Experimental sample-efficient and device-independent GHZ state certification. [PDF]
Dos Santos Martins L +6 more
europepmc +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
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 +4 more
wiley +1 more source
Quantum-like Cognition and Decision-Making: Interpretation of Phases in Quantum-like Superposition. [PDF]
Khrennikov A.
europepmc +1 more source
Diffusion–Model–Driven Discovery of Ferroelectrics for Photocurrent Applications
We developed a diffusion model–based generative AI and high‐throughput screening framework that accelerates the discovery of photovoltaic ferroelectrics. By coupling AI driven crystal generation with machine learning and DFT screening, we identified Ca3P2 and LiCdP as new ferroelectric materials exhibiting strong polarization, feasible switching ...
Byung Chul Yeo +3 more
wiley +1 more source
A Survey on Proof of Sequential Work: Development, Security Analysis, and Application Prospects. [PDF]
Zhang J +7 more
europepmc +1 more source
Quaternary topological BiSbSe2Te are synthesized and demonstrates a broad spectral band photoresponse, ranging from infrared to terahertz and to millimeter waves, with a particular excellence on detection of low quantum energy terahertz photons. The observed photoresponse is attributed to the excitation of plasmonic nonequilibrium electrons originating
Tianning Zhang +14 more
wiley +1 more source
QRBT: Quantum Driven Reinforcement Learning for Scalable Blockchain Transaction Processing. [PDF]
Lella KK, Mallu SRK.
europepmc +1 more source
Generative AI‐Driven Accelerated Discovery of Passivation Molecules for Perovskite Solar Cells
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 +7 more
wiley +1 more source
Logarithmic-Size Post-Quantum Linkable Ring Signatures Based on Aggregation Operations. [PDF]
Zheng M +5 more
europepmc +1 more source
Quantum Noise Random Number Generator Architecture
Recommendations of how to design a quantum entropy source in order to generate unpredictable private and secret random ...
openaire +1 more source

