Geometric characterization of optimal classical RACs with explicit constructions, optimality proofs for several families, and a quantum RAC establishing classical-quantum separation for the (2^k-1, k) family.
hub Canonical reference
Almudever, and Sebastian Feld
Canonical reference. 100% of citing Pith papers cite this work as background.
20
Pith papers citing it
Background
100% of classified citations
hub tools
citation-role summary
background 7
citation-polarity summary
verdicts
UNVERDICTED 20roles
background 6polarities
background 6representative citing papers
QRisk isolates backend-specific abnormal error patterns on NISQ devices via delta debugging and mitigates them with commuting gate swaps, cutting excess noise by 24-45% on IBM backends where noise models predict no difference.
Qurator jointly optimizes queue time and fidelity for hybrid quantum-classical workflows across providers using quantum-aware DAG scheduling and a unified logarithmic fidelity score, achieving 30-75% wait reduction at high load with bounded accuracy cost.
A hybrid GHZ-BSM routing strategy outperforms pure BSM routing in square grid quantum networks but requires global-information adaptations to beat BSM in complex topologies such as Waxman, scale-free, and SURFnet.
Co-optimization of flexible Iceberg error-detection gadgets with QAOA via tree search improves success probability and post-selection on Quantinuum H2-1 hardware up to 34 algorithmic qubits.
Lottery BP adds randomness to belief propagation decoding and uses syndrome voting to achieve far higher accuracy on topological quantum codes while reducing reliance on expensive global decoders.
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.
Presents a tensor-parallel distributed MPS method with block-cyclic partitioning and pivoted QR that emulates Google's RCS benchmark at bond dimension 16384 on 32 nodes, claiming three orders of magnitude better accuracy than prior methods.
Constructions for universal quantum computation in the [[n,n-2,2]] error-detecting code detect single-gate errors at computation end, providing weak fault tolerance with reduced overhead versus full error correction.
Three scheduling strategies for hybrid quantum-HPC systems cut classical resource use by up to 64% or boost QPU utilization depending on workload balance, validated on real hardware.
A new GPU quantum simulator framework achieves 64x-146x speedups for 20-28 qubit circuits via backend selection, gate fusion, and adaptive precision while integrating with Qiskit and others.
Detailed revision of a single phase-kickback item on a quantum computing survey reveals complex student reasoning and supports triangulating multiple data types when building conceptual assessments.
Quantum walks integrated with variational circuits and CUDA-Q acceleration generate high-fidelity adaptive probability distributions for 1D financial modeling and 2D digit patterns.
A topical review unifying statistical mechanics, tensor network, and AI approaches to approximate maximum likelihood decoding for quantum error correction codes.
The authors describe a visionary layered architecture for unifying classical and quantum compute resources under a single job submission and scheduling interface.
Grover quantum search with classical Siamese pre-processing generates magic squares on small grids and confirms the expected quadratic query advantage over brute-force and backtracking.
Qimax parallelizes the extended stabilizer formalism for GPU execution and reports faster simulation of near-Clifford circuits than Qiskit or Pennylane in selected cases.
The paper reviews QUDO, T-QUDO and HOBO formulations, provides explicit encodings between them, discusses limitations, and gives examples for knapsack, TSP and games including N-Queens and Peg Solitaire.
Tensor networks developed for quantum states are reviewed as tools for machine learning models, with assessment of their potential computational, explanatory, and privacy advantages alongside remaining challenges.
A synthesis of expert insights from the ADAC Quantum Computing Working Group and member survey on the complementary roles of quantum and classical high-performance computing in future hybrid infrastructures.
citing papers explorer
-
Random Access Codes: Explicit Constructions, Optimality, and Classical-Quantum Gaps
Geometric characterization of optimal classical RACs with explicit constructions, optimality proofs for several families, and a quantum RAC establishing classical-quantum separation for the (2^k-1, k) family.
-
Isolating Recurring Execution-Dependent Abnormal Patterns on NISQ Quantum Devices
QRisk isolates backend-specific abnormal error patterns on NISQ devices via delta debugging and mitigates them with commuting gate swaps, cutting excess noise by 24-45% on IBM backends where noise models predict no difference.
