arXiv subjects

Boliang Yu

Publications and source records attributed to Boliang Yu.

12 recordsLinked to original sources

arXiv2026

How tightly can PBH abundance information constrain scalar-induced gravitational waves?

Primordial black hole (PBH) abundances and scalar-induced gravitational waves (SIGWs) probe the same primordial fluctuations through different physical weights. We examine the predictive power of precise synthetic information on absolute PBH abundances over a finite stellar-mass interval, together with an exact total abundance and external population bounds. For Gaussian perturbations under a fixed quantum chromodynamics (QCD) formation prescription, two smooth, symmetric lognormal spectra satisfy the same abundance conditions while producing nonproportional leading-order SIGW spectra. The two spectra differ by about 20% when averaged over the lower of two adjacent nanohertz windows but by nearly a factor of 60 in the higher-frequency window, so the difference cannot be represented by a single rescaling of the gravitational-wave background. Peak position and width compensate with amplitude in the abundance calculation, while the higher-frequency window draws almost all its energy from scalar-mode pairs with both wavenumbers above the primordial peak. Under the principal abundance benchmark, local finite-width components yield larger contrasts at a fixed nanohertz frequency through distinct mode couplings under both the QCD and stochastic peak-curvature formation prescriptions. For a separately generated population, extending mass information over most of its abundance restricts the lognormal peak-position and width compensation and reduces the higher-window contrast, while the unequal window responses persist. These results show why joint PBH-SIGW inference must propagate primordial shapes compatible with the PBH abundance information rather than assign one tensor template to a single abundance fit.

astro-ph.CO↗

arXiv2026

Rapid microscopic decorrelation precedes sustained collective ordering in quenched two-dimensional colloids

Independent Brownian noise can rapidly separate trajectories launched from the same microscopic configuration, but configuration-space distance need not reveal their later assembly outcomes. We studied this distinction in 480 two-dimensional Brownian-dynamics trajectories generated as three independent-noise replicas of 40 parent configurations under four finite-duration quenches. Ninety-two of 160 replica sets sharing one parent and one protocol reached both ordered and non-ordered terminal outcomes. A relative-diffusion calculation relates the free-particle mean-squared replica separation to the time-integrated diffusivity. The measured mean-squared separation remained about one-sixth of the free-particle reference, while its scaling was indistinguishable for replica pairs with the same and different outcomes. In contrast, outcome-resolved global sixfold order, ordered-particle population and coherence, and reciprocal-space translational order separated progressively after quench completion. With quench durations weighted equally, global order, the state score combining global and population order, coherence, and translational order remained informative 0.50 reduced time units before terminal assessment. This result persisted after either changing the terminal window or reducing the integration timestep. Transient threshold crossings were common, and 94.5\% of non-ordered crossings subsequently lost the required ordered-particle population. An independent $N=128$ ensemble showed state-score discrimination at temperatures for which both terminal classes occurred. The assembly dynamics therefore separate generic microscopic decorrelation from the later emergence and finite-window persistence of collective order associated with terminal structure.

cond-mat.soft↗

arXiv2026

Lightest-mass suppression and weaker Majorana cancellation in Froggatt--Nielsen textures

The effective Majorana mass is the length of a sum of three complex electron-flavour contributions. A mass-generation model determines both their sizes and how they cancel. We compare direct effective coefficients with a three-right-handed-neutrino seesaw measure at fixed Froggatt--Nielsen charges and common lepton conditions. In the normal-ordering benchmark truncated-normal ensemble, seesaw generation lowers the lightest-mass median by a factor of 3.2 while raising the effective-mass median by 13\%. A comparison reweighted to a common lightest-mass distribution locates nearly all of the coherent mean-square increase in weaker destructive solar-pair interference. In a fixed-amplitude phase-exchange control, the response follows the conditional phase law. A second texture exposes the competing spectral effect: smaller amplitudes can outweigh weaker cancellation in the original mean square. The interference information also affects how a prediction can be used. Replacing induced phases by independent uniform phases at unchanged posterior masses and electron weights raises the benchmark direct median by 29\%. The matrix ensemble therefore predicts a joint arrangement of amplitudes and phases whose coherent information is lost when only masses and electron-flavour weights are retained.

