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DOE OSTI2016

STM Studies of Spin-Orbit Coupled Phases in Real- and Momentum-Space

The recently discovered class of spin-orbit coupled materials with interesting topological character are fascinating both from fundamental as well as application point of view. Two striking examples are 3D topological insulators (TIs) and topological crystalline insulators (TCIs). These materials host linearly dispersing (Dirac like) surface states with an odd number of Dirac nodes and are predicted to carry a quantized half-integer value of the axion field. The non-trivial topological properties of TIs and TCIs arise from strong spin-orbit coupling leading to an inverted band structure; which also leads to the chiral spin texture in momentum space. In this project we used low temperature scanning tunneling microscopy (STM) and spectroscopy (STS) to study materials with topological phases in real- and momentum-space. We studied both single crystals and thin films of topological materials which are susceptible to being tuned by doping, strain or gating, allowing us to explore their physical properties in the most interesting regimes and set the stage for future technological applications. .

36 MATERIALS SCIENCE↗

DOE OSTI2018

Radioactive aerosols training

An introduction to radioactive aerosols will be presented in this class. There will be a specific focus on transuranic materials, typical to those used in operations at Los Alamos. The uptake of radioactive aerosols is affected by the physical characteristics of the airborne material, the behavior of the aerosol in air (or gas), and the interaction of the material with the worker. Aerosol behavior in the radiological workplace will influence filtration, release control, and dose considerations. This course will review the basics of aerosol technology, distinguishing between the classical (Newtonian) and molecular (quantized) regimes. Particles from about 1 to 10 microns (diameter) are described by classical physics, but particles from about 0.01 to 0.3 microns must be understood through modern molecular theory (i.e. Einstein, 1905). The class will discuss relevant LANL accidents that involved aerosol releases from the years 1971, 1994, 2000, 2003 and 2005.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2018

Microwave remote sensing for atmospheric chemistry

Microwave remote sensing is a well-established technique for making sensitive thermal emission measurements at microwave frequencies. This thermal emission described by Planck’s law is the electromagnetic radiation at microwave wavelengths intrinsically emitted from hot objects. This is the blackbody radiation that constitutes the microwave baseline signal. The transitions between quantized rotational states of the constituent gas species gives rise to spectral features on top of this background signal. A distribution of the atmospheric constituents is retrieved from the measured emission lineshape correlated to pressure broadening as a function of altitude. Thus microwave radiometers enable the detection and continuous monitoring of trace gases present in the atmosphere. Microwave radiometers are deployed at various sites around the world measuring an assortment of species and meteorological parameters of interest. Several groups worldwide are active in this field, NRL remote sensing division and the Institute of Physics at the University of Bern among the prominent few. The technology is quite mature with the availability of room temperature RF components at W–band frequencies.

58 GEOSCIENCES↗

DOE OSTI2018

Quantum Representation of Classical Dynamics

A constructive proof is given to show that there is an exact embedding of a classical system of N ordinary differential equations (ODEs) within a quantum mechanical system corresponding to a classical phase space of dimension 2N. Doubling the classical phase space allows one to express any set of ODEs through a classical Hamiltonian that is a sum over a set of constraints. The Lagrange multipliers that enforce the constraints are canonically conjugate to the dependent variables of the original ODE and satisfy equations that ensure that the evolution of the system is symplectic. For the quantized system on extended phase space, Heisenberg’s uncertainty principle is satisfied by each variable and its canonically conjugate momentum, the Lagrange multiplier. However, there is no uncertainty in a simultaneous measurement for any of the variables of the original ODE. Hence,there is complete fidelity for the quantum representation of the classical system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Quantifying neural information content: a case study of the impact of hippocampal adult neurogenesis

