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CERN Document Server 找到 14 笔记录  1 - 10下一个  跳到记录: 检索需时 0.78 秒. 
1.
Statistics of topological defects across a phase transition in a superconducting quantum processor / Teplitskiy, Daniil (CERN) ; Kiss, Oriel (CERN) ; Grossi, Michele (CERN) ; Mandarino, Antonio (Gdansk U. ; Milan U.)
When a quantum phase transition is crossed within a finite time, critical slowing down disrupts adiabatic dynamics, resulting in the formation of topological defects. [...]
arXiv:2410.06250. - 7.
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2.
Early Fault-Tolerant Quantum Algorithms in Practice: Application to Ground-State Energy Estimation / Kiss, Oriel (U. Toronto (main) ; CERN ; U. Trento (main)) ; Azad, Utkarsh (U. Toronto (main)) ; Requena, Borja (U. Toronto (main) ; ICFO, Barcelona) ; Roggero, Alessandro (U. Trento (main) ; ECT, Trento ; FBK, CIT, Trento ; INFN, Trento) ; Wakeham, David (U. Toronto (main)) ; Arrazola, Juan Miguel (U. Toronto (main))
We explore the practicality of early fault-tolerant quantum algorithms, focusing on ground-state energy estimation problems. [...]
arXiv:2405.03754. - 16 p.
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3.
Symmetry-invariant quantum machine learning force fields / Le, Isabel Nha Minh (IBM, Zurich ; JARA, Aachen) ; Kiss, Oriel (CERN) ; Schuhmacher, Julian (IBM, Zurich) ; Tavernelli, Ivano (IBM, Zurich) ; Tacchino, Francesco (IBM, Zurich)
Machine learning techniques are essential tools to compute efficient, yet accurate, force fields for atomistic simulations. [...]
arXiv:2311.11362. - 12 p.
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4.
Counterdiabatic optimized driving in quantum phase sensitive models / Barone, Francesco Pio (CERN ; Padua U.) ; Kiss, Oriel (CERN) ; Grossi, Michele (CERN) ; Vallecorsa, Sofia (CERN) ; Mandarino, Antonio (Gdansk U.)
State preparation plays a pivotal role in numerous quantum algorithms, including quantum phase estimation. This paper extends and benchmarks counterdiabatic driving protocols across three one-dimensional spin systems characterized by phase transitions: the axial next-nearest neighbor Ising (ANNNI), XXZ, and Haldane-Shastry (HS) models. [...]
arXiv:2311.04282.- 2024-03-19 - 16 p. - Published in : New J. Phys. 26 (2024) 033031 Fulltext: 2311.04282 - PDF; document - PDF;
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5.
Hybrid Ground-State Quantum Algorithms based on Neural Schrödinger Forging / de Schoulepnikoff, Paulin (Ecole Polytechnique, Lausanne ; CERN) ; Kiss, Oriel (CERN) ; Vallecorsa, Sofia (CERN) ; Carleo, Giuseppe (Ecole Polytechnique, Lausanne) ; Grossi, Michele (CERN)
Entanglement forging based variational algorithms leverage the bi-partition of quantum systems for addressing ground state problems. The primary limitation of these approaches lies in the exponential summation required over the numerous potential basis states, or bitstrings, when performing the Schmidt decomposition of the whole system. [...]
arXiv:2307.02633.- 2024-04-04 - 15 p. - Published in : Phys. Rev. Res. 6 (2024) 023021 Fulltext: 2307.02633 - PDF; Publication - PDF;
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6.
Trainability barriers and opportunities in quantum generative modeling / Rudolph, Manuel S. (Ecole Polytechnique, Lausanne) ; Lerch, Sacha (Ecole Polytechnique, Lausanne) ; Thanasilp, Supanut (Ecole Polytechnique, Lausanne ; Chulalongkorn U.) ; Kiss, Oriel (CERN ; Geneva U.) ; Shaya, Oxana (LPHE, Lausanne) ; Vallecorsa, Sofia (CERN) ; Grossi, Michele (CERN) ; Holmes, Zoë (Ecole Polytechnique, Lausanne)
Quantum generative models, in providing inherently efficient sampling strategies, show promise for achieving a near-term advantage on quantum hardware. Nonetheless, important questions remain regarding their scalability. [...]
arXiv:2305.02881.- 2024-11-13 - 52 p. - Published in : npj Quantum Inf. 10 (2024) 116 Fulltext: 2305.02881 - PDF; document - PDF;
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7.
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Stochastic quantum simulations for scattering experiments / Kiss, Oriel Orphee Moira (speaker) (Universite de Geneve (CH))
NEW START TIME: 14:00Simulating many-body quantum systems is a promising task for quantum computers. However, early fault-tolerant devices are not expected to correct arbitrary amounts of error, making the quest for better algorithms an important task [...]
2023 - 3734. QTI Lectures External link: Event details In : Stochastic quantum simulations for scattering experiments
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8.
Importance sampling for stochastic quantum simulations / Kiss, Oriel (CERN ; U. Geneva (main)) ; Grossi, Michele (CERN) ; Roggero, Alessandro (Trento U. ; INFN, Trento)
Simulating many-body quantum systems is a promising task for quantum computers. However, the depth of most algorithms, such as product formulas, scales with the number of terms in the Hamiltonian, and can therefore be challenging to implement on near-term, as well as early fault-tolerant quantum devices. [...]
arXiv:2212.05952.- 2023-04-13 - 17 p. - Published in : Quantum 7 (2023) 977 Fulltext: document - PDF; Publication - PDF; 2212.05952 - PDF; External link: Preprint
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9.
Finite-size criticality in fully connected spin models on superconducting quantum hardware / Grossi, Michele (CERN) ; Kiss, Oriel (CERN ; Geneva U.) ; De Luca, Francesco (Trieste U.) ; Zollo, Carlo (Trieste U.) ; Gremese, Ian (Trieste U.) ; Mandarino, Antonio (Gdansk U.)
The emergence of a collective behavior in a many-body system is responsible of the quantum criticality separating different phases of matter. Interacting spin systems in a magnetic field offer a tantalizing opportunity to test different approaches to study quantum phase transitions. [...]
arXiv:2208.02731.- 2023-02-10 - 13 p. - Published in : Phys. Rev. E 107 (2023) 024113 Fulltext: PDF;
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10.
Quantum phase detection generalization from marginal quantum neural network models / Monaco, Saverio (CERN ; Padua U.) ; Kiss, Oriel (CERN ; Geneva U.) ; Mandarino, Antonio (Gdansk U.) ; Vallecorsa, Sofia (CERN) ; Grossi, Michele (CERN)
Quantum machine learning offers a promising advantage in extracting information about quantum states, e.g. phase diagram. [...]
arXiv:2208.08748.- 2023-02-10 - 6 p. - Published in : Phys. Rev. B 107 (2023) L081105 Fulltext: Publication - PDF; 2208.08748 - PDF;
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CERN Document Server : 找到 14 笔记录   1 - 10下一个  跳到记录:
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