1
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Bernaschi M, González-Adalid Pemartín I, Martín-Mayor V, Parisi G. The quantum transition of the two-dimensional Ising spin glass. Nature 2024; 631:749-754. [PMID: 38987607 PMCID: PMC11269196 DOI: 10.1038/s41586-024-07647-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 06/03/2024] [Indexed: 07/12/2024]
Abstract
Quantum annealers are commercial devices that aim to solve very hard computational problems1, typically those involving spin glasses2,3. Just as in metallurgic annealing, in which a ferrous metal is slowly cooled4, quantum annealers seek good solutions by slowly removing the transverse magnetic field at the lowest possible temperature. Removing the field diminishes the quantum fluctuations but forces the system to traverse the critical point that separates the disordered phase (at large fields) from the spin-glass phase (at small fields). A full understanding of this phase transition is still missing. A debated, crucial question regards the closing of the energy gap separating the ground state from the first excited state. All hopes of achieving an exponential speed-up, compared to classical computers, rest on the assumption that the gap will close algebraically with the number of spins5-9. However, renormalization group calculations predict instead that there is an infinite-randomness fixed point10. Here we solve this debate through extreme-scale numerical simulations, finding that both parties have grasped parts of the truth. Although the closing of the gap at the critical point is indeed super-algebraic, it remains algebraic if one restricts the symmetry of possible excitations. As this symmetry restriction is experimentally achievable (at least nominally), there is still hope for the quantum annealing paradigm11-13.
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Affiliation(s)
| | | | - Víctor Martín-Mayor
- Departamento de Física Teórica, Universidad Complutense de Madrid, Madrid, Spain
| | - Giorgio Parisi
- Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy
- Nanotec-Rome unit, CNR, Rome, Italy
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2
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Chen Y, Huang JH, Sun Y, Zhang Y, Li Y, Xu X. Haplotype-resolved assembly of diploid and polyploid genomes using quantum computing. CELL REPORTS METHODS 2024; 4:100754. [PMID: 38614089 PMCID: PMC11133727 DOI: 10.1016/j.crmeth.2024.100754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 01/03/2024] [Accepted: 03/20/2024] [Indexed: 04/15/2024]
Abstract
Precision medicine's emphasis on individual genetic variants highlights the importance of haplotype-resolved assembly, a computational challenge in bioinformatics given its combinatorial nature. While classical algorithms have made strides in addressing this issue, the potential of quantum computing remains largely untapped. Here, we present the vehicle routing problem (VRP) assembler: an approach that transforms this task into a vehicle routing problem, an optimization formulation solvable on a quantum computer. We demonstrate its potential and feasibility through a proof of concept on short synthetic diploid and triploid genomes using a D-Wave quantum annealer. To tackle larger-scale assembly problems, we integrate the VRP assembler with Google's OR-Tools, achieving a haplotype-resolved local assembly across the human major histocompatibility complex (MHC) region. Our results show encouraging performance compared to Hifiasm with phasing accuracy approaching the theoretical limit, underscoring the promising future of quantum computing in bioinformatics.
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Affiliation(s)
- Yibo Chen
- BGI Research, Shenzhen 518083, China
| | | | - Yuhui Sun
- BGI Research, Shenzhen 518083, China
| | - Yong Zhang
- BGI Research, Wuhan 430047, China; Guangdong Bigdata Engineering Technology Research Center for Life Sciences, BGI Research, Shenzhen 518083, China.
| | - Yuxiang Li
- BGI Research, Wuhan 430047, China; Guangdong Bigdata Engineering Technology Research Center for Life Sciences, BGI Research, Shenzhen 518083, China.
| | - Xun Xu
- BGI Research, Shenzhen 518083, China; BGI Research, Wuhan 430047, China.
