Binary Scaling Research Articles

Parallel scattering, saturation, and generalized Abramovskii-Gribov-Kancheli (AGK) theorem in the EPOS4 framework, with applications for heavy-ion collisions at sNN of 5.02 TeV and 200 GeV

Ultrarelativistic heavy-ion collisions will first realize many nucleon-nucleon scatterings, happening instantaneously and therefore necessarily in parallel, due to the short collision time. An appropriate quantum mechanical tool to treat that problem is S-matrix theory, and it has been known for a long time how to derive a simple geometric probabilistic picture, still widely used, and here the Abramovskii-Gribov-Kancheli (AGK) theorem plays a crucial role. All this is done in a scenario where energy conservation is not taken care of, but this is needed, in particular for Monte Carlo simulations. When introducing energy-momentum sharing properly, the AGK theorem does not apply anymore, nor do simple geometric concepts such as binary scaling. I will discuss this (very serious) problem, and how it can be solved, in the EPOS4 framework. When connecting the multiple-Pomeron approach (for parallel scatterings) and perturbative QCD, one is actually forced to implement in a very particular way saturation scales in order to get an approach free of contradictions. One recovers a generalized AGK theorem (gAGK), valid at large pt (larger than the relevant saturation scales). I discuss how gAGK is related to factorization (in proton-proton scatterings) and binary scaling (in heavy-ion collisions). I will show some applications, using this new approach as an initial condition for hydrodynamical evolutions, for heavy-ion collisions at sNN of 5.02 TeV and 200 GeV, to get some idea about the energy dependence. Published by the American Physical Society 2024

W±-boson production in p–Pb collisions at sqrt{s_{textrm{NN}}} = 8.16 TeV and Pb–Pb collisions at sqrt{s_{textrm{NN}}} = 5.02 TeV

The production of the W± bosons measured in p–Pb collisions at a centre-of-mass energy per nucleon–nucleon collision sqrt{s_{textrm{NN}}} = 8.16 TeV and Pb–Pb collisions at sqrt{s_{textrm{NN}}} = 5.02 TeV with ALICE at the LHC is presented. The W± bosons are measured via their muonic decay channel, with the muon reconstructed in the pseudorapidity region −4 < {eta}_{textrm{lab}}^{mu } < −2.5 with transverse momentum {p}_{textrm{T}}^{mu } > 10 GeV/c. While in Pb–Pb collisions the measurements are performed in the forward (2.5 < {y}_{textrm{cms}}^{mu } < 4) rapidity region, in p–Pb collisions, where the centre-of-mass frame is boosted with respect to the laboratory frame, the measurements are performed in the backward (−4.46 < {y}_{textrm{cms}}^{mu } < −2.96) and forward (2.03 < {y}_{textrm{cms}}^{mu } < 3.53) rapidity regions. The W− and W+ production cross sections, lepton-charge asymmetry, and nuclear modification factors are evaluated as a function of the muon rapidity. In order to study the production as a function of the p–Pb collision centrality, the production cross sections of the W− and W+ bosons are combined and normalised to the average number of binary nucleon–nucleon collision 〈Ncoll〉. In Pb–Pb collisions, the same measurements are presented as a function of the collision centrality. Study of the binary scaling of the W±-boson cross sections in p–Pb and Pb–Pb collisions is also reported. The results are compared with perturbative QCD calculations, with and without nuclear modifications of the Parton Distribution Functions (PDFs), as well as with available data at the LHC. Significant deviations from the theory expectations are found in the two collision systems, indicating that the measurements can provide additional constraints for the determination of nuclear PDFs and in particular of the light-quark distributions.

Density estimation of an ultrahigh-speed rarefied flow field based on force analysis of a pendulum sphere

The similarity criterion for high speed or high enthalpy rarefied reaction flows is the binary scaling law, one of which is the product of the incoming flow density and the characteristic scale of the test model in a rarefied wind tunnel should be equal to that under the flight condition. This is to ensure that the ratio between the characteristic distance of the relaxation process and the characteristic length of the body is equal. However, in a rarefied wind tunnel, it is difficult to directly measure the flow density below 10−5 kg/m3 using common methods due to the relatively high rarefied degree, an indirect density estimation method based on force analysis of a pendulum sphere was proposed in this study. The oscillation trajectory of the pendulum sphere under ultrahigh-speed rarefied flow conditions was recorded and the corresponding aerodynamic drag force acted on the sphere along the trajectory was analyzed, based on which the density distribution of the flow was then estimated combined with DSMC simulations. The obtained results show that in the present study, the flow is in under-expanded condition and the measured density sharply decreased from 10−6 kg/m3 to 10−7 kg/m3 at 140–170 mm from the nozzle outlet.

