• #### Classification of flat bands from irremovable discontinuities of Bloch wave functions

We show that flat bands can be categorized into two distinct classes, that is, singular and non-singular flat bands, by exploiting the singular behavior of their Bloch wave functions in momentum space. In the case of a singular flat band, its Bloch wave function possesses irremovable discontinuities generated by the band crossing with other bands. Once the degeneracy at the band crossing point is lifted, the flat band becomes dispersive and may acquire a finite Chern number in general. On the other hand, the Bloch wave function of a non-singular flat band has no singularity, and thus it can be completely isolated from other bands while preserving the perfect flatness. All one dimensional flat bands belong to the non-singular class. We show that a singular flat band displays a novel bulk-boundary correspondence such that the presence of the robust boundary mode is guaranteed by the singularity of the Bloch wave function. Moreover, we develop a general scheme to construct a flat band model Hamiltonian in which one can freely design its singular or non-singular nature. Finally, we propose a general formula for the compact localized state spanning the flat band, which can be easily implemented in numerics and offer a basis set useful in analyzing correlation effects in flat bands.
Flat bandHamiltonianBloch waveUnit cellTorusChern numberMomentum spaceNearest-neighbor siteLattice modelKagome lattice...
• #### Reconciling the Diversity and Uniformity of Galactic Rotation Curves with Self-Interacting Dark Matter

Galactic rotation curves exhibit diverse behavior in the inner regions, while obeying an organizing principle, i.e., they can be approximately described by a radial acceleration relation or the Modified Newtonian Dynamics phenomenology. We analyze the rotation curve data from the SPARC sample, and explicitly demonstrate that both the diversity and uniformity are naturally reproduced in a hierarchical structure formation model with the addition of dark matter self-interactions. The required concentrations of the dark matter halos are fully consistent with the concentration-mass relation predicted by the Planck cosmological model. The inferred stellar mass-to-light ($3.6 \mu m$) ratios scatter around $0.5 M_\odot/L_\odot$, as expected from population synthesis models, leading to a tight radial acceleration relation and baryonic Tully-Fisher relation. The inferred stellar-halo mass relation is consistent with the expectations from abundance matching. These results indicate that the inner dark matter halos of galaxies are thermalized due to the self-interactions of dark matter particles.
Self-interacting dark matterRotation CurveGalaxyModified Newtonian DynamicsSpitzer Photometry and Accurate Rotation CurvesDark matterMonte Carlo Markov chainBaryonic Tully-Fisher relationCold dark matterNavarro-Frenk-White profile...
• #### The Golden Mean and the Physics of Aestheticsver. 3

The golden mean, Phi, has been applied in diverse situations in art, architecture and music, and although some have claimed that it represents a basic aesthetic proportion, others have argued that it is only one of a large number of such ratios. We review its early history, especially its relationship to the Mount Meru of Pingala. We examine the successive divisions of 3, 7, and 22 in Indian music and suggest derivation from variants of Mount Meru. We also speculate on the neurophysiological basis behind the sense that the golden mean is a pleasant proportion.
MountingArchitecture
• #### A characterisation for Finsler metrics of constant curvature and a Finslerian version of Beltrami Theoremver. 2

We define a Weyl-type curvature tensor that provides a characterisation for Finsler metrics of constant flag curvature. When the Finsler metric reduces to a Riemannian metric, the Weyl-type curvature tensor reduces to the classic projective Weyl tensor. In the general case, the Weyl-type curvature tensor differs from the Weyl projective curvature, it is not a projective invariant, and hence Beltrami Theorem does not work in Finsler geometry. We provide the relation between the Weyl-type curvature tensors of two projectively related Finsler metrics. Using this formula we show that a projective deformation preserves the property of having constant flag curvature if and only if the projective factor is a Hamel function. This way we provide a Finslerian version of Beltrami Theorem.
Beltrami's theoremCurvature tensorCurvatureConstant curvatureRiemannian metricWeyl tensorGeometry...
• #### The Hawking temperature, the uncertainty principle and quantum black holes

In 1974, Stephen Hawking theoretically discovered that black holes emit thermal radiation and have a characteristic temperature, known as the Hawking temperature. The aim of this paper is to present a simple heuristic derivation of the Hawking temperature, based on the Heisenberg uncertainty principle. The result obtained coincides exactly with Hawking's original finding. In parallel, this work seeks to clarify the physical meaning of Hawking's discovery. This article may be useful as pedagogical material in a high school physics course or in an introductory undergraduate physics course.
Black holeGeneral relativityHawking temperatureQuantum mechanicsHorizonUncertainty principleQuantum black holeHawking radiationQuantum gravityAtomic nucleus...
• #### Monty Hall problem revisited once more

The Monty Hal problem is an attractive puzzle. It combines simple statement with answers that seem surprising to most audiences. The problem was thoroughly solved over two decades ago. Yet, more recent discussions indicate that the solution is incompletely understood. Here, we review the solution and discuss pitfalls and other aspects that make the problem interesting.
Monty Hall problemMathematical proofLucidAndromeda IIProbabilityEventSurveysRight Hand Side of the expressionForceProbability theory...
• #### Novel collider signature of $U_1$ Leptoquark and $B\to \pi$ observables

One of the most popular models that is known to be able to solve the lepton flavour universality violating charged ($b\to c$) and neutral current ($b\to s$) anomalies is the Leptoquark Model. However, collider searches for such leptoquarks till date are only restricted towards their scalar counterpart. In this work we examine the {\it multijet} + $\mET$ collider signatures of a vector leptoquark ($U_1$) which has the potential to mediate both the charged and neutral current processes at tree level. From our collider analysis we derive the exclusion mass limits for the $U_1$ leptoquark at 95\% C.L. at the current and future experiment of Large Hadron Collider. We also calculate the effect of such a leptoquark in $B\to\pi$ observables. These can be used as further benchmarks if a hint towards the presence of such a leptoquark is discovered.
• #### X, Y, Z Search at Belle IIver. 2

