Bridging model and experiment in systems neuroscience with Cleo: the Closed-Loop, Electrophysiology, and Optophysiology simulation testbed

Kavli Affiliate: Adam S. Charles | Authors: Kyle A. Johnsen, Nathanael A. Cruzado, Zachary C. Menard, Adam A. Willats, Adam S. Charles, Jeffrey E. Markowitz and Christopher J. Rozell | Summary: Systems neuroscience has experienced an explosion of new tools for reading and writing neural activity, enabling exciting new experiments such as all-optical or closed-loop […]


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3D map-guided modeling of functional endometrial tissue using multi-compartment assembloids

Kavli Affiliate: Denis Wirtz | KEHAN REN, VICTORIA DUARTE, XIN DI ZHOU, BRYAN HO, ANDRE FORJAZ, ASHLEIGH CRAWFORD, GRETCHEN M ALICEA-REBECCA, SAURABH JOSHI, PRAFUL R NAIR, EBAN A HANNA and DENIS WIRTZ | Summary: The human endometrium is a dynamic tissue that lines the uterus and undergoes constant remodeling, making it especially susceptible to gynecological […]


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A Single-Molecule Quantum Heat Engine

Kavli Affiliate: Herre S. J. Van Der Zant | First 5 Authors: Serhii Volosheniuk, Serhii Volosheniuk, , , | Summary: Particle-exchange heat engines operate without moving parts or time-dependent driving, relying solely on static energy-selective transport. Here, we realize a particle-exchange quantum heat engine based on a single diradical molecule, only a few nanometers in […]


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Tunable Superconducting Quantum Interference Device Coupler for Fluxonium Qubits

Kavli Affiliate: Irfan Siddiqi | First 5 Authors: Abhishek Chakraborty, Abhishek Chakraborty, , , | Summary: Tunable couplers enable high-fidelity two-qubit gates leveraging high on/off coupling ratios and reduced crosstalk within a single design. We investigate a galvanically connected direct-current superconducting quantum interference device (dc SQUID) as a minimal tunable coupling element for fluxonium qubits. […]


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Beyond Emotion Recognition: A Multi-Turn Multimodal Emotion Understanding and Reasoning Benchmark

Kavli Affiliate: Zhuo Li | First 5 Authors: Jinpeng Hu, Jinpeng Hu, , , | Summary: Multimodal large language models (MLLMs) have been widely applied across various fields due to their powerful perceptual and reasoning capabilities. In the realm of psychology, these models hold promise for a deeper understanding of human emotions and behaviors. However, […]


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