arXiv subjects

Andrew D. Baczewski

Publications and source records attributed to Andrew D. Baczewski.

At least 37 records · Page 2Linked to original sources

arXiv2023

Feedback-based quantum algorithms for ground state preparation

The ground state properties of quantum many-body systems are a subject of interest across chemistry, materials science, and physics. Thus, algorithms for finding ground states can have broad impacts. Variational quantum algorithms are one class of ground state algorithms that has received significant attention in recent years. These algorithms utilize a hybrid quantum-classical computing framework to prepare ground states on quantum computers. However, this requires solving a classical optimization problem that can become prohibitively expensive in high dimensions. Here, we develop formulations of feedback-based quantum algorithms for ground state preparation that can be used to address this challenge for two broad classes of Hamiltonians: Fermi-Hubbard Hamiltonians, and molecular Hamiltonians represented in second quantization. Feedback-based quantum algorithms are optimization-free; in place of classical optimization, quantum circuit parameters are set according to a deterministic feedback law derived from quantum Lyapunov control principles. This feedback law guarantees a monotonic improvement in solution quality with respect to the depth of the quantum circuit. A variety of numerical illustrations are provided that analyze the convergence and robustness of feedback-based quantum algorithms for these problem classes.

quant-ph↗

arXiv2023

Quantum computation of stopping power for inertial fusion target design

Stopping power is the rate at which a material absorbs the kinetic energy of a charged particle passing through it -- one of many properties needed over a wide range of thermodynamic conditions in modeling inertial fusion implosions. First-principles stopping calculations are classically challenging because they involve the dynamics of large electronic systems far from equilibrium, with accuracies that are particularly difficult to constrain and assess in the warm-dense conditions preceding ignition. Here, we describe a protocol for using a fault-tolerant quantum computer to calculate stopping power from a first-quantized representation of the electrons and projectile. Our approach builds upon the electronic structure block encodings of Su et al. [PRX Quantum 2, 040332 2021], adapting and optimizing those algorithms to estimate observables of interest from the non-Born-Oppenheimer dynamics of multiple particle species at finite temperature. Ultimately, we report logical qubit requirements and leading-order Toffoli costs for computing the stopping power of various projectile/target combinations relevant to interpreting and designing inertial fusion experiments. We estimate that scientifically interesting and classically intractable stopping power calculations can be quantum simulated with roughly the same number of logical qubits and about one hundred times more Toffoli gates than is required for state-of-the-art quantum simulations of industrially relevant molecules such as FeMoCo or P450.

quant-ph↗

arXiv2023

Self-healing of Trotter error in digital adiabatic state preparation

Adiabatic time evolution can be used to prepare a complicated quantum many-body state from one that is easier to synthesize and Trotterization can be used to implement such an evolution digitally. The complex interplay between non-adiabaticity and digitization influences the infidelity of this process. We prove that the first-order Trotterization of a complete adiabatic evolution has a cumulative infidelity that scales as $\mathcal O(T^{-2} δt^2)$ instead of $\mathcal O(T^2 δt^2)$ expected from general Trotter error bounds, where $δt$ is the time step and $T$ is the total time. This result suggests a self-healing mechanism and explains why, despite increasing $T$, infidelities for fixed-$δt$ digitized evolutions still decrease for a wide variety of Hamiltonians. It also establishes a correspondence between the Quantum Approximate Optimization Algorithm (QAOA) and digitized quantum annealing.

quant-ph↗

arXiv2023

Trajectory sampling and finite-size effects in first-principles stopping power calculations

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 aluminium 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.

cond-mat.mtrl-sci↗

arXiv2023

Evidence of free-bound transitions in warm dense matter and their impact on equation-of-state measurements