Search for exotics has increased importance since the observation of the X(3872), 13 years ago, announced by the Belle Collaboration. The observation of pentaquark states by LHCb, and the Z-charged states observed at Belle and BES III have raised even more the attention to the field. Presently several states are observed that do not fit potential models, and looking for them in different production mechanisms and search for their decay modes it is important, as well as to do precise measurement of their mass, width, lineshape. We shortly report in this note about the plan in searching for exotics at Belle II at KEK (Tsukuba, Japan), that just ended the Phase-II running period, and show the first re-discovery results using 5 pb$^{-1}$ integrated luminosity.
BELLE IIStatisticsX(3872)Belle experimentIntegrated luminosityInvariant massBound stateY(4260)KEKPentaquark...
• #### Observation of Transverse $\Lambda/\bar{\Lambda}$ Hyperon Polarization in $e^+e^-$ Annihilation at Bellever. 2

We report the first observation of the spontaneous polarization of $\Lambda$ and $\bar{\Lambda}$ hyperons transverse to the production plane in $e^+e^-$ annihilation, which is attributed to the effect arising from a polarizing fragmentation function. For inclusive $\Lambda/\bar{\Lambda}$ production, we also report results with subtracted feed-down contributions from $\Sigma^0$ and charm. This measurement uses a dataset of 800.4 fb$^{-1}$ collected by the Belle experiment at or near a center-of-mass energy of 10.58 GeV. We observe a significant polarization that rises with the fractional energy carried by the $\Lambda/\bar{\Lambda}$ hyperon.
HyperonFragmentation functionBelle experimentFragmentationTransverse momentumPerturbative QCDMonte Carlo methodCharm quarkColliderParton...
• #### $\Lambda_c$ branching fractions

An analysis of observed and anticipated $\Lambda_c$ decays, recently published in this journal, is provided with a table of inputs and a figure denoting branching fractions. It is based on the 2018 compilation in {\tt http://pdg.lbl.gov/2018/listings/rpp2018-list-lambdac-plus.pdf} and employs a statistical isospin model to estimate branching fractions for as-yet-unseen decay modes.
Branching ratioIsospinDecay modeCERNCharmed baryonsSemileptonic decayCabibbo-Kobayashi-Maskawa matrixPhase spaceMeasurementNeutron...
• #### A unified leptoquark model confronted with lepton non-universality in $B$-meson decays

The anomalies in the $B$-meson sector, in particular $R_{K^{(*)}}$ and $R_{D^{(*)}}$, are often interpreted as hints for physics beyond the Standard Model. To this end, leptoquarks or a heavy $Z'$ represent the most popular SM extensions which can explain the observations. However, adding these fields by hand is not very satisfactory as it does not address the big questions like a possible embedding into a unified gauge theory. On the other hand, light leptoquarks within a unified framework are challenging due to additional constraints such as lepton flavor violation. The existing accounts typically deal with this issue by providing estimates on the relevant couplings. In this letter we consider a complete model based on the $SU(4)_{\rm C}\otimes SU(2)_{\rm L}\otimes U(1)_{\rm R}$ gauge symmetry, a subgroup of $SO(10)$, featuring both scalar and vector leptoquarks. We demonstrate that this setup has, in principle, all the potential to accommodate $R_{K^{(*)}}$ and $R_{D^{(*)}}$ while respecting bounds from other sectors usually checked in this context. However, it turns out that $K_L \to e^{\pm} \mu^{\mp}$ severely constraints not only the vector but also the scalar leptoquarks and, consequently, also the room for any sizeable deviations of $R_{K^{(*)}}$ from 1. We briefly comment on the options for extending the model in order to conform this constraint. Moreover, we present a simple criterion for all-orders proton stability within this class of models.
LeptoquarkMeson decaysBeyond the Standard ModelLepton flavour violationSubgroupEmbeddingGauge symmetryGauge theoryLeptonsScalar...
• #### Exotic Tetraquark Mesons in Large-$N_c$ Limit: an Unexpected Great Surprise

Two-ordinary-meson scattering in large-$N_c$ QCD implies consistency criteria for intermediate-tetraquark contributions. Their fulfilment at $N_c$-leading order constrains the nature of the spectrum of genuinely exotic tetraquark states.
TetraquarkFlavourDecay widthDegree of freedomBound stateTwo-point correlation functionDecay rateMandelstam variablesSubcategoryScattering amplitude...
• #### Compact Structures in Standard Field Theoryver. 3

We investigate the presence of static solutions in models described by real scalar field in two-dimensional spacetime. After taking advantage of a procedure introduced sometime ago, we solve intricate nonlinear ordinary differential equations and illustrate how to find compact structures in models engendering standard kinematics. In particular, we study linear stability and show that all the static solutions we have found are linearly stable.
CompactonKinematicsScalar fieldField theoryZero modeSolitonOrdinary differential equationsHamiltonianStandard ModelSpontaneous symmetry breaking...
• #### My Years with Julian Schwinger: From Source Theory through Sonoluminescence

I recall my interactions with Julian Schwinger, first as a graduate student at Harvard, and then as a postdoc at UCLA, in the period 1968--81, and subsequently. Some aspects of his legacy to physics are discussed.
Field theoryQuantum electrodynamicsCasimir effectElectrodynamicsQuantum mechanicsDyonDeep inelastic scatteringStrong interactionsRenormalizationMagnetic charge...
• #### Quantum treatment of Verlinde's entropic force conjecture

Verlinde conjectured that gravitation is an emergent entropic force. This surprising conjecture was proved in [Physica A {\bf 505} (2018) 190] within a purely classical context. Here, we appeal to a quantum environment to deal with the conjecture in the case of bosons and consider also the classical limit of quantum mechanics (QM).
Quantum mechanicsVerlinde formulaClassical limitEntropyStatistical mechanicsBose gasCosmologyCatenaryHolographic principleGeneral relativity...
• #### Yes, Aboriginal Australians Can and Did Discover the Variability of Betelgeuse

