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Monitoring of project performance is a crucial task of project managers that significantly affect the project success or failure. Earned Value Management (EVM) is a well-known tool to evaluate project performance and effective technique for identifying delays and proposing appropriate corrective actions. The original EVM analysis is a monetary-based method and it can be misleading in the evaluation of the project schedule performance and estimation of the project duration. Earned Duration Management (EDM) is a more recent method which introduces metrics for the project schedule performance evaluation and improves EVM analysis. In this paper, we apply statistical control charts on EDM indices to better investigate the variations of project schedule performance. Control charts are decision support tools to detect the out of control performance. Usually project performance measurements are auto-correlated and not following the normal distribution. Hence, in this paper, a two-step adjustment framework is proposed to make the control charts applicable to non-normal and auto-correlated measurements. The case study project illustrates how the new method can be implemented in practice. The numerical results conclude that that employing control chart method along with analyzing the actual values of EDM indices increase the capability of project management teams to detect cost and schedule problems on time
|
statistics
|
We interpret the $X_1(2900)$ as an $S$-wave $\bar{D}_1K$ molecular state in the Bethe-Salpeter equation approach with the ladder and instantaneous approximations for the kernel. By solving the Bethe-Salpeter equation numerically with the kernel containing one-particle-exchange diagrams and introducing three different form factors (monopole, dipole, and exponential form factors) in the verties, we find the bound state exists. We also study the decay width of the decay $X_1(2900)$ to $D^-K^+$.
|
high energy physics phenomenology
|
Underwater robots play an important role in oceanic geological exploration, resource exploitation, ecological research, and other fields. However, the visual perception of underwater robots is affected by various environmental factors. The main challenge now is that images captured by underwater robots are color-distorted. The hue of underwater images tends to be close to green and blue. In addition, the contrast is low and the details are fuzzy. In this paper, a new underwater image enhancement algorithm based on deep learning and image formation model is proposed. Experimental results show that the advantages of the proposed method are that it eliminates the influence of underwater environmental factors, enriches the color, enhances details, achieves higher scores in PSNR and SSIM metrics, and helps feature key-point point matching get better results. Another significant advantage is that its computation speed is much faster than other methods.
|
electrical engineering and systems science
|
We consider the problem of designing a state feedback control law to achieve nonovershooting tracking for feedback linearisable multiple-input multiple-output nonlinear systems. The reference signal is assumed to be obtained from a linear exosystem. The design method adopts known methods for the nonovershooting tracking of linear systems and extends them to the output regulation of feedback linearisable nonlinear systems. The method accommodates arbitrary initial conditions and offers design choice of the tracking convergence speed.
|
mathematics
|
The Froissart bound on the total cross section is subjected to test against very high energy data. We have found no clear evidence for its violation. The scaling property of differential cross section in the diffraction region is investigated. It exhibits scaling in the ISR, SPS, Tevatron and LHC energy domain which had hitherto remained unexplored. The slope of the diffraction peak is fitted and the data are tested against the rigorous bounds.
|
high energy physics phenomenology
|
We observe cavity mediated spin-dependent interactions in an off-resonantly driven multi-level atomic Bose-Einstein condensate that is strongly coupled to an optical cavity. Applying a driving field with adjustable polarization, we identify the roles of the scalar and the vectorial components of the atomic polarizability tensor for single and multi-component condensates. Beyond a critical strength of the vectorial coupling, we observe a spin texture in a condensate of two internal states, providing perspectives for global dynamic gauge fields and self-consistently spin-orbit coupled gases.
|
condensed matter
|
The understanding of the dynamics of nonequilibrium cooling and heating processes at the nanoscale is still an open problem. These processes can follow surprising relaxation paths due to, e.g., memory effects, which significantly alter the expected equilibration routes. The Kovacs effect can take place when a thermalization process is suddenly interrupted by a change of the bath temperature, leading to a non-monotonic dependence of the energy of the system. Here, we demonstrate that the Kovacs effect can be observed in the thermalization of the center of mass motion of a levitated nanoparticle. The temperature is controlled during the experiment through an external source of white gaussian noise. We describe our experiments in terms of the dynamics of a Brownian particle in a harmonic trap without any fitting parameter, suggesting that the Kovacs effect canappear in a large variety of systems.
|
condensed matter
|
The significance of vehicle-to-everything (V2X) communications has been ever increased as connected and autonomous vehicles get more emergent in practice. The key challenge is the dynamicity: each vehicle needs to recognize the frequent changes of the surroundings and apply them to its networking behavior. This is the point where the need for machine learning is highlighted. However, the learning itself is extremely complicated due to the dynamicity as well, which necessitates that the learning framework itself must be resilient and flexible according to the environment. As such, this paper proposes a V2X networking framework integrating reinforcement learning (RL) into scheduling of multiple access. Specifically, the learning mechanism is formulated as a multi-armed bandit (MAB) problem, which enables a vehicle, without any assistance from external infrastructure, to (i) learn the environment, (ii) quantify the accident risk, and (iii) adapt its backoff counter according to the risk. The results of this paper show that the proposed learning protocol is able to (i) evaluate an accident risk close to optimal and (ii) as a result, yields a higher chance of transmission for a dangerous vehicle.
|
electrical engineering and systems science
|
We demonstrate that electrostatic interactions between helical electrons at the edge of a quantum spin Hall insulator and a dynamical impurity can induce quasi-elastic backscattering. Modelling the impurity as a two-level system, we show that transitions between counterpropagating Kramers-degenerate electronic states can occur without breaking time-reversal symmetry, provided that the impurity also undergoes a transition. The associated electrical resistance has a weak temperature dependence down to a non-universal temperature scale. Our results extend the range of known backscattering mechanisms in helical edge modes to include scenarios where electron tunnelling out of the system is absent.
|
condensed matter
|
In the linear minimum mean square error (LMMSE) estimation for orthogonal frequency division multiplexing (OFDM) systems, the problem about the determination of the algorithm's parameters, especially those related with channel frequency response (CFR) correlation, has not been readily solved yet. Although many approaches have been proposed to determine the statistic parameters, it is hard to choose the best one within those approaches in the design phase, since every approach has its own most suitable application conditions and the real channel condition is unpredictable. In this paper, we propose an enhance LMMSE estimation capable of selecting parameters by itself. To this end, sampled noise MSE is first proposed to evaluate the practical performance of interpolation. Based on this evaluation index, a novel parameter comparison scheme is proposed to determine the parameters which can endow LMMSE estimation best performance within a parameter set. After that, the structure of the enhanced LMMSE is illustrated, and it is applied in OFDM systems. Besides, the issues about theoretical analysis on accuracy of the parameter comparison scheme, the parameter set design and algorithm complexity are explained in detail. At last, our analyses and performance of the proposed estimation method are demonstrated by simulation experiments.
|
electrical engineering and systems science
|
Having reliable estimates of the occurrence rates of extreme events is highly important for insurance companies, government agencies and the general public. The rarity of an extreme event is typically expressed through its return period, i.e., the expected waiting time between events of the observed size if the extreme events of the processes are independent and identically distributed. A major limitation with this measure is when an unexpectedly high number of events occur within the next few months immediately after a \textit{T} year event, with \textit{T} large. Such events undermine the trust in the quality of these risk estimates. The clustering of apparently independent extreme events can occur as a result of local non-stationarity of the process, which can be explained by covariates or random effects. We show how accounting for these covariates and random effects provides more accurate estimates of return levels and aids short-term risk assessment through the use of a new risk measure, which provides evidence of risk which is complementary to the return period.
|
statistics
|
In terms of the characteristic functions of the quantum states, we present a complete operator description of a lossy photon-subtraction scheme. Feeding a single-mode squeezed vacuum into a variable beam splitter and counting the photons in one of the output channels, a broad class of multiphoton-subtracted squeezed vacuum states (MSSVSs) can be generated in other channel. Here the losses are considered in the beginning and the end channels in the circuit. Indeed, this scheme has been discussed in Ref. [Phys. Rev. A 100, 022341 (2019)]. However, different from the above work, we give all the details of the optical fields in all stages. In addition, we present the analytical expressions and numerical simulations for the success probability, the quadrature squeezing effect, photon-number distribution and Wigner function of the MSSVSs. Some interesting results effected by the losses are obtained.
|
quantum physics
|
We study the models of Kafri, Taylor and Milburn (KTM) and Tilloy and Di\'osi (TD), both of which implement gravity between quantum systems through a continuous measurement and feedback mechanism. The first model is for two particles, moving in one dimension, where the Newtonian potential is linearized. The second is applicable to any quantum system, within the context of Newtonian gravity. We address the issue of how to generalize the KTM model for an arbitrary finite number of particles. We find that the most straightforward generalisations are either inconsistent or are ruled out by experimental evidence. We also show that the TD model does not reduce to the KTM model under the approximations which define the latter model. We then argue that under the simplest conditions, the TD model is the only viable implementation of a full-Newtonian interaction through a continuous measurement and feedback mechanism.
|
quantum physics
|
In the present work we examine the possibility of detecting light dark matter particles (WIMP) utilizing their possible interactions with the electrons. Employing reasonable theoretical models we evaluate the expected event rates in the following cases: i) For WIMPs in the meV region treating electrons as free and utilizing calorimetric detectors at low temperatures. ii) Detecting recoiling electrons with energy in the eV region ejected out of an atom in the case of WIMPs with a mass more than an order of magnitude heavier than the electron. iii) By observing atomic excitations in the range of 1 meV to 10 eV excitation energy induced by the electron spin interaction in a magnetic field.
|
high energy physics phenomenology
|
Observations reveal that strong solar flares and coronal mass ejections tend to occur in complex active regions characterized by delta-sunspots, spot rotation, sheared polarity inversion lines (PILs), and magnetic flux ropes. Here we report on the first modeling of spontaneous delta-spot generation as a result of flux emergence from the turbulent convection zone. Utilizing state-of-the-art radiative magnetohydrodynamics code R2D2, we simulate the emergence of a force-free flux tube in the convection zone that stretches down to -140 Mm. Elevated by large-scale convective upflows, the tube appears on the photosphere as two emerging bipoles. The opposite polarities collide against each other due to the subsurface connectivity, and they develop into a pair of closely-packed delta-spots. The Lorentz force drives the spot rotation and a strong counter-streaming flow of 10 km/s at the PIL in delta-spots, which, in tandem with local convection, strengthens the horizontal field to 4 kG and builds up a highly-sheared PIL. In the atmosphere above the PIL, a flux rope structure is created. All these processes follow the multi-buoyant segment theory of the delta-spot formation, and they occur as a natural consequence of interaction between magnetic flux and turbulent convection, suggesting that the generation of delta-spots and the resultant flare eruptions may be a stochastically determined process.
