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pro vyhledávání: '"LIU, Junjie"'
The Dicke model, which describes the collective interaction between an ensemble of atoms and a single-mode photon field, serves as a fundamental framework for studying light-matter interactions and quantum electrodynamic phenomena. In this work, we i
Externí odkaz:
http://arxiv.org/abs/2411.08365
Autor:
Vaganov, Mikhail V., Suaud, Nicolas, Lambert, Francois, Cahier, Benjamin, Herrero, Christian, Guillot, Regis, Barra, Anne-Laure, Guihery, Nathalie, Mallah, Talal, Ardavan, Arzhang, Liu, Junjie
Controlling quantum spins using electric rather than magnetic fields promises significant architectural advantages for developing quantum technologies. In this context, spins in molecular nanomagnets offer tunability of spin-electric couplings (SEC)
Externí odkaz:
http://arxiv.org/abs/2409.01982
Learning representations with a high Probability of Necessary and Sufficient Causes (PNS) has been shown to enhance deep learning models' ability. This task involves identifying causal features that are both sufficient (guaranteeing the outcome) and
Externí odkaz:
http://arxiv.org/abs/2408.16577
Autor:
Liu, Junjie
Large-scale face clustering has achieved significant progress, with many efforts dedicated to learning to cluster large-scale faces with supervised-learning. However, complex model design and tedious clustering processes are typical in existing metho
Externí odkaz:
http://arxiv.org/abs/2408.13431
Self-supervised monocular depth estimation aims to infer depth information without relying on labeled data. However, the lack of labeled information poses a significant challenge to the model's representation, limiting its ability to capture the intr
Externí odkaz:
http://arxiv.org/abs/2406.08928
The realization of effective quantum error correction protocols remains a central challenge in the development of scalable quantum computers. Protocols employing redundancy over multiple physical qubits to encode a single error-protected logical qubi
Externí odkaz:
http://arxiv.org/abs/2405.20827
Autor:
Liu, Junjie, Jung, Kenneth A.
Publikováno v:
Phys. Rev. E 109, 044118 (2024)
Whether the strong coupling to thermal baths can improve the performance of quantum thermal machines remains an open issue under active debate. Here, we revisit quantum thermal machines operating with the quasi-static Carnot cycle and aim to unveil t
Externí odkaz:
http://arxiv.org/abs/2311.15465
Exploiting large language models (LLMs) to tackle reasoning has garnered growing attention. It still remains highly challenging to achieve satisfactory results in complex logical problems, characterized by plenty of premises within the prompt and req
Externí odkaz:
http://arxiv.org/abs/2310.03309
Through the Bayesian lens of data assimilation, uncertainty on model parameters is traditionally quantified through the posterior covariance matrix. However, in modern settings involving high-dimensional and computationally expensive forward models,
Externí odkaz:
http://arxiv.org/abs/2310.01397
Efficient RGB-D semantic segmentation has received considerable attention in mobile robots, which plays a vital role in analyzing and recognizing environmental information. According to previous studies, depth information can provide corresponding ge
Externí odkaz:
http://arxiv.org/abs/2308.06024