Stanek, Lucas J.; Hansen, Stephanie B.; Kononov, Alina K.; Cochrane, Kyle C.; Clay III, Raymond C.; Townsend, Joshua P.; Dumi, Amanda; Lentz, Meghan; Melton, Cody A.; Baczewski, Andrew D.; Knapp, Patrick F.; Haines, Brian M.; Hu, S.X.; Murillo, Michael S.; Stanton, Liam G.; Whitley, Heather D.; Baalrud, Scott D.; Babati, Lucas J.; Bethkenhagen, Mandy; Blanchet, Augustin; Collins, Lee A.; Faussurier, Gerald; French, Martin; Johnson, Zachary A.; Karasiev, Valentin V.; Kumar, Shashikant; Nichols, Katarina A.; Petrov, George M.; Recoules, Vanina; Redmer, Ronald; Ropke, Gerd; Schorner, Maximilian; Shaffer, Nathaniel R.; Sharma, Vidushi; Silvestri, Luciano G.; Soubiran, Francois; Suryanarayana, Phanish; Tacu, Mikael; White, Alexander J.
We report the results of the second charged-particle transport coefficient code comparison workshop, which was held in Livermore, California on 24-27 July 2023. This workshop gathered theoretical, computational, and experimental scientists to assess the state of computational and experimental techniques for understanding charged-particle transport coefficients relevant to high-energy-density plasma science. Data for electronic and ionic transport coefficients, namely, the direct current electrical conductivity, electron thermal conductivity, ion shear viscosity, and ion thermal conductivity were computed and compared for multiple plasma conditions. Additional comparisons were carried out for electron-ion properties such as the electron-ion equilibration time and alpha particle stopping power. Overall, 39 participants submitted calculated results from 18 independent approaches, spanning methods from parameterized semi-empirical models to time-dependent density functional theory. In the cases studied here, we find significant differences—several orders of magnitude—between approaches, particularly at lower temperatures, and smaller differences—roughly a factor of five—among first-principles models. We investigate the origins of these differences through comparisons of underlying predictions of ionic and electronic structure. The results of this workshop help to identify plasma conditions where computationally inexpensive approaches are accurate, where computationally expensive models are required, and where experimental measurements will have high impact.
Real-time time-dependent density functional theory (TDDFT) is presently the most accurate available method for computing electronic stopping powers from first principles. However, obtaining application-relevant results often involves either costly averages over multiple calculations or ad hoc selection of a representative ion trajectory. We consider a broadly applicable, quantitative metric for evaluating and optimizing trajectories in this context. This methodology enables rigorous analysis of the failure modes of various common trajectory choices in crystalline materials. Although randomly selecting trajectories is common practice in stopping power calculations in solids, we show that nearly 30% of random trajectories in an FCC aluminum crystal will not representatively sample the material over the time and length scales feasibly simulated with TDDFT, and unrepresentative choices incur errors of up to 60%. We also show that finite-size effects depend on ion trajectory via “ouroboros” effects beyond the prevailing plasmon-based interpretation, and we propose a cost-reducing scheme to obtain converged results even when expensive core-electron contributions preclude large supercells. This work helps to mitigate poorly controlled approximations in first-principles stopping power calculations, allowing 1–2 order of magnitude cost reductions for obtaining representatively averaged and converged results.
Recent work on atomic-precision dopant incorporation technologies has led to the creation of both boron and aluminum δ -doped layers in silicon with densities above the solid solubility limit. We use density functional theory to predict the band structure and effective mass values of such δ layers, first modeling them as ordered supercells. Structural relaxation is found to have a significant impact on the impurity band energies and effective masses of the boron layers, but not the aluminum layers. However, disorder in the δ layers is found to lead to a significant flattening of the bands in both cases. We calculate the local density of states and doping potential for these δ -doped layers, demonstrating that their influence is highly localized with spatial extents at most 4 nm. We conclude that acceptor δ -doped layers exhibit different electronic structure features dependent on both the dopant atom and spatial ordering. This suggests prospects for controlling the electronic properties of these layers if the local details of the incorporation chemistry can be fine-tuned.
A large body of work has demonstrated that parameterized artificial neural networks (ANNs) can efficiently describe ground states of numerous interesting quantum many-body Hamiltonians. However, the standard variational algorithms used to update or train the ANN parameters can get trapped in local minima, especially for frustrated systems and even if the representation is sufficiently expressive. We propose a parallel tempering method that facilitates escape from such local minima. This methods involves training multiple ANNs independently, with each simulation governed by a Hamiltonian with a different “driver” strength, in analogy to quantum parallel tempering, and it incorporates an update step into the training that allows for the exchange of neighboring ANN configurations. We study instances from two classes of Hamiltonians to demonstrate the utility of our approach using Restricted Boltzmann Machines as our parameterized ANN. The first instance is based on a permutation-invariant Hamiltonian whose landscape stymies the standard training algorithm by drawing it increasingly to a false local minimum. The second instance is four hydrogen atoms arranged in a rectangle, which is an instance of the second quantized electronic structure Hamiltonian discretized using Gaussian basis functions. We study this problem in a minimal basis set, which exhibits false minima that can trap the standard variational algorithm despite the problem’s small size. We show that augmenting the training with quantum parallel tempering becomes useful to finding good approximations to the ground states of these problem instances.
