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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Mechanisms for stabilizing θ'(Al 2 Cu) precipitates at elevated temperatures investigated with phase field modeling

While most Al–Cu and Al–Si–Cu alloys strengthened by the metastable θ' phase exhibit extensive microstructural degradation above 200 °C, recent experimental work has demonstrated that θ' precipitates can be stabilized to 350 °C by microalloying additions of Mn and Zr, resulting in improved mechanical properties at elevated temperatures. Here, the present work utilizes phase field modeling to study the relationship between microalloying solute elements and the coarsening resistance of θ'. Simulations are designed to parse out the relative influence of various stabilization mechanisms on microstructural evolution of θ' precipitates at elevated temperatures. Specifically, a ternary alloying element is added to a virtual microstructure to study the operation and effectiveness of stabilization mechanisms including solute drag, diffusion barriers, interfacial energy reduction, and lattice strain modification. Simulation results are compared with atom probe tomography observations. Lastly, the simulations rationalize experimental observations of microstructural evolution and solute segregation in Al–Cu–Mn–Zr alloys, and reveal the interlinked thermodynamic and kinetic mechanisms that determine the elevated temperature stability of θ' precipitates.

36 MATERIALS SCIENCE↗
DOE OSTI2015

In-situ Mass Spectrometric Determination of Molecular Structural Evolution at the Solid Electrolyte Interphase in Lithium-Ion Batteries

Dynamic molecular evolution at solid/liquid electrolyte interface is always a mystery for a rechargeable battery due to the challenge to directly probe/observe the solid/liquid interface under reaction conditions, which in essence appears to be similarly true for all the fields involving solid/liquid phases, such as electrocatalysis, electrodeposition, biofuel conversion, biofilm, and biomineralization, We use in-situ liquid secondary ion mass spectroscopy (SIMS) for the first time to directly observe the molecular structural evolution at the solid electrode/liquid electrolyte interface for a lithium (Li)-ion battery under dynamic operating conditions. We have discovered that the deposition of Li metal on copper electrode leads to the condensation of solvent molecules around the electrode. Chemically, this layer of solvent condensate tends to deplete the salt anion and with low concentration of Li+ ions, which essentially leads to the formation of a lean electrolyte layer adjacent to the electrode and therefore contributes to the overpotential of the cell. This unprecedented molecular level dynamic observation at the solid electrode/liquid electrolyte interface provides vital chemical information that is needed for designing of better battery chemistry for enhanced performance, and ultimately opens new avenues for using liquid SIMS to probe molecular evolution at solid/liquid interface in general.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2021

Quantum algorithms for open lattice field theory

Certain aspects of some unitary quantum systems are well described by evolution via a non-Hermitian effective Hamiltonian, as in the Wigner-Weisskopf theory for spontaneous decay. Conversely, any non-Hermitian Hamiltonian evolution can be accommodated in a corresponding unitary system + environment model via a generalization of Wigner-Weisskopf theory. This demonstrates the physical relevance of novel features such as exceptional points in quantum dynamics, and opens up avenues for studying many-body systems in the complex plane of coupling constants. In the case of lattice field theory, sparsity lends these channels the promise of efficient simulation on standardized quantum hardware. We thus consider quantum operations that correspond to Suzuki-Lie-Trotter approximation of lattice field theories undergoing nonunitary time evolution, with potential applicability to studies of spin or gauge models at finite chemical potential, with topological terms, to quantum phase transitions—a range of models with sign problems. We develop non-Hermitian quantum circuits and explore their promise on a benchmark, the quantum one-dimensional Ising model with complex longitudinal magnetic field, showing that observables can probe the Lee-Yang edge singularity. The development of attractors past critical points in the space of complex couplings indicates a potential for study on near-term noisy hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Microdiverse bacterial clades prevail across Antarctic wetlands

