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Access to online visual search engines implies sharing of private user content - the query images. We introduce the concept of targeted mismatch attack for deep learning based retrieval systems to generate an adversarial image to conceal the query image. The generated image looks nothing like the user intended query, but leads to identical or very similar retrieval results. Transferring attacks to fully unseen networks is challenging. We show successful attacks to partially unknown systems, by designing various loss functions for the adversarial image construction. These include loss functions, for example, for unknown global pooling operation or unknown input resolution by the retrieval system. We evaluate the attacks on standard retrieval benchmarks and compare the results retrieved with the original and adversarial image. | computer science |
Nonparametric kernel density and local polynomial regression estimators are very popular in Statistics, Economics, and many other disciplines. They are routinely employed in applied work, either as part of the main empirical analysis or as a preliminary ingredient entering some other estimation or inference procedure. This article describes the main methodological and numerical features of the software package nprobust, which offers an array of estimation and inference procedures for nonparametric kernel-based density and local polynomial regression methods, implemented in both the R and Stata statistical platforms. The package includes not only classical bandwidth selection, estimation, and inference methods (Wand and Jones, 1995; Fan and Gijbels, 1996), but also other recent developments in the statistics and econometrics literatures such as robust bias-corrected inference and coverage error optimal bandwidth selection (Calonico, Cattaneo and Farrell, 2018, 2019). Furthermore, this article also proposes a simple way of estimating optimal bandwidths in practice that always delivers the optimal mean square error convergence rate regardless of the specific evaluation point, that is, no matter whether it is implemented at a boundary or interior point. Numerical performance is illustrated using an empirical application and simulated data, where a detailed numerical comparison with other R packages is given. | statistics |
We study the motion of dispersed nanoprobes in entangled active-passive polymer mixtures. By comparing the two architectures of linear vs. unconcatenated and unknotted circular polymers, we demonstrate that novel, rich physics emerge. For both polymer architectures, nanoprobes of size smaller than the entanglement threshold of the solution move faster as activity is increased and more energy is pumped in the system. For larger nanoprobes, a surprising phenomenon occurs: while in linear solutions they move qualitatively as before, in active-passive ring solutions nanoprobes {\it decelerate} with respect to the purely passive conditions. We rationalize this effect in terms of the non-equilibrium, topology-dependent association (clustering) of nanoprobes to the cold component of the ring mixture reminiscent of the recently discovered [Weber et al., Phys. Rev. Lett. 116, 058301 (2016)] phase separation in scalar active-passive mixtures. We conclude with a potential connection to the microrheology of the chromatin in the nuclei of the cells. | condensed matter |
We have reviewed the current status of the inclusive neutrino scattering from $^{12}$C in the low energy region corresponding to the neutrino beams from the pion, muon and kaon decaying at rest. The theoretical calculations of total cross sections in various nuclear models with special emphasis on the recent experiments with the monoenergetic neutrinos from KDAR [1] along with the older experiments from KARMEN and LSND collaborations have been discussed in the context of the recent works by Akbar et al. [2] and Nikolakopoulos et al. [3]. The inadequacy of the various theoretical models used to explain the experimental results on the inclusive neutrino scattering from nuclei at low energies has been highlighted and the need for a better understanding of the nuclear medium effects beyond the impulse approximation has been emphasized. | high energy physics phenomenology |
We introduce a multivariable Casson-Lin type invariant for links in $S^3$. This invariant is defined as a signed count of irreducible $\operatorname{SU}(2)$ representations of the link group with fixed meridional traces. For 2-component links with linking number one, the invariant is shown to be a sum of multivariable signatures. We also obtain some results concerning deformations of $\operatorname{SU}(2)$ representations of link groups. | mathematics |
The proper time method plays an important role in modern mathematics and physics. It includes many approaches, each of which has its pros and cons. This work is devoted to the description of one model case, which reflects the subtleties of construction and can be extended to a more general cases (curved space, manifold with boundary), and contains two interrelated parts: asymptotic expansion and path intergal representation. The paper discusses in details the importance of gauge conditions and role of the ordered exponentials, gives the proof of a new non-recursive formula for the Seeley-DeWitt coefficients on the diagonal, as well as the equivalence of the two main approaches using the exponential formula. | high energy physics theory |
The Fisher information matrix (FIM) is fundamental to understanding the trainability of deep neural nets (DNN), since it describes the parameter space's local metric. We investigate the spectral distribution of the conditional FIM, which is the FIM given a single sample, by focusing on fully-connected networks achieving dynamical isometry. Then, while dynamical isometry is known to keep specific backpropagated signals independent of the depth, we find that the parameter space's local metric linearly depends on the depth even under the dynamical isometry. More precisely, we reveal that the conditional FIM's spectrum concentrates around the maximum and the value grows linearly as the depth increases. To examine the spectrum, considering random initialization and the wide limit, we construct an algebraic methodology based on the free probability theory. As a byproduct, we provide an analysis of the solvable spectral distribution in two-hidden-layer cases. Lastly, experimental results verify that the appropriate learning rate for the online training of DNNs is in inverse proportional to depth, which is determined by the conditional FIM's spectrum. | statistics |
Scattering amplitudes computed by superstring perturbation theory are known to holomorphically split into chiral half integrands at fixed internal loop momentum. It is established by direct computation that upon reduction to the ordinary moduli space, the chiral half integrands of the superstring match those computed by the ambitwistor string in the limit of zero tension ($\alpha'\rightarrow\infty$). Subtleties that arise at higher genus due to the nonprojectedness of the supermoduli space are considered and arguments as to their resolution are furnished. | high energy physics theory |
Constructing and implementing useful quantum algorithms is one of the central challenges in quantum information science. Efficient sampling from a classical Gibbs distribution is an important computational problem with applications ranging from statistical physics over Monte Carlo and optimization algorithms to machine learning. Here, we introduce a family of quantum algorithms that provide unbiased samples by preparing a state that encodes the entire Gibbs distribution. We show that this approach leads to a speedup over a classical Markov chain for several examples including the Ising model and sampling from weighted, independent sets of two different graphs. We further propose a realistic implementation of sampling from independent sets based on Rydberg atom arrays. Our approach connects computational complexity with phase transitions, providing a physical interpretation of quantum speedup, and opens the door to exploring potentially useful sampling algorithms using near-term quantum devices. | quantum physics |
It is conjectured that the exceptional-point (EP) singularity of a one-parametric quasi-Hermitian $N$ by $N$ matrix Hamiltonian $H(t)$ can play the role of a quantum phase-transition interface connecting different dynamical regimes of a unitary quantum system. Six realizations of the EP-mediated quantum phase transitions "of the third kind" are described in detail. Fairly realistic Bose-Hubbard (BH) and discrete anharmonic oscillator (AO) models of any matrix dimension $N$ are considered in the initial, intermediate, or final phase. In such a linear algebraic illustration of the changes of phase, all ingredients (and, first of all, all transition matrices) are constructed in closed, algebraic, non-numerical form. | quantum physics |
We study the $e^+ e^- \to K^+ ( D_s^{*-} D^0 + D_s^- D^{*0})$ reaction recently measured at BESIII, from where a new $Z_{cs}$ state has been reported. We study the interaction of $\bar D_s D^*$ with the coupled channels $J/\psi K^-$, $K^{*-} \eta_c$, $D_s^- D^{*0}$, $D_s^{*-} D^0$ by means of an extension to the charm sector of the local hidden gauge approach. We find that the $D_s^- D^{*0}+ D_s^{*-} D^0$ combination couples to $J/\psi K^-$ and $K^{*-} \eta_c$, but the $D_s^- D^{*0}- D_s^{*-} D^0$ combination does not. The coupled channels help to build up strength in the $D_s^- D^{*0}+ D_s^{*-} D^0$ diagonal scattering matrix close to threshold and, although the interaction is not strong enough to produce a bound state or resonance, it is sufficient to produce a large accumulation of strength at the $\bar D_s D^*$ threshold in the $e^+ e^- \to K^+ ( D_s^{*-} D^0 + D_s^- D^{*0})$ reaction in agreement with experiment. | high energy physics phenomenology |
Similarities in the chemical composition of two of the closest Milky Way satellites, namely the Large Magellanic Cloud (LMC) and the Sagittarius (Sgr) dwarf galaxy, have been proposed in the literature, suggesting similar chemical enrichment histories between the two galaxies. This proposition, however, rests on different abundance analyses, which likely introduce various systematics that hamper a fair comparison among the different data sets. In order to bypass this issue (and highlight real similarities and differences between their abundance patterns), we present a homogeneous chemical analysis of 30 giant stars in LMC, 14 giant stars in Sgr and 14 giants in the Milky Way, based on high-resolution spectra taken with the spectrograph UVES-FLAMES. The LMC and Sgr stars, in the considered metallicity range ([Fe/H]>-1.1 dex), show very similar abundance ratios for almost all the elements, with differences only in the heavy s-process elements Ba, La and Nd, suggesting a different contribution by asymptotic giant branch stars. On the other hand, the two galaxies have chemical patterns clearly different from those measured in the Galactic stars, especially for the elements produced by massive stars. This finding suggests the massive stars contributed less to the chemical enrichment of these galaxies with respect to the Milky Way. The derived abundances support similar chemical enrichment histories for the LMC and Sgr. | astrophysics |
The asymmetric quantum Rabi model (AQRM) exhibits level crossings in the eigenspectrum for the values $\epsilon\in\frac{1}{2}\mathbb{Z}$ of the bias parameter $\epsilon$. Such level crossings are expected to be associated with some hidden symmetry of the model. The origin of this hidden symmetry is established by finding the operators which commute with the AQRM hamiltonian at these special values. The construction is given explicitly for the first several cases and can be applied to other related light-matter interaction models for which similar level crossings have been observed in the presence of a bias term. | quantum physics |
