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Parent, E.; Sewalls, H.; Freire, P. C.; Matheny, T.; Lyne, A. G.; Perera, B. B.; Cardoso, F.; McLaughlin, M. A.; Allen, B.; Brazier, A.; et al(
, The Astrophysical Journal)
Abstract We present new discoveries and results from long-term timing of 72 pulsars discovered in the Pulsar Arecibo L -band Feed Array (PALFA) survey, including precise determination of astrometric and spin parameters, and flux density and scatter broadening measurements at 1.4 GHz. Notable discoveries include two young pulsars (characteristic ages ∼30 kyr) with no apparent supernova remnant associations, three mode-changing, 12 nulling and two intermittent pulsars. We detected eight glitches in five pulsars. Among them is PSR J1939+2609, an apparently old pulsar (characteristic age ∼1 Gy), and PSR J1954+2529, which likely belongs to a newly emerging class of binary pulsars.more »The latter is the only pulsar among the 72 that is clearly not isolated: a nonrecycled neutron star with a 931 ms spin period in an eccentric ( e = 0.114) wide ( P b = 82.7 days) orbit with a companion of undetermined nature having a minimum mass of ∼0.6 M ⊙ . Since operations at Arecibo ceased in 2020 August, we give a final tally of PALFA sky coverage, and compare its 207 pulsar discoveries to the known population. On average, they are 50% more distant than other Galactic plane radio pulsars; PALFA millisecond pulsars (MSPs) have twice the dispersion measure per unit spin period than the known population of MSP in the plane. The four intermittent pulsars discovered by PALFA more than double the population of such objects, which should help to improve our understanding of pulsar magnetosphere physics. The statistics for these, rotating radio transients, and nulling pulsars suggest that there are many more of these objects in the Galaxy than was previously thought.« less
Free, publicly-accessible full text available January 1, 2023
Chatterjee, S; Chakma, A; Gangopadhyay, A; Roy, N; Mitra, B; Chakraborty, S(
, ICMI '20: Proceedings of the 2020 International Conference on Multimodal Interaction)
Annotated IMU sensor data from smart devices and wearables are essential for developing supervised models for fine-grained human activity recognition, albeit generating sufficient annotated data for diverse human activities under different environments is challenging. Existing approaches primarily use human-in-the-loop based techniques, including active learning; however, they are tedious, costly, and time-consuming. Leveraging the availability of acoustic data from embedded microphones over the data collection devices, in this paper, we propose LASO, a multimodal approach for automated data annotation from acoustic and locomotive information. LASO works over the edge device itself, ensuring that only the annotated IMU data is collected, discardingmore »the acoustic data from the device itself, hence preserving the audio-privacy of the user. In the absence of any pre-existing labeling information, such an auto-annotation is challenging as the IMU data needs to be sessionized for different time-scaled activities in a completely unsupervised manner. We use a change-point detection technique while synchronizing the locomotive information from the IMU data with the acoustic data, and then use pre-trained audio-based activity recognition models for labeling the IMU data while handling the acoustic noises. LASO efficiently annotates IMU data, without any explicit human intervention, with a mean accuracy of 0.93 ($\pm 0.04$) and 0.78 ($\pm 0.05$) for two different real-life datasets from workshop and kitchen environments, respectively.« less
Eftekhari, T.; Margalit, B.; Omand, C. M.; Berger, E.; Blanchard, P. K.; Demorest, P.; Metzger, B. D.; Murase, K.; Nicholl, M.; Villar, V. A.; et al(
, The Astrophysical Journal)
Ferdman, R. D.; Freire, P. C.; Perera, B. B.; Pol, N.; Camilo, F.; Chatterjee, S.; Cordes, J. M.; Crawford, F.; Hessels, J. W.; Kaspi, V. M.; et al(
, Nature)
Madison, D. R.; Agarwal, D.; Aggarwal, K.; Young, O.; Cromartie, H. T.; Lam, M. T.; Chatterjee, S.; Cordes, J. M.; Garver-Daniels, N.; Lorimer, D. R.; et al(
, The Astrophysical Journal)
Antoniadis, J; Arzoumanian, Z; Babak, S; Bailes, M; Bak Nielsen, A-S; Baker, P T; Bassa, C G; Bécsy, B; Berthereau, A; Bonetti, M; et al(
, Monthly Notices of the Royal Astronomical Society)
ABSTRACT We searched for an isotropic stochastic gravitational wave background in the second data release of the International Pulsar Timing Array, a global collaboration synthesizing decadal-length pulsar-timing campaigns in North America, Europe, and Australia. In our reference search for a power-law strain spectrum of the form $h_c = A(f/1\, \mathrm{yr}^{-1})^{\alpha }$, we found strong evidence for a spectrally similar low-frequency stochastic process of amplitude $A = 3.8^{+6.3}_{-2.5}\times 10^{-15}$ and spectral index α = −0.5 ± 0.5, where the uncertainties represent 95 per cent credible regions, using information from the auto- and cross-correlation terms between the pulsars in the array. For a spectral index of α =more »−2/3, as expected from a population of inspiralling supermassive black hole binaries, the recovered amplitude is $A = 2.8^{+1.2}_{-0.8}\times 10^{-15}$. None the less, no significant evidence of the Hellings–Downs correlations that would indicate a gravitational-wave origin was found. We also analysed the constituent data from the individual pulsar timing arrays in a consistent way, and clearly demonstrate that the combined international data set is more sensitive. Furthermore, we demonstrate that this combined data set produces comparable constraints to recent single-array data sets which have more data than the constituent parts of the combination. Future international data releases will deliver increased sensitivity to gravitational wave radiation, and significantly increase the detection probability.« less
Free, publicly-accessible full text available January 19, 2023
Hsieh, S.; Bhattacharyya, P.; Zu, C.; Mittiga, T.; Smart, T. J.; Machado, F.; Kobrin, B.; Höhn, T. O.; Rui, N. Z.; Kamrani, M.; et al(
, Science)
Pressure alters the physical, chemical, and electronic properties of matter. The diamond anvil cell enables tabletop experiments to investigate a diverse landscape of high-pressure phenomena. Here, we introduce and use a nanoscale sensing platform that integrates nitrogen-vacancy (NV) color centers directly into the culet of diamond anvils. We demonstrate the versatility of this platform by performing diffraction-limited imaging of both stress fields and magnetism as a function of pressure and temperature. We quantify all normal and shear stress components and demonstrate vector magnetic field imaging, enabling measurement of the pressure-driven α ↔ ϵ phase transition in iron and the complexmore »pressure-temperature phase diagram of gadolinium. A complementary NV-sensing modality using noise spectroscopy enables the characterization of phase transitions even in the absence of static magnetic signatures.« less
