{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":25,"n_cols":5,"rows_kept":25,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[9,2,9,3],[11,2,11,3],[12,2,12,3],[15,2,15,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNISA996538664903316"]
[null,null,"Titolo",null,"Computational Science - ICCS 2023 : 23rd International Conference, Prague, Czech Republic, July 3-5, 2023, Proceedings, Part V / / Jirí Mikyska [and five others], editors"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2023]"]
[{"$nulls":4},"©2023"]
[null,null,"ISBN",null,"3-031-36030-3"]
[null,null,"Edizione",null,"[First edition.]"]
[null,null,"Descrizione fisica",null,"1 online resource (809 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science Series ; ; Volume 10477"]
[null,null,"Disciplina",null,"511.3"]
[null,null,"Soggetti",null,"Computational complexity"]
[{"$nulls":4},"Computer science"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents - Part V -- Quantum Computing -- Searching B-Smooth Numbers Using Quantum Annealing: Applications to Factorization and Discrete Logarithm Problem -- 1 Introduction -- 2 Classical Methods for Integer Factorization and Discrete Logarithm -- 2.1 Quadratic Sieve Method -- 2.2 Index Calculus Method -- 3 Hybrid Methods -- 3.1 Known Results and Previous Work -- 3.2 Our Result - Factorization by Quantum Annealing as a Subroutine -- 3.3 Quantum Annealing Stage - Summary -- 4 Experiments -- 4.1 Results for Integer Factorization -- 4.2 Results for Discrete Logarithm Problem over Prime Field -- 5 Summary -- References -- Classification of Hybrid Quantum-Classical Computing -- 1 Introduction -- 2 Literature -- 3 Types of Hybrid Computing -- 3.1 Vertical Hybrid Quantum Computing -- 3.2 Horizontal Hybrid Quantum Computing -- 4 Application -- 5 Conclusions -- References -- Solving (Max) 3-SAT via Quadratic Unconstrained Binary Optimization -- 1 Introduction -- 2 Foundations -- 2.1 Satisfiability Problems -- 2.2 Quadratic Unconstrained Binary Optimization -- 3 Related Work -- 3.1 Chancellorn+m -- 3.2 Choi3m -- 4 Approaches -- 4.1 A 2n + m Approach -- 4.2 An n + m Approach -- 5 Empirical Evaluation -- 6 Conclusion and Future Work -- References -- Black Box Optimization Using QUBO and the Cross Entropy Method -- 1 Introduction -- 2 Background -- 2.1 MAX-SAT -- 2.2 Feedback Vertex Set (FVS) -- 2.3 MaxClique -- 2.4 Quadratic Unconstrained Binary "]
[{"$nulls":4},"Optimization (QUBO) -- 2.5 Cross-Entropy Method -- 3 Related Work -- 4 Black Box Optimization with Cross Entropy and QUBO (BOX-QUBO) -- 5 Experiments -- 6 Conclusion and Future Work -- References -- Sub-exponential ML Algorithm for Predicting Ground State Properties -- 1 Introduction -- 2 Preliminaries and Related Work -- 2.1 Formulation -- 2.2 Classical Shadows."]
[{"$nulls":4},"2.3 Predicting Ground States of Quantum Many-Body Systems -- 3 Proposed Method -- 3.1 Idea -- 3.2 Algorithm Details -- 4 Conclusion -- References -- Quantum Factory Method: A Software Engineering Approach to Deal with Incompatibilities in Quantum Libraries -- 1 Introduction -- 2 State of the Art -- 2.1 Quantum Software Engineering -- 2.2 OpenQASM: A Not-so-Standard Standard -- 3 Proposal -- 3.1 Design Patterns -- 3.2 Application -- 4 Examples -- 4.1 Building Simple Circuits -- 4.2 Building Quantum Rule-Based Systems -- 4.3 Experiments and Results -- 5 Discussion and Conclusions -- References -- A Polynomial Size Model with Implicit SWAP Gate Counting for Exact Qubit Reordering -- 1 Introduction -- 2 Background -- 2.1 Building Blocks of QC -- 2.2 Decomposing Multi-qubit Gates -- 3 Problem Definition -- 4 Mathematical Model -- 5 Experimental Results -- 5.1 Experimental Setup -- 5.2 Results -- 6 Conclusion -- References -- Translating Constraints into QUBOs for the Quadratic Knapsack Problem -- 1 Introduction -- 2 Background -- 2.1 Quantum and Simulated Annealing -- 2.2 QUBO Definition -- 2.3 Original QUBO Formulation for the QKP -- 2.4 Alternative QUBO Formulations for the QKP -- 3 Benchmark of QUBO Formulations -- 3.1 Problem Instances -- 3.2 Penalty Values -- 3.3 Approach -- 3.4 Results -- 4 Conclusion -- References -- Qubit: The Game. Teaching Quantum Computing through a Game-Based Approach -- 1 Introduction -- 2 Related Works -- 3 Quantum Concepts -- 3.1 Qubit -- 3.2 Superposition -- 3.3 Bloch Sphere -- 3.4 Quantum Gates -- 3.5 Projection -- 3.6 Entanglement -- 3.7 Decoherence -- 4 Qubit: The Game -- 4.1 General Description -- 4.2 Design -- 4.3 Mechanics -- 4.4 Quick Start -- 5 Pilot Study -- 5.1 Survey Design -- 5.2 Findings -- 5.3 Discussion -- 6 Conclusions -- References."]