We present continued radio and X-ray observations of the previously relativistic tidal disruption event (TDE) Swift J164449.3+573451 (\sw) extending to about 9.4 years post disruption, as part of ongoing campaigns with the Jansky Very Large Array (VLA) and the \textit{Chandra} X-ray observatory. We find that the X-ray emission has faded below detectable levels, with an upper limit of $\lesssim 3.5\times 10^{-15}$ erg cm$^{-2}$ s$^{-1}$ in a 100 ks observation, while the radio emission continues to be detected and steadily fade. Both are consistent with forward shock emission from a non-relativistic outflow, although we find that the radio spectral energy distribution is better fit at these late times with an electron power law index of $p\approx 3$ (as opposed to $p\approx 2.5$ at earlier times). With the revised spectral index we find $\epsilon_B\approx 0.01$ using the radio and X-ray data, and a density of $\approx 0.04$ cm$^{3}$ at a radius of $R\approx 0.65$ pc ($R_{\rm sch}\approx 2\times 10^6$ R$_\odot$) from the black hole. The energy scale of the blastwave is $\approx 10^{52}$ erg. We also report detections of \sw\ at 3 GHz from the first two epochs of the VLA Sky Survey (VLASS), and find that $\sim 10^2$ off-axis \sw-like events to $z\sim 0.5$ may be present in the VLASS data. Finally, we find that \sw\ itself will remain detectable for decades at radio frequencies, although observations at sub-GHz frequencies will become increasingly important to characterize its dynamical evolution. | astrophysics |
Heterosis is the improved or increased function of any biological quality in a hybrid offspring. We have studied yet the largest maize SNP dataset for traits prediction. We develop linear and non-linear models which consider relationships between different hybrids as well as other effect. Specially designed model proved to be efficient and robust in prediction maize's traits. | statistics |
Aseptic loosening, or loss of implant fixation, is a common complication following total joint replacement. Revision surgeries cost the healthcare system over $8 billion annually in the US. Despite the prevalence of aseptic loosening, timely and accurate detection remains a challenge because traditional imaging modalities such as plain radiographs struggle to reliably detect the early stages of implant loosening. Motivated by this challenge, we present a novel approach for in vivo monitoring and failure detection of cemented joint replacements. Poly(methyl methacrylate) (PMMA) bone cement is modified with low volume fractions of chopped carbon fiber (CF) to impart piezoresistive-based self-sensing. Electrical impedance tomography (EIT) is then used to detect and monitor load-induced deformation and fracture of CF/PMMA in a phantom tank. We therefore show that EIT indeed is able to adeptly detect loading force on a prosthetic surrogate, distinguish between increasing load magnitudes, detect failure of implant fixation, and even distinguish between cement cracking and cement de-bonding. Because EIT is a low-cost, physiologically benign, and potentially real-time imaging modality, the feasibility study herein presented has potential to transform the standard of care for post-operative monitoring of implant conditions. Beyond clinical relevance, this technique could positively impact orthopedic researchers by providing, via in vivo monitoring, insight into the factors that initiate aseptic loosening. | electrical engineering and systems science |
In this work we study the effects of New Physics (NP) operators on the inclusive $\bar{B} \to X_c \tau^- \bar{\nu}_\tau$ decay including power $(\mathcal{O}(1/m_b^2))$ corrections in the NP operators. In analogy with $R(D^{(*)})$ observables, we study the observable $R(X_c)=\frac{\mathcal{B}(\bar{B} \to X_c \tau^- \bar{\nu}_\tau)}{\mathcal{B}(\bar{B} \to X_c \ell^- \bar{\nu}_\ell)}$. We present some numerical results for $R(X_c)$ and compare the results for this observable with and without power corrections in the NP contributions. | high energy physics phenomenology |
In this paper we compare the composition fluctuations and interaction potentials of a good metallic glass former, Cu$_{50}$Zr$_{50}$, and a poor glass former, Ni$_{50}$Al$_{50}$. The Bhatia-Thornton correlations functions are calculated. Inspired by the observation of chemical ordering at the NiAl surface, we derive a new property, R$_{cn}$( q ), corresponding to linear susceptibility of concentration to a perturbation in density. We present a direct comparison of the potentials for the two model alloys, using a 2nd order density expansion, establish that the one body energy plays a crucial role in stabilizing the crystal relative to the liquid in both alloys but that the three body contribution to the heat of fusion is significantly larger in NiAl that CuZr. | condensed matter |
This paper focuses on a new task, i.e., transplanting a category-and-task-specific neural network to a generic, modular network without strong supervision. We design a functionally interpretable structure for the generic network. Like building LEGO blocks, we teach the generic network a new category by directly transplanting the module corresponding to the category from a pre-trained network with a few or even without sample annotations. Our method incrementally adds new categories to the generic network but does not affect representations of existing categories. In this way, our method breaks the typical bottleneck of learning a net for massive tasks and categories, i.e., the requirement of collecting samples for all tasks and categories at the same time before the learning begins. Thus, we use a new distillation algorithm, namely back-distillation, to overcome specific challenges of network transplanting. Our method without training samples even outperformed the baseline with 100 training samples. | computer science |
We prove global well-posedness of the initial value problem for a class of variational quasilinear wave equations, in one spatial dimension, with initial data that is not-necessarily small. Key to our argument is a form of quasilinear null condition (a "nilpotent structure") that persists for our class of equations even in the large data setting. This in particular allows us to prove global well-posedness for $C^2$ initial data of moderate decrease, provided the data is sufficiently close to that which generates a simple traveling wave. We take here a geometric approach inspired by works in mathematical relativity and recent works on shock formation for fluid systems. First we recast the equations of motion in terms of a dynamical double-null coordinate system; we show that this formulation semilinearizes our system and decouples the wave variables from the null structure equations. After solving for the wave variables in the double-null coordinate system, we next analyze the null structure equations, using the wave variables as input, to show that the dynamical coordinates are $C^1$ regular and covers the entire space-time. | mathematics |
Using X-ray constrained beta-models for the radial distribution of gas in the outskirts of galaxies, we analyze the termination of galactic winds and the formation and evolution of halo clouds by thermal instability. At low mass-loss rates, galactic winds are trapped within the halo, but they burst into the intergalactic medium during intermittent strong outflows with (dM/dt)_w > 10 M_sun/yr. We develop analytic models of halo clouds as they cool radiatively over condensation time scales t_c = (390 Myr)(T_6 /n_{-4}) (Z/Z_sun)^-1 for hydrogen number densities n_H = (10^{-4} cm^{-3}) n_{-4}, gas temperatures T = (10^6 K)T_6, and metallicities (Z/Z_sun). Halo gas can form kpc-scale clouds out to galactocentric distances r = 30-65 kpc, where efficient radiative cooling from 10^6 K down to 10^4 K occurs at Z > 0.3 Z_sun on timescales less than 1 Gyr. After condensing to column densities N_H > 3.5x10^{16} cm^{-2}, these clouds lose hydrostatic pressure support and fall inward on dynamical time scales of 200 Myr. Our baseline analysis will be followed by numerical calculations to understand the governing principles of halo cloud formation and transport of gas to the galactic disk. | astrophysics |
For a function $f$ from $\mathbb{F}_2^n$ to $\mathbb{F}_2^n$, the planarity of $f$ is usually measured by its differential uniformity and differential spectrum. In this paper, we propose the concept of vanishing flats, which supplies a combinatorial viewpoint on the planarity. First, the number of vanishing flats of $f$ can be regarded as a measure of the distance between $f$ and the set of almost perfect nonlinear functions. In some cases, the number of vanishing flats serves as an "intermediate" concept between differential uniformity and differential spectrum, which contains more information than differential uniformity, however less than the differential spectrum. Secondly, the set of vanishing flats forms a combinatorial configuration called partial quadruple system, since it convey detailed structural information about $f$. We initiate this study by considering the number of vanishing flats and the partial quadruple systems associated with monomials and Dembowski-Ostrom polynomials. In addition, we present an application of vanishing flats to the partition of a vector space into disjoint equidimensional affine spaces. We conclude the paper with several further questions and challenges. | computer science |
We use the method of spectral networks to calculate BPS degeneracies in the Minahan-Nemeschansky $E_7$ theory, as representations of the $E_7$ flavor symmetry. Our results provide another example of a pattern noticed earlier in the Minahan-Nemeschansky $E_6$ theory: when the electromagnetic charge is $n$ times a primitive charge, the BPS index is a positive integer multiple of $(-1)^{n+1} n$. We also calculate BPS degeneracies in the Minahan-Nemeschansky $E_6$ theory for larger charges than were previously computed. | high energy physics theory |
Atom-dimer exchange and dissociation reaction rates are predicted for different combinations of two $^4$He atoms and one of the alkaline species among $^{6}$Li, $^{7}$Li and $^{23}$Na, by using three-body scattering formalism with short-range two-body interactions. Our study was concerned with low-energy reaction rates in which the $s-$, $p-$ and $d-$ wave contributions are the relevant ones. The $^4$He is chosen as one of the atoms in the binary mixture, in view of previous available investigations and laboratory accessibilities. Focusing on possible experimental cold-atom realizations with two-atomic mixtures, in which information on atom-dimer reaction rates can be extracted, we predict the occurrence of a dip in the elastic reaction rate for colliding energies smaller than 20 mK, when the dimer is the $^4$He$^{23}$Na molecule. We are also anticipating a zero in the elastic $p-$wave contribution for the $^4$He + $^4$He$^7$Li and $^4$He + $^4$He$^{23}$Na reaction processes. With weakly-bound molecules reacting with atoms at very low colliding energies, we interpret our results on the light of Efimov physics which supports model independence and robustness of our predictions. Specific sensitivities on the effective range were evidenced, highlighted by the particular inversion role of the $p-$ and $d-$waves in the atom exchange and dissociation processes. | physics |
We provide a sufficient condition for the monogamy inequality of multi-party quantum entanglement of arbitrary dimensions in terms of entanglement of formation. Based on the classical-classical-quantum(ccq) states whose quantum parts are obtained from the two-party reduced density matrices of a three-party quantum state, we show the additivity of the mutual information of the ccq states guarantees the monogamy inequality of the three-party pure state in terms of EoF. After illustrating the result with some examples, we generalize our result of three-party systems into any multi-party systems of arbitrary dimensions. | quantum physics |
Using duality in optimization theory we formulate a dual approach to the S-matrix bootstrap that provides rigorous bounds to 2D QFT observables as a consequence of unitarity, crossing symmetry and analyticity of the scattering matrix. We then explain how to optimize such bounds numerically, and prove that they provide the same bounds obtained from the usual primal formulation of the S-matrix Bootstrap, at least once convergence is attained from both perspectives. These techniques are then applied to the study of a gapped system with two stable particles of different masses, which serves as a toy model for bootstrapping popular physical systems. | high energy physics theory |
The NANOGrav pulsar timing array experiment reported evidence for a stochastic common-spectrum process affecting pulsar timing residuals in its 12.5-year dataset, which might be interpreted as the first detection of a stochastic gravitational wave background (SGWB). I examine whether the NANOGrav signal might be explained by an inflationary SGWB, focusing on the implications for the tensor spectral index $n_T$ and the tensor-to-scalar ratio $r$. Explaining NANOGrav while complying with upper limits on $r$ from BICEP2/Keck Array and Planck requires $r \gtrsim {\cal O}(10^{-6})$ in conjunction with an extremely blue tensor spectrum, $0.7 \lesssim n_T \lesssim 1.3$. After discussing models which can realize such a blue spectrum, I show that this region of parameter space can be brought in agreement with Big Bang Nucleosynthesis constraints for a sufficiently low reheating scale, $T_{\rm rh} \lesssim 100\,{\rm GeV}-1\,{\rm TeV}$. With the important caveat of having assumed a power-law parametrization for the primordial tensor spectrum, an inflationary interpretation of the NANOGrav signal is therefore not excluded. | astrophysics |
