arXiv subjects

Yue Chang

Publications and source records attributed to Yue Chang.

At least 37 records · Page 2Linked to original sources

arXiv2025

Fast Subspace Fluid Simulation with a Temporally-Aware Basis

We present a novel reduced-order fluid simulation technique leveraging Dynamic Mode Decomposition (DMD) to achieve fast, memory-efficient, and user-controllable subspace simulation. We demonstrate that our approach combines the strengths of both spatial reduced order models (ROMs) as well as spectral decompositions. By optimizing for the operator that evolves a system state from one timestep to the next, rather than the system state itself, we gain both the compressive power of spatial ROMs as well as the intuitive physical dynamics of spectral methods. The latter property is of particular interest in graphics applications, where user control of fluid phenomena is of high demand. We demonstrate this in various applications including spatial and temporal modulation tools and fluid upscaling with added turbulence. We adapt DMD for graphics applications by reducing computational overhead, incorporating user-defined force inputs, and optimizing memory usage with randomized SVD. The integration of OptDMD and DMD with Control (DMDc) facilitates noise-robust reconstruction and real-time user interaction. We demonstrate the technique's robustness across diverse simulation scenarios, including artistic editing, time-reversal, and super-resolution. Through experimental validation on challenging scenarios, such as colliding vortex rings and boundary-interacting plumes, our method also exhibits superior performance and fidelity with significantly fewer basis functions compared to existing spatial ROMs. The inherent linearity of the DMD operator enables unique application modes, such as time-reversible fluid simulation. This work establishes another avenue for developing real-time, high-quality fluid simulations, enriching the space of fluid simulation techniques in interactive graphics and animation.

cs.GR↗

arXiv2025

Lifting the Winding Number: Precise Discontinuities in Neural Fields for Physics Simulation

Cutting thin-walled deformable structures is common in daily life, but poses significant challenges for simulation due to the introduced spatial discontinuities. Traditional methods rely on mesh-based domain representations, which require frequent remeshing and refinement to accurately capture evolving discontinuities. These challenges are further compounded in reduced-space simulations, where the basis functions are inherently geometry- and mesh-dependent, making it difficult or even impossible for the basis to represent the diverse family of discontinuities introduced by cuts. Recent advances in representing basis functions with neural fields offer a promising alternative, leveraging their discretization-agnostic nature to represent deformations across varying geometries. However, the inherent continuity of neural fields is an obstruction to generalization, particularly if discontinuities are encoded in neural network weights. We present Wind Lifter, a novel neural representation designed to accurately model complex cuts in thin-walled deformable structures. Our approach constructs neural fields that reproduce discontinuities precisely at specified locations, without baking in the position of the cut line. Crucially, our approach does not embed the discontinuity in the neural network's weights, opening avenues to generalization of cut placement. Our method achieves real-time simulation speeds and supports dynamic updates to cut line geometry during the simulation. Moreover, the explicit representation of discontinuities makes our neural field intuitive to control and edit, offering a significant advantage over traditional neural fields, where discontinuities are embedded within the network's weights, and enabling new applications that rely on general cut placement.

cs.GR↗

arXiv2025

Non-Markovian Multiphoton Chiral Dynamics with Giant Systems

Chiral interactions enable directional control of quantum light, providing new routes for nonreciprocal photon dynamics. While previous studies focused on single photon regimes, this work explores the non-Markovian multiphoton regime in a giant nonlinear system nonlocally coupled to a one-dimensional waveguide, with a tunable phase difference breaking parity symmetry. We show that single-photon transport remains reciprocal, but multiphoton dynamics become chiral, generating direction-dependent higher-order correlations and enabling deterministic creation of multiphoton states with nontrivial statistics from a single input direction, even under strong dissipation. The non-Markovian nature allows tuning of transmitted photon statistics via the coupling-point separation. At a specific phase, internal dynamics become Markovian while output photons retain non-Markovian features. Under strong coherent driving, we uncover nonreciprocal dissipative phase transitions and demonstrate how non-Markovianity shapes the critical response. This framework offers a general strategy for controlling chiral multiphoton dynamics in nonlocally coupled waveguide QED systems.

