arXiv subjects

Xiaohui Liu

Publications and source records attributed to Xiaohui Liu.

At least 55 records · Page 3Linked to original sources

arXiv2024

Shedding Light on Hadronization by Quarkonium Energy Correlator

We propose to measure the energy correlator in quarkonium production, which tracks the energy deposited in the calorimeter $χ$-angular distance away from the identified quarkonium. The observable eliminates the need for jets while sustaining the perturbative predictive power. Analyzing the power correction to the energy correlator, we demonstrate the novel observable supplies a unique gateway to probing the hadronization, especially when $\cosχ\gtrsim 0$ in the quarkonium rest frame where the perturbative emissions are depleted due to the dead-cone effects. We expect the quarkonium energy correlator to add a new dimension to quarkonium studies.

hep-ph↗

arXiv2024

A kiloparsec-scale ordered magnetic field in a galaxy at z=5.6

Magnetic fields are widely observed in various astronomical contexts, yet much remains unknown about their significance across different systems and cosmic epochs. Our current knowledge of the evolution of magnetic fields is limited by scarce observations in the distant Universe, where galaxies have recently been found to be more evolved than most model predictions. To address this gap, we conducted rest-frame 131 um full-polarisation observations of dust emission in a strongly lensed dusty star-forming galaxy, SPT0346-52, at z=5.6, when the Universe was only 1 Gyr old. Dust grains can become aligned with local magnetic fields, resulting in the emission of linearly polarised thermal infrared radiation. Our observations have revealed a median polarisation level of $0.9\pm0.2$ percent with a variation of $\pm0.4$ percent across the 3 kpc extention, indicating the presence of large-scale ordered magnetic fields. The polarised dust emission is patchy, offset from the total dust emission and mostly overlaps with the [C II] emission at a velocity of about -150 km/s. The bimodal distribution of field orientations, their spatial distribution, and the connection with the cold gas kinematics further emphasise the complexity of the magnetic environment in this galaxy and the potential role of mergers in shaping its magnetic fields. Such early formation of ordered galactic magnetic fields also suggests that both small-scale and large-scale dynamos could be efficient in early galaxies. Continued observations of magnetic fields in early galaxies, as well as expanding surveys to a wider galaxy population, are essential for a comprehensive understanding of the prevalence and impact of magnetic fields in the evolving Universe.

astro-ph.GA↗

arXiv2024

Universality in the Near-Side Energy-Energy Correlator

We investigate the energy-energy correlator (EEC) of hadrons produced on the same side in $e^+e^-$ annihilation or in leading jets in $pp$ collisions. We observe a remarkable universality of the correlator. Using a non-perturbative transverse momentum dependent (TMD) fragmentation function to model the transition from the ``free-hadron" region to the perturbative collinear region, we are able to describe the near-side shapes and peaks over a wide range of energy for both the $e^+e^-$ annihilation and the $pp$ jet substructure measurements in terms of just two parameters. We present further predictions for the ratio of the projected three-point energy correlator to the EEC. The excellent agreement between our calculations and the experimental data may provide new insights into the role of non-perturbative physics for EECs, and suggests the possibility of exploring non-perturbative TMDs using theoretical tools developed for the energy correlators.

hep-ph↗

arXiv2024

Functional Adaptive Huber Linear Regression

Robust estimation has played an important role in statistical and machine learning. However, its applications to functional linear regression are still under-developed. In this paper, we focus on Huber's loss with a diverging robustness parameter which was previously used in parametric models. Compared to other robust methods such as median regression, the distinction is that the proposed method aims to estimate the conditional mean robustly, instead of estimating the conditional median. We only require $(1+κ)$-th moment assumption ($κ>0$) on the noise distribution, and the established error bounds match the optimal rate in the least-squares case as soon as $κ\ge 1$. We establish convergence rate in probability when the functional predictor has a finite 4-th moment, and finite-sample bound with exponential tail when the functional predictor is Gaussian, in terms of both prediction error and $L^2$ error. The results also extend to the case of functional estimation in a reproducing kernel Hilbert space (RKHS).