Globally increasing migration pressures call for new modelling approaches in order to design effective policies. It is important to have not only efficient models to predict migration flows but also to understand how specific parameters influence these flows. In this paper, we propose an artificial neural network (ANN) to model international migration. Moreover, we use a technique for interpreting machine learning models, namely Partial Dependence Plots (PDP), to show that one can well study the effects of drivers behind international migration. We train and evaluate the model on a dataset containing annual international bilateral migration from $1960$ to $2010$ from $175$ origin countries to $33$ mainly OECD destinations, along with the main determinants as identified in the migration literature. The experiments carried out confirm that: 1) the ANN model is more efficient w.r.t. a traditional model, and 2) using PDP we are able to gain additional insights on the specific effects of the migration drivers. This approach provides much more information than only using the feature importance information used in previous works. | physics |
In this paper, we present detailed studies on the feasibility at $pp$, $e^-p$ and $e^+e^-$ colliders for model-independent sensitivity estimates on the total cross-section and on the anomalous $\tau^+\tau^-\gamma$ interaction through the tau pair production channels $pp \to p\tau\bar \tau \gamma p$, $e^-p \to e^- \tau\bar \tau \gamma p$ and $e^+e^- \to e^+ \tau\bar \tau \gamma e^-$ at the $\gamma^*\gamma^* \to \tau^+\tau^-\gamma$ mode. Measurements of the anomalous couplings of the $\tau$-lepton $\tilde{a}_\tau$ and $\tilde{d}_\tau$ provide an excellent opportunity to probing extensions of the Standard Model. We estimate the sensitivity at the $95\%$ Confidence Level, and we consider that the $\tau$-lepton decays leptonically or semi-leptonically. We found that of the three considered colliders, the future CLIC at high energy and high luminosity should provide the best sensitivity on the dipole moments of the $\tau$-lepton $\tilde a_\tau= [-0.00128, 0.00105]$ and $ |\tilde{d}_\tau({\rm ecm})|= 6.4394\times 10^{-18}$, which show a potential advantage compared to those from LHC and FCC-he. | high energy physics phenomenology |
We develop a multipolar theory of second-harmonic generation (SHG) by dielectric nanoparticles made of noncentrosymmetric materials with bulk quadratic nonlinearity. We specifically analyze two regimes of optical excitation: illumination by a plane wave and single-mode excitation, when the laser pump drives the magnetic dipole mode only. Considering two classes of nonlinear crystalline solids (dielectric perovskite material and III-V semiconductor), we apply a symmetry approach to derive selection rules for the multipolar composition of the nonlinear radiation. The developed description can be used for design of efficient nonlinear optical nanoantennas with reconfigurable radiation characteristics. | physics |
A tree tensor network is proposed for the entanglement distillation of large N SU(N)1 Chern-Simons theory and Riemann surfaces, adopting a proposal of Bao, et al. This is illustrated for the entanglement entropy S(A) of a bipartite many-body system A, where here S(A) = log N. | high energy physics theory |
Building upon the worldline effective field theory (EFT) formalism for spinning bodies developed for the Post-Newtonian regime, we generalize the EFT approach to Post-Minkowskian (PM) dynamics to include rotational degrees of freedom in a manifestly covariant framework. We introduce a systematic procedure to compute the total change in momentum and spin in the gravitational scattering of compact objects. For the special case of spins aligned with the orbital angular momentum, we show how to construct the radial action for elliptic-like orbits using the Boundary-to-Bound correspondence. As a paradigmatic example, we solve the scattering problem to next-to-leading PM order with linear and bilinear spin effects and arbitrary initial conditions, incorporating for the first time finite-size corrections. We obtain the aligned-spin radial action from the resulting scattering data, and derive the periastron advance and binding energy for circular orbits. We also provide the (square of the) center-of-mass momentum to ${\cal O}(G^2)$, which may be used to reconstruct a Hamiltonian. Our results are in perfect agreement with the existent literature, while at the same time extend the knowledge of the PM dynamics of compact binaries at quadratic order in spins. | high energy physics theory |
Off-shell Ward identities in non-abelian gauge theory continue to be a subject of active research, since they are, in general, inhomogeneous and their form depends on the chosen gauge-fixing procedure. For the three-gluon and four-gluon vertices, it is known that a relatively simple form of the Ward identity can be achieved using the pinch technique or, equivalently, the background-field method with quantum Feynman gauge. The latter is also the gauge-fixing underlying the string-inspired formalism, and here we use this formalism to derive the corresponding form of the Ward identity for the one-loop N - gluon amplitudes. | high energy physics theory |
We propose a novel approach to reconstruct RGB-D indoor scene based on plane primitives. Our approach takes as input a RGB-D sequence and a dense coarse mesh reconstructed from it, and generates a lightweight, low-polygonal mesh with clear face textures and sharp features without losing geometry details from the original scene. Compared to existing methods which only cover large planar regions in the scene, our method builds the entire scene by adaptive planes without losing geometry details and also preserves sharp features in the mesh. Experiments show that our method is more efficient to generate textured mesh from RGB-D data than state-of-the-arts. | computer science |
We present the NNLO calculation for single-inclusive jet production in polarized DIS $\vec{e}\vec{p} \rightarrow {\rm jet} +X$. We perform the computation based on the Projection-to-Born method by combining our recent NLO result for di-jet production in polarized DIS along with the NNLO coefficients for the inclusive cross section. In this way, we achieve NNLO accuracy in a fully exclusive way for single-jet observables, the first time for a polarized cross section. We study the perturbative stability and phenomenological consequences of the QCD corrections for Electron Ion Collider kinematics. | high energy physics phenomenology |
Unitarity cut method has been proved to be very useful in the computation of one-loop integrals. In this paper, we generalize the method to the situation where the powers of propagators in the denominator are larger than one in general. We show how to use the trick of differentiation over masses to translate the problem to the integrals where all powers are just one. Then by using the unitarity cut method, we can find the wanted reduction coefficients of all basis except the tadpole. Using this method, we calculate the reduction of scalar bubble, scalar triangle, scalar box and scalar pentagon with general power of propagators. | high energy physics theory |
Let $\mathcal{E}$ be a weakly idempotent complete exact category with enough injective and projective objects. Assume that $\mathcal{M} \subseteq \mathcal{E}$ is a rigid, contravariantly finite subcategory of $\mathcal{E}$ containing all the injective and projective objects, and stable under taking direct sums and summands. In this paper, $\mathcal{E}$ is equipped with the structure of a prefibration category with cofibrant replacements. As a corollary, we show, using the results of Demonet and Liu in \cite{DL}, that the category of finite presentation modules on the costable category $\overline{\mathcal{M}}$ is a localization of $\mathcal{E}$. We also deduce that $\mathcal{E} \to \mathrm{mod}\overline{\mathcal{M}}$ admits a calculus of fractions up to homotopy. These two corollaries are analogues for exact categories of results of Buan and Marsh in \cite{BM2}, \cite{BM1} (see also \cite{Be}) that hold for triangulated categories. If $\mathcal{E}$ is a Frobenius exact category, we enhance its structure of prefibration category to the structure of a model category (see the article of Palu in \cite{Palu} for the case of triangulated categories). This last result applies in particular when $\mathcal{E}$ is any of the Hom-finite Frobenius categories appearing in relation to cluster algebras. | mathematics |
In humans, Attention is a core property of all perceptual and cognitive operations. Given our limited ability to process competing sources, attention mechanisms select, modulate, and focus on the information most relevant to behavior. For decades, concepts and functions of attention have been studied in philosophy, psychology, neuroscience, and computing. For the last six years, this property has been widely explored in deep neural networks. Currently, the state-of-the-art in Deep Learning is represented by neural attention models in several application domains. This survey provides a comprehensive overview and analysis of developments in neural attention models. We systematically reviewed hundreds of architectures in the area, identifying and discussing those in which attention has shown a significant impact. We also developed and made public an automated methodology to facilitate the development of reviews in the area. By critically analyzing 650 works, we describe the primary uses of attention in convolutional, recurrent networks and generative models, identifying common subgroups of uses and applications. Furthermore, we describe the impact of attention in different application domains and their impact on neural networks' interpretability. Finally, we list possible trends and opportunities for further research, hoping that this review will provide a succinct overview of the main attentional models in the area and guide researchers in developing future approaches that will drive further improvements. | computer science |
Using the platform of a trapped-atom clock on a chip, we have generated spin-squeezed states with up to 8.1(9) dB of metrological squeezing in a cloud of $2\times 10^4$ ultracold alkali atoms by quantum nondemolition (QND) measurement in a fiber Fabry-Perot microcavity. Observing the time evolution of the squeezed state on unprecedented timescales of more than one second reveals a surprising measurement amplification effect in the final measurement of the spin state. It results from a subtle interplay between the spin dynamics of interacting indistinguishable particles and energy-dependent cavity coupling and leads to an increased cavity shift per spin, and thus to a higher signal per photon read out. Metrological spin squeezing is preserved for 1 s. Both results open up encouraging perspectives for squeezing-enhanced atomic clocks in a metrologically relevant stability regime. | quantum physics |
In many practical tasks it is needed to estimate an effect of treatment on individual level. For example, in medicine it is essential to determine the patients that would benefit from a certain medicament. In marketing, knowing the persons that are likely to buy a new product would reduce the amount of spam. In this chapter, we review the methods to estimate an individual treatment effect from a randomized trial, i.e., an experiment when a part of individuals receives a new treatment, while the others do not. Finally, it is shown that new efficient methods are needed in this domain. | statistics |
This letter studies an unmanned aerial vehicle-enabled wireless power transfer system within a radio-map-based robust positioning design. | electrical engineering and systems science |
This review article summarizes the requirement of low temperature conditions in existing experimental approaches to quantum computation and quantum simulation. | quantum physics |
We consider a robust version of multiple-set linear canonical analysis obtained by using a S-estimator of covariance operator. The related influence functions are derived. Asymptotic properties of this robust method are obtained and a robust test for mutual non-correlation is introduced. | mathematics |