hep-ph↗

arXiv2026

Flavor decoherence and washout timing in nonthermal leptogenesis after inflation

We investigate why changing the heavy-neutrino mass hierarchy can reverse the baryon asymmetry in nonthermal leptogenesis after hilltop inflation. Along the mass trajectory studied here, lowering the mass of the lighter state, $N_1$, reverses the final asymmetry while leaving the dominant injection from $N_2$ decays nearly unchanged. The mass change primarily delays $N_1$ washout relative to electron--muon flavor decoherence; at fixed source and background, translating the washout history while preserving its shape and integrated strength reproduces more than 99\% of the yield changes from the nonthermal $N_2$ source at two physical target masses. Decomposing the $N_2$ CP source shows that the projector-aligned component remains positive under both washout histories, whereas the initially trace-free component reverses its propagated contribution and accounts for about 99.7\% of the timing contrast in the fixed-source comparison. Rapid damping of $eμ$ flavor coherence largely removes this contrast, while rapid chemical equilibration does not. Later washout therefore acts on a more decohered flavor state, reducing the positive $eμ$ contribution and allowing negative diagonal contributions to determine the final sign. At a mass recomputed to reproduce the observed baryon yield, a 10\% increase of the muon collision operator reverses the sign in a fixed-input sensitivity test.

hep-ph↗

arXiv2026

Loading history and window geometry bound compact-state slip ranking during granular shear startup

Granular slip forecasting can conflate material state, loading progress, and the geometry of event-centered sampling. We separated these contributions in slowly sheared two-dimensional frictional disks using a compact neural score of stress, pressure, coordination, non-affine motion, and force-network observables. The model was developed on 36 trajectories and frozen efore testing on 18 new trajectories under two nested stress-drop definitions. Inspection of held-out results revealed post-event sampling asymmetry; recovery-aware analyses are therefore descriptive. With trajectories weighted equally, the compact score ranked near-slip windows above both prevalence and within-trajectory circular-phase controls under both definitions (representative average precision 0.310 versus prevalence 0.173; phase-null upper bound 0.257). Loading-history coordinates ranked more strongly, reaching 0.534 for causal elapsed strain. The recovery-aware rule retained 78.4\% of activity-gated events and preferentially selected longer preceding intervals; ranking by time since the previous catalogued event remained compatible with a count-conditioned geometry null. Compact observables thus contain temporally aligned slip information, but stronger loading-history baselines and window-geometry sensitivity bound that evidence. These startup data do not isolate a state-specific short-horizon precursor beyond loading history or support a renewal interpretation of elapsed-strain ranking.

cond-mat.soft↗

arXiv2026

Directional memory of early spectral selection during spinodal decomposition in finite systems

Cahn-Hilliard phase separation turns small composition fluctuations into coarsening domains. In Fourier space, the pattern forms a ring whose angular intensity favors an axis. We ask whether the axis favored early in an evolution remains related to the axis favored later in the same evolution. We analyze two-dimensional simulations with isotropic initial fluctuations and no imposed direction. We introduce $Q_2$, a normalized angular average over the Fourier spectrum, as a measure of the strength and direction of spectral anisotropy. Linear growth amplifies different wave numbers at different rates, selecting an early axis from the angular imbalances in the initial spectrum. This axis remains correlated with the late axis during coarsening. At a fixed time, shallow quenches show stronger early-late alignment. This advantage disappears when the quenches are compared at similar stages of domain growth. Adding the early $Q_2$ to a prediction based on quench depth, mean composition, and box size reduces the mean absolute error for late $Q_2$ by $3.53\%$. This reduction disappears when only the magnitude of the early $Q_2$ is retained, or when its direction is replaced by the direction from another evolution. The early Fourier intensity therefore carries information about the later state of the same evolving field.

