BZPEERReading, trust and collaboration for research
Menu

Discover

GraphFollow connections around a paper, topic or saved view.

Workspaces

HomePick up where your research flow left off.InboxHandle requests, replies and notifications from one place.CollectionsCurate reading lists, evidence sets and shareable dossiers.ResearchSee your private provenance graph, trail and imports.CollaborationMove from discovery into focused discussion rooms.PublishDraft, preview and publish full-text research articles.

Network

ExpertsFind specialists worth following or asking for help.CommunitiesJoin research circles organized around shared work.PartnersSee external organizations active around the same topics.

Opportunities

ListingsBrowse roles, calls and collaborations with clearer fit signals.

Account

Log inReturn to your reading and collaboration workspace.Create accountStart saving work, following people and joining teams.
Log inCreate account

Researcher profile

Siyu Chen

Siyu Chen contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
cond-mat.mes-hallhep-phComputer Visioncond-mat.mtrl-scicond-mat.otherhep-exArtificial Intelligencephysics.comp-phphysics.opticsastro-ph.COastro-ph.HEBiological PhysicsCell BehaviorComputer Science and Game Theorycond-mat.softcond-mat.str-elcond-mat.supr-conecon.GNeess.SYhep-thInformation TheoryMachine Learningmath.ITMultiagent Systemsq-fin.ECSystems and Control

Trust snapshot

Quick read

Trust 21 - EmergingVerification L1Unclaimed author
20works
0followers
26topics
4close collaborators

Actions

Decide how to stay connected

Follow researcher0

Identity and collaboration

How to connect with this researcher

Claiming links this public author record to a researcher profile and unlocks direct collaboration workflows.

Log in to claim

Direct collaboration

Open a focused conversation when the fit is right

Claim this author entity first to unlock direct invitations.

Research graph

See the researcher in context

Open full explorer

Inspect adjacent work, topics, institutions and collaborators without jumping out to a separate graph page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Published work

20 published item(s)

preprint2026arXiv

Coexistence of trapped and flow-transported nuclei enables fast pigeon post communication across multinucleated cell

Multi-nucleated cells exist in all domains of life, ranging from animals, plants and fungi to single-celled organisms such as the slime mold Physarum polycephalum. The large cell size, in the case of Physarum reaching centimeters and more, challenges the coordination of nuclei activity as signals need to cross large distances. In search for a mechanism for fast long-ranged communication among nuclei, we quantify nuclei dynamics and cytoplasmic flows in Physarum's tubular network. We observe nuclei in two interchangeable, dynamic states: mobile, flowing within the cytoplasmic shuttle flow, or trapped in the tube's porous cell cortex. As we find nuclei to accumulate at the tube's inner fluid-porous interface we theoretically explore and confirm, with physiological parameters, that slowing down of mobile nuclei during flow is sufficient for diffusible signal exchange between mobile and trapped nuclei. We analytically derive that communication akin to pigeon-post with mobile nuclei serving as pigeons shuttling between trapped nuclei acting as waypoints, gives rise to signaling velocities that account for the rapid intracellular reorganization observed in Physarum. Since signal transfer by flow-transported nuclei outcompetes the mere diffusion of signals encoded in cytosolic proteins, pigeon-post communication surpasses alternative signaling mechanisms, even diffusive relay signaling up to twenty-fold in velocity. The key ingredients of pigeon-post communication, namely alternating flows and waypoints, exist in other multi-nucleated cells and may also be generalized beyond intracellular signaling.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

First Thin-Film Lithium Tantalate Polarization Controller Enabling Reset-Free Mrad/s Tracking for Optical Interconnects

The rapid escalation of computing power driven by large-scale artificial intelligence is placing unprecedented demands on the bandwidth, latency, and energy efficiency of data-center interconnects (DCIs). Self-homodyne coherent (SHC) transmission is a promising architecture because it preserves the spectral efficiency of coherent detection while greatly simplifying digital signal processing, but its practical deployment is critically limited by random and often ultrafast state-of-polarization (SOP) fluctuations that induce carrier fading and destabilize coherent reception. Here we report the first integrated polarization controller based on thin-film lithium tantalate (TFLT), enabling reset-free polarization tracking at Mrad/s speeds. The four-stage electro-optic device exhibits polarization-dependent loss (PDL) below 0.3 dB, a half-wave voltage below 2.5 V, high modulation bandwidth, and negligible DC drift. To accommodate the finite tuning range of integrated phase shifters, we develop a finite-boundary gradient-descent (FBGD) control algorithm that ensures reset-free SOP evolution with no phase jump. The implemented adaptive polarization controller (APC) is validated through both standalone polarization-tracking measurements and a dual-polarization 16-QAM SHC 400-Gbps transmission system. Transient polarization disturbances can be tracked at speeds up to 2 Mrad/s, while stable reset-free operation under continuous polarization disturbances is maintained up to 1 Mrad/s. This reset-free performance represents more than doubling the state of the art, while the pre-FEC bit-error rates remain below the HD-FEC threshold under realistic DCI conditions and lightning-scale polarization disturbances. These results establish TFLT as a new platform for ultrafast, low-power, reset-free, and drift-free polarization control in coherent optical interconnects and beyond.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Temporal Beam Self-Cleaning in Second-Harmonic Generation

