Results 171 to 180 of about 34,577 (263)

Coherence Depletion in Quantum Algorithms. [PDF]

Entropy (Basel), 2019
Liu YC, Shang J, Zhang X.
europepmc   +1 more source

Study of Free‐Space Optical Quantum Network: Review and Prospectives

Advanced Science, EarlyView.
Free from the constraints of fiber connections, free‐space quantum network enables longer and more flexible quantum network connections. This review summarizes and comparatively analyzes free‐space quantum network experiments based on ground stations, satellites, and mobile platforms.
Hua‐Ying Liu, Zhenda Xie, Shining Zhu
wiley   +1 more source

Photonic scheme of discrete quantum Fourier transform for quantum algorithms via quantum dots. [PDF]

Sci Rep, 2019
Heo J, Won K, Yang HJ, Hong JP, Choi SG.
europepmc   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Metasurface for programmable quantum algorithms with classical and quantum light. [PDF]

Nanophotonics
Tanuwijaya RS, Liang H, Xi J, Wong WC, Yung TK, Tam WY, Li J.   +6 more
europepmc   +1 more source

Quantum algorithms for topological and geometric analysis of data. [PDF]

Nat Commun, 2016
Lloyd S, Garnerone S, Zanardi P.
europepmc   +1 more source

Generative AI‐Driven Accelerated Discovery of Passivation Molecules for Perovskite Solar Cells

Advanced Science, EarlyView.
A generative artificial intelligence (AI) framework combining a discriminative machine learning model (SMILES‐X) and a generative language model (GPT‐2) autonomously discovers new molecular passivators for perovskite solar cells (PSCs). Through an iterative design loop, over 100 000 candidates are generated and screened, and randomly selected molecules
Adroit T. N. Fajar, Guillaume Lambard, Jessie Manopo, Ruili Guo, Kevin Septioga, Rizfi F. Pari, Toshinori Matsushima, Zhanglin Guo   +7 more
wiley   +1 more source

Unleashing quantum algorithms with Qinterpreter: bridging the gap between theory and practice across leading quantum computing platforms. [PDF]

PeerJ Comput Sci
Contreras-Sepúlveda W, Villegas-Martínez BM, Gesing S, Sánchez-Mondragón JJ, Sánchez-Pérez JC, Vidales-Basurto CA, Escobedo-Alatorre JJ, Torres-Palencia AD, Palillero-Sandoval O, Licea-Rodriguez J, Lozano-Crisóstomo N, García-Melgarejo JC, Palacios-Perez EN.   +12 more
europepmc   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Towards provably efficient quantum algorithms for large-scale machine-learning models. [PDF]

Nat Commun
Liu J, Liu M, Liu JP, Ye Z, Wang Y, Alexeev Y, Eisert J, Jiang L.   +7 more
europepmc   +1 more source