arXiv subjects

Mingyu Li

Publications and source records attributed to Mingyu Li.

At least 19 recordsLinked to original sources

arXiv2026

Galaxies Below the Fundamental Metallicity Relation Are Morphologically Disturbed: Merian H$α$ Morphologies and DESI Metallicities

Empirical results have revealed a connection between a galaxy's metallicity, mass, and star formation rate, known as the fundamental metallicity relation (FMR), in which metallicity increases with stellar mass and decreases with SFR. Physical interpretations of the FMR suggest that actively star-forming galaxies are fueled by pristine gas, likely obtained via IGM accretion or minor mergers. Here we demonstrate the value of galaxy morphology as an additional axis in the FMR. Using medium-band imaging from the Merian Survey, we construct spatially resolved maps of stellar continuum and H$α$ emission for a large sample of galaxies with DESI DR1 spectra, reaching stellar masses down to $10^8$ M$_\odot$. We measure non-parametric morphological parameters from the emission maps and derive gas-phase oxygen abundances from the spectra using strong-line calibrations. We fit a series of simple linear models to explore correlations among the metallicity, stellar mass, sSFR, and morphological parameters. We find that galaxies that are more metal-poor than predicted by the FMR appear particularly disturbed. At fixed stellar mass and sSFR, metallicity is inversely correlated with the asymmetry of both the continuum and H$α$ morphology. The observed trends -- and the existence of particularly metal-poor, morphologically disturbed, highly star-forming galaxies -- are consistent with external burst triggering. Our results indicate that a galaxy's morphology is linked to its metallicity and star formation history, providing an additional observational probe of the physical drivers of elevated star-formation in low-mass galaxies.

astro-ph.GA↗

arXiv2026

LATED: Ly$α$-anchored photometric selection of candidate metal-free and extremely metal-poor star formation from the end of reionisation to cosmic noon

Cosmological simulations allow a low-level tail of Population III (Pop III) star formation to persist to $z=2-6$. Spectroscopic confirmation is expensive, so an efficient photometric pre-selection is needed. We present LATED (Lyman-Alpha Tomography of Extremely Metal-poor Domains), which selects metal-free and extremely metal-poor candidates from a Ly$α$-emitter parent sample using strong-line diagnostics. The method requires three bands and two colours, $x=m_{\rm OIII}-m_{{\rm H}α}$ and $y=m_{{\rm H}α}-m_{\rm cont}$, which trace oxygen abundance and the H$α$ equivalent width, respectively. Requiring that the filters simultaneously contain [O III]+H$β$ and H$α$, together with a Ly$α$ parent selection, defines five windows spanning $z=1.92-6.60$ (four JWST/NIRCam, one Roman/WFI). The criteria, $x\geq x_{\rm min}(z)$ and $y\leq y_{\rm max}(z)$, are set by the per-redshift extrema of a forward-modelled Pop III template locus. Ordinary metal-enriched star-forming and AGN templates fall outside the selection region, and possible contaminants such as little red dots are flagged by their multi-band colours. To check contamination empirically, we apply LATED to 1126 JADES spectroscopic galaxies, and no source is selected in the four NIRCam windows. We release a Python package which converts the same photometry into R3=[O III]/H$β$ as a measurement or upper limit, reproducing JADES spectroscopy with small 0.12 dex scatter. Applied to 85 archival MUSE Ly$α$ emitters in Abell 2744, LATED recovers the confirmed extremely metal-poor galaxy AMORE6 and reveals three new candidates at $z=3-5$. Photometry alone cannot establish a metal-free nature. LATED delivers prioritised candidates for spectroscopic follow-up, providing a scalable route toward a systematic census of late-time Pop III star formation.

astro-ph.GA↗

arXiv2026

LATED: JWST integral field spectroscopy of a galaxy caught in chemical infancy at $z=4.8$ behind Abell 2744

