Discovery of a Magnetic DZ White Dwarf with Zeeman-Split Lines of Heavy Elements

A spectroscopic survey of previously-unstudied Luyten Half Second proper motion stars has resulted in the discoveries of two new cool magnetic white dwarfs. One (LHS 2273) is a routine DA star, T= 6,500K, with Zeeman-split H alpha and H beta, for which a simple model suggests a polar field strength of 18.5 MG viewed close to equator-on. However, the white dwarf LHS 2534 proves to be the first magnetic DZ showing Zeeman-split Na I and Mg I components, as well as Ca I and Ca II lines for which Zeeman components are blended. The Na I splittings result in a mean surface field strength estimate of 1.92 MG. Apart from the magnetic field, LHS 2534 is one of the most heavily-blanketed and coolest DZ white dwarfs at T ~ 6,000K.Comment: 7 pages, Astrophysical Journal (Letters), in pres

From Spitzer Galaxy Photometry to Tully-Fisher Distances

This paper involves a data release of the observational campaign: Cosmicflows with Spitzer (CFS). Surface photometry of the 1270 galaxies constituting the survey is presented. An additional ~ 400 galaxies from various other Spitzer surveys are also analyzed. CFS complements the Spitzer Survey of Stellar Structure in Galaxies, that provides photometry for an additional 2352 galaxies, by extending observations to low galactic latitudes (|b|<30 degrees). Among these galaxies are calibrators, selected in K band, of the Tully-Fisher relation. The addition of new calibrators demonstrate the robustness of the previously released calibration. Our estimate of the Hubble constant using supernova host galaxies is unchanged, H0 = 75.2 +/- 3.3 km/s/Mpc. Distance-derived radial peculiar velocities, for the 1935 galaxies with all the available parameters, will be incorporated into a new data release of the Cosmicflows project. The size of the previous catalog will be increased by 20%, including spatial regions close to the Zone of Avoidance.Comment: Accepted for publication in MNRAS, 16 pages, 14 figures, 6 table

Quantum limit of photothermal cooling

We study the problem of cooling a mechanical oscillator using the photothermal (bolometric) force. Contrary to previous attempts to model this system, we take into account the noise effects due to the granular nature of photon absorption. This allows us to tackle the cooling problem down to the noise dominated regime and to find reasonable estimates for the lowest achievable phonon occupation in the cantilever

Machine learning approaches for early DRG classification and resource allocation

Recent research has highlighted the need for upstream planning in healthcare service delivery systems, patient scheduling, and resource allocation in the hospital inpatient setting. This study examines the value of upstream planning within hospital-wide resource allocation decisions based on machine learning (ML) and mixed-integer programming (MIP), focusing on prediction of diagnosis-related groups (DRGs) and the use of these predictions for allocating scarce hospital resources. DRGs are a payment scheme employed at patients’ discharge, where the DRG and length of stay determine the revenue that the hospital obtains. We show that early and accurate DRG classification using ML methods, incorporated into an MIP-based resource allocation model, can increase the hospital’s contribution margin, the number of admitted patients, and the utilization of resources such as operating rooms and beds. We test these methods on hospital data containing more than 16,000 inpatient records and demonstrate improved DRG classification accuracy as compared to the hospital’s current approach. The largest improvements were observed at and before admission, when information such as procedures and diagnoses is typically incomplete, but performance was improved even after a substantial portion of the patient’s length of stay, and under multiple scenarios making different assumptions about the available information. Using the improved DRG predictions within our resource allocation model improves contribution margin by 2.9% and the utilization of scarce resources such as operating rooms and beds from 66.3% to 67.3% and from 70.7% to 71.7%, respectively. This enables 9.0% more nonurgent elective patients to be admitted as compared to the baseline

Confidence and Backaction in the Quantum Filter Equation

We study the confidence and backaction of state reconstruction based on a continuous weak measurement and the quantum filter equation. As a physical example we use the traditional model of a double quantum dot being continuously monitored by a quantum point contact. We examine the confidence of the estimate of a state constructed from the measurement record, and the effect of backaction of that measurement on that state. Finally, in the case of general measurements we show that using the relative entropy as a measure of confidence allows us to define the lower bound on the confidence as a type of quantum discord.Comment: 9 pages, 6 figure