Atomic-precision advanced manufacturing enables unique silicon quantum electronics built on quantum dots fabricated from small numbers of phosphorus dopants. The number of dopant atoms comprising a dot plays a central role in determining the behavior of charge and spin confined to the dots and thus overall device performance. In this work, we use both theoretical and experimental techniques to explore the combined impact of lithographic variation and stochastic kinetics on the number of P incorporations in quantum dots made using these techniques and how this variation changes as a function of the size of the dot. Using a kinetic model of PH3 dissociation augmented with novel reaction barriers, we demonstrate that for a 2 × 3 silicon dimer window the probability that no donor incorporates goes to zero, allowing for certainty in the placement of at least one donor. However, this still comes with some uncertainty in the precise number of incorporated donors (either one or two), and this variability may still impact certain applications. We also examine the impact of the size of the initial lithographic window, finding that the incorporation fraction saturates to δ-layer-like coverage as the circumference-to-area ratio decreases. We predict that this incorporation fraction depends strongly on the dosage of the precursor and that the standard deviation of the number of incorporations scales as ∼√n, as would be expected for a sequence of largely independent incorporation events. Finally, we characterize an array of 36 experimentally prepared multidonor 3 × 3 nm lithographic windows with scanning tunneling microscopy, measuring the fidelity of the lithography to the desired array and the final location of PHx fragments within these lithographic windows. We use our kinetic model to examine the expected variability due to the observed lithographic error, predicting a negligible impact on incorporation statistics. We find good agreement between our model and the inferred incorporation locations in these windows from scanning tunneling microscope measurements.
Abstract: Due to a beneficial balance of computational cost and accuracy, real-time time-dependent density-functional theory has emerged as a promising first-principles framework to describe electron real-time dynamics. Here we discuss recent implementations around this approach, in particular in the context of complex, extended systems. Results include an analysis of the computational cost associated with numerical propagation and when using absorbing boundary conditions. We extensively explore the shortcomings for describing electron–electron scattering in real time and compare to many-body perturbation theory. Modern improvements of the description of exchange and correlation are reviewed. In this work, we specifically focus on the Qb@ll code, which we have mainly used for these types of simulations over the last years, and we conclude by pointing to further progress needed going forward. Graphical abstract: [Figure not available: see fulltext.].
The extreme sensitivity of 2D materials to defects and nanostructure requires precise imaging techniques to verify presence of desirable and absence of undesirable features in the atomic geometry. Helium-ion beams have emerged as a promising materials imaging tool, achieving up to 20 times higher resolution and 10 times larger depth-of-field than conventional or environmental scanning electron microscopes. Here, we offer first-principles theoretical insights to advance ion-beam imaging of atomically thin materials by performing real-time time-dependent density functional theory simulations of single impacts of 10-200 keV light ions in free-standing graphene. We predict that detecting electrons emitted from the back of the material (the side from which the ion exits) would result in up to three times higher signal and up to five times higher contrast images, making 2D materials especially compelling targets for ion-beam microscopy. This predicted superiority of exit-side emission likely arises from anisotropic kinetic emission. The charge induced in the graphene equilibrates on a sub-fs time scale, leading to only slight disturbances in the carbon lattice that are unlikely to damage the atomic structure for any of the beam parameters investigated here.
Predictive design of REHEDS experiments with radiation-hydrodynamic simulations requires knowledge of material properties (e.g. equations of state (EOS), transport coefficients, and radiation physics). Interpreting experimental results requires accurate models of diagnostic observables (e.g. detailed emission, absorption, and scattering spectra). In conditions of Local Thermodynamic Equilibrium (LTE), these material properties and observables can be pre-computed with relatively high accuracy and subsequently tabulated on simple temperature-density grids for fast look-up by simulations. When radiation and electron temperatures fall out of equilibrium, however, non-LTE effects can profoundly change material properties and diagnostic signatures. Accurately and efficiently incorporating these non-LTE effects has been a longstanding challenge for simulations. At present, most simulations include non-LTE effects by invoking highly simplified inline models. These inline non-LTE models are both much slower than table look-up and significantly less accurate than the detailed models used to populate LTE tables and diagnose experimental data through post-processing or inversion. Because inline non-LTE models are slow, designers avoid them whenever possible, which leads to known inaccuracies from using tabular LTE. Because inline models are simple, they are inconsistent with tabular data from detailed models, leading to ill-known inaccuracies, and they cannot generate detailed synthetic diagnostics suitable for direct comparisons with experimental data. This project addresses the challenge of generating and utilizing efficient, accurate, and consistent non-equilibrium material data along three complementary but relatively independent research lines. First, we have developed a relatively fast and accurate non-LTE average-atom model based on density functional theory (DFT) that provides a complete set of EOS, transport, and radiative data, and have rigorously tested it against more sophisticated first-principles multi-atom DFT models, including time-dependent DFT. Next, we have developed a tabular scheme and interpolation methods that compactly capture non-LTE effects for use in simulations and have implemented these tables in the GORGON magneto-hydrodynamic (MHD) code. Finally, we have developed post-processing tools that use detailed tabulated non-LTE data to directly predict experimental observables from simulation output.