Antarctica's extreme environmental conditions impose selection pressures on microbial communities. Indeed, a previous study revealed that bacterial assemblages at the Cierva Point Wetland Complex (CPWC) are shaped by strong homogeneous selection. Yet which bacterial phylogenetic clades are shaped by selection processes and their ecological strategies to thrive in such extreme conditions remain unknown. Here, we applied the phyloscore and feature-level βNTI indexes coupled with phylofactorization to successfully detect bacterial monophyletic clades subjected to homogeneous (HoS) and heterogenous (HeS) selection. Remarkably, only the HoS clades showed high relative abundance across all samples and signs of putative microdiversity. The majority of the amplicon sequence variants (ASVs) within each HoS clade clustered into a unique 97% sequence similarity operational taxonomic unit (OTU) and inhabited a specific environment (lotic, lentic or terrestrial). Our findings suggest the existence of microdiversification leading to sub-taxa niche differentiation, with putative distinct ecotypes (consisting of groups of ASVs) adapted to a specific environment. We hypothesize that HoS clades thriving in the CPWC have phylogenetically conserved traits that accelerate their rate of evolution, enabling them to adapt to strong spatio-temporally variable selection pressures. Variable selection appears to operate within clades to cause very rapid microdiversification without losing key traits that lead to high abundance. Variable and homogeneous selection, therefore, operate simultaneously but on different aspects of organismal ecology. The result is an overall signal of homogeneous selection due to rapid within-clade microdiversification caused by variable selection. It is unknown whether other systems experience this dynamic, and we encourage future work evaluating the transferability of our results.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Evolution of the high-power spallation neutron mercury target at the SNS

The Spallation Neutron Source (SNS) began operation in 2006 and first operated at its full 1.4 MW power in 2013. Targets, which receive the pulsed proton beam, were a limiting factor for reliable full power operation for several years. Reaching reliable target operation at 1.4 MW required not only changes to the target design but also support and coordination across the entire SNS enterprise. The history and some key lessons learned are presented.

Winder, Drew E↗
DOE OSTI2021

Modeling and Optimizing Pumped Storage in a Multi-stage Large Scale Electricity Market under Portfolio Evolution

To leverage the fast-ramping capability of resources to provide great value to the grid, electricity system operators such as the Midcontinent Independent System Operator (MISO) continue to evolve their approaches for integrating energy storage resources, including pumpedstorage hydro (PSH), into the electricity markets. However, new challenges arise in modeling and optimizing these energy-limited resources across multiple market clearing processes and planning studies with uncertainties and imperfect information. For instance, current market practices of PSH owners specifying pumping/generating hours can result in sub-optimal generation dispatch. Letting grid operators optimize PSH with the consideration of multiple operating modes and energy limitation constraints can potentially bring economic benefits to both the system and the PSH owners. However, in multi-stage clearing process of electricity markets, utilizing the PSH flexibility to deal with realized uncertainties can cause deviation in the multi-stage scheduling processes. The resulting financial risks from the schedule deviation may not be acceptable to PSH owners. In addition, to effectively utilize this energy limited resource, the state of charge (SOC) constraints of PSH needs to be continuously optimized and the marginal cost of deviation need to reflect the expected cost to purchase or sell energy at future times to compensate for deviations. This project aims to develop a prototype enhanced PSH model and improved price signals in the multi-stage market clearing process with proper consideration of the unique characteristics of PSH, in order to better align underlying PSH capabilities with evolving grid needs, particularly including the needs for more frequent and larger cycling to manage variability and uncertainty from renewables.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Making BREAD: Biomimetic Strategies for Artificial Intelligence Now and in the Future

The Artificial Intelligence (AI) revolution foretold of during the 1960s is well underway in the second decade of the twenty first century. Its period of phenomenal growth likely lies ahead. AI-operated machines and technologies will extend the reach of Homo sapiens far beyond the biological constraints imposed by evolution: outwards further into deep space, as well as inwards into the nano-world of DNA sequences and relevant medical applications. And yet, we believe, there are crucial lessons that biology can offer that will enable a prosperous future for AI. For machines in general, and for AI's especially, operating over extended periods or in extreme environments will require energy usage orders of magnitudes more efficient than exists today. In many operational environments, energy sources will be constrained. The AI's design and function may be dependent upon the type of energy source, as well as its availability and accessibility. Any plans for AI devices operating in a challenging environment must begin with the question of how they are powered, where fuel is located, how energy is stored and made available to the machine, and how long the machine can operate on specific energy units. While one of the key advantages of AI use is to reduce the dimensionality of a complex problem, the fact remains that some energy is required for functionality. Hence, the materials and technologies that provide the needed energy represent a critical challenge toward future use scenarios of AI and should be integrated into their design. Here we look to the brain and other aspects of biology as inspiration for Biomimetic Research for Energy-efficient AI Designs (BREAD).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Resonances in a Chaotic Attractor Crisis of the Lorenz Flow