Recently, a widely publicized claim has been made that the Aboriginal Australians discovered the variability of the red star Betelgeuse in the modern Orion, plus the variability of two other prominent red stars: Aldebaran and Antares. This result has excited the usual healthy skepticism, with questions about whether any untrained peoples can discover the variability and whether such a discovery is likely to be placed into lore and transmitted for long periods of time. Here, I am offering an independent evaluation, based on broad experience with naked-eye sky viewing and astro-history. I find that it is easy for inexperienced observers to detect the variability of Betelgeuse over its range in brightness from V = 0.0 to V = 1.3, for example in noticing from season-to-season that the star varies from significantly brighter than Procyon to being greatly fainter than Procyon. Further, indigenous peoples in the Southern Hemisphere inevitably kept watch on the prominent red star, so it is inevitable that the variability of Betelgeuse was discovered many times over during the last 65 millennia. The processes of placing this discovery into a cultural context (in this case, put into morality stories) and the faithful transmission for many millennia is confidently known for the Aboriginal Australians in particular. So this shows that the whole claim for a changing Betelgeuse in the Aboriginal Australian lore is both plausible and likely. Given that the discovery and transmission is easily possible, the real proof is that the Aboriginal lore gives an unambiguous statement that these stars do indeed vary in brightness, as collected by many ethnographers over a century ago from many Aboriginal groups. So I strongly conclude that the Aboriginal Australians could and did discover the variability of Betelgeuse, Aldebaran, and Antares.
BetelgeuseRed starsProcyonAntaresStar...
• #### Prospects for Measurements with Strange Hadrons at LHCb

This report details the capabilities of LHCb and its upgrades towards the study of kaons and hyperons. The analyses performed so far are reviewed, elaborating on the prospects for some key decay channels, while proposing some new measurements in LHCb to expand its strangeness research program.
• #### Chirality and intrinsic dissipation of spin modes in two-dimensional electron liquids

We review recent theoretical and experimental developments concerning collective spin excitations in two-dimensional electron liquid (2DEL) systems, with particular emphasis on the interplay between many-body and spin-orbit effects, as well as the intrinsic dissipation due to the spin-Coulomb drag. Historically, the experimental realization of 2DELs in silicon inversion layers in the 60s and 70s created unprecedented opportunities to probe subtle quantum effects, culminating in the discovery of the quantum Hall effect. In the following years, high quality 2DELs were obtained in doped quantum wells made in typical semiconductors like GaAs or CdTe. These systems became important test beds for quantum many-body effects due to Coulomb interaction, spin dynamics, spin-orbit coupling, effects of applied magnetic fields, as well as dissipation mechanisms. Here we focus on the recent results involving chiral effects and intrinsic dissipation of collective spin modes: these are not only of fundamental interest but also important towards demonstrating new concepts in spintronics. Moreover, new realizations of 2DELs are emerging beyond traditional semiconductors, for instance in multilayer graphene, oxide interfaces, dichalcogenide monolayers, and many more. The concepts discussed in this review will be relevant also for these emerging systems.
Quantum wellPlasmonSpin waveDissipationCollective spinChiralitySpin-flipElectron liquidSemiconductorHamiltonian...
• #### The mass of sound

We show that the commonly accepted statement that sound waves do not transport mass is only true at linear order. Using effective field theory techniques, we confirm the result found in [Phys. Rev. B97, 134516 (2018), 1705.08914] for zero-temperature superfluids, and extend it to the case of solids and ordinary fluids. We show that, in fact, sound waves do carry mass---in particular, gravitational mass. This implies that a sound wave not only is affected by gravity but also generates a tiny gravitational field. Our findings are valid for non-relativistic media as well, and could have intriguing experimental implications.
PhononSuperfluidWave packetGravitational fieldsSpeed of soundEffective field theoryEffective actionHamiltonianExpectation ValuePerfect fluid...
• #### A high-bias, low-variance introduction to Machine Learning for physicists

Machine Learning (ML) is one of the most exciting and dynamic areas of modern research and application. The purpose of this review is to provide an introduction to the core concepts and tools of machine learning in a manner easily understood and intuitive to physicists. The review begins by covering fundamental concepts in ML and modern statistics such as the bias-variance tradeoff, overfitting, regularization, and generalization before moving on to more advanced topics in both supervised and unsupervised learning. Topics covered in the review include ensemble models, deep learning and neural networks, clustering and data visualization, energy-based models (including MaxEnt models and Restricted Boltzmann Machines), and variational methods. Throughout, we emphasize the many natural connections between ML and statistical physics. A notable aspect of the review is the use of Python notebooks to introduce modern ML/statistical packages to readers using physics-inspired datasets (the Ising Model and Monte-Carlo simulations of supersymmetric decays of proton-proton collisions). We conclude with an extended outlook discussing possible uses of machine learning for furthering our understanding of the physical world as well as open problems in ML where physicists maybe able to contribute. (Notebooks are available at https://physics.bu.edu/~pankajm/MLnotebooks.html )
Neural networkDeep Neural NetworksRegularizationRegressionLogistic regressionConvolutional neural networkMachine learningDeep learningSupervised learningArchitecture...
• #### Theta-problem and the String Swampland

In the context of $\mathcal{N}=2$ supergravity without vector multiplets coupled to hypermultiplets, the coupling constant of graviphoton $\tau$ is apriori a free parameter. Stringy realization of this and using a mathematical conjecture leads to the statement that $j(\tau)\in \mathbb{R}$ so that the $\theta$-angle is $0$ or $\pi$. We conjecture that for any consistent realization of $\mathcal{N}=2$ supergravity theories coupled only to hypermultiplets this is the case and the rest belong to the swampland. This leads to the speculation that the $\theta$-angle for QCD or QED may also be fixed to $0$ for quantum gravitational consistency.
3-foldQuantum gravitySupergravitySwamplandGraviphotonVacuum expectation valueEffective LagrangianFine structure constantGauge coupling constantType IIB string theory...
• #### Non-Compact WZW Conformal Field Theories