The spatial-temporal beam quality of laser sources is crucial for applications such as nonlinear spectroscopy and master oscillator power amplification systems. However, the temporal stability remains challenged by issues like line-width broadening and high-power demand in efforts to improve it. In this work, we investigate the effect of the second-harmonic generation process on the laser characteristics under three longitudinal mode regimes: single-longitudinal-mode, dual-longitudinal-mode, and multi-longitudinal-mode. The results demonstrate that the second-harmonic generation process effectively stabilizes the temporal characteristics of the laser and enhances its correlation, leading to a temporally clean output beam. The physical mechanism of the observed temporal stabilization effect can be attributed to a high-peak-pulse attenuation effect, jointly induced by nonuniform longitudinal-mode depletion and phase preservation in the residual fundamental wave. Statistical analysis indicates that at the maximum fundamental-wave power in the multi-longitudinal-mode regime, the standard deviation and peak-to-valley values derived from the normalized temporal profile decrease from 0.6122 and 5.6846 for the fundamental wave to 0.189 and 0.8847 for the residual fundamental wave. Meanwhile, the background level of the intensity auto-correlation function rises from ~0.72 to ~0.96, revealing its evolution toward a more coherent state. To the best of our knowledge, this research presents the first demonstration of laser temporal stabilization and correlation enhancement via second-harmonic generation. It not only deepens the comprehension of second-harmonic generation mechanisms, but also opens up a new avenue for realizing temporal beam self-cleaning of light.

0 citations0 reviewsNo code linkedOpen access
preprint2025arXiv

Impact of electronic correlations on the superconductivity of high-pressure CeH$_9$

Rare-earth superhydrides have attracted considerable attention because of their high critical superconducting temperature under extreme pressures. They are known to have localized valence electrons, implying strong electronic correlations. However, such many-body effects are rarely included in first-principles studies of rare-earth superhydrides because of the complexity of their high-pressure phases. In this work, we use a combined density functional theory and dynamical mean-field theory approach to study both electrons and phonons in the prototypical rare-earth superhydride CeH$_9$, shedding light on the impact of electronic correlations on its critical temperature for phonon-mediated superconductivity. Our findings indicate that electronic correlations result in a larger electronic density at the Fermi level, a bigger superconducting gap, and softer vibrational modes associated with hydrogen atoms. Together, the inclusion of these correlation signatures increases the Migdal-Eliashberg superconducting critical temperature from 47 K to 96 K, close to the measured 95 K. Our results reconcile experimental observations and theoretical predictions for CeH$_9$ and herald a path towards the quantitative modeling of phonon-mediated superconductivity for interacting electron systems.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

Temperature effects in topological insulators of transition metal dichalcogenide monolayers

We investigate the role of temperature on the topological insulating state of metal dichalcogenide monolayers, 1T$^\prime$-MX$_2$ (M=W, Mo and X=S, Se). Using first principles calculations based on density functional theory, we consider three temperature-related contributions to the topological band gap: electrons coupling with short-wavelength phonons, with long-wavelength phonons \textit{via} Fröhlich coupling, and thermal expansion. We find that electron-phonon coupling promotes the topology of the electronic structures of all 1T$^\prime$-MX$_2$ monolayers, while thermal expansion acts as a counteracting effect. Additionally, we derive the band renormalization from Fröhlich coupling in the two-dimensional context and observe its relatively modest contribution to 1T$^\prime$-MX$_2$ monolayers. Finally, we present a simplified physical picture to understand the "inverse Varshni" effect driven by band inversion in topological insulators. Our work reveals that, among the four 1T$^\prime$-MX$_2$ studied monolayers, MoSe$_2$ is a promising candidate for room temperature applications as its band gap displays remarkable resilience against thermal expansion, while the topological order of WS$_2$ can be tuned under the combined influence of strain and temperature. Both materials represent novel examples of temperature promoted topological insulators.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

