arXiv subjects

J. P. Dodson

Publications and source records attributed to J. P. Dodson.

15 recordsLinked to original sources

arXiv2026

Individually tunable Si/SiGe quantum dot operating voltages via gate-biased illumination

Semiconductor quantum dot qubits often require very different voltages on each gate to bring them to a correct operating point. Here, we present a method by which one can controllably and repeatably alter the nanoscale trapped charge distribution at an oxide-semiconductor interface. We demonstrate this method on a Si/SiGe quantum dot device, and we find that the operating voltages can be controlled and made much more uniform. The method relies on illumination with near-infrared light in the presence of applied gate voltages, and it enables the tuning of the device operating point on a gate-by-gate basis. We present an explanation of the underlying physics using self-consistent Schrödinger-Poisson simulations. As an application of this method, we tune a triple quantum dot to have uniform and small operating voltages in the (1,1,1) charge configuration. Importantly, we show that shifting the operating voltages in this way does not change the measured charge noise.

cond-mat.mes-hall↗

arXiv2026

A digitally controlled silicon quantum processing unit

Commercially-relevant quantum computers will require large numbers of high-performing qubits that can be manufactured, integrated, and controlled at scale. Silicon exchange-only (EO) qubits are a strong candidate modality due to their control-signal simplicity and compatibility with advanced semiconductor manufacturing, but questions remain around the achievability of sufficiently low noise and a scalable control and wiring solution. Here we introduce a quantum processing unit composed of a custom-designed cryogenic CMOS controller, a novel high-density superconducting ribbon cable, and a low-noise EO qubit device. The quantum chip features a three-rail array of 54 exchange-coupled quantum dots, configurable to host up to 18 EO qubits. We integrate and use these components to demonstrate qubit performance for both single-qubit and entangling operations that advances the EO state of the art by an order of magnitude. We further validate this system by implementing a distance-5 repetition code and a quantum error detecting code then make detailed comparisons with simulations. Our approach facilitates a utility-scale quantum computer with manageable operational and capital requirements.

quant-ph↗

arXiv2026

Single-shot latched readout of a quantum dot qubit using barrier gate pulsing

Latching techniques are widely used to enhance readout of qubits. These methods require precise tuning of multiple tunnel rates, which can be challenging to achieve under realistic experimental conditions, such as when a qubit is coupled to a single reservoir. Here, we present a method for single-shot measurement of a quantum dot qubit with a single reservoir using a latched-readout scheme. Our approach involves pulsing a barrier gate to dynamically control qubit-to-reservoir tunnel rates, a method that is readily applicable to the latched readout of various spin-based qubits. We use this method to enable qubit state latching and to reduce the qubit reset time in measurements of coherent Larmor oscillations of a Si/SiGe quantum dot hybrid qubit.

cond-mat.mes-hall↗

arXiv2025

Two-dimensional Si spin qubit arrays with multilevel interconnects

The promise of quantum computation is contingent upon physical qubits with both low gate error rate and broad scalability. Silicon-based spins are a leading qubit platform, but demonstrations to date have not utilized fabrication processes capable of extending arrays in two dimensions while maintaining complete control of individual spins. Here, we implement an interconnect process, common in semiconductor manufacturing, with multiple back-end-of-line layers to show an extendable two-dimensional array of spins with fully controllable nearest-neighbor exchange interactions. In a device using three interconnect layers, we encode exchange-only qubits and achieve average single-qubit gate fidelities consistent with single-layer devices, including fidelities greater than 99.9%, as measured by blind randomized benchmarking. Moreover, with spin connectivity in two dimensions, we show that both linear and right-angle exchange-only qubits with high performance can be formed, enabling qubit array reconfigurability in the presence of defects. This extendable device platform demonstrates that industrial manufacturing techniques can be leveraged for scalable spin qubit technologies.