When Population III (Pop III) star formation ended remains an open question. LATED-1 is an intrinsically faint ($M_\mathrm{UV}=-16.15$) Ly$α$ emitter at $z=4.80$ revealed by VLT/MUSE behind the lensing cluster Abell 2744 ($z=0.308$). Before any spectroscopic metallicity constraints, it was identified as an extremely metal-poor or metal-free galaxy candidate from JWST imaging by LATED, our novel photometric selection framework. Here we present serendipitous JWST/NIRSpec PRISM integral-field spectroscopy of this target. The spectrum reveals Ly$α$, H$β$, and H$α$ at 7.0, 5.6, and 17.7$σ$, as well as tentative detections of [O III]$λ\lambda4959,5007$ at 2.9$σ$, and yields $R3=\mathrm{[O\,III]\lambda5007/Hβ}=0.59^{+0.27}_{-0.21}$, upholding the earlier LATED photometric prediction of $R3<1.54$ ($2σ$ limit). The canonical JWST-based strong-line calibration, extrapolated to low metallicity, implies $\log (O/H)=6.45^{+0.17}_{-0.19}$, or $Z/Z_\odot=0.58_{-0.20}^{+0.28}\%$, placing LATED-1 among the most metal-poor galaxies known. Its modest magnification ($μ=2.80$) leaves the intrinsic properties insensitive to the lens model. LATED-1 is therefore a dwarf galaxy caught in the earliest state of chemical enrichment, and a compelling target for testing whether Pop III star formation can persist to $z<5$. The result demonstrates that photometric selection, especially through the LATED methodology, can reach below one per cent solar metallicity to identify Pop III galaxy candidates for spectroscopic follow-up.

astro-ph.GA↗

arXiv2026

VibeAvatar: Aligning Phonetic Kinematics and Human Aesthetics for High-Fidelity Talking Avatar Synthesis

Multi-modal talking avatar synthesis aims to generate realistic talking videos from a reference portrait and speech. Despite rapid progress in diffusion-based methods, existing approaches still struggle to jointly achieve accurate lip articulation, human-preferred motion aesthetics, and efficient inference. We observe that phonetic accuracy and motion aesthetics arise from fundamentally different sources and should be addressed at complementary stages rather than learned implicitly by a single generator. Based on this insight, we propose VibeAvatar, which disentangles these two objectives through a Phonetic Kinematics Adapter (PKA) that converts recognition-oriented speech features into phonetic-kinematic conditions at the conditioning stage, and an Aesthetic Motion Policy (AMP) that optimizes a flow-consistent stochastic sampling policy via Group Relative Policy Optimization (GRPO) at the post-training stage. With a lightweight flow-based motion generator operating in a compact 1D warp-based latent motion space, VibeAvatar achieves state-of-the-art results in articulation, aesthetics, and efficiency on both objective metrics and user studies, while generating a 10-second 512px video in under 10 seconds with only $\sim$3GB VRAM.

cs.CV↗

arXiv2026

First-star imprints in a metal-poor galaxy overdensity near the end of reionization

The first generation of stars, known as Population III (Pop III), formed from primordial gas consisting solely of hydrogen and helium and is believed to have emerged only a few hundred million years after the Big Bang. Detecting the chemical enrichment of metal-poor circumgalactic gas offers a promising way to trace the enrichment signature of Pop III stars. Along the sightline to the quasar SDSS J0100+2802, a metal absorber at $z = 5.945$, showing over-abundant carbon and silicon compared to solar, has been reported to be consistent with the enrichment pattern of Pop III stars. With the James Webb Space Telescope, we report the discovery of an unusually metal-poor galaxy overdensity of 17 members (mean metallicity $\approx 3\%$ solar) near this metal absorber, which is $\sim 0.4$ dex more metal-poor than coeval galaxies in similarly overdense environments. This less chemically evolved system may have provided favorable conditions for preserving the absorption signatures of Pop III enrichment. We infer a minimum dark matter halo of $\log(M_{\mathrm{h,min}}/M_{\odot})=10.68^{+0.93}_{-1.72}$, supporting late-time Pop III formation at the outskirts of atomic hydrogen cooling halos. Our findings open a promising observational pathway to identify the chemical imprints of the first stars and constrain the conditions for their formation.

astro-ph.GA↗

arXiv2026

AEON-z5: A Candidate AGN-driven Outflow Enriching the Circumgalactic Medium at $z\simeq5.23$