Stochastic incorporation kinetics can be a limiting factor in the scalability of semiconductor fabrication technologies using atomic-precision techniques. While these technologies have recently been extended from donors to acceptors, the extent to which kinetics will impact single-acceptor incorporation has yet to be assessed. To identify the precursor molecule and dosing conditions that are promising for deterministic incorporation, we develop and apply an atomistic model for the single-acceptor incorporation rates of several recently demonstrated molecules: diborane (B2H6), boron trichloride (BCl3), and aluminum trichloride in both monomer (AlCl3) and dimer forms (Al2Cl6). While all three precursors can realize single-acceptor incorporation, we predict that diborane is unlikely to realize deterministic incorporation, boron trichloride can realize deterministic incorporation with modest heating (50 °C), and aluminum trichloride can realize deterministic incorporation at room temperature. We conclude that both boron and aluminum trichloride are promising precursors for atomic-precision single-acceptor applications, with the potential to enable the reliable production of large arrays of single-atom quantum devices.
Nuclear spins were among the first physical platforms to be considered for quantum information processing1,2, because of their exceptional quantum coherence3 and atomic-scale footprint. However, their full potential for quantum computing has not yet been realized, owing to the lack of methods with which to link nuclear qubits within a scalable device combined with multi-qubit operations with sufficient fidelity to sustain fault-tolerant quantum computation. Here we demonstrate universal quantum logic operations using a pair of ion-implanted 31P donor nuclei in a silicon nanoelectronic device. A nuclear two-qubit controlled-Z gate is obtained by imparting a geometric phase to a shared electron spin4, and used to prepare entangled Bell states with fidelities up to 94.2(2.7)%. The quantum operations are precisely characterized using gate set tomography (GST)5, yielding one-qubit average gate fidelities up to 99.95(2)%, two-qubit average gate fidelity of 99.37(11)% and two-qubit preparation/measurement fidelities of 98.95(4)%. These three metrics indicate that nuclear spins in silicon are approaching the performance demanded in fault-tolerant quantum processors6. We then demonstrate entanglement between the two nuclei and the shared electron by producing a Greenberger–Horne–Zeilinger three-qubit state with 92.5(1.0)% fidelity. Because electron spin qubits in semiconductors can be further coupled to other electrons7–9 or physically shuttled across different locations10,11, these results establish a viable route for scalable quantum information processing using donor nuclear and electron spins.
Atomically precise ultradoping of silicon is possible with atomic resists, area-selective surface chemistry, and a limited set of hydride and halide precursor molecules, in a process known as atomic precision advanced manufacturing (APAM). It is desirable to expand this set of precursors to include dopants with organic functional groups and here we consider aluminium alkyls, to expand the applicability of APAM. We explore the impurity content and selectivity that results from using trimethyl aluminium and triethyl aluminium precursors on Si(001) to ultradope with aluminium through a hydrogen mask. Comparison of the methylated and ethylated precursors helps us understand the impact of hydrocarbon ligand selection on incorporation surface chemistry. Combining scanning tunneling microscopy and density functional theory calculations, we assess the limitations of both classes of precursor and extract general principles relevant to each.
We demonstrate the ability to fabricate vertically stacked Si quantum dots (QDs) within SiGe nanowires with QD diameters down to 2 nm. These QDs are formed during high-temperature dry oxidation of Si/SiGe heterostructure pillars, during which Ge diffuses along the pillars' sidewalls and encapsulates the Si layers. Continued oxidation results in QDs with sizes dependent on oxidation time. The formation of a Ge-rich shell that encapsulates the Si QDs is observed, a configuration which is confirmed to be thermodynamically favorable with molecular dynamics and density functional theory. The type-II band alignment of the Si dot/SiGe pillar suggests that charge trapping on the Si QDs is possible, and electron energy loss spectra show that a conduction band offset of at least 200 meV is maintained for even the smallest Si QDs. Our approach is compatible with current Si-based manufacturing processes, offering a new avenue for realizing Si QD devices.