Warm dense matter (WDM) is now routinely created and probed in laboratories around the world, providing unprecedented insights into conditions achieved in stellar atmospheres, planetary interiors, and inertial confinement fusion experiments. However, the interpretation of these experiments is often filtered through models with systematic errors that are difficult to quantify. Due to the simultaneous presence of quantum degeneracy and thermal excitation, processes in which free electrons are de-excited into thermally unoccupied bound states transferring momentum and energy to a scattered x-ray photon become viable. Here we show that such free-bound transitions are a particular feature of WDM and vanish in the limits of cold and hot temperatures. The inclusion of these processes into the analysis of recent X-ray Thomson Scattering experiments on WDM at the National Ignition Facility and the Linac Coherent Light Source significantly improves model fits, indicating that free-bound transitions have been observed without previously being identified. This interpretation is corroborated by agreement with a recently developed model-free thermometry technique and presents an important step for precisely characterizing and understanding the complex WDM state of matter.

physics.plasm-ph↗

arXiv2023

Utilizing multimodal microscopy to reconstruct Si/SiGe interfacial atomic disorder and infer its impacts on qubit variability

SiGe heteroepitaxial growth yields pristine host material for quantum dot qubits, but residual interface disorder can lead to qubit-to-qubit variability that might pose an obstacle to reliable SiGe-based quantum computing. We demonstrate a technique to reconstruct 3D interfacial atomic structure spanning multiqubit areas by combining data from two verifiably atomic-resolution microscopy techniques. Utilizing scanning tunneling microscopy (STM) to track molecular beam epitaxy (MBE) growth, we image surface atomic structure following deposition of each heterostructure layer revealing nanosized SiGe undulations, disordered strained-Si atomic steps, and nonconformal uncorrelated roughness between interfaces. Since phenomena such as atomic intermixing during subsequent overgrowth inevitably modify interfaces, we measure post-growth structure via cross-sectional high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM). Features such as nanosized roughness remain intact, but atomic step structure is indiscernible in $1.0\pm 0.4$~nm-wide intermixing at interfaces. Convolving STM and HAADF-STEM data yields 3D structures capturing interface roughness and intermixing. We utilize the structures in an atomistic multivalley effective mass theory to quantify qubit spectral variability. The results indicate (1) appreciable valley splitting (VS) variability of roughly $\pm$ $50\%$ owing to alloy disorder, and (2) roughness-induced double-dot detuning bias energy variability of order $1-10$ meV depending on well thickness. For measured intermixing, atomic steps have negligible influence on VS, and uncorrelated roughness causes spatially fluctuating energy biases in double-dot detunings potentially incorrectly attributed to charge disorder.

cond-mat.mtrl-sci↗

arXiv2023

Electronic structure of boron and aluminum $δ$-doped layers in silicon

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 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.

cond-mat.mtrl-sci↗

arXiv2023

Quantum-Inspired Tempering for Ground State Approximation using Artificial Neural Networks

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.

cond-mat.dis-nn↗

arXiv2023

Improving dynamic collision frequencies: impacts on dynamic structure factors and stopping powers in warm dense matter

Simulations and diagnostics of high-energy-density plasmas and warm dense matter rely on models of material response properties, both static and dynamic (frequency-dependent). Here, we systematically investigate variations in dynamic electron-ion collision frequencies $ν(ω)$ in warm dense matter using data from a self-consistent-field average-atom model. We show that including the full quantum density of states, strong collisions, and inelastic collisions lead to significant changes in $ν(ω)$. These changes result in red shifts and broadening of the plasmon peak in the dynamic structure factor, an effect observable in x-ray Thomson scattering spectra, and modify stopping powers around the Bragg peak. These changes improve the agreement of computationally efficient average-atom models with first-principles time-dependent density functional theory in warm dense aluminum, carbon, and deuterium.