Local bifurcations of stationary points and limit cycles have successfully been characterized in terms of the critical exponents of these solutions. Lyapunov exponents and their associated covariant Lyapunov vectors have been proposed as tools for supporting the understanding of critical transitions in chaotic dynamical systems. However, it is in general not clear how the statistical properties of dynamical systems change across a boundary crisis during which a chaotic attractor collides with a saddle. This behavior is investigated here for a boundary crisis in the Lorenz flow, for which neither the Lyapunov exponents nor the covariant Lyapunov vectors provide a criterion for the crisis. Instead, the convergence of the time evolution of probability densities to the invariant measure, governed by the semigroup of transfer operators, is expected to slow down at the approach of the crisis. Such convergence is described by the eigenvalues of the generator of this semigroup, which can be divided into two families, referred to as the stable and unstable Ruelle–Pollicott resonances, respectively. The former describes the convergence of densities to the attractor (or escape from a repeller) and is estimated from many short time series sampling the state space. The latter is responsible for the decay of correlations, or mixing, and can be estimated from a long times series, invoking ergodicity. It is found numerically for the Lorenz flow that the stable resonances do approach the imaginary axis during the crisis, as is indicative of the loss of global stability of the attractor. On the other hand, the unstable resonances, and a fortiori the decay of correlations, do not flag the proximity of the crisis, thus questioning the usual design of early warning indicators of boundary crises of chaotic attractors and the applicability of response theory close to such crises.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Regarding the optimization of O1-mode ECRH and the feasibility of EBW startup on NSTX-U

Recently published scenarios for fully non-inductive startup and operation on the National Spherical Torus eXperiment Upgrade (NSTX-U) [Menard J et al 2012 Nucl. Fusion 52 083015] show Electron Cyclotron Resonance Heating (ECRH) as an important component in preparing a target plasma for efficient High Harmonic Fast Wave and Neutral Beam heating. The modelling of the propagation and absorption of EC waves in the evolving plasma is required to define the most effective window of operation, and to optimize the launcher geometry for maximal heating and current drive during this window. Here in this paper, we extend a previous optimization of O1-mode ECRH on NSTX-U to account for the full time-dependent performance of the ECRH using simulations performed with TRANSP. We find that the evolution of the density profile has a prominent role in the optimization by defining the time window of operation, which in certain cases may be a more important metric to compare launcher performance than the average power absorption. This feature cannot be captured by analysis on static profiles, and should be accounted for when optimizing ECRH on any device that operates near the cutoff density. Additionally, the utility of the electron Bernstein wave (EBW) in driving current and generating closed flux surfaces in the early startup phase has been demonstrated on a number of devices. Using standalone GENRAY simulations, we find that efficient EBW current drive is possible on NSTX-U if the injection angle is shifted below the midplane and aimed towards the top half of the vacuum vessel. However, collisional damping of the EBW is projected to be significant, in some cases accounting for up to 97\% of the absorbed EBW power.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Predictive characterization of aging and degradation of reactor materials in extreme environments. Final report, December 20, 2013 - September 20, 2017