|
astrophysics
|
Quantum Brownian motion model is a typical model in the study of nonequilibrium quantum thermodynamics. Entropy is one of the most fundamental physical concepts in thermodynamics. In this work, by solving the quantum Langevin equation, we study the von Neumann entropy of a particle undergoing quantum Brownian motion. In both the strong and the weak coupling regimes, we obtain the analytical expression of the time evolution of the Wigner function in terms of the initial Wigner function. The result is applied to the thermodynamic equilibrium initial state, which reproduces its classical counterpart in the high-temperature limit. Based on these results, for those initial states having well-defined classical counterparts, we obtain the explicit expression of the quantum corrections to the entropy of the system. Moreover, under the Markovian approximation, we obtain the expression of the quantum corrections to the total entropy production rate ${e_{\rm p}}$ and the heat dissipation rate ${h_{\rm d}}$. Our results bring important insights to the understanding of entropy in open quantum systems.
|
quantum physics
|
Due to a variety of factors, pathological images have large color variabilities, which hamper the performance of computer-aided diagnosis (CAD) systems. Stain normalization has been used to reduce the color variability and increase the accuracy of CAD systems. Among them, the conventional methods perform stain normalization on a pixel-by-pixel basis, but estimate stain parameters just relying on one single reference image and thus would incur some inaccurate normalization results. As for the current deep learning-based methods, it can automatically extract the color distribution and need not pick a representative reference image. While the deep learning-based methods have a complex structure with millions of parameters, and a relatively low computational efficiency and a risk to introduce artifacts. In this paper, a fast and robust stain normalization network with only 1.28K parameters named StainNet is proposed. StainNet can learn the color mapping relationship from a whole dataset and adjust the color value in a pixel-to-pixel manner. The proposed method performs well in stain normalization and achieves a better accuracy and image quality. Application results show the cervical cytology classification achieved a higher accuracy when after stain normalization of StainNet.
|
electrical engineering and systems science
|
We consider the third order differential equation derived from the deformed Seiberg-Witten differential for pure ${\cal N}=2$ SYM with gauge group $SU(3)$ in Nekrasov-Shatashvili limit of $\Omega$-background. We show that this is the same differential equation that emerges in the context of Ordinary Differential Equation/Integrable Models (ODI/IM) correspondence for $2d$ $A_2$ Toda CFT with central charge $c=98$. We derive the corresponding $QQ$ and related $TQ$ functional relations and establish the asymptotic behaviour of $Q$ and $T$ functions at small instanton parameter $q \rightarrow 0$. Moreover, numerical integration of the Floquet monodromy matrix of the differential equation leads to evaluation of the $A$-cycles $a_{1,2,3}$ at any point of the moduli space of vacua parametrised by the vector multiplet scalar VEVs $\langle \textbf{tr}\,\phi^2\rangle$ and $\langle \textbf{tr}\,\phi^3\rangle$ even for large values of $q$ which are well beyond the reach of instanton calculus. The numerical results at small $q$ are in excellent agreement with instanton calculation. We conjecture a very simple relation between Baxter's $T$-function and $A$-cycle periods $a_{1,2,3}$, which is an extension of Alexei Zamolodchikov's conjecture about Mathieu equation.
|
high energy physics theory
|
Speaker segmentation consists in partitioning a conversation between one or more speakers into speaker turns. Usually addressed as the late combination of three sub-tasks (voice activity detection, speaker change detection, and overlapped speech detection), we propose to train an end-to-end segmentation model that does it directly. Inspired by the original end-to-end neural speaker diarization approach (EEND), the task is modeled as a multi-label classification problem using permutation-invariant training. The main difference is that our model operates on short audio chunks (5 seconds) but at a much higher temporal resolution (every 16ms). Experiments on multiple speaker diarization datasets conclude that our model can be used with great success on both voice activity detection and overlapped speech detection. Our proposed model can also be used as a post-processing step, to detect and correctly assign overlapped speech regions. Relative diarization error rate improvement over the best considered baseline (VBx) reaches 18% on AMI, 17% on DIHARD 3, and 16% on VoxConverse.
|
electrical engineering and systems science
|
Based on the concepts of quantum synchronization and quantum phase synchronization proposed by A. Mari \textit{et al.} in Phys. Rev. Lett. 111, 103605 (2013), we introduce and characterize the measure of a more generalized quantum synchronization called quantum $\varphi$-synchronization under which the pairs of variables have the same amplitude and possess the same $\varphi$ phase shift. Naturally, quantum synchronization and quantum anti-synchronization become special cases of quantum $\varphi$-synchronization. Their relations and differences are also discussed. To illustrate these theories, we investigate the quantum $\varphi$-synchronization and quantum phase synchronization phenomena of two coupled optomechanical systems with periodic modulation and show that quantum $\varphi$-synchronization is more general as a measure of synchronization. We also show the phenomenon of quantum anti-synchronization when $\varphi=\pi$.
|
quantum physics
|
In this paper, we explore the mechanisms that regulate the formation and evolution of stellar black hole binaries (BHBs) around supermassive black holes (SMBHs). We show that dynamical interactions can efficiently drive "in-situ" BHB formation if the SMBH is surrounded by a massive nuclear cluster (NC), while orbitally segregated star clusters can replenish the BHB reservoir in SMBH-dominated nuclei. We discuss how the combined action of stellar hardening and mass segregation sculpts the BHB orbital properties. We use direct N-body simulations including post-Newtonian corrections up to 2.5 order to study the BHB-SMBH interplay, showing that the Kozai-Lidov mechanism plays a crucial role in shortening binaries lifetime. We find that the merging probability weakly depends on the SMBH mass in the $10^6-10^9{\rm ~M}_\odot$ mass range, leading to a merger rate $\Gamma \simeq 3-8$ yr$^{-1}$ Gpc$^{-3}$ at redshift zero. Nearly $40\%$ of the mergers have masses in the "BH mass gap", $50-140{\rm ~M}_\odot$, thus indicating that galactic nuclei are ideal places to form BHs in this mass range. We argue that gravitational wave (GW) sources with components mass $m_1>40{\rm ~M}_\odot$ and $m_2<30{\rm ~M}_\odot$ would represent a strong indicator of a galactic nuclei origin. The majority of these mergers could be multiband GW sources in the local Universe: nearly $40\%$ might be seen by LISA as eccentric sources and, a few years later, as circular sources by LIGO and the Einstein Telescope, making decihertz observatories like DECIGO unique instruments to bridge the observations during the binary inspiral.
|
astrophysics
|
We use MUSE/VLT to conduct a survey of $z\sim3$ physical quasar pairs at close separation with a fast observation strategy. Our aim is twofold: (i) explore the Ly$\alpha$ glow around the faint-end of the quasar population; (ii) take advantage of the combined illumination of a quasar pair to unveil large-scale intergalactic structures extending between the two quasars. Here, we report the results for a quasar pair ($z=3.020,3.008$; $i=21.84,22.15$), separated by 11.6 arcsec (or 89 projected kpc). MUSE reveals filamentary Ly$\alpha$ structures extending between the two quasars with an average surface brightness of SB$_{\rm Ly\alpha}=1.8\times10^{-18}$ erg s$^{-1}$ cm$^{-2}$ arcsec$^{-2}$. Photoionization models of the constraints in the Ly$\alpha$, HeII, and CIV line emissions show that the emitting structures are intergalactic bridges with an extent between $\sim89$ and up to $\sim600$ kpc. Our models rule out the possibility that the structure extends for $\sim 2.9$ Mpc, i.e., the separation inferred from the uncertain systemic redshift difference of the quasars if the difference was only due to the Hubble flow. At the current spatial resolution and surface brightness limit, the average projected width of an individual bridge is about 35 kpc. We also detect a strong absorption in HI, NV, and CIV along the background sight-line at higher $z$, which we interpret as due to at least two components of cool, metal enriched, and relatively ionized CGM or IGM surrounding the quasar pair. Two additional HI absorbers are detected along both quasar sight-lines at $\sim -900$ and $-2800$ km s$^{-1}$ from the system, with the latter having associated CIV absorption only along the foreground quasar sight-line. The absence of galaxies in the MUSE field of view at the redshifts of these two absorbers suggests that they trace large-scale structures or expanding shells in front of the quasar pair.
|
astrophysics
|
We consider the effects of off-shell Hawking radiation on scattering processes involving black holes coupled to quantum fields. The focus here is to the case of gravitational scattering of a scalar field mediated by the exchange of virtual Hawking gravitons from a four-dimensional Schwarzschild black hole. Our result is obtained in the context of a worldline effective field theory for the black hole, and is valid in the semi-classical limit where the Schwarzschild radius $r_s$ is larger than the Planck length $1/m_{Pl}$. In addition, we assume that four-momentum exchange $q$ is smaller than $r_s^{-1}$ and that the incoming particle has energy larger then the black hole's Hawking temperature. The inelastic cross section we obtain is a new, leading order quantum gravity effect, arising at the same order in $q^2/m_{Pl}^2$ as the well understood one-loop graviton vacuum polarization corrections to gravitational scattering between massive particles.
|
high energy physics theory
|
Perovskites have attracted much attention due to their remarkable optical properties. While it is well established that excitons dominate their optical response, the impact of higher excitonic states and formation of phonon sidebands in optical spectra still need to be better understood. Here, we perform a theoretical study on excitonic properties of monolayered hybrid organic perovskites -- supported by temperature-dependent photoluminescence measurements. Solving the Wannier equation, we obtain microscopic access to the Rydberg-like series of excitonic states including their wavefunctions and binding energies. Exploiting the generalized Elliot formula, we calculate the photoluminescence spectra demonstrating a pronounced contribution of a phonon sideband for temperatures up to 50 K -- in agreement with experimental measurements. Finally, we predict temperature-dependent linewidths of the three energetically lowest excitonic transitions and identify the underlying phonon-driven scattering processes.
|
condensed matter
|
In this work, we have proposed a modular $A_4$ symmetric model of neutrino mass which, simultaneously, explains observed baryon asymmetry of the Universe(BAU). In minimal extension of the standard model(SM) with two right-handed neutrinos we work in Type-I+II seesaw scenario in a supersymmetric framework. At Type-I seesaw level, the model predicts scaling in the neutrino mass matrix. We implement Type-II seesaw to break the scaling and to have correct low energy phenomenology. The breaking is proportional to the $vev$ alignment of the scalar triplet implementing Type-II seesaw and Yukawa coupling of modular weight 6($Y_1^{6}$). The model predicts normal hierarchical neutrino masses and provide a robust range ($0.05-0.07$)eV for sum of neutrino masses($\sum m_{i}$). Lepton number violating $0\nu\beta\beta$ decay amplitude($M_{ee}$) is obtained to lie in the range ($0.04-0.06$)eV. Future $0\nu\beta\beta$ decay experiments such as NEXT and nEXO shall pose crucial test for the model. Both $CP$ conserving and $CP$ violating solutions are allowed in the model. Interesting correlations are obtained, specially, between Yukawa couplings of modular weight 2 and complex modulus $\tau$. Contrary to $Y_2^{2}$ and $Y_3^{2}$, the Yukawa coupling $Y_1^{2}$ is found to be insensitive to $\tau$ and thus to $CP$ violation because complex modulus $\tau$ is the only source of $CP$ violation in the model. We, also, investigate the prediction of the model for BAU. The model exhibit consistent explanation of BAU for right-handed Majorana neutrino mass scale in the range ($10^{11}-10^{13}$)GeV.
