Quadratic Unconstrained Binary Optimization

Also known as QUBO

Quadratic unconstrained binary optimization represents decisions with binary variables and scores each assignment using a quadratic objective; constraints are often incorporated as penalty terms. Researchers solve these models with methods such as simulated annealing, quantum annealing, QAOA, quantum-inspired simulated bifurcation, and classical optimization, often alongside preprocessing, graph coarsening, or decomposition to reduce problem size. Applications range from routing, scheduling, and portfolio selection to image reconstruction, machine learning, and scientific sampling. A central challenge is making formulations fit limited hardware connectivity and precision while keeping penalties, noise, and approximation from undermining feasibility or real-world task performance.

Latest papers

21 papers1 paper in the last four weeks, down 67% on the four weeks before. 0.0% of all new papers.

Landscape-Dependent Performance of Photonic Quantum Solvers in QUBO Feature Selection for Financial Risk Detection
Oct 2, 2026Nirvik Sahoo, Paul Robert GriffinFeature Selection Photonic Computing
Singapore Management University 80 Stamford Road, Singapore 178902
QuantumQUBO Agent: Automating Quadratic Unconstrained Binary Optimization (QUBO) Formulation Generation from Natural Language
Sep 9, 2026Niloy Kumar Mondal, Md Rizwan ParvezMulti-Agent LLM Systems Large Language Model-Guided Optimization
Bangladesh University of Engineering and Technology · Qatar Computing Research Institute, HBKU, Doha, Qatar.
Task-Aware QUBO Allocation for Mixed-Precision Quantization
Sep 4, 2026Osama Orabi, Artur Zagitov, Hadi Salloum +2Mixed-Precision Quantization Cost-Aware Inference
Laboratory of Quantum Computing, Innopolis University, 420500 Innopolis, Russia · Q Deep, Laboratory of Quantum Computing, 420502 Innopolis, Russia · Moscow Independent Research Institute of Artificial Intelligence (MIRAI), 117218 Moscow, Russia +2
GNN-Guided Graph Coarsening and Adaptive QUBO Penalties for the Capacitated Vehicle Routing Problem with Time Windows on a Quantum Annealer
Sep 4, 2026Youssef Kamel Rezk, Paweł GoraQuantum Annealing Graph Coarsening
Alamein International University, Alamein, Egypt · Jagiellonian University, Kraków, Poland · Fundacja Quantum AI, Warsaw, Poland
Resource-Efficient QUBO Formulation for Anchored Currency Arbitrage
Aug 16, 2026Eric A. F. Reinhardt, Adam J. HauserQuadratic Unconstrained Binary Optimization Algorithmic Trading
Department of Physics and Astronomy University of Alabama, Tuscaloosa, AL 35487, USA
LC-Implicit-QAOA: Active-Workspace-Capped Exact Objective-and-Gradient Evaluation for Training over Bounded QUBO Light Cones
Aug 6, 2026Chih-Chung HsuQuadratic Unconstrained Binary Optimization Variational Quantum Circuits
Institute of Smart Industry and Green Energy, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
Superpixel-Based QUBO for Scalable Quantum-Enhanced Medical Image Segmentation
Jul 27, 2026Mohammad Chalhoub, Mahdi Chehimi, Laia Domingo +3Image Segmentation Superpixel Segmentation
Department of Electrical and Computer Engineering, American University of Beirut, Beirut, Lebanon · Centre de Visi´o per Computador (CVC), Barcelona, Spain · Ingenii Inc., New York, USA +3
Formulation-Level Auto-Tuning for QUBO-Based Machine Learning: A Case Study Across Multiple Quantum-Inspired Annealers
Jul 21, 2026Naoya Mizuki, Takahiro Katagiri, Daichi Mukunoki +1Black-Box Optimization Quantum-Inspired ML
Graduate School of Informatics, Nagoya University · Information Technology Center, Nagoya University
Quantum Compressed Sensing CT Reconstruction Algorithm Based on Penalized Weighted Least Squares and Guided Total Variation
Jul 12, 2026Yuwen Zhang, Yujie Liu, Ao Wang +4Sparse-View CT Reconstruction Quadratic Unconstrained Binary Optimization
Department of Medical Imaging Technology, Peking University Health Science Center, Beijing, China
COMET: Combinatorial Optimization for Multiplex Editing Targets Via Constraint-Preserving QAOA
Jul 2, 2026Priyansh Singhal, Sumit Maheshwari, Piyush JoshiQuadratic Unconstrained Binary Optimization Constrained Optimization
Independent Researcher India · Microsoft Boston, USA · Department of Computer Science & Engineering IIIT Sri City, India
Quantum CT via Dynamic Interval Encoding and Prior-Balanced QUBO Reconstruction
Jun 23, 2026Ao Wang, Yikuang Yuluo, Yujie Liu +7Image Reconstruction Sparse-View CT Reconstruction
Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China · Key Lab of Optoelectronic Technology and Systems and the Engineering Research Center of Industrial Computed Tomography Nondestructive Testing, Ministry of Education, Chongqing University, Chongqing 400044, China · Pattern Recognition Lab (LME), Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Martensstraße 3, 91058 Erlangen, Germany
Adaptive Enhanced Quantum-inspired Simulated Bifurcation Algorithm for Population State Perception
Jun 23, 2026Dongmei Liu, Jian Li, Xiubo Chen +1Combinatorial Optimization Quadratic Unconstrained Binary Optimization
State Key Laboratory of Networking and Switching Technology, Cyber Security Center, School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China
Implicit Binarization via Complex Phase Dynamics in Combinatorial Optimization
May 23, 2026Khen Cohen, Mark Glass, Meir Feder +1Combinatorial Optimization Quadratic Unconstrained Binary Optimization
School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel · School of Electrical and Computer Engineering, Tel Aviv University, Tel Aviv, Israel
Combinatorial Optimization of Robotic Hand Kinematic Structures Using a Potential-Dexterity-Based QUBO Formulation
May 15, 2026HyoJae Kang, Yeong Jae Park, Jeongdo Ahn +1Robotic Hand Design Quantum Annealing
Advanced Robotics Research Center, Korea Institute of Machinery & Materials (KIMM) · Mechanical Engineering, University of Science & Technology (UST)
Neural QAOA $^{2}$ : Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization
May 13, 2026Zubin Zheng, Jiahao Wu, Shengcai LiuGraph Partitioning Quadratic Unconstrained Binary Optimization
Guangdong Provincial Key Labora- tory of Brain-Inspired Intelligent Computation, Department of CSE, SUSTech.
Neural Network Pruning via QUBO Optimization
Apr 7, 2026Osama Orabi, Artur Zagitov, Hadi Salloum +3Neural Network Pruning Quadratic Unconstrained Binary Optimization
Department of Computer Science and Engineering, Innopolis University, 420500 Innopolis, Russia · Q Deep, Laboratory of Quantum Computing, 420502 Innopolis, Russia · Research Center of the Artificial Intelligence Institute, Innopolis University, 420500 Innopolis, Russia +2
Q-BIOLAT: Binary Latent Protein Fitness Landscapes for QUBO-Based Optimization
Mar 29, 2026Truong-Son HyMolecular Optimization Surrogate-Assisted Optimization
Department of Computer Science, University of Alabama at Birmingham, Birmingham, Alabama, USA
Diversity-Aware Adaptive Collocation for Physics-Informed Neural Networks via Sparse QUBO Optimization and Hybrid Coresets
Mar 6, 2026Hadi Salloum, Maximilian Mifsud Bonici, Sinan Ibrahim +2Physics-Informed ML Coreset Selection
Research Center for Artificial Intelligence, Innopolis University, Innopolis, Russia · Moscow Center for Advanced Studies, 20, Kulakova Str., Moscow, Russia · Laboratory of Quantum Computing, Innopolis University, Innopolis, Russia +5
Quantum-Assisted Optimal Rebalancing with Uncorrelated Asset Selection for Algorithmic Trading Walk-Forward QUBO Scheduling via QAOA
Mar 4, 2026Abraham Itzhak WeinbergAlgorithmic Trading Portfolio Optimization
AI-WEINBERG, AI Experts, Tel Aviv, Israel
Layer-wise QUBO-Based Training of CNN Classifiers for Quantum Annealing
Mar 3, 2026Mostafa Atallah, Rebekah HerrmanImage Classification Hybrid Quantum-Classical ML
Department of Industrial and Systems Engineering, University of Tennessee - Knoxville, Knoxville, 37996, TN, USA. · Department of Physics, Faculty of Science, Cairo University, Giza, 12613, Egypt.
Scalable Multi-Robot Path Planning via Quadratic Unconstrained Binary Optimization
Feb 16, 2026Javier González VillasmilMulti-Robot Motion Planning Multi-Agent Path Finding

