{"total":10,"items":[{"citing_arxiv_id":"2605.22275","ref_index":14,"ref_count":1,"confidence":0.55,"is_internal_anchor":false,"paper_title":"Adaptive Measurement Allocation for Learning Kernelized SVMs Under Noisy Observations","primary_cat":"cs.LG","submitted_at":"2026-05-21T10:19:23+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"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.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.17587","ref_index":28,"ref_count":1,"confidence":0.55,"is_internal_anchor":false,"paper_title":"Large-Scale Quantum Kernels for Hyperspectral Data Classification","primary_cat":"quant-ph","submitted_at":"2026-05-17T18:32:12+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"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.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.11823","ref_index":1,"ref_count":1,"confidence":0.55,"is_internal_anchor":false,"paper_title":"Adiabatic Quantum Simulation of the Topological Su--Schrieffer--Heeger--Hubbard Model","primary_cat":"quant-ph","submitted_at":"2026-05-12T09:10:58+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"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.","context_count":1,"top_context_role":"background","top_context_polarity":"background","context_text":"on future large-scale quantum computers. Index Terms-Adiabatic quantum simulation, Hamiltonian simulation, Topological invariants, Su-Schrieffer-Heeger model, Hubbard model. I. INTRODUCTION Simulating interacting many-body systems is widely re- garded as one of the most promising near-term applications of quantum computation in the noisy intermediate-scale quantum (NISQ) era [1], [2]. Classical numerical methods often become intractable because the Hilbert space grows exponentially with system size [3]-[5]. Quantum computers, by contrast, provide a natural platform for representing, evolving, and measuring quantum states [6], potentially enabling the study of interacting quantum systems beyond the reach of classical approaches [7]."},{"citing_arxiv_id":"2605.11529","ref_index":1,"ref_count":1,"confidence":0.55,"is_internal_anchor":false,"paper_title":"QuBridge: Layer-wise Fidelity Decomposition in Quantum Computation Pipeline","primary_cat":"quant-ph","submitted_at":"2026-05-12T04:53:56+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"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.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.04604","ref_index":27,"ref_count":1,"confidence":0.55,"is_internal_anchor":false,"paper_title":"Generative Quantum-inspired Kolmogorov-Arnold Eigensolver","primary_cat":"quant-ph","submitted_at":"2026-05-06T07:53:55+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"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.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.04459","ref_index":4,"ref_count":1,"confidence":0.55,"is_internal_anchor":false,"paper_title":"Triage: An Adaptive Parallel Window Decoding Scheduler for Real-time Fault-Tolerant Quantum Computation","primary_cat":"quant-ph","submitted_at":"2026-05-06T03:39:24+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"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.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.26430","ref_index":3,"ref_count":1,"confidence":0.55,"is_internal_anchor":false,"paper_title":"A Multi-Level Integrity Evaluation Framework for Quantum Circuits under Controlled Anomaly Injection","primary_cat":"quant-ph","submitted_at":"2026-04-29T08:39:54+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"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.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.24475","ref_index":1,"ref_count":1,"confidence":0.55,"is_internal_anchor":false,"paper_title":"Improving Zero-Noise Extrapolation via Physically Bounded Models","primary_cat":"quant-ph","submitted_at":"2026-04-27T13:44:37+00:00","verdict":"CONDITIONAL","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"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.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.19426","ref_index":2,"ref_count":1,"confidence":0.55,"is_internal_anchor":false,"paper_title":"Noise-Induced Landscape Distortion in QAOA for Constrained Binary Optimization: Empirical Characterization on IBM Quantum Hardware","primary_cat":"quant-ph","submitted_at":"2026-04-21T12:55:50+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"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.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.18285","ref_index":14,"ref_count":1,"confidence":0.55,"is_internal_anchor":false,"paper_title":"EQE-QAOA: An Equivalence-Preserving Qubit Efficient Framework for Combinatorial Optimization","primary_cat":"cs.ET","submitted_at":"2026-04-20T13:57:49+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"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.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null}],"limit":50,"offset":0}