arXiv subjects

J. Zhu

Publications and source records attributed to J. Zhu.

At least 19 recordsLinked to original sources

arXiv2026

Scalable Bayesian data curation for next-generation radio experiments

Next-generation radio telescopes produce data volumes that preclude manual quality assessment, yet data curation remains essential for science. We present a general, fully automatic Bayesian anomaly-detection method for radio science experiments in which data curation is performed inside the inference: a latent anomaly indicator is marginalised in the likelihood rather than converted into an external pre-flag. Implemented in JAX with GPU-accelerated inference, the pipeline assigns probabilistic data-curation scores without prior knowledge and requires no thresholds, manual inspection, or subjective decisions. We demonstrate the method on the Radio Experiment for the Analysis of Cosmic Hydrogen (REACH), applying it to 4655 observations (one year of REACH data). The pipeline assigns scores across time and frequency, enabling identification of the optimal observations to carry forward into scientific inference while reducing the risk that contaminated data bias the result. In doing so, it simultaneously recovers weather-driven systematics, instrument-component drifts, and narrow-band radio-frequency interference, while revealing complex dependencies between data quality and environmental or instrumental state that would be difficult to uncover by manual curation alone. This turns data curation from an external manual bottleneck into autonomous, inference-level infrastructure for the Square Kilometre Array era.

astro-ph.IM↗

arXiv2026

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos

Without incurring significant computational overhead, train-free long video generation aims to enable foundation video generation models to produce longer videos. Frame-level autoregressive frameworks, e.g., FIFO-diffusion, offer the advantage of generating infinitely long videos with constant memory consumption. However, the mismatch between training and inference, coupled with the challenge of maintaining long-term consistency, limits the effective utilization of foundation models. To mitigate these concerns, we propose \textbf{MIGA}, a novel infinite-frame long video generation method. Firstly, we propose an effective two-stage alignment mechanism that mitigates the training-inference gap by reducing the excessive noise span fed to the model. We then introduce an innovative dual consistency enhancement mechanism, where the self-reflection approach corrects early high-noise frames and the long-range frame guidance approach leverages later low-noise frames with broad coverage to steer generation, jointly improving temporal consistency. Extensive experiments on VBench and NarrLV demonstrate the state-of-the-art performance of MIGA. Our project page is available at https://xiaokunfeng.github.io/miga_homepage/.

cs.CV↗

arXiv2026

Shot noise generated by subpopulations of neural networks

While recent advances in next-generation neural mass models provide exact descriptions of densely coupled neural populations in the thermodynamic limit, populations in vivo remain strictly finite in size. Finite-size effects introduce stochastic fluctuations whose impact on network dynamics depends on their spectral content. Furthermore, coupling between different populations is typically sparse, meaning that only a small, random subset of neurons from one population projects connections to another. This subset (a subpopulation) produces an output signal that is inherently noisy. Given that the subpopulation constitutes only a fraction of the full population, its shot noise differs from that of the whole population in both intensity and spectral shape. In the present work, we analyze these differences and demonstrate that they depend non-trivially on subpopulation size. Using a generalization of our nesting method, we derive an analytical expression for the power spectral density of subpopulation shot noise, which shows excellent agreement with direct numerical simulations. Unlike many previous studies that rely on mathematically convenient but unrealistic Lorentzian distributions (with diverging moments), our approach accounts for more realistic, non-Lorentzian distributions of local neuron parameters using a previously developed reduction technique. These results provide a foundation for a new class of stochastic mean-field models for hierarchical neural networks. Such models can now incorporate the correct, size-dependent frequency spectrum of subpopulation shot noise. Crucially, this spectrum is not a simple scaled version of the full population's noise. Instead, it arises from a non-trivial mixture of two distinct spectral components. This is essential for networks with dense local connectivity and sparse inter-population connectivity.