Most proof-of-principle experiments for spin qubits have been performed using GaAs-based quantum dots because of the excellent control they offer over tunneling barriers and the orbital and spin degrees of freedom. Here, we present the first realization of high-quality single and double quantum dots hosted in an InAs two-dimensional electron gas (2DEG), demonstrating accurate control down to the few-electron regime, where we observe a clear Kondo effect and singlet-triplet spin blockade. We measure an electronic $g$-factor of $16$ and a typical magnitude of the random hyperfine fields on the dots of $\sim 0.6\, \mathrm{mT}$. We estimate the spin-orbit length in the system to be $\sim 5-10\, \mu \mathrm{m}$, which is almost two orders of magnitude longer than typically measured in InAs nanostructures, achieved by a very symmetric design of the quantum well. These favorable properties put the InAs 2DEG on the map as a compelling host for studying fundamental aspects of spin qubits. Furthermore, having weak spin-orbit coupling in a material with a large Rashba coefficient potentially opens up avenues for engineering structures with spin-orbit coupling that can be controlled locally in space and/or time. | condensed matter |
We present a systematic numerical relativity study of the mass ejection and the associated electromagnetic transients and nucleosynthesis from binary neutron star (NS) mergers. We find that a few $10^{-3}\, M_\odot$ of material are ejected dynamically during the mergers. The amount and the properties of these outflow depend on binary parameters and on the NS equation of state (EOS). A small fraction of these ejecta, typically ${\sim}10^{-6}\, M_\odot$, is accelerated by shocks formed shortly after merger to velocities larger than $0.6\, {\rm c}$ and produces bright radio flares on timescales of weeks, months, or years after merger. Their observation could constrain the strength with which the NSs bounce after merger and, consequently, the EOS of matter at extreme densities. The dynamical ejecta robustly produce second and third $r$-process peak nuclei with relative isotopic abundances close to solar. The production of light $r$-process elements is instead sensitive to the binary mass ratio and the neutrino radiation treatment. Accretion disks of up to ${\sim}0.2\, M_\odot$ are formed after merger, depending on the lifetime of the remnant. In most cases, neutrino- and viscously-driven winds from these disks dominate the overall outflow. Finally, we generate synthetic kilonova light curves and find that kilonovae depend on the merger outcome and could be used to constrain the NS EOS. | astrophysics |
This work presents a unified dissipaton-equation-of-motion (DEOM) theory and its evaluations on the Helmholtz free energy change due to the isotherm mixing of two isolated subsystems. One is a local impurity and another is a nonlocal Gaussian bath. DEOM constitutes a fundamental theory for such open quantum mixtures. To complete the theory, we construct also the imaginary-time DEOM formalism via an analytical continuation of dissipaton algebra, which would be limited to equilibrium thermodynamics. On the other hand, the real-time DEOM deals with both equilibrium structural and nonequilibrium dynamic properties. Its combination with the thermodynamic integral formalism would be a viable and accurate means to both equilibrium and transient thermodynamics. As illustrations, we report the numerical results on a spin--boson system, with elaborations on the underlying anharmonic features, the thermodynamic entropy versus the von Neumann entropy, and an indication of "solvent-cage" formation. Beside the required asymptotic equilibrium properties, the proposed transient thermodynamics also supports the basic spontaneity criterion. | condensed matter |
Deep learning techniques are increasingly being considered for geological applications where -- much like in computer vision -- the challenges are characterized by high-dimensional spatial data dominated by multipoint statistics. In particular, a novel technique called generative adversarial networks has been recently studied for geological parametrization and synthesis, obtaining very impressive results that are at least qualitatively competitive with previous methods. The method obtains a neural network parametrization of the geology -- so-called a generator -- that is capable of reproducing very complex geological patterns with dimensionality reduction of several orders of magnitude. Subsequent works have addressed the conditioning task, i.e. using the generator to generate realizations honoring spatial observations (hard data). The current approaches, however, do not provide a parametrization of the conditional generation process. In this work, we propose a method to obtain a parametrization for direct generation of conditional realizations. The main idea is to simply extend the existing generator network by stacking a second inference network that learns to perform the conditioning. This inference network is a neural network trained to sample a posterior distribution derived using a Bayesian formulation of the conditioning task. The resulting extended neural network thus provides the conditional parametrization. Our method is assessed on a benchmark image of binary channelized subsurface, obtaining very promising results for a wide variety of conditioning configurations. | statistics |
The SU(3)--invariant sector of maximal supergravity in four dimensions with an SO(8) gauging is uplifted to $D=11$ supergravity. In order to do this, the SU(3)--neutral sector of the tensor and duality hierarchies of the $D=4$ ${\cal N}=8$ supergravity is first worked out. The consistent $D=11$ embedding of the full, dynamical SU(3) sector is then expressed at the level of the $D=11$ metric and three-form gauge field in terms of these $D=4$ tensors. The redundancies introduced by this approach are eliminated at the level of the $D=11$ four-form field strength by making use of the $D=4$ duality hierarchy. Our results encompass previously known truncations of $D=11$ supergravity down to sectors of SO(8) supergravity with symmetry larger than SU(3), and include new ones. In particular, we obtain a new consistent truncation of $D=11$ supergravity to minimal $D=4$ ${\cal N}=2$ gauged supergravity. | high energy physics theory |
Spectral analysis of electron spin resonance (ESR) is a powerful technique for various investigations including characterization of spin systems, measurements of spin concentration, and probing spin dynamics. The nitrogen-vacancy (NV) center in diamond is a promising magnetic sensor enabling improvement of ESR sensitivity to the level of a single spin. Therefore, understanding the nature of NV-detected ESR (NV-ESR) spectrum is critical for applications to nanoscale ESR. Within this work we investigate the linewidth of NV-ESR from single substitutional nitrogen centers (called P1 centers). NV-ESR is detected by a double electron-electron resonance (DEER) technique. By studying the dependence of the DEER excitation bandwidth on NV-ESR linewidth, we find that the spectral resolution is improved significantly and eventually limited by inhomogeneous broadening of the detected P1 ESR. Moreover, we show that the NV-ESR linewidth can be as narrow as 0.3 MHz. | condensed matter |
We introduce a new technique to estimate the comet nuclear size frequency distribution (SFD) that combines a cometary activity model with a survey simulation and apply it to 150 long period comets (LPC) detected by the Pan-STARRS1 near-Earth object survey. The debiased LPC size-frequency distribution is in agreement with previous estimates for large comets with nuclear diameter $>\sim 1$~km but we measure a significant drop in the SFD slope for small objects with diameters $<1$~km and approaching only $100$~m diameter. Large objects have a slope $\alpha_{big} = 0.72 \pm 0.09 (stat.) \pm 0.15 (sys.)$ while small objects behave as $\alpha_{small} = 0.07 \pm 0.03 (stat.) \pm 0.09 (sys.)$ where the SFD is $\propto 10^{\alpha H_N}$ and $H_N$ represents the cometary nuclear absolute magnitude. The total number of LPCs that are $>1$~km diameter and have perihelia $q<10$~au is $0.46 \pm 0.15 \times 10^9$ while there are only $2.4 \pm 0.5 (stat.) \pm 2 (sys.) \times 10^9$ objects with diameters $>100$~m due to the shallow slope of the SFD for diameters $<1$~m. We estimate that the total number of `potentially active' objects with diameters $\ge 1$~km in the Oort cloud, objects that would be defined as LPCs if their perihelia evolved to $<10$~au, is $(1.5\pm1)\times10^{12}$ with a combined mass of $1.3\pm0.9 \, M_{Earth}$. The debiased LPC orbit distribution is broadly in agreement with expectations from contemporary dynamical models but there are discrepancies that could point towards a future ability to disentangle the relative importance of stellar perturbations and galactic tides in producing the LPC population. | astrophysics |
We augment linear Support Vector Machine (SVM) classifiers by adding three important features: (i) we introduce a regularization constraint to induce a sparse classifier; (ii) we devise a method that partitions the positive class into clusters and selects a sparse SVM classifier for each cluster; and (iii) we develop a method to optimize the values of controllable variables in order to reduce the number of data points which are predicted to have an undesirable outcome, which, in our setting, coincides with being in the positive class. The latter feature leads to personalized prescriptions/recommendations. We apply our methods to the problem of predicting and preventing hospital readmissions within 30-days from discharge for patients that underwent a general surgical procedure. To that end, we leverage a large dataset containing over 2.28 million patients who had surgeries in the period 2011--2014 in the U.S. The dataset has been collected as part of the American College of Surgeons National Surgical Quality Improvement Program (NSQIP). | statistics |
The applicability of Doppler radar for gait analysis is investigated by quantitatively comparing the measured biomechanical parameters to those obtained using motion capturing and ground reaction forces. Nineteen individuals walked on a treadmill at two different speeds, where a radar system was positioned in front of or behind the subject. The right knee angle was confined by an adjustable orthosis in five different degrees. Eleven gait parameters are extracted from radar micro-Doppler signatures. Here, new methods for obtaining the velocities of individual lower limb joints are proposed. Further, a new method to extract individual leg flight times from radar data is introduced. Based on radar data, five spatiotemporal parameters related to rhythm and pace could reliably be extracted. Further, for most of the considered conditions, three kinematic parameters could accurately be measured. The radar-based stance and flight time measurements rely on the correct detection of the time instant of maximal knee velocity during the gait cycle. This time instant is reliably detected when the radar has a back view, but is underestimated when the radar is positioned in front of the subject. The results validate the applicability of Doppler radar to accurately measure a variety of medically relevant gait parameters. Radar has the potential to unobtrusively diagnose changes in gait, e.g., to design training in prevention and rehabilitation. As contact-less and privacy-preserving sensor, radar presents a viable technology to supplement existing gait analysis tools for long-term in-home examinations. | electrical engineering and systems science |
We present an examination of the First Ionization Potential (FIP) fractionation scenario invoking the ponderomotive force in the chromosphere, and its implications for the source(s) of slow speed solar winds by using observations from The Advanced Composition Explorer (ACE). Following a recent conjecture that the abundance enhancements of intermediate FIP elements, S, P, and C, in slow solar winds can be explained by the release of plasma fractionated on open fields, though from regions of stronger magnetic field than usually associated with fast solar wind source regions, we identify a period in 2008 containing four solar rotation cycles that show repeated pattern of sulfur abundance enhancement corresponding to a decrease in solar wind speed. We identify the source regions of these slow winds in global magnetic field models and find that they lie at the boundaries between a coronal hole and its adjacent active region, with origins in both closed and open initial field configurations. Based on magnetic field extrapolations, we model the fractionation and compare our results with element abundances measured by ACE to estimate the solar wind contributions from open and closed field, and to highlight potentially useful directions for further work. | astrophysics |