This project sought to develop a fundamental understanding of the mechanisms underlying a newly observed enhanced germanium (Ge) diffusion process in silicon germanium (SiGe) semiconductor nanostructures during thermal oxidation. Using a combination of oxidationdiffusion experiments, high resolution imaging, and theoretical modeling, a model for the enhanced Ge diffusion mechanism was proposed. Additionally, a nanofabrication approach utilizing this enhanced Ge diffusion mechanism was shown to be applicable to arbitrary 3D shapes, leading to the fabrication of stacked silicon quantum dots embedded in SiGe nanopillars. A new wet etch-based method for preparing 3D nanostructures for highresolution imaging free of obscuring material or damage was also developed. These results enable a new method for the controlled and scalable fabrication of on-chip silicon nanostructures with sub-10 nm dimensions needed for next generation microelectronics, including low energy electronics, quantum computing, sensors, and integrated photonics.
While it is likely practically a bad idea to shrink a transistor to the size of an atom, there is no arguing that it would be fantastic to have atomic-scale control over every aspect of a transistor – a kind of crystal ball to understand and evaluate new ideas. This project showed that it was possible to take a niche technique used to place dopants in silicon with atomic precision and apply it broadly to study opportunities and limitations in microelectronics. In addition, it laid the foundation to attaining atomic-scale control in semiconductor manufacturing more broadly.
A materials synthesis method that we call atomic-precision advanced manufacturing (APAM), which is the only known route to tailor silicon nanoelectronics with full 3D atomic precision, is making an impact as a powerful prototyping tool for quantum computing. Quantum computing schemes using atomic (31P) spin qubits are compelling for future scale-up owing to long dephasing times, one- and two-qubit gates nearing high-fidelity thresholds for fault-tolerant quantum error correction, and emerging routes to manufacturing via proven Si foundry techniques. Multiqubit devices are challenging to fabricate by conventional means owing to tight interqubit pitches forced by short-range spin interactions, and APAM offers the required (Å-scale) precision to systematically investigate solutions. However, applying APAM to fabricate circuitry with increasing numbers of qubits will require significant technique development. Here, we provide a tutorial on APAM techniques and materials and highlight its impacts in quantum computing research. Finally, we describe challenges on the path to multiqubit architectures and opportunities for APAM technique development. Graphic Abstract: [Figure not available: see fulltext.]
The adsorption of AlCl3 on Si(100) and the effect of annealing the AlCl3-dosed substrate were studied to reveal key surface processes for the development of atomic-precision, acceptor-doping techniques. This investigation was performed via scanning tunneling microscopy (STM), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT) calculations. At room temperature, AlCl3 readily adsorbed to the Si substrate dimers and dissociated to form a variety of species. Annealing the AlCl3-dosed substrate at temperatures below 450 °C produced unique chlorinated aluminum chains (CACs) elongated along the Si(100) dimer row direction. An atomic model for the chains is proposed with supporting DFT calculations. Al was incorporated into the Si substrate upon annealing at 450 °C and above, and Cl desorption was observed for temperatures beyond 450 °C. Al-incorporated samples were encapsulated in Si and characterized by secondary ion mass spectrometry (SIMS) depth profiling to quantify the Al atom concentration, which was found to be in excess of 1020 cm-3 across a ∼2.7 nm-thick δ-doped region. The Al concentration achieved here and the processing parameters utilized promote AlCl3 as a viable gaseous precursor for novel acceptor-doped Si materials and devices for quantum computing.
We adapt the robust phase estimation algorithm to the evaluation of energy differences between two eigenstates using a quantum computer. This approach does not require controlled unitaries between auxiliary and system registers or even a single auxiliary qubit. As a proof of concept, we calculate the energies of the ground state and low-lying electronic excitations of a hydrogen molecule in a minimal basis on a cloud quantum computer. The denominative robustness of our approach is then quantified in terms of a high tolerance to coherent errors in the state preparation and measurement. Conceptually, we note that all quantum phase estimation algorithms ultimately evaluate eigenvalue differences.
We present an extension to the robust phase estimation protocol, which can identify incorrect results that would otherwise lie outside the expected statistical range. Robust phase estimation is increasingly a method of choice for applications such as estimating the effective process parameters of noisy hardware, but its robustness is dependent on the noise satisfying certain threshold assumptions. We provide consistency checks that can indicate when those thresholds have been violated, which can be difficult or impossible to test directly. We test these consistency checks for several common noise models, and identify two possible checks with high accuracy in locating the point in a robust phase estimation run at which further estimates should not be trusted. One of these checks may be chosen based on resource availability, or they can be used together in order to provide additional verification.
