arXiv subjects

Xiaoyuan Zhang

Publications and source records attributed to Xiaoyuan Zhang.

At least 73 records · Page 4Linked to original sources

arXiv2024

UMOEA/D: A Multiobjective Evolutionary Algorithm for Uniform Pareto Objectives based on Decomposition

Multiobjective optimization (MOO) is prevalent in numerous applications, in which a Pareto front (PF) is constructed to display optima under various preferences. Previous methods commonly utilize the set of Pareto objectives (particles on the PF) to represent the entire PF. However, the empirical distribution of the Pareto objectives on the PF is rarely studied, which implicitly impedes the generation of diverse and representative Pareto objectives in previous methods. To bridge the gap, we suggest in this paper constructing \emph{uniformly distributed} Pareto objectives on the PF, so as to alleviate the limited diversity found in previous MOO approaches. We are the first to formally define the concept of ``uniformity" for an MOO problem. We optimize the maximal minimal distances on the Pareto front using a neural network, resulting in both asymptotically and non-asymptotically uniform Pareto objectives. Our proposed method is validated through experiments on real-world and synthetic problems, which demonstrates the efficacy in generating high-quality uniform Pareto objectives and the encouraging performance exceeding existing state-of-the-art methods. The detailed model implementation and the code are scheduled to be open-sourced upon publication.

cs.LG↗

arXiv2024

The SRG/eROSITA All-Sky Survey: Weak-Lensing of eRASS1 Galaxy Clusters in KiDS-1000 and Consistency Checks with DES Y3 & HSC-Y3

We aim to participate in the calibration of the X-ray photon count rate to halo mass scaling relation of galaxy clusters selected in the first eROSITA All-Sky Survey on the Western Galactic Hemisphere (eRASS1) using KiDS-1000 weak-lensing (WL) data. We measure the radial shear profiles around eRASS1 galaxy clusters using background galaxies in KiDS-1000, as well as the cluster member contamination. Furthermore we provide consistency checks with the other stage-III WL surveys who take part in the eRASS1 mass calibration, DES Y3 and HSC-Y3. We determine the cluster member contamination of eRASS1 clusters present in KiDS-1000 based on source number density profiles, where we account for the obscuration caused by cluster galaxies. The extracted shear profiles, together with the contamination model and the lens sample selection, are then analysed through a Bayesian population model. We calibrate the WL mass bias parameter by analysing realistic synthetic shear profiles from mock cluster catalogues. Our consistency checks between KiDS-1000 and DES Y3 & HSC-Y3 include the comparison of contamination-corrected density contrast profiles employing the union of background sources around common clusters, as well as the individual scaling relation results. We present a global contamination model for eRASS1 clusters in KiDS-1000 and the calibration results of the X-ray photon count rate to halo mass relation. The results of the WL mass bias parameter show that the uncertainty of the multiplicative shear bias dominates the systematic error budget at low clusters redshifts while the uncertainty of our contamination model does at high ones. The cross-checks between the three WL surveys show that they are statistically consistent with each other. This enables for the first time cosmological constraints from clusters calibrated by three state-of-the-art WL surveys. (abridged)

astro-ph.CO↗

arXiv2024

Three-point Energy Correlators in Hadronic Higgs Decays

We present the analytic calculation of the leading order three-point energy correlator (EEEC) in hadronic Higgs decays, including both gluon-initiated channel $H\rightarrow g g+X$ and quark-initiated channel $H\rightarrow q\bar q+X$. The phase space integration is evaluated directly using Mandelstam variables $s_{ij}=(p_i+p_j)^2$, and the appearing square roots can be rationalized by either conformal ratios or celestial coordinate variables. Throughout the calculation, we observe the same transcendental function space as in $\mathcal{N}=4$ super Yang-Mills (SYM) theory and $e^+e^-\rightarrow \text{ hadrons}$. Different infrared limits are also explored using the full analytic result, offering the fixed-order data for EEEC factorization and resummation. Given its non-trivial shape dependence, the EEEC presents an excellent opportunity to explore the dynamics of gluon jets originating from the $H \to gg$ decay channel at future lepton colliders.

hep-ph↗

arXiv2024

Three-point energy correlator in $\mathcal{N}=4$ super Yang-Mills Theory

An analytic formula is given for the three-point energy correlator (EEEC) at leading order (LO) in maximally supersymmetric Yang-Mills theory ($\mathcal{N}=4$ sYM). This is the first analytic calculation of a three-parameter event shape observable, which provides valuable data for various studies ranging from conformal field theories to jet substructure. The associated class of functions define a new type of single-valued polylogarithms characterized by 16 alphabet letters, which manifest a $D_6 \times Z_2$ dihedral symmetry of the event shape. With the unexplored simplicity in the perturbative structure of EEEC, all kinematic regions including collinear, squeezed and coplanar limits are now available.