We discuss non-compact WZW sigma models, especially the ones with symmetric space $H^{\bf C}/H$ as the target, for $H$ a compact Lie group. They offer examples of non-rational conformal field theories. We remind their relation to the compact WZW models but stress their distinctive features like the continuous spectrum of conformal weights, diverging partition functions and the presence of two types of operators analogous to the local and non-local insertions recently discussed in the Liouville theory. Gauging non-compact abelian subgroups of $H^{\bf C}$ leads to non-rational coset theories. In particular, gauging one-parameter boosts in the $SL(2,\bC)/SU(2)$ model gives an alternative, explicitly stable construction of a conformal sigma model with the euclidean 2D black hole target. We compute the (regularized) toroidal partition function and discuss the spectrum of the theory. A comparison is made with more standard approach based on the $U(1)$ coset of the $SU(1,1)$ WZW theory where stability is not evident but where unitarity becomes more transparent.
CosetPartition functionConformal field theoryBlack holeWess-Zumino-Witten modelSigma modelGreen's functionSubgroupUnitarityEigenfunction...
• #### Five-Particle Phase-Space Integrals in QCD

We present analytical expressions for the 31 five-particle phase-space master integrals in massless QCD as an $\epsilon$-series with coefficients being multiple zeta values of weight up to 12. In addition, we provide computer code for the Monte-Carlo integration in higher dimensions, based on the RAMBO algorithm, that has been used to numerically cross-check the obtained results in 4, 6, and 8 dimensions.
Phase-space integralsMonte Carlo methodPhase spacePropagatorPrecisionColliderVegaDegenerate Fermi gasStatistical errorWolfram Mathematica...
• #### Sensitivity of quantum information to environment perturbations measured with the out-of-time-order correlation function

Measures to quantify the flow of quantum information and its sensitivity to environment perturbations are needed to better understand the evolution of open quantum systems and to distinguish non-Markovian from Markovian dynamics. Here, we show that the extent of correlations in many-body quantum systems is an experimentally accessible metric for quantifying the spread of quantum information. Our experiment applies multiple-quantum nuclear magnetic resonance (NMR) technique to take snapshots of the multi-spin correlations between a central spin and the spins in its surrounding environment. We argue that the width of the distribution of these multi-spin correlations is the natural metric for quantifying the flow of information between the system and the environment. Quantum information shared between the two is sensitive to environment perturbations. The out-of-time-order correlation function (OTOC) is used to measure this sensitivity. By analyzing the decay of the OTOC as a function of our metric instead of time, we demonstrate the exponential behavior of the OTOC.
Quantum informationHamiltonianNuclear magnetic resonanceOut of TimeTwo-point correlation functionPulse sequenceDensity matrixMultidimensional ArrayOrientationFlip-flop...
• #### A Tour of TensorFlow

Deep learning is a branch of artificial intelligence employing deep neural network architectures that has significantly advanced the state-of-the-art in computer vision, speech recognition, natural language processing and other domains. In November 2015, Google released $\textit{TensorFlow}$, an open source deep learning software library for defining, training and deploying machine learning models. In this paper, we review TensorFlow and put it in context of modern deep learning concepts and software. We discuss its basic computational paradigms and distributed execution model, its programming interface as well as accompanying visualization toolkits. We then compare TensorFlow to alternative libraries such as Theano, Torch or Caffe on a qualitative as well as quantitative basis and finally comment on observed use-cases of TensorFlow in academia and industry.
GraphMachine learningDeep learningGoogle.comPythonNeural networkApplication programming interfaceArchitectureOptimizationConvolutional neural network...
• #### Dropout is a special case of the stochastic delta rule: faster and more accurate deep learning

Multi-layer neural networks have lead to remarkable performance on many kinds of benchmark tasks in text, speech and image processing. Nonlinear parameter estimation in hierarchical models is known to be subject to overfitting. One approach to this overfitting and related problems (local minima, colinearity, feature discovery etc.) is called dropout (Srivastava, et al 2014, Baldi et al 2016). This method removes hidden units with a Bernoulli random variable with probability $p$ over updates. In this paper we will show that Dropout is a special case of a more general model published originally in 1990 called the stochastic delta rule ( SDR, Hanson, 1990). SDR parameterizes each weight in the network as a random variable with mean $\mu_{w_{ij}}$ and standard deviation $\sigma_{w_{ij}}$. These random variables are sampled on each forward activation, consequently creating an exponential number of potential networks with shared weights. Both parameters are updated according to prediction error, thus implementing weight noise injections that reflect a local history of prediction error and efficient model averaging. SDR therefore implements a local gradient-dependent simulated annealing per weight converging to a bayes optimal network. Tests on standard benchmarks (CIFAR) using a modified version of DenseNet shows the SDR outperforms standard dropout in error by over 50% and in loss by over 50%. Furthermore, the SDR implementation converges on a solution much faster, reaching a training error of 5 in just 15 epochs with DenseNet-40 compared to standard DenseNet-40's 94 epochs.
Delta ruleOverfittingNeural networkDeep learningImage ProcessingClassificationBackpropagationSimulated annealingArchitectureHidden layer...
• #### A Fourier View of REINFORCE

We show a connection between the Fourier spectrum of Boolean functions and the REINFORCE gradient estimator for binary latent variable models. We show that REINFORCE estimates (up to a factor) the degree-1 Fourier coefficients of a Boolean function. Using this connection we offer a new perspective on variance reduction in gradient estimation for latent variable models: namely, that variance reduction involves eliminating or reducing Fourier coefficients that do not have degree 1. We then use this connection to develop low-variance unbiased gradient estimators for binary latent variable models such as sigmoid belief networks. The estimator is based upon properties of the noise operator from Boolean Fourier theory and involves a sample-dependent baseline added to the REINFORCE estimator in a way that keeps the estimator unbiased. The baseline can be plugged into existing gradient estimators for further variance reduction.
Statistical estimatorLatent variableOptimizationNeural networkInferenceHarmonic analysisBackpropagationMonte Carlo methodOrthonormal basisFeedforward neural network...
• #### DarkCapPy: Dark Matter Capture and Annihilation

