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NASA NTRS2011

The Beginning and End of the Universe

Cosmology is the scientific study of how the Universe began more than 13 billion years ago, how its properties have changed from that time to the present, and what its eventual fate might be. Observational cosmology uses telescopes like the Hubble to reach back in time to find the faint echoes of the Big Bang. In this lecture, I will give an overview of cosmology, highlighting the very rapid progress this field has made in the last decade, and the role that NASA space telescopes have played and will continue to play in the years to come. I will then focus on two of the most intriguing of those recent discoveries: inflation and dark energy. Our universe began in an extremely rapid accelerated expansion, called inflation, which removed all traces anything that may have existed before, flattened the geometry of space-time, and turned microscopic quantum fluctuations into the largest structures in the universe. At the present time, more than 70% of the mass-energy in the Universe consists of a mysterious substance called dark energy. The dark energy causes the expansion of the Universe to accelerate, and he will discuss the ways that we might be able to measure that acceleration more accurately, revealing the nature of the dark energy and learning the eventual fate of the Universe.

Gardner, Jonathan P.↗

NASA NTRS2012

The Beginning and End of the Universe

Gardner, Jonathan P.↗

DOE OSTI2024

Tagged DVCS on neutron with the CLAS12 Experiment and the detector BONuS12 at Jefferson Lab (USA)

Hadronic physics studies the properties of the proton and neutron. The theory of Quantum Chromodynamics (QCD) governs the structure of hadrons. Non-perturbative structure functions are used to describe the hadrons? structure. Generalized Parton Distributions (GPDs) are a set of structure functions providing access to a 3D view of the nucleon. GPDs contain information about the longitudinal momentum and transverse position of quarks and their correlation. They are related to the spin structure and play a role in solving the proton spin puzzle. They provide access to the quarks? orbital angular momentum, a crucial puzzle piece. For this, measurements on the proton, already present, and neutron are necessary. This thesis aims to explore Compton scattering on the neutron with a deuterium target by measuring the spectator proton with the CLAS12 detector and the BONuS12 RTPC at Jefferson Lab. This work first describes the implementation, which I carried out, of a Kalman filter to reconstruct spectator protons in the BONuS12 detector. The second part of the manuscript is dedicated to the work on the analysis of DVCS on the neutron with the subtraction of background noises. Two different methods for the subtraction of ?0 will be detailed. Finally, the obtained results are presented and discussed

Ouillon, Mathieu↗

NASA NTRS1986

Semiconductor superlattice photodetectors

Technical progress made in the study of superlattice photoconductors is summarized and papers submitted for publication are listed. Since the quantum-well regions may contain several subbands, each of which may be occupied by electrons depending on the doping concentrations, it is important to include the multi-subbands in calculating the impact ionization rate. The electrons occupying the higher subbands require a smaller amount of energy to get out of the quantum well; thus, those higher level subband electrons contribute significantly to the impact ionization rate. The results of the subbands have been calculated. Results concerning the nonparabolicity effect of the band structure, the effect of the quantum-well size, and the effect of the band-edge discontinuity and doping are also summarized.

Chuang, S. L.↗

DOE OSTI2026

pyDiSCaMB : enabling the use of multipolar scattering factors in Phenix

Multipolar scattering models, such as the transferable aspherical atom model, account for atomic chemical interactions and provide a more accurate representation of experimental data. However, the simpler independent atom model (IAM), which assumes non-interacting atoms, is the only model available in the most widely used macromolecular refinement programs. This is primarily because IAM offers a hard-to-beat combination of computational efficiency and modelling power at typical macromolecular resolutions. By contrast, more accurate multipolar modelling has historically been limited due to its computational cost and the absence of an interface between software capable of calculating structure factors and gradients based on multipolar models and software designed for macromolecular refinement. This work introduces pyDiSCaMB , a Python software package designed to integrate between the computational crystallography toolbox ( cctbx ) and the quantum crystallography library DiSCaMB ( Densities in Structural Chemistry and Molecular Biology ), thus enabling multipolar scattering models in Phenix 's toolkit. The implementation, features and capabilities of pyDiSCaMB are presented, the runtimes for the calculation of structure factor and target gradients with respect to atomic parameters are explored, and Fourier images of electrostatic potential, electron density and deformation maps are computed as illustrative examples. The pyDiSCaMB library will make multipolar modelling widely available to the structural biology community, potentially transforming refinement and model-building for both crystallography and cryogenic electron microscopy (cryoEM).