physics.plasm-ph↗

arXiv2023

Quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods

Quantum algorithms for simulating electronic ground states are slower than popular classical mean-field algorithms such as Hartree-Fock and density functional theory, but offer higher accuracy. Accordingly, quantum computers have been predominantly regarded as competitors to only the most accurate and costly classical methods for treating electron correlation. However, here we tighten bounds showing that certain first quantized quantum algorithms enable exact time evolution of electronic systems with exponentially less space and polynomially fewer operations in basis set size than conventional real-time time-dependent Hartree-Fock and density functional theory. Although the need to sample observables in the quantum algorithm reduces the speedup, we show that one can estimate all elements of the $k$-particle reduced density matrix with a number of samples scaling only polylogarithmically in basis set size. We also introduce a more efficient quantum algorithm for first quantized mean-field state preparation that is likely cheaper than the cost of time evolution. We conclude that quantum speedup is most pronounced for finite temperature simulations and suggest several practically important electron dynamics problems with potential quantum advantage.

quant-ph↗

arXiv2022

Electronic Density Response of Warm Dense Matter

Matter at extreme temperatures and pressures -- commonly known as warm dense matter (WDM) in the literature -- is ubiquitous throughout our Universe and occurs in a number of astrophysical objects such as giant planet interiors and brown dwarfs. Moreover, WDM is very important for technological applications such as inertial confinement fusion, and is realized in the laboratory using different techniques. A particularly important property for the understanding of WDM is given by its electronic density response to an external perturbation. Such response properties are routinely probed in x-ray Thomson scattering (XRTS) experiments, and, in addition, are central for the theoretical description of WDM. In this work, we give an overview of a number of recent developments in this field. To this end, we summarize the relevant theoretical background, covering the regime of linear-response theory as well as nonlinear effects, the fully dynamic response and its static, time-independent limit, and the connection between density response properties and imaginary-time correlation functions (ITCF). In addition, we introduce the most important numerical simulation techniques including ab initio path integral Monte Carlo (PIMC) simulations and different thermal density functional theory (DFT) approaches. From a practical perspective, we present a variety of simulation results for different density response properties, covering the archetypal model of the uniform electron gas and realistic WDM systems such as hydrogen. Moreover, we show how the concept of ITCFs can be used to infer the temperature from XRTS measurements of arbitrarily complex systems without the need for any models or approximations. Finally, we outline a strategy for future developments based on the close interplay between simulations and experiments.

physics.plasm-ph↗

arXiv2022

An \textit{ab initio} study of shock-compressed copper

We investigate shock-compressed copper in the warm dense matter regime by means of density functional theory molecular dynamics simulations. We use neural-network-driven interatomic potentials to increase the size of the simulation box and extract thermodynamic properties in the hydrodynamic limit. We show the agreement of our simulation results with experimental data for solid copper at ambient conditions and liquid copper near the melting point under ambient pressure. Furthermore, a thorough analysis of the dynamic ion-ion structure factor in shock-compressed copper is performed and the adiabatic speed of sound is extracted and compared with experimental data.

cond-mat.other↗

arXiv2022

Robust incorporation in multi-donor patches created using atomic-precision advanced manufacturing

Atomic-precision advanced manufacturing enables the placement of dopant atoms within $\pm$1 lattice site in crystalline Si. However, it has recently been shown that reaction kinetics can introduce uncertainty in whether a single donor will incorporate at all in a minimal 3-dimer lithographic window. In this work, we explore the combined impact of lithographic variation and stochastic kinetics on P incorporation as the size of such a window is increased. We augment a kinetic model for PH$_3$ dissociation leading to P incorporation on Si(100)-2$\times$1 to include barriers for reactions across distinct dimer rows. Using this model, we demonstrate that even for a window consisting of 2$\times$3 silicon dimers, the probability that at least one donor incorporates is nearly unity. We also examine the impact of size of the lithographic window, finding that the incorporation fraction saturates to $δ$-layer like coverage as the circumference-to-area ratio approaches zero. 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 $\sim \sqrt{n}$, as would be expected for a series of largely independent incorporation events. Finally, we characterize an array of experimentally prepared multi-donor lithographic windows and use our kinetic model to study variability due to the observed lithographic roughness, predicting a negligible impact on incorporation statistics. We find good agreement between our model and the inferred incorporation in these windows from scanning tunneling microscope measurements, indicating the robustness of atomic-precision advanced manufacturing to errors in patterning for multi-donor patches.

