A winding pump phase in a ring of parametric oscillators creates a single unidirectional, topologically protected phase dislocation whose speed can be tuned and stopped by pump amplitude.
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Lucas, Frontiers in Physics2 (2014), 10.3389/fphy.2014.00005
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quant-ph 29 cs.AR 2 cs.ET 2 cond-mat.soft 1 cond-mat.stat-mech 1 cs.AI 1 cs.CL 1 cs.CR 1 cs.LG 1 cs.PL 1roles
background 7representative citing papers
Coherent-state propagation enables quasi-polynomial classical simulation of bosonic circuits with logarithmically many Kerr gates at exponentially small trace-distance error, with polynomial runtime in the weak-nonlinearity regime.
A hardware-efficient binary-tree ansatz has a closed-form diagonal Fubini–Study metric, enabling metric-aware VQE and time evolution without auxiliary circuits, with linear-in-k pruning for sparse sectors.
Presents an end-to-end constraint-aware quantum optimization pipeline using XY-mixer QAOA and Grover Adaptive Search for low-energy defect configurations in doped ZrO2, with QAOA validated against exact enumeration on a high-accuracy QUBO surrogate of MACE energies.
Continuous-time Adam dynamics outperform gradient-descent and momentum dynamics on analog Ising machines for Max-Cut, with a simpler first-order approximation also introduced.
Truncated-binary encoding approximates high-cardinality CFN problems as low-degree HUBO Hamiltonians with an L^∞ error bound, conditions preserving the global minimum, and a smoothness-based criterion for choosing the cutoff.
Ising machines outperform every tested Potts machine on Max-k-Cut problems, with the performance gap widening from k=3 to k=4.
A pre-computation method sets penalization weights for constrained QUBO problems with provable guarantees for Gibbs solvers and polynomial scaling for many problem classes.
Adaptive min-vertex-cut qubit freezing plus bias folding makes DC-QAOA partition every graph (to n=10k) while matching quality on separable instances and beating QAOA2 at equal coverage.
AtomTreeSearch embeds a neutral-atom quantum MWIS subroutine inside Monte Carlo Tree Search and matches or exceeds OR-Tools and simulated annealing on TSP instances up to 100 cities.
Constructs and proves correct a QUBO Hamiltonian H_mod,k whose zero-energy ground states exist exactly when a graph admits a nowhere-zero Z_k-flow, with degeneracy matching the flow polynomial.
A regularized Pauli-sparse counterdiabatic method is added to linear-ramp QAOA, yielding higher approximation ratios on ferromagnetic chain and perturbed MaxCut instances than the uncorrected ramp.
Introduces a parallelizable hybrid tensor network algorithm for time-evolving matrix product states that combines classical BUG integration with quantum methods without synchronization barriers.
Introduces Λ-lr-QAOA and piecewise-ramp QAOA that promote penalty schedules to variational parameters and use a feasibility-driven loss on budget-constrained MWIS satellite planning instances.
Coupling-Grouped XY-QAOA enables joint anomaly-feature selection via a constraint-preserving grouped-angle QAOA variant, achieving 45.9-61.3% circuit depth reduction and larger feasible executions (64 qubits at p=2) on IBM Heron hardware compared to standard approaches.
Applies egglog equality saturation and datalog rules to optimize higher-order function handling for LaTeX output and constraint detection in a lambda-calculus-based mathematical optimization modeler.
A penalty-free pipeline samples an objective-only QUBO on D-Wave hardware and enforces cardinality classically, cutting chain-break fractions from 71-92% to at most 0.04% across tested equity and betting instances.
LeapHybridCQM matches Gurobi optima with ~0.68% QPU wall-clock, classical Tabu matches those objectives, and penalty encoding forces a complete logical graph independent of covariance density.
DQI-Kit automates encoding of objectives and constraints into Max-LINSAT instances and estimates expected DQI performance on the resulting problems.
A logarithmic HUBO encoding with a lexicographic penalty solves minimum graph coloring and related partition-count problems using exponentially fewer qubits per vertex than one-hot encoding.