Ramakrishna, Kushal; Cangi, Attila; Dornheim, Tobias; Baczewski, Andrew D.; Vorberger, Jan
The theoretical understanding of plasmon behavior is crucial for an accurate interpretation of inelastic scattering diagnostics in many experiments. We highlight the utility of linear response time-dependent density functional theory (LR-TDDFT) as a first-principles framework for consistently modeling plasmon properties. We provide a comprehensive analysis of plasmons in aluminum from ambient to warm dense matter conditions and assess typical properties such as the dynamical structure factor, the plasmon dispersion, and the plasmon lifetime. We compare our results with scattering measurements and with other TDDFT results as well as models such as the random phase approximation, the Mermin approach, and the dielectric function obtained using static local field corrections of the uniform electron gas parametrized from path-integral Monte Carlo simulations. We conclude that results for the plasmon dispersion and lifetime are inconsistent between experiment and theories and that the common practice of extracting and studying plasmon dispersion relations is an insufficient procedure to capture the complicated physics contained in the dynamic structure factor in its full breadth.
Diborane (B2H6) is a promising molecular precursor for atomic precision p-type doping of silicon that has recently been experimentally demonstrated [ Škereň et al. Nat. Electron. 2020 ]. We use density functional theory (DFT) calculations to determine the reaction pathway for diborane dissociating into a species that will incorporate as electrically active substitutional boron after adsorbing onto the Si(100)-2×1 surface. Our calculations indicate that diborane must overcome an energy barrier to adsorb, explaining the experimentally observed low sticking coefficient (<1 × 10-4 at room temperature) and suggesting that heating can be used to increase the adsorption rate. Upon sticking, diborane has an ≈50% chance of splitting into two BH3 fragments versus merely losing hydrogen to form a dimer such as B2H4. As boron dimers are likely electrically inactive, whether this latter reaction occurs is shown to be predictive of the incorporation rate. The dissociation process proceeds with significant energy barriers, necessitating the use of high temperatures for incorporation. Using the barriers calculated from DFT, we parameterize a Kinetic Monte Carlo model that predicts the incorporation statistics of boron as a function of the initial depassivation geometry, dose, and anneal temperature. Our results suggest that the dimer nature of diborane inherently limits its doping density as an acceptor precursor and furthermore that heating the boron dimers to split before exposure to silicon can lead to poor selectivity on hydrogen and halogen resists. This suggests that, while diborane works as an atomic precision acceptor precursor, other non-dimerized acceptor precursors may lead to higher incorporation rates at lower temperatures.
The attachment of dopant precursor molecules to depassivated areas of hydrogen-terminated silicon templated with a scanning tunneling microscope (STM) has been used to create electronic devices with subnanometer precision, typically for quantum physics experiments. This process, which we call atomic precision advanced manufacturing (APAM), dopes silicon beyond the solid-solubility limit and produces electrical and optical characteristics that may also be useful for microelectronic and plasmonic applications. However, scanned probe lithography lacks the throughput required to develop more sophisticated applications. Here, we demonstrate and characterize an APAM device workflow where scanned probe lithography of the atomic layer resist has been replaced by photolithography. An ultraviolet laser is shown to locally and controllably heat silicon above the temperature required for hydrogen depassivation on a nanosecond timescale, a process resistant to under- and overexposure. STM images indicate a narrow range of energy density where the surface is both depassivated and undamaged. Modeling that accounts for photothermal heating and the subsequent hydrogen desorption kinetics suggests that the silicon surface temperatures reached in our patterning process exceed those required for hydrogen removal in temperature-programmed desorption experiments. A phosphorus-doped van der Pauw structure made by sequentially photodepassivating a predefined area and then exposing it to phosphine is found to have a similar mobility and higher carrier density compared with devices patterned by STM. Lastly, it is also demonstrated that photodepassivation and precursor exposure steps may be performed concomitantly, a potential route to enabling APAM outside of ultrahigh vacuum.
Analog quantum simulation is an approach for studying physical systems that might otherwise be computationally intractable to simulate on classical high-performance computing (HPC) systems. The key idea behind analog quantum simulation is the realization of a physical system with a low-energy effective Hamiltonian that is the same as the low-energy effective Hamiltonian of some target system to be studied. Purpose-built nanoelectronic devices are a natural candidate for implementing the analog quantum simulation of strongly correlated materials that are otherwise challenging to study using classical HPC systems. However, realizing devices that are sufficiently large to study the properties of a non-trivial material system (e.g., those described by a Fermi-Hubbard model) will eventually require the fabrication, control, and measurement of at least 0(10) quantum dots, or other engineered quantum impurities. As a step toward large-scale analog or digital quantum simulation platforms based on nanoelectronic devices, we propose a new approach to analog quantum simulation that makes use of the large Hilbert space dimension of the electronic baths that are used to adjust the occupancy of one or a few engineered quantum impurities. This approach to analog quantum simulation allows us to study a wide array of quantum impurity models. We can further augment the computational power of such an approach by combining it with a classical computer to facilitate dynamical mean-field theory (DMFT) calculations. DMFT replaces the solution of a lattice impurity problem with the solution of a family of localized impurity problems with bath couplings that are adjusted to satisfy a self-consistency condition between the two models. In DMFT, the computationally challenging task is the high-accuracy solution of an instance of a quantum impurity model that is determined self-consistently in coordination with a mean-field calculation. We propose using one or a few engineered quantum impurities with adjustable couplings to baths to realize an analog quantum coprocessor that effects the solution of such a model through measurements of a physical quantum impurity, operating in coordination with a classical computer to achieve a self-consistent solution to a DMFT calculation. We focus on implementation details relevant to a number of technologies for which Sandia has design, fabrication, and measurement expertise. The primary technical advances outlined in this report concern the development of a supporting modeling capability. As with all analog quantum simulation platforms, the successful design and operation of individual devices depends critically on one's ability to predict the effective low-energy Hamiltonian governing its dynamics Our project has made this possible and lays the foundation for future experimental implementations.