INTERN: A New Learning Paradigm Towards General Vision

Enormous waves of technological innovations over the past several years, marked by the advances in AI technologies, are profoundly reshaping the industry and the society. However, down the road, a key challenge awaits us, that is, our capability of meeting rapidly-growing scenario-specific demands is severely limited by the cost of acquiring a commensurate amount of training data. This difficult situation is in essence due to limitations of the mainstream learning paradigm: we need to train a new model for each new scenario, based on a large quantity of well-annotated data and commonly from scratch. In tackling this fundamental problem, we move beyond and develop a new learning paradigm named INTERN. By learning with supervisory signals from multiple sources in multiple stages, the model being trained will develop strong generalizability. We evaluate our model on 26 well-known datasets that cover four categories of tasks in computer vision. In most cases, our models, adapted with only 10% of the training data in the target domain, outperform the counterparts trained with the full set of data, often by a significant margin. This is an important step towards a promising prospect where such a model with general vision capability can dramatically reduce our reliance on data, thus expediting the adoption of AI technologies. Furthermore, revolving around our new paradigm, we also introduce a new data system, a new architecture, and a new benchmark, which, together, form a general vision ecosystem to support its future development in an open and inclusive manner. See project website at https://opengvlab.shlab.org.cn .

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Learning from Radiation at a Very High Energy Lepton Collider

We study the potential of lepton collisions with about $10\text{ TeV}$ center of mass energy to probe Electroweak, Higgs and Top short-distance physics at the $100\text{ TeV}$ scale, pointing out the interplay with the long-distance ($100\text{ GeV}$) phenomenon of Electroweak radiation. On one hand, we find that sufficiently accurate theoretical predictions require the resummed inclusion of radiation effects, which we perform at the double logarithmic order. On the other hand, we notice that short-distance physics does influence the emission of Electroweak radiation. Therefore the investigation of the radiation pattern can enhance the sensitivity to new short-distance physical laws. We illustrate these aspects by studying Effective Field Theory contact interactions in di-fermion and di-boson production, and comparing cross-section measurements that require or that exclude the emission of massive Electroweak bosons. The combination of the two types of measurements is found to enhance the sensitivity to the new interactions. Based on these results, we perform sensitivity projections to Higgs and Top Compositeness and to minimal $Z'$ new physics scenarios at future muon colliders.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Market Design for Tradable Mobility Credits

Tradable mobility credit (TMC) schemes are an approach to travel demand management that have received significant attention in recent years. This paper proposes and analyzes alternative market models for a TMC system -- focusing on market design aspects such as allocation/expiration of tokens, rules governing trading, transaction fees, and regulator intervention -- and develops a methodology to explicitly model the dis-aggregate behavior of individuals within the market. Extensive simulation experiments are conducted within a combined mode and departure time context for the morning commute problem to compare the performance of the alternative designs relative to congestion pricing and a no-control scenario. The simulation experiments employ a day-to-day assignment framework wherein transportation demand is modeled using a logit-mixture model with income effects and supply is modeled using a standard bottleneck model. The results indicate that small fixed transaction fees can effectively mitigate undesirable behavior in the market without a significant loss in efficiency (total welfare) whereas proportional transaction fees are less effective both in terms of efficiency and in avoiding undesirable market behavior. Further, an allocation of tokens in continuous time can be beneficial in dealing with non-recurrent events and avoiding concentrated trading activity. In the presence of income effects, despite small fixed transaction fees, the TMC system yields a marginally higher social welfare than congestion pricing while attaining revenue neutrality. Further, it is more robust in the presence of forecasting errors and non-recurrent events due to the adaptiveness of the market. Finally, as expected, the TMC scheme is more equitable (when revenues from congestion pricing are not redistributed) although it is not guaranteed to be Pareto-improving when tokens are distributed equally.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Near Interference-Free Space-Time User Scheduling for MmWave Cellular Network

The highly directional beams applied in millimeter wave (mmWave) cellular networks make it possible to achieve near interference-free (NIF) transmission under judiciously designed space-time user scheduling, where the power of intra-/inter-cell interference between any two users is below a predefined threshold. In this paper, we investigate two aspects of the NIF space-time user scheduling in a multi-cell mmWave network with multi-RF-chain base stations. Firstly, given that each user has a requirement on the number of space-time resource elements, we study the NIF user scheduling problem to minimize the unfulfilled user requirements, so that the space-time resources can be utilized most efficiently and meanwhile all strong interferences are avoided. A near-optimal scheduling algorithm is proposed with performance close to the lower bound of unfulfilled requirements. Furthermore, we study the joint NIF user scheduling and power allocation problem to minimize the power consumption under the constraint of rate requirements. Based on our proposed NIF scheduling, an energy-efficient joint scheduling and power allocation scheme is designed with limited channel state information, which outperforms the existing independent set based schemes, and has near-optimal performance as well.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Nonuniform grids for Brillouin zone integration and interpolation