Understanding of reactor material behavior in extreme environments is vital not only to the development of new materials for the next generation nuclear reactors, but also to the extension of the operating lifetimes of the current fleet of nuclear reactors. To this end, this project conducted a suite of unique experimental techniques, augmented by a mesoscale computational framework, to understand and predict the long-term effects of irradiation, temperature, and stress on material microstructures and their macroscopic behavior. The experimental techniques and computational tools were demonstrated on two distinctive types of reactor materials, namely, Zr alloys and high-Cr martensitic steels. These materials are chosen as the test beds because they are the archetypes of high-performance reactor materials (cladding, wrappers, ducts, pressure vessel, piping, etc.). To fill the knowledge gaps, and to meet the technology needs, a suite of innovative in situ transmission electron microscopy (TEM) characterization techniques (heating, heavy ion irradiation, He implantation, quantitative small-scale mechanical testing, and various combinations thereof) were developed and used to elucidate and map the fundamental mechanisms of microstructure evolution in both Zr and Cr alloys for a wide range environmental boundary conditions in the thermal-mechanical-irradiation input space. Knowledge gained from the experimental observations of the active mechanisms and the role of local microstructural defects on the response of the material has been incorporated into a mathematically rigorous and comprehensive three-dimensional mesoscale framework capable of accounting for the compositional variation, microstructural evolution and localized deformation (radiation damage) to predict aging and degradation of key reactor materials operating in extreme environments. Predictions from this mesoscale framework were compared with the in situ TEM observations to validate the model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Learning Distributed Geometric Koopman Operator for Sparse Networked Dynamical Systems

Koopman operator theory provides an alternative to study nonlinear networked dynamical systems by mapping the state space to an abstract higher dimensional space where the system evolution is linear. Recent works show the application of graph neural networks (GNNs) to learn state to object-centric embeddings and achieve centralized block-wise computation of Koopman operator (KO) under additional assumptions on the underlying agents properties and constraints on the KO structure. However, the computational complexity of learning the Koopman increases exponentially for networked systems where the number of possible system states grows in a combinatorial fashion with the number of nodes. The learning challenge is further amplified for sparse networks by two factors: 1) sample sparsity for learning the Koopman operator in the non-linear space, and 2) the divergence in the dynamics of individual nodes or from one subgraph to another. Our work aims to address these challenge by formulating the representation learning of networked dynamical systems into a multi-agent paradigm and learning the Koopman operator in a distributive manner. The computational as well as performance advantages of distributed Koopman is predominant for sparse networks whereas for fully connected networks, it is shown to coincide with the centralized one. The empirical study on rope system, network of oscillators and a synthetic power system show comparable and superior performance along with computational benefits with the state-of-the-art methods.

Mukherjee, Sayak↗
DOE OSTI2015

PARALLEL EVOLUTION OF QUASI-SEPARATRIX LAYERS AND ACTIVE REGION UPFLOWS

Persistent plasma upflows were observed with Hinode’s EUV Imaging Spectrometer (EIS) at the edges of active region (AR) 10978 as it crossed the solar disk. We analyze the evolution of the photospheric magnetic and velocity fields of the AR, model its coronal magnetic field, and compute the location of magnetic null-points and quasi-sepratrix layers (QSLs) searching for the origin of EIS upflows. Magnetic reconnection at the computed null points cannot explain all of the observed EIS upflow regions. However, EIS upflows and QSLs are found to evolve in parallel, both temporarily and spatially. Sections of two sets of QSLs, called outer and inner, are found associated to EIS upflow streams having different characteristics. The reconnection process in the outer QSLs is forced by a large-scale photospheric flow pattern, which is present in the AR for several days. We propose a scenario in which upflows are observed, provided that a large enough asymmetry in plasma pressure exists between the pre-reconnection loops and lasts as long as a photospheric forcing is at work. A similar mechanism operates in the inner QSLs; in this case, it is forced by the emergence and evolution of the bipoles between the two main AR polarities. Our findings provide strong support for the results from previous individual case studies investigating the role of magnetic reconnection at QSLs as the origin of the upflowing plasma. Furthermore, we propose that persistent reconnection along QSLs does not only drive the EIS upflows, but is also responsible for the continuous metric radio noise-storm observed in AR 10978 along its disk transit by the Nançay Radio Heliograph.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The End of Galaxy Surveys

