5 papers

quant-ph2026

Mitigating errors in state preparation and measurement with noncomputational states

Conrad J. Haupt, Almudena Carrera Vazquez, Laurin E. Fischer +2

Error mitigation has enabled quantum computing applications with over one hundred qubits and deep circuits. Many error mitigation methods are noise-aware, relying on a faithful cha…

cs.AR2026

Heterogeneous Mapping for Analog In-Memory Computing Accelerators: A Unified Workflow

Corey Lammie

Analog In-Memory Computing (AIMC) accelerators execute matrix-vector multiplications directly within memory arrays, reducing data movement and improving DNN inference efficiency. T…

quant-ph2026

Gradient Scalability and Taylor Surrogation of Quantum Cost Landscapes

Sabri Meyer, Francesco Scala, Francesco Tacchino +1

Variational Quantum Algorithms are promising candidates for near-term quantum computing, yet they face scalability challenges due to barren plateaus, where gradients vanish exponen…

cs.CL2026

Sparse Attention Remapping with Clustering for Efficient LLM Decoding on PIM

Zehao Fan, Garrett Gagnon, Zhenyu Liu +1

Transformer-based models are the foundation of modern machine learning, but their execution, particularly during autoregressive decoding in large language models (LLMs), places sig…

quant-ph2026

Spectral Gaps with Quantum Counting Queries and Oblivious State Preparation

Almudena Carrera Vazquez, Aleksandros Sobczyk

Approximating the -th spectral gap and the corresponding midpoint of an Hermitian matrix with eigenvalues $λ_1…