Decomposition of galactic X-ray emission with PHOX

Context.X-ray observations of galaxies with high spatial resolution instruments such asChandrahave revealed that major contributions to their diffuse emission originate from X-ray-bright point sources in the galactic stellar field. It has been established that these point sources, called X-ray binaries, are accreting compact objects with stellar donors in a binary configuration. They are classified according to the predominant accretion process: wind-fed in the case of high-mass donors and Roche-lobe mass transfer in the case of low-mass donors. Observationally, it is challenging to reliably disentangle these two populations from each other because of their similar spectra.Aims.We provide a numerical framework with which spatially and spectrally accurate representations of X-ray binary populations can be studied from hydrodynamical cosmological simulations. We construct average spectra, accounting for a hot gas component, and verify the emergence of observed scaling relations between galaxy-wide X-ray luminosity (LX) and stellar mass (M*) and betweenLXand the star-formation rate (SFR).Methods.Using simulated galaxy halos extracted from the (48 h−1 cMpc)3volume of the Magneticum Pathfinder cosmological simulations atz = 0.07, we generate mock spectra with the X-ray photon-simulator PHOX. We extend the PHOXcode to account for the stellar component in the simulation and study the resulting contribution in composite galactic spectra.Results.Well-known X-ray binary scaling relations with galactic SFR andM*emerge self-consistently, verifying our numerical approach. Average X-ray luminosity functions are perfectly reproduced up to the one-photon luminosity limit. Comparing our resultingLX − SFR − M*relation for X-ray binaries with recent observations of field galaxies in the Virgo galaxy cluster, we find significant overlap. Invoking a metallicity-dependent model for high-mass X-ray binaries yields an anticorrelation between mass-weighted stellar metallicity and SFR-normalized luminosity. The spatial distribution of high-mass X-ray binaries coincides with star-formation regions of simulated galaxies, while low-mass X-ray binaries follow the stellar mass surface density. X-ray binary emission is the dominant contribution in the hard X-ray band (2–10 keV) in the absence of an actively accreting central super-massive black hole, and it provides a ∼50% contribution in the soft X-ray band (0.5–2 keV), rivaling the hot gas component.Conclusions.We conclude that our modeling remains consistent with observations despite the uncertainties connected to our approach. The predictive power and easily extendable framework hold great value for future investigations of galactic X-ray spectra.

Theoretical and numerical study of the binary scaling law for electron distribution in thermochemical non-equilibrium flows under extremely high Mach number

The binary scaling law is a classical similarity law used in analysing hypersonic flow fields. The objective of this study is to investigate the applicability of the binary scaling law in thermochemical non-equilibrium airflow. Dimensional analysis of vibrational and electron–electronic energy conservation equations was employed to explore the theoretical reasons for the failure of the binary scaling law. Numerical simulation based on a multi-temperature model (translational–rotational temperature T, electron–electronic excitation temperature ${T_e}$ and the vibrational temperatures of ${\textrm{O}_2}$ and ${\textrm{N}_2}$ , $\; {T_{{v_{{\textrm{O}_2}}}}}$ and ${T_{{v_{{\textrm{N}_2}}}}}$ ) with two chemical models (the Gupta model and the Park model) was adopted to study the accuracy of the binary scaling law for electron distribution at high altitude with extremely high Mach number. The results of theoretical analysis indicate that the three-body collision reactions and the translation–electron energy exchange from collisions between electrons and ions, ${Q_{t - e\_ions}}$ , can cause the failure of the binary scaling law. The results of numerical simulation show that the electron-impact ionization reactions are the main reasons for the invalidation of the binary scaling law for electron distribution at high altitude with high Mach number. With an increase of free-stream Mach number, the negative effect on the binary scaling law caused by ${Q_{t - e\_ions}}$ cannot be ignored.

