Zero-noise extrapolation has a finite-shot help-harm boundary below which it increases local mean-squared error due to variance penalties outweighing bias reduction.
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Hardware-efficient varia- tional quantum eigensolver for small molecules and quantum magnets
14 Pith papers cite this work, alongside 3,042 external citations. Polarity classification is still indexing.
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CV-ADAPT-VQE with tailored symmetry-preserving pools achieves significantly shallower circuits than Hamiltonian-based VQE for bosonic lattice models in GPU classical simulations.
Hybrid agent with variational quantum circuits for feature extraction in hierarchical RL outperforms classical baselines with 66% parameter savings, but quantum value estimation degrades results.
A new QNN architecture with unified graph, HAL, and ONNX pipeline enables cross-framework and cross-hardware QML with training time within 8% of native implementations and identical accuracy on Iris, Wine, and MNIST-4 tasks.
ZAPT2 frozen natural orbitals reduce virtual space for systematic convergence of open-shell T1-S0 gaps in CASCI and iQCC quantum eigensolvers, demonstrated on H2O2, O2, CH2 and Ir(ppy)3.
Quantum circuits for single and double fermionic excitations on ion traps reduce MS gate counts by factors of 2 and 4 respectively by using global interactions for optimal parallelism.
An adaptive damping and DIIS protocol stabilizes QmDFT embedding with hybrid functionals on 10 PAHs, yielding LDA agreement with FCI for ground states and B3LYP agreement with experimental gaps while bypassing explicit excited-state computations.
QADR decomposes n-qubit VQCs into local sub-circuits to reduce memory from O(2^n) to O(n * 2^{2d+1}) and mitigate barren plateaus, scaling to 2000 features on MNIST and wind turbine diagnostics while matching classical models.
Tensor-rank quantum and quantum-inspired PINNs solve the Merton HJB PDE with lower error and fewer parameters than classical fully connected PINNs.
For noisy near-term quantum devices, the paper recommends shallow angle encoding over amplitude encoding once two-qubit error rates exceed roughly 10^-3.
Hardware transpilation of parameterized quantum circuits produces ansatz-dependent shifts in expressibility (up to 125%) and trainability (up to 25%), altering the expected trade-off between them.
Introduces a JAX-based framework for pulse-level QML with composable ansatze, end-to-end pulse optimization, and Fourier-analytic diagnostics.
NISQ quantum simulation of spin-wave spectra in 2D chromium tri-halide magnets achieves agreement with classical benchmarks at quasi-constant wall-time scaling.
Review of proposals and experiments using coupled cavity arrays and superconducting circuits to realize many-body physics with photons, including Mott transitions, fractional quantum Hall states, and dissipative phase transitions.
citing papers explorer
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The finite-shot help-harm boundary of zero-noise extrapolation
Zero-noise extrapolation has a finite-shot help-harm boundary below which it increases local mean-squared error due to variance penalties outweighing bias reduction.
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Learning PDEs for Portfolio Optimization with Quantum Physics-Informed Neural Networks
Tensor-rank quantum and quantum-inspired PINNs solve the Merton HJB PDE with lower error and fewer parameters than classical fully connected PINNs.
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Quantum Simulation of Magnetic Materials: from Ab-Initio to NISQ
NISQ quantum simulation of spin-wave spectra in 2D chromium tri-halide magnets achieves agreement with classical benchmarks at quasi-constant wall-time scaling.
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Many-Body Physics and Quantum Simulations with Strongly Interacting Photons
Review of proposals and experiments using coupled cavity arrays and superconducting circuits to realize many-body physics with photons, including Mott transitions, fractional quantum Hall states, and dissipative phase transitions.