Atomic precision advanced manufacturing (APAM) offers creation of donor devices in an atomically thin layer doped beyond the solid solubility limit, enabling unique device physics. This presents an opportunity to use APAM as a pathfinding platform to investigate digital electronics at the atomic limit. Scaling to smaller transistors is increasingly difficult and expensive, necessitating the investigation of alternative fabrication paths that extend to the atomic scale. APAM donor devices can be created using a scanning tunneling microscope (STM). However, these devices are not currently compatible with industry standard fabrication processes. There exists a tradeoff between low thermal budget (LT) processes to limit dopant diffusion and high thermal budget (HT) processes to grow defect-free layers of epitaxial Si and gate oxide. To this end, we have developed an LT epitaxial Si cap and LT deposited Al2O3 gate oxide integrated with an atomically precise single-electron transistor (SET) that we use as an electrometer to characterize the quality of the gate stack. The surface-gated SET exhibits the expected Coulomb blockade behavior. However, the gate’s leverage over the SET is limited by defects in the layers above the SET, including interfaces between the Si and oxide, and structural and chemical defects in the Si cap. We propose a more sophisticated gate stack and process flow that is predicted to improve performance in future atomic precision devices.
The attachment of dopant precursor molecules to depassivated areas of hydrogen-terminated silicon templated with a scanning tunneling microscope (STM) has been used to create electronic devices with sub-nanometer precision, typically for quantum physics demonstrations, and to dope silicon past the solid-solubility limit, with potential applications in microelectronics and plasmonics. However, this process, which we call atomic precision advanced manufacturing (APAM), currently lacks the throughput required to develop sophisticated applications because there is no proven scalable hydrogen lithography pathway. Here, we demonstrate and characterize an APAM device workflow where STM lithography has been replaced with photolithography. An ultraviolet laser is shown to locally heat silicon controllably above the temperature required for hydrogen depassivation. STM images indicate a narrow range of laser energy density where hydrogen has been depassivated, and the surface remains well-ordered. A model for photothermal heating of silicon predicts a local temperature which is consistent with atomic-scale STM images of the photo-patterned regions. Finally, a simple device made by exposing photo-depassivated silicon to phosphine is found to have a carrier density and mobility similar to that produced by similar devices patterned by STM.
Asaad, Serwan; Mourik, Vincent; Joecker, Benjamin; Johnson, Mark A.I.; Baczewski, Andrew D.; Firgau, Hannes R.; Madzik, Mateusz T.; Schmitt, Vivien; Pla, Jarryd J.; Hudson, Fay E.; Itoh, Kohei M.; Mccallum, Jeffrey C.; Dzurak, Andrew S.; Laucht, Arne; Morello, Andrea
Nuclear spins are highly coherent quantum objects. In large ensembles, their control and detection via magnetic resonance is widely exploited, for example, in chemistry, medicine, materials science and mining. Nuclear spins also featured in early proposals for solid-state quantum computers1 and demonstrations of quantum search2 and factoring3 algorithms. Scaling up such concepts requires controlling individual nuclei, which can be detected when coupled to an electron4–6. However, the need to address the nuclei via oscillating magnetic fields complicates their integration in multi-spin nanoscale devices, because the field cannot be localized or screened. Control via electric fields would resolve this problem, but previous methods7–9 relied on transducing electric signals into magnetic fields via the electron–nuclear hyperfine interaction, which severely affects nuclear coherence. Here we demonstrate the coherent quantum control of a single 123Sb (spin-7/2) nucleus using localized electric fields produced within a silicon nanoelectronic device. The method exploits an idea proposed in 196110 but not previously realized experimentally with a single nucleus. Our results are quantitatively supported by a microscopic theoretical model that reveals how the purely electrical modulation of the nuclear electric quadrupole interaction results in coherent nuclear spin transitions that are uniquely addressable owing to lattice strain. The spin dephasing time, 0.1 seconds, is orders of magnitude longer than those obtained by methods that require a coupled electron spin to achieve electrical driving. These results show that high-spin quadrupolar nuclei could be deployed as chaotic models, strain sensors and hybrid spin-mechanical quantum systems using all-electrical controls. Integrating electrically controllable nuclei with quantum dots11,12 could pave the way to scalable, nuclear- and electron-spin-based quantum computers in silicon that operate without the need for oscillating magnetic fields.