-
Qurator: Scheduling Hybrid Quantum-Classical Workflows Across Heterogeneous Cloud Providers
Qurator jointly optimizes queue time and fidelity for hybrid quantum-classical workflows across providers using quantum-aware DAG scheduling and a unified logarithmic fidelity score, achieving 30-75% wait reduction at high load with bounded accuracy cost.
-
Routing Entanglement in Complex Quantum Networks Using GHZ States
A hybrid GHZ-BSM routing strategy outperforms pure BSM routing in square grid quantum networks but requires global-information adaptations to beat BSM in complex topologies such as Waxman, scale-free, and SURFnet.
-
Iceberg Beyond the Tip: Co-Compilation of a Quantum Error Detection Code and a Quantum Algorithm
Co-optimization of flexible Iceberg error-detection gadgets with QAOA via tree search improves success probability and post-selection on Quantinuum H2-1 hardware up to 34 algorithmic qubits.
-
Lottery BP: Unlocking Quantum Error Decoding at Scale
Lottery BP adds randomness to belief propagation decoding and uses syndrome voting to achieve far higher accuracy on topological quantum codes while reducing reliance on expensive global decoders.
-
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.
-
Tensor-Parallel Emulation of Quantum Circuits with Block-Cyclic Distributed Matrix Product States
Presents a tensor-parallel distributed MPS method with block-cyclic partitioning and pivoted QR that emulates Google's RCS benchmark at bond dimension 16384 on 32 nodes, claiming three orders of magnitude better accuracy than prior methods.
-
Weakly Fault-Tolerant Computation in a Quantum Error-Detecting Code
Constructions for universal quantum computation in the [[n,n-2,2]] error-detecting code detect single-gate errors at computation end, providing weak fault tolerance with reduced overhead versus full error correction.
-
Three ways to share a QPU: Scheduling strategies for hybrid Quantum-HPC applications
Three scheduling strategies for hybrid quantum-HPC systems cut classical resource use by up to 64% or boost QPU utilization depending on workload balance, validated on real hardware.
-
GPU-Accelerated Quantum Simulation: Empirical Backend Selection, Gate Fusion, and Adaptive Precision
A new GPU quantum simulator framework achieves 64x-146x speedups for 20-28 qubit circuits via backend selection, gate fusion, and adaptive precision while integrating with Qiskit and others.
-
Assessing student learning in quantum computing: The challenging case of phase kickback
Detailed revision of a single phase-kickback item on a quantum computing survey reveals complex student reasoning and supports triangulating multiple data types when building conceptual assessments.
-
Quantum Walks-Based Adaptive Distribution Generation with Efficient CUDA-Q Acceleration
Quantum walks integrated with variational circuits and CUDA-Q acceleration generate high-fidelity adaptive probability distributions for 1D financial modeling and 2D digit patterns.
-
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.
-
Quantum Integrated High-Performance Computing: Foundations, Architectural Elements and Future Directions
The authors describe a visionary layered architecture for unifying classical and quantum compute resources under a single job submission and scheduling interface.
-
A Quantum Search Approach to Magic Square Constraint Problems with Classical Benchmarking
Grover quantum search with classical Siamese pre-processing generates magic squares on small grids and confirms the expected quadratic query advantage over brute-force and backtracking.
-
Qimax: Efficient quantum simulation via GPU-accelerated extended stabilizer formalism
Qimax parallelizes the extended stabilizer formalism for GPU execution and reports faster simulation of near-Clifford circuits than Qiskit or Pennylane in selected cases.
-
Introduction to QUDO, Tensor QUDO and HOBO formulations: Qudits, Equivalences, Knapsack Problem, Traveling Salesman Problem and Combinatorial Games
The paper reviews QUDO, T-QUDO and HOBO formulations, provides explicit encodings between them, discusses limitations, and gives examples for knapsack, TSP and games including N-Queens and Peg Solitaire.
-
Quantum-inspired tensor networks in machine learning models
Tensor networks developed for quantum states are reviewed as tools for machine learning models, with assessment of their potential computational, explanatory, and privacy advantages alongside remaining challenges.
-
The Role of Quantum Computing in Advancing Scientific High-Performance Computing: A perspective from the ADAC Institute
A synthesis of expert insights from the ADAC Quantum Computing Working Group and member survey on the complementary roles of quantum and classical high-performance computing in future hybrid infrastructures.