Learning multiplication-free linear transformations

In this paper, we propose several dictionary learning algorithms for sparse representations that also impose specific structures on the learned dictionaries such that they have low coding complexity and are numerically efficient to use: reduced number of addition/multiplications and even avoid multiplications altogether. We base our work on factorizations of the dictionaries in highly structured basic building blocks (binary orthonormal, scaling, and shear transformations) for which we can write closed-form solutions to the optimization problems that we consider. We show the effectiveness of our methods on image data where we compare against well-known numerically efficient transforms such as fast Fourier, fast discrete cosine transforms, and fast structured dictionaries.

Consumer food sustainability before and during the Covid-19 Crisis: A quantitative content analysis and food policy implications

Sustainability is one of the major challenges that societies are facing. The question of why and how consumer food sustainability related issues (e.g., food waste, sustainable food shopping behavior, among others) are placed on the public agenda is therefore of high interest to food policy makers. Drawing from media agenda setting theory, this study provides the first analysis of how relationships between consumer food sustainability-related frames appear in the media. Focusing on the COVID-19 crisis, it is examined how the media framed food sustainability issues in 2019 and 2020. 271 newspaper stories are investigated through a rather new approach to quantitative content analysis that incorporated binary coding, optimal scaling, and path analysis. The study’s findings point to various significant relationships between frame contents and implications and similarly bring to light the moderating effects of the COVID-19 crisis and ‘article authorship’ on a number of these relationships. The findings contribute to the understanding of how public opinion regarding food sustainability develops and can help food policymakers and authorities seeking to develop, position, and address issues relevant to food sustainability.

Progress in the Glauber Model at Collider Energies

We review the theoretical and experimental progress in the Glauber model of multiple nucleon and/or parton scatterings after the last 10–15 years of operation with proton and nuclear beams at the BNL Relativistic Heavy Ion Collider and the CERN Large Hadron Collider. The main developments and the state of the art of the field are summarized. These encompass measurements of the inclusive inelastic proton and nuclear cross sections, advances in the description of the proton and nuclear density profiles and their fluctuations, inclusion of subnucleonic degrees of freedom, experimental procedures and issues related to the determination of the collision centrality, validation of the binary scaling prescription for hard scattering cross sections, and constraints on transport properties of quark–gluon matter from varying initial-state conditions in relativistic hydrodynamics calculations. These advances confirm the validity and usefulness of the Glauber formalism for quantitative studies of quantum chromodynamics matter produced in high-energy collisions of systems, from protons to uranium nuclei, of vastly different size.

Multiparton interactions in pp collisions from machine learning-based regression

Multi-Parton Interactions (MPI) in pp collisions have attracted the attention of the heavy-ion community since they can help to elucidate the origin of collective-like effects discovered in small collision systems at the LHC. In this work, we report that in PYTHIA 8.244, the charged-particle production in events with a large number of MPI (${\rm N}_{\rm mpi}$) normalized to that obtained in minimum-bias pp collisions shows interesting features. After the normalization to the corresponding $\langle {\rm N}_{\rm mpi} \rangle$, the ratios as a function of $p_{\rm T}$ exhibit a bump at $p_{\rm T}\approx3$ GeV/$c$; and for higher $p_{\rm T}$ ($>8$ GeV/$c$), the ratios are independent of ${\rm N}_{\rm mpi}$. While the size of the bump increases with increasing ${\rm N}_{\rm mpi}$, the behavior at high $p_{\rm T}$ is expected from the "binary scaling" (parton-parton interactions), which holds given the absence of any parton-energy loss mechanism in PYTHIA. The bump at intermediate $p_{\rm T}$ is reminiscent of the Cronin effect observed for the nuclear modification factor in p--Pb collisions. In order to unveil these effects in data, we propose a strategy to construct an event classifier sensitive to MPI using Machine Learning-based regression. The study is conducted using TMVA, and the regression is performed with Boosted Decision Trees (BDT). Event properties like forward charged-particle multiplicity, transverse spherocity and the average transverse momentum ($\langle p_{\rm T} \rangle$) are used for training. The kinematic cuts are defined in accordance with the ALICE detector capabilities. In addition, we also report that if we apply the trained BDT on existing (${\rm INEL}>0$) pp data, i.e. events with at least one primary charged-particle within $|\eta|<1$, the average number of MPI in pp collisions at $\sqrt{s}=5.02$ and 13 TeV are 3.76$\pm1.01$ and 4.65$\pm1.01$, respectively.