quant-ph↗

arXiv2025

Precise Gradient Discontinuities in Neural Fields for Subspace Physics

Discontinuities in spatial derivatives appear in a wide range of physical systems, from creased thin sheets to materials with sharp stiffness transitions. Accurately modeling these features is essential for simulation but remains challenging for traditional mesh-based methods, which require discontinuity-aligned remeshing -- entangling geometry with simulation and hindering generalization across shape families. Neural fields offer an appealing alternative by encoding basis functions as smooth, continuous functions over space, enabling simulation across varying shapes. However, their smoothness makes them poorly suited for representing gradient discontinuities. Prior work addresses discontinuities in function values, but capturing sharp changes in spatial derivatives while maintaining function continuity has received little attention. We introduce a neural field construction that captures gradient discontinuities without baking their location into the network weights. By augmenting input coordinates with a smoothly clamped distance function in a lifting framework, we enable encoding of gradient jumps at evolving interfaces. This design supports discretization-agnostic simulation of parametrized shape families with heterogeneous materials and evolving creases, enabling new reduced-order capabilities such as shape morphing, interactive crease editing, and simulation of soft-rigid hybrid structures. We further demonstrate that our method can be combined with previous lifting techniques to jointly capture both gradient and value discontinuities, supporting simultaneous cuts and creases within a unified model.

cs.GR↗

arXiv2025

Shape Space Spectra

Eigenanalysis of differential operators, such as the Laplace operator or elastic energy Hessian, is typically restricted to a single shape and its discretization, limiting reduced order modeling (ROM). We introduce the first eigenanalysis method for continuously parameterized shape families. Given a parametric shape, our method constructs spatial neural fields that represent eigenfunctions across the entire shape space. It is agnostic to the specific shape representation, requiring only an inside/outside indicator function that depends on shape parameters. Eigenfunctions are computed by minimizing a variational principle over nested spaces with orthogonality constraints. Since eigenvalues may swap dominance at points of multiplicity, we jointly train multiple eigenfunctions while dynamically reordering them based on their eigenvalues at each step. Through causal gradient filtering, this reordering is reflected in backpropagation. Our method enables applications to operate over shape space, providing a single ROM that encapsulates vibration modes for all shapes, including previously unseen ones. Since our eigenanalysis is differentiable with respect to shape parameters, it facilitates eigenfunction-aware shape optimization. We evaluate our approach on shape optimization for sound synthesis and locomotion, as well as reduced-order modeling for elastodynamic simulation.

cs.GR↗

arXiv2024

Spin relaxation in inhomogeneous magnetic fields with depolarizing boundaries

Field-inhomogeneity-induced relaxation of atomic spins confined in vapor cells with depolarizing walls is studied. In contrast to nuclear spins, such as noble-gas spins, which experience minimal polarization loss at cell walls, atomic spins in uncoated cells undergo randomization at the boundaries. This distinct boundary condition results in a varied dependence of the relaxation rate on the field gradient. By solving the Bloch-Torrey equation under fully depolarizing boundary conditions, we illustrate that the relaxation rate induced by field inhomogeneity is more pronounced for spins with a smaller original relaxation rate (in the absence of the inhomogeneous field). We establish an upper limit for the relaxation rate through calculations in the perturbation regime. Moreover, we connect it to the spin-exchange-relaxation-free magnetometers, demonstrating that its linewidth is most sensitive to inhomogeneous fields along the magnetometer's sensitive axis. Our theoretical result agrees with the experimental data for cells subjected to small pump power. A deviation in high input-power scenarios arises from pump field attenuation, resulting in a non-uniformly distributed light shift that behaves like an inhomogeneous magnetic field.