nlin.CD↗

arXiv2026

Approximating Convex Hulls via Range Queries

Recently, motivated by the rapid increase of the data size in various applications, Monemizadeh [APPROX'23] and Driemel, Monemizadeh, Oh, Staals, and Woodruff [SoCG'25] studied geometric problems in the setting where the only access to the input point set is via querying a range-search oracle. Algorithms in this setting are evaluated on two criteria: (i) the number of queries to the oracle and (ii) the error of the output. In this paper, we continue this line of research and investigate one of the most fundamental geometric problems in the oracle setting, i.e., the convex hull problem. Let $P$ be an unknown set of points in $[0,1]^d$ equipped with a range-emptiness oracle. Via querying the oracle, the algorithm is supposed to output a convex polygon $C \subseteq [0,1]^d$ as an estimation of the convex hull $CH(P)$ of $P$. The error of the output is defined as the volume of the symmetric difference $C \oplus CH(P) = (C \backslash CH(P)) \cup (CH(P) \backslash C)$. We prove tight and near-tight tradeoffs between the number of queries and the error of the output for different variants of the problem, depending on the type of the range-emptiness queries and whether the queries are non-adaptive or adaptive. - Orthogonal emptiness queries in $d$-dimensional space: We show that the minimum error a deterministic algorithm can achieve with $q$ queries is $\Theta(q^{-1/d})$ if the queries are non-adaptive, and $\Theta(q^{-1/(d-1)})$ if the queries are adaptive. In particular, in 2D, the bounds are $\Theta(1/\sqrt{q})$ and $\Theta(1/q)$ for non-adaptive and adaptive queries, respectively. - Halfplane emptiness queries in 2D: We show that the minimum error a deterministic algorithm can achieve with $q$ queries is $\Theta(1/\sqrt{q})$ if the queries are non-adaptive, and $\widetilde{\Theta}(1/q^2)$ if the queries are adaptive. Here $\widetilde{\Theta}(\cdot)$ hides logarithmic factors.

cs.CG↗

arXiv2026

A subdifferential characterization via Busemann functions and applications to DC optimization on Hadamard manifolds

This paper investigates the properties of Busemann functions on Hadamard manifolds and their use in optimization algorithms in Riemannian settings. We present a new Busemann-based characterization of the subdifferential, which is particularly well suited to Riemannian optimization. In the classical Hadamard manifold framework, a subgradient provides a global lower model of a convex function expressed through the inverse exponential map. However, this model may fail to exhibit a useful convexity or concavity structure. By contrast, our characterization yields a concave bounding function by exploiting key properties of Busemann functions. We use this concavity to design and analyze difference-of-convex (DC) optimization methods on Hadamard manifolds. In particular, we reformulate the classical DC algorithm (DCA) for Riemannian contexts and study its convergence properties. We also report preliminary numerical experiments comparing the proposed Busemann DCA, which leads to geodesically convex subproblems, with the classical Riemannian DCA.

math.OC↗

arXiv2025

Radiometer Calibration using Machine Learning

Radiometers are crucial instruments in radio astronomy, forming the primary component of nearly all radio telescopes. They measure the intensity of electromagnetic radiation, converting this radiation into electrical signals. A radiometer's primary components are an antenna and a Low Noise Amplifier (LNA), which is the core of the ``receiver'' chain. Instrumental effects introduced by the receiver are typically corrected or removed during calibration. However, impedance mismatches between the antenna and receiver can introduce unwanted signal reflections and distortions. Traditional calibration methods, such as Dicke switching, alternate the receiver input between the antenna and a well-characterised reference source to mitigate errors by comparison. Recent advances in Machine Learning (ML) offer promising alternatives. Neural networks, which are trained using known signal sources, provide a powerful means to model and calibrate complex systems where traditional analytical approaches struggle. These methods are especially relevant for detecting the faint sky-averaged 21-cm signal from atomic hydrogen at high redshifts. This is one of the main challenges in observational Cosmology today. Here, for the first time, we introduce and test a machine learning-based calibration framework capable of achieving the precision required for radiometric experiments aiming to detect the 21-cm line.

astro-ph.IM↗

arXiv2025

A High-Precision, Fast, Robust, and Cost-Effective Muon Detector Concept for the FCC-ee

