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Stevens J, Szombati D, Maffei M, Elouard C, Assouly R, Cottet N, Dassonneville R, Ficheux Q, Zeppetzauer S, Bienfait A, Jordan AN, Auffèves A, Huard B. Energetics of a Single Qubit Gate. Phys Rev Lett 2022; 129:110601. [PMID: 36154409 DOI: 10.1103/physrevlett.129.110601] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 08/19/2022] [Accepted: 08/24/2022] [Indexed: 06/16/2023]
Abstract
Qubits are physical, a quantum gate thus not only acts on the information carried by the qubit but also on its energy. What is then the corresponding flow of energy between the qubit and the controller that implements the gate? Here we exploit a superconducting platform to answer this question in the case of a quantum gate realized by a resonant drive field. During the gate, the superconducting qubit becomes entangled with the microwave drive pulse so that there is a quantum superposition between energy flows. We measure the energy change in the drive field conditioned on the outcome of a projective qubit measurement. We demonstrate that the drive's energy change associated with the measurement backaction can exceed by far the energy that can be extracted by the qubit. This can be understood by considering the qubit as a weak measurement apparatus of the driving field.
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Affiliation(s)
- J Stevens
- Ecole Normale Supérieure de Lyon, CNRS, Laboratoire de Physique, F-69342 Lyon, France
| | - D Szombati
- Ecole Normale Supérieure de Lyon, CNRS, Laboratoire de Physique, F-69342 Lyon, France
| | - M Maffei
- CNRS and Université Grenoble Alpes, Institut Néel, F-38042 Grenoble, France
| | - C Elouard
- QUANTIC team, INRIA de Paris, 2 Rue Simone Iff, 75012 Paris, France
| | - R Assouly
- Ecole Normale Supérieure de Lyon, CNRS, Laboratoire de Physique, F-69342 Lyon, France
| | - N Cottet
- Ecole Normale Supérieure de Lyon, CNRS, Laboratoire de Physique, F-69342 Lyon, France
| | - R Dassonneville
- Ecole Normale Supérieure de Lyon, CNRS, Laboratoire de Physique, F-69342 Lyon, France
| | - Q Ficheux
- Ecole Normale Supérieure de Lyon, CNRS, Laboratoire de Physique, F-69342 Lyon, France
| | - S Zeppetzauer
- Ecole Normale Supérieure de Lyon, CNRS, Laboratoire de Physique, F-69342 Lyon, France
| | - A Bienfait
- Ecole Normale Supérieure de Lyon, CNRS, Laboratoire de Physique, F-69342 Lyon, France
| | - A N Jordan
- Institute for Quantum Studies, Chapman University, 1 University Drive, Orange, California 92866, USA
- Department of Physics and Astronomy, University of Rochester, Rochester, New York 14627, USA
| | - A Auffèves
- CNRS and Université Grenoble Alpes, Institut Néel, F-38042 Grenoble, France
| | - B Huard
- Ecole Normale Supérieure de Lyon, CNRS, Laboratoire de Physique, F-69342 Lyon, France
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Martínez RA, Dassonneville R, Bejarano D, Jimenez A, Even G, Mészáros G, Sölkner J. Direct and maternal genetic effects on growth, reproduction, and ultrasound traits in zebu Brahman cattle in Colombia1. J Anim Sci 2016; 94:2761-9. [DOI: 10.2527/jas.2016-0453] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Dassonneville R, Fritz S, Ducrocq V, Boichard D. Short communication: Imputation performances of 3 low-density marker panels in beef and dairy cattle. J Dairy Sci 2012; 95:4136-40. [PMID: 22720970 DOI: 10.3168/jds.2011-5133] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2011] [Accepted: 03/05/2012] [Indexed: 11/19/2022]
Abstract
Low-density chips are appealing alternative tools contributing to the reduction of genotyping costs. Imputation enables researchers to predict missing genotypes to recreate the denser coverage of the standard 50K (∼50,000) genotype. Two alternative in silico chips were defined in this study that included markers selected to optimize minor allele frequency and spacing. The objective of this study was to compare the imputation accuracy of these custom low-density chips with a commercially available 3K chip. Data consisted of genotypes of 4,037 Holstein bulls, 1,219 Montbéliarde bulls, and 991 Blonde d'Aquitaine bulls. Criteria to select markers to include in low-density marker panels are described. To mimic a low-density genotype, all markers except the markers present on the low-density panel were masked in the validation population. Imputation was performed using the Beagle software. Combining the directed acyclic graph obtained with Beagle with the PHASEBOOK algorithm provides fast and accurate imputation that is suitable for routine genomic evaluations based on imputed genotypes. Overall, 95 to 99% of alleles were correctly imputed depending on the breed and the low-density chip used. The alternative low-density chips gave better results than the commercially available 3K chip. A low-density chip with 6,000 markers is a valuable genotyping tool suitable for both dairy and beef breeds. Such a tool could be used for preselection of young animals or large-scale screening of the female population.
