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Creators/Authors contains: "Suzuki, D"

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  1. Gravitational microlensing is a phenomenon that allows us to observe the dark remnants of stellar evolution, even if these bodies are no longer emitting electromagnetic radiation. In particular, it can be useful to observe solitary neutron stars or stellar-mass black holes, providing a unique window through which to understand stellar evolution. Obtaining direct mass measurements with this technique requires precise observations of both the change in brightness and the position of the microlensed star. The European Space Agency’sGaiasatellite can provide both. Using publicly available data from different surveys, we analysed events published in theGaiaData Release 3 (GaiaDR3) microlensing catalogue. Here, we describe our selection of candidate dark lenses, where we suspect the lens is a white dwarf (WD), a neutron star (NS), a black hole (BH), or a mass-gap object, with a mass in the range between the heaviest NS and the least massive BH. We estimated the mass of the lenses using information obtained from the best-fitting microlensing models, source star, Galactic model, and the expected parameter distributions. We found eleven candidates for dark remnants: one WDs, three NSs, three mass-gap objects, and four BHs. 
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    Free, publicly-accessible full text available December 1, 2025
  2. Properties of the nuclear equation of state (EoS) can be probed by measuring the dynamical properties of nucleus-nucleus collisions. In this study, we present the directed flow (v1), elliptic flow (v2) and stopping (VarXZ) measured in fixed target Sn+ Sn collisions at 270AMeV with the S'll'RlT Time Projection Chamber. We perform Bayesian analyses in which EoS parameters are var­ied simultaneously within the Improved Quantum Molecular Dynamics-Skyrme (ImQMD-Sky) transport code to obtain a multivariate correlated constraint. The varied parameters include symmetry energy, S0, and slope of the symme­try energy, L, at saturation density, isoscalar effective mass, m;/mN, isovector effective mass, m􀀒/mN and the in-medium cross-section enhancement factor rJ. We find that the flow and VarXZ observables are sensitive to the splitting of proton and neutron effective masses and the in-medium cross-section. Compar­isons of ImQMD-Sky predictions to the S'll' RJT data suggest a narrow range of preferred values for m;/mN, m􀀕/mN and 1/· 
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  3. null (Ed.)
  4. ABSTRACT We present K2-2016-BLG-0005Lb, a densely sampled, planetary binary caustic-crossing microlensing event found from a blind search of data gathered from Campaign 9 of the Kepler K2 mission (K2C9). K2-2016-BLG-0005Lb is the first bound microlensing exoplanet discovered from space-based data. The event has caustic entry and exit points that are resolved in the K2C9 data, enabling the lens-source relative proper motion to be measured. We have fitted a binary microlens model to the Kepler data and to simultaneous observations from multiple ground-based surveys. Whilst the ground-based data only sparsely sample the binary caustic, they provide a clear detection of parallax that allows us to break completely the microlensing mass-position-velocity degeneracy and measure the planet’s mass directly. We find a host mass of 0.58 ± 0.04 M⊙ and a planetary mass of 1.1 ± 0.1 MJ. The system lies at a distance of 5.2 ± 0.2 kpc from Earth towards the Galactic bulge, more than twice the distance of the previous most distant planet found by Kepler. The sky-projected separation of the planet from its host is found to be 4.2 ± 0.3 au which, for circular orbits, deprojects to a host separation $$a = 4.4^{+1.9}_{-0.4}$$ au and orbital period $$P = 13^{+9}_{-2}$$ yr. This makes K2-2016-BLG-0005Lb a close Jupiter analogue orbiting a low-mass host star. According to current planet formation models, this system is very close to the host mass threshold below which Jupiters are not expected to form. Upcoming space-based exoplanet microlensing surveys by NASA’s Nancy Grace Roman Space Telescope and, possibly, ESA’s Euclid mission, will provide demanding tests of current planet formation models. 
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