|
high energy physics phenomenology
|
We present the first results from a study of TESS Sector 1 and 2 light curves for eight evolved massive stars in the LMC: six yellow supergiants (YSGs) and two luminous blue variables (LBVs), including S Doradus. We use an iterative prewhitening procedure to characterize the short-timescale variability in all eight stars. The periodogram of one of the YSGs, HD 269953, displays multiple strong peaks at higher frequencies than its fellows. While the field surrounding HD 269953 is quite crowded, it is the brightest star in the region, and has infrared colors indicating it is dusty. We suggest HD 269953 may be in a post-red supergiant evolutionary phase. We find a signal with a period of $\sim5$ days for the LBV HD 269582. The periodogram of S Doradus shows a complicated structure, with peaks below frequencies of 1.5 cycles per day. We fit the shape of the background noise of all eight light curves, and find a red noise component in all of them. However, the power law slope of the red noise and the timescale over which coherent structures arise changes from star to star. Our results highlight the potential for studying evolved massive stars with TESS.
|
astrophysics
|
From a sample of 15651 RR Lyrae with accurate proper motions in Gaia DR2, we measure the azimuthally averaged kinematics of the inner stellar halo between 1.5 kpc and 20 kpc from the Galactic centre. We find that their kinematics are strongly radially anisotropic, and their velocity ellipsoid nearly spherically aligned over this volume. Only in the inner regions $\lesssim$ 5 kpc does the anisotropy significantly fall (but still with $\beta >$ 0.25) and the velocity ellipsoid tilt towards cylindrical alignment. In the inner regions, our sample of halo stars rotates at up to 50 km s$^{-1}$, which may reflect the early history of the Milky Way, although there is also significant angular momentum exchange with the Galactic bar at these radii. We subsequently apply the Jeans equations to these kinematic measurements in order to non-parametrically infer the azimuthally averaged gravitational acceleration field over this volume, and by removing the contribution from baryonic matter, measure the contribution from dark matter. We find that the gravitational potential of the dark matter is nearly spherical with average flattening $q_\Phi=$ 1.01 $\pm$ 0.06 between 5 kpc and 20 kpc, and by fitting parametric ellipsoidal density profiles to the acceleration field, we measure the flattening of the dark matter halo over these radii to be $q_\rho=$ 1.00 $\pm$ 0.09.
|
astrophysics
|
Studied in this article is non-Markovian open quantum systems parametrized by Hamiltonian H, coupling operator L, and memory kernel function {\gamma}, which is a proper candidate for describing the dynamics of various solid-state quantum information processing devices. We look into the subspace stabilization problem of the system from the perspective of dynamical systems and control. The problem translates itself into finding analytic conditions that characterize invariant and attractive subspaces. Necessary and sufficient conditions are found for subspace invariance based on algebraic computations, and sufficient conditions are derived for subspace attractivity by applying a double integral Lyapunov functional. Mathematical proof is given for those conditions and a numerical example is provided to illustrate the theoretical result.
|
quantum physics
|
The design of future mobility solutions (autonomous vehicles, micromobility solutions, etc.) and the design of the mobility systems they enable are closely coupled. Indeed, knowledge about the intended service of novel mobility solutions would impact their design and deployment process, whilst insights about their technological development could significantly affect transportation management policies. This requires tools to study such a coupling and co-design future mobility systems in terms of different objectives. This paper presents a framework to address such co-design problems. In particular, we leverage the recently developed mathematical theory of co-design to frame and solve the problem of designing and deploying an intermodal mobility system, whereby autonomous vehicles service travel demands jointly with micromobility solutions such as shared bikes and e-scooters, and public transit, in terms of fleets sizing, vehicle characteristics, and public transit service frequency. Our framework is modular and compositional, allowing one to describe the design problem as the interconnection of its individual components and to tackle it from a system-level perspective. Moreover, it only requires very general monotonicity assumptions and it naturally handles multiple objectives, delivering the rational solutions on the Pareto front and thus enabling policy makers to select a policy. To showcase our methodology, we present a real-world case study for Washington D.C., USA. Our work suggests that it is possible to create user-friendly optimization tools to systematically assess the costs and benefits of interventions, and that such analytical techniques might inform policy-making in the future.
|
electrical engineering and systems science
|
We present a new time discretization scheme adapted to the structure of GENERIC systems. The scheme is variational in nature and is based on a conditional incremental minimization. The GENERIC structure of the scheme provides stability and convergence of the scheme. We prove that the scheme can be rigorously implemented in the case of the damped harmonic oscillator. Numerical evidence is collected, illustrating the performance of the method.
|
mathematics
|
The capacity to randomly pick a unitary across the whole unitary group is a powerful tool across physics and quantum information. A unitary $t$-design is designed to tackle this challenge in an efficient way, yet constructions to date rely on heavy constraints. In particular, they are composed of ensembles of unitaries which, for technical reasons, must contain inverses and whose entries are algebraic. In this work, we reduce the requirements for generating an $\varepsilon$-approximate unitary $t$-design. To do so, we first construct a specific $n$-qubit random quantum circuit composed of a sequence of, randomly chosen, 2-qubit gates, chosen from a set of unitaries which is approximately universal on $U(4)$, yet need not contain unitaries and their inverses, nor are in general composed of unitaries whose entries are algebraic; dubbed $relaxed$ seed. We then show that this relaxed seed, when used as a basis for our construction, gives rise to an $\varepsilon$-approximate unitary $t$-design efficiently, where the depth of our random circuit scales as $poly(n, t, log(1/\varepsilon))$, thereby overcoming the two requirements which limited previous constructions. We suspect the result found here is not optimal, and can be improved. Particularly because the number of gates in the relaxed seeds introduced here grows with $n$ and $t$. We conjecture that constant sized seeds such as those in ( Brand\~ao, Harrow, and Horodecki; Commun. Math. Phys. (2016) 346: 397) are sufficient.
|
quantum physics
|
This paper considers the task of learning how to make a prognosis of a patient based on his/her micro-array expression levels. The method is an application of the aggregation method as recently proposed in the literature on theoretical machine learning, and excels in its computational convenience and capability to deal with high-dimensional data. A formal analysis of the method is given, yielding rates of convergence similar to what traditional techniques obtain, while it is shown to cope well with an exponentially large set of features. Those results are supported by numerical simulations on a range of publicly available survival-micro-array datasets. It is empirically found that the proposed technique combined with a recently proposed preprocessing technique gives excellent performances.
|
statistics
|
We argue that in a large class of disordered quantum many-body systems, the late time dynamics of time-dependent correlation functions is captured by random matrix theory, specifically the energy eigenvalue statistics of the corresponding ensemble of disordered Hamiltonians. We find that late time correlation functions approximately factorize into a time-dependent piece, which only depends on spectral statistics of the Hamiltonian ensemble, and a time-independent piece, which only depends on the data of the constituent operators of the correlation function. We call this phenomenon "spectral decoupling," which signifies a dynamical onset of random matrix theory in correlation functions. A key diagnostic of spectral decoupling is $k$-invariance, which we refine and study in detail. Particular emphasis is placed on the role of symmetries, and connections between $k$-invariance, scrambling, and OTOCs. Disordered Pauli spin systems, as well as the SYK model and its variants, provide a rich source of disordered quantum many-body systems with varied symmetries, and we study $k$-invariance in these models with a combination of analytics and numerics.
|
high energy physics theory
|
We study the relation of causal influence between input systems of a reversible evolution and its output systems, in the context of operational probabilistic theories. We analyse two different definitions that are borrowed from the literature on quantum theory -- where they are equivalent. One is the notion based on signalling, and the other one is the notion used to define the neighbourhood of a cell in a quantum cellular automaton. The latter definition, that we adopt in the general scenario, turns out to be strictly weaker than the former: it is possible for a system to have causal influence on another one without signalling to it. We stress that, according to our definition, it is impossible anyway to have causal influence in the absence of an interaction, e.g.~in a Bell-like scenario. We study various conditions for causal influence, and introduce the feature that we call {\em no interaction without disturbance}, under which we prove that signalling and causal influence coincide.
|
quantum physics
|
We consider refractive index sensing with optical bounds states in the continuum (BICs) in dielectric gratings. Applying a perturbative approach we derived the differential sensitivity and the figure of merit of a sensor operating in the spectral vicinity of a BIC. Optimisation design approach for engineering an effective sensor is proposed. An analytic formula for the maximal sensitivity with an optical BIC is derived. The results are supplied with straightforward numerical simulations.
|
physics
|
Extracting information from tables in documents presents a significant challenge in many industries and in academic research. Existing methods which take a bottom-up approach of integrating lines into cells and rows or columns neglect the available prior information relating to table structure. Our proposed method takes a top-down approach, first using a generative adversarial network to map a table image into a standardised `skeleton' table form denoting the approximate row and column borders without table content, then fitting renderings of candidate latent table structures to the skeleton structure using a distance measure optimised by a genetic algorithm.
|
computer science
|
For any polynomial $p\left(x\right)$ over $\mathbb{F}_{l}$ we determine the asymptotic density of hyperelliptic curves over $\mathbb{F}_{q}$ of genus $g$ for which $p\left(x\right)$ divides the characteristic polynomial of Frobenius acting on the $l$-torsion of the Jacobian, and give an explicit formula for this density. We prove this result as a consequence of more general density theorems for quotients of Tate modules of such curves, viewed as modules over the Frobenius. The proof involves the study of measures on $R$-modules over arbitrary rings $R$ which are finite $\mathbb{Z}_{l}$-algebras. In particular we prove a result on the convergence of sequences of such measures, which can be applied to the moments computed in recent work of Lipnowski-Tsimerman to obtain the above results. We also extend the random model for finite $R$-modules proposed in that work to such rings $R$, and prove several of its properties. Notably the measure obtained is in general not inversely proportional to the size of the automorphism group.
|
mathematics
|
The goal of recommendation is to show users items that they will like. Though usually framed as a prediction, the spirit of recommendation is to answer an interventional question---for each user and movie, what would the rating be if we "forced" the user to watch the movie? To this end, we develop a causal approach to recommendation, one where watching a movie is a "treatment" and a user's rating is an "outcome." The problem is there may be unobserved confounders, variables that affect both which movies the users watch and how they rate them; unobserved confounders impede causal predictions with observational data. To solve this problem, we develop the deconfounded recommender, a way to use classical recommendation models for causal recommendation. Following Wang & Blei [23], the deconfounded recommender involves two probabilistic models. The first models which movies the users watch; it provides a substitute for the unobserved confounders. The second one models how each user rates each movie; it employs the substitute to help account for confounders. This two-stage approach removes bias due to confounding. It improves recommendation and enjoys stable performance against interventions on test sets.
|
computer science
|
Understanding the role of entanglement and its dynamics in composite quantum systems lies at the forefront of quantum matter studies. Here we investigate competing entanglement dynamics in an open Ising-spin chain that allows for exchange with an external central qudit probe. We propose a new metric dubbed the multipartite entanglement loss (MEL) that provides an upper bound on the amount of information entropy shared between the spins and the qudit probe that serves to unify physical spin-fluctuations, Quantum Fisher Information (QFI), and bipartite entanglement entropy.
