Quantifying jet transport properties via large pTp_T hadron production

Nuclear modification factor $R_{AA}$ for large $p_T$ single hadron is studied in a next-to-leading order (NLO) perturbative QCD (pQCD) parton model with medium-modified fragmentation functions (mFFs) due to jet quenching in high-energy heavy-ion collisions. The energy loss of the hard partons in the QGP is incorporated in the mFFs which utilize two most important parameters to characterize the transport properties of the hard parton jets: the jet transport parameter $\hat q_{0}$ and the mean free path $\lambda_{0}$, both at the initial time $\tau_0$. A phenomenological study of the experimental data for $R_{AA}(p_{T})$ is performed to constrain the two parameters with simultaneous $\chi^2/{\rm d.o.f}$ fits to RHIC as well as LHC data. We obtain for energetic quarks $\hat q_{0}\approx 1.1 \pm 0.2$ GeV$^2$/fm and $\lambda_{0}\approx 0.4 \pm 0.03$ fm in central $Au+Au$ collisions at $\sqrt{s_{NN}}=200$ GeV, while $\hat q_{0}\approx 1.7 \pm 0.3$ GeV$^2$/fm, and $\lambda_{0}\approx 0.5 \pm 0.05$ fm in central $Pb+Pb$ collisions at $\sqrt{s_{NN}}=2.76$ TeV. Numerical analysis shows that the best fit favors a multiple scattering picture for the energetic jets propagating through the bulk medium, with a moderate averaged number of gluon emissions. Based on the best constraints for $\lambda_{0}$ and $\tau_0$, the estimated value for the mean-squared transverse momentum broadening is moderate which implies that the hard jets go through the medium with small reflection.Comment: 8 pages, 6 figures, revised versio

Optimal Distributed Beamforming for MISO Interference Channels

We consider the problem of quantifying the Pareto optimal boundary in the achievable rate region over multiple-input single-output (MISO) interference channels, where the problem boils down to solving a sequence of convex feasibility problems after certain transformations. The feasibility problem is solved by two new distributed optimal beamforming algorithms, where the first one is to parallelize the computation based on the method of alternating projections, and the second one is to localize the computation based on the method of cyclic projections. Convergence proofs are established for both algorithms.Comment: 7 Pages, 6 figures, extended version for the one in Proceeding of Asilomar, CA, 201

Spectrum sensing by cognitive radios at very low SNR

Spectrum sensing is one of the enabling functionalities for cognitive radio (CR) systems to operate in the spectrum white space. To protect the primary incumbent users from interference, the CR is required to detect incumbent signals at very low signal-to-noise ratio (SNR). In this paper, we present a spectrum sensing technique based on correlating spectra for detection of television (TV) broadcasting signals. The basic strategy is to correlate the periodogram of the received signal with the a priori known spectral features of the primary signal. We show that according to the Neyman-Pearson criterion, this spectral correlation-based sensing technique is asymptotically optimal at very low SNR and with a large sensing time. From the system design perspective, we analyze the effect of the spectral features on the spectrum sensing performance. Through the optimization analysis, we obtain useful insights on how to choose effective spectral features to achieve reliable sensing. Simulation results show that the proposed sensing technique can reliably detect analog and digital TV signals at SNR as low as -20 dB.Comment: IEEE Global Communications Conference 200

1I/2017 U1 (`Oumuamua) is Hot: Imaging, Spectroscopy and Search of Meteor Activity

1I/2017 U1 (`Oumuamua), a recently discovered asteroid in a hyperbolic orbit, is likely the first macroscopic object of extrasolar origin identified in the solar system. Here, we present imaging and spectroscopic observations of \textquoteleft Oumuamua using the Palomar Hale Telescope as well as a search of meteor activity potentially linked to this object using the Canadian Meteor Orbit Radar. We find that \textquoteleft Oumuamua exhibits a moderate spectral gradient of $10\%\pm6\%~(100~\mathrm{nm})^{-1}$, a value significantly lower than that of outer solar system bodies, indicative of a formation and/or previous residence in a warmer environment. Imaging observation and spectral line analysis show no evidence that \textquoteleft Oumuamua is presently active. Negative meteor observation is as expected, since ejection driven by sublimation of commonly-known cometary species such as CO requires an extreme ejection speed of $\sim40$ m s$^{-1}$ at $\sim100$ au in order to reach the Earth. No obvious candidate stars are proposed as the point of origin for \textquoteleft Oumuamua. Given a mean free path of $\sim10^9$ ly in the solar neighborhood, \textquoteleft Oumuamua has likely spent a very long time in the interstellar space before encountering the solar system.Comment: ApJL in pres

Depth Sensitivity and Source-Detector Separations for Near Infrared Spectroscopy Based on the Colin27 Brain Template

Understanding the spatial and depth sensitivity of non-invasive near-infrared spectroscopy (NIRS) measurements to brain tissue–i.e., near-infrared neuromonitoring (NIN) – is essential for designing experiments as well as interpreting research findings. However, a thorough characterization of such sensitivity in realistic head models has remained unavailable. In this study, we conducted 3,555 Monte Carlo (MC) simulations to densely cover the scalp of a well-characterized, adult male template brain (Colin27). We sought to evaluate: (i) the spatial sensitivity profile of NIRS to brain tissue as a function of source-detector separation, (ii) the NIRS sensitivity to brain tissue as a function of depth in this realistic and complex head model, and (iii) the effect of NIRS instrument sensitivity on detecting brain activation. We found that increasing the source-detector (SD) separation from 20 to 65 mm provides monotonic increases in sensitivity to brain tissue. For every 10 mm increase in SD separation (up to ∼45 mm), sensitivity to gray matter increased an additional 4%. Our analyses also demonstrate that sensitivity in depth (S) decreases exponentially, with a “rule-of-thumb” formula S = 0.75*0.85depth. Thus, while the depth sensitivity of NIRS is not strictly limited, NIN signals in adult humans are strongly biased towards the outermost 10–15 mm of intracranial space. These general results, along with the detailed quantitation of sensitivity estimates around the head, can provide detailed guidance for interpreting the likely sources of NIRS signals, as well as help NIRS investigators design and plan better NIRS experiments, head probes and instruments