cond-mat.stat-mech↗

arXiv2026

Hidden amplitude and dynamical information in phase-separation spectra

Framewise variance normalization removes fluctuation amplitude from an observation, but not from the dynamics that generate later patterns. The current normalized spectrum therefore need not determine its own future. We study this effect in three two-dimensional phase-separation models that change transport, add active driving, or suppress large-scale separation. For paired initial fields, their normalized spectra evolve identically in the linear regime. The restoring model provides an exact example: damping does not directly change how the normalized spectrum evolves when both equations are applied to the same field. It nevertheless changes the hidden amplitude, which alters the later nonlinear shape. An exact comparison separates the immediate effect of changing the equation from the effect of reaching a different state through earlier evolution. It also reveals strong cancellation between these effects in the mobility and active models. As a practical test, spectral histories improve classification by about 4-6 percentage points at several later observation windows, although the gain depends on quench depth and spectral construction. Temporal spectra can therefore reveal dynamical consequences of information absent from every individual normalized frame.

cond-mat.soft↗

arXiv2026

Observable dependence and rate identifiability in false-vacuum decay of the quantum Ising chain

Extracting a thermodynamic nucleation rate from finite-time quantum dynamics requires separating observable decay from estimator and finite-size validity. We develop a multilevel identification framework for real-time tensor-network simulations of false-vacuum decay in the one-dimensional quantum Ising chain. Across twelve parameter points, the same coherent two-kink amplitudes semi-quantitatively predict both infinite-chain survival and magnetization dynamics: the survival coefficient has a median lattice-to-theory ratio of 0.896, while the magnetization-area slope ratios span 0.767--0.931. By contrast, the microscopic nearest-neighbour bond response is coherence dominated: vacuum--pair coherence contributes 60.0--81.5% across seven points with matched bond-dimension control, while substantial late-window slope discrepancies remain that cannot be removed by a scalar normalization. The analysis establishes finite-time survival and magnetization benchmarks and identifies the additional finite-size and branch-validation requirements for a bulk thermodynamic rate interpretation. Within the two-kink model and under the adopted common normalization, the lattice-resolved WKB action gives a median fixed-prefactor rate discrepancy of 4.13% from the coherent-bubble spectral calculation. These results distinguish finite-time lattice--theory consistency from the additional observable and finite-size evidence required to identify a thermodynamic nucleation rate.

cond-mat.stat-mech↗

arXiv2026

Movable seams in root-of-unity XXZ chains: Relative flux classes and antiunitary spectral pairing

Starting from the cyclic duality tensors introduced by Vernier, Miao, and Yamazaki (VMY), whose endpoint-traced matrix-product operators obey $\mathbb Z_N$ Tambara--Yamagami fusion and realize topological defect lines of the compactified-boson conformal field theory, we retain the virtual endpoint as an $N$-state dynamical degree of freedom and construct an exactly movable seam in the spin-$\tfrac12$ XXZ chain at $q=\mathrm e^{\mathrm iπM/N}$ with $\gcd(M,N)=1$. The local movement identity holds for any unitary $q$-Weyl pair; in the finite cyclic realization, all output phases are locally gauge equivalent and share the same four seam eigenvalues. On a ring, the output gauge becomes a directed twist on a single bond, while endpoint conjugacy reduces the $2N$ labels to two relative $\mathbb Z_2$ flux classes. An explicit antiunitary symmetry protects the class $η\equiv M-1\pmod 2$: for even $N$ it pairs distinct charge sectors isospectrally, whereas for odd $N$ it fixes one sector and squares to $-I$ there. Hence every many-body energy eigenspace in the protected class has even multiplicity. The source value $η_{\rm VMY}=1-M$ satisfies this condition for every coprime root, whereas the ungauged value $η=0$ does so only for odd $M$. Exact finite-size controls show that the opposite class can contain simple levels, so a global flux invisible to local gauge equivalence distinguishes the two classes spectrally.

cond-mat.stat-mech↗

arXiv2026

Entanglement spectrum ordering and flavor polarization in the two-flavor Schwinger model at vacuum angle $θ= π$

