Zobrazeno 1 - 10
of 668
pro vyhledávání: '"Minh, C. A."'
Quantum error mitigation (QEM) can recover accurate expectation values from a noisy quantum computer by trading off bias for variance, such that an averaged result is more accurate but takes longer to converge. Probabilistic error cancellation (PEC)
Externí odkaz:
http://arxiv.org/abs/2409.04401
Autor:
Robledo-Moreno, Javier, Motta, Mario, Haas, Holger, Javadi-Abhari, Ali, Jurcevic, Petar, Kirby, William, Martiel, Simon, Sharma, Kunal, Sharma, Sandeep, Shirakawa, Tomonori, Sitdikov, Iskandar, Sun, Rong-Yang, Sung, Kevin J., Takita, Maika, Tran, Minh C., Yunoki, Seiji, Mezzacapo, Antonio
A universal quantum computer can be used as a simulator capable of predicting properties of diverse quantum systems. Electronic structure problems in chemistry offer practical use cases around the hundred-qubit mark. This appears promising since curr
Externí odkaz:
http://arxiv.org/abs/2405.05068
Autor:
Sharma, Kunal, Tran, Minh C.
We propose an algorithm for simulating the dynamics of a geometrically local Hamiltonian $A$ under a small geometrically local perturbation $\alpha B$. In certain regimes, the algorithm achieves the optimal scaling and outperforms the state-of-the-ar
Externí odkaz:
http://arxiv.org/abs/2404.02966
Simulating quantum systems is one of the most promising avenues to harness the computational power of quantum computers. However, hardware errors in noisy near-term devices remain a major obstacle for applications. Ideas based on the randomization of
Externí odkaz:
http://arxiv.org/abs/2307.13028
In this work, we study and improve two leading error mitigation techniques, namely Probabilistic Error Cancellation (PEC) and Zero-Noise Extrapolation (ZNE), for estimating the expectation value of local observables. For PEC, we introduce a new estim
Externí odkaz:
http://arxiv.org/abs/2303.06496
A systematic review of machine learning models for management, prediction and classification of ARDS
Publikováno v:
Respiratory Research, Vol 25, Iss 1, Pp 1-14 (2024)
Abstract Aim Acute respiratory distress syndrome or ARDS is an acute, severe form of respiratory failure characterised by poor oxygenation and bilateral pulmonary infiltrates. Advancements in signal processing and machine learning have led to promisi
Externí odkaz:
https://doaj.org/article/62e4547f0ba54fdf98707f8fab2eb426
The intrinsic probabilistic nature of quantum systems makes error correction or mitigation indispensable for quantum computation. While current error-correcting strategies focus on correcting errors in quantum states or quantum gates, these fine-grai
Externí odkaz:
http://arxiv.org/abs/2301.08542
Autor:
Phan, Huy, Lorenzen, Kristian P., Heremans, Elisabeth, Chén, Oliver Y., Tran, Minh C., Koch, Philipp, Mertins, Alfred, Baumert, Mathias, Mikkelsen, Kaare, De Vos, Maarten
Human sleep is cyclical with a period of approximately 90 minutes, implying long temporal dependency in the sleep data. Yet, exploring this long-term dependency when developing sleep staging models has remained untouched. In this work, we show that w
Externí odkaz:
http://arxiv.org/abs/2301.03441
Publikováno v:
Phys. Rev. X 13, 011049 (2023)
A central challenge in analog quantum simulation is to characterize desirable physical properties of quantum states produced in experiments. However, in conventional approaches, the extraction of arbitrary information requires performing measurements
Externí odkaz:
http://arxiv.org/abs/2212.02517
Publikováno v:
PRX Quantum 4, 020323 (2023)
Quantum dynamics can be simulated on a quantum computer by exponentiating elementary terms from the Hamiltonian in a sequential manner. However, such an implementation of Trotter steps has gate complexity depending on the total Hamiltonian term numbe
Externí odkaz:
http://arxiv.org/abs/2211.09133