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DOE OSTI2024

Invariant Features for Accurate Predictions of Quantum Chemical UV-vis Spectra of Organic Molecules

Including invariance of global properties of a phys-ical system as an intrinsic feature in graph neural networks (GNNs) enhances the model's robustness and generalizability and reduces the amount of training data required to obtain a desired accuracy for predictions of these properties. Existing open source GNN libraries construct invariant features only for specific GNN architectures. This precludes the generalization of invariant features to arbitrary message passing neural network (MPNN) layers which, in turn, precludes the use of these libraries for new, user-specified predictive tasks. To address this limitation, we implement invariant MPNNs into the flexible and scalable HydraGNN architecture. HydraGNN enables a seamless switch between various MPNNs in a unified layer sequence and allows for a fair comparison between the predictive performance of different MPNNs. We trained this enhanced HydraGNN archi-tecture on the ultraviolet-visible (UV-vis) spectrum of GDB-9 molecules, a feature that describes the molecule's electronic exci-tation modes, computed with time-dependent density functional tight binding (TD-DFTB) and available open source through the GDB-9-Ex dataset. We assess the robustness (i.e., accuracy and generalizability) of the predictions obtained using different invariant MPNNs with respect to different values of the full width at half maximum (FWHM) for the Gaussian smearing of the theoretical peaks. Our numerical results show that incorporating invariance in the HydraGNN architecture significantly enhances both accuracy and generalizability in predicting UV-vis spectra of organic molecules.

Baker, Justin↗

DOE OSTI2025

Recent Developments in DFTB+, a Software Package for Efficient Atomistic Quantum Mechanical Simulations

DFTB+ is a flexible, open-source software package developed by its community, designed for fast and efficient atomistic quantum mechanical simulations. It employs various methods that approximate density functional theory (DFT), such as density functional-based tight binding (DFTB) and the extended tight binding (xTB) approach allowing simulations of large systems over extended time scales with reasonable accuracy, while being significantly faster than traditional ab initio methods. In recent years, several new extensions of the DFTB method have been developed and implemented in the DFTB+ program package in order to improve the accuracy and generality of the available simulation results. In this paper, we review those enhancements, show several use case examples and discuss the strengths and limitations of its features.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Fluids confined in wedges and by edges: Virial series for the line-thermodynamic properties of hard spheres

This work is devoted to analyze the relation between the thermodynamic properties of a confined fluid and the shape of its confining vessel. Recently, new insights in this topic were found through the study of cluster integrals for inhomogeneous fluids that revealed the dependence on the vessel shape of the low density behavior of the system. Here, the statistical mechanics and thermodynamics of fluids confined in wedges or by edges is revisited, focusing on their cluster integrals. In particular, the well known hard sphere fluid, which was not studied in this framework so far, is analyzed under confinement and its thermodynamic properties are analytically studied up to order two in the density. Furthermore, the analysis is extended to the confinement produced by a corrugated wall. These results rely on the obtained analytic expression for the second cluster integral of the confined hard sphere system as a function of the opening dihedral angle 0 < β < 2π. It enables a unified approach to both wedges and edges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Circular polarization switching and bistability in an optically injected 1300 nm spin-vertical cavity surface emitting laser

We report the experimental observation of circular polarization switching (PS) and polarization bistability (PB) in a 1300 nm dilute nitride spin-vertical cavity surface emitting laser (VCSEL). We demonstrate that the circularly polarized optical signal at 1300 nm can gradually or abruptly switch the polarization ellipticity of the spin-VCSEL from right-to-left circular polarization and vice versa. Moreover, different forms of PS and PB between right- and left-circular polarizations are observed by controlling the injection strength and the initial wavelength detuning. These results obtained at the telecom wavelength of 1300 nm open the door for novel uses of spin-VCSELs in polarization sensitive applications in future optical systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

DFTB+, a software package for efficient approximate density functional theory based atomistic simulations