hep-th↗

arXiv2023

Continuation Path Learning for Homotopy Optimization

Homotopy optimization is a traditional method to deal with a complicated optimization problem by solving a sequence of easy-to-hard surrogate subproblems. However, this method can be very sensitive to the continuation schedule design and might lead to a suboptimal solution to the original problem. In addition, the intermediate solutions, often ignored by classic homotopy optimization, could be useful for many real-world applications. In this work, we propose a novel model-based approach to learn the whole continuation path for homotopy optimization, which contains infinite intermediate solutions for any surrogate subproblems. Rather than the classic unidirectional easy-to-hard optimization, our method can simultaneously optimize the original problem and all surrogate subproblems in a collaborative manner. The proposed model also supports real-time generation of any intermediate solution, which could be desirable for many applications. Experimental studies on different problems show that our proposed method can significantly improve the performance of homotopy optimization and provide extra helpful information to support better decision-making.

cs.LG↗

arXiv2023

NNLL Resummation for Projected Three-Point Energy Correlator

The projected energy correlator measures the energy deposited in multiple detectors as a function of the largest angular distance $x_L = (1 - \cosχ_L)/2$ between detectors. The collinear limit $x_L\to 0$ of the projected energy correlator is particularly interesting for understanding the jet-substructures, while the large logarithms of $x_L$ could potentially spoil the perturbation theory and must be resummed. As a necessary ingredient for its resummation at next-to-next-to-leading logarithmic (NNLL) accuracy, we calculate the two-loop jet functions for the projected three-point energy correlator (E3C), using direct integration method and the parameter space Integration-by-Part (IBP) method. We then present the NNLL resummation for $e^+e^-$ annihilation and an approximate NNLL resummation for $pp\rightarrow jj$ process, where the two-loop hard constant is estimated in the latter case. The convergence is improved and the hadronization effect in the collinear limit is suppressed when considering the ratio of E3C distribution to two-point energy-energy correlator (EEC). Our results show potential in precision determination of strong coupling constant using energy correlators from both $e^+e^-$ data and $pp$ data.

hep-ph↗

arXiv2023

NNLL Resummation of Sudakov Shoulder Logarithms in the Heavy Jet Mass Distribution

The heavy jet mass event shape has large perturbative logarithms near the leading order kinematic threshold at $ρ= \frac{1}{3}$. Catani and Webber named these logarithms Sudakov shoulders and resummed them at double-logarithmic level. A resummation to next-to-leading logarithmic level was achieved recently. Here, we extend the resummation using an effective field theory framework to next-to-next-to-leading logarithmic order and show how to combine it with the resummation of dijet logarithms. We also solve the open problem of an unphysical singularity in the resummed momentum space distribution, in a way similar to how it is resolved in the Drell-Yan $q_T$ spectrum: through a careful analysis of the kinematics and scale-setting in position space. The heavy jet mass Sudakov shoulder is the first observable that does not involve transverse momentum for which position space resummation is critical. These advances may lead to a more precise extraction of the strong coupling constant from $e^+ e^-$ data.

hep-ph↗

arXiv2023

The eROSITA Final Equatorial-Depth Survey (eFEDS): A Machine Learning Approach to Infer Galaxy Cluster Masses from eROSITA X-ray Images

We develop a neural network based pipeline to estimate masses of galaxy clusters with a known redshift directly from photon information in X-rays. Our neural networks are trained using supervised learning on simulations of eROSITA observations, focusing in this paper on the Final Equatorial Depth Survey (eFEDS). We use convolutional neural networks which are modified to include additional information of the cluster, in particular its redshift. In contrast to existing work, we utilize simulations including background and point sources to develop a tool which is usable directly on observational eROSITA data for an extended mass range from group size halos to massive clusters with masses in between $10^{13}M_\odot<M<10^{15}M_\odot.$ Using this method, we are able to provide for the first time neural network mass estimation for the observed eFEDS cluster sample from Spectrum-Roentgen-Gamma/eROSITA observations and we find consistent performance with weak lensing calibrated masses. In this measurement, we do not use weak lensing information and we only use previous cluster mass information which was used to calibrate the cluster properties in the simulations. When compared to simulated data, we observe a reduced scatter with respect to luminosity and count-rate based scaling relations. We comment on the application for other upcoming eROSITA All-Sky Survey observations.