Q-SFD, a QUBO formulation for simultaneous fragment docking with an added inter-fragment distance term, approximately doubles top-1 recovery of reconstruction-feasible pose pairs and places at least one feasible pair in the top-5 for over 90% of benchmark cases without losing pose accuracy.
Superparamagnetic tunnel junctions integrated with standard CMOS produce tunable random voltage fluctuations suitable for probabilistic bits.
QuantumXCT learns parameterized quantum circuits to model interaction-induced unitary transformations between non-interacting and interacting cellular state distributions from transcriptomic profiles.
A parallel-in-time encoding turns quantum dynamical propagators into QUBO instances for direct benchmarking of quantum annealers against classical solvers on models from single-qubit rotations to PT-symmetric systems.
citing papers explorer
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Dynamical frustration in spacetime metamaterials enables cascading logic and synchronization
A winding pump phase in a ring of parametric oscillators creates a single unidirectional, topologically protected phase dislocation whose speed can be tuned and stopped by pump amplitude.
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Coherent-State Propagation: A Computational Framework for Simulating Bosonic Quantum Systems
Coherent-state propagation enables quasi-polynomial classical simulation of bosonic circuits with logarithmically many Kerr gates at exponentially small trace-distance error, with polynomial runtime in the weak-nonlinearity regime.
-
A hardware-efficient variational ansatz with an exact diagonal metric for real- and imaginary-time evolution and Haar sampling
A hardware-efficient binary-tree ansatz has a closed-form diagonal Fubini–Study metric, enabling metric-aware VQE and time evolution without auxiliary circuits, with linear-in-k pruning for sparse sectors.
-
Constraint-Aware Quantum Optimization of Defect Configurations in Doped ZrO2: XY-Mixer QAOA and Grover Adaptive Search
Presents an end-to-end constraint-aware quantum optimization pipeline using XY-mixer QAOA and Grover Adaptive Search for low-energy defect configurations in doped ZrO2, with QAOA validated against exact enumeration on a high-accuracy QUBO surrogate of MACE energies.
-
Beyond Gradient Descent: Adam for Analog Ising Machines
Continuous-time Adam dynamics outperform gradient-descent and momentum dynamics on analog Ising machines for Max-Cut, with a simpler first-order approximation also introduced.
-
Truncated-Binary Encoding: Spectral Degree Reduction of Combinatorial Optimization Problems for Quantum Hardware
Truncated-binary encoding approximates high-cardinality CFN problems as low-degree HUBO Hamiltonians with an L^∞ error bound, conditions preserving the global minimum, and a smoothness-based criterion for choosing the cutoff.
-
Comparative Study of Potts Machine Dynamics and Performance for Max-k-Cut
Ising machines outperform every tested Potts machine on Max-k-Cut problems, with the performance gap widening from k=3 to k=4.
-
Scalable Determination of Penalization Weights for Constrained Optimizations on Approximate Solvers
A pre-computation method sets penalization weights for constrained QUBO problems with provable guarantees for Gibbs solvers and polynomial scaling for many problem classes.
-
Adaptive Qubit Freezing Enables Robust Graph Partitioning for Divide-and-Conquer QAOA
Adaptive min-vertex-cut qubit freezing plus bias folding makes DC-QAOA partition every graph (to n=10k) while matching quality on separable instances and beating QAOA2 at equal coverage.
-
Quantum-enhanced Monte Carlo Tree Search framework for combinatorial optimization problems
AtomTreeSearch embeds a neutral-atom quantum MWIS subroutine inside Monte Carlo Tree Search and matches or exceeds OR-Tools and simulated annealing on TSP instances up to 100 cities.
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A QUBO Formulation for Nowhere-Zero $k$-Flows
Constructs and proves correct a QUBO Hamiltonian H_mod,k whose zero-energy ground states exist exactly when a graph admits a nowhere-zero Z_k-flow, with degeneracy matching the flow polynomial.
-
Pauli-Sparse regularised Counterdiabatic Shortcuts for Linear-Ramp QAOA
A regularized Pauli-sparse counterdiabatic method is added to linear-ramp QAOA, yielding higher approximation ratios on ferromagnetic chain and perturbed MaxCut instances than the uncorrected ramp.
