achieving 99% test accuracy.
How to falsify string theory at a collider
The string landscape accommodates a broad range of possible effective field theories. This poses a challenge for extracting verifiable predictions as well as falsifiable signatures of string theory. Motivated by these considerations, in this work we observe that all known stringy standard models support only low-dimensional representations of the gauge group. While it is in principle possible to produce contrived models with higher-dimensional representations, these generically appear in a tower of states with lighter ones in lower-dimensional representations, i.e., not in isolation. With this in mind, we consider the phenomenologically well-motivated scenario given by adding a single Majorana field in a real, 𝑛-dimensional representation of 𝑆𝑈(2) 𝐿 with 𝑛≥5 and nothing else . This scenario is not realized in any known string construction, and we conjecture that this is true of string theory in general. Detection of this scenario would thus amount to falsifying the (known) string landscape. We recast existing LHC searches for new electroweak states to extract updated bounds on this class of scenarios. Improved limits from future colliders and dark matter detection experiments provide additional routes to potentially falsifying string theory.
Valence 1𝑠−0𝑑 proton vacancy of the 32 Si ground state
The 32 Si( 3 He,d) 33 P reaction was studied in inverse kinematics at 6.3 MeV/u. States in 33 P corresponding to the proton 1s-0d single-particle orbitals were identified up to ≈ 4.5 MeV in excitation energy. The ( 3 He,d) spectroscopic factors were determined from distorted-wave Born approximation calculations. When combined with complementary neutron-adding data, the 1s-0d proton vacancies in the 32 Si ground state were extracted. In conjunction with a reanalysis of data from previous single-particle measurements, the trends in proton and neutron vacancy were explored across the 28,30,32,34 Si isotopes. Both proton and neutron vacancy data show gradual changes in their occupancies. The proton 1s 1/2 orbitals in 32 Si and 34 Si are both consistent with being empty. In conclusion, the ground-state nucleon distributions are described by shell-model calculations constrained to the 1s-0d model space.