19 papers
Hardware-Aware Compilation and Execution of Bivariate Bicycle Codes on Neutral-Atom Systems
Jason Ludmir, Aditya Ranjan, Nicholas S. DiBrita +2
Quantum computers are noisy; without quantum error correction (QEC), deep programs fail as qubits lose information due to decoherence. Among QEC approaches, bivariate bicycle (BB)…
PaQit: Energy-Runtime-Fidelity Co-Optimization for Neutral Atom Quantum Computers
Jason Ludmir, Tirthak Patel
Neutral-atom quantum computers provide a scalable platform for large-scale quantum computation due to their all-optical control, room-temperature operation, and flexible lattice ge…
Identity-Paired Progressive Depth Training: When Trainability Persists Beyond Expressibility
Athanasios Hadjidimoulas, Tirthak Patel, Anastasios Kyrillidis
Variational Quantum Algorithms (VQAs) are a leading paradigm for near-term quantum computing, yet their training suffers from sensitivity to circuit depth, initialization, and land…
HattriQ: Designing Integrated Gradients for Feature Attribution in Quantum Machine Learning
Nicholas S. DiBrita, Jason Han, Younghyun Cho +2
Quantum machine learning (QML) algorithms have demonstrated early promise across hardware platforms, but remain difficult to interpret due to the inherent opacity of quantum state…
Domain-Aware Probability Sampling for Hybrid Quantum Systems using Bayesian Optimization
Nicholas S. DiBrita, Jason Han, Krishna Bhatia +3
We study the problem of probability distribution matching and sampling on near-term quantum computers, aiming to construct parameterized circuits that generate samples from a targe…
TuniQ: Autotuning Compilation Passes for Quantum Workloads at Scale for Effectiveness and Efficiency
Mohammad Abrarul Hasanat, Jason Ludmir, Tirthak Patel +1
Quantum processors are being integrated into HPC ecosystems as co-processors, where compilation of quantum circuits into hardware-executable form determines both output fidelity an…