Neural networks have an intrinsic information content encapsulated by neural firing behaviors and constituted by their neural encoding. Shannon entropy is a fundamental method to quantize the amount of information in a variety of sources such as communication channels. Many approaches have been devised to apply this sort of information measure to neurons with mixed success. However, doing so typically requires knowledge of the firing behavior probability distributions for the neurons of interest (whether modeled or recordings), and furthermore often is only applicable for single neurons and not ensembles. We have observed that conventional compression methods may help overcome some of the limiting factors of standard techniques and allows us to approximate information in neural data. To do so we have used compressibility as a measure of complexity in order to estimate entropy to quantitatively assess information content of neural ensembles.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Why We Need (But Don't have) Quantum Gravity [Slides]

The varied approaches to quantum gravity - Start from quantum field theory, and try to add gravity (string theory); Start from general relativity and attempt to quantize it (loop quantum gravity); Start from discrete building blocks (causal sets, causal dynamical triangulations).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Asynchronous Ballistic Reversible Computing using Superconducting elements

Computing uses energy. At the bare minimum, erasing information in a computer increases the entropy. Landauer has calculated %7E k B T log(2) Joules is dissipated per bit of energy erased. While the success of Moores law has allowed increasing computing power and efficiency for many years, these improvements are coming to an end. This project asks if there is a way to continue those gains by circumventing Landauer through reversible computing. We explore a new reversible computing paradigm, asynchronous ballistic reversible computing or ABRC. The ballistic nature of data in ABRC matches well with superconductivity which provides a low-loss environment and a quantized bit encoding the fluxon. We discuss both these and our development of a superconducting fabrication process at Sandia. We describe a fully reversible 1-bit memory cell based on fluxon dynamics. Building on this model, we propose several other gates which may also offer reversible operation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Understanding Topological Pseudospin Transport in Van Der Waals' Materials

Because of symmetry, crystals often have degenerate valleys in the conduction or the valence band. This “valley” degree of freedom, similar to electronic charge and spin, has been proposed as an information carrier for new classes of electronic and optoelectronic devices. The basic requirement of information processing is to be able to create and manipulate a flow of valley pseudospin, i.e. valley pseudospin current. Valley pseudospin currents have been demonstrated in recent experiments in monolayer molybdenum disulfide and graphene on hexagonal boron nitride. However, the key fundamental questions regarding the nature of valley pseudospin transport remain open. This project will investigate the importance of Berry curvature effects in valley pseudospin transport and explore regimes for quantized valley Hall conductivity and pure valley pseudospin currents. The study will rely on combined optical and electrical transport techniques to create, manipulate and detect valley pseudospin currents in two-dimensional (2D) van der Waals’ materials of hexagonal structure. The insights provided by this research will deepen the understanding of valley pseudospin transport in 2D and help the development of novel valley-based technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy's National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real-time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI's Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: Run in real-time on the edge (≥ 12 Hz), Classification: Achieve less than 5% false positive detection, Classification: Achieve ≥ 95% methane plume detection rate, Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time. In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗

DOE OSTI2022

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations. To make advancements in all the aforementioned scientific areas, many technical aspects need to be more thoroughly studied and deeply understood in parallel discrete event simulation (PDES). The unique dynamics inherent in a discrete event modeling approach, by their very nature, intersect and influence the entire stack of the computing system, including (a) the unique nature of the instruction sets exercised in PDES workloads without a predominance of high-precision floating point operations, (b) virtual time-constrained multi-threaded execution of many logical processes per processor, (c) extremely variable and difficult to predict network traffic characteristics, (d) interfaces and inter-dependencies with machine learning and artificial intelligence codes at higher software layers, and (e) highly challenging load balancing needs, especially in effectively accounting for accelerated/extremely heterogeneous computing in current and future high-performance computing systems. Efficient and accurate parallel execution of PDES workloads is also dominated by challenges in dealing with their asynchronous concurrency fundamentally present at the model level. Conservative synchronization, optimistic/speculative synchronization, and their hybrid schemes open new questions in fundamental computer science with respect to reversibility of computation and prediction (lookahead) of behaviors inherent within model codes. On the implementation front, there are relatively few scalable, general-purpose parallel discrete event simulators in the world, and even fewer have been studied on emerging hardware platforms. To enable scientific advances using PDES, the research needs in computer science must also be pursued and met in the intersection of the algorithmic and hardware-aware aspects of scalable PDES engines. This report is aimed at capturing a computer science-oriented view of this important area of research in PDES, presenting a sample of important applications with their inherent discrete event technology elements. Needs are outlined in core areas of parallel discrete event research as well as cross-cutting directions in computer science research that positively impact scientific advancements across several important application areas. A selection of priority research opportunities in advanced computing for PDES is identified to serve as reference for key research topics and their order of importance for scientific advancements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Disorder, interactions, and their interplay in novel narrow-gap Dirac materials and Weyl semimetals