Classification may not be reliable for several reasons: noise in the data, insufficient input information, overlapping distributions and sharp definition of classes. Faced with several possibilities neural network may in such cases still be useful if instead of a classification elimination of improbable classes is done. Eliminators may be constructed using classifiers assigning new cases to a pool of several classes instead of just one winning class. Elimination may be done with the help of several classifiers using modified error functions. A real life medical application of neural network is presented illustrating the usefulness of elimination. | computer science |
We study the effects of including Yukawa-like dimension-5 operators in the Georgi-Machacek model where the Standard Model is augmented with triplet scalars. We focus only on the charged Higgs sector and investigate the constraints arising from radiative B-meson decays, neutral B-meson mixing and precision measurement of Zbb vertex. We observe that the inclusion of the dimension-5 operators causes substantial alteration of the limits on the charged Higgs masses and the vacuum expectation value of the triplets, derived otherwise using only the dimension-4 operators. | high energy physics phenomenology |
We introduce a new metric of match, called Cartesian tree matching, which means that two strings match if they have the same Cartesian trees. Based on Cartesian tree matching, we define single pattern matching for a text of length n and a pattern of length m, and multiple pattern matching for a text of length n and k patterns of total length m. We present an O(n+m) time algorithm for single pattern matching, and an O((n+m) log k) deterministic time or O(n+m) randomized time algorithm for multiple pattern matching. We also define an index data structure called Cartesian suffix tree, and present an O(n) randomized time algorithm to build the Cartesian suffix tree. Our efficient algorithms for Cartesian tree matching use a representation of the Cartesian tree, called the parent-distance representation. | computer science |
We investigate the asymptotic structure of the free Rarita-Schwinger theory in four spacetime dimensions at spatial infinity in the Hamiltonian formalism. We impose boundary conditions for the spin-3/2 field that are invariant under an infinite-dimensional (abelian) algebra of non-trivial asymptotic fermionic symmetries. The compatibility of this set of boundary conditions with the invariance of the theory under Lorentz boosts requires the introduction of boundary degrees of freedom in the Hamiltonian action, along the lines of electromagnetism. These boundary degrees of freedom modify the symplectic structure by a surface contribution appearing in addition to the standard bulk piece. The Poincar\'e transformations have then well-defined (integrable, finite) canonical generators. Moreover, improper fermionic gauge symmetries, which are also well-defined canonical transformations, are further enlarged and turn out to be parametrized by two independent angle-dependent spinor functions at infinity, which lead to an infinite-dimensional fermionic algebra endowed with a central charge. We extend next the analysis to the supersymmetric spin-$(1,3/2)$ and spin-$(2,3/2)$ multiplets. First, we present the canonical realization of the super-Poincar\'e algebra on the spin-$(1,3/2)$ multiplet, which is shown to be consistently enhanced by the infinite-dimensional abelian algebra of angle-dependent bosonic and fermionic improper gauge symmetries associated with the electromagnetic and the Rarita-Schwinger fields, respectively. A similar analysis of the spin-$(2,3/2)$ multiplet is then carried out to obtain the canonical realization of the super-Poincar\'e algebra, consistently enhanced by the abelian improper bosonic gauge transformations of the spin-$2$ field (BMS supertranslations) and the abelian improper fermionic gauge transformations of the spin-$3/2$ field. | high energy physics theory |
We consider the Wilson line networks of the Chern-Simons $3d$ gravity theory with toroidal boundary conditions which calculate global conformal blocks of degenerate quasi-primary operators in torus $2d$ CFT. After general discussion that summarizes and further extends results known in the literature we explicitly obtain the one-point torus block and two-point torus blocks through particular matrix elements of toroidal Wilson network operators in irreducible finite-dimensional representations of $sl(2,\mathbb{R})$ algebra. The resulting expressions are given in two alternative forms using different ways to treat multiple tensor products of $sl(2,\mathbb{R})$ representations: (1) $3mj$ Wigner symbols and intertwiners of higher valence, (2) totally symmetric tensor products of the fundamental $sl(2,\mathbb{R})$ representation. | high energy physics theory |
We study the effect of tidal forcing on gravitational wave signals from tidally relaxed white dwarf pairs in the LISA, DECIGO and BBO frequency band ($0.1-100\,{\rm mHz}$). We show that for stars not in hydrostatic equilibrium (in their own rotating frames), tidal forcing will result in energy and angular momentum exchange between the orbit and the stars, thereby deforming the orbit and producing gravitational wave power in harmonics not excited in perfectly circular synchronous binaries. This effect is not present in the usual orbit-averaged treatment of the equilibrium tide, and is analogous to transit timing variations in multiplanet systems. It should be present for all LISA white dwarf pairs since gravitational waves carry away angular momentum faster than tidal torques can act to synchronize the spins, and when mass transfer occurs as it does for at least eight LISA verification binaries. With the strain amplitudes of the excited harmonics depending directly on the density profiles of the stars, gravitational wave astronomy offers the possibility of studying the internal structure of white dwarfs, complimenting information obtained from asteroseismology of pulsating white dwarfs. Since the vast majority of white-dwarf pairs in this frequency band are expected to be in the quasi-circular state, we focus here on these binaries, providing general analytic expressions for the dependence of the induced eccentricity and strain amplitudes on the stellar apsidal motion constants and their radius and mass ratios. Tidal dissipation and gravitation wave damping will affect the results presented here and will be considered elsewhere. | astrophysics |
We revisit the sensitivity to non-resonant, heavy Majorana neutrinos $N$ in same-sign $W^\pm W^\pm$ scattering at the $\sqrt{s}=13$ TeV LHC and its high-luminosity upgrade. As a benchmark scenario, we work in the context of the Phenomenological Type I Seesaw model, relying on a simulation up to next-to-leading order in QCD with parton shower matching. After extensively studying the phenomenology of the $pp\to\mu^\pm\mu^\pm j j$ process at the amplitude and differential levels, we design a simple collider analysis with remarkable signal-background separation power. At 95\% confidence level we find that the squared muon-heavy neutrino mixing element $\vert V_{\mu N} \vert^{2}$ can be probed down to about $0.06-0.3 ~ (0.03-0.1)$ for $m_N = 1-10~{\rm TeV}$ with $\mathcal{L}=300$ fb$^{-1}~(3$ ab$^{-1})$. For heavier masses of $m_N = 20~{\rm TeV}$, we report sensitivity for $\vert V_{\mu N} \vert^{2}\gtrsim 0.5~(0.3)$. The $W^\pm W^\pm$ scattering channel can greatly extend the mass range covered by current LHC searches for heavy Majorana neutrinos and particularly adds invaluable sensitivity above a few hundred GeV. We comment on areas where the analysis can be improved as well as on the applicability to other tests of neutrino mass models. | high energy physics phenomenology |
GW170817 was the first ever joint detection of gravitational waves (GW) from a binary neutron star (BNS) merger with the detections of short $\gamma$-ray burst (SGRB) counterparts. Analysis of the multi-band afterglow observations of over more than a year revealed that the outflow from the merger end-product was consistent with structured relativistic jet models with the core of the jet narrowly collimated to half opening angles $\sim5$ deg. In this work, assuming all the BNS mergers produce Gaussian structured jets with properties as inferred for GW170817, we explore the prospects of joint detections of BNS mergers and prompt $\gamma-$ray emission, expected during the current and upcoming upgrades of LIGO-Virgo-KAGRA detectors. We discuss three specific observational aspects: 1) the distribution of detected binary inclination angles 2) the distance reach and 3) the detection rates. Unlike GW-only detections, the joint detections are greatly restricted at large inclination angles, due to the structure of the jets. We find that at lower inclination angles (say below 20 deg), the distance reach as well as the detection rates of the joint detections are limited by GW detectability while at larger inclinations (say above 20 deg), they are limited by the $\gamma$-ray detectability. | astrophysics |
A graph G is (a:b)-colorable if there exists an assignment of b-element subsets of {1,...,a} to vertices of G such that sets assigned to adjacent vertices are disjoint. We show that every planar graph without cycles of length 4 or 5 is (11:3)-colorable, a weakening of recently disproved Steinberg's conjecture. In particular, each such graph with n vertices has an independent set of size at least 3n/11. | mathematics |
Given an incomplete image without additional constraint, image inpainting natively allows for multiple solutions as long as they appear plausible. Recently, multiplesolution inpainting methods have been proposed and shown the potential of generating diverse results. However, these methods have difficulty in ensuring the quality of each solution, e.g. they produce distorted structure and/or blurry texture. We propose a two-stage model for diverse inpainting, where the first stage generates multiple coarse results each of which has a different structure, and the second stage refines each coarse result separately by augmenting texture. The proposed model is inspired by the hierarchical vector quantized variational auto-encoder (VQ-VAE), whose hierarchical architecture isentangles structural and textural information. In addition, the vector quantization in VQVAE enables autoregressive modeling of the discrete distribution over the structural information. Sampling from the distribution can easily generate diverse and high-quality structures, making up the first stage of our model. In the second stage, we propose a structural attention module inside the texture generation network, where the module utilizes the structural information to capture distant correlations. We further reuse the VQ-VAE to calculate two feature losses, which help improve structure coherence and texture realism, respectively. Experimental results on CelebA-HQ, Places2, and ImageNet datasets show that our method not only enhances the diversity of the inpainting solutions but also improves the visual quality of the generated multiple images. Code and models are available at: https://github.com/USTC-JialunPeng/Diverse-Structure-Inpainting. | computer science |
Using a combinatorial bijection with certain abaci diagrams, Nath and Sellers have enumerated $(s, m s \pm 1)$-core partitions into distinct parts. We generalize their result in several directions by including the number of parts of these partitions, by considering $d$-distinct partitions, and by allowing more general $(s, m s \pm r)$-core partitions. As an application of our approach, we obtain the average and maximum number of parts of these core partitions. | mathematics |
The Linac Coherent Light Source changes configurations multiple times per day, necessitating fast tuning strategies to reduce setup time for successive experiments. To this end, we employ a Bayesian approach to transport optics tuning to optimize groups of quadrupole magnets. We use a Gaussian process to provide a probabilistic model of the machine response with respect to control parameters from a modest number of samples. Subsequent samples are selected during optimization using a statistical test combining the model prediction and uncertainty. The model parameters are fit from archived scans, and correlations between devices are added from a simple beam transport model. The result is a sample-efficient optimization routine, which we show significantly outperforms existing optimizers. | physics |