We present two developments for the numerical integration of a function over the Brillouin zone. First, we introduce a nonuniform grid, which we refer to as the Farey grid, that generalizes regular grids. Second, we introduce symmetry-adapted Voronoi tessellation, a general technique to assign weights to the points in an arbitrary grid. Combining these two developments, we propose a strategy to perform Brillouin zone integration and interpolation that provides a significant computational advantage compared to the usual approach based on regular uniform grids. We demonstrate our methodology in the context of first principles calculations with the study of Kohn anomalies in the phonon dispersions of graphene and MgB2, and in the evaluation of the electron-phonon driven renormalization of the band gaps of diamond and bismuthene. In the phonon calculations, we find speedups by a factor of 3 to 4 when using density functional perturbation theory, and by a factor of 6 to 7 when using finite differences in conjunction with supercells. As a result, the computational expense between density functional perturbation theory and finite differences becomes comparable. For electron-phonon coupling calculations we find even larger speedups. Finally, we also demonstrate that the Farey grid can be expressed as a combination of the widely used regular grids, which should facilitate the adoption of this methodology.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Revisiting the constraints on primordial black hole abundance with the isotropic gamma ray background

We revisit the constraints on primordial black holes (PBHs) in the mass range $10^{13}-10^{18}$ g by comparing the 100\,keV-5\,GeV gamma-ray background with isotropic flux from PBH Hawking radiation (HR). We investigate three effects that may update the constraints on the PBH abundance; i) reliably calculating the secondary spectra of HR for energy below 5\,GeV, ii) the contributions to the measured isotropic flux from the Galactic PBH HR and that from annihilation radiation due to evaporated positrons, iii) inclusion of astrophysical background from gamma-ray sources. The conservative constraint is significantly improved by more than an order of magnitude at $2\times10^{16}$g$\lesssim M\lesssim 10^{17}$g over the past relevant work, where the effect ii is dominant. After further accounting for the astrophysical background, more than a tenfold improvement extends to a much wider mass range $10^{15}$g$\lesssim M\lesssim 2\times 10^{17}$g.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

The physics case of a 3 TeV muon collider stage

In the path towards a muon collider with center of mass energy of 10 TeV or more, a stage at 3 TeV emerges as an appealing option. Reviewing the physics potential of such muon collider is the main purpose of this document. In order to outline the progression of the physics performances across the stages, a few sensitivity projections for higher energy are also presented. There are many opportunities for probing new physics at a 3 TeV muon collider. Some of them are in common with the extensively documented physics case of the CLIC 3 TeV energy stage, and include measuring the Higgs trilinear coupling and testing the possible composite nature of the Higgs boson and of the top quark at the 20 TeV scale. Other opportunities are unique of a 3 TeV muon collider, and stem from the fact that muons are collided rather than electrons. This is exemplified by studying the potential to explore the microscopic origin of the current $g$-2 and $B$-physics anomalies, which are both related with muons.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

X-Learner: Learning Cross Sources and Tasks for Universal Visual Representation

In computer vision, pre-training models based on largescale supervised learning have been proven effective over the past few years. However, existing works mostly focus on learning from individual task with single data source (e.g., ImageNet for classification or COCO for detection). This restricted form limits their generalizability and usability due to the lack of vast semantic information from various tasks and data sources. Here, we demonstrate that jointly learning from heterogeneous tasks and multiple data sources contributes to universal visual representation, leading to better transferring results of various downstream tasks. Thus, learning how to bridge the gaps among different tasks and data sources is the key, but it still remains an open question. In this work, we propose a representation learning framework called X-Learner, which learns the universal feature of multiple vision tasks supervised by various sources, with expansion and squeeze stage: 1) Expansion Stage: X-Learner learns the task-specific feature to alleviate task interference and enrich the representation by reconciliation layer. 2) Squeeze Stage: X-Learner condenses the model to a reasonable size and learns the universal and generalizable representation for various tasks transferring. Extensive experiments demonstrate that X-Learner achieves strong performance on different tasks without extra annotations, modalities and computational costs compared to existing representation learning methods. Notably, a single X-Learner model shows remarkable gains of 3.0%, 3.3% and 1.8% over current pretrained models on 12 downstream datasets for classification, object detection and semantic segmentation.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Managing network congestion with a tradable credit scheme: a trip-based MFD approach