Progress of the modern day condensed matter physics is to a large extent driven by the synthesis of new materials, advances in their experimental characterization and theoretical description. Recent discoveries of novel gapless Weyl semimetals, such as NaBi,CdAs, and BiTe-based films, in which magnetic dopants essentially suppress the gap, have added to the family of graphene and topological insulators actively investigated over the past decade. With the field of novel semimetals rapidly maturing, its focus necessarily shifts from demonstrations of the feasibility of such materials to their quantitative characterization. While the transport and optical properties of graphene and topological insulators are well captured within the picture of free non-interacting electrons, gapless 3D Weyl semimetals and narrow-gap 2D semiconductors with Dirac spectrum are known to be extremely susceptible to disorder and electron-electron interactions. This susceptibility obscures the manifestations of nontrivial band structure -- like quantum anomalous Hall effect -- of the new topological materials. Among particular projects to be addressed are: 1) optical conductivity of 3D gapless Dirac fermions in the presence of smooth disorder, 2) interplay of disorder and Coulomb interactions in the spectral properties of such fermions, 3) formation and structure of the impurity band with Coulomb supercritical clusters, 4) Coulomb interaction-driven renormalization of the electron spectrum and of the transport response in the presence of strong magnetic field, 5) instanton approach to the disorder-induced fluctuation states in zero-gap 3D materials, and 6) the role of disorder in quantum anomalous Hall effect. The proposal relies upon the investigators' previous broad expertise in interacting and disordered electron systems. The methods to be employed include perturbative diagrammatic technique, non-perturbative instanton and self-consistent approximations, hydrodynamics of electron liquid. Both analytical as well as numerical approaches are to be employed. The anticipated broader outcome of the proposal includes gaining an in-depth understanding of the interplay of the disorder and interactions under the conditions when this interplay has the most dramatic impact on observables. Traditionally, interaction effects are among the most challenging and interesting problems of condensed matter physics. Similarly, disordered systems typically present very difficult but extremely rich problems in the description of various materials. Importantly, understanding the spectral and transport properties of such materials not only presents the fundamental objective, but is also of particular interest for many applications, such as computation, memory, optics, plasmonics. In particular realization of the quantum anomalous Hall effect may lead to the development of low-power-consumption electronics. Indeed, a major constraint for practical use of the quantum Hall effect is limited by the requirement of the quantizing magnetic field. At the same time, the quantum anomalous Hall effect samples exhibit non-dissipative edge quantum transport in a zero magnetic field.

36 MATERIALS SCIENCE↗

DOE OSTI2022

National High Magnetic Field Laboratory: Pulsed Field Facility Capability Overview [Slides]

High magnetic fields are a fundamental thermodynamic probe of quantum matter. Magnetic fields couple to both electons' spin and charge degrees of freedom. They can be used to manipulate the phase of the electron wavefunction and importantly provide a measure of coherence through orbital quantization. They can both probe and influence the state of a material.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Magnetic imaging of topological phases of matter (Final Report)