DFTB+ is a versatile community developed open source software package offering fast and efficient methods for carrying out atomistic quantum mechanical simulations. By implementing various methods approximating density functional theory (DFT), such as the density functional based tight binding (DFTB) and the extended tight binding method, it enables simulations of large systems and long timescales with reasonable accuracy while being considerably faster for typical simulations than the respective ab initio methods. Based on the DFTB framework, it additionally offers approximated versions of various DFT extensions including hybrid functionals, time dependent formalism for treating excited systems, electron transport using non-equilibrium Green’s functions, and many more. DFTB+ can be used as a user-friendly standalone application in addition to being embedded into other software packages as a library or acting as a calculation-server accessed by socket communication. We give an overview of the recently developed capabilities of the DFTB+ code, demonstrating with a few use case examples, discuss the strengths and weaknesses of the various features, and also discuss on-going developments and possible future perspectives.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2019

Hall viscosity and nonlocal conductivity of gapped graphene

We calculate the Hall viscosity and the nonlocal (i.e., dependent on wave vector q) Hall conductivity of “gapped graphene” (a nontopological insulator with two valleys) in the presence of a strong perpendicular magnetic field. Using the linear-response theory at zero temperature within the Dirac approximation for the Landau levels, we present analytical expressions for both valley and total Hall viscosities and conductivity up to q 2 at all frequencies. Although the final formulas for total Hall viscosity and conductivity are similar to the ones previously obtained for gapless graphene, the derivation reveals a significant difference between the two systems. First of all, both the Hall viscosity and the Hall conductivity vanish when the Fermi level lies in the gap that separates the lowest Landau level in the conduction band from the highest Landau level in the valence band. It is only when the Fermi level is not in the gap that the familiar formulas of gapless graphene are recovered. Second, in the case of gapped graphene, it is not possible (at least, within our present approach) to define a single-valley Hall viscosity: this quantity diverges with a strength proportional to the magnitude of the gap. It is only when both valleys are included that the diverging terms, having opposite signs in the two valleys, cancel out, and the familiar result is recovered. In contrast to this, the nonlocal Hall conductivity is finite in each valley. These results indicate that the Hoyos-Son formula [Phys. Rev. Lett. 108, 066805 (2012)] connecting the Hall viscosity to the coefficient of q 2 in the small-q expansion of the q-dependent Hall conductivity cannot be applied to each valley, but only to the system as a whole. As a result, the problem of defining a “valley Hall viscosity” remains open.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Specific features of ballistic electron transport in double-level open systems in a large-amplitude high-frequency electric field

Analytical expressions for electron coefficients of transmission and reflection in a large-amplitude high-frequency electric field, with a frequency close to resonance, for asymmetric double- and triple-barrier resonant tunneling structures with thin high barriers forming open two-level systems are reported. The dependences of the width and shape of resonant levels on the high-frequency field amplitude are investigated. It is shown that, in these structures there are almost always conditions at which nonresonant scattering channels near the quantum levels can become absolutely transparent.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗

DOE OSTI2015

Fission Fragment Mass Distributions and Total Kinetic Energy Release of 235-Uranium and 238-Uranium in Neutron-Induced Fission at Intermediate and Fast Neutron Energies

This Ph.D. dissertation describes a measurement of the change in mass distributions and average total kinetic energy (TKE) release with increasing incident neutron energy for fission of 235 U and 238 U. Although fission was discovered over seventy-five years ago, open questions remain about the physics of the fission process. The energy of the incident neutron, En, changes the division of energy release in the resulting fission fragments, however, the details of energy partitioning remain ambiguous because the nucleus is a many-body quantum system. Creating a full theoretical model is difficult and experimental data to validate existing models are lacking. Additional fission measurements will lead to higher-quality models of the fission process, therefore improving applications such as the development of next-generation nuclear reactors and defense. This work also paves the way for precision experiments such as the Time Projection Chamber (TPC) for fission cross section measurements and the Spectrometer for Ion Determination in Fission (SPIDER) for precision mass yields.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Johnson, Hans↗