The dispersal of chemically enriched gas from galaxies into their surroundings is a key process in galaxy evolution, yet direct observational evidence at z>5 remains scarce. We present AEON-z5, a galaxy at z~5.23 in the COSMOS field comprising a compact continuum-emitting core surrounded by an extended, line-dominated ionized nebula. JWST/NIRCam imaging shows that H$α$+[N II] and H$β$+[O III] emission extends to projected radii of >4 kpc - 2-2.5 times the typical effective radius at the host stellar mass - reaching the outer ISM and the inner CGM. F444W grism data reveal a highly asymmetric H$α$+[N II] profile, which we interpret as a bipolar outflow and decompose into three kinematic components. The dominant component has a flux-weighted velocity offset of ~+489 km/s and FWHM~630 km/s, with a wing reaching $v_{84}$~792 km/s. A tentative detached feature at $Δv_{LOS}$~2800 km/s, detected at 1.5$σ$ in the 1D spectrum (2.4$σ$ in the 2D fit), may trace an outflow clump. These kinematics are most coherently explained by an AGN in the core. For the extended nebula, we derive a velocity curve shifting redward with radius, reaching 200-400 km/s at $r_p$~1.3-2.5 kpc - a trend that may reflect an accelerating outflow, corotating gas, or recycled inflow viewed in projection. Crucially, the measured [N II]/H$α$ ratios imply near-solar N2-based abundances (0.7-1.0 $Z_\odot$), remaining >0.37 $Z_\odot$ after allowing for AGN excitation and calibration systematics. The combination of large extent, enrichment, and extreme kinematics identifies AEON-z5 as a candidate snapshot of feedback-driven metal transport, offering a direct view of how early AGN activity may redistribute chemically processed gas into the CGM within the first ~1.1 billion years.

astro-ph.GA↗

arXiv2026

Hidden in Pixels. I. Discovery of dual "little red dots" indicates excess clustering on kilo-parsec scales

``Little Red Dots'' (LRDs) are an abundant high-redshift population newly discovered by the James Webb Space Telescope (JWST) and considered to be an early growth phase of supermassive black holes (SMBHs). Using a method of pixel-by-pixel color selection and relaxing the compactness criteria, we identify four dual LRD candidates in the COSMOS-Web survey with projected separations of $0.\!\!^{\prime\prime}2$-$1.\!\!^{\prime\prime}2$. A comparison between existing LRD samples and mock data reveals that the projected separations of these dual LRD candidates are unlikely to result from chance projections of objects at different redshifts. Furthermore, two of the four systems are covered by COSMOS-3D slitless spectroscopy, and a single-line detection at the same observed wavelength for each LRD in a pair strongly supports that they are at identical redshifts. Assuming that the detected lines are H$α$ based on their high equivalent width and broad profile, the spectroscopic redshifts of $z=5.822$ and $5.464$ for the two pairs are consistent with their photometric redshifts, yielding projected separations of $1.64$ and $7.36\,{\rm kpc}$. These discoveries suggest that the angular auto-correlation function (ACF) of LRDs exhibits an excess ($\sim20$-$30$ times) on sub-arcsec (kilo-parsec) separations compared to an extrapolation of a power-law ACF of JWST-found AGNs measured over $10^{\prime\prime}$-$100^{\prime\prime}$. Our sample is likely to represent precursors of mergers between LRDs, and such mergers may be one of the mechanisms that can drive the rapid growth of SMBHs in their early evolutionary stages.

astro-ph.GA↗

arXiv2026

A Steep-Extinction Quasi-stellar Object at z=4.6: JWST Evidence for Abundant Small Dust Grains

The rapid accumulation of massive dust reservoirs in the early Universe remains a major challenge in astrophysics. While core-collapse supernovae can inject large dust grains ($a \gtrsim 0.1\,μ{\rm m}$) on short timescales, explaining the total dust budgets in the early Universe likely requires efficient grain growth in the interstellar medium (ISM). Such growth depends critically on an abundant population of small grains, which maximize the surface area available for accretion and may be generated by rapid dust-processing or dust-formation channels. Here, we report the discovery of a QSO, UDS-27023, at $z=4.556\pm0.003$, identified using JWST/NIRSpec spectroscopy. By quantitatively comparing the spectra to QSO composite templates, we find that UDS-27023 displays an exceptionally steep far-UV extinction curve ($A_{1500}/A_V \approx 8$) but notably lacks the 2175 A bump ($A_\mathrm{bump}/A_V<0.34$ at $3σ$), indicating a dominance of small silicate dust grains. We interpret this phenomenology as evidence for active small-grain production and processing in the QSO environment. Mechanical shattering of pre-existing large grains by QSO-driven shocks and outflows provides one natural pathway, while in situ condensation of silicate grains inside dense QSO-driven winds may offer an additional route. Such a population of steep-extinction QSOs (SEQs) may therefore reveal a short-lived phase in which luminous active galactic nuclei generate, process, and redistribute small grains, potentially facilitating rapid ISM grain growth and enriching the circumgalactic medium.

