arXiv
Verdict: NotableToward Joint Optimization of Circuit Depth and Training Data Size in Adaptively Grown Quantum Classifiers
Building a quantum model involves a tradeoff: how complex the circuit should be, and how much training data it needs.
Quantum machines, new materials, and the universe at every scale.
arXiv
Verdict: NotableBuilding a quantum model involves a tradeoff: how complex the circuit should be, and how much training data it needs.
We present a systematic X-ray spectral analysis of the 2019 and 2022 outbursts of the accreting millisecond pulsar SAX J1808.4-3658 with extit NICER with a particular emphasis on the nature of the longstanding sim 1…
Estimates of the quantum resources needed to run fault-tolerant algorithms are almost always reported as single numbers, even though they rest on uncertain hardware parameters and on cost models that disagree.
Extracting spectral properties such as energy position, broadening, and spectral weight from dielectric spectra is critical for interpreting collective electronic excitations in many-body physics.
JWST/NIRCam imaging has enabled efficient selection of a large number of galaxy candidates at very high redshifts.
Quantum key distribution (QKD) promises theoretically secure communication.
Photonic integrated circuits (PICs) operating in the visible spectral range are crucial for quantum technologies, optical sensing, and nonlinear optics applications.