quant-ph↗

arXiv2024

A Unified Hallucination Mitigation Framework for Large Vision-Language Models

Hallucination is a common problem for Large Vision-Language Models (LVLMs) with long generations which is difficult to eradicate. The generation with hallucinations is partially inconsistent with the image content. To mitigate hallucination, current studies either focus on the process of model inference or the results of model generation, but the solutions they design sometimes do not deal appropriately with various types of queries and the hallucinations of the generations about these queries. To accurately deal with various hallucinations, we present a unified framework, Dentist, for hallucination mitigation. The core step is to first classify the queries, then perform different processes of hallucination mitigation based on the classification result, just like a dentist first observes the teeth and then makes a plan. In a simple deployment, Dentist can classify queries as perception or reasoning and easily mitigate potential hallucinations in answers which has been demonstrated in our experiments. On MMbench, we achieve a 13.44%/10.2%/15.8% improvement in accuracy on Image Quality, a Coarse Perception visual question answering (VQA) task, over the baseline InstructBLIP/LLaVA/VisualGLM.

cs.CV↗

arXiv2024

Quantum Beam Splitter as a Quantum Coherence Controller

We propose a quantum beam splitter (QBS) with tunable reflection and transmission coefficients. More importantly, our device based on a Hermitian parity-time ($\mathcal{PT}$) symmetric system enables the generation and manipulation of asymmetric quantum coherence of the output photons. For the interference of two weak coherent-state inputs, our QBS can produce anti-bunched photons from one output port and bunched photons from the other, showcasing high parity asymmetry and strong coherence control capabilities. Beyond the Hong-Ou-Mandel effect, perfect photon blockade with vanishing $g^{(2)}(0)$ is achievable in two-photon interference. These striking effects of the QBS fundamentally arise from the parity-symmetry-breaking interaction and the quantum interference between the photon scattering channels. Our results could inspire novel applications and the development of innovative photonic devices for the manipulation of weak quantum light.

quant-ph↗

arXiv2023

LiCROM: Linear-Subspace Continuous Reduced Order Modeling with Neural Fields

Linear reduced-order modeling (ROM) simplifies complex simulations by approximating the behavior of a system using a simplified kinematic representation. Typically, ROM is trained on input simulations created with a specific spatial discretization, and then serves to accelerate simulations with the same discretization. This discretization-dependence is restrictive. Becoming independent of a specific discretization would provide flexibility to mix and match mesh resolutions, connectivity, and type (tetrahedral, hexahedral) in training data; to accelerate simulations with novel discretizations unseen during training; and to accelerate adaptive simulations that temporally or parametrically change the discretization. We present a flexible, discretization-independent approach to reduced-order modeling. Like traditional ROM, we represent the configuration as a linear combination of displacement fields. Unlike traditional ROM, our displacement fields are continuous maps from every point on the reference domain to a corresponding displacement vector; these maps are represented as implicit neural fields. With linear continuous ROM (LiCROM), our training set can include multiple geometries undergoing multiple loading conditions, independent of their discretization. This opens the door to novel applications of reduced order modeling. We can now accelerate simulations that modify the geometry at runtime, for instance via cutting, hole punching, and even swapping the entire mesh. We can also accelerate simulations of geometries unseen during training. We demonstrate one-shot generalization, training on a single geometry and subsequently simulating various unseen geometries.

cs.GR↗

arXiv2023

Wall-Collision Effect on Optically-Polarized Atoms in Small and Hot Vapor Cells

In atomic vapor cells, atoms collide with the inner surface, causing their spin to randomize on the walls. This wall-depolarizing effect is diffusive, and it becomes more pronounced in smaller vapor cells under high temperatures. In this work, we investigate the polarization of optically-pumped alkali-metal atoms in a millimeter-sized cell heated to $% 150 $ Celsius. We consider two extreme boundary conditions: fully depolarizing and nondepolarizing boundaries, and we provide an analytical estimation of the polarization difference between them. In the nondepolarizing case, the pump beam's absorption is proportional to the average atomic polarization. However, for fully depolarizing walls, the absorption peak may correspond to a polarization minimum. To mitigate the wall effect, we propose reducing the pump beam's diameter while maintaining the pump power to prevent illumination of the cell wall and increase the pump intensity in the central area. This is crucial for compact vapor-cell devices where the laser frequency can not be detuned since it is locked to the absorption peaks. Additionally, we analyze the wall-depolarizing effect on the performance of an alkali-metal atomic magnetometer operating in the spin-exchange relaxation-free regime. We show that the signal strength is highly limited by wall collisions, and we provide an upper bound for it.

