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Juneteenth - what you and I need to know https://muz4now.com/2023/juneteenth-what-you-and-i-need-to-know/

Juneteenth - what you and I need to know
Stan Stewart - @muz4now

SplashNet: Split-and-Share Encoders for Accurate and Efficient Typing with Surface Electromyography
Nima Hadidi, Jason Chan, Ebrahim Feghhi, Jonathan Kao
https://arxiv.org/abs/2506.12356

SplashNet: Split-and-Share Encoders for Accurate and Efficient Typing with Surface Electromyography
Surface electromyography (sEMG) at the wrists could enable natural, keyboard-free text entry, yet the state-of-the-art emg2qwerty baseline still misrecognizes $51.8\%$ of characters in the zero-shot setting on unseen users and $7.0\%$ after user-specific fine-tuning. We trace many of these errors to mismatched cross-user signal statistics, fragile reliance on high-order feature dependencies, and the absence of architectural inductive biases aligned with the bilateral nature of typing. To addres…

Learning From the Past with Cascading Eligibility Traces
Tokiniaina Raharison Ralambomihanta, Ivan Anokhin, Roman Pogodin, Samira Ebrahimi Kahou, Jonathan Cornford, Blake Aaron Richards
https://arxiv.org/abs/2506.14598

Learning From the Past with Cascading Eligibility Traces
Animals often receive information about errors and rewards after a significant delay. For example, there is typically a delay of tens to hundreds of milliseconds between motor actions and visual feedback. The standard approach to handling delays in models of synaptic plasticity is to use eligibility traces. However, standard eligibility traces that decay exponentially mix together any events that happen during the delay, presenting a problem for any credit assignment signal that occurs with a s…

Empirically-Calibrated H100 Node Power Models for Reducing Uncertainty in AI Training Energy Estimation
Alex C. Newkirk, Jared Fernandez, Jonathan Koomey, Imran Latif, Emma Strubell, Arman Shehabi, Constantine Samaras
https://arxiv.org/abs/2506.14551

Empirically-Calibrated H100 Node Power Models for Reducing Uncertainty in AI Training Energy Estimation
As AI's energy demand continues to grow, it is critical to enhance the understanding of characteristics of this demand, to improve grid infrastructure planning and environmental assessment. By combining empirical measurements from Brookhaven National Laboratory during AI training on 8-GPU H100 systems with open-source benchmarking data, we develop statistical models relating computational intensity to node-level power consumption. We measure the gap between manufacturer-rated thermal design pow…

ExoStart: Efficient learning for dexterous manipulation with sensorized exoskeleton demonstrations
Zilin Si, Jose Enrique Chen, M. Emre Karagozler, Antonia Bronars, Jonathan Hutchinson, Thomas Lampe, Nimrod Gileadi, Taylor Howell, Stefano Saliceti, Lukasz Barczyk, Ilan Olivarez Correa, Tom Erez, Mohit Shridhar, Murilo Fernandes Martins, Konstantinos Bousmalis, Nicolas Heess, Francesco Nori, Maria Bauza Villalonga

ExoStart: Efficient learning for dexterous manipulation with sensorized exoskeleton demonstrations
Recent advancements in teleoperation systems have enabled high-quality data collection for robotic manipulators, showing impressive results in learning manipulation at scale. This progress suggests that extending these capabilities to robotic hands could unlock an even broader range of manipulation skills, especially if we could achieve the same level of dexterity that human hands exhibit. However, teleoperating robotic hands is far from a solved problem, as it presents a significant challenge …

Multi-state detection and spatial addressing in a microscope for ultracold molecules
Jonathan M. Mortlock, Adarsh P. Raghuram, Benjamin P. Maddox, Philip D. Gregory, Simon L. Cornish
https://arxiv.org/abs/2506.12329

Multi-state detection and spatial addressing in a microscope for ultracold molecules
Precise measurement of the particle number, spatial distribution and internal state is fundamental to all proposed experiments with ultracold molecules both in bulk gases and optical lattices. Here, we demonstrate in-situ detection of individual molecules in a bulk sample of 87Rb133Cs molecules. Extending techniques from atomic quantum gas microscopy, we pin the molecules in a deep two-dimensional optical lattice and, following dissociation, collect fluorescence from the constituent atoms using…

Discovery of Faint Nebulosity Around a Z Camelopardalis-type Cataclysmic Variable in Antlia: Nova Shell or Ancient Planetary Nebula?
Howard E. Bond (Penn State University, STScI), Dana Patchick (Deep Sky Hunters Consortium), Daniel Stern (MEA Observatory), Jonathan Talbot (Stark Bayou Observatory), John R. Thorstensen (Dartmouth)
https://

Discovery of Faint Nebulosity Around a Z Camelopardalis-type Cataclysmic Variable in Antlia: Nova Shell or Ancient Planetary Nebula?
We report our discovery of a faint nebula surrounding a previously little-studied 15th-mag variable star, ASASSN-19ds, in the southern-hemisphere constellation Antlia. Spectra verify that the star is a cataclysmic variable (CV). Using new and archival photometry, we confirm that ASASSN-19ds is an eclipsing binary with an orbital period of 0.139 days (3.34 hr). Moreover, its out-of-eclipse brightness shows a "sawtooth" light curve with an amplitude of $\sim$1~mag and an interval between peaks th…

Comparing the Space Densities of Millisecond-Spin Magnetars and Fast X-Ray Transients
Sumedha Biswas, Peter G. Jonker, M. Coleman Miller, Andrew Levan, Jonathan Quirola-V\'asquez
https://arxiv.org/abs/2506.11676

Comparing the Space Densities of Millisecond-Spin Magnetars and Fast X-Ray Transients
Fast X-ray transients (FXTs) are bright X-ray flashes with durations of minutes to hours, peak isotropic luminosities of L_X,peak ~ 10^42-10^47 erg/s, and total isotropic energies of E ~ 10^47-10^50 erg. They have been detected in the soft X-ray band by Chandra, XMM-Newton, Swift-XRT, and, most recently, by Einstein Probe, which has reported more than 50 FXTs in its first year of operation. While several models have been proposed, the nature of many FXTs remains unknown. One model suggests FXTs…

Sensitivity of Optimal Control Solutions and Quantities of Interest with Respect to Component Functions
Jonathan R. Cangelosi, Matthias Heinkenschloss
https://arxiv.org/abs/2506.10804

Sensitivity of Optimal Control Solutions and Quantities of Interest with Respect to Component Functions
This work establishes sensitivities of the solution of an optimal control problem (OCP) and a corresponding quantity of interest (QoI) to perturbations in a state/control-dependent component function that appears in the governing ODEs and the objective function. This extends existing OCP sensitivity results, which consider the sensitivity of the OCP solution with respect to state/control-independent parameters. It is shown that with Carathéodory-type assumptions, the Implicit Function Theorem …

Trion formation and ordering in the attractive SU(3) Fermi-Hubbard model
Jonathan Stepp, Eduardo Ibarra-Garc\'ia-Padilla, Richard T. Scalettar, Kaden R. A. Hazzard
https://arxiv.org/abs/2506.12300

Trion formation and ordering in the attractive SU(3) Fermi-Hubbard model
Recent advances in microwave shielding have increased the stability and control of large numbers of polar molecules, allowing for the first realization of a molecular Bose-Einstein condensate. Remarkably, it was also recently realized that shielded polar molecules exhibit an SU(N) symmetry among their hyperfine states, opening the door to SU(N) systems with larger N, bosonic particle statistics, and tunable interactions -- both repulsive and attractive. Motivated by these results, we have studi…