|
quantum physics
|
The Solovay-Kitaev theorem allows us to approximate any single-qubit gate to arbitrary accuracy with a finite sequence of fundamental operations from a universal set of gates. Inspired by this decomposition, we present a quantum channel simulator capable of implementing any completely positive trace-preserving map. Our realization consists of one ancillary qubit, encoded in the transverse mode of a laser beam (orbital degree of freedom), one qubit system, encoded in its polarization (spin), one spin-orbit CNOT gate and four single-qubit operations performed with prisms and polarization components. Our results describe the implementation of arbitrary single-qubit channels on the photon polarization using the transverse mode as the ancillary qubit.
|
quantum physics
|
It has been observed in the literature that measurements of low-mass Drell-Yan (DY) transverse momentum spectra at low center-of-mass energies $\sqrt{s}$ are not well described by perturbative QCD calculations in collinear factorization in the region where transverse momenta are comparable with the DY mass. We examine this issue from the standpoint of the Parton Branching (PB) method, combining next-to-leading-order (NLO) calculations of the hard process with the evolution of transverse momentum dependent (TMD) parton distributions. We compare our predictions with experimental measurements at low DY mass, and find very good agreement.In addition we use the low mass DY measurements at low $\sqrt{s}$ to determine the width $q_s$ of the intrinsic Gauss distribution of the PB-TMDs at low evolution scales. We find values close to what has earlier been used in applications of PB -TMDs to high-energy processes at the Large Hadron Collider (LHC) and HERA. We find that at low DY mass and low $\sqrt{s}$ even in the region of $p_t/m_{DY} \sim 1$ the contribution of multiple soft gluon emissions (included in the PB-TMDs) is essential to describe themeasurements, while at larger masses ($m_{DY} \sim m_{Z}$) and LHC energies the contribution from soft gluons in the region of $p_t/m_{DY}\sim 1$ is small.
|
high energy physics phenomenology
|
In the context of string theory, several conjectural conditions have been proposed for low energy effective field theories not to be in swampland, the UV-incomplete class. The recent ones represented by the de Sitter and trans-Planckian censorship conjectures in particular seem to conflict with the inflation paradigm of the early universe. We first point out that scenarios where inflation is repeated several times (multi-phase inflation) can be easily compatible with these conjectures. In other words, we relax the constraint on the single inflation for the large scale perturbations to only continue at least around 10 e-folds. In this context, we then investigate if a spectator field can be a source of the almost scale-invariant primordial perturbations on the large scale. As a consequence of such an isocurvature contribution, the resultant perturbations exhibit the non-vanishing non-Gaussianity in general. Also the perturbation amplitude on smaller scales can be completely different from that on the large scale due to the multiplicity of inflationary phases. These signatures will be a smoking gun of this scenario by the future observations.
|
astrophysics
|
We present the first observational evidence for a circumplanetary disk around the protoplanet PDS~70~b, based on a new spectrum in the $K$ band acquired with VLT/SINFONI. We tested three hypotheses to explain the spectrum: Atmospheric emission from the planet with either (1) a single value of extinction or (2) variable extinction, and (3) a combined atmospheric and circumplanetary disk model. Goodness-of-fit indicators favour the third option, suggesting circumplanetary material contributing excess thermal emission --- most prominent at $\lambda \gtrsim 2.3 \mu$m. Inferred accretion rates ($\sim 10^{-7.8}$--$10^{-7.3} M_J$ yr$^{-1}$) are compatible with observational constraints based on the H$\alpha$ and Br$\gamma$ lines. For the planet, we derive an effective temperature of 1500--1600 K, surface gravity $\log(g)\sim 4.0$, radius $\sim 1.6 R_J$, mass $\sim 10 M_J$, and possible thick clouds. Models with variable extinction lead to slightly worse fits. However, the amplitude ($\Delta A_V \gtrsim 3$mag) and timescale of variation ($\lesssim$~years) required for the extinction would also suggest circumplanetary material.
|
astrophysics
|
Pinch-off and satellite droplets formation during breakup of near-inviscid liquid bridge sandwiched between two given equal and coaxial circular plates have been investigated. The breakup always results in the formation of a spindle shape which is the precursor of the satellite droplet at the moment of pinch-off. Interestingly, the slenderness of this spindle is always bigger than 2{\pi} and always results in the formation of only one satellite droplet regardless of the surface tension and the slenderness of the liquid bridge. We predict the cone angle of this spindle formed during the pinch-off of inviscid fluids should be 18.086122158...{\deg}. After pinch-off, the satellite droplets will drift out of the pinch-off regions in the case of symmetrical short bridge, and merge again with the sessile drop in the case of unsymmetrical long bridge. We demonstrate that the velocity of the satellite droplet is consistent with a scaling model based on a balance between capillary forces and the inertia at the pinch-off region.
|
physics
|
We investigate Scattering amplitudes of the reversible $\theta$-exact Seiberg-Witten (SW) map based noncommutative (NC) quantum electrodynamics, and show explicitly the SW map invariance for all tree-level NCQED $2\to2$ proceses, including M\"oller, Bhabha, Compton, pair annihilation, pair production and light-by-light $(\gamma\gamma\to\gamma\gamma)$ scatterings. We apply our NCQED results to the $\gamma\gamma\to\gamma\gamma$ and $\gamma\gamma\to\ell^+\ell^-$ exclusive processes, convoluted to the ultraperipheral lead $^{208}$Pb ion-ion collisions, recently measured by the ATLAS collaboration at LHC. We demonstrate that $\gamma\gamma\to\gamma\gamma$ is the more appropriate channel to probe NC scale $\Lambda_{\rm NC}$ while both are less efficient than some other probes.
|
high energy physics phenomenology
|
I consider a sample of eight pressure-supported low-surface brightness galaxies (seven nearby dwarfs and one ultra-diffuse object) in terms of Milgrom's modified Newtonian dynamics (MOND). These objects are modelled as Milgromian isotropic isothermal spheres characterised by two parameters that are constrained by observations: the constant line-of-sight velocity dispersion and the central surface density. The velocity dispersion determines the total mass, and, with the implied mass-to-light ratio, the central surface brightness. This then specifies the radial run of surface brightness over the entire isothermal sphere. For the objects in this sample the predicted radial distribution of surface brightness is shown to be entirely consistent with observations which constitutes a success for MOND that is independent of the reduced dynamical mass.
|
astrophysics
|
We demonstrate that a large class of one-dimensional quantum and classical exchange models can be described by the same type of graphs, namely Cayley graphs of the permutation group. Their well-studied spectral properties allow us to derive crucial information about those models of fundamental importance in both classical and quantum physics, and to completely characterize their algebraic structure. Notably, we prove that the spectral gap can be obtained in polynomial computational time, which has strong implications in the context of adiabatic quantum computing with quantum spin-chains. This quantity also characterizes the rate to stationarity of some important classical random processes such as interchange and exclusion processes. Reciprocally, we use results derived from the celebrated Bethe ansatz to obtain original mathematical results about these graphs in the unweighted case. We also discuss extensions of this unifying framework to other systems, such as asymmetric exclusion processes -- a paradigmatic model in non-equilibrium physics, or the more exotic non-Hermitian quantum systems.
|
condensed matter
|
Dielectric response and conduction mechanism were investigated for a multiferroic BiFe$_{0.95}$Mn$_{0.05}$O$_3$ epitaxial thin film. A contribution from a thermally activated interface (0.37 eV) and the bulk of the film on the dielectric response were observed through the comparison between experimental results and equivalent circuit model. The low frequency interface relaxation signatures strongly suggest a Maxwell-Wagner space charge origin. The alternative current conductivity deduced from the model follows a power law frequency dependence suggesting a polaronic hopping mechanism while the low frequency limit is in perfect agreement with the direct current conduction mechanism. The current-voltage characteristics were indeed correlated with Schottky-Simmons interface limited transport with activation energy of 0.36 eV, close to the one extracted from the impedance analysis. Such analysis of the electrostatic landscape and dielectric behaviour may help to further understanding the anomalous photo-induced properties in the BiFeO$_3$ system.
|
condensed matter
|
In this paper, the problem of dynamical deployment of unmanned aerial vehicles (UAVs) equipped with visible light communication (VLC) capabilities for optimizing the energy efficiency of UAV-enabled networks is studied. In the studied model, the UAVs can simultaneously provide communications and illumination to service ground users. Since ambient illumination increases the interference over VLC links while reducing the illumination threshold of the UAVs, it is necessary to consider the illumination distribution of the target area for UAV deployment optimization. This problem is formulated as an optimization problem which jointly optimizes UAV deployment, user association, and power efficiency while meeting the illumination and communication requirements of users. To solve this problem, an algorithm that combines the machine learning framework of gated recurrent units (GRUs) with convolutional neural networks (CNNs) is proposed. Using GRUs and CNNs, the UAVs can model the long-term historical illumination distribution and predict the future illumination distribution. Given the prediction of illumination distribution, the original nonconvex optimization problem can be divided into two sub-problems and is then solved using a low-complexity, iterative algorithm. Then, the proposed algorithm enables UAVs to determine the their deployment and user association to minimize the total transmit power. Simulation results using real data from the Earth observations group (EOG) at NOAA/NCEI show that the proposed approach can achieve up to 68.9% reduction in total transmit power compared to a conventional optimal UAV deployment that does not consider the illumination distribution and user association.
|
electrical engineering and systems science
|
Acceleration of machine learning research in healthcare is challenged by lack of large annotated and balanced datasets. Furthermore, dealing with measurement inaccuracies and exploiting unsupervised data are considered to be central to improving existing solutions. In particular, a primary objective in predictive modeling is to generalize well to both unseen variations within the observed classes, and unseen classes. In this work, we consider such a challenging problem in machine learning driven diagnosis: detecting a gamut of cardiovascular conditions (e.g. infarction, dysrhythmia etc.) from limited channel ECG measurements. Though deep neural networks have achieved unprecedented success in predictive modeling, they rely solely on discriminative models that can generalize poorly to unseen classes. We argue that unsupervised learning can be utilized to construct effective latent spaces that facilitate better generalization. This work extensively compares the generalization of our proposed approach against a state-of-the-art deep learning solution. Our results show significant improvements in F1-scores.
