4 papers · 1 filter
Component-Level Inverse Design of Transmon Qubits Using Neural Networks
Olivia Seidel, Firas Abouzahr, Abhishek Chakraborty +11
Designing a superconducting qubit to realize specific Hamiltonian parameters typically requires iterating through a time and compute-intensive forward loop in which the designer ch…
Accelerating Quantum Tensor Network Simulations with Unified Path Variations and Non-Degenerate Batched Sampling
Taylor Lee Patti, Paavai Pari, Yang Gao +5
Quantum trajectory methods reduce the computational overhead of simulating noisy quantum systems, approximating them with stochastically sampled -entry quantum statevector…
GPU-accelerated Effective Hamiltonian Calculator
Abhishek Chakraborty, Taylor L. Patti, Brucek Khailany +2
Effective Hamiltonian calculations for large quantum systems can be both analytically intractable and numerically expensive using standard techniques. In this manuscript, we presen…
Augmenting Simulated Noisy Quantum Data Collection by Orders of Magnitude Using Pre-Trajectory Sampling with Batched Execution
Taylor L. Patti, Thien Nguyen, Justin G. Lietz +2
Classically simulating quantum systems is challenging, as even noiseless -qubit quantum states scale as . The complexity of noisy quantum systems is even greater, requiring…