DarkCapPy is a Python 3/Jupyter package for calculating rates associated with dark matter capture in the Earth, annihilation into light mediators, and the subsequent observable decay of the light mediators near the surface of the Earth. The package includes a calculation of the Sommerfeld enhancement at the center of the Earth and the timescale for capture--annihilation equilibrium. The code is open source and can be modified for other compact astronomical objects and mediator spins.
Dark matterEarthLight mediatorPythonAstronomical objectsSommerfeld enhancementSpin...
• #### Nuclear vs. Integrated Spectroscopy of Galaxies in the Herschel Reference Survey

Context. The determination of the relative frequency of active galactic nuclei (AGN) versus other spectral classes, for example, HII region-like (HII), transition objects (TRAN), passive (PAS), and retired (RET), in a complete set of galaxies in the local Universe is of primary importance to discriminate the source of ionization in the nuclear region of galaxies. Aims. Here we aim to provide a spectroscopic characterization of the nuclei of galaxies belonging to the Herschel Reference Survey (HRS), a volume and magnitude limited sample representative of the local Universe, which has become a benchmark for local and high-z studies, for semianalytical models and cosmological simulations. The comparison between the nuclear spectral classification and the one determined on the global galactic scale provides information about how galaxy properties change from the nuclear to the outer regions. Moreover, the extrapolation of the global star formation (SF) properties from the SDSS fiber spectroscopy compared to the one computed by Halpha photometry can be useful for testing the method based on aperture correction for determining the global star formation rate (SFR) for local galaxies. Methods. By collecting the existing nuclear spectroscopy available from the literature, complemented with new observations obtained using the Loiano 1.52m telescope, we analyze the 322 nuclear spectra of HRS galaxies. Results. Using two diagnostic diagrams (the BPT and the WHAN) we provide a nuclear and an integrated spectral classification for the HRS galaxies. Conclusions. We find that the fraction of AGNs increases with stellar mass, such that at logM > 10.0 M\odot or 66% of the LTGs are AGNs or TRAN.
GalaxyActive Galactic NucleiSloan Digital Sky SurveyClassificationStar formation rateStellar massStellar classificationStar formationLocal UniverseTelescopes...
• #### Tetraquarks and pentaquarks

Greig Cowan and Tim Gershon describe new types of matter called tetraquarks and pentaquarks, and discuss the outlook for understanding these particles.
PentaquarkTetraquarkParticles
• #### Impact of vector new physics couplings on $B_s \to (K,\,K^{\ast})\tau\nu$ and $B \to \pi\tau\nu$ decays

Experimental measurements of $R_{D}$, $R_{D^*}$ and $R_{J/\Psi}$ in $B \to (D,\,D^{\ast})l\nu$ and $B_c \to J/\Psi l \nu$ decays mediated via $b \to c\,l\,\nu$ charged current interactions deviate from standard model prediction by $2.3\sigma$, $3.4\sigma$ and $2\sigma$, respectively. In addition, a deviation of $1.5\sigma$ from the standard model prediction has been witnessed in $\mathcal B(B \to \tau \nu)$ mediated via $b \to u\,l\,\nu$ charged current interactions as well. Motivated by the anomalies present in $B$ and $B_c$ meson decays, we analyze the corresponding $B_s \to (K,\,K^{\ast})\,\tau\,\nu$ and $B \to \pi\tau\nu$ semileptonic decays within the standard model and beyond. We use an effective field theory formalism in which $b \to c$ and $b \to u$ semileptonic decays are assumed to exhibit similar new physics patterns. We give the predictions of various observables such as the branching fractions, ratio of branching ratios, lepton side forward backward asymmetry, lepton polarization fraction and convexity parameter for $B_s \to (K,\,K^{\ast})\tau \nu$ and $B \to \pi\tau\nu$ decay channels within the standard model and within various NP scenarios.
Standard ModelBranching ratioForward-backward asymmetryDecay modeSemileptonic decayCharged currentForm factorTransition form factorEffective LagrangianHelicity...
• #### Molecular gas in distant galaxies from ALMA studiesver. 2

ALMA is now fully operational, and has been observing in early science mode since 2011. The millimetric (mm) and sub-mm domain is ideal to tackle galaxies at high redshift, since the emission peak of the dust at 100$\mu$m is shifted in the ALMA bands (0.3mm to 1mm) for z=2 to 9, and the CO lines, stronger at the high-J levels of the ladder, are found all over the 0.3-3mm range. Pointed surveys and blind deep fields have been observed, and the wealth of data collected reveal a drop at high redshifts (z $>$ 6) of dusty massive objects, although surprisingly active and gas-rich objects have been unveiled through gravitational lensing. The window of the reionization epoch is now wide open, and ALMA has detected galaxies at z=8-9 mainly in continuum, [CII] and [OIII] lines. Galaxies have a gas fraction increasing steeply with redshift, as (1+z)$^2$, while their star formation efficiency increases also but more slightly, as (1+z)$^{0.6}$ to (1+z)$^1$. Individual object studies have revealed luminous quasars, with black hole masses much higher than expected, clumpy galaxies with resolved star formation rate compatible with the Kennicutt-Schmidt relation, extended cold and dense gas in a circumgalactic medium, corresponding to Lyman-$\alpha$ blobs, and proto-clusters, traced by their brightest central galaxies.
GalaxyAtacama Large Millimeter ArrayDust emissionStar formationStellar massQuasarProtoclustersMetallicityMain sequence starStar formation rate...
• #### Two-component dark matter and a massless neutrino in a new B-L model

