Novel QUBO formulations for NP-hard location problems (p-Median, FCFLP, DOMP) enable quantum benchmarking. LP-based warm-start strategies for WS-QAOA outperform SDP/continuous relaxations, demonstrating quantum optimization viability on gate-based simulators.
#QuantumOptimization #QUBO #Research
Researchers enhanced QMOO with Pareto archiving and dominated substitution, achieving competitive performance against NSGA-II/III. RMNK-landscapes introduced as quantum benchmarking testbed; QMOO shows advantage on high-epistasis combinatorial problems.
#QuantumOptimization #NISQ #Research
QUBO formulation of food delivery rider-order assignment benchmarked across SCIP, QAOA, QAOAnsatz, SQA, and CIM. Classical solvers dominate; QAOAnsatz outperforms QAOA on constraints; CIM shows runtime advantages over SQA at scale.
#QuantumOptimization #QAOA #Research
GD-QLC hybridizes Quantum Lyapunov Control with per-layer gradient descent to accelerate QAOA convergence on combinatorial problems. Outperforms FALQON on MAX-CUT, MAX-CLIQUE & MIN-COVER with reduced circuit depth and improved timestep robustness.
#QAOA #QuantumOptimization #Research
Proves NP-hard inapproximability of max-LINSAT beyond random-assignment ratio r/q, establishing a complexity-theoretic boundary that confirms DQI's quantum advantage is structure-dependent, not general-purpose.
#QuantumOptimization #QuantumAlgorithms #Research
Researchers modified QAOA's hypercube mixer for constrained optimization, reducing gate count by up to 42% for problems with 6+ binary variables. Numerical simulations confirm improved noise resilience under depolarizing and damping channels on NISQ hardware.
#QAOA #QuantumOptimization #Research
Novel VQA introduces an ancilla-qubit feasibility oracle and dual-pathway loss function to solve constrained combinatorial optimization, outperforming penalty-based QAOA on MVC and MIS problems with lower circuit complexity than ansatz-based methods.
#QuantumOptimization #QAOA #Research
QAOA at p=1 on real urban street graphs shows planned city grids (Islamabad) yield more reliable convergence than organic networks (Lyari/Karachi), with degree variance—not algebraic connectivity—being the primary predictor of optimization instability.
#QAOA #QuantumOptimization #Research
Researchers benchmark 7 solvers (QAOA, quantum annealing, simulated annealing, tabu search, hybrid) on a vehicle platooning matching problem cast as QUBO, showing CE-QAOA achieves <1.64% optimality gap up to 144 qubits with one-shot parameter transfer.
#QuantumOptimization #QAOA #Research
Reviews QA (TRL 7–9), QAOA (QTRL 3–5), and QRL/QGM (QTRL 2–4) for combinatorial optimization, mapping benchmarks (QOBLIB, QUARK, QED-C, TAQOS) to industrial domains in finance, logistics, and telecom. Quantum annealing leads in deployment readiness.
#QuantumOptimization #QAOA #QuantumAnnealing
QA outperforms simulated annealing in mixed p-spin glass models, reaching sub-threshold energies with power-law decay exponents up to 2× larger in O(1) time—proven analytically via integro-differential equations, eliminating finite-size effects.
#QuantumAnnealing #SpinGlass #QuantumOptimization
Rigetti's quantum preconditioning algorithm tackles energy grid optimization on its 84-qubit Ankaa™-3 processor, benchmarking against best-in-class classical solvers and signaling a near-term path to practical quantum utility.
#QuantumOptimization #QuantumUtility #News
Rigetti introduces self-consistent mean-field QAOA, a magnet-physics-inspired framework enabling current quantum hardware to tackle large-scale optimization problems, demonstrated on a drug design use case using the Ankaa-3 processor.
#QuantumOptimization #QAOA #News
SuperQ (Canada/UAE) and Fraunhofer ITWM partner to develop quantum algorithms for European industries, targeting supply chain optimization, material science simulations, energy modeling, and financial risk analysis.
#QuantumComputing #QuantumOptimization #News
planqc, Saarland University, BMW & Infineon launch QIAPO: a €2.3M project using neutral-atom QPUs to pre-process NP-hard industrial optimization problems, targeting accuracy gains from ~80% to 95% via hybrid quantum-classical methods.
#QuantumOptimization #HybridQuantum #News
QAOA at p=1 achieves 95% convergence on Islamabad's planned grid (88–92% of optimal) vs 63–68% for Lyari's organic network. Urban 'topological DNA' is shown to directly govern quantum optimization reliability on NP-hard minimum vertex cover problems.
#QAOA #QuantumOptimization #UrbanComputing
Kipu Quantum's HSQC pipeline on IBM Heron r3 QPU matches ground-state energy in 14/20 HUBO instances under 1s, outperforming SA & MTS by up to 97x in TTS, while remaining competitive with 128-vCPU and 8×A100 GPU classical solvers.
#QuantumOptimization #HybridQuantumComputing #Research
JPMorganChase researchers introduce RWS-QAOA, a hybrid quantum-classical algorithm that outperforms Goemans-Williamson/HLZ on 96-node hardware and projects quantum-classical runtime crossover below 0.2s on 3,000-node graphs using <1.3M physical qubits.
#QAOA #QuantumOptimization #Research
Researchers prove false traps (local non-global optima) persist in quantum-classical optimization even with sufficient parameters, linking their emergence to quantum indistinguishability—offering new landscape-design strategies to mitigate them.
#QuantumOptimization #VariationalQuantum #Research
cop-QAOA solves constrained knapsack problems on IBM Quantum hardware at up to 150 qubits, matching or beating Gurobi on hard instances—the largest utility-scale demonstration of constrained optimization via shallow constant-depth mixers.
#QAOA #QuantumOptimization #Research
ADGLB modifies laser detuning guided by spectral gap to suppress ground-state leakage in Rydberg AQC, boosting MIS prep from 28%→38% on a 10-atom chain and transferring to 25–37-atom 2D lattices without reoptimization.
#RydbergAtoms #QuantumOptimization #Research
Kipu Quantum & IonQ demonstrate 250-asset portfolio optimization on 64-qubit trapped-ion hardware using BF-DCQO with hardware-aware QUBO decomposition, showing larger qubit budgets directly improve risk-return solution quality.
#QuantumOptimization #QuantumFinance #Research
Variational (matrix) product states for combinatorial optimization
Conor Mc Keever, Guillermo Preisser et al.
Paper
Details
#QuantumOptimization #VariationalMethods #CombinatorialOptimization
Quantum and Classical Heuristics Advance Binary Paint Shop Optimization
Low-depth XQAOA1 achieved a paint-swap ratio of 0.357 on Binary Paint Shop up to 2^12 cars, beating heuristics. The study tested sizes from 2^7 to 2^12 cars. Read more: getnews.me/quantum-and-classical-he... #binarypaintshop #quantumoptimization
Complexity Insights into Decoded Quantum Interferometry Algorithm
Decoded Quantum Interferometry (DQI) is an approximate‑optimization algorithm with hardness from a hidden subset, yet it can be simulated within the polynomial hierarchy. getnews.me/complexity-insights-into... #dqi #quantumoptimization