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3
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Thudiyangal M, Kevrekidis PG, Saxena A, Bishop AR. A nonlinear journey from structural phase transitions to quantum annealing. CHAOS (WOODBURY, N.Y.) 2024; 34:053134. [PMID: 38787313 DOI: 10.1063/5.0203120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 05/02/2024] [Indexed: 05/25/2024]
Abstract
Motivated by an exact mapping between equilibrium properties of a one-dimensional chain of quantum Ising spins in a transverse field (the transverse field Ising (TFI) model) and a two-dimensional classical array of particles in double-well potentials (the "ϕ4 model") with weak inter-chain coupling, we explore connections between the driven variants of the two systems. We argue that coupling between the fundamental topological solitary waves in the form of kinks between neighboring chains in the classical ϕ4 system is the analog of the competing effect of the transverse field on spin flips in the quantum TFI model. As an example application, we mimic simplified measurement protocols in a closed quantum model system by studying the classical ϕ4 model subjected to periodic perturbations. This reveals memory/loss of memory and coherence/decoherence regimes, whose quantum analogs are essential in annealing phenomena. In particular, we examine regimes where the topological excitations control the thermal equilibration following perturbations. This paves the way for further explorations of the analogy between lower-dimensional linear quantum and higher-dimensional classical nonlinear systems.
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Affiliation(s)
- Mithun Thudiyangal
- Department of Atomic and Molecular Physics, Manipal Academy of Higher Education, Manipal 576 104, India
| | - Panayotis G Kevrekidis
- Department of Mathematics and Statistics, University of Massachusetts, Amherst, Amherst, Massachusetts 01003-4515, USA
| | - Avadh Saxena
- Center for Nonlinear Studies and Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - Alan R Bishop
- Center for Nonlinear Studies and Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
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4
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Chae E, Choi J, Kim J. An elementary review on basic principles and developments of qubits for quantum computing. NANO CONVERGENCE 2024; 11:11. [PMID: 38498068 PMCID: PMC10948723 DOI: 10.1186/s40580-024-00418-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 03/04/2024] [Indexed: 03/19/2024]
Abstract
An elementary review on principles of qubits and their prospects for quantum computing is provided. Due to its rapid development, quantum computing has attracted considerable attention as a core technology for the next generation and has demonstrated its potential in simulations of exotic materials, molecular structures, and theoretical computer science. To achieve fully error-corrected quantum computers, building a logical qubit from multiple physical qubits is crucial. The number of physical qubits needed depends on their error rates, making error reduction in physical qubits vital. Numerous efforts to reduce errors are ongoing in both existing and emerging quantum systems. Here, the principle and development of qubits, as well as the current status of the field, are reviewed to provide information to researchers from various fields and give insights into this promising technology.
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Affiliation(s)
- Eunmi Chae
- Department of Physics, Korea University, Seoul , 02841, Republic of Korea.
| | - Joonhee Choi
- Department of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA.
| | - Junki Kim
- SKKU Advanced Institute of Nanotechnology (SAINT) & Department of Nano Science and Technology, Sungkyunkwan University, Suwon, 16419, Republic of Korea.
- Department of Nano Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea.
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5
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Willsch D, Rieger D, Winkel P, Willsch M, Dickel C, Krause J, Ando Y, Lescanne R, Leghtas Z, Bronn NT, Deb P, Lanes O, Minev ZK, Dennig B, Geisert S, Günzler S, Ihssen S, Paluch P, Reisinger T, Hanna R, Bae JH, Schüffelgen P, Grützmacher D, Buimaga-Iarinca L, Morari C, Wernsdorfer W, DiVincenzo DP, Michielsen K, Catelani G, Pop IM. Observation of Josephson harmonics in tunnel junctions. NATURE PHYSICS 2024; 20:815-821. [PMID: 38799981 PMCID: PMC11116114 DOI: 10.1038/s41567-024-02400-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 01/14/2024] [Indexed: 05/29/2024]
Abstract
Approaches to developing large-scale superconducting quantum processors must cope with the numerous microscopic degrees of freedom that are ubiquitous in solid-state devices. State-of-the-art superconducting qubits employ aluminium oxide (AlOx) tunnel Josephson junctions as the sources of nonlinearity necessary to perform quantum operations. Analyses of these junctions typically assume an idealized, purely sinusoidal current-phase relation. However, this relation is expected to hold only in the limit of vanishingly low-transparency channels in the AlOx barrier. Here we show that the standard current-phase relation fails to accurately describe the energy spectra of transmon artificial atoms across various samples and laboratories. Instead, a mesoscopic model of tunnelling through an inhomogeneous AlOx barrier predicts percent-level contributions from higher Josephson harmonics. By including these in the transmon Hamiltonian, we obtain orders of magnitude better agreement between the computed and measured energy spectra. The presence and impact of Josephson harmonics has important implications for developing AlOx-based quantum technologies including quantum computers and parametric amplifiers. As an example, we show that engineered Josephson harmonics can reduce the charge dispersion and associated errors in transmon qubits by an order of magnitude while preserving their anharmonicity.