In this work, we present an in-depth and systematic analysis using tools such as local interpretable model-agnostic explanations (LIME) (arXiv:1602.04938) and divergence measures to analyze what changes lead to improvement in performance in fine tuned models for synthetic aperture sonar (SAS) data. We examine the sensitivity to factors in the fine tuning process such as class imbalance. Our findings show not only an improvement in seafloor texture classification, but also provide greater insight into what features play critical roles in improving performance as well as a knowledge of the importance of balanced data for fine tuning deep learning models for seafloor classification in SAS imagery. | electrical engineering and systems science |
We introduce the first quasi-static particle-in-cell (PIC) code: WAND-PIC which doesn't require the commonly used predictor-corrector method in solving electromagnetic fields. We derive the field equations under quasi-static approximation and find the explicit form of the "time" derivative of transverse plasma current. After that, equations for the magnetic fields can be solved exactly without predicting the future quantities. Algorithm design and code structure are greatly simplified. With the help of explicit quasi-static equations and our adaptive step size, plasma bubbles driven by the large beam charges can be simulated efficiently without suffering from the numerical instabilities associated with the predictor-corrector method. In addition, WAND-PIC is able to simulate the sophisticated interactions between high-frequency laser fields and beam particles through the method of sub-cycling. Comparisons between the WAND-PIC and a first-principle full PIC code (VLPL) is presented. WAND-PIC is open-source [1], fully three-dimensional and parallelized with the in-house multigrid solver. Scalability, time complexity, and parallelization efficiency up to thousands of cores are also discussed in this work. | physics |
The World Health Organization's Expanded Programme on Immunization (WHO-EPI) was developed to ensure that all children have access to common childhood vaccinations. Unfortunately, because of inefficient distribution networks and cost constraints, millions of children in many low and middle-income countries still go without being vaccinated. In this paper, we formulate a mathematical programming model for the design of a typical WHO-EPI network with the goal of minimizing costs while providing the opportunity for universal coverage. Since it is only possible to solve small versions of the model optimally, we describe an iterative heuristic that cycles between solving restrictions of the original problem and show that it can find very good solutions in reasonable time for larger problems that are not directly solvable. | mathematics |
Quantum causality is an emerging field of study which has the potential to greatly advance our understanding of quantum systems. One of the most important problems in quantum causality is linked to this prominent aphorism that states correlation does not mean causation. A direct generalization of the existing causal inference techniques to the quantum domain is not possible due to superposition and entanglement. We put forth a new theoretical framework for merging quantum information science and causal inference by exploiting entropic principles. For this purpose, we leverage the concept of conditional density matrices to develop a scalable algorithmic approach for inferring causality in the presence of latent confounders (common causes) in quantum systems. We apply our proposed framework to an experimentally relevant scenario of identifying message senders on quantum noisy links, where it is validated that the input before noise as a latent confounder is the cause of the noisy outputs. We also demonstrate that the proposed approach outperforms the results of classical causal inference even when the variables are classical by exploiting quantum dependence between variables through density matrices rather than joint probability distributions. Thus, the proposed approach unifies classical and quantum causal inference in a principled way. This successful inference on a synthetic quantum dataset can lay the foundations of identifying originators of malicious activity on future multi-node quantum networks. | quantum physics |
Let $(X^n, \check{X}^n)$ be a mirror pair of an $n$-dimensional complex torus $X^n$ and its mirror partner $\check{X}^n$. Then, a simple projectively flat bundle $E(L,\mathcal{L})\rightarrow X^n$ is constructed from each affine Lagrangian submanifold $L$ in $\check{X}^n$ with a unitary local system $\mathcal{L} \rightarrow L$. In this paper, we first interpret these simple projectively flat bundles $E(L,\mathcal{L})$ in the language of factors of automorphy. Furthermore, we give a geometric interpretation for exact triangles consisting of three simple projectively flat bundles $E(L,\mathcal{L})$ and their shifts by focusing on the dimension of intersections of the corresponding affine Lagrangian submanifolds $L$. Finally, as an application of this geometric interpretation, we discuss whether such an exact triangle on $X^n$ ($n \geq 2$) is obtained as the pullback of an exact triangle on $X^1$ by a suitable holomorphic projection $X^n \rightarrow X^1$. | mathematics |
Electron-positron annihilation largely occurs in local thermal and chemical equilibrium after the neutrinos fall out of thermal equilibrium and during the Big Bang Nucleosynthesis (BBN) epoch. The effects of this process are evident in BBN yields as well as the relativistic degrees of freedom. We self-consistently calculate the collision integral for electron-positron creation and annihilation using the Klein-Nishina amplitude and appropriate statistical factors for Fermi-blocking and Bose-enhancement. Our calculations suggest that this annihilation freezes out when the photon-electron-positron-baryon plasma temperature is approximately 16 keV, after which its rate drops below the Hubble rate. In the temperature regime near 16 keV, we break the assumption of chemical equilibrium between the electrons, positrons, and photons to independently calculate the evolution of the chemical potentials of the electrons and positrons while computing the associated collision integrals at every time step. We find that the electron and positron chemical potentials deviate from the case with chemical equilibrium. While our results do not affect the interpretation of precision cosmological measurements in elucidating the standard cosmological model, these out of equilibrium effects may be important for testing physics beyond the standard model. | high energy physics phenomenology |
Packing is an obfuscation technique widely used by malware to hide the content and behavior of a program. Much prior research has explored how to detect whether a program is packed. This research includes a broad variety of approaches such as entropy analysis, syntactic signatures and more recently machine learning classifiers using various features. However, no robust results have indicated which algorithms perform best, or which features are most significant. This is complicated by considering how to evaluate the results since accuracy, cost, generalization capabilities, and other measures are all reasonable. This work explores eleven different machine learning approaches using 119 features to understand: which features are most significant for packing detection; which algorithms offer the best performance; and which algorithms are most economical. | computer science |
In this survey, symmetry provides a framework for classification of manifolds with differential-geometric structures. We highlight pseudo-Riemannian metrics, conformal structures, and projective structures. A range of techniques have been developed and successfully deployed in this subject, some of them based on algebra and dynamics and some based on analysis. We aim to illustrate this variety. | mathematics |
The Raman selection rules arise from the crystal symmetry and then determine the Raman activity and polarization of scattered phonon modes. However, these selection rules can be broken in resonant process due to the strong electron-phonon coupling effect. Here we reported the observation of breakdown of Raman selection rules in few-layer WS$_2$ by using resonant Raman scattering with dark A exciton. In this case, not only the infrared active modes and backscattering forbidden modes are observed, but the intensities of all observed phonon modes become strongest under paralleled-polarization and independent on the Raman tensors of phonons. We attributed this phenomenon to the interaction between dark A exciton and the scatted phonon, the so-called intraband Fr\"{o}hlich interaction, where the Raman scattering possibility is totally determined by the symmetry of exciton rather than the phonons due to strong electron-phonon coupling. Our results not only can be used to easily detect the optical forbidden excitonic and phononic states but also provide a possible way to manipulate optical transitions between electronic levels. | condensed matter |
Hydrocarbons are observed in the gas or solid phases of solar system objects, including comets, Trans-Neptunian Objects, planets and their moons. In the presence of water ice in these environments, hydrocarbons-bearing clathrate hydrates could form. In clathrate hydrates, guest molecules are trapped in crystalline water cages of different sizes, a phase used in models of planetary (sub-)surfaces or icy bodies such as comets. The phases in presence, the potential estimate of abundances of hydrocarbon species, the spectroscopic behaviour of hydrocarbon species in the different phases must be recorded to provide reference spectra for the comparison with remote observations. We show in this study the specific encaged ethylene signatures, with bands similar in position, but shifted from the pure ethylene ice spectrum. They show a marked temperature dependence both in position and width. Some vibrational modes are activated in the infrared by interaction with the water ice cages. | astrophysics |
A very long lifetime emission with non-single exponential decay characteristic has been reported for single InAs/GaAs quantum dot (QD) samples, in which there exists a long-lived metastable state in the wetting layer (WL) [ACS Photonics 2020,7,3228-3235]. In this article we have proposed a new three-level model to simulate the emission decay curve. In this model, assuming that the excitons in metastable state will diffuse and be trapped by QDs, and then emit fluorescence in QDs, a stretched-like exponential decay formula is derived as I(t)=At^({\beta}-1)e^(-(rt)^{\beta}), which can well describe the long lifetime decay curve with an analytical expression of average lifetime <{\tau}>=1/r{\Gamma}(1/{\beta}+1), where {\Gamma} is the Gamma function. Furthermore, based on the proposed three-level model, an expression of the second-order auto-correlation function g^2 (t) which can well fit the measured g^2 (t) curve is also obtained. | quantum physics |
Non-relativistic QCD axions or axion-like particles are among the most popular candidates for cold Dark Matter (DM) in the universe. We proposed to detect axion-like DM, using linearly polarized pulsar light as a probe. Because of birefringence effect potentially caused by an oscillating galactic axion DM background, when pulsar light travels across the galaxy, its linear polarization angle may vary with time. With a soliton+NFW galactic DM density profile, we show that this strategy can potentially probe an axion-photon coupling as small as $\sim 10^{-13}$ GeV$^{-1}$ for axion mass $m_a \sim 10^{-22}-10^{-20}$ eV, given the current measurement accuracy. An exclusion limit stronger than CAST ($ \sim 10^{-10}$ GeV$^{-1}$) and SN1987A ($ \sim 10^{-11}$ GeV$^{-1}$) could be extended up to $m_a \sim 10^{-18}$ eV and $\sim 10^{-19}$ eV, respectively. | astrophysics |
The article considers vector parameter estimators in statistical models generated by Levy processes. An improved one step estimator is presented that can be used for improving any other estimator. Combined numerical methods for optimization problems are proposed. A software has been developed and a correspondent testing and comparison have been presented. | statistics |
In this paper, we prove that a two-dimensional self-shrinker, homeomorphic to the sphere, immersed in the three dimensional Euclidean space $\mathbb{R}^3$ is a round sphere, provided its mean curvature and the norm of the its position vector have an upper bound in terms of the norm of its traceless second fundamental form. The example constructed by Drugan justifies that the hypothesis on the second fundamental form is necessary. We can also prove the same kind of rigidity results for surfaces with parallel weighted mean curvature vector in $\mathbb{R}^n$ with radial weight. These results are applications of a new generalization of Cauchy's Theorem in complex analysis which concludes that a complex function is identically zero or its zeroes are isolated if it satisfies some weak holomorphy. | mathematics |
