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.
hub
Rieffel, Davide Venturelli, and Rupak Biswas
16 Pith papers cite this work, alongside 758 external citations. Polarity classification is still indexing.
16
Pith papers citing it
758
external citations · OpenAlex
hub tools
citation-role summary
background 2
citation-polarity summary
roles
background 2polarities
background 2representative citing papers
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.
CRiSP uses neural-guided MCTS and curriculum learning to insert Clifford prefixes before parameterized rotations in VQAs, yielding mean 3.17x and max 45x gains in energy accuracy on 22-qubit QAOA benchmarks versus prior Clifford initializers.
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.
Exhaustively parametrised feasibility-respecting quantum circuits can reach every feasible solution to problems like TSP with certainty using fixed parameters by leveraging group actions and generating sequences.
A qubit-efficient colored-permutation encoding for CVRP enables Constraint-Enhanced QAOA to recover verified optimal solutions on benchmarks without additional capacity qubits.
CE-QAOA with finite layers achieves dimension-free success probability bounds q0 ≥ x/(1+x) via Fejér filtering under a wrapped phase-separation condition.
Closed-form tight penalty coefficients for two QUBO reformulations of max-k-cut that depend on the weighted degrees of graph vertices.
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 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.
Proves finite-shot mean-squared-error laws for virtual distillation and symmetry verification that define certified operating windows and a selection trichotomy for their comparison.
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.
Iterative-QAOA warm-starts for the shipment selection problem yield hybrid logistics plans with up to 12% more shipments delivered on specific real instances while keeping operational cost flat.
Numerical experiments on QAOA show optimal parameters often break expected patterns, performance becomes less parameter-sensitive with depth, and component-wise iterative fixing performs competitively or better at low depth.
Graph contraction reduces TSP instances to smaller sub-problems solvable by quantum annealers, shown via Path Integral Monte Carlo simulation and D-Wave hardware.
Empirical tests show QUBO-SA and QAOA-inspired schedulers lose feasibility beyond 10-15 tasks while MILP, CP-SAT, GA and HEFT remain robust on the same instances.
citing papers explorer
-
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.
-
Classical State Preparation for Variational Quantum Algorithms via Reinforcement Learning
CRiSP uses neural-guided MCTS and curriculum learning to insert Clifford prefixes before parameterized rotations in VQAs, yielding mean 3.17x and max 45x gains in energy accuracy on 22-qubit QAOA benchmarks versus prior Clifford initializers.
-
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.
-
Exhaustive and feasible parametrisation with applications to the travelling salesperson problem
Exhaustively parametrised feasibility-respecting quantum circuits can reach every feasible solution to problems like TSP with certainty using fixed parameters by leveraging group actions and generating sequences.
-
Optimal, Qubit-Efficient Quantum Vehicle Routing via Colored-Permutations
A qubit-efficient colored-permutation encoding for CVRP enables Constraint-Enhanced QAOA to recover verified optimal solutions on benchmarks without additional capacity qubits.
-
Finite-Depth, Finite-Shot Guarantees for Constrained Quantum Optimization via Fej\'er Filtering
CE-QAOA with finite layers achieves dimension-free success probability bounds q0 ≥ x/(1+x) via Fejér filtering under a wrapped phase-separation condition.
-
Characterizing QUBO Reformulations of the Max-k-Cut Problem for Quantum Computing
Closed-form tight penalty coefficients for two QUBO reformulations of max-k-cut that depend on the weighted degrees of graph vertices.
-
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.
-
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.
-
Certified Finite-Shot Operating Windows for Virtual Distillation and Symmetry Verification
Proves finite-shot mean-squared-error laws for virtual distillation and symmetry verification that define certified operating windows and a selection trichotomy for their comparison.
-
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.
-
Hybrid Quantum-Classical Optimization Workflows for the Shipment Selection Problem
Iterative-QAOA warm-starts for the shipment selection problem yield hybrid logistics plans with up to 12% more shipments delivered on specific real instances while keeping operational cost flat.
-
Going off Pattern? QAOA Parameter Heuristics and Potentials of Parsimony
Numerical experiments on QAOA show optimal parameters often break expected patterns, performance becomes less parameter-sensitive with depth, and component-wise iterative fixing performs competitively or better at low depth.
-
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.
-
An Empirical Evaluation of Quantum-Inspired QUBO Methods for Heterogeneous HPC Workflow Mapping and Scheduling
Empirical tests show QUBO-SA and QAOA-inspired schedulers lose feasibility beyond 10-15 tasks while MILP, CP-SAT, GA and HEFT remain robust on the same instances.