GQKAE uses quantum-inspired Kolmogorov-Arnold networks to reduce parameters by 66% in generative quantum eigensolvers while achieving chemical accuracy on H4, N2, LiH, and other molecules.
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Quantum computing in the NISQ era and beyond
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Introduces geometric-sensitivity and active-set-instability signals to adaptively allocate measurements for kernel SVMs under Bernoulli noise, with theory and synthetic/quantum-kernel experiments showing improved margin and support-vector recovery.
A gate-based adiabatic quantum simulation framework for the SSHH model, validated by classical circuit simulations, shows topological signatures remain robust to weak Hubbard interactions but collapse beyond a symmetry-breaking threshold, with polynomial resource scaling.
Triage is an adaptive parallel window decoding scheduler that reduces average logical error rates by 52.6% compared to standard temporal parallelism while keeping stalls low under scarce classical resources.
Physically bounded extrapolation models for zero-noise extrapolation reduce unphysical predictions and improve stability compared to unbounded fits on large synthetic benchmarks and real hardware.
Noise on IBM quantum hardware compresses the QAOA variational energy landscape span by 24-30% without shifting the global minimum for three constrained QUBO portfolio optimization instances.
EQE-QAOA reduces qubit count for QAOA while exactly preserving optimization performance by confining dynamics to an invariant subspace and applying an isometric re-encoding.
Simulated fidelity quantum kernels achieve competitive or better accuracy than RBF kernels on Indian Pines binary and multiclass tasks and Methane Detection data without heavy dimensionality reduction.
QuBridge decomposes quantum pipelines into qubit selection, pulse assignment, and error encoding layers, quantifying their fidelity impacts via ablation on teleportation under IBM noise models.
A three-metric framework (SIS, OIS, IGS) detects anomalies in quantum circuits more reliably than structural checks alone, as shown by controlled injections where high structural similarity still misses most behavioral deviations.
citing papers explorer
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Generative Quantum-inspired Kolmogorov-Arnold Eigensolver
GQKAE uses quantum-inspired Kolmogorov-Arnold networks to reduce parameters by 66% in generative quantum eigensolvers while achieving chemical accuracy on H4, N2, LiH, and other molecules.
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Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations
Introduces geometric-sensitivity and active-set-instability signals to adaptively allocate measurements for kernel SVMs under Bernoulli noise, with theory and synthetic/quantum-kernel experiments showing improved margin and support-vector recovery.
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Adiabatic Quantum Simulation of the Topological Su--Schrieffer--Heeger--Hubbard Model
A gate-based adiabatic quantum simulation framework for the SSHH model, validated by classical circuit simulations, shows topological signatures remain robust to weak Hubbard interactions but collapse beyond a symmetry-breaking threshold, with polynomial resource scaling.
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Triage: An Adaptive Parallel Window Decoding Scheduler for Real-time Fault-Tolerant Quantum Computation
Triage is an adaptive parallel window decoding scheduler that reduces average logical error rates by 52.6% compared to standard temporal parallelism while keeping stalls low under scarce classical resources.
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Improving Zero-Noise Extrapolation via Physically Bounded Models
Physically bounded extrapolation models for zero-noise extrapolation reduce unphysical predictions and improve stability compared to unbounded fits on large synthetic benchmarks and real hardware.
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Noise-Induced Landscape Distortion in QAOA for Constrained Binary Optimization: Empirical Characterization on IBM Quantum Hardware
Noise on IBM quantum hardware compresses the QAOA variational energy landscape span by 24-30% without shifting the global minimum for three constrained QUBO portfolio optimization instances.
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EQE-QAOA: An Equivalence-Preserving Qubit Efficient Framework for Combinatorial Optimization
EQE-QAOA reduces qubit count for QAOA while exactly preserving optimization performance by confining dynamics to an invariant subspace and applying an isometric re-encoding.
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Large-Scale Quantum Kernels for Hyperspectral Data Classification
Simulated fidelity quantum kernels achieve competitive or better accuracy than RBF kernels on Indian Pines binary and multiclass tasks and Methane Detection data without heavy dimensionality reduction.
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QuBridge: Layer-wise Fidelity Decomposition in Quantum Computation Pipeline
QuBridge decomposes quantum pipelines into qubit selection, pulse assignment, and error encoding layers, quantifying their fidelity impacts via ablation on teleportation under IBM noise models.
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A Multi-Level Integrity Evaluation Framework for Quantum Circuits under Controlled Anomaly Injection
A three-metric framework (SIS, OIS, IGS) detects anomalies in quantum circuits more reliably than structural checks alone, as shown by controlled injections where high structural similarity still misses most behavioral deviations.