|
electrical engineering and systems science
|
To provide spectroscopic data for lowly charged tungsten ions relevant to fusion research, this work focuses on the W8+ ion. Six visible spectra lines in the range of 420-660 nm are observed with a compact electron-beam ion trap in Shanghai. These lines are assigned to W8+ based on their intensity variations as increasing electron-beam energy and the M1 line from the ground configuration in W7+. Furthermore, transition energies are calculated for the 30 lowest levels of the 4f14 5s2 5p4, 4f13 5s2 5p5 and 4f12 5s2 5p6 configurations of W8+ by using the flexible atomic code (FAC) and GRASP package, respectively. Reasonably good agreement is found between our two independent atomic-structure calculations. The resulting atomic parameters are adopted to simulate the spectra based on the collisional-radiative model implemented in the FAC code. This assists us with identification of six strong M1 transitions in 4f13 5s2 5p5 and 4f12 5s2 5p6 configurations from our experiments
|
physics
|
Multiplex networks are a representation of real-world complex systems as a set of entities (i.e. nodes) connected via different types of connections (i.e. layers). The observed connections in these networks may not be complete and the link prediction task is about locating the missing links across layers. Here, the main challenge is about collecting relevant evidence from different layers to assist the link prediction task. It is known that co-membership in communities increases the likelihood of connectivity between nodes. We discuss that co-membership in the communities of the similar layers augments the chance of connectivity. The layers are considered similar if they show significant inter-layer community overlap. Moreover, we found that although the presence of link is correlated in layers but the extent of this correlation is not the same across different communities. Our proposed, ML-BNMTF, as a link prediction method in multiplex networks, is devised based on these findings. ML-BNMTF outperforms baseline methods specifically when the global link overlap is low.
|
physics
|
This is a tutorial and survey paper for Locally Linear Embedding (LLE) and its variants. The idea of LLE is fitting the local structure of manifold in the embedding space. In this paper, we first cover LLE, kernel LLE, inverse LLE, and feature fusion with LLE. Then, we cover out-of-sample embedding using linear reconstruction, eigenfunctions, and kernel mapping. Incremental LLE is explained for embedding streaming data. Landmark LLE methods using the Nystrom approximation and locally linear landmarks are explained for big data embedding. We introduce the methods for parameter selection of number of neighbors using residual variance, Procrustes statistics, preservation neighborhood error, and local neighborhood selection. Afterwards, Supervised LLE (SLLE), enhanced SLLE, SLLE projection, probabilistic SLLE, supervised guided LLE (using Hilbert-Schmidt independence criterion), and semi-supervised LLE are explained for supervised and semi-supervised embedding. Robust LLE methods using least squares problem and penalty functions are also introduced for embedding in the presence of outliers and noise. Then, we introduce fusion of LLE with other manifold learning methods including Isomap (i.e., ISOLLE), principal component analysis, Fisher discriminant analysis, discriminant LLE, and Isotop. Finally, we explain weighted LLE in which the distances, reconstruction weights, or the embeddings are adjusted for better embedding; we cover weighted LLE for deformed distributed data, weighted LLE using probability of occurrence, SLLE by adjusting weights, modified LLE, and iterative LLE.
|
statistics
|
On February 6, 2019, an EMMI workshop on 'Central exclusive production at the LHC' was held at Heidelberg. Here we make some remarks on the topics presented in the talks and the discussions of this meeting. We hope that this will be useful for further studies of central exclusive reactions.
|
high energy physics phenomenology
|
This paper addresses Monte Carlo algorithms for calculating the Shapley-Shubik power index in weighted majority games. First, we analyze a naive Monte Carlo algorithm and discuss the required number of samples. We then propose an efficient Monte Carlo algorithm and show that our algorithm reduces the required number of samples as compared to the naive algorithm.
|
computer science
|
Missing data are common in data analyses in biomedical fields, and imputation methods based on random forests (RF) have become widely accepted, as the RF algorithm can achieve high accuracy without the need for specification of data distributions or relationships. However, the predictions from RF do not contain information about prediction uncertainty, which was unacceptable for multiple imputation. Available RF-based multiple imputation methods tried to do proper multiple imputation either by sampling directly from observations under predicting nodes without accounting for the prediction error or by making normality assumption about the prediction error distribution. In this study, a novel RF-based multiple imputation method was proposed by constructing conditional distributions the empirical distribution of out-of-bag prediction errors. The proposed method was compared with previous method with parametric assumptions about RF's prediction errors and predictive mean matching based on simulation studies on data with presence of interaction term. The proposed non-parametric method can deliver valid multiple imputation results. The accompanying R package for this study is publicly available.
|
statistics
|
Micro-combs [1 - 4], optical frequency combs generated by integrated micro-cavity resonators, offer the full potential of their bulk counterparts [5,6], but in an integrated footprint. The discovery of temporal soliton states (DKS dissipative Kerr solitons) [4,7-11] as a means of modelocking microcombs has enabled breakthroughs in many fields including spectroscopy [12,13], microwave photonics [14], frequency synthesis [15], optical ranging [16,17], quantum sources [18,19], metrology [20,21] and more. One of their most promising applications has been optical fibre communications where they have enabled massively parallel ultrahigh capacity multiplexed data transmission [22,23]. Here, by using a new and powerful class of microcomb called soliton crystals [11], we achieve unprecedented data transmission over standard optical fibre using a single integrated chip source. We demonstrate a line rate of 44.2 Terabits per second using the telecommunications C band at 1550nm with a spectral efficiency, a critically important performance metric, of 10.4 bits/s/Hz. Soliton crystals exhibit robust and stable generation and operation as well as a high intrinsic efficiency that, together with a low soliton microcomb spacing of 48.9 GHz enable the use of a very high coherent data modulation format of 64 QAM (quadrature amplitude modulated). We demonstrate error free transmission over 75 km of standard optical fibre in the laboratory as well as in a field trial over an installed metropolitan optical fibre network. These experiments were greatly aided by the ability of the soliton crystals to operate without stabilization or feedback control. This work demonstrates the capability of optical soliton crystal microcombs to perform in demanding and practical optical communications networks.
|
physics
|
We investigate the source detection problem in epidemiology, which is one of the most important issues for control of epidemics. Mathematically, we reformulate the problem as one of identifying the relevant component in a multivariate Gaussian mixture model. Focusing on the study of cholera and diseases with similar modes of transmission, we calibrate the parameters of our mixture model using human mobility networks within a stochastic, spatially explicit epidemiological model for waterborne disease. Furthermore, we adopt a Bayesian perspective, so that prior information on source location can be incorporated (e.g., reflecting the impact of local conditions). Posterior-based inference is performed, which permits estimates in the form of either individual locations or regions. Importantly, our estimator only requires first-arrival times of the epidemic by putative observers, typically located only at a small proportion of nodes. The proposed method is demonstrated within the context of the 2000-2002 cholera outbreak in the KwaZulu-Natal province of South Africa.
|
statistics
|
Qubitization is a modern approach to estimate Hamiltonian eigenvalues without simulating its time evolution. While in this way approximation errors are avoided, its resource and gate requirements are more extensive: qubitization requires additional qubits to store information about the Hamiltonian, and Toffoli gates to probe them throughout the routine. Recently, it was shown that storing the Hamiltonian in a unary representation can alleviate the need for such gates in one of the qubitization subroutines. Building on that principle, we develop an entirely new decomposition of the entire algorithm: without Toffoli gates, we can encode the Hamiltonian into qubits within logarithmic depth.
|
quantum physics
|
Realizing the utility of Ly$\alpha$ emission to trace the evolution of the intergalactic medium (IGM) during the epoch of reionization requires deep spectroscopy across the boundary of optical and near-infrared (NIR) spectrographs at $z\sim7.2$ when Ly$\alpha$ emission is at $\sim$1$\mu$m. Our Texas Spectroscopic Search for Ly$\alpha$ Emission at the End of Reionization includes 18 nights of deep spectroscopic observations using the Keck DEIMOS (optical) and MOSFIRE (NIR) spectrographs. Within this dataset we observe Ly$\alpha$ emission from 183 photometric-redshift selected galaxies at $z =$ 5.5 - 8.3 from the Cosmic Assembly Near infrared Deep Extragalactic Legacy Survey (CANDELS). Our overlapping MOSFIRE observations, over 84 galaxies total, provide the deepest NIR spectroscopic data yet obtained for Ly$\alpha$ from galaxies $z > 7$, with $>16$ hr integration time for four observed galaxies. Here we analyze these four targets, and we report the discovery of a new $z = 7.60$ Ly$\alpha$ detection as well as provide an updated observation of the previously confirmed $z=7.51$ Ly$\alpha$ emission from Finkelstein et al. (2013) with a $\sim$3$\times$ longer exposure time. Our analysis of these Ly$\alpha$ emission line profiles reveal a significant asymmetric shape. The two detected Ly$\alpha$ emission lines from bright sources ($M_{\text{UV}}<-20.25$) could imply that these bright galaxies inhabit ionized bubbles in a partially neutral IGM, although deeper exposures may yet reveal Ly$\alpha$ emission in the fainter sources.
|
astrophysics
|
The idea of this work is to investigate the constraints on the dark matter (DM) allowed parameter space from high scale validity (absolute stability of Higgs vacuum and perturbativity) in presence of multi particle dark sector and heavy right handed neutrinos to address correct neutrino mass. We illustrate a simple two component DM model, consisting of one inert $SU(2)_L$ scalar doublet and a scalar singlet, both stabilised by additional $\mathcal{Z}_2 \times \mathcal{Z}^{'}_2$ symmetry, which also aid to vacuum stability. We demonstrate DM-DM interaction helps achieving a large allowed parameter space for both the DM components by evading direct search bound. High scale validity puts further constraints on the model, for example, on the mass splitting between the charged and neutral component of inert doublet, which has important implication to its leptonic signature(s) at the Large Hadron Collider (LHC).
|
high energy physics phenomenology
|
The study of the competition or coexistence of different ground states in many-body systems is an exciting and actual topic of research, both experimentally and theoretically. Quantum fluctuations of a given phase can suppress or enhance another phase depending on the nature of the coupling between the order parameters, their dynamics and the dimensionality of the system. The zero temperature phase diagrams of systems with competing scalar order parameters with quartic and bilinear coupling terms have been previously studied for the cases of a zero temperature bicritical point and of coexisting orders. In this work, we apply the Matsubara summation technique from finite temperature quantum field theory to introduce the effects of thermal fluctuations on the effective potential of these systems. This is essential to make contact with experiments. We consider two and three-dimensional materials characterized by a Lorentz invariant quantum critical theory. We obtain that in both cases, thermal fluctuations lead to weak first-order temperature phase transitions, at which coexisting phases arising from quantum corrections become unstable. We show that above this critical temperature, the system presents scaling behavior consistent with that approaching a quantum critical point. Below the transition the specific heat has a thermally activated contribution with a gap related to the size of the domains of the ordered phases. We show that the critical temperature (Tc) in the coexistence region decreases as a function of the distance to the zero temperature classical bicritical point. This indicates that at the fine tuned value of this transition, the system attains the highest Tc in the region of coexistence.
|
condensed matter
|
From Gaia DR 2 data of eight high velocity hot post-AGB candidates LS 3593, LSE 148, LS 5107, HD 172324, HD 214539, LS IV -12 111, LS III +52 24, and LS 3099, we found that six of them have accurate parallaxes which made it possible to derive their distances, absolute visual magnitudes (M_V) and luminosity (log L/L_sun). Except LS 5107 all the remaining seven stars have accurate effective temperature (T_eff) in the literature. Some of these stars are metal-poor and some of them do not have circumstellar dust shells. In the past the distances of some stars were estimated to be 6~kpc which we find it to be incorrect. The accurate Gaia DR2 parallaxes show that they are relatively nearby post-AGB stars. When compared with post-AGB evolutionary tracks we find their initial masses in the range of 1M_sun to 2M_sun. We find the luminosity of LSE 148 to be significantly lower than that of post-AGB stars, suggesting that this is a post-horizontal branch star or post-early-AGB star. LS 3593 and LS 5107 are new high velocity hot post-AGB stars from Gaia DR2.