[{"$nulls":4},"Software Aided Approach for Constrained Optimization Based on QAOA Modifications -- 1 Introduction -- 2 Preliminaries -- 2.1 Combinatorial Problem Formulation Models -- 2.2 Quantum Approximate Optimization Algorithm -- 2.3 Knapsack Problem -- 3 Related Work -- 4 Proposed QAOA Modifications for Constrained Problems -- 4.1 Weight-Free Hamiltonian -- 4.2 Alternate Variational Parameter Set -- 5 QHyper Experiment Framework -- 6 Global Optimizer Variants -- 7 Experiment Results -- 8 Summary and Future Work -- References -- GCS-Q: Quantum Graph Coalition Structure Generation -- 1 Introduction -- 2 Problem Formulation -- 3 Related Works -- 4 Methods -- 4.1 Optimal Split -- 4.2 QUBO Formulation for Optimal Split -- 4.3 GCS-Q Algorithm -- 4.4 Discussion -- 5 Evaluation -- 5.1 Experimental Settings -- 5.2 Results -- 5.3 Performance Analysis -- 6 Conclusion and Future Work -- References -- Learning qubo Models for Quantum Annealing: A Constraint-Based Approach -- 1 Introduction -- 2 Quantum Annealing and qubo -- 3 Motivating Example -- 3.1 Basic Example -- 3.2 A More Complex Example -- 4 Method Design -- 5 Experiments -- 5.1 Experimental Protocols -- 5.2 Experimental Results -- 6 Conclusion -- References -- TAQOS: A Benchmark Protocol for Quantum Optimization Systems -- 1 Introduction -- 1.1 Related Work -- 2 TAQOS Benchmark Protocol -- 2.1 Metrics -- 2.2 Use Case on the Max-Cut Problem -- 3 Conclusion -- References -- Enabling Non-linear Quantum Operations Through Variational Quantum Splines -- 1 Introduction -- 2 Related Works -- 3 "]
[{"$nulls":4},"Contribution -- 4 Methods -- 4.1 Preliminaries -- 4.2 VQSplines: Variational Algorithm for QSplines -- 4.3 GQSplines: Generalized Quantum Splines -- 5 Evaluation -- 5.1 Experimental Settings -- 5.2 Results -- 6 Discussion -- 7 Conclusion -- References."]