quant-ph↗

arXiv2023

CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations

The long runtime of high-fidelity partial differential equation (PDE) solvers makes them unsuitable for time-critical applications. We propose to accelerate PDE solvers using reduced-order modeling (ROM). Whereas prior ROM approaches reduce the dimensionality of discretized vector fields, our continuous reduced-order modeling (CROM) approach builds a low-dimensional embedding of the continuous vector fields themselves, not their discretization. We represent this reduced manifold using continuously differentiable neural fields, which may train on any and all available numerical solutions of the continuous system, even when they are obtained using diverse methods or discretizations. We validate our approach on an extensive range of PDEs with training data from voxel grids, meshes, and point clouds. Compared to prior discretization-dependent ROM methods, such as linear subspace proper orthogonal decomposition (POD) and nonlinear manifold neural-network-based autoencoders, CROM features higher accuracy, lower memory consumption, dynamically adaptive resolutions, and applicability to any discretization. For equal latent space dimension, CROM exhibits 79$\times$ and 49$\times$ better accuracy, and 39$\times$ and 132$\times$ smaller memory footprint, than POD and autoencoder methods, respectively. Experiments demonstrate 109$\times$ and 89$\times$ wall-clock speedups over unreduced models on CPUs and GPUs, respectively. Videos and codes are available on the project page: https://crom-pde.github.io

cs.LG↗

arXiv2022

Double-hit separation and dE/dx resolution of a time projection chamber with GEM readout

A time projection chamber (TPC) with micropattern gaseous detector (MPGD) readout is investigated as main tracking device of the International Large Detector (ILD) concept at the planned International Linear Collider (ILC). A prototype TPC equipped with a triple gas electron multiplier (GEM) readout has been built and operated in an electron test beam. The TPC was placed in a 1 T solenoidal field at the DESY II Test Beam Facility, which provides an electron beam up to 6 GeV/c. The performance of the readout modules, in particular the spatial point resolution, is determined and compared to earlier tests. New studies are presented with first results on the separation of close-by tracks and the capability of the system to measure the specific energy loss dE/dx. This is complemented by a simulation study on the optimization of the readout granularity to improve particle identification by dE/dx.

physics.ins-det↗

arXiv2022

Entanglement filter with Rydberg atoms

Devices capable of deterministically manipulating the photonic entanglement are of paramount importance, since photons are the ideal messengers for quantum information. Here, we report a Rydberg-atom-based entanglement filter that preserves the desired photonic entangled state and deterministically blocks the transmission of the unwanted ones. Photonic entanglement with near-unity fidelity can be extracted from an input state with an arbitrarily low initial fidelity. The protocol is inherently robust, and succeeds both in the Rydberg blockade regime and in the interaction-induced dissipation regime. Such an entanglement filter opens new routes toward scalable photonic quantum information processing with multiple ensembles of Rydberg atoms.

physics.atom-ph↗

arXiv2022

Accessing strongly-coupled systems without compromising them

The last decades have seen a burst of experimental platforms reaching the so-called strong-coupling regime, where quantum coherent effects dominate over incoherent processes such as dissipation and thermalization. This has allowed us to create highly nontrivial quantum states and put counterintuitive quantum-mechanical effects to test beyond the wildest expectations of the founding fathers of quantum physics. The strong-coupling regime comes with certain challenges though: the need for a large isolation makes it difficult to access the system for control or monitoring purposes. In this work we propose a way to access such systems through an engineered environment that does not compromise their strong-coupling effects. As a proof of principle, we apply the approach to the photon-blockade effect present in nonlinear resonators, but argue that the mechanism is quite universal. We also propose an architecture based on superconducting circuits where the required unconventional environment can be implemented, opening the way to the experimental analysis of our ideas.

quant-ph↗

arXiv2021

Nuclear Zeeman Effect on Heading Errors and the Suppression in Atomic Magnetometers