quant-ph↗

arXiv2025

Automation of Quantum Dot Measurement Analysis via Explainable Machine Learning

The rapid development of quantum dot (QD) devices for quantum computing has necessitated more efficient and automated methods for device characterization and tuning. This work demonstrates the feasibility and advantages of applying explainable machine learning techniques to the analysis of quantum dot measurements, paving the way for further advances in automated and transparent QD device tuning. Many of the measurements acquired during the tuning process come in the form of images that need to be properly analyzed to guide the subsequent tuning steps. By design, features present in such images capture certain behaviors or states of the measured QD devices. When considered carefully, such features can aid the control and calibration of QD devices. An important example of such images are so-called $\textit{triangle plots}$, which visually represent current flow and reveal characteristics important for QD device calibration. While image-based classification tools, such as convolutional neural networks (CNNs), can be used to verify whether a given measurement is $\textit{good}$ and thus warrants the initiation of the next phase of tuning, they do not provide any insights into how the device should be adjusted in the case of $\textit{bad}$ images. This is because CNNs sacrifice prediction and model intelligibility for high accuracy. To ameliorate this trade-off, a recent study introduced an image vectorization approach that relies on the Gabor wavelet transform (Schug $\textit{et al.}$ 2024 $\textit{Proc. XAI4Sci: Explainable Machine Learning for Sciences Workshop (AAAI 2024) (Vancouver, Canada)}$ pp 1-6). Here we propose an alternative vectorization method that involves mathematical modeling of synthetic triangles to mimic the experimental data. Using explainable boosting machines, we show that this new method offers superior explainability of model prediction without sacrificing accuracy.

cs.CV↗

arXiv2022

SiGe quantum wells with oscillating Ge concentrations for quantum dot qubits

Large-scale arrays of quantum-dot spin qubits in Si/SiGe quantum wells require large or tunable energy splittings of the valley states associated with degenerate conduction band minima. Existing proposals to deterministically enhance the valley splitting rely on sharp interfaces or modifications in the quantum well barriers that can be difficult to grow. Here, we propose and demonstrate a new heterostructure, the "Wiggle Well," whose key feature is Ge concentration oscillations inside the quantum well. Experimentally, we show that placing Ge in the quantum well does not significantly impact our ability to form and manipulate single-electron quantum dots. We further observe large and widely tunable valley splittings, from 54 to 239 ueV. Tight-binding calculations, and the tunability of the valley splitting, indicate that these results can mainly be attributed to random concentration fluctuations that are amplified by the presence of Ge alloy in the heterostructure, as opposed to a deterministic enhancement due to the concentration oscillations. Quantitative predictions for several other heterostructures point to the Wiggle Well as a robust method for reliably enhancing the valley splitting in future qubit devices.

quant-ph↗

arXiv2022

Latched readout for the quantum dot hybrid qubit

A primary method of reading out a quantum dot hybrid qubit involves projection of the logical basis onto distinct charge states that are readily detected by an integrated charge sensing dot. However, in the simplest configuration, the excited charge state decays rapidly, making single-shot readout challenging. Here, we demonstrate a readout procedure where the qubit excited state is latched to a metastable charge configuration whose lifetime is tunnel rate limited, persisting here as long as 2.5 ms. Additionally, we show that working in the (4,1)-(3,2) charge configuration enables a latched readout window that is larger and more tunable than typical charge configurations, because the size of the readout window is determined by an orbital splitting rather than a valley splitting.

cond-mat.mes-hall↗

arXiv2022

How valley-orbit states in silicon quantum dots probe quantum well interfaces

The energies of valley-orbit states in silicon quantum dots are determined by an as yet poorly understood interplay between interface roughness, orbital confinement, and electron interactions. Here, we report measurements of one- and two-electron valley-orbit state energies as the dot potential is modified by changing gate voltages, and we calculate these same energies using full configuration interaction calculations. The results enable an understanding of the interplay between the physical contributions and enable a new probe of the quantum well interface.

cond-mat.mes-hall↗

arXiv2021

Valley splittings in Si/SiGe quantum dots with a germanium spike in the silicon well

Silicon-germanium heterostructures have successfully hosted quantum dot qubits, but the intrinsic near-degeneracy of the two lowest valley states poses an obstacle to high fidelity quantum computing. We present a modification to the Si/SiGe heterostructure by the inclusion of a spike in germanium concentration within the quantum well in order to increase the valley splitting. The heterostructure is grown by chemical vapor deposition and magnetospectroscopy is performed on gate-defined quantum dots to measure the excited state spectrum. We demonstrate a large and widely tunable valley splitting as a function of applied vertical electric field and lateral dot confinement. We further investigate the role of the germanium spike by means of tight-binding simulations in single-electron dots and show a robust doubling of the valley splitting when the spike is present, as compared to a standard (spike-free) heterostructure. This doubling effect is nearly independent of the electric field, germanium content of the spike, and spike location. This experimental evidence of a stable, tunable quantum dot, despite a drastic change to the heterostructure, provides a foundation for future heterostructure modifications.

cond-mat.mes-hall↗

arXiv2020

Coherent control and spectroscopy of a semiconductor quantum dot Wigner molecule

Multi-electron semiconductor quantum dots have found wide application in qubits, where they enable readout and enhance polarizability. However, coherent control in such dots has typically been restricted to only the lowest two levels, and such control in the strongly interacting regime has not been realized. Here we report quantum control of eight different resonances in a silicon-based quantum dot. We use qubit readout to perform spectroscopy, revealing a dense set of energy levels with characteristic spacing far smaller than the single-particle energy. By comparing with full configuration interaction calculations, we argue that the dense set of levels arises from Wigner-molecule physics.