We propose a new extension of the Standard Model by a $U(1)_{B-L}$ gauge symmetry in which the anomalies are canceled by two right-handed neutrinos plus four chiral fermions with fractional B-L charges. Two scalar fields that break the B-L symmetry and give masses to the new fermions are also required. After symmetry breaking, two neutrinos acquire Majorana masses via the seesaw mechanism leaving a massless neutrino in the spectrum. Additionally, the other new fermions arrange themselves into two Dirac particles, both of which are automatically stable and contribute to the observed dark matter density. This model thus realizes in a natural way, without ad hoc discrete symmetries, a two-component dark matter scenario. We analyze in some detail the dark matter phenomenology of this model. The dependence of the relic densities with the parameters of the model is illustrated and the regions consistent with the observed dark matter abundance are identified. Finally, we impose the current limits from LHC and direct detection experiments, and show that the high mass region of this model remains unconstrained.
Dark matterDark matter particleNeutrinoSterile neutrinoLarge Hadron ColliderDark matter particle massNeutrino massLaboratory dark matter searchStandard ModelCollider...
• #### Comments on Lorentz Transformations, Dressed Asymptotic States and Hawking Radiationver. 2

We consider two applications of the factorization of infrared dynamics in QED and gravity. The first is a redefinition of the Lorentz transformations that makes them commute with supertranslations. The other is the process of particle creation near a black hole horizon. For the latter we show that the emission of soft particles factors out of the S-matrix in the fixed-background approximation and to leading order in the soft limit. The factorization is implemented by dressing the incoming and outgoing asymptotic states with clouds of soft photons and soft gravitons. We find that while the soft photon cloud has no effect, the soft graviton cloud induces a phase shift in the Bogolyubov coefficients relating the incoming and outgoing modes. However, the flux of outgoing particles, given by the absolute value of the Bogolyubov coefficient, is insensitive to this phase.
Lorentz transformationDegree of freedomGravitonHawking radiationS-matrixBlack hole horizonEntanglementGauge fieldSoft photonsHorizon...
• #### E and B polarizations from inhomogeneous and solar surface turbulence

Gradient- and curl-type or E- and B-type polarizations have been routinely analyzed to study the physics contributing to the cosmic microwave background polarization and galactic foregrounds. They characterize the parity-even and parity-odd properties of the underlying physical mechanisms, for example helical hydromagnetic turbulence in the case of dust polarization. Here we study spectral correlation functions characterizing the party-even and parity-odd parts of linear polarization for homogeneous and inhomogeneous helical turbulence to show that only the latter can give rise to a parity-odd polarization signal. We identify a strong negative skewness of the E polarization as the prime cause for producing the observed enhanced EE/BB correlation ratio. We close with a preliminary assessment of using linear polarization of the Sun to characterize its helical turbulence without being subjected to the pi ambiguity that magnetic inversion techniques have to address.
TurbulenceSolar surfaceSunMagnetic helicityHelicityTwo-point correlation functionCosmic microwave backgroundCorrelation ratioCosmic microwave background polarizationMagnetohydrodynamics...
• #### van der Waals hadron resonance gas and QCD phase diagram

Taking into account the recently developed van der Waals (VDW) like equation of state (EoS) for grand canonical ensemble of fermions, the temperature dependent profiles of normalized entropy density ($s /T^3$) and the ratio of shear viscosity and entropy density ($\eta/ s$) for hadron resonance gas have been evaluated. The VDW parameters, corresponding to interactions between (anti)baryons, have been obtained by contrasting lattice EoS for QCD matter at finite chemical potentials ($\mu_{B}$) and for $T \le$ 160 MeV. The temperature and chemical potential dependent study of $s /T^3$ and $\eta /s$ for hadron gas, by signalling onsets of first order phase transition and crossover in the hadronic phase of QCD matter, helps in understanding the QCD phase diagram in the ($T, \mu_{B}$) - plane. An estimation of probable location of critical point matches predictions from other recent studies.
Finite temperature QCDCritical pointQuark matterShear viscosityEntropyFirst-order phase transitionsPhase diagramRelativistic Heavy Ion ColliderPhase transitionsLattice calculations...
• #### Black holes and class groupsver. 2

The theory of quadratic forms and class numbers has connections to many classical problems in number theory. Recently, class numbers have appeared in the study of black holes in string theory. We describe this connection and raise questions in the hope of inspiring new collaborations between number theorists and physicists.
Black holeAttractorCompactificationSupersymmetricConformal field theoryString theoryNumber theoryDualityEntropySupergravity...
• #### Efficiently decoding the 3D toric codes and welded codes on cubic lattices

The recent years have seen a growing interest in quantum codes in three dimensions (3D). One of the earliest proposed 3D quantum codes is the 3D toric code. It has been shown that 3D color codes can be mapped to 3D toric codes. The 3D toric code on cubic lattice is also a building block for the welded code which has highest energy barrier to date. Although well known, the performance of the 3D toric code has not been studied extensively. In this paper, we propose efficient decoding algorithms for the 3D toric code on a cubic lattice with and without boundaries and report their performance for various quantum channels. We observe a threshold of $\gtrsim 12\%$ for the bit flip errors, $\approx 3\%$ for phase flip errors and $24.8\%$ for erasure channel. We also study the performance of the welded 3D toric code on the quantum erasure channel. We did not observe a threshold for the welded code over the erasure channel.
QubitToric codeErasurePhase errorGraphFreezingPeriodic boundary conditionsVertex operatorQuantum channelCoset...
• #### Policy Optimization as Wasserstein Gradient Flows

Policy optimization is a core component of reinforcement learning (RL), and most existing RL methods directly optimize parameters of a policy based on maximizing the expected total reward, or its surrogate. Though often achieving encouraging empirical success, its underlying mathematical principle on {\em policy-distribution} optimization is unclear. We place policy optimization into the space of probability measures, and interpret it as Wasserstein gradient flows. On the probability-measure space, under specified circumstances, policy optimization becomes a convex problem in terms of distribution optimization. To make optimization feasible, we develop efficient algorithms by numerically solving the corresponding discrete gradient flows. Our technique is applicable to several RL settings, and is related to many state-of-the-art policy-optimization algorithms. Empirical results verify the effectiveness of our framework, often obtaining better performance compared to related algorithms.
Gradient flowOptimizationReinforcement learningManifoldFokker-Planck equationBottleneck neural networkBrownian motionPancharatnam-Berry phaseRegressionNeural network...
• #### A very deep Chandra observation of the Perseus cluster: shocks, ripples and conductionver. 2

