5 papers
g-tensor Optimization in Ge/SiGe Quantum Dots
Aram Shojaei, Edmondo Valvo, Maximilian Rimbach-Russ +2
Planar germanium heterostructures hosting hole-spin qubits are among the leading platforms for scalable semiconductor-based quantum computing. Yet, device performance is hindered b…
Accurate ground states of lattice gauge theory in 2+1D and 3+1D
Thomas Spriggs, Eliska Greplova, Juan Carrasquilla +1
We present a neural network wavefunction framework for solving non-Abelian lattice gauge theories in a continuous group representation. Using a combination of equivariant n…
Adiabatic Fine-Tuning of Neural Quantum States Enables Detection of Phase Transitions in Weight Space
Vinicius Hernandes, Thomas Spriggs, Saqar Khaleefah +1
Neural quantum states (NQS) have emerged as a powerful tool for approximating quantum wavefunctions using deep learning. While these models achieve remarkable accuracy, understandi…
Unified evolutionary optimization for high-fidelity spin qubit operations
Sam R. Katiraee-Far, Yuta Matsumoto, Brennan Undseth +9
Developing optimal strategies to calibrate quantum processors for high-fidelity operation is one of the outstanding challenges in quantum computing today. Here, we demonstrate mult…
Data needs and challenges for quantum dot devices automation
Justyna P. Zwolak, Jacob M. Taylor, Reed W. Andrews +17
Gate-defined quantum dots are a promising candidate system for realizing scalable, coupled qubit systems and serving as a fundamental building block for quantum computers. However,…