Summary
One of the biggest and most relevant challenges in physics is the accurate study of strongly correlated quantum many-body systems, which give rise to very remarkable phenomena like high-Tc superconductivity (HTSC), quantum spin liquids with topological order, and other novel phases of matter. Understanding these systems is the key to designing new materials and quantum devices for future groundbreaking technologies. In recent years enormous progress in the study of these systems has been achieved with two-dimensional tensor network algorithms, which can be seen as a generalization of the powerful density-matrix renormalization group method to higher dimensions. While already the current algorithms are very powerful and outperform other state-of-the-art approaches, the development of new algorithms with a higher accuracy and broader application range is crucial to enable to solve the most pressing open problems.
Building upon my previous breakthroughs in this field, I will develop the next generation of tensor network algorithms, including novel powerful methods for ground states, time evolution, spectral functions, finite temperature, open systems, and multi-scale approaches. I will use them for groundbreaking simulations of relevant open problems in several fields with unprecedented accuracy. Major milestones include (1) simulations of realistic models of cuprate materials in order to shed new light on the pseudogap phase and pairing mechanism in HTSC, (2) cutting-edge simulations of frustrated materials to reveal the nature of excitations and thermodynamic properties of quantum spin liquids and other challenging states, and (3) predictions of novel states of matter in SU(N) and open quantum systems which can be realized in experimental quantum simulators. This ambitious project will strongly advance our fundamental understanding of strongly correlated systems and set a new state-of-the-art in simulating quantum many-body problems.
Building upon my previous breakthroughs in this field, I will develop the next generation of tensor network algorithms, including novel powerful methods for ground states, time evolution, spectral functions, finite temperature, open systems, and multi-scale approaches. I will use them for groundbreaking simulations of relevant open problems in several fields with unprecedented accuracy. Major milestones include (1) simulations of realistic models of cuprate materials in order to shed new light on the pseudogap phase and pairing mechanism in HTSC, (2) cutting-edge simulations of frustrated materials to reveal the nature of excitations and thermodynamic properties of quantum spin liquids and other challenging states, and (3) predictions of novel states of matter in SU(N) and open quantum systems which can be realized in experimental quantum simulators. This ambitious project will strongly advance our fundamental understanding of strongly correlated systems and set a new state-of-the-art in simulating quantum many-body problems.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101001604 |
| Start date: | 01-12-2021 |
| End date: | 30-11-2026 |
| Total budget - Public funding: | 1 999 630,00 Euro - 1 999 630,00 Euro |
Cordis data
Original description
One of the biggest and most relevant challenges in physics is the accurate study of strongly correlated quantum many-body systems, which give rise to very remarkable phenomena like high-Tc superconductivity (HTSC), quantum spin liquids with topological order, and other novel phases of matter. Understanding these systems is the key to designing new materials and quantum devices for future groundbreaking technologies. In recent years enormous progress in the study of these systems has been achieved with two-dimensional tensor network algorithms, which can be seen as a generalization of the powerful density-matrix renormalization group method to higher dimensions. While already the current algorithms are very powerful and outperform other state-of-the-art approaches, the development of new algorithms with a higher accuracy and broader application range is crucial to enable to solve the most pressing open problems.Building upon my previous breakthroughs in this field, I will develop the next generation of tensor network algorithms, including novel powerful methods for ground states, time evolution, spectral functions, finite temperature, open systems, and multi-scale approaches. I will use them for groundbreaking simulations of relevant open problems in several fields with unprecedented accuracy. Major milestones include (1) simulations of realistic models of cuprate materials in order to shed new light on the pseudogap phase and pairing mechanism in HTSC, (2) cutting-edge simulations of frustrated materials to reveal the nature of excitations and thermodynamic properties of quantum spin liquids and other challenging states, and (3) predictions of novel states of matter in SU(N) and open quantum systems which can be realized in experimental quantum simulators. This ambitious project will strongly advance our fundamental understanding of strongly correlated systems and set a new state-of-the-art in simulating quantum many-body problems.
Status
SIGNEDCall topic
ERC-2020-COGUpdate Date
27-04-2024
Geographical location(s)