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Affiliation(s)
- Dennis Willsch
- Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany
| | - Dennis Rieger
- IQMT, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany
- PHI, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Patrick Winkel
- IQMT, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany
- PHI, Karlsruhe Institute of Technology, Karlsruhe, Germany
- Departments of Applied Physics and Physics, Yale University, New Haven, CT USA
- Yale Quantum Institute, Yale University, New Haven, CT USA
| | - Madita Willsch
- Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany
- AIDAS, Jülich, Germany
| | | | - Jonas Krause
- Physics Institute II, University of Cologne, Köln, Germany
| | - Yoichi Ando
- Physics Institute II, University of Cologne, Köln, Germany
| | - Raphaël Lescanne
- LPENS, Mines Paris-PSL, ENS-PSL, Inria, Université PSL, CNRS, Paris, France
- Alice & Bob, Paris, France
| | - Zaki Leghtas
- LPENS, Mines Paris-PSL, ENS-PSL, Inria, Université PSL, CNRS, Paris, France
| | - Nicholas T. Bronn
- IBM Quantum, IBM T. J. Watson Research Center, Yorktown Heights, NY USA
| | - Pratiti Deb
- IBM Quantum, IBM T. J. Watson Research Center, Yorktown Heights, NY USA
| | - Olivia Lanes
- IBM Quantum, IBM T. J. Watson Research Center, Yorktown Heights, NY USA
| | - Zlatko K. Minev
- IBM Quantum, IBM T. J. Watson Research Center, Yorktown Heights, NY USA
| | - Benedikt Dennig
- IQMT, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany
- PHI, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Simon Geisert
- IQMT, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany
| | - Simon Günzler
- IQMT, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany
| | - Sören Ihssen
- IQMT, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany
| | - Patrick Paluch
- IQMT, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany
- PHI, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Thomas Reisinger
- IQMT, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany
| | - Roudy Hanna
- PGI-9, Forschungszentrum Jülich and JARA Jülich-Aachen Research Alliance, Jülich, Germany
- RWTH Aachen University, Aachen, Germany
| | - Jin Hee Bae
- PGI-9, Forschungszentrum Jülich and JARA Jülich-Aachen Research Alliance, Jülich, Germany
| | - Peter Schüffelgen
- PGI-9, Forschungszentrum Jülich and JARA Jülich-Aachen Research Alliance, Jülich, Germany
| | - Detlev Grützmacher
- PGI-9, Forschungszentrum Jülich and JARA Jülich-Aachen Research Alliance, Jülich, Germany
- RWTH Aachen University, Aachen, Germany
| | | | | | - Wolfgang Wernsdorfer
- IQMT, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany
- PHI, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - David P. DiVincenzo
- RWTH Aachen University, Aachen, Germany
- PGI-2, Forschungszentrum Jülich, Jülich, Germany
| | - Kristel Michielsen
- Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany
- AIDAS, Jülich, Germany
- RWTH Aachen University, Aachen, Germany
| | - Gianluigi Catelani
- PGI-11, Forschungszentrum Jülich, Jülich, Germany
- Quantum Research Center, Technology Innovation Institute, Abu Dhabi, UAE
| | - Ioan M. Pop
- IQMT, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany
- PHI, Karlsruhe Institute of Technology, Karlsruhe, Germany
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6
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Calvanese Strinati M, Conti C. Hyperscaling in the Coherent Hyperspin Machine. PHYSICAL REVIEW LETTERS 2024; 132:017301. [PMID: 38242655 DOI: 10.1103/physrevlett.132.017301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 11/06/2023] [Accepted: 12/06/2023] [Indexed: 01/21/2024]
Abstract
Classical and quantum systems are used to simulate the Ising Hamiltonian, an essential component in large-scale optimization and machine learning. However, as the system size increases, devices like quantum annealers and coherent Ising machines face an exponential drop in their success rate. Here, we introduce a novel approach involving high-dimensional embeddings of the Ising Hamiltonian and a technique called "dimensional annealing" to counteract the decrease in performance. This approach leads to an exponential improvement in the success rate and other performance metrics, slowing down the decline in performance as the system size grows. A thorough examination of convergence dynamics in high-performance computing validates the new methodology. Additionally, we suggest practical implementations using technologies like coherent Ising machines, all-optical systems, and hybrid digital systems. The proposed hyperscaling heuristics can also be applied to other quantum or classical Ising devices by adjusting parameters such as nonlinear gain, loss, and nonlocal couplings.