Lithographic quantum dots (QDs) are highly controllable few-level quantum systems created in semiconductor nanoelectronic devices, with a variety of scientific applications. These include technologically-driven applications like quantum computing and more fundamental applications in which they serve as a platform for exploring basic many-body physics. This document is a brief summary of my Ph.D. research so far and the directions with which I intend to continue it. Highlights include theoretical efforts to understand and design qubits in germanium hole QDs, as well as explorations of the possibility of using QDs coupled to nearby baths for analog simulation of quantum impurity models.
Quantum materials have long promised to revolutionize everything from energy transmission (high temperature superconductors) to both quantum and classical information systems (topological materials). However, their discovery and application has proceeded in an Edisonian fashion due to both an incomplete theoretical understanding and the difficulty of growing and purifying new materials. This project leverages Sandia's unique atomic precision advanced manufacturing (APAM) capability to design small-scale tunable arrays (designer materials) made of donors in silicon. Their low-energy electronic behavior can mimic quantum materials, and can be tuned by changing the fabrication parameters for the array, thereby enabling the discovery of materials systems which can't yet be synthesized. In this report, we detail three key advances we have made towards development of designer quantum materials. First are advances both in APAM technique and underlying mechanisms required to realize high-yielding donor arrays. Second is the first-ever observation of distinct phases in this material system, manifest in disordered 2D sheets of donors. Finally are advances in modeling the electronic structure of donor clusters and regular structures incorporating them, critical to understanding whether an array is expected to show interesting physics. Combined, these establish the baseline knowledge required to manifest the strongly-correlated phases of the Mott-Hubbard model in donor arrays, the first step to deploying APAM donor arrays as analogues of quantum materials.
In the field of semiconductor quantum dot spin qubits, there is growing interest in leveraging the unique properties of hole-carrier systems and their intrinsically strong spin-orbit coupling to engineer novel qubits. Recent advances in semiconductor heterostructure growth have made available high quality, undoped Ge/SiGe quantum wells, consisting of a pure strained Ge layer flanked by Ge-rich SiGe layers above and below. These quantum wells feature heavy hole carriers and a cubic Rashba-type spin-orbit interaction. Here, we describe progress toward realizing spin qubits in this platform, including development of multi-metal-layer gated device architectures, device tuning protocols, and charge-sensing capabilities. Iterative improvement of a three-layer metal gate architecture has significantly enhanced device performance over that achieved using an earlier single-layer gate design. We discuss ongoing, simulation-informed work to fine-tune the device geometry, as well as efforts toward a single-spin qubit demonstration.
In the field of semiconductor quantum dot spin qubits, there is growing interest in leveraging the unique properties of hole-carrier systems and their intrinsically strong spin-orbit coupling to engineer novel qubits. Recent advances in semiconductor heterostructure growth have made available high quality, undoped Ge/SiGe quantum wells, consisting of a pure strained Ge layer flanked by Ge-rich SiGe layers above and below. These quantum wells feature heavy hole carriers and a cubic Rashba-type spin-orbit interaction. Here, we describe progress toward realizing spin qubits in this platform, including development of multi-metal-layer gated device architectures, device tuning protocols, and charge-sensing capabilities. Iterative improvement of a three-layer metal gate architecture has significantly enhanced device performance over that achieved using an earlier single-layer gate design. We discuss ongoing, simulation-informed work to fine-tune the device geometry, as well as efforts toward a single-spin qubit demonstration.
The silicon metal-oxide-semiconductor (MOS) material system is a technologically important implementation of spin-based quantum information processing. However, the MOS interface is imperfect leading to concerns about 1/f trap noise and variability in the electron g-factor due to spin-orbit (SO) effects. Here we advantageously use interface-SO coupling for a critical control axis in a double-quantum-dot singlet-triplet qubit. The magnetic fieldorientation dependence of the g-factors is consistent with Rashba and Dresselhaus interface-SO contributions. The resulting all-electrical, two-Axis control is also used to probe the MOS interface noise. The measured inhomogeneous dephasing time, T2m, of 1.6 ?s is consistent with 99.95% 28Si enrichment. Furthermore, when tuned to be sensitive to exchange fluctuations, a quasi-static charge noise detuning variance of 2 μeV is observed, competitive with low-noise reports in other semiconductor qubits. This work, therefore, demonstrates that the MOS interface inherently provides properties for two-Axis qubit control, while not increasing noise relative to other material choices.