DOE OSTI2025

Spin squeezing in an ensemble of nitrogen–vacancy centres in diamond

Spin-squeezed states provide a seminal example of how the structure of quantum mechanical correlations can be controlled to produce metrologically useful entanglement. These squeezed states have been demonstrated in a wide variety of quantum systems ranging from atoms in optical cavities to trapped ion crystals. By contrast, despite their numerous advantages as practical sensors, spin ensembles in solid-state materials have yet to be controlled with sufficient precision to generate targeted entanglement such as spin squeezing. Here we report the experimental demonstration of spin squeezing in a solid-state spin system. Our experiments are performed on a strongly interacting ensemble of nitrogen–vacancy colour centres in diamond at room temperature, and squeezing (−0.50 ± 0.13 dB) below the noise of uncorrelated spins is generated by the native magnetic dipole–dipole interaction between nitrogen–vacancy centres. To generate and detect squeezing in a solid-state spin system, we overcome several challenges. First, we develop an approach, using interaction-enabled noise spectroscopy, to characterize the quantum projection noise in our system without directly resolving the spin probability distribution. Second, noting that the random positioning of spin defects severely limits the generation of spin squeezing, we implement a pair of strategies aimed at isolating the dynamics of a relatively ordered sub-ensemble of nitrogen–vacancy centres. Furthermore, our results open the door to entanglement-enhanced metrology using macroscopic ensembles of optically active spins in solids.

Atomic and molecular physics↗

DOE OSTI2022

DeePKS + ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials

Recently, the development of machine learning (ML) potentials has made it possible to perform large-scale and long-time molecular simulations with the accuracy of quantum mechanical (QM) models. However, for different levels of QM methods, such as density functional theory (DFT) at the meta-GGA level and/or with exact exchange, quantum Monte Carlo, etc., generating a sufficient amount of data for training an ML potential has remained computationally challenging due to their high cost. In this work, we demonstrate that this issue can be largely alleviated with Deep Kohn–Sham (DeePKS), an ML-based DFT model. DeePKS employs a computationally efficient neural network-based functional model to construct a correction term added upon a cheap DFT model. Upon training, DeePKS offers closely matched energies and forces compared with high-level QM method, but the number of training data required is orders of magnitude less than that required for training a reliable ML potential. As such, DeePKS can serve as a bridge between expensive QM models and ML potentials: one can generate a decent amount of high-accuracy QM data to train a DeePKS model and then use the DeePKS model to label a much larger amount of configurations to train an ML potential. Further, this scheme for periodic systems is implemented in a DFT package ABACUS, which is open source and ready for use in various applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

NanoMechanics: Elasticity and Friction in Nano‐Objects

A large scientific and technological effort is underway to investigate the properties of two‐dimensional (2D) materials to become building blocks in integrated nano‐electronic and photonic circuits, composites, coatings, energy harvesting nano‐ systems, nano‐sensors, and nano‐electro‐mechanical systems (NEMS).While several experiments and calculations have revealed exciting novel phenomena in these nanostructures, many scientific and technological questions remain open. In particular, understanding and controlling the structure and mechanical properties of 2D materials at the interface with a solid surface is of key importance to enable the aforementioned nanotechnologies, as well as to fulfill the potential of strain engineering to tailor their properties. The vision of this DoE research program was to investigate novel mechanical properties and phenomena in 1D and 2D materials with the overarching goal of defining a new basic understanding of mechanical behavior in nano and quantum systems. The group of the PI has developed in the last years several studies on the mechanical properties of Carbon nanotubes and oxide nanobelts, more recently the PI has focused her attention on the properties of two‐dimensional materials, such as graphene and MoS 2 , which are a few‐atomic‐layer thick films and hold a great potential for technological and energy applications. The most studied 2D material is graphene, existing as a single layer of graphite or a few‐layer thick epitaxial graphene film. Graphene possesses a large in‐plane Young’s modulus as well as high intrinsic carrier mobility, and high in‐plane thermal conductivity. Besides graphene, also 2D films of graphene oxide (GO), hexagonal Boron Nitride (h‐BN), and transition metal dichalcogenides such as MoS 2 exhibit unique and excellent properties and hold great promise for nanotechnology applications. This research program was aimed at developing a new basic understanding of the mechanical properties of 1D and 2D materials at the interface with solid substrates, with a focus on the role of defects, materials structure, and substrate interaction. Ultimately, we aimed at developing the basic knowledge and experimental tools for manipulating 1D and 2D materials’ structure, stacking, substrate interaction, defects, and number of layers to realize an entirely new class of ultra‐hard, ultra‐thin, and ultra‐light active materials with ad‐ hoc mechanical properties for a variety of applications.

