Integrating amplitude estimation into QNN readout achieves O(1/N) estimation error with one shot instead of the usual O(1/sqrt(N)) Monte Carlo scaling.
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Pseudorandom Generators with- out the XOR Lemma
15 Pith papers cite this work, alongside 2,651 external citations. Polarity classification is still indexing.
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A dual Fourier-PSF and contour-PSF framework resolves the smoothness-sparsity trade-off for efficient quantum simulation of singular and holomorphic matrix functions.
New scalable QRAM simulator reveals post-selection constraints on error filtration and produces refined near-deterministic performance criteria.
Lattice-surgery scheduling is mapped to 3D path embedding and solved with look-ahead Dijkstra projection, yielding 3.8x lower execution time on quantum phase estimation benchmarks versus greedy scheduling.
The 2D HLF problem lies in QNC^0 but not in AC^0, with an exponential average-case correlation lower bound against AC^0 circuits.
Quantum circuits show high average condition (97.56%) and decision (97.63%) coverage but lower path coverage (71.84%), with probabilistic versions adding confidence levels (averages 88.87%, 88.65%, 37.18%); mutation testing reveals weak or no correlation between structural coverage and fault finding
CBMD decomposes non-Hermitian evolution operators into Hermitian LCU terms via a matrix residue theorem, matching known optimal query bounds and offering a route to polynomial matrix functions.
VarQEC uses a distinguishability loss as a machine-learning objective to variationally discover resource-efficient encoding circuits optimized for given noise models.
QARMA applies transformer-augmented reinforcement learning to qubit allocation and reuse in modular quantum systems, reporting up to 86% average reduction in inter-core communications versus optimized Qiskit baselines.
Quantum algorithm encodes regularized Stokes equations via Schrödingerisation into an explicit circuit with claimed exponential speedup in dimensionality, tested on Qiskit.
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.
Large qLDPC blocks in distributed quantum computing enable Pauli-based computation to run up to 10x faster than surface codes for optimization algorithms by using spare nodes to bypass serialization bottlenecks.
Noise in lattice-based cryptography fails to erase information permanently, so quantum error correction and learning can extract secrets, making unconditional post-quantum security claims premature.
A topical review unifying statistical mechanics, tensor network, and AI approaches to approximate maximum likelihood decoding for quantum error correction codes.
citing papers explorer
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Single-shot quantum neural networks with amplitude estimation
Integrating amplitude estimation into QNN readout achieves O(1/N) estimation error with one shot instead of the usual O(1/sqrt(N)) Monte Carlo scaling.
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A Unified Poisson Summation Framework for Generalized Quantum Matrix Transformations
A dual Fourier-PSF and contour-PSF framework resolves the smoothness-sparsity trade-off for efficient quantum simulation of singular and holomorphic matrix functions.
-
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.
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Efficient and high-performance routing of lattice-surgery paths on three-dimensional lattice
Lattice-surgery scheduling is mapped to 3D path embedding and solved with look-ahead Dijkstra projection, yielding 3.8x lower execution time on quantum phase estimation benchmarks versus greedy scheduling.
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Exponential separation between shallow quantum circuits and unbounded fan-in shallow classical circuits
The 2D HLF problem lies in QNC^0 but not in AC^0, with an exponential average-case correlation lower bound against AC^0 circuits.
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Probabilistic Condition, Decision and Path Coverage of Circuit-based Quantum Programs
Quantum circuits show high average condition (97.56%) and decision (97.63%) coverage but lower path coverage (71.84%), with probabilistic versions adding confidence levels (averages 88.87%, 88.65%, 37.18%); mutation testing reveals weak or no correlation between structural coverage and fault finding
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Quantum Simulation of Non-Hermitian Special Functions and Dynamics via Contour-based Matrix Decomposition
CBMD decomposes non-Hermitian evolution operators into Hermitian LCU terms via a matrix residue theorem, matching known optimal query bounds and offering a route to polynomial matrix functions.
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Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction
VarQEC uses a distinguishability loss as a machine-learning objective to variationally discover resource-efficient encoding circuits optimized for given noise models.
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Learning-Optimized Qubit Mapping and Reuse to Minimize Inter-Core Communication in Modular Quantum Architectures
QARMA applies transformer-augmented reinforcement learning to qubit allocation and reuse in modular quantum systems, reporting up to 86% average reduction in inter-core communications versus optimized Qiskit baselines.
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Quantum Simulation of Stokes Flow via Schr\"odingerisation and Artificial Compressibility
Quantum algorithm encodes regularized Stokes equations via Schrödingerisation into an explicit circuit with claimed exponential speedup in dimensionality, tested on Qiskit.
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Quantum Algorithm for Distributed Reduction of Entanglements (QADR): A Trainable and Simulation-Efficient QML Framework
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.
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Space-Time Tradeoffs of Pauli-Based Computation in Distributed qLDPC Architectures
Large qLDPC blocks in distributed quantum computing enable Pauli-based computation to run up to 10x faster than surface codes for optimization algorithms by using spare nodes to bypass serialization bottlenecks.
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Fundamental Limitations of Post-Quantum Cryptographic Architectures
Noise in lattice-based cryptography fails to erase information permanently, so quantum error correction and learning can extract secrets, making unconditional post-quantum security claims premature.
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Maximum Likelihood Decoding of Quantum Error Correction Codes
A topical review unifying statistical mechanics, tensor network, and AI approaches to approximate maximum likelihood decoding for quantum error correction codes.
- Probabilistic Computers (and Hence Quantum Computers) Are Rigorously More Powerful Than Classical Deterministic Computers, and Derandomization