For nearly a century, imaging and spectroscopic surveys of galaxies have given us information about the contents of the universe. We attempt to define the logical end point of such surveys by defining not the next galaxy survey but rather the final galaxy survey at near-infrared wavelengths; this would be the galaxy survey that exhausts the information content useful for addressing extant questions. Such a survey would require incredible advances in a number of technologies, and the survey details will depend on the as yet poorly constrained properties of the earliest galaxies. Using an exposure time calculator, we define nominal surveys for extracting the useful information for three science cases: dark energy cosmology, galaxy evolution, and supernovae (SN). We define scaling relations that trade off sky background, telescope aperture, and focal plane size to allow for a survey of a given depth over a given area. For optimistic assumptions, a 280 m telescope with a marginally resolved focal plane of 20 deg 2 operating at L2 could potentially exhaust the cosmological information content of galaxies in a 10 yr survey. For galaxy evolution (making use of gravitational lensing to magnify the earliest galaxies) and SN, the same telescope would suffice. We discuss the technological advances needed to complete the last galaxy survey. While the final galaxy survey remains well outside of our technical reach today, we present scaling relations that show how we can progress toward the goal of exhausting the information content encoded in the shapes, positions, and colors of galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

FutureTense

Protective vaccines and reliable diagnostics are essential tools for controlling viral diseases. However, the efficacy of these tools can be diminished by mutations in viral genomes. The delay between the emergence of new viral strains and the redesign of vaccines and diagnostics allows for continued viral transmission. Is it possible to address this challenge by computationally predicting viral genome sequence evolution? Can we “future-proof” vaccines and diagnostics by targeting both current and anticipated future sequence variants? While predicting viral evolution is still an unsolved, “grand challenge” problem in biology, the large, and rapidly growing, number of SARS-CoV-2 genome sequences provide an opportunity to quantify the ability of machine learning to predict viral genome sequence evolution. Towards this end, we have developed a simple computational model for predicting viral evolution at the level of individual nucleotides. The key metric for quantifying the per-base, prediction accuracy for viral evolution is the Mann-Whitney U statistic (or, equivalently, the area under the receiver operator curve). Since the Mann-Whitney U statistic is not a differentiable function, existing deep leaning packages (like Pytorch and Keras/TensorFlow) are not useful, as they require that the accuracy metric/objective function be analytically differentiable with respect to the model parameters. To overcome this challenge, we have implemented custom software, “FutureTense”, that can train a machine learning model by maximizing the non-differentiable Mann-Whitney U statistic. This software trains a machine learning model by exploring along the direction of the discrete gradient of the Mann-Whitney U statistic in the model parameter space. Parallel computing and genome sequence-specific optimizations are used to accelerate model training. The resulting machine learning model learns the observed high C->U mutation rates in the SARS-CoV-2 genome (which are potentially induced by host defenses) and provides prediction accuracies that are significantly better than one would expect from random chance. While predicting viral evolution is still quite far from a solved problem, the surprising performance of this simple model gives hope that the accuracy of predicting viral genome evolution can be further increased by more sophisticated approaches.

Gans, Jason↗
DOE OSTI2016

Evolution of deep-bed filtration of engine exhaust particulates with trapped mass

Micro-scale filtration experiments were performed on cordierite filter samples using particulate matter (PM) generated by a spark-ignition direct-injection (SIDI) engine fueled with tier II EEE certification gasoline. Size-resolved mass and number concentrations were obtained from several engine operating conditions. The resultant mass-mobility relationships showed weak dependence on the operating condition. An integrated particle size distribution (IPSD) method was used estimate the PM mass concentration in the exhaust stream from the SIDI engine and a heavy duty diesel (HDD) engine. The average estimated mass concentration between all conditions was ~77****** % of the gravimetric measurements performed on Teflon filters. Despite the relatively low elemental carbon fraction (~0.4 to 0.7), the IPSD mass for stoichiometric SIDI exhaust was ~83±38 % of the gravimetric measurement. Identical cordierite filter samples with properties representative of diesel particulate filters were sequentially loaded with PM from the different SIDI engine operating conditions, in order of increasing PM mass concentration. Simultaneous particle size distribution measurements upstream and downstream of the filter sample were used to evaluate filter performance evolution and the instantaneous trapped mass within the filter for two different filter face velocities. The evolution of filtration performance for the different samples was sensitive only to trapped mass, despite using PM from a wide range of operating conditions. Higher filtration velocity resulted in a more rapid shift in the most penetrating particle size towards smaller mobility diameters.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Environmental and Operational Performance of CO2-EOR as a CCUS Technology: A Cranfield Example with Dynamic LCA Considerations