Multi-variant differential evolution algorithm for feature selection

This work introduces a new population-based stochastic search technique, named multi-variant differential evolution (MVDE) algorithm for solving fifteen well-known real world problems from UCI repository and compared to four popular optimization methods. The MVDE proposes a new self-adaptive scaling factor based on cosine and logistic distributions as an almost factor-free optimization technique. For more updated chances, this factor is binary-mapped by incorporating an adaptive crossover operator. During the evolution, both greedy and less-greedy variants are managed by adjusting and incorporating the binary scaling factor and elite identification mechanism into a new multi-mutation crossover process through a number of sequentially evolutionary phases. Feature selection decreases the number of features by eliminating irrelevant or misleading, noisy and redundant data which can accelerate the process of classification. In this paper, a new feature selection algorithm based on the MVDE method and artificial neural network is presented which enabled MVDE to get a combination features’ set, accelerate the accuracy of the classification, and optimize both the structure and weights of Artificial Neural Network (ANN) simultaneously. The experimental results show the encouraging behavior of the proposed algorithm in terms of the classification accuracies and optimal number of feature selection.

X-Ray Binary Luminosity Function Scaling Relations in Elliptical Galaxies: Evidence for Globular Cluster Seeding of Low-mass X-Ray Binaries in Galactic Fields

We investigate X-ray binary (XRB) luminosity function (XLF) scaling relations for Chandra detected populations of low-mass XRBs (LMXBs) within the footprints of 24 early-type galaxies. Our sample includes Chandra and HST observed galaxies at D < 25 Mpc that have estimates of the globular cluster (GC) specific frequency (SN) reported in the literature. As such, we are able to directly classify X-ray-detected sources as being either coincident with unrelated background/foreground objects, GCs, or sources that are within the fields of the galaxy targets. We model the GC and field LMXB population XLFs for all galaxies separately, and then construct global models characterizing how the LMXB XLFs vary with galaxy stellar mass and SN. We find that our field LMXB XLF models require a component that scales with SN, and has a shape consistent with that found for the GC LMXB XLF. We take this to indicate that GCs are "seeding" the galactic field LMXB population, through the ejection of GC-LMXBs and/or the diffusion of the GCs in the galactic fields themselves. However, we also find that an important LMXB XLF component is required for all galaxies that scales with stellar mass, implying that a substantial population of LMXBs are formed "in situ," which dominates the LMXB population emission for galaxies with SN < 2. For the first time, we provide a framework quantifying how directly-associated GC LMXBs, GC-seeded LMXBs, and in-situ LMXBs contribute to LMXB XLFs in the broader early-type galaxy population.

Development of technique for face detection in image based on binarization, scaling and segmentation methods

A technique for face detection in the image is proposed, which is based on binarization, scaling, and segmentation of the image, followed by the determination of the largest connected component that matches the image of the face. Modern methods of binarization, scaling, and taxonomic image segmentation have one or more of the following disadvantages: they have a high computational complexity; require the determination of parameter values. Taxonomic image segmentation methods may have additional disadvantages: they do not allow noise and outliers selection; clusters can’t have different shapes and sizes, and their number is fixed. Due to this, to improve the efficiency of face detection techniques, the methods of binarization, scaling and taxonomic segmentation needs to be improved. A binarization method is proposed, the distinction of which is the use of the image background. This allows to simplify the process of scaling and segmentation (since all the pixels in the background are represented by the same color), non-uniform brightness of the face, and not to use the threshold settings and additional parameters. A binary image scaling method is proposed, the distinction of which is the use of an arithmetic mean filter with threshold processing and fast wavelet transform. This allows to speed up the image segmentation process by about P 2 times, where P is the scaling parameter, and not to use the time-consuming procedure for determining. A binary scaled image segmentation method is proposed, the distinction of which is the use of density clustering. This allows to separate areas of the face of non-uniform brightness from the image background, noise and outliers. It also allows clusters to have different shapes and sizes, to not require setting the number of clusters and additional parameters. To determine the scaling parameter, numerous studies were conducted in this work, which concluded that the dependence of the segmentation time on the scaling parameter is close to exponential. It was also found that for small P, where P is the scaling parameter, the quality of face detection deteriorates slightly. The proposed technique for face detection in image based on binarization, scaling and segmentation can be used in intelligent computer systems for biometric identification of a person by the face image