-
Time Evolution on Hybrid Tensor Networks -- A Novel and Parallelizable Algorithm
Introduces a parallelizable hybrid tensor network algorithm for time-evolving matrix product states that combines classical BUG integration with quantum methods without synchronization barriers.
-
Feasibility-driven QAOA with penalty scheduling
Introduces Λ-lr-QAOA and piecewise-ramp QAOA that promote penalty schedules to variational parameters and use a feasibility-driven loss on budget-constrained MWIS satellite planning instances.
-
Coupling-Grouped XY-QAOA for Joint Anomaly-Feature Selection
Coupling-Grouped XY-QAOA enables joint anomaly-feature selection via a constraint-preserving grouped-angle QAOA variant, achieving 45.9-61.3% circuit depth reduction and larger feasible executions (64 qubits at p=2) on IBM Heron hardware compared to standard approaches.
-
Optimizing Optimizations, Declaratively: Optimizing the Higher-Order Functions in Mathematical Optimization with egglog
Applies egglog equality saturation and datalog rules to optimize higher-order function handling for LaTeX output and constraint detection in a lambda-calculus-based mathematical optimization modeler.
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A Penalty-Free Pipeline for Direct Quantum-Annealer Portfolio Optimization
A penalty-free pipeline samples an objective-only QUBO on D-Wave hardware and enforces cardinality classically, cutting chain-break fractions from 71-92% to at most 0.04% across tested equity and betting instances.
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Where the Quantum Lives in D-Wave Hybrid Portfolio Optimization: An Operational Decomposition Audit
LeapHybridCQM matches Gurobi optima with ~0.68% QPU wall-clock, classical Tabu matches those objectives, and penalty encoding forces a complete logical graph independent of covariance density.
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From Constraint to Code: DQI-Kit -- A Software Framework for Decoded Quantum Interferometry
DQI-Kit automates encoding of objectives and constraints into Max-LINSAT instances and estimates expected DQI performance on the resulting problems.
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Qubit-efficient and gate-efficient encodings of graph partitioning problems for quantum optimization
A logarithmic HUBO encoding with a lexicographic penalty solves minimum graph coloring and related partition-count problems using exponentially fewer qubits per vertex than one-hot encoding.
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Simultaneous Fragment Docking for Geometrically Linkable Pose Pairs
Q-SFD, a QUBO formulation for simultaneous fragment docking with an added inter-fragment distance term, approximately doubles top-1 recovery of reconstruction-feasible pose pairs and places at least one feasible pair in the top-5 for over 90% of benchmark cases without losing pose accuracy.
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CMOS-integrated superparamagnetic tunnel junction-based p-bit
Superparamagnetic tunnel junctions integrated with standard CMOS produce tunable random voltage fluctuations suitable for probabilistic bits.
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QuantumXCT: Learning Interaction-Induced State Transformation in Cell-Cell Communication via Quantum Entanglement and Generative Modeling
QuantumXCT learns parameterized quantum circuits to model interaction-induced unitary transformations between non-interacting and interacting cellular state distributions from transcriptomic profiles.
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Quantum-inspired dynamical models on quantum and classical annealers
A parallel-in-time encoding turns quantum dynamical propagators into QUBO instances for direct benchmarking of quantum annealers against classical solvers on models from single-qubit rotations to PT-symmetric systems.
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Sampling (noisy) quantum circuits through randomized rounding
Gaussian randomized rounding on two-qubit marginals of depth-D circuits with local depolarizing noise p yields samples whose expected Max-Cut cost matches the noisy quantum device up to an approximation ratio of 1-O[(1-p)^D].
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A compact QUBO encoding of computational logic formulae demonstrated on cryptography constructions
A compact QUBO encoding derived via ILP reduces logical variables by thousands in AES, MD5, SHA1 and SHA256, with over 8x reduction for AES-256.
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Quantum-Assisted Genetic Algorithm
QAGAs employ reverse quantum annealing for mutations and classical crossovers, outperforming standard quantum annealing at locating global optima on spin-glass instances using the D-Wave 2000Q.
