Viktor Svensson

Viktor Svensson

 

Postdoctoral Fellow

Research group | Semiconductor physics
Main supervisor | Morten Hjorth-Jensen
Co-supervisor | Marianne Etzelmüller Bathen
Affiliation | Department of Physics, UiO
Contact | viktor.svensson@fys.uio.no


Short bio

2022-2024, Postdoc, Lund University 
Superconductor-semiconductor hybrid structures

2017-2021, PhD, National Centre for Nuclear Research (NCBJ), Warszawa 
International Max Planck Research School (IMPRS), Potsdam  
Relativistic hydrodynamics in heavy-ion collisions

2010-2016, Master of Science in Engineering physics, Lund University

Research interests and hobbies

I'm a theorist, and I'm interested in the potential of mesoscopic quantum systems for quantum technology and for answering questions about fundamental physics. This includes studying superconductor-semiconductor hybrid structures for topological quantum computation with Majorana bound states as well as using quantum systems for physical reservoir computing.

DSTrain project

Quantum dot networks as a platform for quantum neuromorphic computing

This project sits at the intersection between machine learning and quantum computing. Both these fields have the potential to change how we perform computation, but they also face significant challenges: energy use and training of large machine learning models, and achieving fine-grained control and error mitigation in quantum systems.

In this project, we will study how one can use the natural complex dynamics of quantum systems, combined with ideas from machine learning, to accomplish tasks such as forecasting of time series or the characterization of unknown quantum states. The quantum system will be used as a reservoir computer: the input signal is processed by the reservoir and a large number of measurements are collected and analyzed by traditional machine learning methods.

This requires less fine-grained control of the quantum system, which makes it suitable for devices available in the near future. This includes small and noisy quantum computers, but also systems which are not specifically designed for computation, such as a network of quantum dots. The hope is that one can sidestep the challenges listed above, while still offering a quantum advantage in processing power.


Publications

DSTrain publications

Previous publications

W. Samuelson, V. Svensson, and M. Leijnse, ‘Minimal quantum dot based Kitaev chain with only local superconducting proximity effect’, _Phys. Rev. B_, vol. 109, no. 3, p. 035415, Jan. 2024, doi: [10.1103/PhysRevB.109.035415](https://doi.org/10.1103/PhysRevB.109.035415).

N. C. Jayarama and V. Svensson, ‘Real-space circuit complexity as a probe of phase diagrams’, _Phys. Rev. B_, vol. 107, no. 7, p. 075122, Feb. 2023, doi: [10.1103/PhysRevB.107.075122](https://doi.org/10.1103/PhysRevB.107.075122).

M. C. Ba?uls, M. P. Heller, K. Jansen, J. Knaute, and V. Svensson, ‘Quantum information perspective on meson melting’, Phys. Rev. D, vol. 108, no. 7, p. 076016, Oct. 2023, doi: 10.1103/PhysRevD.108.076016.

M. P. Heller, A. Serantes, M. Spaliński, V. Svensson, and B. Withers, ‘Relativistic Hydrodynamics: A Singulant Perspective’, Phys. Rev. X, vol. 12, no. 4, p. 041010, Oct. 2022, doi: 10.1103/PhysRevX.12.041010.

M. P. Heller, A. Serantes, M. Spaliński, V. Svensson, and B. Withers, ‘Hydrodynamic Gradient Expansion Diverges beyond Bjorken Flow’, Phys. Rev. Lett., vol. 128, no. 12, p. 122302, Mar. 2022, doi: 10.1103/PhysRevLett.128.122302.

X. Du, M. P. Heller, S. Schlichting, and V. Svensson, ‘Exponential approach to the hydrodynamic attractor in Yang-Mills kinetic theory’, Phys. Rev. D, vol. 106, no. 1, p. 014016, Jul. 2022, doi: 10.1103/PhysRevD.106.014016.

M. P. Heller, A. Serantes, M. Spaliński, V. Svensson, and B. Withers, ‘Transseries for causal diffusive systems’, J. High Energ. Phys., vol. 2021, no. 4, p. 192, Apr. 2021, doi: 10.1007/JHEP04(2021)192.

M. P. Heller, A. Serantes, M. Spaliński, V. Svensson, and B. Withers, ‘Hydrodynamic gradient expansion in linear response theory’, Phys. Rev. D, vol. 104, no. 6, p. 066002, Sep. 2021, doi: 10.1103/PhysRevD.104.066002.

M. P. Heller, A. Serantes, M. Spaliński, V. Svensson, and B. Withers, ‘Convergence of hydrodynamic modes: insights from kinetic theory and holography’, _SciPost Physics_, vol. 10, no. 6, p. 123, Jun. 2021, doi: [10.21468/SciPostPhys.10.6.123](https://doi.org/10.21468/SciPostPhys.10.6.123).

M. P. Heller, R. Jefferson, M. Spaliński, and V. Svensson, ‘Hydrodynamic Attractors in Phase Space’, _Phys. Rev. Lett._, vol. 125, no. 13, p. 132301, Sep. 2020, doi: [10.1103/PhysRevLett.125.132301](https://doi.org/10.1103/PhysRevLett.125.132301).

M. C. Ba?uls, M. P. Heller, K. Jansen, J. Knaute, and V. Svensson, ‘From spin chains to real-time thermal field theory using tensor networks’, _Phys. Rev. Research_, vol. 2, no. 3, p. 033301, Aug. 2020, doi: [10.1103/PhysRevResearch.2.033301](https://doi.org/10.1103/PhysRevResearch.2.033301).

V. Svensson, ‘The Role of Nonhydrodynamic Modes in Bjorken Flow’, presented at the Cracow Epiphany Conference on Advances in Heavy Ion Physics, Acta Phys. Pol. B, 2019, pp. 1251--1261. doi: [10.5506/APhysPolB.50.1251](https://doi.org/10.5506/APhysPolB.50.1251).

M. P. Heller and V. Svensson, ‘How does relativistic kinetic theory remember about initial conditions?’, _Phys. Rev. D_, vol. 98, no. 5, p. 054016, Sep. 2018, doi: [10.1103/PhysRevD.98.054016](https://doi.org/10.1103/PhysRevD.98.054016).

M. P. Heller, A. Kurkela, M. Spaliński, and V. Svensson, ‘Hydrodynamization in kinetic theory: Transient modes and the gradient expansion’, _Phys. Rev. D_, vol. 97, no. 9, p. 091503, May 2018, doi: [10.1103/PhysRevD.97.091503](https://doi.org/10.1103/PhysRevD.97.091503).

Published Dec. 10, 2024 2:43 PM - Last modified Dec. 10, 2024 2:43 PM