MATTS data bank↗

DOE OSTI2025

Lithography-Defined Semiconductor Moirés with Anomalous In-Gap Quantum Hall States

Quantum materials and phenomena have attracted great interest for their potential applications in next-generation microelectronics and quantum-information technologies. In one especially interesting class of quantum materials, moiré superlattices (MSLs) formed by twisted bilayers of 2D materials, a wide range of novel phenomena are observed. However, there exist daunting challenges such as reproducibility and scalability of utilizing 2D MSLs for microelectronics and quantum technologies due to their exfoliate-tear-stack method. Here, we propose lithography-defined semiconductor MSLs, in which three fundamental parameters electron−electron interaction, spin−orbit coupling, and band topology are designable. We experimentally investigate quantum-transport properties in a moiré specimen made in an InAs quantum well. Strong anomalous in-gap states are observed within the same integer quantum Hall state. Our work opens up new horizons for studying 2D quantum-materials phenomena in semiconductors featuring superior industry-level quality and state-of-the-art technologies, and they may potentially enable new quantum-information and microelectronics technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Kondo effect in ferromagnetic quantum critical CeRh 6 ⁢Ge 4

The mechanism of a pressure-induced quantum critical point in the heavy fermion ferromagnet CeRh 6 ⁢Ge 4 has attracted interest, as ferromagnetic quantum criticality in a clean itinerant Ce compound is typically avoided. The localized versus itinerant character of the 4⁢𝑓 electrons is a key aspect for understanding this behavior. We investigated the electronic structure of the 4⁢𝑓 shell in CeRh 6 ⁢Ge 4 using core-level photoelectron and x-ray absorption spectroscopy, demonstrating the hybridization of Ce 4⁢𝑓 with the conduction electrons. Linearly polarized x-ray absorption reveals a temperature-dependent linear dichroism consistent with the crystal-electric-field sequence as inferred from the static susceptibility. This dichroism cannot be described by an ionic full-multiplet model alone, but is reproduced by including the Kondo effect within a single-impurity Anderson model in the noncrossing approximation. The Kondo effect mixes higher-lying crystal-field states into a resulting multiorbital ground state with 4⁢𝑓 occupancy, 𝑛 𝑓 ∼ 0.9. Deviations at low temperatures between the measured linear dichroism and calculated dichroism suggest an orbital-dependent Kondo effect. A scenario in which there is a multiorbital ground state and orbital-dependent Kondo hybridization should be a starting point for a model of pressure-induced criticality in CeRh 6 ⁢Ge 4 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Review of honeycomb-based Kitaev materials with zigzag magnetic ordering

The search for a Kitaev quantum spin liquid in crystalline magnetic materials has fueled intense interest in the two-dimensional honeycomb systems. Many promising candidate Kitaev systems are characterized by a long-range-ordered magnetic structure with an antiferromagnetic zigzag-type order, where the static moments form alternating ferromagnetic chains. Recent experiments on high-quality single crystals uncovered the existence of intriguing multi-k magnetic structures, which evolved from zigzag structures. Those discoveries have sparked new theoretical developments and amplified interest in these materials. We present an overview of the honeycomb materials known to display this type of magnetic structure and provide detailed crystallographic information for the possible single- and multi-k variants.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Convergent Protocols for Computing Protein–Ligand Interaction Energies Using Fragment-Based Quantum Chemistry

Fragment-based quantum chemistry methods offer a way to sidestep the steep nonlinear scaling of electronic structure calculations so that large molecular systems can be investigated using high-level methods. Here, we use fragmentation to compute protein–ligand interaction energies in systems with several thousand atoms, using a new software platform for managing fragment-based calculations that implements a screened many-body expansion. Convergence tests using a minimal-basis semiempirical method (HF-3c) indicate that two-body calculations, with single-residue fragments and simple hydrogen caps, are sufficient to reproduce interaction energies obtained using conventional supramolecular electronic structure calculations, to within 1 kcal/mol at about 1% of the computational cost. We also demonstrate that the HF-3c results are illustrative of trends obtained with density functional theory in basis sets up to augmented quadruple-ζ quality. Strategic deployment of fragmentation facilitates the use of converged biomolecular model systems alongside high-quality electronic structure methods and basis sets, bringing ab initio quantum chemistry to systems of hitherto unimaginable size. This will be useful for generation of high-quality training data for machine learning applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Electronic structure of the honeycomb iridate Cu 2 ⁢IrO 3 at high pressure