We propose a high-precision, fast, robust and cost-effective muon detector concept for an FCC-ee experiment. This design combines precision drift tubes with fast plastic scintillator strips to enable both spatial and timing measurements. The drift tubes deliver two-dimensional position measurements perpendicular to the tubes with a resolution around 100~$\mu$m. Meanwhile, the scintillator strips, read out with the wavelength-shifting fibers and silicon photomultipliers, provide fast timing information with a precision of 200~ps or better and measure the third coordinate along the tubes with a resolution of about 1~mm.

hep-ex↗

arXiv2024

Dual-readout calorimetry with homogeneous crystals

High resolution calorimetry with state-of-the-art energy resolution performance for both electromagnetic (EM) and hadronic signals can be achieved using the dual-readout (DR) technique, both in a homogeneous scintillating-crystal calorimeter and in a traditional fiber and absorber-based DR hadronic section. We present results from the CalVision consortium studying the collection of Cerenkov and scintillation signals in PbWO$_4$ and BGO crystal samples exposed to 120\,GeV proton beams at the Fermilab Test Beam Facility, including proof-of-principle measurements aimed at demonstrating the identification of a sufficiently large Cerenkov signal in homogeneous scintillating crystals to support dual-readout capability.

physics.ins-det↗

arXiv2023

Computing Wasserstein Barycenter via operator splitting: the method of averaged marginals

The Wasserstein barycenter (WB) is an important tool for summarizing sets of probability measures. It finds applications in applied probability, clustering, image processing, etc. When the measures' supports are finite, computing a (balanced) WB can be done by solving a linear optimization problem whose dimensions generally exceed standard solvers' capabilities. In the more general setting where measures have different total masses, we propose a convex nonsmooth optimization formulation for the so-called unbalanced WB problem. Due to their colossal dimensions, we introduce a decomposition scheme based on the Douglas-Rachford splitting method that can be applied to both balanced and unbalanced WB problem variants.Our algorithm, which has the interesting interpretation of being built upon averaging marginals, operates a series of simple (and exact) projections that can be parallelized and even randomized, making it suitable for large-scale datasets. Numerical comparisons against state-of-the-art methods on several data sets from the literature illustrate the method's performance.

math.OC↗

arXiv2023

The New Small Wheel electronics

The increase in luminosity, and consequent higher backgrounds, of the LHC upgrades require improved rejection of fake tracks in the forward region of the ATLAS Muon Spectrometer. The New Small Wheel upgrade of the Muon Spectrometer aims to reduce the large background of fake triggers from track segments that are not originated from the interaction point. The New Small Wheel employs two detector technologies, the resistive strip Micromegas detectors and the "small" Thin Gap Chambers, with a total of 2.45 Million electrodes to be sensed. The two technologies require the design of a complex electronics system given that it consists of two different detector technologies and is required to provide both precision readout and a fast trigger. It will operate in a high background radiation region up to about 20 kHz/cm$^{2}$ at the expected HL-LHC luminosity of $\mathcal{L}$=7.5$\times10^{34}$cm$^{-2}$s$^{-1}$. The architecture of the system is strongly defined by the GBTx data aggregation ASIC, the newly-introduced FELIX data router and the software based data handler of the ATLAS detector. The electronics complex of this new detector was designed and developed in the last ten years and consists of multiple radiation tolerant Application Specific Integrated Circuits, multiple front-end boards, dense boards with FPGA's and purpose-built Trigger Processor boards within the ATCA standard. The New Small Wheel has been installed in 2021 and is undergoing integration within ATLAS for LHC Run 3. It should operate through the end of Run 4 (December 2032). In this manuscript, the overall design of the New Small Wheel electronics is presented.