|
astrophysics
|
The origin of magnetic fields in the universe is an open problem. Seed magnetic fields possibly produced in early times may have survived up to the present day close to their original form, providing an untapped window to the primeval universe. The recent observations of high-energy neutrinos from the blazar TXS 0506+056 in association with an electromagnetic counterpart in a broad range of wavelengths can be used to probe intergalactic magnetic fields via the time delay between the neutrinos and gamma rays as well as the time dependence of the gamma-ray fluxes. Using extensive three-dimensional Monte Carlo simulations, we present a novel method to constrain these fields. We apply it to TXS 0506+056 and, for the first time, derive constraints on both the magnetic-field strength and its coherence length, considering six orders of magnitude for each.
|
astrophysics
|
Hedges' unbiased estimator g* has been broadly used in statistics. We propose a sequence of polynomials to better approximate the multiplicative correction factor of g* by incorporating analytic estimations to the ratio of gamma functions.
|
statistics
|
The linear error-correcting codes are known to be well suited for battling and correcting the burst errors caused by noise in the wireless data transmission system. However, different types of codes offer different decoding and burst-error-correcting capabilities. This paper compares the Low-Density-Parity Check (LDPC) and Reed Solomon (RS) encoding schemes in battling and correcting the burst error caused by the clipping distortion occurred due to the dynamic range constraints in an Orthogonal Frequency Division Multiplexing (OFDM) based Visible Light Communication (VLC). The unipolar conversion applied to the output of the multiplexer in this system results in a clipping noise which distorts the data symbols on the subcarriers in OFDM block. Considering that such distortion impacts the data symbol on each subcarrier differently, RS and LDP are used to encode the data block before being modulated for mapping the OFDM block. In order to control the extreme value of the output of the multiplexer, the transmitter applies puncturing to the generated codeword before mapping OFDM subcarriers, leaving the corresponding subcarriers of the punctured symbols empty. This will lead to the reduction of clipping events in the optical front-end and will mitigate the impact of nonlinear distortion on the modulated symbols for the occupied subcarriers. The redundancy in the codeword generated by the encoder is used not only to control the clipping probability by shortening the number of active subcarriers but also for the reconstruction of the original codeword and correction of the errors caused by channel noise. This work investigates the ability of LDCP and RS encoders in battling the effects of clipping noise in the frequency domain and compares their performances in improving the bit error ratio (BER) performance of an OFDM-based VLC.
|
electrical engineering and systems science
|
Covid-19 has had a disastrous economic impact on countries and industries as countries have gone through the lockdown process to reduce the health impact of Covid-19. As countries have started lifting Covid-19 related restrictions, businesses have been allowed to again have on-site customers. However, just a limited number of people are being allowed on-site as long as social distancing measures are being followed. This has resulted in heavy burdens on businesses as their number of customers have decreased substantially. In this study, we propose a model to minimize the economic impact of Covid-19 for businesses that have implemented social distancing measures, as well as to minimize the health impact of Covid-19 for their customers and employees. We introduce the quantity Spread in which minimizing Spread gives the optimum number and arrangement of people at a given site while applying social distancing measures. We apply our model to a real-world scenario and optimize the number of passengers and their arrangements under a social distancing measure for two different popular aircraft seat layouts using the Annealing Monte Carlo technique. We obtain the optimal numbers and optimal arrangements of passengers considering both family groups and individual passengers for the social distancing measure. The obtained optimal arrangements of passengers show complex patterns with groups and individual passengers mixed in complex and non-trivial ways. This demonstrates the necessity of using our model or its variants to find these optimal arrangements. In addition, we show that any other arrangements of passengers with the same number of passengers is a suboptimal arrangement with higher health risks as a result of less distance between passengers. Our model could be implemented for other social situations such as sports events, theaters, medical centers, etc.
|
physics
|
We study a scalar singlet dark matter (DM) having mass in sub-TeV regime by extending the minimal scalar singlet DM setup by additional vector like fermions. While the minimal scalar singlet DM satisfies the relic and direct detection constraints for mass beyond TeV only, presence of its portal coupling with vector like fermions opens up additional co-annihilation channels. These vector like fermions also help in achieving electroweak vacuum stability all the way up to Planck scale. We find that for one generation of vector like quarks consisting of a $SU(2)_L$ doublet and a singlet, scalar singlet DM with mass a few hundred GeV can indeed satisfy relic, direct detection and other relevant constraints while also making the electroweak vacuum absolutely stable. The same can be achieved by introducing vector like leptons too, but with three generations. While the model with vector like quarks is minimal, the three generations of vector like lepton doublet and neutral singlet can also give rise to light neutrino mass at one loop level.
|
high energy physics phenomenology
|
Ultrasound Localization Microscopy (ULM) offers a cost-effective modality for microvascular imaging by using intravascular contrast agents (microbubbles). However, ULM has a fundamental trade-off between acquisition time and spatial resolution, which makes clinical translation challenging. In this paper, in order to circumvent the trade-off, we introduce a spatiotemporal filtering operation dubbed velocity filtering, which is capable of separating contrast agents into different groups based on their vector velocities thus reducing interference in the localization step, while simultaneously offering blood velocity mapping at super resolution, without tracking individual microbubbles. As side benefit, the velocity filter provides noise suppression before microbubble localization that could enable substantially increased penetration depth in tissue typically by 4cm or more. We provide a theoretical analysis of the performance of velocity filter. Numerical experiments confirm that the proposed velocity filter is able to separate the microbubbles with respect to the speed and direction of their motion. In combination with subsequent localization of microbubble centers, e.g. by matched filtering, the velocity filter improves the quality of the reconstructed vasculature significantly and provides blood flow information. Overall, the proposed imaging pipeline in this paper enables the use of higher concentrations of microbubbles while preserving spatial resolution, thus helping circumvent the trade-off between acquisition time and spatial resolution. Conveniently, because the velocity filtering operation can be implemented by fast Fourier transforms(FFTs) it admits fast, and potentially real-time realization. We believe that the proposed velocity filtering method has the potential to pave the way to clinical translation of ULM.
|
electrical engineering and systems science
|
To date, investigations of carrier-envelope-phase (CEP) dependent effects have been limited to optical pulses with few cycles and high intensity, and have not been reported for other types of pulses. Optomechanical systems are shown to have the potential to go beyond these limits. We present an approach using optomechanics to extend the concept of the traditional CEP in the few-cycle regime to mechanical pulses and develop a two-step model to give a physical insight. By adding an auxiliary continuous optical field, we show that a CEP-dependent effect appears even in the multi-cycle regime of mechanical pulses. We obtain the approximated analytical solutions providing full understanding for these optomechanically induced CEP-dependent effects. In addition, our findings show that one can draw on the optomechanical interaction to revive the CEP-dependent effects on optical pulses with an arbitrary number of cycles and without specific intensity requirements. The effects of CEP, broadly extended to encompass few- and multi-cycle optical and mechanical pulses, may stimulate a variety of applications in the preparation of a CEP-stabilized pulse, the generation of ultrasonic pulses with a desired shape, the linear manipulation of optical combs, and more.
|
physics
|
To effectively apply robots in working environments and assist humans, it is essential to develop and evaluate how visual grounding (VG) can affect machine performance on occluded objects. However, current VG works are limited in working environments, such as offices and warehouses, where objects are usually occluded due to space utilization issues. In our work, we propose a novel OCID-Ref dataset featuring a referring expression segmentation task with referring expressions of occluded objects. OCID-Ref consists of 305,694 referring expressions from 2,300 scenes with providing RGB image and point cloud inputs. To resolve challenging occlusion issues, we argue that it's crucial to take advantage of both 2D and 3D signals to resolve challenging occlusion issues. Our experimental results demonstrate the effectiveness of aggregating 2D and 3D signals but referring to occluded objects still remains challenging for the modern visual grounding systems. OCID-Ref is publicly available at https://github.com/lluma/OCID-Ref
|
computer science
|
Neural networks have been widely used, and most networks achieve excellent performance by stacking certain types of basic units. Compared to increasing the depth and width of the network, designing more effective basic units has become an important research topic. Inspired by the elastic collision model in physics, we present a universal structure that could be integrated into the existing network structures to speed up the training process and increase their generalization abilities. We term this structure the "Inter-layer Collision" (IC) structure. We built two kinds of basic computational units (IC layer and IC block) that compose the convolutional neural networks (CNNs) by combining the IC structure with the convolution operation. Compared to traditional convolutions, both of the proposed computational units have a stronger non-linear representation ability and can filter features useful for a given task. Using these computational units to build networks, we bring significant improvements in performance for existing state-of-the-art CNNs. On the imagenet experiment, we integrate the IC block into ResNet-50 and reduce the top-1 error from 22.85% to 21.49%, which also exceeds the top-1 error of ResNet-100 (21.75%).
|
computer science
|
Solvent-solute interactions in precursor solutions of lead halide perovskites (LHP) critically impact the quality of solution-processed materials, as they lead to the formation of a variety of poly-iodoplumbates that act as building blocks for LHP. The formation of [PbI$_{2+n}$]$^{n-}$ complexes is often expected in diluted solutions while coordination occurring at high concentrations is not well understood yet. In a combined \textit{ab initio} and experimental work, we demonstrate that the optical spectra of the quasi-one-dimensional iodoplumbate complexes PbI$_2$(DMSO)$_4$, Pb$_2$I$_4$(DMSO)$_6$, and Pb$_3$I$_6$(DMSO)$_8$ formed in dimethyl sulfoxide solutions are compatible with the spectral fingerprints measured at high concentrations of lead iodide. This finding suggests that the formation of polynuclear lead-halide complexes should be accounted for in the interpretation of optical spectra of LHP precursor solutions.
|
condensed matter
|
This paper presents a simulator-assisted training method (SimVAE) for variational autoencoders (VAE) that leads to a disentangled and interpretable latent space. Training SimVAE is a two-step process in which first a deep generator network(decoder) is trained to approximate the simulator. During this step, the simulator acts as the data source or as a teacher network. Then an inference network (encoder)is trained to invert the decoder. As such, upon complete training, the encoder represents an approximately inverted simulator. By decoupling the training of the encoder and decoder we bypass some of the difficulties that arise in training generative models such as VAEs and generative adversarial networks (GANs). We show applications of our approach in a variety of domains such as circuit design, graphics de-rendering and other natural science problems that involve inference via simulation.
|
statistics
|
We compute the contributions of dimension six two-quark operators to the non-leptonic decay width of heavy hadrons due to the flavor changing bottom-to-up-quark transition in the heavy quark expansion. Analytical expressions for the Darwin term $\rho_D$ and the spin-orbit term $\rho_{\rm LS}$ are obtained with leading order accuracy.