We show that all self-adjoint extensions of semi-bounded Sturm--Liouville operators with general limit-circle endpoint(s) can be obtained via an additive singular form bounded self-adjoint perturbation of rank equal to the deficiency indices, say $d\in\{1,2\}$. This characterization generalizes the well-known analog for semi-bounded Sturm--Liouville operators with regular endpoints. Explicitly, every self-adjoint extension of the minimal operator can be written as \begin{align*} \boldsymbol{A}_\Theta=\boldsymbol{A}_0+{\bf B}\Theta{\bf B}^*, \end{align*} where $\boldsymbol{A}_0$ is a distinguished self-adjoint extension and $\Theta$ is a self-adjoint linear relation in $\mathbb{C}^d$. The perturbation is singular in the sense that it does not belong to the underlying Hilbert space but is form bounded with respect to $\boldsymbol{A}_0$, i.e. it belongs to $\mathcal{H}_{-1}(\boldsymbol{A}_0)$. The construction of a boundary triple and compatible boundary pair for the symmetric operator ensure that the perturbation is well-defined and self-adjoint extensions are in a one-to-one correspondence with self-adjoint relations $\Theta$. As an example, self-adjoint extensions of the classical symmetric Jacobi differential equation (which has two limit-circle endpoints) are obtained and their spectra are analyzed with tools both from the theory of boundary triples and perturbation theory. | mathematics |
Combining graph representation learning with multi-view data (side information) for recommendation is a trend in industry. Most existing methods can be categorized as \emph{multi-view representation fusion}; they first build one graph and then integrate multi-view data into a single compact representation for each node in the graph. However, these methods are raising concerns in both engineering and algorithm aspects: 1) multi-view data are abundant and informative in industry and may exceed the capacity of one single vector, and 2) inductive bias may be introduced as multi-view data are often from different distributions. In this paper, we use a \emph{multi-view representation alignment} approach to address this issue. Particularly, we propose a multi-task multi-view graph representation learning framework (M2GRL) to learn node representations from multi-view graphs for web-scale recommender systems. M2GRL constructs one graph for each single-view data, learns multiple separate representations from multiple graphs, and performs alignment to model cross-view relations. M2GRL chooses a multi-task learning paradigm to learn intra-view representations and cross-view relations jointly. Besides, M2GRL applies homoscedastic uncertainty to adaptively tune the loss weights of tasks during training. We deploy M2GRL at Taobao and train it on 57 billion examples. According to offline metrics and online A/B tests, M2GRL significantly outperforms other state-of-the-art algorithms. Further exploration on diversity recommendation in Taobao shows the effectiveness of utilizing multiple representations produced by \method{}, which we argue is a promising direction for various industrial recommendation tasks of different focus. | computer science |
In this paper, tangent-, principal normal-, and binormal-wise associated curves are defined such that each of these vectors of any given curve lies on the osculating, normal, and rectifying plane of its mate, respectively. For each associated curve, a new moving frame and the corresponding curvatures are found, and in addition to this the possible solutions for distance functions between the curve and its associated mate are discussed. In particular, it is seen that the involute curves belong to the family of tangent associated curves, the Bertrand and the Mannheim curves belong to the principal normal associated curves. Finally, as an application, we present some examples and map a given curve together with its mate and their frames. | mathematics |
The fifth edition of the "Computing Applications in Particle Physics" school was held on 3-7 February 2020, at Istanbul University, Turkey. This particular edition focused on the processing of simulated data from the Large Hadron Collider collisions using an Analysis Description Language and its runtime interpreter called CutLang. 24 undergraduate and 6 graduate students were initiated to collider data analysis during the school. After 3 days of lectures and exercises, the students were grouped into teams of 3 or 4 and each team was assigned an analysis publication from ATLAS or CMS experiments. After 1.5 days of independent study, each team was able to reproduce the assigned analysis using CutLang. | high energy physics phenomenology |
In this paper, we are concerned with differentially private SGD algorithms in the setting of stochastic convex optimization (SCO). Most of existing work requires the loss to be Lipschitz continuous and strongly smooth, and the model parameter to be uniformly bounded. However, these assumptions are restrictive as many popular losses violate these conditions including the hinge loss for SVM, the absolute loss in robust regression, and even the least square loss in an unbounded domain. We significantly relax these restrictive assumptions and establish privacy and generalization (utility) guarantees for private SGD algorithms using output and gradient perturbations associated with non-smooth convex losses. Specifically, the loss function is relaxed to have $\alpha$-H\"{o}lder continuous gradient (referred to as $\alpha$-H\"{o}lder smoothness) which instantiates the Lipschitz continuity ($\alpha=0$) and strong smoothness ($\alpha=1$). We prove that noisy SGD with $\alpha$-H\"older smooth losses using gradient perturbation can guarantee $(\epsilon,\delta)$-differential privacy (DP) and attain optimal excess population risk $O\Big(\frac{\sqrt{d\log(1/\delta)}}{n\epsilon}+\frac{1}{\sqrt{n}}\Big)$, up to logarithmic terms, with gradient complexity (i.e. the total number of iterations) $T =O( n^{2-\alpha\over 1+\alpha}+ n).$ This shows an important trade-off between $\alpha$-H\"older smoothness of the loss and the computational complexity $T$ for private SGD with statistically optimal performance. In particular, our results indicate that $\alpha$-H\"older smoothness with $\alpha\ge {1/2}$ is sufficient to guarantee $(\epsilon,\delta)$-DP of noisy SGD algorithms while achieving optimal excess risk with linear gradient complexity $T = O(n).$ | statistics |
Context : Star formation takes place in cold dense cores in molecular clouds. Earlier observations have found that dense cores exhibit subsonic non-thermal velocity dispersions. In contrast, CO observations show that the ambient large-scale cloud is warmer and has supersonic velocity dispersions. Aims : We aim to study the ammonia ($\rm NH_3$) molecular line profiles with exquisite sensitivity towards the coherent cores in L1688 in order to study their kinematical properties in unprecedented detail. Methods : We used $\rm NH_3$ (1,1) and (2,2) data from the first data release (DR1) in the Green Bank Ammonia Survey (GAS). We first smoothed the data to a larger beam of 1' to obtain substantially more extended maps of velocity dispersion and kinetic temperature, compared to the DR1 maps. We then identified the coherent cores in the cloud and analysed the averaged line profiles towards the cores. Results : For the first time, we detected a faint (mean $\rm NH_3$(1,1) peak brightness $<$0.25 K in $T_{MB}$), supersonic component towards all the coherent cores in L1688. We fitted two components, one broad and one narrow, and derived the kinetic temperature and velocity dispersion of each component. The broad components towards all cores have supersonic linewidths ($\mathcal{M}_S \ge 1$). This component biases the estimate of the narrow dense core component's velocity dispersion by $\approx$28% and the kinetic temperature by $\approx$10%, on average, as compared to the results from single-component fits. Conclusions : Neglecting this ubiquitous presence of a broad component towards all coherent cores causes the typical single-component fit to overestimate the temperature and velocity dispersion. This affects the derived detailed physical structure and stability of the cores estimated from $\rm NH_3$ observations. | astrophysics |
Characterizing the shared memberships of individuals in a classification scheme poses severe interpretability issues, even when using a moderate number of classes (say 4). Mixed membership models quantify this phenomenon, but they typically focus on goodness-of-fit more than on interpretable inference. To achieve a good numerical fit, these models may in fact require many extreme profiles, making the results difficult to interpret. We introduce a new class of multivariate mixed membership models that, when variables can be partitioned into subject-matter based domains, can provide a good fit to the data using fewer profiles than standard formulations. The proposed model explicitly accounts for the blocks of variables corresponding to the distinct domains along with a cross-domain correlation structure, which provides new information about shared membership of individuals in a complex classification scheme. We specify a multivariate logistic normal distribution for the membership vectors, which allows easy introduction of auxiliary information leveraging a latent multivariate logistic regression. A Bayesian approach to inference, relying on P\'olya gamma data augmentation, facilitates efficient posterior computation via Markov Chain Monte Carlo. We apply this methodology to a spatially explicit study of malaria risk over time on the Brazilian Amazon frontier. | statistics |
We obtain a lower bound for \[ \#\{x/2< p_{n}\leq x:\ p_n \equiv\ldots\equiv p_{n+m}\equiv a\text{ (mod $q$)},\ p_{n+m} - p_{n}\leq y\}, \] where $p_{n}$ is the $n^{\text{th}}$ prime. | mathematics |
Scientific hypotheses in a variety of applications have domain-specific structures, such as the tree structure of the International Classification of Diseases (ICD), the directed acyclic graph structure of the Gene Ontology (GO), or the spatial structure in genome-wide association studies. In the context of multiple testing, the resulting relationships among hypotheses can create redundancies among rejections that hinder interpretability. This leads to the practice of filtering rejection sets obtained from multiple testing procedures, which may in turn invalidate their inferential guarantees. We propose Focused BH, a simple, flexible, and principled methodology to adjust for the application of any pre-specified filter. We prove that Focused BH controls the false discovery rate under various conditions, including when the filter satisfies an intuitive monotonicity property and the p-values are positively dependent. We demonstrate in simulations that Focused BH performs well across a variety of settings, and illustrate this method's practical utility via analyses of real datasets based on ICD and GO. | statistics |
The success of deep learning has been witnessed as a promising technique for computer-aided biomedical image analysis, due to end-to-end learning framework and availability of large-scale labelled samples. However, in many cases of biomedical image analysis, deep learning techniques suffer from the small sample learning (SSL) dilemma caused mainly by lack of annotations. To be more practical for biomedical image analysis, in this paper we survey the key SSL techniques that help relieve the suffering of deep learning by combining with the development of related techniques in computer vision applications. In order to accelerate the clinical usage of biomedical image analysis based on deep learning techniques, we intentionally expand this survey to include the explanation methods for deep models that are important to clinical decision making. We survey the key SSL techniques by dividing them into five categories: (1) explanation techniques, (2) weakly supervised learning techniques, (3) transfer learning techniques, (4) active learning techniques, and (5) miscellaneous techniques involving data augmentation, domain knowledge, traditional shallow methods and attention mechanism. These key techniques are expected to effectively support the application of deep learning in clinical biomedical image analysis, and furtherly improve the analysis performance, especially when large-scale annotated samples are not available. We bulid demos at https://github.com/PengyiZhang/MIADeepSSL. | computer science |