This study evaluates the potential of carbon dioxide-enhanced oil recovery (CO2-EOR) to reduce greenhouse gas emissions without compromising oil production goals. A novel, dynamic carbon lifecycle analysis (d-LCA) was developed and used to understand the evolution of the environmental impact (CO2 emissions) and mitigation (geologic CO2 storage) associated with an expanded carbon capture, utilization and storage (CCUS) system, from start to closure of operations. EOR operational performance was assessed through CO2 utilization rates, which relate usage of CO2 to oil production. Because field operational strategies have a significant impact on reservoir engineering parameters that affect both CO2 storage and oil production (e.g., sweep efficiency, flood conformance, fluid saturation distribution), we conducted a scenario analysis that assessed the operational and environmental performance of four common and novel CO2-EOR field development strategies. Each scenario was evaluated with and without stacked saline carbon storage, an EOR/storage combination strategy where excess CO2 from the recycling facility is injected into an underlying saline aquifer for long-term carbon storage. The dynamic interplay between operational and environmental performance formed the basis of our CCUS technology analysis. The results showed that all CO2-EOR evaluated scenarios start operating with a negative carbon footprint and, years into the project, transitioned into operating with a positive carbon footprint. The transition points were significantly different in each scenario. Water-alternating-gas (WAG) was identified as the CO2 injection strategy with the highest potential to co-optimize EOR and carbon storage goals. The results provide an understanding of the evolution of the system’s net carbon balance in all four field development strategies studied. The environmental performance can be significantly improved with stacked storage, where a negative carbon footprint can be maintained throughout the life of the operation in most of the injection scenarios modelled. This information will be useful to CO2-EOR operators seeking value in storing more CO2 through a carbon credit program (e.g., the 45Q carbon credit program in the USA). Most importantly, this study serves as confirmation that CO2-EOR can be operationally designed to both enhance oil production and reduce greenhouse gas emissions into the atmosphere.

58 GEOSCIENCES↗
DOE OSTI2015

FAST MAGNETIC FIELD AMPLIFICATION IN THE EARLY UNIVERSE: GROWTH OF COLLISIONLESS PLASMA INSTABILITIES IN TURBULENT MEDIA

In this work we report on a numerical study of the cosmic magnetic field amplification due to collisionless plasma instabilities. The collisionless magnetohydrodynamic equations derived account for the pressure anisotropy that leads, in specific conditions, to the firehose and mirror instabilities. We study the time evolution of seed fields in turbulence under the influence of such instabilities. An approximate analytical time evolution of the magnetic field is provided. The numerical simulations and the analytical predictions are compared. We found that (i) amplification of the magnetic field was efficient in firehose-unstable turbulent regimes, but not in the mirror-unstable models; (ii) the growth rate of the magnetic energy density is much faster than the turbulent dynamo; and (iii) the efficient amplification occurs at small scales. The analytical prediction for the correlation between the growth timescales and pressure anisotropy is confirmed by the numerical simulations. These results reinforce the idea that pressure anisotropies—driven naturally in a turbulent collisionless medium, e.g., the intergalactic medium, could efficiently amplify the magnetic field in the early universe (post-recombination era), previous to the collapse of the first large-scale gravitational structures. This mechanism, though fast for the small-scale fields (∼kpc scales), is unable to provide relatively strong magnetic fields at large scales. Other mechanisms that were not accounted for here (e.g., collisional turbulence once instabilities are quenched, velocity shear, or gravitationally induced inflows of gas into galaxies and clusters) could operate afterward to build up large-scale coherent field structures in the long time evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Noise-resistant Landau-Zener sweeps from geometrical curves

Landau-Zener physics is often exploited to generate quantum logic gates and to perform state initialization and readout. The quality of these operations can be degraded by noise fluctuations in the energy gap at the avoided crossing. We leverage a recently discovered correspondence between qubit evolution and space curves in three dimensions to design noise-robust Landau-Zener sweeps through an avoided crossing. In the case where the avoided crossing is purely noise-induced, we prove that operations based on monotonic sweeps cannot be robust to noise. Hence, we design families of phase gates based on non-monotonic drives that are error-robust up to second order. In the general case where there is an avoided crossing even in the absence of noise, we present a general technique for designing robust driving protocols that takes advantage of a relationship between the Landau-Zener problem and space curves of constant torsion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