We present the first results from a very deep Chandra X-ray observation of the core of the Perseus cluster of galaxies. A pressure map reveals a clear thick band of high pressure around the inner radio bubbles. The gas in the band must be expanding outward and the sharp front to it is identified as a shock front, yet we see no temperature jump across it; indeed there is more soft emission behind the shock than in front of it. We conclude that in this inner region either thermal conduction operates efficiently or the co-existing relativistic plasma seen as the radio mini-halo is mediating the shock. If common, isothermal shocks in cluster cores mean that we cannot diagnose the expansion speed of radio bubbles from temperature measurements alone. They can at times expand more rapidly than currently assumed without producing significant regions of hot gas. Bubbles may also be significantly more energetic. The pressure ripples found in earlier images are identified as isothermal sound waves. A simple estimate based on their amplitude confirms that they can be an effective distributed heat source able to balance radiative cooling. We see multiphase gas with about 10^9 Msun at a temperature of about 0.5 keV. Much, but not all, of this cooler gas is spatially associated with the optical filamentary nebula around the central galaxy, NGC 1275. A residual cooling flow of about 50 Msun/yr may be taking place. A channel is found in the pressure map along the path of the bubbles, with indications found of outer bubbles. The channel connects in the S with a curious cold front.
Perseus galaxy clusterGalaxy filamentThermal conductivityDissipationGalaxyIntra-cluster mediumRadio sourcesRelativistic plasmaChandra X-ray ObservatoryCooling flow...
• #### When Recurrent Models Don't Need To Be Recurrentver. 2

We prove stable recurrent neural networks are well approximated by feed-forward networks for the purpose of both inference and training by gradient descent. Our result applies to a broad range of non-linear recurrent neural networks under a natural stability condition, which we observe is also necessary. Complementing our theoretical findings, we verify the conclusions of our theory on both real and synthetic tasks. Furthermore, we demonstrate recurrent models satisfying the stability assumption of our theory can have excellent performance on real sequence learning tasks.
Recurrent neural networkLong short term memoryHidden stateInferenceTriangle inequalityOptimizationHyperparameterNon-linear dynamical systemArchitectureEmbedding...
• #### Attention Is All You Needver. 5

The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models also connect the encoder and decoder through an attention mechanism. We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely. Experiments on two machine translation tasks show these models to be superior in quality while being more parallelizable and requiring significantly less time to train. Our model achieves 28.4 BLEU on the WMT 2014 English-to-German translation task, improving over the existing best results, including ensembles by over 2 BLEU. On the WMT 2014 English-to-French translation task, our model establishes a new single-model state-of-the-art BLEU score of 41.8 after training for 3.5 days on eight GPUs, a small fraction of the training costs of the best models from the literature. We show that the Transformer generalizes well to other tasks by applying it successfully to English constituency parsing both with large and limited training data.
TransductionArchitectureRecurrent neural networkMachine translationConvolutional neural networkEmbeddingPath lengthHidden layerHidden stateInference...
• #### Recent Anomalies in B Physics

$B$ physics plays important roles in searching for the new physics (NP) beyond the standard model (SM). Recently, some deviations between experimental data and SM predictions were reported, namely $R(D^{(*)})$, $P_5^\prime$ and $R_{K^{(*)}}$ anomalies. If these anomalies were further confirmed in future, they would be unambiguous hints of NP. Theoretically, in order to explain these anomalies, a large number of models have been proposed, such as models including leptoquark or $Z^\prime$. However, these new particles have not been discovered directly in LHC. Moreover, the models should pass the examination of $B_s\to \mu^+\mu^-$ and $B_s^0-\bar B_s^0$ mixing. In future, the analysis of data taken during the ongoing Run 2 of the LHC and the forthcoming Belle-II will present new insight both into the observables of interest and into new strategies to control uncertainties. Theoretically, the existed models should be further tested; and more NP models are welcomed to explain these anomalies simultaneously without affecting other measurements consistent with SM.
Standard ModelLeptoquarkLarge Hadron ColliderLHCbBELLE IIBranching ratioBeyond the Standard ModelATLAS Experiment at CERNSemileptonic decayWilson coefficients...
• #### Higgs data does not rule out a sequential fourth generation with an extended scalar sectorver. 2

Contrary to the common perception, we show that the current Higgs data does not eliminate the possibility of a sequential fourth generation that get their masses through the same Higgs mechanism as the first three generations. The inability to fix the sign of the bottom-quark Yukawa coupling from the available data plays a crucial role in accommodating a chiral fourth generation which is consistent with the bounds on the Higgs signal strengths. We show that effects of such a fourth generation can remain completely hidden not only in the production of the Higgs boson through gluon fusion but also to its subsequent decay to $\gamma\gamma$ and $Z\gamma$. This, however, is feasible only if the scalar sector of the Standard Model is extended. We also provide a practical example illustrating how our general prescription can be embedded in a realistic model.
Higgs bosonStandard ModelLarge Hadron ColliderYukawa couplingTwo Higgs Doublet ModelBottom quarkGluon fusionUnitarityNeutrinoFlavour Changing Neutral Currents...
• #### Charged Fermions Below 100 GeV

How light can a fermion be if it has unit electric charge? We revisit the lore that LEP robustly excludes charged fermions lighter than about 100 GeV. We review LEP chargino searches, and find them to exclude charged fermions lighter than 90 GeV, assuming a higgsino-like cross section. However, if the charged fermion couples to a new scalar, destructive interference among production channels can lower the LEP cross section by a factor of 3. In this case, we find that charged fermions as light as 75 GeV can evade LEP bounds, while remaining consistent with constraints from the LHC. As the LHC collects more data, charged fermions in the 75-100 GeV mass range serve as a target for future monojet and disappearing track searches.
• #### Production of Cool Gas in Thermally-Driven Outflowsver. 2