math.ST↗

arXiv2024

Long Range Energy-energy Correlator at the LHC

We study the forward-backward azimuthal angular correlations of hadrons in association with multi-particle production in the central rapidity region in proton-proton collisions at the LHC. We apply the nucleon energy-energy correlator framework, where the spinning gluon distribution introduces a nontrivial $\cos(2ϕ)$ asymmetries. We will demonstrate that the fundamental helicity structure of QCD amplitudes predicts a unique power counting rule: $\cos(2ϕ)$ asymmetry starts at ${O}(α_s^2)$ order for dijet, ${O}(α_s)$ for three jet and ${O}(1)$ for four (and more) jet productions. Our results will help us to understand the long standing puzzle of nearside ridge behavior observed in high multiplicity events of $pp$ collisions at the LHC.

hep-ph↗

arXiv2024

Field-Tunable Valley Coupling and Localization in a Dodecagonal Semiconductor Quasicrystal

Quasicrystals are characterized by atomic arrangements possessing long-range order without periodicity. Van der Waals (vdW) bilayers provide a unique opportunity to controllably vary atomic alignment between two layers from a periodic moiré crystal to an aperiodic quasicrystal. Here, we reveal a remarkable consequence of the unique atomic arrangement in a dodecagonal WSe2 quasicrystal: the K and Q valleys in separate layers are brought arbitrarily close in momentum space via higher-order Umklapp scatterings. A modest perpendicular electric field is sufficient to induce strong interlayer K-Q hybridization, manifested as a new hybrid excitonic doublet. Concurrently, we observe the disappearance of the trion resonance and attribute it to quasicrystal potential driven localization. Our findings highlight the remarkable attribute of incommensurate systems to bring any pair of momenta into close proximity, thereby introducing a novel aspect to valley engineering.

cond-mat.mtrl-sci↗

arXiv2024

The DIS 1-Jettiness Event Shape at N$^3$LL+${\cal O}(α_s^2)$

We present results for the $τ_1$ and $τ_{1a}$ 1-Jettiness global event shape distributions, for Deep Inelastic Scattering (DIS), at the N$^3$LL + ${\cal O}(α_s^2)$ level of accuracy. These event-shape distributions quantify and characterize the pattern of final state radiation in electron-nucleus collisions. They can be used as a probe of nuclear structure functions, nuclear medium effects in jet production, and for a precision extraction of the QCD strong coupling. The results presented here, along with the corresponding numerical codes, can be used for analyses with HERA data, in EIC simulation studies, and for eventual comparison with real EIC data.

hep-ph↗

arXiv2024

A camera system for real-time optical calibration of water-based neutrino telescopes

Calibrating the optical properties within the detection medium of a neutrino telescope is crucial for determining its angular resolution and energy scale. For the next generation of neutrino telescopes planned to be constructed in deep water, such as the TRopIcal DEep-sea Neutrino Telescope (TRIDENT), there are additional challenges due to the dynamic nature and potential non-uniformity of the water medium. This necessitates a real-time optical calibration system distributed throughout the large detector array. This study introduces a custom-designed CMOS camera system equipped with rapid image processing algorithms, providing a real-time optical calibration method for TRIDENT and other similar projects worldwide. In September 2021, the TRIDENT Pathfinder experiment (TRIDENT Explorer, T-REX for short) successfully deployed this camera system in the West Pacific Ocean at a depth of 3420 meters. Within 30 minutes, about 3000 images of the T-REX light source were captured, allowing for the in-situ measurement of seawater attenuation and absorption lengths under three wavelengths. This deep-sea experiment for the first time showcased a technical demonstration of a functioning camera calibration system in a dynamic neutrino telescope site, solidifying a substantial part of the calibration strategies for the future TRIDENT project.

physics.ins-det↗

arXiv2024

On the energy budget of starquake-induced repeating fast radio bursts

With a growing sample of fast radio bursts (FRBs), we investigate the energy budget of different power sources within the framework of magnetar starquake triggering mechanism. During a starquake, the energy can be released in any form through strain, magnetic, rotational, and gravitational energies. The strain energy can be converted from other three kinds of energy during starquakes. The following findings are revealed: 1. The crust can store free magnetic energy of $\sim10^{46}$ erg by existing toroidal fields, sustaining $10^6$ bursts with frequent starquakes occurring due to crustal instability. 2. The strain energy develops as a rigid object spins down, which can be released during a global starquake accompanied by a glitch. However, it takes a long time to accumulate enough strain energy via spindown. 3. The rotational energy of a magnetar with $P\lesssim0.1\rm\,s$ can match the energy and luminosity budget of FRBs. 4. The budget of the total gravitational energy is high, but the mechanism and efficiency of converting this energy to radiation deserve further exploration.