This study investigates the efficiency and effectiveness of an area-based tradable credit scheme (TCS) using the trip-based Macroscopic Fundamental Diagram model for the morning commute problem. In the proposed TCS, the regulator distributes initial credits to all travelers and designs a time-varying and trip length specific credit tariff. Credits are traded between travelers and the regulator via a credit market, and the credit price is determined by the demand and supply of credits. The heterogeneity of travelers is considered in terms of desired arrival time, trip length and departure-time choice preferences. The TCS is incorporated into a day-to-day modelling framework to examine the travelers' learning process, the evolution of network, and the properties of the credit market. The existence of an equilibrium solution and the uniqueness of the credit price at the equilibrium state are established analytically. Furthermore, an open-source simulation framework is developed to validate the analytical properties of the proposed TCS and compare it with alternative control strategies in terms of mobility, network performance, and social welfare. Bayesian optimization is then adopted to optimize the credit toll scheme. The numerical results demonstrate that the proposed TCS outperforms the no-control case and matches the performance of the time-of-day pricing strategy, while maintaining revenue-neutral nature.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Manipulation and braiding of Weyl nodes using symmetry-constrained phase transitions

Weyl semimetals are arguably the most paradigmatic form of a gapless topological phase. While the stability of Weyl nodes, as quantified by their topological charge, has been extensively investigated, recent interest has shifted to the manipulation of the location of these Weyl nodes for non-Abelian braiding. To accomplish this braiding it is necessary to drive significant Weyl node motion using realistic experimental parameter changes. We show that a family of phase transitions characterized by certain symmetry constraints impose that the Weyl nodes have to reorganise by a large amount, shifting from one high symmetry plane to another. Additionally, for a subset of pairs of nodes with nontrivial Euler class topology, this reorganization can only occur through a braiding process with adjacent nodes. As a result, the Weyl nodes are forced to move a large distance across the Brillouin zone and to braid, all driven by small temperature changes, a process we illustrate with Cd$_2$Re$_2$O$_7$. Our work opens up routes to readily manipulate Weyl nodes using only slight external parameter changes, paving the way for the practical realization of reciprocal space braiding.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020

This technical report introduces our winning solution to the spatio-temporal action localization track, AVA-Kinetics Crossover, in ActivityNet Challenge 2020. Our entry is mainly based on Actor-Context-Actor Relation Network. We describe technical details for the new AVA-Kinetics dataset, together with some experimental results. Without any bells and whistles, we achieved 39.62 mAP on the test set of AVA-Kinetics, which outperforms other entries by a large margin. Code will be available at: https://github.com/Siyu-C/ACAR-Net.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Parametrized classifiers for optimal EFT sensitivity

We study unbinned multivariate analysis techniques, based on Statistical Learning, for indirect new physics searches at the LHC in the Effective Field Theory framework. We focus in particular on high-energy $ZW$ production with fully leptonic decays, modeled at different degrees of refinement up to NLO in QCD. We show that a considerable gain in sensitivity is possible compared with current projections based on binned analyses. As expected, the gain is particularly significant for those operators that display a complex pattern of interference with the Standard Model amplitude. The most effective method is found to be the "Quadratic Classifier" approach, an improvement of the standard Statistical Learning classifier where the quadratic dependence of the differential cross section on the EFT Wilson coefficients is built-in and incorporated in the loss function. We argue that the Quadratic Classifier performances are nearly statistically optimal, based on a rigorous notion of optimality that we can establish for an approximate analytic description of the $ZW$ process.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

RANDOM MASK: Towards Robust Convolutional Neural Networks

Robustness of neural networks has recently been highlighted by the adversarial examples, i.e., inputs added with well-designed perturbations which are imperceptible to humans but can cause the network to give incorrect outputs. In this paper, we design a new CNN architecture that by itself has good robustness. We introduce a simple but powerful technique, Random Mask, to modify existing CNN structures. We show that CNN with Random Mask achieves state-of-the-art performance against black-box adversarial attacks without applying any adversarial training. We next investigate the adversarial examples which 'fool' a CNN with Random Mask. Surprisingly, we find that these adversarial examples often 'fool' humans as well. This raises fundamental questions on how to define adversarial examples and robustness properly.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Thermal Regelation of a Single Particle

In this paper we study the process termed thermal regelation at single particle level. We experimentally extract the physical parameters that determine the interactions between ice and the silica particle for the regelation process. As the premelted layer around the particle plays a key role here, we use the extracted parameters to calculate the thickness of this thin premelted layer, at different given particle sizes.

0 citations0 reviewsNo code linkedOpen access