11 papers
Cautious optimism for deep parameterized quantum circuits
Marie Kempkes, Elies Gil-Fuster, Carlos Bravo-Prieto +5
A central challenge in quantum machine learning is understanding the scaling behavior of parameterized quantum circuits (PQCs). In particular, it remains unclear how their performa…
Multiple-time Quantum Imaginary Time Evolution
Julio Del Castillo, Mats Granath, Evert van Nieuwenburg
Quantum Imaginary-Time Evolution (QITE) is a powerful method for preparing ground states on quantum hardware. However, executing QITE has costly measurement budgets for general Ham…
Evidence of Quantum Machine Learning Advantage with Tens of Noisy Qubits
Onur Danaci, Yash J. Patel, Riccardo Molteni +3
Learning problems involving quantum data are natural candidates for demonstrating an advantage in quantum machine learning. Recent results indicate that, for certain tasks and unde…
Stoquastic permutationally invariant Bell operators
Jan Li, Owidiusz Makuta, Evert van Nieuwenburg +1
As Hermitian operators, many-body Bell operators can naturally be identified as many-body Hamiltonians. An important subclass of such Hamiltonians is the stoquastic class, characte…
Extracting Photon-Number Information from Superconducting Nanowire Single-Photon Detectors Traces via Mean-Derivative Projection
I. S. Kuijf, F. B. Baalbergen, L. Seldenthuis +2
Photon-number resolved detection with superconducting nanowire single-photon detectors (SNSPDs) attracts increasing interest, but lacks a systematic framework for interpreting and…
Coherence Protection for Mobile Spin Qubits in Silicon
Jan A. Krzywda, Yuta Matsumoto, Maxim De Smet +6
Mobile spin qubit architectures promise flexible connectivity for efficient quantum error correction and relaxed device layout constraints, but their viability rests on preserving…