Measurement of electrons from heavy-flavour hadron decays as a function of multiplicity in p-Pb collisions at sqrt{s_{mathrm{NN}}} = 5.02 TeV

The multiplicity dependence of electron production from heavy-flavour hadron decays as a function of transverse momentum was measured in p-Pb collisions at sqrt{s_{mathrm{NN}}} = 5.02 TeV using the ALICE detector at the LHC. The measurement was performed in the centre-of-mass rapidity interval −1.07 < ycms< 0.14 and transverse momentum interval 2 < pT< 16 GeV/c. The multiplicity dependence of the production of electrons from heavy-flavour hadron decays was studied by comparing the pT spectra measured for different multiplicity classes with those measured in pp collisions (QpPb) and in peripheral p-Pb collisions (Qcp). The QpPb results obtained are consistent with unity within uncertainties in the measured pT interval and event classes. This indicates that heavy-flavour decay electron production is consistent with binary scaling and independent of the geometry of the collision system. Additionally, the results suggest that cold nuclear matter effects are negligible within uncertainties, in the production of heavy-flavour decay electrons at midrapidity in p-Pb collisions.

Measurement of electroweak boson production in pp, p+Pb and Pb+Pb collisions with the ATLAS detector

Measurement of electroweak boson production in different collision systems are of great interest to understanding the partonic structure of heavy nuclei, and serve as a constraint on the initial state in larger collision systems. Their production yields in Pb+Pb with respect to pp collisions provide direct tests of both binary collision scaling and possible modification of parton distribution functions (nPDF) due to nuclear effects. Further, the p+Pb collisions provide a relatively clean environment to study nPDFs in detail. The ATLAS detector has a broad acceptance with excellent performance even in the high occupancy environment of central heavy-ion collisions. In this proceedings the latest ATLAS results on W and Z boson production at the centre-of-mass energy of 5.02 TeV are presented, including updated precise result production in pp collisions. Also photon yields are reported in 8.16 TeV in different collision systems are presented.

Measurement and numerical simulation of shock standoff distances over hypersonic spheres in CO2 in a ballistic range

To gather test data of the nonequilibrium flow in CO2 and investigate the influence of the two-temperature nonequilibrium model on numerical simulations, measurements of shock standoff distances over hypersonic spheres in CO2 have been taken in the hypervelocity ballistic ranges of the Hypervelocity Aerodynamics Institute, China Aerodynamics Research and Development Center. Corresponding numerical simulations using the two-temperature model were also performed. The measurements were made for spheres with diameters of 10 mm and 20 mm, flight velocities between 2.122 and 4.220 km/s, and ambient pressures between 2.42 and 14.74 kPa. Test flow fields were visualized by the shadowgraphy for the measurement of shock standoff distances. The shock standoff distances generally decrease as ρR (freestream density × radius of the model, namely the binary scaling parameter) increases. The flow is mainly nonequilibrium when ρR is of the order of 10−4 kg/m2, and the two-temperature nonequilibrium model is applicable for the calculation of the flow field under such conditions. When ρR increases to the order of 10−3 kg/m2, the flow approaches the equilibrium state.

X-Ray Binary Luminosity Function Scaling Relations for Local Galaxies Based on Subgalactic Modeling