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Affiliation(s)
| | - Claudio Conti
- Centro Ricerche Enrico Fermi (CREF), Via Panisperna 89a, 00184 Rome, Italy
- Physics Department, Sapienza University of Rome, 00185 Rome, Italy
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7
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Bonde B, Patil P, Choubey B. The Future of Drug Development with Quantum Computing. Methods Mol Biol 2024; 2716:153-179. [PMID: 37702939 DOI: 10.1007/978-1-0716-3449-3_7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/14/2023]
Abstract
Novel medication development is a time-consuming and expensive multistage procedure. Recent technology developments have lowered timeframes, complexity, and cost dramatically. Current research projects are driven by AI and machine learning computational models. This chapter will introduce quantum computing (QC) to drug development issues and provide an in-depth discussion of how quantum computing may be used to solve various drug discovery problems. We will first discuss the fundamentals of QC, a review of known Hamiltonians, how to apply Hamiltonians to drug discovery challenges, and what the noisy intermediate-scale quantum (NISQ) era methods and their limitations are.We will further discuss how these NISQ era techniques can aid with specific drug discovery challenges, including protein folding, molecular docking, AI-/ML-based optimization, and novel modalities for small molecules and RNA secondary structures. Consequently, we will discuss the latest QC landscape's opportunities and challenges.
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Affiliation(s)
- Bhushan Bonde
- Evotec (UK) Ltd., Oxfordshire, UK.
- Digital Futures Institute, University of Suffolk, Ipswich, UK.
| | - Pratik Patil
- Evotec (UK) Ltd., Oxfordshire, UK
- Digital Futures Institute, University of Suffolk, Ipswich, UK
| | - Bhaskar Choubey
- Digital Futures Institute, University of Suffolk, Ipswich, UK
- Chair of Analogue Circuits and Image Sensors, Siegen University, Siegen, Germany
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8
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Hoffmann M, Poschenrieder JM, Incudini M, Baier S, Fitz A, Maier A, Hartung M, Hoffmann C, Trummer N, Adamowicz K, Picciani M, Scheibling E, Harl MV, Lesch I, Frey H, Kayser S, Wissenberg P, Schwartz L, Hafner L, Acharya A, Hackl L, Grabert G, Lee SG, Cho G, Cloward M, Jankowski J, Lee HK, Tsoy O, Wenke N, Pedersen AG, Bønnelykke K, Mandarino A, Melograna F, Schulz L, Climente-González H, Wilhelm M, Iapichino L, Wienbrandt L, Ellinghaus D, Van Steen K, Grossi M, Furth PA, Hennighausen L, Di Pierro A, Baumbach J, Kacprowski T, List M, Blumenthal DB. Network medicine-based epistasis detection in complex diseases: ready for quantum computing. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.07.23298205. [PMID: 38076997 PMCID: PMC10705612 DOI: 10.1101/2023.11.07.23298205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs)1-3. Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs. With NeEDL (network-based epistasis detection via local search), we leverage network medicine to inform the selection of EIs that are an order of magnitude more statistically significant compared to existing tools and consist, on average, of five SNPs. We further show that this computationally demanding task can be substantially accelerated once quantum computing hardware becomes available. We apply NeEDL to eight different diseases and discover genes (affected by EIs of SNPs) that are partly known to affect the disease, additionally, these results are reproducible across independent cohorts. EIs for these eight diseases can be interactively explored in the Epistasis Disease Atlas (https://epistasis-disease-atlas.com). In summary, NeEDL is the first application that demonstrates the potential of seamlessly integrated quantum computing techniques to accelerate biomedical research. Our network medicine approach detects higher-order EIs with unprecedented statistical and biological evidence, yielding unique insights into polygenic diseases and providing a basis for the development of improved risk scores and combination therapies.
