| 1. |
- Joffrin, E., et al.
(författare)
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Overview of the JET preparation for deuterium-tritium operation with the ITER like-wall
- 2019
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Ingår i: Nuclear Fusion. - : IOP Publishing. - 1741-4326 .- 0029-5515. ; 59:11
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Forskningsöversikt (refereegranskat)abstract
- For the past several years, the JET scientific programme (Pamela et al 2007 Fusion Eng. Des. 82 590) has been engaged in a multi-campaign effort, including experiments in D, H and T, leading up to 2020 and the first experiments with 50%/50% D-T mixtures since 1997 and the first ever D-T plasmas with the ITER mix of plasma-facing component materials. For this purpose, a concerted physics and technology programme was launched with a view to prepare the D-T campaign (DTE2). This paper addresses the key elements developed by the JET programme directly contributing to the D-T preparation. This intense preparation includes the review of the physics basis for the D-T operational scenarios, including the fusion power predictions through first principle and integrated modelling, and the impact of isotopes in the operation and physics of D-T plasmas (thermal and particle transport, high confinement mode (H-mode) access, Be and W erosion, fuel recovery, etc). This effort also requires improving several aspects of plasma operation for DTE2, such as real time control schemes, heat load control, disruption avoidance and a mitigation system (including the installation of a new shattered pellet injector), novel ion cyclotron resonance heating schemes (such as the three-ions scheme), new diagnostics (neutron camera and spectrometer, active Alfven eigenmode antennas, neutral gauges, radiation hard imaging systems...) and the calibration of the JET neutron diagnostics at 14 MeV for accurate fusion power measurement. The active preparation of JET for the 2020 D-T campaign provides an incomparable source of information and a basis for the future D-T operation of ITER, and it is also foreseen that a large number of key physics issues will be addressed in support of burning plasmas.
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| 2. |
- Bergström, Anders, et al.
(författare)
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Grey wolf genomic history reveals a dual ancestry of dogs
- 2022
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 607:7918, s. 313-320
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Tidskriftsartikel (refereegranskat)abstract
- The grey wolf (Canis lupus) was the first species to give rise to a domestic population, and they remained widespread throughout the last Ice Age when many other large mammal species went extinct. Little is known, however, about the history and possible extinction of past wolf populations or when and where the wolf progenitors of the present-day dog lineage (Canis familiaris) lived. Here we analysed 72 ancient wolf genomes spanning the last 100,000 years from Europe, Siberia and North America. We found that wolf populations were highly connected throughout the Late Pleistocene, with levels of differentiation an order of magnitude lower than they are today. This population connectivity allowed us to detect natural selection across the time series, including rapid fixation of mutations in the gene IFT88 40,000–30,000 years ago. We show that dogs are overall more closely related to ancient wolves from eastern Eurasia than to those from western Eurasia, suggesting a domestication process in the east. However, we also found that dogs in the Near East and Africa derive up to half of their ancestry from a distinct population related to modern southwest Eurasian wolves, reflecting either an independent domestication process or admixture from local wolves. None of the analysed ancient wolf genomes is a direct match for either of these dog ancestries, meaning that the exact progenitor populations remain to be located.
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| 3. |
- Kozin, Valerii K., et al.
(författare)
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Effective Hamiltonians for Discrete Time Crystals
- 2020
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Ingår i: Fifth international conference on quantum technologies (ICQT-2019). - : AIP Publishing.
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Konferensbidrag (refereegranskat)abstract
- We analyze the effective Hamiltonian for the 2T discrete time crystal (2T-DTC or DTC). This effective Hamiltonian is given by spin 1/2 many-body Hamiltonian which includes all-to-all coupling terms, thus being of infinite range. We describe the possible structure of the Hamiltonian, including many-body localized version which prevents thermalization. Finally, we show how the DTC melts when symmetry breaking terms are added.
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| 4. |
- Kozin, Valerii K., et al.
(författare)
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Quantum Time Crystals from Hamiltonians with Long-Range Interactions
- 2019
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Ingår i: Physical Review Letters. - : American Physical Society. - 0031-9007 .- 1079-7114. ; 123:21
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Tidskriftsartikel (refereegranskat)abstract
- Time crystals correspond to a phase of matter where time-translational symmetry (TTS) is broken. Up to date, they are well studied in open quantum systems, where an external drive allows us to break discrete TTS, ultimately leading to Floquet time crystals. At the same time, genuine time crystals for closed quantum systems are believed to be impossible. In this study we propose a form of a Hamiltonian for which the unitary dynamics exhibits the time crystalline behavior and breaks continuous TTS. This is based on a spin-1/2 many-body Hamiltonian which has long-range multispin interactions in the form of spin strings, thus bypassing previously known no-go theorems. We show that quantum time crystals are stable to local perturbations at zero temperature. Finally, we reveal the intrinsic connection between continuous and discrete TTS, thus linking the two realms.
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| 5. |
- Shirinyan, Albert A., et al.
(författare)
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Self-organizing maps as a method for detecting phase transitions and phase identification
- 2019
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Ingår i: Physical Review B. - : American Physical Society. - 2469-9950 .- 2469-9969. ; 99:4
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Tidskriftsartikel (refereegranskat)abstract
- Originating from image recognition, methods of machine learning allow for effective feature extraction and dimensionality reduction in multidimensional datasets, thereby providing an extraordinary tool to deal with classical and quantum models in many-body physics. In this study, we employ a specific unsupervised machine learning technique-self-organizing maps-to create a low-dimensional representation of microscopic states, relevant for macroscopic phase identification and detecting phase transitions. We explore the properties of spin Hamiltonians of two archetype model systems: a two-dimensional Heisenberg ferromagnet and a three-dimensional crystal, Fe in the body-centered-cubic structure. The method of self-organizing maps, which is known to conserve connectivity of the initial dataset, is compared to the cumulant method theory and is shown to be as accurate while being computationally more efficient in determining a phase transition temperature. We argue that the method proposed here can be applied to explore a broad class of second-order phase-transition systems, not only magnetic systems but also, for example, order-disorder transitions in alloys.
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