Gate-controllable spin-orbit coupling is often one requisite for spintronic devices. For practical spin field-effect transistors, another essential requirement is ballistic spin transport, where the spin precession length is shorter than the mean free path such that the gate-controlled spin precession is not randomized by disorder. In this letter, we report the observation of a gate-induced crossover from weak localization to weak anti-localization in the magneto-resistance of a high-mobility two-dimensional hole gas in a strained germanium quantum well. From the magneto-resistance, we extract the phase-coherence time, spin-orbit precession time, spin-orbit energy splitting, and cubic Rashba coefficient over a wide density range. The mobility and the mean free path increase with increasing hole density, while the spin precession length decreases due to increasingly stronger spin-orbit coupling. As the density becomes larger than ∼6 × 1011 cm-2, the spin precession length becomes shorter than the mean free path, and the system enters the ballistic spin transport regime. We also report here the numerical methods and code developed for calculating the magneto-resistance in the ballistic regime, where the commonly used HLN and ILP models for analyzing weak localization and anti-localization are not valid. These results pave the way toward silicon-compatible spintronic devices.
Kim, Jeongnim; Baczewski, Andrew D.; Beaudet, Todd D.; Benali, Anouar; Bennett, Michael B.; Berrill, Mark A.; Blunt, Nick S.; Casula, Michele; Ceperley, David M.; Chiesa, Simone; Clark, Bryan K.; Clay III, Raymond C.; Delaney, Kris T.; Dewing, Mark; Esler, Kenneth P.; Hao, Hongxia; Hein, Olle; Kent, Paul R.C.; Krogel, Jaron T.; Kylanpaa, Ilkka; Li, Ying W.; Lopez, M.G.; Luo, Ye; Martin, Richard M.; Mathuriya, Amrita; Mcminis, Jeremy; Melton, Cody A.; Mitas, Lubos; Neuscamman, Eric; Parker, William D.; Pineda Flores, Sergio D.; Romero, Nichols A.; Rubenstein, Brenda M.; Shea, Jacqueline A.R.; Shin, Hyeondeok; Shulenburger, Luke N.; Tillack, Andreas F.; Townsend, Joshua P.; Tubman, Norm M.; Van Der Goetz, Brett; Vincent, Jordan E.; Yang, Yubo; Zhang, Shuai; Morales, Miguel A.; Zhao, Luning
QMCPACK is an open source quantum Monte Carlo package for ab-initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wave functions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit (CPU) and graphical processing unit (GPU) systems. We detail the program’s capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://www.qmcpack.org.
This paper describes our work over the past few years to use tools from quantum chemistry to describe electronic structure of nanoelectronic devices. These devices, dubbed "artificial atoms", comprise a few electrons, con ned by semiconductor heterostructures, impurities, and patterned electrodes, and are of intense interest due to potential applications in quantum information processing, quantum sensing, and extreme-scale classical logic. We detail two approaches we have employed: nite-element and Gaussian basis sets, exploring the interesting complications that arise when techniques that were intended to apply to atomic systems are instead used for artificial, solid-state devices.
The silicon metal-oxide-semiconductor (MOS) material system is technologically important for the implementation of electron spin-based quantum information technologies. Researchers predict the need for an integrated platform in order to implement useful computation, and decades of advancements in silicon microelectronics fabrication lends itself to this challenge. However, fundamental concerns have been raised about the MOS interface (e.g. trap noise, variations in electron g-factor and practical implementation of multi-QDs). Furthermore, two-axis control of silicon qubits has, to date, required the integration of non-ideal components (e.g. microwave strip-lines, micro-magnets, triple quantum dots, or introduction of donor atoms). In this paper, we introduce a spin-orbit (SO) driven singlet- triplet (ST) qubit in silicon, demonstrating all-electrical two-axis control that requires no additional integrated elements and exhibits charge noise properties equivalent to other more model, but less commercially mature, semiconductor systems. We demonstrate the ability to tune an intrinsic spin-orbit interface effect, which is consistent with Rashba and Dresselhaus contributions that are remarkably strong for a low spin-orbit material such as silicon. The qubit maintains the advantages of using isotopically enriched silicon for producing a quiet magnetic environment, measuring spin dephasing times of 1.6 μs using 99.95% 28Si epitaxy for the qubit, comparable to results from other isotopically enhanced silicon ST qubit systems. This work, therefore, demonstrates that the interface inherently provides properties for two-axis control, and the technologically important MOS interface does not add additional detrimental qubit noise. isotopically enhanced silicon ST qubit systems
Silicon-based metal-oxide-semiconductor quantum dots are prominent candidates for high-fidelity, manufacturable qubits. Due to silicon's band structure, additional low-energy states persist in these devices, presenting both challenges and opportunities. Although the physics governing these valley states has been the subject of intense study, quantitative agreement between experiment and theory remains elusive. Here, we present data from an experiment probing the valley states of quantum dot devices and develop a theory that is in quantitative agreement with both this and a recently reported experiment. Through sampling millions of realistic cases of interface roughness, our method provides evidence that the valley physics between the two samples is essentially the same.