Spin-orbit torque nano-oscillators based on bilayers of ferromagnetic (FM) and nonmagnetic (NM) metals are ultra-compact current-controlled microwave signal sources. They serve as a convenient testbed for studies of spin-orbit torque physics and are attractive for practical applications such as microwave assisted magnetic recording, neuromorphic computing, and chip-to-chip wireless communications. However, a major drawback of these devices is low output microwave power arising from the relatively small anisotropic magnetoresistance (AMR) of the FM layer. Here we experimentally show that the output power of a spin-orbit torque nano-oscillator can be enhanced by nearly three orders of magnitude without compromising its structural simplicity. Addition of a FM reference layer to the oscillator allows us to employ current-in-plane giant magnetoresistance (CIP GMR) to boost the output power of the device. This enhancement of the output power is a result of both large magnitude of GMR compared to that of AMR and different angular dependences of GMR and AMR. Our results pave the way for practical applications of spin-orbit torque nano-oscillators. | condensed matter |
We consider uniform random permutations drawn from a family enumerated through generating trees. We develop a new general technique to establish a central limit theorem for the number of consecutive occurrences of a fixed pattern in such permutations. We propose a technique to sample uniform permutations in such families as conditioned random colored walks. Building on that, we derive the behavior of the consecutive patterns in random permutations studying properties of the consecutive increments in the corresponding random walks. The method applies to families of permutations with a one-dimensional-labeled generating tree (together with some technical assumptions) and implies local convergence for random permutations in such families. We exhibit ten different families of permutations, most of them being permutation classes, that satisfy our assumptions. To the best of our knowledge, this is the first work where generating trees - which were introduced to enumerate combinatorial objects - have been used to establish probabilistic results. | mathematics |
We investigate the singularity structure of the $(-1)^F$ graded partition function in QCD with $n_f \geq 1$ massive adjoint fermions in the large-$N$ limit. Here, $F$ is fermion number and $N$ is the number of colors. The large $N$ partition function is made reliably calculable by taking space to be a small three-sphere $S^3$. Singularites in the graded partition function are related to phase transitions and to Hagedorn behavior in the $(-1)^F$-graded density of states. We study the flow of the singularities in the complex "inverse temperature" $\beta$ plane as a function of the quark mass. This analysis is a generalization of the Lee-Yang-Fisher-type analysis for a theory which is always in the thermodynamic limit thanks to the large $N$ limit. We identify two distinct mechanisms for the appearance of physical Hagedorn singularities and center-symmetry changing phase transitions at real positive $\beta$, inflow of singularities from the $\beta=0$ point, and collisions of complex conjugate pairs of singularities. | high energy physics theory |
We give a sufficient condition for the strict parabolic power concavity of the convolution in space variable of a function defined on $\mathbb{R}^n \times (0,+\infty)$ and a function defined on $\mathbb{R}^n$. Since the strict parabolic power concavity of a function defined on $\mathbb{R}^n \times (0,+\infty)$ naturally implies the strict power concavity of a function defined on $\mathbb{R}^n$, our sufficient condition implies the strict power concavity of the convolution of two functions defined on $\mathbb{R}^n$. As applications, we show the strict parabolic power concavity and strict power concavity in space variable of the Gauss--Weierstass integral and the Poisson integral for the upper half-space. | mathematics |
When a single molecule is connected to external electrodes by linker groups, the connectivity of the linkers to the molecular core can be controlled to atomic precision by appropriate chemical synthesis. Recently, the connectivity dependence of the electrical conductance and Seebeck coefficient of single molecules has been investigated both theoretically and experimentally. Here we study the connectivity dependence of the Wigner delay time of single-molecule junctions and the connectivity dependence of superconducting proximity effects, which occur when the external electrodes are replaced by superconductors. Although absolute values of transport properties depend on complex and often uncontrolled details of the coupling between the molecule and electrodes, we demonstrate that ratios of transport properties can be predicted using tables of 'magic numbers,' which capture the connectivity dependence of superconducting proximity effects and Wigner delay times within molecules. These numbers are calculated easily, without the need for large-scale computations. For normal-molecule-superconducting junctions, we find that the electrical conductance is proportional to the fourth power of their magic numbers, whereas for superconducting-molecule-superconducting junctions, the critical current is proportional to the square of their magic numbers. For more conventional normal-molecule-normal junctions, we demonstrate that delay time ratios can be obtained from products of magic number tables. | condensed matter |
With the increasing adoption of private blockchain platforms, consortia operating in various sectors such as trade, finance, logistics, etc., are becoming common. Despite having the benefits of a completely decentralized architecture which supports transparency and distributed control, existing private blockchains limit the data, assets, and processes within its closed boundary, which restricts secure and verifiable service provisioning to the end-consumers. Thus, platforms such as e-commerce with multiple sellers or cloud federation with a collection of cloud service providers cannot be decentralized with the existing blockchain platforms. This paper proposes a decentralized gateway architecture interfacing private blockchain with end-users by leveraging the unique combination of public and private blockchain platforms through interoperation. Through the use case of decentralized cloud federations, we have demonstrated the viability of the solution. Our testbed implementation with Ethereum and Hyperledger Fabric, with three service providers, shows that such consortium can operate within an acceptable response latency while scaling up to 64 parallel requests per second for cloud infrastructure provisioning. Further analysis over the Mininet emulation platform indicates that the platform can scale well with minimal impact over the latency as the number of participating service providers increases. | computer science |
Primordial black holes (PBHs) in the mass range $(30$--$100)~M_{\odot}$ are interesting candidates for dark matter, as they sit in a narrow window between microlensing and cosmic microwave background constraints. There are however tight constraints from the binary merger rate observed by the LIGO and Virgo experiments. In deriving these constraints, PBHs were treated as point Schwarzschild masses, while the more careful analysis in an expanding universe we present here, leads to a time-dependent mass. This implies a stricter set of conditions for a black hole binary to form and means that black holes coalesce much more quickly than was previously calculated, namely well before the LIGO/Virgo's observed mergers. The observed binaries are those coalescing within galactic halos, with a merger rate consistent with data. This reopens the possibility for dark matter in the form of LIGO-mass PBHs. | astrophysics |
We propose that a simple, Lagrangian 2d $\mathcal{N}=(0, 2)$ duality interface between the 3d $\mathcal{N}=2$ XYZ model and 3d $\mathcal{N}=2$ SQED can be associated to the simplest triangulated 4-manifold: the 4-simplex. We then begin to flesh out a dictionary between more general triangulated 4-manifolds with boundary and 2d $\mathcal{N}=(0, 2)$ interfaces. In particular, we identify IR dualities of interfaces associated to local changes of 4d triangulation, governed by the (3,3), (2,4), and (4,2) Pachner moves. We check these dualities using supersymmetric half-indices. We also describe how to produce stand-alone 2d theories (as opposed to interfaces) capturing the geometry of 4-simplices and Pachner moves by making additional field-theoretic choices, and find in this context that the Pachner moves recover abelian $\mathcal{N}=(0,2)$ trialities of Gadde-Gukov-Putrov. Our work provides new, explicit tools to explore the interplay between 2d dualities and 4-manifold geometry that has been developed in recent years. | high energy physics theory |
Causality is a seminal concept in science: any research discipline, from sociology and medicine to physics and chemistry, aims at understanding the causes that could explain the correlations observed among some measured variables. While several methods exist to characterize classical causal models, no general construction is known for the quantum case. In this work we present quantum inflation, a systematic technique to falsify if a given quantum causal model is compatible with some observed correlations. We demonstrate the power of the technique by reproducing known results and solving open problems for some paradigmatic examples of causal networks. Our results may find an application in many fields: from the characterization of correlations in quantum networks to the study of quantum effects in thermodynamic and biological processes. | quantum physics |
Though used extensively, the concept and process of machine learning (ML) personalization have generally received little attention from academics, practitioners, and the general public. We describe the ML approach as relying on the metaphor of the person as a feature vector and contrast this with humanistic views of the person. In light of the recent calls by the IEEE to consider the effects of ML on human well-being, we ask whether ML personalization can be reconciled with these humanistic views of the person, which highlight the importance of moral and social identity. As human behavior increasingly becomes digitized, analyzed, and predicted, to what extent do our subsequent decisions about what to choose, buy, or do, made both by us and others, reflect who we are as persons? This paper first explicates the term personalization by considering ML personalization and highlights its relation to humanistic conceptions of the person, then proposes several dimensions for evaluating the degree of personalization of ML personalized scores. By doing so, we hope to contribute to current debate on the issues of algorithmic bias, transparency, and fairness in machine learning. | statistics |
Spectral lines from N-like ions can be used to measure the temperature and density of various types of astrophysical plasmas. The atomic databases of astrophysical plasma modelling codes still have room for improvement in their electron-impact excitation data sets for N-like ions, especially $R$-matrix data. This is particularly relevant for future observatories (e.g. Arcus) which will host high-resolution spectrometers. We aim to obtain level-resolved effective collision strengths for all transitions up to $nl=5d$ over a wide range of temperatures for N-like ions from O II to Zn XXIV (i.e., O$^{+}$ to Zn$^{23+}$) and to assess the accuracy of the present work. We also examine the impact of our new data on plasma diagnostics by modelling solar observations with CHIANTI. We have carried-out systematic $R$-matrix calculations for N-like ions which included 725 fine-structure target levels in both the configuration interaction target and close-coupling collision expansions. The $R$-matrix intermediate coupling frame transformation method was used to calculate the collision strengths, while the AUTOSTRUCTURE code was used for the atomic structures. We compare the present results for selected ions with those in archival databases and the literature. The comparison covers energy levels, oscillator strengths, and effective collision strengths. We show examples of improved plasma diagnostics when compared to CHIANTI models which use only distorted wave data as well as some which use previous $R$-matrix data. The electron-impact excitation data are archived according to the Atomic Data and Analysis Structure (ADAS) data class it adf04 and will be available in OPEN-ADAS. The data can be used to improve the atomic databases for astrophysical plasma diagnostics. | astrophysics |
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