astro-ph.GA↗

arXiv2026

Pointing the Way, Hiding the Destination: Practical Private Dense Retrieval at Scale

Hosted retrieval-augmented generation (RAG) and semantic search allow users to query valuable provider-held corpora, raising two competing demands: to hide each query and chosen result, yet reveal only the documents that the user is authorized to receive. Existing cryptographic approaches either make this costly by processing the entire corpus for every query, or sacrifice quality for efficiency by scanning a few clusters. We repurpose learned deep hashing as a private filter: a randomized binary code points the provider to a short candidate list, while encrypted reranking and oblivious key transfer protect the precise query and final selection. This shortlist short-circuits full-corpus cryptographic search without sacrificing retrieval quality: with 200-500 candidates, it closely matches full-corpus retrieval across five zero-shot corpora spanning 25K to 5.4M documents. On the full 2.68M-passage NQ corpus over a 10-Gbps link, our protocol only adds 0.73 seconds, or 10 percent, to a 128-token Qwen3-32B RAG pipeline. The released code satisfies directional metric differential privacy (DP) and substantially reduces embedding-inversion and property-inference leakage, demonstrating that a carefully learned shortlist can make private dense retrieval both accurate and practical.

cs.CR↗

arXiv2026

Soft-NBCE: Entropy-Weighted Chunk Fusion for Long-Context

The quadratic complexity of self-attention remains a bottleneck for Large Language Models (LLMs) processing ultra-long contexts. The Naive Bayes Cognitive Engine (NBCE) parallelizes long-context inference by chunking documents and routing to the lowest-entropy chunk at each decoding step. This hard-selection strategy causes semantic fragmentation during cross-chunk reasoning, as abrupt routing changes between adjacent tokens disrupt the model's contextual grounding. We present Soft-NBCE, a lightweight extension that replaces discrete chunk selection with soft entropy-weighted chunk fusion. A temperature-scaled Softmax over predictive entropies assigns continuous weights to all chunks, enabling log-space aggregation across chunk-conditioned distributions. To partially compensate for the conditional independence assumption introduced by chunking, we propose Consistency Distillation, a LoRA-based self-distillation that constrains the chunked logit distribution toward a full-context teacher via KL-divergence. On LongBench multi-hop benchmarks, Soft-NBCE with Consistency Distillation improves consistently over NBCE-style baselines (MuSiQue F1: 0.310 vs.\ 0.275 for Vanilla NBCE; HotpotQA F1: 0.479 vs.\ 0.427) while maintaining retrieval accuracy (NIAH-32K: 0.909) at O(L^2/n) peak memory.

cs.LG↗

arXiv2026

Expected Value Alignment for Generative Reward Modeling in Formal Mathematics Verification

Large Language Models (LLMs) are increasingly used with formal interactive theorem provers such as Lean 4. Scaling these systems with reinforcement learning or search methods requires process reward models (PRMs) that can evaluate intermediate reasoning steps. Existing reward-model designs expose a practical trade-off. Value-head models provide continuous scores but modify the generative model interface, while generative reward models preserve textual rationales but are poorly matched to continuous floating-point regression because numeric values are split across tokens. We introduce Expected Value Alignment (EVA), a reward-modeling procedure that keeps the surface output discrete while extracting continuous scores from the model's token distribution. The model emits integer scores in a structured JSON format, and EVA computes a continuous score as the expectation over the logits of the corresponding anchor tokens. Training combines the causal language modeling objective with an auxiliary mean squared error loss on these expected values. We instantiate EVA in \textit{Leibniz}, a reward model for Lean 4 formal verification, and evaluate it against zero-shot and reward-modeling baselines. The evaluation demonstrates that continuous logit-based scoring significantly reduces discretization artifacts while retaining the interpretability of generative critiques.

cs.AI↗

arXiv2026

Lagrange: An Open-Vocabulary, Energy-Based Sparse Framework for Generalized End-to-End Driving