astro-ph.CO↗

arXiv2022

The NuSTAR and Chandra view of CL 0217+70 and Its Tell-Tale Radio Halo

Mergers of galaxy clusters are the most energetic events in the universe, driving shock and cold fronts, generating turbulence, and accelerating particles that create radio halos and relics. The galaxy cluster CL 0217+70 is a remarkable late stage merger, with a double peripheral radio relic and a giant radio halo. A Chandra study detects surface brightness edges that correspond to radio features within the halo. In this work, we present a study of this cluster with NuSTAR and Chandra data using spectro-imaging methods. The global temperature is found to be kT = 9.1 keV. We set an upper limit for the IC flux of ~2.7x10^(-12) erg s^(-1) cm^(-2), and a lower limit to the magnetic field of 0.08 microG. Our local IC search revealed a possibility that IC emission may have a significant contribution at the outskirts of a radio halo emission and on/near shock regions within ~0.6 r500 of clusters. We detected a "hot spot" feature in our temperature map coincident a surface brightness edge, but our investigation on its origin is inconclusive. If the "hot spot" is the downstream of a shock, we set a lower limit of kT > 21 keV to the plasma, that corresponds to M~2. We found three shock fronts within 0.5 r500. Multiple weak shocks within the cluster center hint at an ongoing merger activity and continued feeding of the giant radio halo. CL 0217+70 is the only example hosting these secondary shocks in multiple form.

astro-ph.HE↗

arXiv2022

Sudakov Shoulder Resummation for Thrust and Heavy Jet Mass

When the allowed range of an observable grows order-by-order in perturbation theory, its perturbative expansion can have discontinuities (as in the $C$ parameter) or discontinuities in its derivatives (as in thrust or heavy jet mass) called Sudakov shoulders. We explore the origin of these logarithms using both perturbation theory and effective field theory. We show that for thrust and heavy jet mass, the logarithms arise from kinematic configurations with narrow jets and deduce the next-to-leading logarithmic series. The left-shoulder logarithms in heavy jet mass ($ρ$) of the form $r\ α_s^n \ln^{2n}r $ with $r=\frac{1}{3}-ρ$ are particularly dangerous, because they invalidate fixed order perturbation theory in regions traditionally used to extract $α_s$. Although the factorization formula shows there are no non-global logarithms, we find Landau-pole like singularities in the resummed distribution associated with the cusp anomalous dimension, and that power corrections are exceptionally important.

hep-ph↗

arXiv2022

Pareto Set Learning for Expensive Multi-Objective Optimization

Expensive multi-objective optimization problems can be found in many real-world applications, where their objective function evaluations involve expensive computations or physical experiments. It is desirable to obtain an approximate Pareto front with a limited evaluation budget. Multi-objective Bayesian optimization (MOBO) has been widely used for finding a finite set of Pareto optimal solutions. However, it is well-known that the whole Pareto set is on a continuous manifold and can contain infinite solutions. The structural properties of the Pareto set are not well exploited in existing MOBO methods, and the finite-set approximation may not contain the most preferred solution(s) for decision-makers. This paper develops a novel learning-based method to approximate the whole Pareto set for MOBO, which generalizes the decomposition-based multi-objective optimization algorithm (MOEA/D) from finite populations to models. We design a simple and powerful acquisition search method based on the learned Pareto set, which naturally supports batch evaluation. In addition, with our proposed model, decision-makers can readily explore any trade-off area in the approximate Pareto set for flexible decision-making. This work represents the first attempt to model the Pareto set for expensive multi-objective optimization. Experimental results on different synthetic and real-world problems demonstrate the effectiveness of our proposed method.

cs.NE↗

arXiv2022

Analytic Computation of Three-point Energy Correlator in QCD

The energy correlator measures the energy deposited in multiple detectors as a function of the angles among them. In this paper, an analytic formula is given for the three-point energy correlator with full angle dependence at leading order in electron-positron annihilation. This is the first analytic computation of trijet event shape observables in QCD, which provides valuable data for phenomenological studies. The result is computed with direct integration, where appropriate parameterizations of both phase space and kinematic space are adopted to simplify the calculation. With full shape dependence, our result provides the expansions in various kinematic regions such as equilateral, triple collinear and squeezed limits, which benefit studies on both factorization and large logarithm resummation.

hep-ph↗

arXiv2022

A novel MDPSO-SVR hybrid model for feature selection in electricity consumption forecasting