Cu 2 IrO 3 has attracted recent interest due to its proximity to the Kitaev quantum spin liquid state and the complex structural response observed at high pressures. We use x-ray spectroscopy and scattering as well as electrical transport techniques to unveil the electronic structure of Cu 2 IrO 3 at ambient and high pressures. Despite featuring a Ir 4+ J eff = 1/2 state at ambient pressure, Ir L 3 -edge resonant inelastic x-ray scattering reveals broadened electronic excitations that point to the importance of Ir 5d-Cu 3d interaction. High pressure first drives an Ir-Ir dimer state with collapsed < L · S > and < L z >/< S z >, signaling the formation of 5d molecular orbitals. A novel Cu → Ir charge transfer is observed above 30 GPa at low temperatures, leading to an approximate Ir 3+ and Cu 1.5+ valence, with persistent insulating electrical transport seemingly driven by charge segregation of Cu 1+ /Cu 2+ ions into distinct sites. Concomitant x-ray spectroscopy and diffraction measurements through different thermodynamic paths demonstrate a strong electron-lattice coupling, with J eff = 1/2 and Ir 3+ /Cu 1.5+ electronic states occurring only in phases 1 and 5, respectively. Remarkably, the charge-transfer state can only be reached if Cu 2 IrO 3 is pressurized at low temperature, suggesting that phonons play an important role in the inhibiting this phase. Furthermore, these results point to the choice of thermodynamic path across interplanar collapse transition as a key parameter to access novel states in intercalated iridates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Large-Scale Materials Modeling at Quantum Accuracy: Ab Initio Simulations of Quasicrystals and Interacting Extended Defects in Metallic Alloys

Ab initio electronic-structure has remained dichotomous between achievable accuracy and length-scale. Quantum many-body (QMB) methods realize quantum accuracy but fail to scale. Density functional theory (DFT) scales favorably but remains far from quantum accuracy. We present a framework that breaks this dichotomy by use of three interconnected modules: (i) invDFT: a methodological advance in inverse DFT linking QMB methods to DFT; (ii) MLXC: a machine-learned density functional trained with invDFT data, commensurate with quantum accuracy; (iii) DFT-FE-MLXC: an adaptive higher-order spectral finite-element (FE) based DFT implementation that integrates MLXC with efficient solver strategies and HPC innovations in FE-specific dense linear algebra, mixed-precision algorithms, and asynchronous compute-communication. Furthermore, we demonstrate a paradigm shift in DFT that not only provides an accuracy commensurate with QMB methods in ground-state energies, but also attains an unprecedented performance of 659.7 PFLOPS (43.1% peak FP64 performance) on 619,124 electrons using 8,000 GPU nodes of Frontier supercomputer.

density functional theory↗

DOE OSTI2022

Variational quantum eigensolver with reduced circuit complexity

Abstract The variational quantum eigensolver (VQE) is one of the most promising algorithms to find eigenstates of a given Hamiltonian on noisy intermediate-scale quantum devices (NISQ). The practical realization is limited by the complexity of quantum circuits. Here we present an approach to reduce quantum circuit complexity in VQE for electronic structure calculations. Our ClusterVQE algorithm splits the initial qubit space into clusters which are further distributed on individual (shallower) quantum circuits. The clusters are obtained based on mutual information reflecting maximal entanglement between qubits, whereas inter-cluster correlation is taken into account via a new “dressed” Hamiltonian. ClusterVQE therefore allows exact simulation of the problem by using fewer qubits and shallower circuit depth at the cost of additional classical resources, making it a potential leader for quantum chemistry simulations on NISQ devices. Proof-of-principle demonstrations are presented for several molecular systems based on quantum simulators as well as IBM quantum devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Quantum oscillations and transport properties of layered single-crystal SrCu 4 ⁢As 2