Scaling end-to-end autonomous driving to complex, open-world environments requires perceptual models that generalize to anomalous scenarios and planners that produce kinematically valid trajectories. Existing paradigms face a distinct dichotomy between representational efficiency and generalization capacity. Dense models (e.g., occupancy networks), while geometrically robust, incur critical computational bottlenecks and struggle with high-level semantic reasoning. Conversely, sparse, query-based planners are efficient but reliant on closed-set definitions, rendering them vulnerable to out-of-distribution (OOD) events. Although recent Vision-Language-Action (VLA) models offer open-vocabulary reasoning, their autoregressive, discrete token generation fundamentally conflicts with the continuous, high-frequency control requirements of vehicle dynamics. To address this, we propose Lagrange, an open-vocabulary, computationally sparse driving framework based on Masked Latent Fields (MLF). Rather than relying on dense volumetric reconstructions or closed-set query mechanisms, Lagrange exploits Vision-Language Models (VLMs) to encode class-agnostic object proposals into continuous semantic visual tokens. We introduce an intent-driven masked cross-attention module that temporally filters irrelevant entities, decoding the attended tokens into an implicit continuous energy field defined over spatial coordinates. By framing decision-making as a Lagrangian action minimization problem spanning this energy field, we enforce strict compliance with vehicle kinematics while executing collision avoidance. Extensive offline evaluations on both standard (nuScenes) and long-tail (CODA) benchmarks demonstrate that Lagrange establishes a promising framework for robust, interpretable, and kinematically feasible open-world autonomy.

cs.AI↗

arXiv2026

A Formal Kinetic Theory for Zeroth-Order Newton Dynamics:Stein-Corrected Hessian Estimation and Curvature--Variance Trade-offs

Zeroth-order Newton-type methods are useful when gradients and Hessians are unavailable, but they behave quite differently from first-order gradient-free methods. We develop a kinetic framework for algorithms that estimate both gradient and Hessian from black-box function values. The naive random-direction Hessian estimator turns out to be biased even on quadratics; a Gaussian--Stein correction is needed to estimate the Hessian of the Gaussian-smoothed objective. Linearizing the inverse Hessian exposes two noise channels: gradient noise preconditioned by the inverse Hessian, and Hessian noise transmitted through an inverse-Hessian sandwich. Under a noisy oracle the second channel carries the second-difference factor $μ_H^{-4}$. A small-mass kinetic lift links the finite-step Newton update to an underdamped phase-space model; the overdamped spatial limit yields a Lyapunov bound that exposes the curvature--variance trade-off between step size, batch sizes, smoothing radii, and regularization. Numerical experiments confirm estimator identities, the gradient and Hessian variance laws, dimension scaling, inverse-perturbation accuracy, and optimization behavior under query-budget and regularization ablations.

math.OC↗

arXiv2026

Low Ly$α$ Visibility in Galaxy Overdensities: Reionization Topology and Neutral-Fraction Ceilings from DIVER over $4.8<z<11$

Ly-alpha emission is widely used to trace cosmic reionization, but its interpretation depends on how Ly-alpha visibility varies with galaxy environment. We use deep JWST/NIRSpec observations from Deep Insights into UV Spectroscopy at the Epoch of Reionization (DIVER) in GOODS-N to measure Ly-alpha visibility for 250 galaxies at 4.8 25 A. We combine these measurements with H-alpha and [O III] emitters from JWST/NIRCam wide-field slitless spectroscopy to map the density field around each DIVER galaxy. Galaxies with high Ly-alpha equivalent widths (W_Lyalpha>25 A) or high effective Ly-alpha escape fractions (f_esc,Lyalpha^eff>0.05) tend to lie farther from nearby H-alpha and [O III] emitters than galaxies with lower Ly-alpha visibility. The clearest signal occurs near the prominent GOODS-N overdensity at z~5.2, where fewer than 15% of galaxies show strong Ly-alpha emission. This trend is opposite to the simplest inside-out reionization expectation that overdensities produce larger ionized regions and enhance Ly-alpha visibility. Possible explanations include circumgalactic and local intergalactic opacity, dense absorbers, and gas kinematics. We also derive an empirical upper envelope for f_esc,Lyalpha^eff and calibrate it with reionization simulations. Interpreting this envelope as a limiting IGM-attenuation signal gives neutral-fraction ceilings of _max=0.36, 0.76, 0.74, 0.84, and 1.0 at z~5.2, 5.8, 6.7, 7.7, and 9.8, respectively. The z~8 ceiling disfavors an almost completely neutral IGM at this epoch. These results support patchy reionization already underway by z~8 and show that galaxy Ly-alpha visibility encodes both large-scale ionization topology and near-source gas structure.

