arXiv subjects

Jason Chadwick

Publications and source records attributed to Jason Chadwick.

4 recordsLinked to original sources

arXiv2026

ReloQate: Transient Drift Detection and In-Situ Recalibration in Surface Code Quantum Error Correction

Quantum error correction (QEC) promises to exponentially suppress qubit noise, but typically assumes spatially-uniform and temporally-constant noise rates. However, real quantum hardware exhibits variation in noise levels over time, which will be amplified by QEC if not addressed. To mitigate this drift in error rates, we leverage transient information readily available in surface code quantum error correction to predict logical error rates (LER) in real time. We infer a prediction model by sampling physical error rates from real hardware, and mapping detector fire rate (DFR), or parity of stabilizer measurements across QEC rounds, to LER. This allows for on-the-fly LER predictions without the typical characterization overhead required to determine LER. This method can easily be extended to other stabilizer codes. Importantly, we observe that this prediction should be accurate yet conservative (i.e. give an upper estimate) to enable appropriately fast responses to real-time physical error changes. That is, responses should be executed marginally ahead of time to allow for their execution to complete, and minimize time spent (ideally none) above intolerable error rates. More importantly, we pair this predictor with a scheme which remaps drifted logical qubits to fresh tiles in a patch-based architecture while their original tiles are recalibrated. Our results demonstrate DFR-based prediction to be an effective LER predictor, and remapping as a spatially efficient and timely mitigation response for small code distances, both of which are significant steps in furthering practical QEC.

quant-ph↗

arXiv2026

Spacetime-Efficient and Hardware-Compatible Complex Quantum Logic Units in qLDPC Codes

Quantum low-density parity-check (qLDPC) codes offer a promising route to scalable fault-tolerant quantum computing due to their substantially reduced footprint. However, these gains can be diluted at utility scale if we cannot also realize space-time efficient logical operations for relevant quantum applications. We present RASCqL, a reaction-time-limited architecture for space-time efficient complex-instruction-set quantum computation with qLDPC logic. RASCqL supports key algorithmic subroutines such as quantum arithmetic and state preparation directly within co-designed qLDPC codes, achieving $2\times$ to $7\times$ reductions in qubit footprint while maintaining space-time volume comparable to state-of-the-art transversal surface-code architectures. Unlike prior approaches that aim for versatile logical instruction sets for arbitrary circuits, RASCqL adopts an application-tailored code modification that embeds specific complex Clifford transformations useful for common subroutines as virtually implementable operations arising from code automorphisms. RASCqL further leverages parallel physical operations available in reconfigurable neutral-atom arrays to enable fast QEC cycles and high-fidelity transversal operations. At the cost of increased design complexity and specialization, RASCqL can improve end-to-end resource estimates for applications such as factoring and quantum chemistry simulation in both footprint and space-time volume under realistic physical error rates of approximately $2\times10^{-3}$ to $5\times10^{-4}$, without requiring additional hardware capabilities. These results demonstrate that qLDPC codes can serve as complex quantum logic units for useful quantum algorithms, extending their practical utility in fault-tolerant quantum computing architectures.

quant-ph↗

arXiv2023

Qompress: Efficient Compilation for Ququarts Exploiting Partial and Mixed Radix Operations for Communication Reduction

Quantum computing is in an era of limited resources. Current hardware lacks high fidelity gates, long coherence times, and the number of computational units required to perform meaningful computation. Contemporary quantum devices typically use a binary system, where each qubit exists in a superposition of the $\ket{0}$ and $\ket{1}$ states. However, it is often possible to access the $\ket{2}$ or even $\ket{3}$ states in the same physical unit by manipulating the system in different ways. In this work, we consider automatically encoding two qubits into one four-state qu\emph{quart} via a \emph{compression scheme}. We use quantum optimal control to design efficient proof-of-concept gates that fully replicate standard qubit computation on these encoded qubits. We extend qubit compilation schemes to efficiently route qubits on an arbitrary mixed-radix system consisting of both qubits and ququarts, reducing communication and minimizing excess circuit execution time introduced by longer-duration ququart gates. In conjunction with these compilation strategies, we introduce several methods to find beneficial compressions, reducing circuit error due to computation and communication by up to 50\%. These methods can increase the computational space available on a limited near-term machine by up to 2x while maintaining circuit fidelity.

quant-ph↗

arXiv2022

Time-Efficient Qudit Gates through Incremental Pulse Re-seeding

Current efforts to build quantum computers focus mainly on the two-state qubit, which often involves suppressing readily-available higher states. In this work, we break this abstraction and synthesize short-duration control pulses for gates on generalized d-state qudits. We present Incremental Pulse Re-seeding, a practical scheme to guide optimal control software to the lowest-duration pulse by iteratively seeding the optimizer with previous results. We find a near-linear relationship between Hilbert space dimension and gate duration through explicit pulse optimization for one- and two-qudit gates on transmons. Our results suggest that qudit operations are much more efficient than previously expected in the practical regime of interest and have the potential to significantly increase the computational power of current hardware.

quant-ph↗