178 citations · 976 across the 49 of their papers we have counts for
11 papers · 1 filter
Overcoming Configuration Bottleneck: Modular Pathways to Stable Semiconductor Spin-Qubit Arrays
Justyna P. Zwolak, Anthony Sigillito
Over the past decade, semiconductor spin qubits have progressed from few-qubit demonstrations towards larger-scale devices fabricated in increasingly reproducible academic and indu…
FAlCon: A unified framework for algorithmic control of quantum dot devices
Tyler J. Kovach, Daniel Schug, Zach D. Merino +3
As spin-based quantum systems scale, their setup and control complexity increase sharply. In semiconductor quantum dot (QD) experiments, device-to-device variability, heterogeneous…
Colloquium: Advances in automation of quantum dot devices control
Justyna P. Zwolak, Jacob M. Taylor
Arrays of quantum dots (QDs) are a promising candidate system to realize scalable, coupled qubit systems and serve as a fundamental building block for quantum computers. In such se…
Toward Robust Autotuning of Noisy Quantum Dot Devices
Joshua Ziegler, Thomas McJunkin, E. S. Joseph +7
The current autotuning approaches for quantum dot (QD) devices, while showing some success, lack an assessment of data reliability. This leads to unexpected failures when noisy or…
Ray-based framework for state identification in quantum dot devices
Justyna P. Zwolak, Thomas McJunkin, Sandesh S. Kalantre +4
Quantum dots (QDs) defined with electrostatic gates are a leading platform for a scalable quantum computing implementation. However, with increasing numbers of qubits, the complexi…
Auto-tuning of double dot devices in situ with machine learning
Justyna P. Zwolak, Thomas McJunkin, Sandesh S. Kalantre +7
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 applicatio…
QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments
Justyna P. Zwolak, Sandesh S. Kalantre, Xingyao Wu +2
Over the past decade, machine learning techniques have revolutionized how research is done, from designing new materials and predicting their properties to assisting drug discovery…
Machine Learning techniques for state recognition and auto-tuning in quantum dots
Sandesh S. Kalantre, Justyna P. Zwolak, Stephen Ragole +4
Recent progress in building large-scale quantum devices for exploring quantum computing and simulation paradigms has relied upon effective tools for achieving and maintaining good…
Recurrent construction of optimal entanglement witnesses for 2N qubit systems
Justyna P. Zwolak, Dariusz Chruściński
We provide a recurrent construction of entanglement witnesses for a bipartite systems living in a Hilbert space corresponding to qubits ( qubits in each subsystem). Our con…
New tools for investigating positive maps in matrix algebras
Justyna Pytel Zwolak, Dariusz Chruściński
We provide a novel tool which may be used to construct new examples of positive maps in matrix algebras (or, equivalently, entanglement witnesses). It turns out that this can be us…
Stability of Frustration-Free Hamiltonians
Spyridon Michalakis, Justyna Pytel
We prove stability of the spectral gap for gapped, frustration-free Hamiltonians under general, quasi-local perturbations. We present a necessary and sufficient condition for stabi…