Electricity consumption forecasting has vital importance for the energy planning of a country. Of the enabling machine learning models, support vector regression (SVR) has been widely used to set up forecasting models due to its superior generalization for unseen data. However, one key procedure for the predictive modeling is feature selection, which might hurt the prediction accuracy if improper features were selected. In this regard, a modified discrete particle swarm optimization (MDPSO) was employed for feature selection in this study, and then MDPSO-SVR hybrid mode was built to predict future electricity consumption. Compared with other well-established counterparts, MDPSO-SVR model consistently performs best in two real-world electricity consumption datasets, which indicates that MDPSO for feature selection can improve the prediction accuracy and the SVR equipped with the MDPSO can be a promised alternative for electricity consumption forecasting.

cs.NE↗

arXiv2022

Simplifying Polylogarithms with Machine Learning

Polylogrithmic functions, such as the logarithm or dilogarithm, satisfy a number of algebraic identities. For the logarithm, all the identities follow from the product rule. For the dilogarithm and higher-weight classical polylogarithms, the identities can involve five functions or more. In many calculations relevant to particle physics, complicated combinations of polylogarithms often arise from Feynman integrals. Although the initial expressions resulting from the integration usually simplify, it is often difficult to know which identities to apply and in what order. To address this bottleneck, we explore to what extent machine learning methods can help. We consider both a reinforcement learning approach, where the identities are analogous to moves in a game, and a transformer network approach, where the problem is viewed analogously to a language-translation task. While both methods are effective, the transformer network appears more powerful and holds promise for practical use in symbolic manipulation tasks in mathematical physics.

cs.LG↗

arXiv2022

On Function Spaces Related to H-sober Spaces

In this paper, we mainly study the function spaces related to H-sober spaces. For an irreducible subset system H and $T_{0}$ spaces $X$ and $Y$, it is proved that $Y$ is H-sober iff the function space $\mathbb{C}(X, Y)$ of all continuous functions $f : X\longrightarrow Y$ equipped with the topology of pointwise convergence is H-sober iff the function space $\mathbb{C}(X, Y)$ equipped with the Isbell topology is H-sober. One immediate corollary is that for a $T_{0}$ space $X$, $Y$ is a sober space (resp., $d$-space, well-filtered space) iff the function space $\mathbb{C}(X, Y)$ equipped with the topology of pointwise convergence is a sober space (resp., $d$-space, well-filtered space) iff the function space $\mathbb{C}(X, Y)$ equipped with the the Isbell topology is a sober space (resp., $d$-space, well-filtered space). It is shown that $T_{0}$ spaces $X$ and $Y$, if the function space $\mathbb{C}(X, Y)$ equipped with the compact-open topology is H-sober, then $Y$ is H-sober. The function space $\mathbb{C}(X, Y)$ equipped with the Scott topology is also discussed.

math.GN↗

arXiv2021

Intra-day variability of BL Lacertae from 2016 to 2018

We monitored BL Lacertae in the B, V, R and I bands for 14 nights during the period of 2016-2018. The source showed significant intraday variability on 12 nights. We performed colour-magnitude analysis and found that the source exhibited bluer-when-brighter chromatism. This bluer-when-brighter behavior is at least partly caused by the larger variation amplitude at shorter wavelength. The variations at different wavelengths are well correlated and show no inter-band time lag.

astro-ph.GA↗

arXiv2021

A shock near the virial radius of the Perseus Cluster

Previous X-ray studies of the Perseus Cluster, consisting of 85 Suzaku pointings along eight azimuthal directions, revealed a particularly steep decrease in the projected temperature profile near the virial radius (~r200) towards the northwest (NW). To further explore this shock candidate, another 4 Suzaku observations on the NW edge of the Perseus Cluster have been obtained. These deeper data were designed to provide the best possible control of systematic uncertainties in the spectral analysis. Using the combined Suzaku observations, we have carefully investigated this interesting region by analyzing the spectra of various annuli and extracting projected thermodynamic profiles. We find that the projected temperature profile shows a break near r200, indicating a shock with M = 1.9+-0.3. Corresponding discontinuities are also found in the projected emission measure and the density profiles at the same location. This evidence of a shock front so far away from the cluster center is unprecedented, and may provide a first insight into the properties of large-scale virial shocks which shape the process of galaxy cluster growth.

astro-ph.HE↗

arXiv2021

The Compton Scattering Total Cross Section at Next-to-Leading Order

An analytic formula is given for the total scattering cross section of an electron and a photon at order $α^3$. This includes both the double-Compton scattering real-emission contribution as well as the virtual Compton scattering part. When combined with the recent analytic result for the pair-production cross section, the complete $α^3$ cross section is now known. Both the next-to-leading order calculation as well as the pair-production cross section are computed using modern multiloop calculation techniques, where cut diagrams are decomposed into a set of master integrals that are then computed using differential equations.

hep-ph↗