Kavli Affiliate: Hsiao-Mei (Sherry) Cho| First 5 Authors: [#item_custom_name[1, [#item_custom_name[2, [#item_custom_name[3, [#item_custom_name[4, [#item_custom_name[5| Summary:The efficient generation of random quantum states is a long-standing challenge, motivated by their diverse applications in quantum information processing tasks. In this work, we identify entanglement as the key resource that enables local random unitaries to generate global random states by […]

Kavli Affiliate: Noah Kurinsky | Summary:We present a detailed characterization of a new generation of athermal-phonon single-charge sensitive Si HVeV detectors, the best of which achieved 612 meV $pm$ 4 meV baseline resolution. Our sub-eV energy resolution enables precise measurements of single-photon events and reveal consistent energy losses of 0.81 eV $pm$ 0.03 eV per […]

Kavli Affiliate: Noah Kurinsky | Summary:We present a detailed characterization of a new generation of athermal-phonon single-charge sensitive Si HVeV detectors, the best of which achieved 589~meV~$pm$~5~meV baseline resolution. Our sub-eV energy resolution enables precise measurements of single-photon events and reveal consistent energy losses of 0.92~eV~$pm$~0.02~eV per charge excitation across two facilities. We demonstrate that […]

Kavli Affiliate: Noah Kurinsky | Summary:The Superconducting Quasiparticle-Amplifying Transmon (SQUAT) is a new sensor architecture for THz (meV) detection based on a weakly charge-sensitive transmon directly coupled to a transmission line. In such devices, energy depositions break Cooper pairs in the qubit capacitor islands, generating quasiparticles. Quasiparticles that tunnel across the Josephson junction change the […]

Kavli Affiliate: Hsiao-Mei (Sherry) Cho| First 5 Authors: [#item_custom_name[1, [#item_custom_name[2, [#item_custom_name[3, [#item_custom_name[4, [#item_custom_name[5| Summary:Language-driven dexterous grasp generation requires the models to understand task semantics, 3D geometry, and complex hand-object interactions. While vision-language models have been applied to this problem, existing approaches directly map observations to grasp parameters without intermediate reasoning about physical interactions. We present […]

Kavli Affiliate: Hsiao-Mei (Sherry) Cho| First 5 Authors: [#item_custom_name[1, [#item_custom_name[2, [#item_custom_name[3, [#item_custom_name[4, [#item_custom_name[5| Summary:Deploying speaker verification on resource-constrained devices remains challenging due to the computational cost of high-capacity models; knowledge distillation (KD) offers a remedy. Classical KD entangles target confidence with non-target structure in a Kullback-Leibler term, limiting the transfer of relational information. Decoupled KD […]

Kavli Affiliate: Eli Rykoff | Summary:We introduce IRMaGiC, an algorithm built based on RedMaGiC desgined to enhance the selection of Luminous Red Galaxies (LRGs) across the redshift range $1 leq z leq 2$. We show that this method extends the capabilities of the redMaGiC algorithm by applying it to simulated photometric data from the Vera […]

Kavli Affiliate: Eli Rykoff | Summary:We introduce IRMaGiC, an algorithm built based on RedMaGiC desgined to enhance the selection of Luminous Red Galaxies (LRGs) across the redshift range $1 leq z leq 2$. We show that this method extends the capabilities of the redMaGiC algorithm by applying it to simulated photometric data from the Vera […]

Kavli Affiliate: Seth Digel | Summary:The Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that challenge traditional analysis pipelines. The LSST Dark Energy Science Collaboration (DESC) aims to derive robust constraints on dark energy and dark matter from these data, […]

Kavli Affiliate: Hsiao-Mei (Sherry) Cho| First 5 Authors: [#item_custom_name[1, [#item_custom_name[2, [#item_custom_name[3, [#item_custom_name[4, [#item_custom_name[5| Summary:Open-vocabulary keyword spotting (KWS) with text-based enrollment has emerged as a flexible alternative to fixed-phrase triggers. Prior utterance-level matching methods, from an embedding-learning standpoint, learn embeddings at a single fixed dimensionality. We depart from this design and propose Matryoshka Audio-Text Embeddings (MATE), […]