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20242026
most citedDynamically Generated Decoherence-Free Subspaces and Subsystems on Superconducting Qubits

11 citations · 20 across the 13 of their papers we have counts for

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quant-ph2026

Satisfying Quantum Codes: Physics-Informed and Hardware-Aware Code Design with SAT Solvers

Ben DalFavero, William M. Watkins, Margarite L. LaBorde +4

Although quantum error correction is widely believed to be necessary for impactful applications of quantum computers, the design of quantum error correction codes is largely done b…

quant-ph2026

Revealing Noise in Axial Motion Through Quantum Noise Spectroscopy on a Trapped Ion Processor

Vivian Maloney, Matthew Chow, Leigh Norris +7

Native noise processes in quantum processors are often difficult to isolate because multiple error mechanisms contribute to the same measured loss of coherence. Here we use dephasi…

quant-ph2026

Entanglement Scaling and Problem Structure in Quantum Approximate and Adiabatic Optimization Algorithms

Georgios Arapantonis, Paraj Titum, Gregory Quiroz

Entanglement is widely regarded as a key resource underlying the power of quantum algorithms and their potential to achieve quantum advantage. With the emergence of variational qua…

quant-ph2026

Assessing Spatiotemporally Correlated Noise in Superconducting Qubits via Pulse-Based Quantum Noise Spectroscopy

Mayra Amezcua, Leigh Norris, Tom Gilliss +4

Spatiotemporally correlated errors are widespread in quantum devices and are particularly adversarial to error correcting schemes. To characterize these errors, we propose and vali…

quant-ph2026

Quantum Noise Suppression at Scale with Crosstalk-Robust Gate Sets

Andy J. Goldschmidt, Emilio Peláez Cisneros, Ryan Sitler +3

We introduce crosstalk-robust gate sets, which are obtained using a novel, scalable optimal control problem exploiting locality. Through the suppression of pairwise quantum crossta…

quant-ph2026

Towards Predictive Quantum Algorithmic Performance: Modeling Time-Correlated Noise at Scale

Amit Jamadagni, Gregory Quiroz, Eugene Dumitrescu

Combining tensor network techniques with quantum autoregressive moving average models, we quantify the effects of time-correlated noise on quantum algorithms and predict their perf…