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Affiliation(s)
- Markus Hoffmann
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany
- Institute for Advanced Study (Lichtenbergstrasse 2 a, D-85748 Garching, Germany), Technical University of Munich, Germany
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America
| | - Julian M. Poschenrieder
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany
- Institute for Computational Systems Biology, University of Hamburg, Germany
| | - Massimiliano Incudini
- Dipartimento di Informatica, Universit’a di Verona, Strada le Grazie 15 - 34137, Verona, Italy
| | - Sylvie Baier
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany
| | - Amelie Fitz
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, DTU, 2800 Kgs. Lyngby, Denmark
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Andreas Maier
- Institute for Computational Systems Biology, University of Hamburg, Germany
| | - Michael Hartung
- Institute for Computational Systems Biology, University of Hamburg, Germany
| | - Christian Hoffmann
- Institute for Computational Systems Biology, University of Hamburg, Germany
| | - Nico Trummer
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany
| | - Klaudia Adamowicz
- Institute for Computational Systems Biology, University of Hamburg, Germany
| | - Mario Picciani
- Computational Mass Spectrometry, Technical University of Munich, Freising, Germany
| | - Evelyn Scheibling
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany
| | - Maximilian V. Harl
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany
| | - Ingmar Lesch
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany
| | - Hunor Frey
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany
| | - Simon Kayser
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany
| | - Paul Wissenberg
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany
| | - Leon Schwartz
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany
| | - Leon Hafner
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany
- Institute for Advanced Study (Lichtenbergstrasse 2 a, D-85748 Garching, Germany), Technical University of Munich, Germany
| | - Aakriti Acharya
- Division Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics, Technische Universität Braunschweig and Hannover Medical School, Rebenring 56, 38106 Braunschweig, Germany
- Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Rebenring 56, 38106 Braunschweig, Braunschweig, Germany
| | - Lena Hackl
- Institute for Computational Systems Biology, University of Hamburg, Germany
| | - Gordon Grabert
- Division Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics, Technische Universität Braunschweig and Hannover Medical School, Rebenring 56, 38106 Braunschweig, Germany
- Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Rebenring 56, 38106 Braunschweig, Braunschweig, Germany
| | - Sung-Gwon Lee
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America
- School of Biological Sciences and Technology, Chonnam National University, Gwangju, Korea
| | - Gyuhyeok Cho
- Department of Chemistry, Gwangju Institute of Science and Technology, Gwangju, Korea
| | - Matthew Cloward
- Department of Biology, Brigham Young University, Provo, UT, USA
| | - Jakub Jankowski
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America
| | - Hye Kyung Lee
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America
| | - Olga Tsoy
- Institute for Computational Systems Biology, University of Hamburg, Germany
| | - Nina Wenke
- Institute for Computational Systems Biology, University of Hamburg, Germany
| | - Anders Gorm Pedersen
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, DTU, 2800 Kgs. Lyngby, Denmark
| | - Klaus Bønnelykke
- Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Antonio Mandarino
- International Centre for Theory of Quantum Technologies, University of Gdańsk, 80-309 Gdańsk, Poland
| | - Federico Melograna
- BIO3 - Systems Genetics; GIGA-R Medical Genomics, University of Liège, Liège, Belgium
- BIO3 - Systems Medicine; Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Laura Schulz
- Leibniz Supercomputing Centre of the Bavarian Academy of Sciences and Humanities (LRZ), Garching b. München, Germany
| | | | - Mathias Wilhelm
- Computational Mass Spectrometry, Technical University of Munich, Freising, Germany
| | - Luigi Iapichino
- Leibniz Supercomputing Centre of the Bavarian Academy of Sciences and Humanities (LRZ), Garching b. München, Germany
| | - Lars Wienbrandt
- Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany
| | - David Ellinghaus
- Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany
| | - Kristel Van Steen
- BIO3 - Systems Genetics; GIGA-R Medical Genomics, University of Liège, Liège, Belgium
- BIO3 - Systems Medicine; Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Michele Grossi
- European Organization for Nuclear Research (CERN), Geneva 1211, Switzerland
| | - Priscilla A. Furth
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America
- Departments of Oncology & Medicine, Georgetown University, Washington, DC, USA
| | - Lothar Hennighausen
- Institute for Advanced Study (Lichtenbergstrasse 2 a, D-85748 Garching, Germany), Technical University of Munich, Germany