hep-ex↗

arXiv2022

The Future Circular Collider: a Summary for the US 2021 Snowmass Process

In this white paper for the 2021 Snowmass process, we give a description of the proposed Future Circular Collider (FCC) project and its physics program. The paper summarizes and updates the discussion submitted to the European Strategy on Particle Physics. After construction of an approximately 90 km tunnel, an electron-positron collider based on established technologies allows world-record instantaneous luminosities at center-of-mass energies from the Z resonance up to tt thresholds, enabling a rich set of fundamental measurements including Higgs couplings determinations at the sub percent level, precision tests of the weak and strong forces, and searches for new particles, including dark matter, both directly and via virtual corrections or mixing. Among other possibilities, the FCC-ee will be able to (i) indirectly discover new particles coupling to the Higgs and/or electroweak bosons up to scales around 7 and 50 TeV, respectively; (ii) perform competitive SUSY tests at the loop level in regions not accessible at the LHC; (iii) study heavy-flavor and tau physics in ultra-rare decays beyond the LHC reach, and (iv) achieve the best potential in direct collider searches for dark matter, sterile neutrinos, and axion-like particles with masses up to around 90 GeV. The tunnel can then be reused for a proton-proton collider, establishing record center-of-mass collision energy, allowing unprecedented reach for direct searches for new particles up to the around 50 TeV scale, and a diverse program of measurements of the Standard Model and Higgs boson, including a precision measurement of the Higgs self-coupling, and conclusively testing weakly-interacting massive particle scenarios of thermal relic dark matter.

hep-ex↗

arXiv2022

Construction of Precision sMDT Detector for ATLAS Muon Spectrometer Upgrade

This paper describes the small-diameter monitored drift-tube detector construction at the University of Michigan as a contribution to the ATLAS Muon Spectrometer upgrade for the high-luminosity Large Hadron Collider at CERN. Measurements of the first 30 chambers built at Michigan show that the drift tube wire position accuracy meets the specification of 20 microns. The positions of the platforms for alignment and magnetic field sensors are all installed well within the required precision. The cosmic ray test measurements show single wire tracking resolution of 100 +- 7 microns with an average detection efficiency above 99 %. The infrastructure, tooling, techniques, and procedures for chamber production are described in detail. The results from the chamber quality control tests of the first 30 constructed chambers are reported.

hep-ex↗

arXiv2022

The application of encoder-decoder neural networks in high accuracy and efficiency slit-scan emittance measurements

A superconducting radio-frequency (SRF) photo injector is in operation at the electron linac for beams with high brilliance and low emittance (ELBE) radiation center and generates continuous wave (CW) electron beams with high average current and high brightness for user operation since 2018. The speed of emittance measurement at the SRF gun beamline can be increased by improving the slit-scan system, thus the measurement time for one phase space mapping can be shortened from about 15 minutes to 90 seconds. A parallel algorithm and machine learning have been used to reduce the beamlet image noise. In order to estimate the uncertainty in the calculation of normalized emittance, we analyze the main error contributions such as slit position uncertainty, image noise, space charge effects and energy measurement inaccuracy.

physics.acc-ph↗

arXiv2022

GRANDMA Observations of ZTF/Fink Transients during Summer 2021

We present our follow-up observations with GRANDMA of transient sources revealed by the Zwicky Transient Facility (ZTF). Over a period of six months, all ZTF triggers were examined in real time by a dedicated science module implemented in the Fink broker, which will be used for the data processing of the Vera C. Rubin Observatory. In this article, we present three selection methods to identify kilonova candidates. Out of more than 35 million candidates, a hundred sources have passed our selection criteria. Six were then followed-up by GRANDMA (by both professional and amateur astronomers). The majority were finally classified either as asteroids or as supernovae events. We mobilized 37 telescopes, bringing together a large sample of images, taken under various conditions and quality. To complement the orphan kilonova candidates (those without associated gamma-ray bursts, which were all), we included three additional supernovae alerts to conduct further observations of during summer 2021. We demonstrate the importance of the amateur astronomer community that contributed images for scientific analyzes of new sources discovered in a magnitude range r'=17-19 mag. We based our rapid kilonova classification on the decay rate of the optical source that should exceed 0.3 mag/day. GRANDMA's follow-up determined the fading rate within 1.5+/-1.2 days post-discovery, without waiting for further observations from ZTF. No confirmed kilonovae were discovered during our observing campaign. This work will be continued in the coming months in the view of preparing for kilonova searches in the next gravitational-wave observing run O4.