Abstract We present new Chandra constraints on the X-ray luminosity functions (XLFs) of X-ray binary (XRB) populations, as well as their scaling relations, for a sample of 38 nearby galaxies (D = 3.4–29 Mpc). Our galaxy sample is drawn primarily from the Spitzer Infrared Nearby Galaxies Survey (SINGS) and contains a wealth of Chandra (5.8 Ms total) and multiwavelength data, allowing for star formation rates (SFRs) and stellar masses (M ⋆) to be measured on subgalactic scales. We divided the 2478 X-ray-detected sources into 21 subsamples in bins of specific SFR (sSFR ≡ SFR/M ⋆) and constructed XLFs. To model the XLF dependence on sSFR, we fit a global XLF model, containing contributions from high-mass XRBs (HMXBs), low-mass XRBs (LMXBs), and background sources from the cosmic X-ray background that respectively scale with SFR, M ⋆, and sky area. We find an HMXB XLF that is more complex in shape than previously reported and an LMXB XLF that likely varies with sSFR, potentially due to an age dependence. When applying our global model to XLF data for each individual galaxy, we discover a few galaxy XLFs that significantly deviate from our model beyond statistical scatter. Most notably, relatively low-metallicity galaxies have an excess of HMXBs above ≈1038 erg s−1, and elliptical galaxies that have relatively rich populations of globular clusters (GCs) show excesses of LMXBs compared to the global model. Additional modeling of how the XRB XLF depends on stellar age, metallicity, and GC specific frequency is required to sufficiently characterize the XLFs of galaxies.

Measurement of W and Z Boson Production in 5 TeV pp, p+Pb and Pb+Pb Collisions with the ATLAS Detector

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Experimental evidence of the impact of radiation coupling on binary scaling applied to shock layer flows

Binary scaling is a similitude law used to study the aerothermodynamics of hypersonic vehicles in ground-based high-enthalpy facilities. It enables the duplication of shock layer flows in the vicinity of the stagnation point, including binary chemistry and nonequilibrium processes, over length scales that are practical for experimental testing. It is built on the assumption of a flow devoid of radiation coupling, which drastically narrows down the envelope of flows for which binary scaling can be used. Indeed, if it is strong enough, radiative heat transfer will cause a substantial amount of energy to leak out of the shock layer to the free-stream and other flow regions. As demonstrated in this paper, the strength of that coupling will increase as the length-scale of the flow increases, impacting other flow properties such as its chemical composition or temperature. The resulting impact on macroscopic features of the flow are for example a reduction of the wall heat flux (both convective and radiative) or of the shock standoff distance. These side impacts are identified with experimental measurements on the shock standoff distance in an expansion tube with CO2–N2 mixture flows representative of the venusian atmosphere over cylinders.

B -meson production at forward and backward rapidity in p+p and Cu + Au collisions at sNN=200 GeV

The fraction of $J/\psi$ mesons which come from B-meson decay, $\textrm{F}_{B{\rightarrow}J/\psi}$, is measured for J/$\psi$ rapidity \mbox{$1.2<|y|<2.2$} and $p_T>0$ in $p$+$p$ and Cu+Au collisions at $\sqrt{s_{_{NN}}}$=200 GeV with the PHENIX detector. The extracted fraction is $\textrm{F}_{B{\rightarrow}J/\psi}$ = 0.025 $\pm$ 0.006(stat) $\pm$ 0.010(syst) for $p$+$p$ collisions. For Cu+Au collisions, $\textrm{F}_{B{\rightarrow}J/\psi}$ is 0.094 $\pm$ 0.028(stat) $\pm$ 0.037(syst) in the Au-going direction ($-2.2<y<-1.2$) and 0.089 $\pm$ 0.026(stat) $\pm$ 0.040(syst) in the Cu-going direction ($1.2<y<2.2$). The nuclear modification factor, $R_{\rm CuAu}$, of B mesons in Cu+Au collisions is consistent with binary scaling of measured yields in $p$+$p$ at both forward and backward rapidity.

Binary Multidimensional Scaling for Hashing.

Hashing is a useful technique for fast nearest neighbor search due to its low storage cost and fast query speed. Unsupervised hashing aims at learning binary hash codes for the original features so that the pairwise distances can be best preserved. While several works have targeted on this task, the results are not satisfactory mainly due to the over-simplified model. In this paper, we propose a unified and concise unsupervised hashing framework, called binary multidimensional scaling, which is able to learn the hash code for distance preservation in both batch and online mode. In the batch mode, unlike most existing hashing methods, we do not need to simplify the model by predefining the form of hash map. Instead, we learn the binary codes directly based on the pairwise distances among the normalized original features by alternating minimization. This enables a stronger expressive power of the hash map. In the online mode, we consider the holistic distance relationship between current query example and those we have already learned, rather than only focusing on current data chunk. It is useful when the data come in a streaming fashion. Empirical results show that while being efficient for training, our algorithm outperforms state-of-the-art methods by a large margin in terms of distance preservation, which is practical for real-world applications.