arXiv subjects

Michael Chan

Publications and source records attributed to Michael Chan.

6 recordsLinked to original sources

arXiv2025

Automated electrostatic characterization of quantum dot devices in single- and bilayer heterostructures

As quantum dot (QD)-based spin qubits advance toward larger, more complex device architectures, rapid, automated device characterization and data analysis tools become critical. The orientation and spacing of transition lines in a charge stability diagram (CSD) contain a fingerprint of a QD device's capacitive environment, making these measurements useful tools for device characterization. However, manually interpreting these features is time-consuming, error-prone, and impractical at scale. Here, we present an automated protocol for extracting underlying capacitive properties from CSDs. Our method integrates machine learning, image processing, and object detection to identify and track charge transitions across large datasets without manual labeling. We demonstrate this method using experimentally measured data from a strained-germanium single-quantum-well (planar) and a strained-germanium double-quantum-well (bilayer) QD device. Unlike for planar QD devices, CSDs in bilayer germanium heterostructure exhibit a larger set of transitions, including interlayer tunneling and distinct loading lines for the vertically stacked QDs, making them a powerful testbed for automation methods. By analyzing the properties of many CSDs, we can statistically estimate physically relevant quantities, like relative lever arms and capacitive couplings. Thus, our protocol enables rapid extraction of useful, nontrivial information about QD devices.

cond-mat.mes-hall↗

arXiv2025

A Three-Dimensional Array of Quantum Dots

Quantum dots can confine single electrons or holes to define spin qubits that can be operated with high fidelity. Experimental work has progressed from linear to two-dimensional arrays of quantum dots, enabling qubit interactions that are essential for quantum simulation and computation. Here, we explore architectures beyond planar geometries by constructing quantum dot arrays in three dimensions. We realize an eight-quantum dot system in a silicon-germanium heterostructure comprising two stacked germanium quantum wells, where quantum dots are positioned at the vertices of a cuboid. Using electrostatic gate control, we load a single hole into any of the eight quantum dots. To demonstrate the potential of multilayer quantum dot systems, we show coherent spin control and hopping-induced spin rotations by shuttling between the quantum wells. The ability to extend quantum dot arrays in three dimensions provides opportunities for novel quantum hardware and high-connectivity quantum circuits.

cond-mat.mes-hall↗

arXiv2025

Deep Neural Encoder-Decoder Model to Relate fMRI Brain Activity with Naturalistic Stimuli

We propose an end-to-end deep neural encoder-decoder model to encode and decode brain activity in response to naturalistic stimuli using functional magnetic resonance imaging (fMRI) data. Leveraging temporally correlated input from consecutive film frames, we employ temporal convolutional layers in our architecture, which effectively allows to bridge the temporal resolution gap between natural movie stimuli and fMRI acquisitions. Our model predicts activity of voxels in and around the visual cortex and performs reconstruction of corresponding visual inputs from neural activity. Finally, we investigate brain regions contributing to visual decoding through saliency maps. We find that the most contributing regions are the middle occipital area, the fusiform area, and the calcarine, respectively employed in shape perception, complex recognition (in particular face perception), and basic visual features such as edges and contrasts. These functions being strongly solicited are in line with the decoder's capability to reconstruct edges, faces, and contrasts. All in all, this suggests the possibility to probe our understanding of visual processing in films using as a proxy the behaviour of deep learning models such as the one proposed in this paper.

cs.CV↗

arXiv2023

Flux-Tunable Hybridization in a Double Quantum Dot Interferometer

A single electron shared between two levels threaded by a magnetic flux is an irreducibly simple quantum system in which interference is predicted to occur. We demonstrate tuning of the tunnel coupling between two such electronic levels with flux, implemented in a loop comprising two quantum dots. Using radio-frequency reflectometry of the dots' gate electrodes we extract the inter-dot coupling, which exhibits oscillations with a periodicity of one flux quantum. In different tunneling regimes we benchmark the oscillations' contrast, and find that their amplitude varies with the levels involved, while tunneling is generically not suppressed at oscillation minima. These results establish the feasibility and limitations of parity readout of qubits with tunnel couplings tuned by flux.

cond-mat.mes-hall↗

arXiv2022

Quantum capacitance of a superconducting subgap state in an electrostatically floating dot-island

We study a hybrid device defined in an InAs nanowire with an epitaxial Al shell that consists of a quantum dot in contact with a superconducting island. The device is electrically floating, prohibiting transport measurements, but providing access to states that would otherwise be highly excited and unstable. Radio-frequency reflectometry with lumped-element resonators couples capacitatively to the quantum dot, and detects the presence of discrete subgap states. We perform a detailed study of the case with no island states, but with quantum-dot-induced subgap states controlled by the tunnel coupling. When the gap to the quasi-continuum of the excited states is small, the capacitance loading the resonator is strongly suppressed by thermal excitations, an effect we dub "thermal screening". The resonance frequency shift and changes in the quality factor at charge transitions can be accounted for using a single-level Anderson impurity model. The established measurement method, as well as the analysis and simulation framework, are applicable to more complex hybrid devices such as Andreev molecules or Kitaev chains.

cond-mat.mes-hall↗

arXiv2022

Variable and orbital-dependent spin-orbit field orientations in a InSb double quantum dot characterized via dispersive gate sensing

Utilizing dispersive gate sensing (DGS), we investigate the spin-orbit field ($\textbf{B}_{SO}$) orientation in a many-electron double quantum dot (DQD) defined in an InSb nanowire. While characterizing the inter-dot tunnel couplings, the measured dispersive signal depends on the electron charge occupancy, as well as on the amplitude and orientation of the external magnetic field. The dispersive signal is mostly insensitive to the external field orientation when a DQD is occupied by a total odd number of electrons. For a DQD occupied by a total even number of electrons, the dispersive signal is reduced when the finite external magnetic field aligns with the effective $\textbf{B}_{SO}$ orientation. This fact enables the identification of $\textbf{B}_{SO}$ orientations for different DQD electron occupancies. The $\textbf{B}_{SO}$ orientation varies drastically between charge transitions, and is generally neither perpendicular to the nanowire nor in the chip plane. Moreover, $\textbf{B}_{SO}$ is similar for pairs of transitions involving the same valence orbital, and varies between such pairs. Our work demonstrates the practicality of DGS in characterizing spin-orbit interactions in quantum dot systems, without requiring any current flow through the device.

cond-mat.mes-hall↗