astro-ph.HE↗

arXiv2022

The GRANDMA network in preparation for the fourth gravitational-wave observing run

GRANDMA is a world-wide collaboration with the primary scientific goal of studying gravitational-wave sources, discovering their electromagnetic counterparts and characterizing their emission. GRANDMA involves astronomers, astrophysicists, gravitational-wave physicists, and theorists. GRANDMA is now a truly global network of telescopes, with (so far) 30 telescopes in both hemispheres. It incorporates a citizen science programme (Kilonova-Catcher) which constitutes an opportunity to spread the interest in time-domain astronomy. The telescope network is an heterogeneous set of already-existing observing facilities that operate coordinated as a single observatory. Within the network there are wide-field imagers that can observe large areas of the sky to search for optical counterparts, narrow-field instruments that do targeted searches within a predefined list of host-galaxy candidates, and larger telescopes that are devoted to characterization and follow-up of the identified counterparts. Here we present an overview of GRANDMA after the third observing run of the LIGO/VIRGO gravitational-wave observatories in $2019-2020$ and its ongoing preparation for the forthcoming fourth observational campaign (O4). Additionally, we review the potential of GRANDMA for the discovery and follow-up of other types of astronomical transients.

astro-ph.IM↗

arXiv2022

Measurement of the ($π^-$, Ar) total hadronic cross section at the LArIAT experiment

We present the first measurement of the negative pion total hadronic cross section on argon, which we performed at the Liquid Argon In A Testbeam (LArIAT) experiment. All hadronic reaction channels, as well as hadronic elastic interactions with scattering angle greater than 5~degrees are included. The pions have a kinetic energies in the range 100-700~MeV and are produced by a beam of charged particles impinging on a solid target at the Fermilab Test Beam Facility. LArIAT employs a 0.24~ton active mass Liquid Argon Time Projection Chamber (LArTPC) to measure the pion hadronic interactions. For this measurement, LArIAT has developed the ``thin slice method", a new technique to measure cross sections with LArTPCs. While generally higher than the prediction, our measurement of the ($π^-$,Ar) total hadronic cross section is in agreement with the prediction of the Geant4 model when considering a model uncertainty of $\sim$5.1\%.

hep-ex↗

arXiv2022

Dual-Readout Calorimetry for Future Experiments Probing Fundamental Physics

In this White Paper for the 2021 Snowmass process, we detail the status and prospects for dual-readout calorimetry. While all calorimeters allow estimation of energy depositions in their active material, dual-readout calorimeters aim to provide additional information on the light produced in the sensitive media via, for example, wavelength and polarization, and/or a precision timing measurements, allowing an estimation of the shower-by-shower particle content. Utilizing this knowledge of the shower particle content may allow unprecedented energy resolution for hadronic particles and jets and new types of particle flow algorithms. We also discuss the impact continued development of this kind of calorimetry could have on precision on Higgs boson property measurements at future colliders.

physics.ins-det↗

arXiv2022

Direct Observation of Coherent Longitudinal and Shear Acoustic Phonons in TaAs Using Ultrafast X-ray Diffraction

Using femtosecond time-resolved X-ray diffraction, we investigated optically excited coherent acoustic phonons in the Weyl semimetal TaAs. The low symmetry of the (112) surface probed in our experiment enables the simultaneous excitation of longitudinal and shear acoustic modes, whose dispersion closely matches our simulations. We observed an asymmetry in the spectral lineshape of the longitudinal mode that is notably absent from the shear mode, suggesting a time-dependent frequency chirp that is likely driven by photoinduced carrier diffusion. We argue on the basis of symmetry that these acoustic deformations can transiently alter the electronic structure near the Weyl points and support this with model calculations. Our study underscores the benefit of using off-axis crystal orientations when optically exciting acoustic deformations in topological semimetals, allowing one to transiently change their crystal and electronic structures.

cond-mat.mtrl-sci↗