Here, we report a systematic investigation of the physical properties and Fermi-surface topology of layered single-crystal SrCu 4⁢ As 2 using electrical transport, magnetotransport, and quantum-oscillation experiments plus band-structure calculations. The temperature-dependent electrical resistivity reveals a hysteretic phase transition at 𝑇 𝑃 =59 K, most likely associated with a structural change. Hall resistivity data suggest a marked change in the average hole density resulting from the latter phase transition near 𝑇 𝑃 . A large, linear, and nonsaturating magnetoresistance is observed at low temperatures in SrCu 4 ⁢As 2 , likely attributable to the multipocket Fermi surface. Quantum-oscillation data measured in magnetic fields of up to 60 T show several oscillation frequencies exhibiting low effective masses, indicating the presence of Dirac-like band dispersion in SrCu 4 ⁢As 2 , as suggested by the band structure calculations.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Studying the hadron structure with PANDA and CLAS using machine learning techniques

The hadron spectroscopy and structure are currently very active fields of research to study the non-perturbative regime of quantum chronodynamics. The first one studies the complex structure of excited hadrons by looking at their decay products, while the latter uses lepton scattering on nucleons. Both methods require reconstruction algorithms with great efficiency and good particle identification and background rejection rates. This work aims to provide these by either improving the existing methods or developing new ones. The first part of this document presents a feasibility study of a predicted hybrid charmonium state for the PANDA experiment. Lattice QCD calculations predict the ground state hybrid charmonium to be a spin exotic with quantum numbers of JP C = 1?+ at a mass of around 4.3 GeV with a width to be around 20 MeV. A machine learning based data analysis scheme is proposed to further improve the signal efficiency and the background reduction, alongside with improvements of the analysis software (PandaRoot), that are vital for this study. These improvements include a reworked clustering algorithm for the electromagnetic calorimeter (EMC) and an optimized monte carlo matching for neutral particles. The second part of this document is about studying the proton structure. A multidimensional study of the structure function ratio Fsin(?)LU /FUU has been performed for K±, based on the measurement of beam-spin asymmetries. It uses the high statistics data recorded with the CLAS12 spectrometer at Jefferson Laboratory. Fsin(?)LU is a twist-3 quantity that provides information about the quark gluon correlations in the proton. This document will present for the first time a simultaneous analysis of two kaon channels over a large kinematic range of z, xB , PT and Q2 with virtualities Q2 ranging from 1 GeV2 up to 8 GeV2 using machine learning techniques for improved particle identification.

Kripko, Aron↗

NASA NTRSDate not supplied

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗

DOE OSTI2026

Improving the Precision of First-Principles Calculation of Parton Physics from Lattice Quantum Chromodynamics

Large momentum effective theory (LaMET) provides a general framework for computing the multi-dimensional partonic structure of the proton from first principles using lattice quantum chromodynamics (QCD). In this effective field theory approach, LaMET predicts parton distributions through a power expansion and perturbative matching of a class of Euclidean observables—quasi-distributions—evaluated at large proton momenta. Recent advances in lattice renormalization, such as the hybrid scheme with leading renormalon resummation, together with improved matching kernel that incorporates higher-loop corrections and resummations, have enhanced both the perturbative and power accuracy of LaMET, enabling a reliable quantification of theoretical uncertainties. Moreover, the Coulomb-gauge correlator approach further simplifies lattice analyses and improves the precision of transverse-momentum-dependent structures, particularly in the non-perturbative region. State-of-the-art LaMET calculations have already yielded certain parton observables with important phenomenological impact. In addition, the recently proposed kinematically enhanced lattice interpolation operators promise access to unprecedented proton momenta with greatly improved signal-to-noise ratios, which will extend the range of LaMET prediction and further suppress the power corrections. The remaining challenges, such as controlling excited-state contamination in lattice matrix elements and extracting gluonic distributions, are expected to benefit from emerging lattice techniques for ground-state isolation and noise reduction. Thus, lattice QCD studies of parton physics have entered an exciting stage of precision control and systematic improvement, which will have a broader impact for nuclear and particle experiments.