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, United States of America
| | - Alessandra Di Pierro
- Dipartimento di Informatica, Universit’a di Verona, Strada le Grazie 15 - 34137, Verona, Italy
| | - Jan Baumbach
- Institute for Computational Systems Biology, University of Hamburg, Germany
- Computational BioMedicine Lab, University of Southern Denmark, Denmark
| | - Tim Kacprowski
- Division Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics, Technische Universität Braunschweig and Hannover Medical School, Rebenring 56, 38106 Braunschweig, Germany
- Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Rebenring 56, 38106 Braunschweig, Braunschweig, Germany
| | - Markus List
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Germany
| | - David B. Blumenthal
- Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
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9
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Ye M, Tian Y, Lin J, Luo Y, You J, Hu J, Zhang W, Chen W, Li X. Universal Quantum Optimization with Cold Atoms in an Optical Cavity. PHYSICAL REVIEW LETTERS 2023; 131:103601. [PMID: 37739373 DOI: 10.1103/physrevlett.131.103601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 08/15/2023] [Indexed: 09/24/2023]
Abstract
Cold atoms in an optical cavity have been widely used for quantum simulations of many-body physics, where the quantum control capability has been advancing rapidly in recent years. Here, we show the atom cavity system is universal for quantum optimization with arbitrary connectivity. We consider a single-mode cavity and develop a Raman coupling scheme by which the engineered quantum Hamiltonian for atoms directly encodes number partition problems. The programmability is introduced by placing the atoms at different positions in the cavity with optical tweezers. The number partition problem solution is encoded in the ground state of atomic qubits coupled through a photonic cavity mode, which can be reached by adiabatic quantum computing. We construct an explicit mapping for the 3-SAT and vertex cover problems to be efficiently encoded by the cavity system, which costs linear overhead in the number of atomic qubits. The atom cavity encoding is further extended to quadratic unconstrained binary optimization problems. The encoding protocol is optimal in the cost of atom number scaling with the number of binary degrees of freedom of the computation problem. Our theory implies the atom cavity system is a promising quantum optimization platform searching for practical quantum advantage.
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Affiliation(s)
- Meng Ye
- State Key Laboratory of Surface Physics, Key Laboratory of Micro and Nano Photonic Structures (MOE), and Department of Physics, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, AI Tower, Xuhui District, Shanghai 200232, China
| | - Ye Tian
- Department of Physics and State Key Laboratory of Low Dimensional Quantum Physics, Tsinghua University, Beijing 100084, China
- Frontier Science Center for Quantum Information, Beijing 100084, China
- Collaborative Innovation Center of Quantum Matter, Beijing 100084, China
| | - Jian Lin
- State Key Laboratory of Surface Physics, Key Laboratory of Micro and Nano Photonic Structures (MOE), and Department of Physics, Fudan University, Shanghai 200433, China
| | - Yuchen Luo
- State Key Laboratory of Surface Physics, Key Laboratory of Micro and Nano Photonic Structures (MOE), and Department of Physics, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, AI Tower, Xuhui District, Shanghai 200232, China
| | - Jiaqi You
- Department of Physics and State Key Laboratory of Low Dimensional Quantum Physics, Tsinghua University, Beijing 100084, China
- Frontier Science Center for Quantum Information, Beijing 100084, China
- Collaborative Innovation Center of Quantum Matter, Beijing 100084, China
| | - Jiazhong Hu
- Department of Physics and State Key Laboratory of Low Dimensional Quantum Physics, Tsinghua University, Beijing 100084, China
- Frontier Science Center for Quantum Information, Beijing 100084, China
- Collaborative Innovation Center of Quantum Matter, Beijing 100084, China
| | - Wenjun Zhang
- Department of Physics and State Key Laboratory of Low Dimensional Quantum Physics, Tsinghua University, Beijing 100084, China
- Frontier Science Center for Quantum Information, Beijing 100084, China
- Collaborative Innovation Center of Quantum Matter, Beijing 100084, China
| | - Wenlan Chen
- Department of Physics and State Key Laboratory of Low Dimensional Quantum Physics, Tsinghua University, Beijing 100084, China
- Frontier Science Center for Quantum Information, Beijing 100084, China
- Collaborative Innovation Center of Quantum Matter, Beijing 100084, China
| | - Xiaopeng Li
- State Key Laboratory of Surface Physics, Key Laboratory of Micro and Nano Photonic Structures (MOE), and Department of Physics, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, AI Tower, Xuhui District, Shanghai 200232, China
- Institute of Nanoelectronics and Quantum Computing, Fudan University, Shanghai 200433, China
- Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China
- Shanghai Research Center for Quantum Sciences, Shanghai 201315, China
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