2D Materials↗

DOE OSTI2022

The QICK (Quantum Instrumentation Control Kit): Readout and control for qubits and detectors

We introduce a Xilinx RF System-on-Chip (RFSoC)-based qubit controller (called the Quantum Instrumentation Control Kit, or QICK for short), which supports the direct synthesis of control pulses with carrier frequencies of up to 6 GHz. The QICK can control multiple qubits or other quantum devices. The QICK consists of a digital board hosting an RFSoC field-programmable gate array, custom firmware, and software and an optional companion custom-designed analog front-end board. We characterize the analog performance of the system as well as its digital latency, important for quantum error correction and feedback protocols. We benchmark the controller by performing standard characterizations of a transmon qubit. We achieve an average gate fidelity of ℱ avg =99.93%. All of the schematics, firmware, and software are open-source.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Role of p-GaN layer thickness in the degradation of InGaN-GaN MQW solar cells under 405 nm laser excitation

GaN-based solar cells with InGaN multiple quantum wells (MQWs) are promising devices for application in space environment, concentrator solar systems, wireless power transmission and multi-junction solar cells. It is therefore important to understand their degradation kinetics when submitted to high-temperature and high-intensity stress. We submitted three samples of GaN-InGaN MQW solar cells with p-AlGaN electron-blocking-layer with different thickness of the p-GaN layer to constant power stress at 310 W/cm 2 , 175 °C for several hundred hours. The main degradation modes are a reduction of open-circuit voltage, short-circuit current, external quantum efficiency, power conversion efficiency and electroluminescence. In particular, we observed that a thinner p-GaN layer results in a stronger degradation observed on the cell operating parameters. The analysis of the dark I-V characteristics showed an increase in low-forward bias current and the analysis of electroluminescence showed a decrease in the electroluminescene emitted by the (forward biased) cell, as a consequence of stress. This work highlights that the cause of degradation is possibly related to a diffusion mechanism, which results in an increase of defect density in the active region. Finally, the impurities involved in the diffusion processes possibly originate from the p-side of the devices, therefore a thicker p-GaN layer reduces the amount of defects reaching the active region.

14 SOLAR ENERGY↗

DOE OSTI2016

Optical method for distance and displacement measurements of the probe-sample separation in a scanning near-field optical microscope

In this work, we present an alternative optical method to determine the probe-sample separation distance in a scanning near-field optical microscope. The experimental method is based in a Lloyd’s mirror interferometer and offers a measurement precision deviation of ∼100 nm using digital image processing and numerical analysis. The technique can also be strategically combined with the characterization of piezoelectric actuators and stability evaluation of the optical system. It also opens the possibility for the development of an automatic approximation control system valid for probe-sample distances from 5 to 500 μm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Generalized Hydrodynamics: A Perspective

Conventional hydrodynamics describes systems with few long-lived excitations. In one dimension, however, many experimentally relevant systems feature a large number of long-lived excitations and conserved quantities even at high temperature, because they are proximate to integrable limits. Such models cannot be treated using conventional hydrodynamics. The framework of generalized hydrodynamics (GHD) was recently developed to treat the dynamics of one-dimensional models: It combines ideas from integrability, hydrodynamics, and kinetic theory to come up with a quantitative theory of transport. GHD has successfully settled several long-standing questions about one-dimensional transport; it has also been leveraged to study dynamical questions beyond the transport of conserved quantities and to systems that are not integrable. In this article, we introduce the main ideas and predictions of GHD, survey some of the most recent theoretical extensions and experimental tests of the GHD framework, and discuss some open questions in transport that the GHD perspective might elucidate. Published by the American Physical Society 2025

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Digital quantum simulation of NMR experiments

Simulations of nuclear magnetic resonance (NMR) experiments can be an important tool for extracting information about molecular structure and optimizing experimental protocols but are often intractable on classical computers for large molecules such as proteins and for protocols such as zero-field NMR. We demonstrate the first quantum simulation of an NMR spectrum, computing the zero-field spectrum of the methyl group of acetonitrile using four qubits of a trapped-ion quantum computer. We reduce the sampling cost of the quantum simulation by an order of magnitude using compressed sensing techniques. We show how the intrinsic decoherence of NMR systems may enable the zero-field simulation of classically hard molecules on relatively near-term quantum hardware and discuss how the experimentally demonstrated quantum algorithm can be used to efficiently simulate scientifically and technologically relevant solid-state NMR experiments on more mature devices. Our work opens a practical application for quantum computation.

74 ATOMIC AND MOLECULAR PHYSICS↗