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You're reading from  A Practical Guide to Quantum Machine Learning and Quantum Optimization

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Published inMar 2023
PublisherPackt
ISBN-139781804613832
Edition1st Edition
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Authors (2):
Elías F. Combarro
Elías F. Combarro
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Elías F. Combarro

Elías F. Combarro holds degrees from the University of Oviedo (Spain) in both Mathematics (1997, award for second highest grades in the country) and Computer Science (2002, award for highest grades in the country). After some research stays at the Novosibirsk State University (Russia), he obtained a Ph.D. in Mathematics (Oviedo, 2001) with a dissertation on the properties of some computable predicates under the supervision of Prof. Andrey Morozov and Prof. Consuelo Martínez. Since 2009, Elías F. Combarro has been an associate professor at the Computer Science Department of the University of Oviedo. He has published more than 50 research papers in international journals on topics such as Computability Theory, Machine Learning, Fuzzy Measures and Computational Algebra. His current research focuses on the application Quantum Computing to algebraic, optimisation and machine learning problems. From July 2020 to January 2021, he was a Cooperation Associate at CERN openlab. Currently, he is the Spain representative in the Advisory Board of CERN Quantum Technology Initiative, a member of the Advisory Board of SheQuantum and one of the founders of the QSpain, a quantum computing think tank based in Spain.
Read more about Elías F. Combarro

Samuel González-Castillo
Samuel González-Castillo
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Samuel González-Castillo

Samuel González-Castillo holds degrees from the University of Oviedo (Spain) in both Mathematics and Physics (2021). He is currently a mathematics research student at the National University of Ireland, Maynooth, where he works as a graduate teaching assistant. He completed his physics bachelor thesis under the supervision of Prof. Elías F. Combarro and Prof. Ignacio F. Rúa (University of Oviedo), and Dr. Sofia Vallecorsa (CERN). In it, he worked alongside other researchers from ETH Zürich on the application of Quantum Machine Learning to classification problems in High Energy Physis. In 2021, he was a summer student at CERN developing a benchmarking framework for quantum simulators. He has contributed to several conferences on quantum computing.
Read more about Samuel González-Castillo

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3.3 Moving from Ising to QUBO and back

Consider the following problem. Let’s say that you are given a set of integers and a target integer value , and you are asked whether there is any subset of whose sum is . For instance, if and , then the answer is affirmative, because . However, if and , the answer is negative because all the numbers in the set are even and they cannot add up to an odd number.

This problem, called the Subset Sum problem, is known to be -complete (see, for instance, Section 7.5 in the book by Sipser [90] for a proof). It turns out that we can reduce the Subset Sum problem to finding a spin configuration of minimal energy for an Ising model, (which is an -hard problem – see Section 3.1.3). This means that we can rewrite any instance of Subset Sum as an Ising ground state problem (check Appendix C, Computational Complexity, for a refresher on reductions).

However, it may not be directly evident how to do so.

In fact, it is much simpler to pose the...

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A Practical Guide to Quantum Machine Learning and Quantum Optimization
Published in: Mar 2023Publisher: PacktISBN-13: 9781804613832

Authors (2)

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Elías F. Combarro

Elías F. Combarro holds degrees from the University of Oviedo (Spain) in both Mathematics (1997, award for second highest grades in the country) and Computer Science (2002, award for highest grades in the country). After some research stays at the Novosibirsk State University (Russia), he obtained a Ph.D. in Mathematics (Oviedo, 2001) with a dissertation on the properties of some computable predicates under the supervision of Prof. Andrey Morozov and Prof. Consuelo Martínez. Since 2009, Elías F. Combarro has been an associate professor at the Computer Science Department of the University of Oviedo. He has published more than 50 research papers in international journals on topics such as Computability Theory, Machine Learning, Fuzzy Measures and Computational Algebra. His current research focuses on the application Quantum Computing to algebraic, optimisation and machine learning problems. From July 2020 to January 2021, he was a Cooperation Associate at CERN openlab. Currently, he is the Spain representative in the Advisory Board of CERN Quantum Technology Initiative, a member of the Advisory Board of SheQuantum and one of the founders of the QSpain, a quantum computing think tank based in Spain.
Read more about Elías F. Combarro

author image
Samuel González-Castillo

Samuel González-Castillo holds degrees from the University of Oviedo (Spain) in both Mathematics and Physics (2021). He is currently a mathematics research student at the National University of Ireland, Maynooth, where he works as a graduate teaching assistant. He completed his physics bachelor thesis under the supervision of Prof. Elías F. Combarro and Prof. Ignacio F. Rúa (University of Oviedo), and Dr. Sofia Vallecorsa (CERN). In it, he worked alongside other researchers from ETH Zürich on the application of Quantum Machine Learning to classification problems in High Energy Physis. In 2021, he was a summer student at CERN developing a benchmarking framework for quantum simulators. He has contributed to several conferences on quantum computing.
Read more about Samuel González-Castillo