[{"$nulls":4},"Exploring the Capabilities of Quantum Support Vector Machines for Image Classification on the MNIST Benchmark -- 1 Introduction -- 2 Theoretical Background -- 2.1 Introduction to Quantum Computing -- 2.2 Support Vector Machine -- 2.3 Quantum Kernel -- 3 Computational Experiments -- 4 Conclusions -- References -- Determination of the Lower Bounds of the Goal Function for a Single-Machine Scheduling Problem on D-Wave Quantum Annealer -- 1 Introduction -- 2 Formulation of the Problem -- 3 Determining the Lower Bound on the D-Wave Quantum Machine -- 4 Experimental Research -- 5 Summary -- References -- Simulating Sparse and Shallow Gaussian Boson Sampling -- 1 Introduction -- 2 Setup -- 3 Classical Simulation of Sparse and Shallow GBS -- 4 Complexity of the Classical Algorithm for Non-displaced Gaussian Threshold Boson Sampling -- 5 Conclusion and Outlook -- A Matrix Operations -- B Factorizing Probabilities over Block Direct Sums -- C Supplementary Calculations -- References -- Solving Higher Order Binary Optimization Problems on NISQ Devices: Experiments and Limitations -- 1 Introduction -- 2 Problem Formulation -- 3 Experimental Setup -- 3.1 Setup of D-Wave Systems -- 3.2 Setup of the QAOA -- 4 Results -- 5 Conclusion -- References -- Constructing Generalized Unitary Group Designs -- 1 Introduction -- 2 Background and Notation -- 3 Constructing Higher Order Designs from Lower Ones -- 3.1 Constructing 2-designs -- 3.2 Possible Construction of Higher Designs -- 4 Unitary 2-Designs from Orthogonal and Symplectic 2-Designs -- 5 Summary and Outlook -- References -- Multi-objective Quantum-Inspired Genetic Algorithm for Supervised Learning of Deep Classification Models -- 1 Introduction -- 2 Related Work -- 3 Dataset with X-Ray Image Collection -- 4 Multi-objective Quantum Deep Learning -- 5 Numerical Experiments -- 6 Concluding Remarks -- References."]
[{"$nulls":4},"Simulations of Flow and Transport: Modeling, Algorithms and Computation -- Numerical Simulation of Virus-Laden Droplets Transport from Lung to Lung by Using Eighth-Generation Airway Model -- 1 Introduction -- 2 Numerical Approach -- 2.1 Flow Field and Heat Analysis -- 2.2 Movement of Virus-Laden Droplets -- 3 Simulation of Droplets -- 3.1 Numerical Model -- 3.2 Computational Condition for Droplets Analysis -- 3.3 Assessing the Risk of Infection -- 3.4 Computational Conditions for Flow and Heat Analysis -- 4 Results and Discussion of Droplets Analysis -- 5 Conclusions -- References -- Constraint Energy Minimizing Generalized Multiscale Finite Element Method for Highly Heterogeneous Compressible Flow -- 1 Introduction -- 2 Formulation of the Problem -- 3 Construction of Multiscale Basis Function -- 4 Numerical Results -- 5 Conclusions and Future Directions -- References -- Numerical Simulation of Propeller Hydrodynamics Using the Open Source Software -- 1 Introduction -- 2 Numerical Method -- 2.1 Governing Equations -- 2.2 Open-Source Software -- 3 Numerical Setup -- 4 Results and Discussions -- 5 Conclusion -- References -- Numerical Simulation of Supersonic Jet Noise Using Open Source Software -- 1 Introduction -- 2 Mathematical Model and Numerical Method -- 2.1 OpenFOAM Software, HybridCentralSolvers -- 2.2 OpenFOAM Software, QGDSolver -- 2.3 AMReX Software, CNS Solver -- 2.4 LibAcoustics Library -- 3 Computational Setup -- 4 Results and Discussion -- 5 Conclusion -- References -- DNS of Thermocapillary Migration of a Bi-dispersed Suspension of Droplets -- 1 Introduction -- 2 Mathematical "]
[{"$nulls":4},"Formulation and Numerical Methods -- 2.1 One Fluid Formulation for Incompressible Two-Phase Flow -- 2.2 The Multi-marker UCLS Method -- 2.3 Marangoni Force -- 2.4 Equation of State = (T) and Energy Equation -- 2.5 Regularization of Physical Properties."]
[{"$nulls":4},"2.6 Numerical Methods."]
[null,null,null,"Sommario/riassunto","The five-volume set LNCS 14073-14077 constitutes the proceedings of the 23rd International Conference on Computational Science, ICCS 2023, held in Prague, Czech Republic, during July 3-5, 2023. The total of 188 full papers and 94 short papers presented in this book set were carefully reviewed and selected from 530 submissions. 54 full and 37 short papers were accepted to the main track; 134 full and 57 short papers were accepted to the workshops/thematic tracks. The theme for 2023, \"Computation at the Cutting Edge of Science\", highlights the role of Computational Science in assisting multidisciplinary research. This conference was a unique event focusing on recent developments in scalable scientific algorithms, advanced software tools; computational grids; advanced numerical methods; and novel application areas. These innovative novel models, algorithms, and tools drive new science through efficient application in physical systems, computational and systems biology, environmental systems, finance, and others."]