Longitudinal dynamics of large and small systems from a 3D Bayesian calibration of RHIC top-energy collision data
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Engineering topics
Publications and source records attributed to Wu, X..
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We introduce the NASA/IPAC Extragalactic Database (NED) Local Volume Sample (NED-LVS), a subset of ~1.9 million objects with distances out to 1000 Mpc. We use UV and IR fluxes available in NED from all-sky surveys to derive physical properties, and estimate the completeness relative to the expected local luminosity density. The completeness relative to near-IR luminosities (which traces a galaxy's stellar mass) is roughly 100% at D < 30 Mpc and remains moderate (70%) out to 300 Mpc. For brighter galaxies (≳L * ), NED-LVS is ~100% complete out to ~400 Mpc. When compared to other local Universe samples (GLADE and HECATE), all three are ~100% complete below 30 Mpc. At distances beyond ~80 Mpc, NED-LVS is more complete than both GLADE and HECATE by ~10%–20%. NED-LVS is the underlying sample for the NED gravitational-wave follow-up service (NED-GWF), which provides prioritized lists of host candidates for GW events within minutes of alerts issued by the LIGO–Virgo–KAGRA collaboration. We test the prioritization of galaxies in the volume of GW170817 by three physical properties, where we find that both stellar mass and inverse specific star formation rate place the correct host galaxy in the top 10. In addition, NED-LVS can be used for a wide variety of other astrophysical studies: galaxy evolution, star formation, large-scale structure, galaxy environments, and more. The data in NED are updated regularly, and NED-LVS will be updated concurrently. Consequently, NED-LVS will continue to provide an increasingly complete sample of galaxies for a multitude of astrophysical research areas for years to come.
Tin adatoms on a Si(111) substrate with a one-third monolayer coverage form a two-dimensional triangular lattice with one unpaired electron per site. These electrons order into an antiferromagnetic Mott-insulating state, but doping the Sn layer with holes creates a two-dimensional conductor that becomes superconducting at low temperatures. Although the pairing symmetry of the superconducting state is currently unknown, the combination of repulsive interactions and frustration inherent in the triangular adatom lattice opens up the possibility of a chiral order parameter. Here we study the superconducting state of Sn/Si(111) using scanning tunneling microscopy, scanning tunneling spectroscopy and quasiparticle interference imaging. Here we find evidence for a doping-dependent superconducting critical temperature with a fully gapped order parameter, the presence of time-reversal symmetry breaking and a strong enhancement in zero-bias conductance near the edges of the superconducting domains. Although each individual piece of evidence could have a more mundane interpretation, our combined results suggest the possibility that Sn/Si(111) is an unconventional chiral d-wave superconductor.
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Deep Neural Networks (DNNs) have been widely used as a data-driven modelling tool in nuclear engineering. However, as a Machine Learning model, Artificial Neural Network (ANN) predictions are subjected to uncertainties originating from the noise in training data, incomplete coverage of the domain, and imperfect neural network architectures. In this work, we target at quantifying the prediction/approximation uncertainties of ANNs using Monte Carlo Dropout (MCD), as well as Bayesian Neural Networks (BNNs) which are solved by variational inference. With a demonstration problem in which neural networks are used to predict the assembly axial neutron flux profiles, the results have shown that the three different neural network models (regular DNNs, DNNs solved with MCD and BNNs) can produce results that agree very well among each other and with the measurement data, on cycles that are not used in the training process. Besides the excellent generalization capability, the uncertainty bands produced by MCD and BNN agree very well, and in general, they can fully envelop the noisy measurement data points. (authors)
The kagome lattice 1 , which is the most prominent structural motif in quantum physics, benefits from inherent non-trivial geometry so that it can host diverse quantum phases, ranging from spin-liquid phases, to topological matter, to intertwined orders 2,3,4,5,6,7,8 and, most rarely, to unconventional superconductivity 6,9 . Recently, charge sensitive probes have indicated that the kagome superconductors AV 3 Sb 5 (A = K, Rb, Cs) 9,10,11 exhibit unconventional chiral charge order 12,13,14,15,16,17,18,19, which is analogous to the long-sought-after quantum order in the Haldane model 20 or Varma model 21 . However, direct evidence for the time-reversal symmetry breaking of the charge order remains elusive. Here we use muon spin relaxation to probe the kagome charge order and superconductivity in KV 3 Sb 5 . We observe a noticeable enhancement of the internal field width sensed by the muon ensemble, which takes place just below the charge ordering temperature and persists into the superconducting state. Notably, the muon spin relaxation rate below the charge ordering temperature is substantially enhanced by applying an external magnetic field. We further show the multigap nature of superconductivity in KV 3 Sb 5 and that the T c /λ$^{-2}_{ab}$ ratio (where T c is the superconducting transition temperature and λ ab is the magnetic penetration depth in the kagome plane) is comparable to those of unconventional high-temperature superconductors. Our results point to time-reversal symmetry-breaking charge order intertwining with unconventional superconductivity in the correlated kagome lattice.
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Quantum information science still requires basic science research to achieve its full potential. However, scientists require access to fabricated device samples if we are to utilize the full toolset for solving the pressing issues in the field such as materials, device layout, or optimal error correction methods.Currently, access to samples is either prohibitively expensive, or requires close collaboration with one of the few groups in the world developing these systems. A dedicated quantum foundry could,in principle,provide affordable samples designed with current best practices to a host of scientists who otherwise do not have access. We detail several different foundry models which we believe will assist the community in developing the science for both the underlying processes, as well as the more advanced chip layout and circuit design. Opening access to the broader community has the potential to significantly lower the barrier to entry and vastly improve the ability for researchers in fields ranging from condensed matter to materials characterization to systems engineering to contribute to accelerating the advance of quantum information science and technology.
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