Entanglement spectra in gauge theories can encode both symmetry breaking and the organization of gauge sectors. In the two-flavor Schwinger model at vacuum angle $θ=π$, we find that the joint Schmidt distribution $p_{Q_A,F_A}$, labeled by the subsystem gauge charge $Q_A$ and flavor imbalance $F_A$, reveals a cut-dependent gauge-sector hierarchy and a mass-induced flavor asymmetry: changing the staggered cut reorganizes the gauge-charge distribution $p_{Q_A}$, while mass imbalance breaks the $F_A\leftrightarrow-F_A$ symmetry of the conditional flavor distribution $p_{F_A|Q_A}$. Defining the combined weight $W_F^{(q)}=p_{q,+1}+p_{q,-1}$ and conditional polarization $\mathcal P_F^{(q)}=(p_{q,+1}-p_{q,-1})/W_F^{(q)}$, we find that changing the cut reverses the weight hierarchy, $W_F^{(-1)}>W_F^{(+1)}$ at unit-cell boundaries but $W_F^{(+1)}>W_F^{(-1)}$ at intra-cell cuts, while mass imbalance drives $\mathcal P_F^{(q)}$ away from zero with a $q$-dependent cut response. Symmetry resolution therefore separates gauge-sector ordering, sector weight, and flavor polarization that are mixed in the globally ordered entanglement spectrum.

hep-lat↗

arXiv2025

AortaDiff: A Unified Multitask Diffusion Framework For Contrast-Free AAA Imaging

While contrast-enhanced CT (CECT) is standard for assessing abdominal aortic aneurysms (AAA), the required iodinated contrast agents pose significant risks, including nephrotoxicity, patient allergies, and environmental harm. To reduce contrast agent use, recent deep learning methods have focused on generating synthetic CECT from non-contrast CT (NCCT) scans. However, most adopt a multi-stage pipeline that first generates images and then performs segmentation, which leads to error accumulation and fails to leverage shared semantic and anatomical structures. To address this, we propose a unified deep learning framework that generates synthetic CECT images from NCCT scans while simultaneously segmenting the aortic lumen and thrombus. Our approach integrates conditional diffusion models (CDM) with multi-task learning, enabling end-to-end joint optimization of image synthesis and anatomical segmentation. Unlike previous multitask diffusion models, our approach requires no initial predictions (e.g., a coarse segmentation mask), shares both encoder and decoder parameters across tasks, and employs a semi-supervised training strategy to learn from scans with missing segmentation labels, a common constraint in real-world clinical data. We evaluated our method on a cohort of 264 patients, where it consistently outperformed state-of-the-art single-task and multi-stage models. For image synthesis, our model achieved a PSNR of 25.61 dB, compared to 23.80 dB from a single-task CDM. For anatomical segmentation, it improved the lumen Dice score to 0.89 from 0.87 and the challenging thrombus Dice score to 0.53 from 0.48 (nnU-Net). These segmentation enhancements led to more accurate clinical measurements, reducing the lumen diameter MAE to 4.19 mm from 5.78 mm and the thrombus area error to 33.85% from 41.45% when compared to nnU-Net. Code is available at https://github.com/yuxuanou623/AortaDiff.git.

cs.CV↗

arXiv2021

IREM: High-Resolution Magnetic Resonance (MR) Image Reconstruction via Implicit Neural Representation

For collecting high-quality high-resolution (HR) MR image, we propose a novel image reconstruction network named IREM, which is trained on multiple low-resolution (LR) MR images and achieve an arbitrary up-sampling rate for HR image reconstruction. In this work, we suppose the desired HR image as an implicit continuous function of the 3D image spatial coordinate and the thick-slice LR images as several sparse discrete samplings of this function. Then the super-resolution (SR) task is to learn the continuous volumetric function from a limited observations using an fully-connected neural network combined with Fourier feature positional encoding. By simply minimizing the error between the network prediction and the acquired LR image intensity across each imaging plane, IREM is trained to represent a continuous model of the observed tissue anatomy. Experimental results indicate that IREM succeeds in representing high frequency image feature, and in real scene data collection, IREM reduces scan time and achieves high-quality high-resolution MR imaging in terms of SNR and local image detail.

eess.IV↗