Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Martin J A Schuetz"'
Autor:
Gili Rosenberg, John Kyle Brubaker, Martin J. A. Schuetz, Grant Salton, Zhihuai Zhu, Elton Yechao Zhu, Serdar Kadıoğlu, Sima E. Borujeni, Helmut G. Katzgraber
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 5, Iss 4, Pp 1760-1795 (2023)
We propose and implement an interpretable machine learning classification model for Explainable AI (XAI) based on expressive Boolean formulas. Potential applications include credit scoring and diagnosis of medical conditions. The Boolean formula defi
Externí odkaz:
https://doaj.org/article/0669b6bf00d5475b9e1ccf90ed56b4cf
Autor:
Jernej Rudi Finžgar, Martin J. A. Schuetz, J. Kyle Brubaker, Hidetoshi Nishimori, Helmut G. Katzgraber
Publikováno v:
Physical Review Research, Vol 6, Iss 2, p 023063 (2024)
We propose and analyze the use of Bayesian optimization techniques to design quantum annealing schedules with minimal user and resource requirements. We showcase our scheme with results for two paradigmatic spin models. We find that Bayesian optimiza
Externí odkaz:
https://doaj.org/article/f2b613213af74958b0efaef4910948e2
Autor:
Ruben S. Andrist, Martin J. A. Schuetz, Pierre Minssen, Romina Yalovetzky, Shouvanik Chakrabarti, Dylan Herman, Niraj Kumar, Grant Salton, Ruslan Shaydulin, Yue Sun, Marco Pistoia, Helmut G. Katzgraber
Publikováno v:
Physical Review Research, Vol 5, Iss 4, p 043277 (2023)
Rydberg atom arrays are among the leading contenders for the demonstration of quantum speedups. Motivated by recent experiments with up to 289 qubits [Ebadi et al., Science 376, 1209 (2022)0036-807510.1126/science.abo6587], we study the maximum-indep
Externí odkaz:
https://doaj.org/article/529bac3458824f419db1407d76013bf2
Autor:
Alexander M. Dalzell, B. David Clader, Grant Salton, Mario Berta, Cedric Yen-Yu Lin, David A. Bader, Nikitas Stamatopoulos, Martin J. A. Schuetz, Fernando G. S. L. Brandão, Helmut G. Katzgraber, William J. Zeng
Publikováno v:
PRX Quantum, Vol 4, Iss 4, p 040325 (2023)
We study quantum interior-point methods (QIPMs) for second-order cone programming (SOCP), guided by the example use case of portfolio optimization (PO). We provide a complete quantum circuit-level description of the algorithm from problem input to pr
Externí odkaz:
https://doaj.org/article/4829c40142644d01bdd4f645f19bacde
Publikováno v:
Physical Review Research, Vol 4, Iss 4, p 043131 (2022)
We show how graph neural networks can be used to solve the canonical graph coloring problem. We frame graph coloring as a multiclass node classification problem and utilize an unsupervised training strategy based on the statistical physics Potts mode
Externí odkaz:
https://doaj.org/article/2e28c2843c6c4696af8a618cd8c8ec03
Publikováno v:
Physical Review Applied
We propose a protocol for the deterministic generation of entanglement between two ensembles of nuclear spins surrounding two distant quantum dots. The protocol relies on the injection of electrons with definite polarization, their sequential interac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c46b3be4ae32f52088a3bac9161c5c9f
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/104296
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/104296
We provide a comprehensive reply to the comment written by Chiara Angelini and Federico Ricci-Tersenghi [arXiv:2206.13211] and argue that the comment singles out one particular non-representative example problem, entirely focusing on the maximum inde
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::23555962c19cd9de597afec77dc257e3
http://arxiv.org/abs/2302.03602
http://arxiv.org/abs/2302.03602
We provide a comprehensive reply to the comment written by Stefan Boettcher [arXiv:2210.00623] and argue that the comment singles out one particular non-representative example problem, entirely focusing on the maximum cut problem (MaxCut) on sparse g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee4e1881be563108e15c853aa4dba0bc
Combinatorial optimization problems are pervasive across science and industry. Modern deep learning tools are poised to solve these problems at unprecedented scales, but a unifying framework that incorporates insights from statistical physics is stil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a74e3867a89c1eca9389b058defe3e5
https://resolver.caltech.edu/CaltechAUTHORS:20220505-181556200
https://resolver.caltech.edu/CaltechAUTHORS:20220505-181556200
Autor:
Martin J. A. Schütz
This thesis offers a comprehensive introduction to surface acoustic waves in the quantum regime. It addresses two of the most significant technological challenges in developing a scalable quantum information processor based on spins in quantum dots: