arXiv subjects

Joan Étude Arrow

Publications and source records attributed to Joan Étude Arrow.

3 recordsLinked to original sources

arXiv2026

Benchmarking Quantum Simulations of the Lipkin-Meshkov-Glick Model Using Large Tensor Networks

As quantum computing matures, it is critical to benchmark its real-world problem solving performance against competitive classical methods, such as tensor networks. In this work, we leverage the Density Matrix Renormalization Group (DMRG) algorithm to compute ground state energies of the Lipkin Meshkov Glick (LMG) model as a comparative benchmark against popular noisy intermediate-scale (NISQ) algorithms like the Variational Quantum Eigensolver (VQE) and Sample-Based Quantum Diagonalization (SQD) method. By running DMRG on the NERSC Perlmutter supercomputer, we provide one of the largest LMG ground state energy datasets in literature, containing accurate ground state energies for systems up to 1400 particles. We compare these results with VQE and SQD implementations on an IBM Eagle quantum computer for comparison. VQE achieved results within 1 percent error for 6 particles, while exceeding that threshold for all other values while SQD extended that range to 17 particles, suggesting that in a noisy intermediate scale quantum era, subspace-based approaches may strike the best balance between accuracy, circuit depth, and noise resilience.

quant-ph↗

arXiv2026

Hybrid Quantum-Classical Machine Learning Algorithms for Multi-Output Time-Series Forecasting at Utility Scale

Multi-output time-series forecasting in energy systems is challenging because of nonlinear dynamics, multi-scale seasonality, and strong dependencies across correlated series. In this work, we investigate two hybrid quantum-classical frameworks for multi-stream time-series forecasting on a real Smart Meter dataset comprising 103 household electricity consumption time-series, with experiments executed on the $ibm\_marrakesh$ superconducting quantum processor. The first model, Kernelized Quantum Reservoir Computing with Repeated Measurement (KQRC-RM), combines coupled quantum reservoirs, ancilla-assisted repeated measurement, and kernelized readouts to model temporal dynamics and cross-stream correlations jointly. For a 3-stream time-series input and output, the KQRC-RM model using 114 qubits achieves an MAE of 0.0811 on MPS simulator (36.92\% improvement over its classical analog) whereas performance degrades to an MAE of 0.1524 on hardware. The second, a Projected Quantum Kernel Gaussian Process (QGP), replaces fidelity-based kernels with projected kernels constructed from local reduced-state statistics. Using a topology-aware 100-qubit QGP model to predict 100 multi-output time-series values, we observe 49\% of time-series outputs achieve high-accuracy predictions (MAE $<0.15$), with an average MAE of $0.082$ for this low-error group. The medium-error regime (MAE $0.15$-$0.35$) has an average MAE of $0.229$, while the high-error regime (MAE $>0.35$) has an average MAE of $0.664$. Overall, this reduces the average MAE relative to the classical GP baseline by 62.01\% on MPS simulator and 40.37\% on hardware. Together, these results demonstrate the feasibility of hybrid quantum machine learning for multi-input, multi-output time-series forecasting at the 100+ qubit scale on NISQ devices.

quant-ph↗

arXiv2023

A Holistic Approach to Quantum Ethics Education

This paper first provides an overview of the growing subfield of quantum ethics, including a working definition; research to date into social, economic, and political implications of quantum technologies; and directions for future research. Second, it introduces the Quantum Ethics Project (QEP), its activities to date, and its organizing philosophy. The third section reports on QEP's ongoing curriculum development work, i.e. creating one of the first full-length courses on Ethics and Social Impacts of Quantum Technology. We outline the pedagogical approach being taken in the course design, including key learning outcomes, topic areas, teaching methods, and rationale. Finally, we discuss current limitations and future areas of attention, such as drawbacks to teaching ethical reasoning and ideas for assessment and implementation.

physics.ed-ph↗