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Affiliation(s)
- R Dassonneville
- INRA, UMR1313 Génétique Animale et Biologie Intégrative, 78350 Jouy-en-Josas, France.
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Dassonneville R, Brøndum RF, Druet T, Fritz S, Guillaume F, Guldbrandtsen B, Lund MS, Ducrocq V, Su G. Effect of imputing markers from a low-density chip on the reliability of genomic breeding values in Holstein populations. J Dairy Sci 2011; 94:3679-86. [PMID: 21700057 DOI: 10.3168/jds.2011-4299] [Citation(s) in RCA: 66] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2011] [Accepted: 04/08/2011] [Indexed: 11/19/2022]
Abstract
The purpose of this study was to investigate the imputation error and loss of reliability of direct genomic values (DGV) or genomically enhanced breeding values (GEBV) when using genotypes imputed from a 3,000-marker single nucleotide polymorphism (SNP) panel to a 50,000-marker SNP panel. Data consisted of genotypes of 15,966 European Holstein bulls from the combined EuroGenomics reference population. Genotypes with the low-density chip were created by erasing markers from 50,000-marker data. The studies were performed in the Nordic countries (Denmark, Finland, and Sweden) using a BLUP model for prediction of DGV and in France using a genomic marker-assisted selection approach for prediction of GEBV. Imputation in both studies was done using a combination of the DAGPHASE 1.1 and Beagle 2.1.3 software. Traits considered were protein yield, fertility, somatic cell count, and udder depth. Imputation of missing markers and prediction of breeding values were performed using 2 different reference populations in each country: either a national reference population or a combined EuroGenomics reference population. Validation for accuracy of imputation and genomic prediction was done based on national test data. Mean imputation error rates when using national reference animals was 5.5 and 3.9% in the Nordic countries and France, respectively, whereas imputation based on the EuroGenomics reference data set gave mean error rates of 4.0 and 2.1%, respectively. Prediction of GEBV based on genotypes imputed with a national reference data set gave an absolute loss of 0.05 in mean reliability of GEBV in the French study, whereas a loss of 0.03 was obtained for reliability of DGV in the Nordic study. When genotypes were imputed using the EuroGenomics reference, a loss of 0.02 in mean reliability of GEBV was detected in the French study, and a loss of 0.06 was observed for the mean reliability of DGV in the Nordic study. Consequently, the reliability of DGV using the imputed SNP data was 0.38 based on national reference data, and 0.48 based on EuroGenomics reference data in the Nordic validation, and the reliability of GEBV using the imputed SNP data was 0.41 based on national reference data, and 0.44 based on EuroGenomics reference data in the French validation.
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Affiliation(s)
- R Dassonneville
- INRA, UMR1313 Génétique Animale et Biologie Intégrative (GABI), 78350 Jouy-en-Josas, France.
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