The look of high-velocity red-giant star collisions

Kavli Affiliate: Pau Amaro Seoane | First 5 Authors: Luc Dessart, Taeho Ryu, Pau Amaro Seoane, Andrew M. Taylor, | Summary: High-velocity stellar collisions driven by a supermassive black hole (BH) or BH-driven disruptive collisions, in dense, nuclear clusters can rival the energetics of supergiant star explosions following gravitational collapse of their iron core. Here, […]


Continue.. The look of high-velocity red-giant star collisions

Modulation Instability and Wavenumber Bandgap Breathers in a Time Layered Phononic Lattice

Kavli Affiliate: Chiara Daraio | First 5 Authors: Christopher Chong, Brian Kim, Evelyn Wallace, Chiara Daraio, | Summary: We demonstrate the existence of wavenumber bandgap (q-gap) breathers in a time-periodic phononic lattice. These breathers are localized in time and periodic in space, and are the counterparts to the classical breathers found in spatially-periodic systems. We […]


Continue.. Modulation Instability and Wavenumber Bandgap Breathers in a Time Layered Phononic Lattice

Modulation Instability and Wavenumber Bandgap Breathers in a Time Layered Phononic Lattice

Kavli Affiliate: Chiara Daraio | First 5 Authors: Christopher Chong, Brian Kim, Evelyn Wallace, Chiara Daraio, | Summary: We demonstrate the existence of wavenumber bandgap (q-gap) breathers in a time-periodic phononic lattice. These breathers are localized in time and periodic in space, and are the counterparts to the classical breathers found in spatially-periodic systems. We […]


Continue.. Modulation Instability and Wavenumber Bandgap Breathers in a Time Layered Phononic Lattice

The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets

Kavli Affiliate: Max Tegmark | First 5 Authors: Samuel Marks, Max Tegmark, , , | Summary: Large Language Models (LLMs) have impressive capabilities, but are prone to outputting falsehoods. Recent work has developed techniques for inferring whether a LLM is telling the truth by training probes on the LLM’s internal activations. However, this line of […]


Continue.. The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets

The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets

Kavli Affiliate: Max Tegmark | First 5 Authors: Samuel Marks, Max Tegmark, , , | Summary: Large Language Models (LLMs) have impressive capabilities, but are also prone to outputting falsehoods. Recent work has developed techniques for inferring whether a LLM is telling the truth by training probes on the LLM’s internal activations. However, this line […]


Continue.. The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets

Discovery of a variable energy-dependent X-ray polarization in the accreting neutron star GX 5-1

Kavli Affiliate: Herman L. Marshall | First 5 Authors: Sergio Fabiani, Fiamma Capitanio, Rosario Iaria, Juri Poutanen, Andrea Gnarini | Summary: We report on the coordinated observations of the neutron star low-mass X-ray binary (NS-LMXB) gx in X-rays (IXPE, NICER, Nustar and INTEGRAL), optical (REM and LCO), near-infrared (REM), mid-infrared (VLT VISIR), and radio (ATCA). […]


Continue.. Discovery of a variable energy-dependent X-ray polarization in the accreting neutron star GX 5-1

Pi-DUAL: Using Privileged Information to Distinguish Clean from Noisy Labels

Kavli Affiliate: Ke Wang | First 5 Authors: Ke Wang, Guillermo Ortiz-Jimenez, Rodolphe Jenatton, Mark Collier, Efi Kokiopoulou | Summary: Label noise is a pervasive problem in deep learning that often compromises the generalization performance of trained models. Recently, leveraging privileged information (PI) — information available only during training but not at test time — […]


Continue.. Pi-DUAL: Using Privileged Information to Distinguish Clean from Noisy Labels

Pi-DUAL: Using Privileged Information to Distinguish Clean from Noisy Labels

Kavli Affiliate: Ke Wang | First 5 Authors: Ke Wang, Guillermo Ortiz-Jimenez, Rodolphe Jenatton, Mark Collier, Efi Kokiopoulou | Summary: Label noise is a pervasive problem in deep learning that often compromises the generalization performance of trained models. Recently, leveraging privileged information (PI) — information available only during training but not at test time — […]


Continue.. Pi-DUAL: Using Privileged Information to Distinguish Clean from Noisy Labels

Measurement of branching fractions and direct $CP$ asymmetries for $B to Kπ$ and $Btoππ$ decays at Belle II

Kavli Affiliate: T. Higuchi | First 5 Authors: Belle II Collaboration, I. Adachi, L. Aggarwal, H. Ahmed, H. Aihara | Summary: We report measurements of the branching fractions and direct $it{CP}$ asymmetries of the decays $B^0 to K^+ pi^-$, $B^+ to K^+ pi^0$, $B^+ to K^0 pi^+$, and $B^0 to K^0 pi^0$, and use these […]


Continue.. Measurement of branching fractions and direct $CP$ asymmetries for $B to Kπ$ and $Btoππ$ decays at Belle II