Oct 2, 2026J/K move · Enter open · S save

Landscape-Dependent Performance of Photonic Quantum Solvers in QUBO Feature Selection for Financial Risk Detection

Nirvik Sahoo, Paul Robert Griffin

Singapore Management University 80 Stamford Road, Singapore 178902

Feature Selection Photonic Computing Financial Fraud Detection Quadratic Unconstrained Binary Optimization Class-Imbalanced Learning

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Feature selection for imbalanced classification tasks such as credit card fraud and consumer default detection requires balancing predictive relevance, inter-feature redundancy, and computational feasibility. We benchmark three computing paradigms, classical branch-and-bound optimization (Gurobi), photonic entropy computing (QCI Dirac-3), and simulated photonic boson sampling (Piquasso), across thirteen feature-selection methods on two datasets: ULB Credit Card Fraud (30 features) and AmEx consumer default (159 features). Each method is routed to the solver matched to its mathematical structure. On ULB, Dirac-3 MI-Spearman matches the all-features model using 13 of 30 features (mean F1 0.873 +/- 0.023 over five runs, best run 0.896), and Piquasso is the best method at k=5. On AmEx, performance rises steadily with the feature budget and every paradigm approaches F1 = 0.80 only near the full feature set. Most differences between Gurobi and Dirac-3 on identical methods fall within run-to-run variation; the large gaps occur where the certified optimum generalizes poorly, most sharply for distance correlation on AmEx at k=25 (Gurobi F1 = 0.422 vs. a Dirac-3 mean of 0.746). At matched budgets, F1 varies about ten times more across methods on ULB than on AmEx, which we trace to how concentrated the predictive signal is in each feature space.