|
high energy physics phenomenology
|
We study the collective dynamics of a clean Floquet system of cold atoms, numerically simulating two realistic set-ups based on a regular chain of interacting Rydberg atoms driven by laser fields. In both cases, the population evolution and its Fourier spectrum display clear signatures of a discrete time crystal (DTC), exhibiting the appearance of a robust subharmonic oscillation which persists on a time scale increasing with the chain size, within a certain range of control parameters. We also characterize how the DTC stability is affected by dissipative processes, typically present in this atomic system even though the Rydberg state is very long lived.
|
quantum physics
|
One of the main approaches used to construct prior distributions for objective Bayes methods is the concept of random imaginary observations. Under this setup, the expected-posterior prior (EPP) offers several advantages, among which it has a nice and simple interpretation and provides an effective way to establish compatibility of priors among models. In this paper, we study the power-expected posterior prior as a generalization to the EPP in objective Bayesian model selection under normal linear models. We prove that it can be represented as a mixture of $g$-prior, like a wide range of prior distributions under normal linear models, and thus posterior distributions and Bayes factors are derived in closed form, keeping therefore computational tractability. Comparisons with other mixtures of $g$-prior are made and emphasis is given in the posterior distribution of g and its effect on Bayesian model selection and model averaging.
|
statistics
|
This paper describes a wearable wireless mouse-cursor controller that optically tracks the degree of tilt of the user's head to move the mouse relative distances and therefore the degrees of tilt. The raw data can be processed locally on the wearable device before wirelessly transmitting the mouse-movement reports over Bluetooth Low Energy (BLE) protocol to the host computer; but for exploration of algorithms, the raw data can also be processed on the host. The use of standard Human-Interface Device (HID) profile enables plug-and-play of the proposed mouse device on modern computers without requiring separate driver installation. It can be used in two different modes to move the cursor, the joystick mode and the direct mapped mode. Experimental results show that this head-controlled mouse to be intuitive and effective in operating the mouse cursor with fine-grained control of the cursor even by untrained users.
|
computer science
|
The dynamics of the $J^{PC}=0^{-+}$, $0^{++}$, and $2^{++}$ resonance contributions to the decay $J/\psi\to\gamma X(J^{PC})\to\gamma\phi\phi$ is analysed using the data obtained by BESIII collaboration. The effective coupling constants parameterising invariant amplitudes of the transitions $J/\psi\to\gamma X(J^{PC})$ and $X(J^{PC})\to\phi\phi$ and masses of $X(J^{PC})$ resonances are found from the fits. They are used for evaluation of the branching fractions $B_{X(J^{PC})\to\phi\phi}$, relative branching fractions $B_{J/\psi\to\gamma X(J^{PC})\to\gamma\phi\phi}$, and for obtaining the photon angular distributions.
|
high energy physics phenomenology
|
Classical GR governs the evolution of black holes for a long time, but at some exponentially large time it must break down. The breakdown, and what comes after it, is not well understood. In this paper I'll discuss the problem using concepts drawn from complexity geometry. In particular the geometric concept of cut locus plays a key role.
|
high energy physics theory
|
In this paper the phase structure of dense baryon matter composed of $u$ and $d$ quarks with two colors has been investigated in the presence of baryon $\mu_B$, isospin $\mu_I$ and chiral isospin $\mu_{I5}$ chemical potentials in the framework of Nambu--Jona-Lasinio model. In the chiral limit, it has been shown that the duality between phases with spontaneous chiral symmetry breaking and condensation of charged pions, found in the three color case, remains valid in the two color case. In addition, it has been shown that there are two more dualities in the phase diagram in two color case, namely (as in the case with $\mu_{I5}=0$), at $\mu_{I5}\ne 0$ the general $(\mu,\mu_I,\mu_{I5})$-phase portrait of the model has dual symmetry between the phase with condensation of charged pions and the phase with diquark condensation. This duality stays exact even in the physical point, $m_0\ne 0$. And at $m_0=0$ the $(\mu,\mu_I,\mu_{I5})$-phase portrait becomes even more symmetrical, since dual symmetry between phases with spontaneous chiral symmetry breaking and diquark condensation appears. It is shown that due to the dualities the phase diagram is extremely symmetric and has interlacing structure. One can show that the phase portrait of two-color NJL model can be obtained just by duality properties from the results of investigations of three-color NJL model (it was noticed only after the numerical calculations have been performed). Three-color case shares only one duality of the two color one, and one can only see a facet of this enormously symmetric picture in the case of three colors. Using dualities only, it is possible to show that there are no mixed phases (phases with two non-zero condensates). This prediction of dualities is of great use, because for sure it can be shown by the direct calculations but it would be enormously more complicated and time-consuming numerically.
|
high energy physics phenomenology
|
Multi-agent networked control systems (NCSs) are often subject to model uncertainty and are limited by large communication cost, associated with feedback of data between the system nodes. To provide robustness against model uncertainty and to reduce the communication cost, this paper investigates the mixed $H_2/H_{\infty}$ control problem for NCS under the sparsity constraint. First, proximal alternating linearized minimization (PALM) is employed to solve the centralized social optimization where the agents have the same optimization objective. Next, we investigate a sparsity-constrained noncooperative game, which accommodates different control-performance criteria of different agents, and propose a best-response dynamics algorithm based on PALM that converges to an approximate Generalized Nash Equilibrium (GNE) of this game. A special case of this game, where the agents have the same $H_2$ objective, produces a partially-distributed social optimization solution. We validate the proposed algorithms using a network with unstable node dynamics and demonstrate the superiority of the proposed PALM-based method to a previously investigated sparsity-constrained mixed $H_2/H_{\infty}$ controller.
|
electrical engineering and systems science
|
We discuss prospects for Monte Carlo event generators incorporating the dynamics of transverse momentum dependent (TMD) parton distribution functions. We illustrate TMD evolution in the parton branching formalism, and present Monte Carlo applications of the method.
|
high energy physics phenomenology
|
This is a review of selected topics from recent work on symmetry charges in asymptotically flat spacetime done by the author in collaboration with U. Kol and R. Javadinezhad. First we reinterpret the reality constraint on the boundary graviton as the gauge fixing of a new local symmetry, called dual supertranslations. This symmetry extends the BMS group and bears many similarities to the dual (magnetic) gauge symmetry of electrodynamics. We use this new gauge symmetry to propose a new description of the TAUB-NUT space that does not contain closed time-like curves. Next we summarize progress towards the definition of Lorentz and super-Lorentz charges that commute with supertranslations and with the soft graviton mode.
|
high energy physics theory
|
The presence of outlying observations may adversely affect statistical testing procedures that result in unstable test statistics and unreliable inferences depending on the distortion in parameter estimates. In spite of the fact that the adverse effects of outliers in panel data models, there are only a few robust testing procedures available for model specification. In this paper, a new weighted likelihood based robust specification test is proposed to determine the appropriate approach in panel data including individual-specific components. The proposed test has been shown to have the same asymptotic distribution as that of most commonly used Hausman's specification test under null hypothesis of random effects specification. The finite sample properties of the robust testing procedure are illustrated by means of Monte Carlo simulations and an economic-growth data from the member countries of the Organisation for Economic Co-operation and Development. Our records reveal that the robust specification test exhibit improved performance in terms of size and power of the test in the presence of contamination.
|
statistics
|
Social engineering through social media channels targeting organizational employees is emerging as one of the most challenging information security threats. Social engineering defies traditional security efforts due to the method of attack relying on human naivet\'e or error. The vast amount of information now made available to social engineers through online social networks is facilitating methods of attack which rely on some form of human error to enable infiltration into company networks. While, paramount to organisational information security objectives is the introduction of relevant comprehensive policy and guideline, perspectives and practices vary from global region to region. This paper identifies such regional variations and then presents a detailed investigation on information security outlooks and practices, surrounding social media, in Australian organisations (both public and private). Results detected disparate views and practices, suggesting further work is needed to achieve effective protection against security threats arsing due to social media adoption.
|
computer science
|
We have carried out a search for substructure within the globular cluster systems of M84 (NGC 4374) and M86 (NGC 4406), two giant elliptical galaxies in the Virgo Cluster. We use wide-field (36 arcmin x 36 arcmin), multi-color broadband imaging to identify globular cluster candidates in these two galaxies as well as several other nearby lower-mass galaxies. Our analysis of the spatial locations of the globular cluster candidates reveals several substructures, including: a peak in the projected number density of globular clusters in M86 that is offset from the system center and may be at least partly due to the presence of the dwarf elliptical galaxy NGC 4406B; a bridge that connects the M84 and M86 globular cluster systems; and a boxy iso-density contour along the southeast side of the M86 globular cluster system. We divide our sample into red (metal-rich) and blue (metal-poor) globular cluster candidates to look for differences in the spatial distributions of the two populations and find that the blue cluster candidates are the dominant population in each of the substructures we identify. We also incorporate the measurements from two radial velocity surveys of the globular clusters in the region and find that the bridge substructure is populated by globular clusters with a mix of velocities that are consistent with either M86 and M84, possibly providing further evidence for interaction signatures between the two galaxies.
|
astrophysics
|
This paper aims at providing multi-source remote sensing images registered in geometric space for image fusion. Focusing on the characteristics and differences of multi-source remote sensing images, a feature-based registration algorithm is implemented. The key technologies include image scale-space for implementing multi-scale properties, Harris corner detection for keypoints extraction, and partial intensity invariant feature descriptor (PIIFD) for keypoints description. Eventually, a multi-scale Harris-PIIFD image registration algorithm framework is proposed. The experimental results of four sets of representative real data show that the algorithm has excellent, stable performance in multi-source remote sensing image registration, and can achieve accurate spatial alignment, which has strong practical application value and certain generalization ability.
|
electrical engineering and systems science
|
In earlier work, we studied holographic entanglement entropy in QCD phases using a dynamical Einstein-Maxwell-dilaton gravity model whose dual boundary theory mimics essential features of QCD above and below deconfinement. The model although displays subtle differences compared to the standard QCD phases, however, it introduces a notion of temperature in the phase below the deconfinement critical temperature and captures quite well the entanglement and thermodynamic properties of QCD phases. Here we extend our analysis to study the mutual and $n$-partite information by considering $n$ strips with equal lengths and equal separations, and investigate how these quantities leave their imprints in holographic QCD phases. We discover a rich phase diagram with $n\geq2$ strips and the corresponding mutual and $n$-partite information shows rich structure, consistent with the thermodynamical transitions, while again revealing some subtleties. Below the deconfinement critical temperature, we find no dependence of the mutual and $n$-partite information on temperature and chemical potential.