This project presents a detailed understanding of the local electronic transport in two different types of conductors. The experimental tools are a combination of local magnetic probes and electronic transport measurements. The first set of samples were superconducting microstructures that exhibited unusual transport behavior. Magnetic imaging revealed the presence of a strain field in the microstructures, which spatially modulated the superconducting properties. This strain field can be controlled through a variety of design parameters opening opportunities for a broad range of quantum materials including topological phases of matter. The second set of samples was fabricated from Cr-doped (Bi,Sb) 2 Te 3 heterostructures that exhibited the quantum anomalous Hall effect (QAHE). Magnetic imaging visualized the current flow in these devices, while simultaneous transport measurements verified that the devices exhibit the QAHE. Surprisingly, the current flowed in the interior of the sample even when exhibiting a high level of quantization.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Letter of Intent for a Drell-Yan experiment with a polarized proton target

It is well known that the proton is a spin-1/2 particle, but how the constituents (quarks and gluons) assemble to this quantized spin is still a mystery. There is a worldwide effort to map out the individual contributions to the proton spin. It is established that the quark spins contribute around 30%, while the gluon intrinsic angular momentum is still under active investigation at the Relativistic Heavy Ion Collider. Fully resolving the proton spin puzzle requires information on the orbital angular momentum (OAM) of both quarks and gluons. Recent studies have shown that the so-called transverse momentum dependent parton distribution functions (TMDs) can inform us about the OAM of the partons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Collective Energy Transport of Excitons in Two-dimensional Materials (Final Report)

The goal of this project is to explore collective behavior that exists in samples with large numbers of interacting particles. The behavior of these systems goes beyond the independent particle picture that is commonly used to describe a vast majority of solid–state phenomena, including the transport of quantized carriers of charge and heat in solids. While collective behavior gives rise to superconductivity at low temperatures, signatures of collective behaviors in both charge and heat transport appear at rather high temperatures in several recent studies of low–dimensional materials. One specific example of this collective behavior is the formation of excitons (i.e., bound electron–hole pairs), which is pronounced in two–dimensional (2D) materials such as transition metal dichalcogenides (TMDCs), with exciton binding energies exceeding the thermal energy at room temperature. In this project, we pursue, optical, electronic, thermal, and thermoelectric measurements to obtain unique insights into the unusual collective energy transport behaviors of excitons in 2D materials and heterostructures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

SIS-AOP Cueing/Segmenting Algorithm (FOA_SIS-AOP) Using the Sandia FOA 4.0 Framework

For machine vision, one of the most important operations is fast and effective object cueing or segmentation. Sandia National Labs has a long history of development and implementation of very fast and effective cueing/segmentation algorithms. This report covers the history, motivation and implementation of evolving frameworks (Sandia FOA Frameworks) upon which this long legacy of successful algorithms are built. The report describes the innovative microprocessor implementation, enabling extremely fast morphological processing, combined with a novel adaptive quantization front - end and a feature - based backend that resulted in Sandia developing fast and effective cueing in a wide variety of applications, from defect detection to SAR ATR. The report covers evolution from Sandia FOA 1.0 Framework (1995) to current Sandia FOA 4.0 Framework (2021). Requirements for the cueing algorithm for SIS - AOP (FOA_SIS - AOP) that drove the Sandia FOA 4.0 Framework development are discussed, along with information on how to use the Sandia FOA Frameworks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Matching Curved Lattices to Anisotropic Tangent Planes

Radial quantization would be the ideal formalism for studying strongly-coupled near-conformal quantum field theories but it requires the ability to perform lattice calculations on static, curved manifolds, specifically a very long cylinder whose cross section is a sphere. Smoothly discretizing the surface of a sphere requires a graph with unequal edge lengths. The geometry of such graphs is well understood since 1961 using Regge Calculus. But, lattice quantum field theories are defined in terms of couplings which appear in the action rather than edge lengths and so the relationship between couplings and lengths must be determined dynamically. A simple example is computing the ratio of spatial to temporal lattice spacings in anisotropic lattice QCD. I will discuss our conjecture that computing anisotropic lattice spacing ratios on affine transformations of regular flat lattices is sufficient to determine coupling assignments on curved lattices.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