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Scaling Up Thermodynamic AI Models
A backpropagation training method for deep conv nets enables thermodynamic inference on Ising hardware with reported CIFAR accuracies plus theory bounding inference cost versus accuracy.
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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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ROA-Based Subharmonic Injection Locking for Oscillator-Based Ising Machines
ROA brick topology supplies PVT-robust 2.31 GHz SHIL that preserves 93-97% accuracy in 324-node OIM max-cut while ROSC-SHIL loses locking.
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Neural and Tensor Networks in the Study of Quantum Annealing Processors
The thesis introduces a topology-aware tensor-network heuristic called SpinGlassPEPS.jl and thermodynamic metrics to benchmark quantum annealers on Ising problems while accounting for dissipation and effective temperature.
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Quantum Subroutines in Branch-Price-and-Cut for Vehicle Routing
The authors integrate quantum annealing and QAOA as subroutines for pricing and separation in a branch-price-and-cut algorithm for vehicle routing problems.
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A Quantum-Assisted Agentic Distributed Artificial Intelligence Framework for Deadline-Bounded Orchestration of Hybrid Renewable Microgrids
A quantum-assisted agentic DAI framework formulates microgrid dispatch as QUBO problems solved by solver portfolios with agentic selection and belief-shaped storage valuation, achieving exact optimum in a 24-hour simulation with 97.83% renewable utilization.
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Quantum-Driven Neuromorphic Computing for Million-Qubit-Scale Workloads
Apollo is a room-temperature 10000-node CMOS neuromorphic chip whose p-qubit network emulates transverse-field quantum annealing via Suzuki-Trotter and reportedly achieves lower energies than cryogenic QA on 3D spin-glass benchmarks across 300 realizations.
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Revisiting the Quantum-Guided Cluster Algorithm: Improvements and Numerical Experiments
Extends QGCA with NNN correlations, reports strong performance on non-degenerate tile-planted Max-Cut instances, and outlines a future MCMC extension.
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SAFE ma-QAOA: Surrogate-Assisted and Fine-Tuning Enhanced Multi-Angle QAOA with Parameter Distillation
Combining a truncated classical surrogate, angle pruning, and exact fine-tuning cuts the number of active angles and estimated fine-tuning cost of ma-QAOA on small spin-glass and Max-Cut instances while preserving near-optimal approximation ratios.
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PUBO Formulation for MST and Application to Optimum-Path Forest
Reformulates MST as PUBO, applies FALQON to optimize prototypes for OPF classifiers, and reports accuracies comparable to classical Prim's algorithm on real datasets.
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Quantum-Inspired Hamiltonian Optimization, Stochastic Tensor Networks and Adaptive Congestion Routing for Large-Scale QKD Networks
A quantum-inspired framework using effective Hamiltonians, Metropolis annealing and stochastic tensor-network compression is proposed for adaptive multi-demand routing in large-scale QKD networks.
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Quantum Model for CVRPTW
A Grover-search-based quantum model for CVRPTW that encodes constraints with only linear additional decision qubits relative to TSP formulations.
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A detailed algorithmic study on a reuse-aware, near memory, all-digital Ising machine
SACHI reuses CPU L1 cache for all-digital Ising acceleration and reports 300x performance and 80x energy gains over BRIM on asset allocation, molecular dynamics, image segmentation, and TSP.
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A Hybrid Classical-Quantum Annealing Algorithm for the TSP
Graph contraction reduces TSP instances to smaller sub-problems solvable by quantum annealers, shown via Path Integral Monte Carlo simulation and D-Wave hardware.
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Multi-Objective Optimization by Quantum-Annealing-Inspired Algorithms
GPU-based quantum-annealing-inspired algorithms outperform both quantum processors and industry classical solvers in sampling speed and full runtime on MO-MaxCut instances.
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A Unified Generative-AI Framework for Smart Energy Infrastructure: Intelligent Gas Distribution, Utility Billing, Carbon Analytics, and Quantum-Inspired Optimisation
Proposes a generative-AI framework integrating smart metering, quantum-inspired optimization for gas distribution, billing, and carbon analytics in energy infrastructure.