cond-mat.mes-hall↗

arXiv2022

First-principles simulation of light-ion microscopy of graphene

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 3 times higher signal and up to 5 times higher contrast images, making 2D materials especially compelling targets for ion-beam microscopy. We also find that 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.

cond-mat.mtrl-sci↗

arXiv2022

Precision tomography of a three-qubit donor quantum processor in silicon

Nuclear spins were among the first physical platforms to be considered for quantum information processing, because of their exceptional quantum coherence and atomic-scale footprint. However, their full potential for quantum computing has not yet been realized, due to the lack of methods 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 spin, and used to prepare entangled Bell states with fidelities up to 94.2(2.7)%. The quantum operations are precisely characterised using gate set tomography (GST), 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 processors. 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. Since electron spin qubits in semiconductors can be further coupled to other electrons or physically shuttled across different locations, these results establish a viable route for scalable quantum information processing using donor nuclear and electron spins.

quant-ph↗

arXiv2022

Reaction pathways of BCl$_3$ for acceptor delta-doping of silicon

BCl$_3$ is a promising candidate for atomic-precision acceptor doping in Si, but optimizing the electrical properties of structures created with this technique requires a detailed understanding of adsorption and dissociation pathways for this precursor. Here, we use density functional theory and scanning tunneling microscopy (STM) to identify and explore these pathways for BCl$_3$ on Si(100) at different annealing temperatures. We demonstrate that BCl$_3$ adsorbs selectively without a reaction barrier, and subsequently dissociates relatively easily with reaction barriers $\approx$1 eV. Using this dissociation pathway, we parameterize a Kinetic Monte Carlo model to predict B incorporation rates as a function of dosing conditions. STM is used to image BCl$_{3}$ adsorbates, identifying several surface configurations and tracking the change in their distribution as a function of the annealing temperature, matching predictions of the kinetic model well. This straightforward pathway for atomic-precision acceptor doping helps enable a wide range of applications including bipolar nanoelectronics, acceptor-based qubits, and superconducting Si.

cond-mat.mtrl-sci↗

arXiv2021

Predictions of bound-bound transition signatures in x-ray Thomson scattering

Bound-bound transitions can occur when localized atomic orbitals are thermally depleted, allowing excitations that would otherwise be forbidden at zero temperature. We predict signatures of bound-bound transitions in x-ray Thomson scattering measurements of laboratory-accessible warm dense conditions. Efficient average-atom models amended to include quasibound states achieve continuity of observables under ionization and agree with time-dependent density functional theory in their prediction of these scattering signatures, which hold compelling diagnostic potential for high-energy-density experiments.

physics.plasm-ph↗

arXiv2021

Engineering local strain for single-atom nuclear acoustic resonance in silicon

Mechanical strain plays a key role in the physics and operation of nanoscale semiconductor systems, including quantum dots and single-dopant devices. Here we describe the design of a nanoelectronic device where a single nuclear spin is coherently controlled via nuclear acoustic resonance (NAR) through the local application of dynamical strain. The strain drives spin transitions by modulating the nuclear quadrupole interaction. We adopt an AlN piezoelectric actuator compatible with standard silicon metal-oxide-semiconductor processing, and optimize the device layout to maximize the NAR drive. We predict NAR Rabi frequencies of order 200 Hz for a single $^{123}$Sb nucleus in a wide region of the device. Spin transitions driven directly by electric fields are suppressed in the center of the device, allowing the observation of pure NAR. Using electric field gradient-elastic tensors calculated by density-functional theory, we extend our predictions to other high-spin group-V donors in silicon, and to the isoelectronic $^{73}$Ge atom.

cond-mat.mes-hall↗