astro-ph.HE↗

arXiv2024

The FRB-searching pipeline of the Tianlai Cylinder Pathfinder Array

This paper presents the design, calibration, and survey strategy of the Fast Radio Burst (FRB) digital backend and its real-time data processing pipeline employed in the Tianlai Cylinder Pathfinder array. The array, consisting of three parallel cylindrical reflectors and equipped with 96 dual-polarization feeds, is a radio interferometer array designed for conducting drift scans of the northern celestial semi-sphere. The FRB digital backend enables the formation of 96 digital beams, effectively covering an area of approximately 40 square degrees with 3 dB beam. Our pipeline demonstrates the capability to make automatic search of FRBs, detecting at quasi-real-time and classify FRB candidates automatically. The current FRB searching pipeline has an overall recall rate of 88\%. During the commissioning phase, we successfully detected signals emitted by four well-known pulsars: PSR B0329+54, B2021+51, B0823+26, and B2020+28. We report the first discovery of an FRB by our array, designated as FRB 20220414A. We also investigate the optimal arrangement for the digitally formed beams to achieve maximum detection rate by numerical simulation.

astro-ph.IM↗

arXiv2024

Long Range Azimuthal Correlation, Entanglement and Bell Inequality Violation by Spinning Gluons at the LHC

We apply the recently developed concept of the nucleon energy-energy correlator (NEEC) for the gluon sector to investigate the long-range azimuthal angular correlations in proton-proton collisions at the LHC. The spinning gluon in these collisions will introduce a significant nonzero $\cos(2ϕ)$ asymmetries in both Higgs Boson and top quark pair productions. The genesis of the $\cos(2ϕ)$ correlation lies in the intricate quantum entanglement. Owing to the substantial $\cos(2ϕ)$ effect, the NEEC observable in Higgs Boson and $t{\bar t}$ production emerges as a pivotal avenue for delving into quantum entanglement and scrutinizing the Bell inequality at high-energy colliders.

hep-ph↗

arXiv2024

TMDs from Semi-inclusive Energy Correlators

We introduce a novel category of observables known as the Semi-Inclusive Energy Correlators (SIECs), an extension of the recently proposed nucleon energy correlator to integrate a new element, the fragmenting energy correlation function. These SIECs gauge the correlation between the examined hadron and the surrounding radiations, providing a comprehensive tomography of the radiative patterns originating from initial state radiation or parton fragmentation. As such, they could function as the generating functions for numerous kinematic distributions. To illustrate, we find a direct relation between the transverse momentum moments (TMMs) of the transverse momentum-dependent (TMD) distributions and the SIECs. We demonstrate how the TMMs of the TMD parton distributions and the fragmentation functions can be distinctively derived from the nucleon energy correlator and the fragmenting energy correlator, respectively, without enforcing the back-to-back kinematics.

hep-ph↗

arXiv2024

Double-Real-Virtual and Double-Virtual-Real Corrections to the Three-Loop Thrust Soft Function

We compute the ${\cal O}(α_s^3)$ double-real-virtual (RRV) and double-virtual-real (VVR) soft contributions to the thrust/zero-jettiness event shape. The result clears up one of the most stubborn obstacles toward the complete ${\cal O}(α_s^3)$ thrust soft function. The results presented here serve as the key input to realize the next-to-next-to-next-to-leading logarithmic prime (N${}^3$LL') % and even the next-to-next-to-next-to-next-to-leading logarithmic (N${}^4$LL) resummation of the thrust event shape. The obtained results also constitute the important ingredients of the $N$-jettiness-subtraction scheme at next-to-next-to-next-to-leading order (N${}^3$LO).

hep-ph↗

arXiv2024

Estimating and Mitigating the Congestion Effect of Curbside Pick-ups and Drop-offs: A Causal Inference Approach

Curb space is one of the busiest areas in urban road networks. Especially in recent years, the rapid increase of ride-hailing trips and commercial deliveries has induced massive pick-ups/drop-offs (PUDOs), which occupy the limited curb space that was designed and built decades ago. These PUDOs could jam curbside utilization and disturb the mainline traffic flow, evidently leading to significant negative societal externalities. However, there is a lack of an analytical framework that rigorously quantifies and mitigates the congestion effect of PUDOs in the system view, particularly with little data support and involvement of confounding effects. To bridge this research gap, this paper develops a rigorous causal inference approach to estimate the congestion effect of PUDOs on general regional networks. A causal graph is set to represent the spatio-temporal relationship between PUDOs and traffic speed, and a double and separated machine learning (DSML) method is proposed to quantify how PUDOs affect traffic congestion. Additionally, a re-routing formulation is developed and solved to encourage passenger walking and traffic flow re-routing to achieve system optimization. Numerical experiments are conducted using real-world data in the Manhattan area. On average, 100 additional units of PUDOs in a region could reduce the traffic speed by 3.70 and 4.54 mph on weekdays and weekends, respectively. Re-routing trips with PUDOs on curb space could respectively reduce the system-wide total travel time by 2.44% and 2.12% in Midtown and Central Park on weekdays. Sensitivity analysis is also conducted to demonstrate the effectiveness and robustness of the proposed framework.

