Quantum circuits for coherent multilayer neural network inference achieve quadratic to polylogarithmic speedups over classical methods depending on quantum data access models for inputs and weights.
Title resolution pending
8 Pith papers cite this work. Polarity classification is still indexing.
8
Pith papers citing it
citation-role summary
background 3
citation-polarity summary
fields
quant-ph 8verdicts
UNVERDICTED 8roles
background 3representative citing papers
Quantum algorithm approximates k-th spectral gap Δ_k and midpoint μ_k of Hermitian matrix to εΔ_k error with O(N²/(ε² Δ_k²) polylog) QRAM complexity, claiming speedup for large gaps, plus Ω(N²) black-box lower bound.
New scalable QRAM simulator reveals post-selection constraints on error filtration and produces refined near-deterministic performance criteria.
Encodes M by N matrix into quantum state using Θ(log(MN)) qubits in O(log²(MN)) time via segment tree embedded in bucket brigade QRAM with constant ancillas and O(MN) memory cells.
Proposes a quantum-walker qRAM on a single binary tree using local operations that reduces resources while preserving optimal query complexity.
Quantum sieving for SVP in dimension 400 needs ~10^13 physical qubits and ~10^31 years under optimistic assumptions, offering no practical speedup over classical methods.
Encoding strategies for quantum fluid simulations trade off compactness against practicality in state preparation, measurement, boundary conditions, and nonlinear operations, with no single approach being universally optimal.
A comprehensive review organizing progress at the AI-quantum information intersection from both directions.
citing papers explorer
-
Accelerating Inference for Multilayer Neural Networks with Quantum Computers
Quantum circuits for coherent multilayer neural network inference achieve quadratic to polylogarithmic speedups over classical methods depending on quantum data access models for inputs and weights.
-
Spectral Gaps with Quantum Counting Queries and Oblivious State Preparation
Quantum algorithm approximates k-th spectral gap Δ_k and midpoint μ_k of Hermitian matrix to εΔ_k error with O(N²/(ε² Δ_k²) polylog) QRAM complexity, claiming speedup for large gaps, plus Ω(N²) black-box lower bound.
-
Refined Criteria for QRAM Error Suppression via Efficient Large-Scale QRAM Simulator
New scalable QRAM simulator reveals post-selection constraints on error filtration and produces refined near-deterministic performance criteria.
-
Efficient Quantum State Preparation with Bucket Brigade QRAM
Encodes M by N matrix into quantum state using Θ(log(MN)) qubits in O(log²(MN)) time via segment tree embedded in bucket brigade QRAM with constant ancillas and O(MN) memory cells.
-
A resource-efficient quantum-walker Quantum RAM
Proposes a quantum-walker qRAM on a single binary tree using local operations that reduces resources while preserving optimal query complexity.
-
On the practicality of quantum sieving algorithms for the shortest vector problem
Quantum sieving for SVP in dimension 400 needs ~10^13 physical qubits and ~10^31 years under optimistic assumptions, offering no practical speedup over classical methods.
-
Encoding strategies for quantum enhanced fluid simulations: opportunities and challenges
Encoding strategies for quantum fluid simulations trade off compactness against practicality in state preparation, measurement, boundary conditions, and nonlinear operations, with no single approach being universally optimal.
-
When AI meets quantum information: A comprehensive review
A comprehensive review organizing progress at the AI-quantum information intersection from both directions.