Galactic outflows commonly contain multiphase gas, and its physical origin requires explanation. Using the CGOLS (Cholla Galactic OutfLow Simulations) suite of high-resolution isolated galaxy models, we demonstrate the viability of rapid radiative cooling as a source of fast-moving ($v \sim 1000$ km/s), cool ($10^4$ K) gas observed in absorption line studies of outflows around some star-forming galaxies. By varying the mass-loading and geometry of the simulated winds, we identify a region of parameter space that leads to cool gas in outflows. In particular, when using an analytically-motivated central feedback model, we find that cooling flows can be produced with reasonable mass-loading rates ($\dot{M}_{wind} / \dot{M}_{SFR} \sim 0.5$), provided the star formation rate surface density is high. When a more realistic clustered feedback model is applied, destruction of high density clouds near the disk and interactions between different outflow regions indicate that lower mass-loading rates of the hot gas within the feedback region may still produce multiphase outflows. These results suggest an origin for fast-moving cool gas in outflows that does not rely on directly accelerating cool gas from the interstellar medium. These cooling flows may additionally provide an explanation for the multiphase gas ubiquitously observed in the halos of star-forming galaxies at low redshift.
CoolingGalactic windSupernovaRadiative coolingStar formationInterstellar mediumStar formation rateGalaxyFluid dynamicsCircumgalactic medium...
• #### A Brief Survey of Deep Reinforcement Learningver. 2

Deep reinforcement learning is poised to revolutionise the field of AI and represents a step towards building autonomous systems with a higher level understanding of the visual world. Currently, deep learning is enabling reinforcement learning to scale to problems that were previously intractable, such as learning to play video games directly from pixels. Deep reinforcement learning algorithms are also applied to robotics, allowing control policies for robots to be learned directly from camera inputs in the real world. In this survey, we begin with an introduction to the general field of reinforcement learning, then progress to the main streams of value-based and policy-based methods. Our survey will cover central algorithms in deep reinforcement learning, including the deep $Q$-network, trust region policy optimisation, and asynchronous advantage actor-critic. In parallel, we highlight the unique advantages of deep neural networks, focusing on visual understanding via reinforcement learning. To conclude, we describe several current areas of research within the field.
Deep Reinforcement LearningReinforcement learningDeep Neural NetworksRoboticsDeep learningAutonomous systemSurveysFieldAlgorithmsNetworks...
• #### MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

We present a class of efficient models called MobileNets for mobile and embedded vision applications. MobileNets are based on a streamlined architecture that uses depth-wise separable convolutions to build light weight deep neural networks. We introduce two simple global hyper-parameters that efficiently trade off between latency and accuracy. These hyper-parameters allow the model builder to choose the right sized model for their application based on the constraints of the problem. We present extensive experiments on resource and accuracy tradeoffs and show strong performance compared to other popular models on ImageNet classification. We then demonstrate the effectiveness of MobileNets across a wide range of applications and use cases including object detection, finegrain classification, face attributes and large scale geo-localization.
ArchitectureClassificationConvolutional neural networkObject detectionDistillationCOCO simulationDeep Neural NetworksSmall-scale dynamoRegularizationCrossed product...
• #### Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes

Synchronized stochastic gradient descent (SGD) optimizers with data parallelism are widely used in training large-scale deep neural networks. Although using larger mini-batch sizes can improve the system scalability by reducing the communication-to-computation ratio, it may hurt the generalization ability of the models. To this end, we build a highly scalable deep learning training system for dense GPU clusters with three main contributions: (1) We propose a mixed-precision training method that significantly improves the training throughput of a single GPU without losing accuracy. (2) We propose an optimization approach for extremely large mini-batch size (up to 64k) that can train CNN models on the ImageNet dataset without losing accuracy. (3) We propose highly optimized all-reduce algorithms that achieve up to 3x and 11x speedup on AlexNet and ResNet-50 respectively than NCCL-based training on a cluster with 1024 Tesla P40 GPUs. On training ResNet-50 with 90 epochs, the state-of-the-art GPU-based system with 1024 Tesla P100 GPUs spent 15 minutes and achieved 74.9\% top-1 test accuracy, and another KNL-based system with 2048 Intel KNLs spent 20 minutes and achieved 75.4\% accuracy. Our training system can achieve 75.8\% top-1 test accuracy in only 6.6 minutes using 2048 Tesla P40 GPUs. When training AlexNet with 95 epochs, our system can achieve 58.7\% top-1 test accuracy within 4 minutes, which also outperforms all other existing systems.
PrecisionDeep learningOptimizationDeep Neural NetworksStochastic gradient descentSchedulingConvolutional neural networkArithmeticArchitectureRegularization...
• #### An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modelingver. 2

For most deep learning practitioners, sequence modeling is synonymous with recurrent networks. Yet recent results indicate that convolutional architectures can outperform recurrent networks on tasks such as audio synthesis and machine translation. Given a new sequence modeling task or dataset, which architecture should one use? We conduct a systematic evaluation of generic convolutional and recurrent architectures for sequence modeling. The models are evaluated across a broad range of standard tasks that are commonly used to benchmark recurrent networks. Our results indicate that a simple convolutional architecture outperforms canonical recurrent networks such as LSTMs across a diverse range of tasks and datasets, while demonstrating longer effective memory. We conclude that the common association between sequence modeling and recurrent networks should be reconsidered, and convolutional networks should be regarded as a natural starting point for sequence modeling tasks. To assist related work, we have made code available at http://github.com/locuslab/TCN .
ArchitectureLong short term memoryRecurrent neural networkDilationMachine translationHyperparameterConvolutional neural networkDeep learningClassificationRegularization...