cs.LG↗

arXiv2023

Learning Real-World Image De-Weathering with Imperfect Supervision

Real-world image de-weathering aims at removing various undesirable weather-related artifacts. Owing to the impossibility of capturing image pairs concurrently, existing real-world de-weathering datasets often exhibit inconsistent illumination, position, and textures between the ground-truth images and the input degraded images, resulting in imperfect supervision. Such non-ideal supervision negatively affects the training process of learning-based de-weathering methods. In this work, we attempt to address the problem with a unified solution for various inconsistencies. Specifically, inspired by information bottleneck theory, we first develop a Consistent Label Constructor (CLC) to generate a pseudo-label as consistent as possible with the input degraded image while removing most weather-related degradations. In particular, multiple adjacent frames of the current input are also fed into CLC to enhance the pseudo-label. Then we combine the original imperfect labels and pseudo-labels to jointly supervise the de-weathering model by the proposed Information Allocation Strategy (IAS). During testing, only the de-weathering model is used for inference. Experiments on two real-world de-weathering datasets show that our method helps existing de-weathering models achieve better performance. Codes are available at https://github.com/1180300419/imperfect-deweathering.

cs.CV↗

arXiv2023

AcademicGPT: Empowering Academic Research

Large Language Models (LLMs) have demonstrated exceptional capabilities across various natural language processing tasks. Yet, many of these advanced LLMs are tailored for broad, general-purpose applications. In this technical report, we introduce AcademicGPT, designed specifically to empower academic research. AcademicGPT is a continual training model derived from LLaMA2-70B. Our training corpus mainly consists of academic papers, thesis, content from some academic domain, high-quality Chinese data and others. While it may not be extensive in data scale, AcademicGPT marks our initial venture into a domain-specific GPT tailored for research area. We evaluate AcademicGPT on several established public benchmarks such as MMLU and CEval, as well as on some specialized academic benchmarks like PubMedQA, SCIEval, and our newly-created ComputerScienceQA, to demonstrate its ability from general knowledge ability, to Chinese ability, and to academic ability. Building upon AcademicGPT's foundation model, we also developed several applications catered to the academic area, including General Academic Question Answering, AI-assisted Paper Reading, Paper Review, and AI-assisted Title and Abstract Generation.

cs.CL↗

arXiv2023

Exploring Light-Cone Distribution Amplitudes from Quantum Computing

Light-cone distribution amplitudes (LCDAs) are essential nonperturbative quantities for theoretical predictions of exclusive high-energy processes in quantum chromodynamics (QCD). We demonstrate the prospect of calculating LCDAs on a quantum computer by applying a recently proposed quantum algorithm, with staggered fermions, to the simulation of the LCDA in the (1+1)-dimensional Nambu-Jona-Lasinio (NJL) model on classical hardware. The agreement between the result from the classical simulation of the quantum algorithm and that from exact diagonalization justifies the proposed quantum algorithm. We find that the resulting LCDA in the NJL model exhibits features shared with the LCDAs obtained from QCD.

hep-ph↗

arXiv2023

Partonic collinear structure by quantum computing

We present a systematic quantum algorithm, which integrates both the hadronic state preparation and the evaluation of real-time light-front correlators, to study parton distribution functions (PDFs). As a proof of concept, we demonstrate the first direct simulation of the PDFs in the 1+1 dimensional Nambu-Jona-Lasinio model. We show the results obtained by exact diagonalization and by quantum computation using classical hardware. The agreement between these two distinct methods and the qualitative consistency with QCD PDFs validate the proposed quantum algorithm. Our work suggests the encouraging prospects of calculating QCD PDFs on current and near-term quantum devices. The presented quantum algorithm is expected to have many applications in high energy particle and nuclear physics.

hep-ph↗