astro-ph.GA↗

arXiv2026

OraclePhys: A Systematic Framework for LLM Fine-Tuning on Structural Mechanics

What a language model internalizes from fine-tuning is usually diagnosed after the fact. We make it an experimental variable. OraclePhys is a systematic fine-tuning framework with three components: OraclePhys-Bench, an exactly-graded structural-mechanics benchmark whose finite-element oracle scores every answer and counterfactual edit -- no human labels, no LLM judging; OraclePhys-30K, a supervision dataset of seven answer forms over byte-identical structure descriptions; and a controlled training study across the seven forms and three verifier roles. The study yields two findings. First, the label's answer form -- not its bit count -- causally determines what fine-tuning teaches: a ranking objective installs an out-of-distribution forward model where the untrained base sits at the guessing prior, a scalar objective at best a partial one, a boolean nothing detectable; the vector-scalar gulf survives a second physics domain, a second model family, and a paraphrased evaluation surface. Second, written or score-filtered answers install this capability, while advantage-weighted scores (GRPO) raise reward yet leave the model statistically equivalent to its start on held-out physics -- within the recipes and budgets tested -- sufficing only for routing. The trained 8B -- the first LLM on spatial structural response -- reaches the task's data-precision frontier: above a frontier LLM at zero- and 32-shot, at a specialist's level. What the label spells out about the target computation is what fine-tuning teaches; what you train on is what you route.

cs.LG↗

arXiv2026

SimP: Unifying Syntax- and Semantic-Guided Techniques for Efficient Program Reduction

Compiler bugs are pervasive in modern compiler systems, but the test programs that trigger them are often too large for practical debugging. Program reduction addresses this by minimizing test program size while preserving the original bug-triggering behavior. Existing approaches mainly rely on syntax-guided, rule-based deletion strategies that iteratively remove parts of the program in a trial-and-error manner. While effective in reduction quality, these approaches suffer from slow reduction speed. This paper presents SimP, a program reduction framework that combines traditional reduction with LLM-based syntax- and semantic-guided reduction. SimP leverages customized prompt design to guide the reduction process. SimP synergistically combines rule-based and LLM-based reduction stages to optimize the reduction performance. The results show that SimP improves reduction efficiency while achieving comparable reduction quality, with negligible LLM monetary cost.

cs.PL↗

arXiv2026

Determinism-Preserving GPU Spatial Sharing with Vitamin-E

GPU sharing faces a determinism--utilization tradeoff: fixed bindings can strand capacity as demand fluctuates, while resource-driven kernel reshaping improves utilization by altering a launch's parallel structure, potentially changing output bits. We rethink modern GPU scheduling and observe that it decouples logical structure from physical width: one unmodified launch spans a family of widths through changes in block placement and wave count. From this observation, we derive the parallel-structure invariant: for fixed-structure deterministic workloads, keeping each launch immutable makes its output bits independent of physical width. Guided by this invariant, Vitamin-E late-binds immutable launches to pooled physical contexts, preserving bitwise equality across allocations, whereas resource-driven reshaping can alter the selected token under temperature-zero greedy decoding. Across all workload--baseline comparisons, Vitamin-E achieves up to 3.50$\times$ the aggregate normalized LLM training throughput, 62.5\% lower inference p99 latency, and 1.43$\times$ the background-training throughput. With the same mechanism, \textsc{TPOT-First} reduces TPOT SLO violations by up to 46.1\% over \textsc{Throughput-Oriented} on three serving workloads, demonstrating mechanism effectiveness and policy flexibility.

cs.DC↗

arXiv2026

Distinguishing types of correlated errors in superconducting qubits

Errors in superconducting qubits that are correlated in time and space can pose problems for quantum error correction codes. Radiation from cosmic and terrestrial sources can increase the quasiparticle (QP) density in a superconducting qubit device, resulting in an increased rate of QPs tunneling across proximal Josephson junctions (JJs) and causing correlated errors. Mechanical vibrations, such as those induced by the pulse tube (PT) in a dry dilution refrigerator, are also a known source of correlated errors. We measure two types of errors in the same device, linking the first to ionizing radiation and the second to PT operation. We present a method for distinguishing these two types of errors by their temporal, spatial, and frequency domain features, enabling physically motivated error-mitigation strategies. We also present accelerometer data to study the correlation between PT-induced vibrations and the errors. We measure arrays of transmon qubits where the difference in superconducting gap across the JJ is less than the qubit energy, as well as those where the gap is greater than the qubit energy, which has been shown to mitigate radiation-induced errors. The rate of both types of errors is reduced in these latter devices, suggesting that gap engineering is also protective against PT-induced errors.

quant-ph↗