|
high energy physics theory
|
The explosive growth of easily-accessible unlabeled data has lead to growing interest in active learning, a paradigm in which data-hungry learning algorithms adaptively select informative examples in order to lower prohibitively expensive labeling costs. Unfortunately, in standard worst-case models of learning, the active setting often provides no improvement over non-adaptive algorithms. To combat this, a series of recent works have considered a model in which the learner may ask enriched queries beyond labels. While such models have seen success in drastically lowering label costs, they tend to come at the expense of requiring large amounts of memory. In this work, we study what families of classifiers can be learned in bounded memory. To this end, we introduce a novel streaming-variant of enriched-query active learning along with a natural combinatorial parameter called lossless sample compression that is sufficient for learning not only with bounded memory, but in a query-optimal and computationally efficient manner as well. Finally, we give three fundamental examples of classifier families with small, easy to compute lossless compression schemes when given access to basic enriched queries: axis-aligned rectangles, decision trees, and halfspaces in two dimensions.
|
computer science
|
In this paper, we consider conditional gradient methods. These are methods that use a linear minimization oracle, which, for a given vector $p \in \mathbb{R}^n$, computes the solution of the subproblem $$\arg \min_{x\in X}{\langle p,x \rangle}.$$ There are a variety of conditional gradient methods that have a linear convergence rate in a strongly convex case. However, in all these methods, the dimension of the problem is included in the rate of convergence, which in modern applications can be very large. In this paper, we prove that in the strongly convex case, the convergence rate of the conditional gradient methods in the best case depends on the dimension of the problem $ n $ as $ \widetilde {\Omega} (\sqrt {n}) $. Thus, the conditional gradient methods may turn out to be ineffective for solving strongly convex optimization problems of large dimensions. Also, the application of conditional gradient methods to minimization problems of a quadratic form is considered. The effectiveness of the Frank-Wolfe method for solving the quadratic optimization problem in the convex case on a simplex (PageRank) has already been proved. This work shows that the use of conditional gradient methods to solve the minimization problem of a quadratic form in a strongly convex case is ineffective due to the presence of dimension in the convergence rate of these methods. Therefore, the Shrinking Conditional Gradient method is considered. Its difference from the conditional gradient methods is that it uses a modified linear minimization oracle. The convergence rate of such an algorithm does not depend on dimension. Using the Shrinking Conditional Gradient method the complexity of solving the minimization problem of quadratic form on a $ \infty $-ball is obtained. The resulting evaluation of the method is comparable to the complexity of the gradient method.
|
mathematics
|
As 3D scanning solutions become increasingly popular, several deep learning setups have been developed geared towards that task of scan completion, i.e., plausibly filling in regions there were missed in the raw scans. These methods, however, largely rely on supervision in the form of paired training data, i.e., partial scans with corresponding desired completed scans. While these methods have been successfully demonstrated on synthetic data, the approaches cannot be directly used on real scans in absence of suitable paired training data. We develop a first approach that works directly on input point clouds, does not require paired training data, and hence can directly be applied to real scans for scan completion. We evaluate the approach qualitatively on several real-world datasets (ScanNet, Matterport, KITTI), quantitatively on 3D-EPN shape completion benchmark dataset, and demonstrate realistic completions under varying levels of incompleteness.
|
computer science
|
We study the properties of a homogeneous dilute Bose-Bose gas in a weak-disorder potential at zero temperature. By using the perturbation theory, we calculate the disorder corrections to the condensate density, the equation of state, the compressibility, and the superfluid density as a function of density, strength of disorder, and miscibility parameter. It is found that the disorder potential may lead to modifying the miscibility-immiscibility condition and a full miscible phase turns out to be impossible in the presence of the disorder. We show that the intriguing interplay of the disorder and intra- and interspecies interactions may strongly influence the localization of each component, the quantum fluctuations, and the compressibility, as well as the superfluidity of the system.
|
condensed matter
|
The antenna selection (AS) in non-orthogonal multiple access (NOMA) networks is still a challenging problem since finding optimal AS solution may not be available for all channel realizations and has quite computational complexity when it exists. For this reason, in this paper, we develop a new suboptimal solution, majority based transmit antenna selection (TAS-maj), with significant reduction in computational complexity. The TAS-maj basically selects the transmit antenna with the majority. It is more efficient when compared to previously proposed suboptimal AS algorithms, namely max-max-max (A^3) and max-min-max (AIA) because these schemes are merely interested in optimizing the performance of the strongest and weakest users, respectively at the price of worse performance for the remaining users. On the other hand, the TAS-maj scheme yields better performance for more than half of mobile users in the NOMA networks. In this paper, we consider a multiple-input multiple-output communication system, where all the nodes are equipped with multi-antenna. Besides the TAS-maj is employed at the base station, a maximal ratio combining (MRC) is also employed at each mobile user in order to achieve superior performance. The impact of the channel estimation errors (CEEs) and feedback delay (FD) on the performance of the TAS-maj/MRC scheme is studied in the NOMA network over Nakagami-m fading channels.
|
electrical engineering and systems science
|
A nonzero-mass hypothesis for the photon can produces a frequency-dependent dispersion of light, which results in arrival-time differences of photons with different frequencies originating from a given transient source. Extragalactic fast radio bursts (FRBs), with their low frequency emissions, short time durations, and long propagation distances, are excellent astrophysical probes to constrain the rest mass of the photon $m_{\gamma}$. However, the derivation of a limit on $m_{\gamma}$ is complicated by the similar frequency dependences of dispersion expected from the plasma and nonzero photon mass effects. If a handful measurements of redshift for FRBs are available, the different redshift dependences of the plasma and photon mass contributions to the dispersion measure (DM) might be able to break dispersion degeneracy in testing the photon mass. For now, nine FRBs with redshift measurements have been reported, which can turn this idea into reality. Taking into account the DM contributions from both the plasma and a possible photon mass, we use the data on the nine FRBs to derive a combined limit of $m_{\gamma}\leq7.1\times10^{-51}\;{\rm kg}$, or equivalently $m_{\gamma}\leq4.0\times10^{-15}\; {\rm eV}/c^{2}$ at 68\% confidence level, which is essentially as good as or represents a factor of 7 improvement over previous limits obtained by the single FRBs. Additionally, a reasonable estimation for the DM contribution from the host galaxy, $\rm DM_{host}$, can be simultaneously achieved in our analysis. The rapid progress in localizing FRBs will further tighten the constraints on both $m_{\gamma}$ and $\rm DM_{host}$.
|
astrophysics
|
Purpose: There is increasing interest in computed tomography (CT) image estimations from magnetic resonance (MR) images. The estimated CT images can be utilised for attenuation correction, patient positioning, and dose planning in diagnostic and radiotherapy workflows. This study aims to introduce a novel statistical learning approach for improving CT estimation from MR images and to compare the performance of our method with the existing model based CT image estimation methods. Methods: The statistical learning approach proposed here consists of two stages. At the training stage, prior knowledges about tissue-types from CT images were used together with a Gaussian mixture model (GMM) to explore CT image estimations from MR images. Since the prior knowledges are not available at the prediction stage, a classifier based on RUSBoost algorithm was trained to estimate the tissue-types from MR images. For a new patient, the trained classifier and GMMs were used to predict CT image from MR images. The classifier and GMMs were validated by using voxel level 10-fold cross-validation and patient-level leave-one-out cross-validation, respectively. Results: The proposed approach has outperformance in CT estimation quality in comparison with the existing model based methods, especially on bone tissues. Our method improved CT image estimation by 5% and 23% on the whole brain and bone tissues, respectively. Conclusions: Evaluation of our method shows that it is a promising method to generate CT image substitutes for the implementation of fully MR-based radiotherapy and PET/MRI applications.
|
statistics
|
In light of recent renewed interest in streaks in turbulent jets, the current work explores their coexistence with vortex rings in the near field of turbulent round jets. A Reynolds number, $Re=1.5 \times 10^5$ jet is studied at two diameters downstream of the nozzle, using high-speed stereo particle image velocimetry. The spectra of individual velocity components reveal radially localized signatures of the large scale structures. The radial shapes of the spectral proper orthogonal decomposition modes corresponding to the signatures, confirm the presence of high speed streaks in the outer edge of the jet at low Strouhal number, $St \rightarrow 0$. The vortex rings and streamwise vortices are found to occur in the shear layer at $St \approx 0.49$, where they convect together as a system and feed the streaks. The role of vortex rings in the existence of streaks is then studied by strengthening the rings through axisymmetric excitation. The streaks are observed to persist, retaining their shapes and show only slight changes in their energies.
|
physics
|
We consider the $\mathbb{C}\mathbb{P}^{(N_f-1)}$ Non-Linear-Sigma-Model in the dimension $4<d<6$. The critical behaviour of this model in the large $N_f$ limit is reviewed. We propose a Higher Derivative Gauge (HDG) theory as an ultraviolet completion of the $\mathbb{C}\mathbb{P}^{(N_f-1)}$ NLSM. Tuning mass operators to zero, the HDG in the IR limit reaches to the critical $\mathbb{C}\mathbb{P}^{(N_f-1)}$. With partial tunings the HDG reaches either to the critical $U(N_f)$-Yukawa model or to the critical pure scalar QED (no Yukawa interactions). We renormalize the HDG in its critical dimension $d=6$. We study the fixed points of the HDG in $d=6-2\epsilon$ and we calculate the scaling dimensions of various observables finding a full agreement with the order $O(1/N_f)$ predictions of the corresponding critical models.
|
high energy physics theory
|
Conformal blocks are the fundamental, theory-independent building blocks in any CFT, so it is important to understand their holographic representation in the context of AdS/CFT. We describe how to systematically extract the holographic objects which compute higher-point global (scalar) conformal blocks in arbitrary spacetime dimensions, extending the result for the four-point block, known in the literature as a geodesic Witten diagram, to five- and six-point blocks. The main new tools which allow us to obtain such representations are various higher-point propagator identities, which can be interpreted as generalizations of the well-known flat space star-triangle identity, and which compute integrals over products of three bulk-to-bulk and/or bulk-to-boundary propagators in negatively curved spacetime. Using the holographic representation of the higher-point conformal blocks and higher-point propagator identities, we develop geodesic diagram techniques to obtain the explicit direct-channel conformal block decomposition of a broad class of higher-point AdS diagrams in a scalar effective bulk theory, with closed-form expressions for the decomposition coefficients. These methods require only certain elementary manipulations and no bulk integration, and furthermore provide quite trivially a simple algebraic origin of the logarithmic singularities of higher-point tree-level AdS diagrams. We also provide a more compact repackaging in terms of the spectral decomposition of the same diagrams, as well as an independent discussion on the closely related but computationally simpler framework over $p$-adics which admits comparable statements for all previously mentioned results.
|
high energy physics theory
|
A new underground lab, Yemilab, is being constructed in Handuk iron mine, Korea. The default design of Yemilab includes a space for a future neutrino experiment. We propose to build a water-based liquid scintillator (WbLS) detector of 4$\sim$5 kiloton size at the Yemilab. The WbLS technology combines the benefits from both water and liquid scintillator (LS) in a single detector so that low energy physics and rare event searches can have higher sensitivities due to the larger size detector with increased light yield. No experiment has ever used a WbLS technology since it still needs some R&D studies, as currently being performed by THEIA group. If this technology works successfully with kiloton scale detector at Yemilab then it can be applied to future T2HKK (Hyper-K 2$^{nd}$ detector in Korea) to improve its physics potentials especially in the low energy region.
|
physics
|
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