Zhao, Yong [Argonne National Laboratory (ANL), Arg↗

NASA NTRS2010

Physics of Life: A Model for Non-Newtonian Properties of Living Systems

This innovation proposes the reconciliation of the evolution of life with the second law of thermodynamics via the introduction of the First Principle for modeling behavior of living systems. The structure of the model is quantum-inspired: it acquires the topology of the Madelung equation in which the quantum potential is replaced with the information potential. As a result, the model captures the most fundamental property of life: the progressive evolution; i.e. the ability to evolve from disorder to order without any external interference. The mathematical structure of the model can be obtained from the Newtonian equations of motion (representing the motor dynamics) coupled with the corresponding Liouville equation (representing the mental dynamics) via information forces. All these specific non-Newtonian properties equip the model with the levels of complexity that matches the complexity of life, and that makes the model applicable for description of behaviors of ecological, social, and economical systems. Rather than addressing the six aspects of life (organization, metabolism, growth, adaptation, response to stimuli, and reproduction), this work focuses only on biosignature ; i.e. the mechanical invariants of life, and in particular, the geometry and kinematics of behavior of living things. Living things obey the First Principles of Newtonian mechanics. One main objective of this model is to extend the First Principles of classical physics to include phenomenological behavior on living systems; to develop a new mathematical formalism within the framework of classical dynamics that would allow one to capture the specific properties of natural or artificial living systems such as formation of the collective mind based upon abstract images of the selves and non-selves; exploitation of this collective mind for communications and predictions of future expected characteristics of evolution; and for making decisions and implementing the corresponding corrections if the expected scenario is different from the originally planned one. This approach postulates that even a primitive living species possesses additional, non-Newtonian properties that are not included in the laws of Newtonian or statistical mechanics. These properties follow from a privileged ability of living systems to possess a self-image (a concept introduced in psychology) and to interact with it. The proposed mathematical system is based on the coupling of the classical dynamical system representing the motor dynamics with the corresponding Liouville equation describing the evolution of initial uncertainties in terms of the probability density and representing the mental dynamics. The coupling is implemented by the information-based supervising forces that can be associated with self-awareness. These forces fundamentally change the pattern of the probability evolution, and therefore, lead to a major departure of the behavior of living systems from the patterns of both Newtonian and statistical mechanics. This innovation is meant to capture the signature of life based only on observable behavior, not on any biochemistry. This will not prevent the use of this model for developing artificial living systems, as well as for studying some general properties of behavior of natural, living systems.

Zak, Michail↗

DOE OSTI2021

Spin-Coherent Transport under Strong Spin-Orbit Interaction (Final Technical Report)

The major goals of the project consisted of acquiring insight in spin-dependent quantum coherent electronic transport phenomena arising from spin-orbit interaction, via experiments on semiconductor heterostructures and thin film semimetals patterned into mesoscopic and nanoscale geometries. The solid-state physics findings contain insight potentially useful for the creation of new quantum states of matter, for spin operations in quantum information processing, for future spin electronics, and for other future functionalities of power-saving electronic devices. The subject was of fundamental interest, but was also of long-term applied interest for quantum devices, spintronics devices, and general electronic devices. The experiments were conducted by low-temperature electronic magnetotransport in nanoscale structures of length scales similar to the quantum phase- and spin-coherence lengths and the carrier mean-free paths in the materials. Emphasis was placed on quantum coherence and spin coherence, to understand coherent spin-dependent electronic processes, on transport of electrons with very long mean-free path (ballistic transport), on the transfer of electron spin to nuclear spin (dynamic nuclear spin polarization in bismuth), and on the study of materials with quantum states emerging from spin-orbit interaction and electron-electron interaction (bismuth iridates). In two-dimensional electron systems in quantum wells of the narrow-bandgap semiconductors InAs and InGaAs the objectives included the characterization of quantum states arising from the Aharonov-Casher quantum-mechanical phase as an electromagnetic dual of the Aharonov-Bohm phase. Objectives also included quantum electronic transport at the mesoscopic scale on the semimetal bismuth in thin film form, and particularly on its strongly spin-orbit coupled surface states. An almost-strain-free method was developed to grow high-quality bismuth thin films. Devices fabricated on these films were then used to study a novel nuclear spin torque, whereby the bismuth carrier spin was transferred to the bismuth nuclei by the agency of both spin-orbit interaction and hyperfine interaction. Aspects of ballistic transport were studied in GaAs/AlGaAs heterostructures of very high mobility, and a hitherto unsuspected similarity was discovered between ballistic transport and hydrodynamic transport, of potential use in future power-saving electronic devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