cond-mat.mes-hall↗

arXiv2020

Fabrication process and failure analysis for robust quantum dots in silicon

We present an improved fabrication process for overlapping aluminum gate quantum dot devices on Si/SiGe heterostructures that incorporates low-temperature inter-gate oxidation, thermal annealing of gate oxide, on-chip electrostatic discharge (ESD) protection, and an optimized interconnect process for thermal budget considerations. This process reduces gate-to-gate leakage, damage from ESD, dewetting of aluminum, and formation of undesired alloys in device interconnects. Additionally, cross-sectional scanning transmission electron microscopy (STEM) images elucidate gate electrode morphology in the active region as device geometry is varied. We show that overlapping aluminum gate layers homogeneously conform to the topology beneath them, independent of gate geometry, and identify critical dimensions in the gate geometry where pattern transfer becomes non-ideal, causing device failure.

physics.app-ph↗

arXiv2020

Microwave Engineering for Semiconductor Quantum Dots in a cQED Architecture

We develop an engineered microwave environment for coupling high Q superconducting resonators to quantum dots using a multilayer fabrication stack for the dot control wiring. Analytic and numerical models are presented to understand how parasitic capacitive coupling to the dot bias leads can result in microwave energy leakage and low resonator quality factors. We show that by controlling the characteristic impedance of the dot bias wiring, on-chip quality factors of 8140 can be attained without the addition of explicit filtering. Using this approach we demonstrate single electron occupation in double and triple dots detected via dipole or quadrupole coupling to a superconducting resonator. Additionally, by using multilayer fabrication we are able to improve ground plane integrity and keep microwave crosstalk below -20 dB out to 18 GHz while maintaining high wire density which will be necessary for future circuit quantum electrodyanmics (cQED) quantum dot processors.

cond-mat.mes-hall↗

arXiv2020

Auto-tuning of double dot devices in situ with machine learning

The current practice of manually tuning quantum dots (QDs) for qubit operation is a relatively time-consuming procedure that is inherently impractical for scaling up and applications. In this work, we report on the {\it in situ} implementation of a recently proposed autotuning protocol that combines machine learning (ML) with an optimization routine to navigate the parameter space. In particular, we show that a ML algorithm trained using exclusively simulated data to quantitatively classify the state of a double-QD device can be used to replace human heuristics in the tuning of gate voltages in real devices. We demonstrate active feedback of a functional double-dot device operated at millikelvin temperatures and discuss success rates as a function of the initial conditions and the device performance. Modifications to the training network, fitness function, and optimizer are discussed as a path toward further improvement in the success rate when starting both near and far detuned from the target double-dot range.

quant-ph↗

arXiv2020

Progress Towards a Capacitively Mediated CNOT Between Two Charge Qubits in Si/SiGe

Fast operations, an easily tunable Hamiltonian, and a straightforward two-qubit interaction make charge qubits a useful tool for benchmarking device performance and exploring two-qubit dynamics. Here, we tune a linear chain of four Si/SiGe quantum dots to host two double dot charge qubits. Using the capacitance between the double dots to mediate a strong two-qubit interaction, we simultaneously drive coherent transitions to generate correlations between the qubits. We then sequentially pulse the qubits to drive one qubit conditionally on the state of the other. We find that a conditional $π$-rotation can be driven in just 74 ps with a modest fidelity demonstrating the possibility of two-qubit operations with a 13.5 GHz clockspeed.

quant-ph↗

arXiv2019

Measurements of capacitive coupling within a quadruple quantum dot array

We present measurements of the capacitive coupling energy and the inter-dot capacitances in a linear quadruple quantum dot array in undoped Si/SiGe. With the device tuned to a regime of strong ($>$1 GHz) intra-double dot tunnel coupling, as is typical for double dot qubits, we measure a capacitive coupling energy of $20.9 \pm 0.3$ GHz. In this regime, we demonstrate a fitting procedure to extract all the parameters in the 4D Hamiltonian for two capacitively coupled charge qubits from a 2D slice through the quadruple dot charge stability diagram. We also investigate the tunability of the capacitive coupling energy, using inter-dot barrier gate voltages to tune the inter- and intra-double dot capacitances, and change the capacitive coupling energy of the double dots over a range of 15-32 GHz. We provide a model for the capacitive coupling energy based on the electrostatics of a network of charge nodes joined by capacitors, which shows how the coupling energy should depend on inter-double dot and intra-double dot capacitances in the network, and find that the expected trends agree well with the measurements of coupling energy.

quant-ph↗