The heading error has been known to be caused mainly by the nonlinear Zeeman effect and the orientation-dependent light shift. In this work, we find that the nuclear Zeeman effect can also have a significant impact on the heading errors, especially for continuously-driving magnetometers with unresolved magnetic transitions. It not only shifts the precession frequency but deforms the heading errors and causes asymmetry: the heading errors for pump lasers with opposite helicities are different. The heading error also depends on the relative direction (parallel or vertical) of the probe laser to the RF driving magnetic field. Thus, one can design the configuration of the magnetometer and make it work in the smaller-heading-error regime. To suppress the heading error, our studies suggest to sum up the output precession frequencies from atomic cells pumped by two lasers with opposite helicities and probed by lasers propagating in orthogonal directions (one parallel and another perpendicular to the RF field), instead of utilizing probe lasers propagating in the same directions. Due to the nuclear Zeeman effect, the average precession frequencies in the latter case can have a non-negligible angular dependence, while in the former case the nuclear-Zeeman-effect induced heading error can be largely compensated and the residue is within 1Hz. Furthermore, for practical use, we propose to simply utilize a small magnetic field parallel/antiparallel to the pump laser. By tuning the magnitude of this auxiliary field, the heading error can be flattened around different angles, which can improve the accuracy when the magnetometer works around a certain orientation angle.

quant-ph↗

arXiv2021

A novel method to measure the dE/dx resolution of a TPC prototype using 266 nm UV laser

The specific energy loss (dE/dx) resolution is critical for particle identification and separation in TPC. In connection with the R&D for the TPC at the Circular Electron Positron Collider (CEPC), we find the laser ionisation obeys the Gaussian distribution theoretically and experimentally. Based on this, we develop a novel method using a 266 nm UV laser to measure the dE/dx resolution. Comparing to the traditional methods with particle beams or cosmic rays, the novel method with 266 nm UV laser is more convenient and flexible. We verify the method's feasibility with a TPC prototype and extrapolate the dE/dx resolution to the CEPC TPC. The estimation of the dE/dx resolution is without the magnetic field.

physics.ins-det↗

arXiv2021

Feasibility study of TPC detector at high luminosity $Z$ pole on the circular collider

With the development of the circular collider, it is necessary to make accurate physics experimental measurements of particle properties at higher luminosity $Z$ pole. Micro-pattern gaseous detectors (MPGDs), which contain Gaseous Electron Multiplier (GEM) and Micro-mesh gaseous structures (Micromegas), have excellent potential for development as the readout devices of the time projection chamber (TPC) tracker detector. To meet the updated physics requirements of the high luminosity $Z$ from the preliminary concept design report (preCDR) to concept design report (CDR) at the circular electron positron collider (CEPC), In this paper, the space charge distortion of the TPC detector is simulated with the CEPC beam structure. Using the multi-physics simulation software package, the distribution of ion estimated by Geant4 is used as the input for the differential equation, and the relationship between the ion density distribution and electric field in the detector chamber is simulated. These simulation results show that the maximum deviation for Higgs $\mathcal{O}$(25 $μ$m) meets the performance requirements in CEPC TPC detector at the high luminosity $Z$ pole, while it is still a considerable challenge for $Z$ pole, with the maximum deviation $\mathcal{O}$($>100~μ$m). According to the previous developments, the cascaded structure of GEM and Micromegas detector has been measured. The new considerations of the detector's requirements were given, the gain needs to be reached to about 2000 with IBF$\times$Gain under 0.1, and IBF means the ions back flow ratio of the detector. The pixel TPC is a potential option to replace the traditional MPGDs with the low gain, low occupancy, and outstanding pattern recognition. Finally, some update parameters and experiments results were compared.

physics.ins-det↗

arXiv2019

Quadrupole Effects on Nuclear Magnetic Resonance Gyroscopes

Nuclear magnetic resonance gyroscopes that detect rotation as a shift in the precession frequency of nuclear spins, have attracted a lot of attentions. Under a feedback-generated drive, the precession frequency is supposed to be dependent only on the angular momentum and an applied magnetic field. However, nuclei with spins larger than 1/2, experience electric quadrupole interaction with electric field gradients at the cell walls. This quadrupole interaction shifts the precession frequencies of the nuclear spins, which brings inaccuracy to the rotation measurement as the quadrupole interaction constant $C_q$ is difficult to precisely measure. In this work, the effects of quadrupole interaction on nuclear magnetic resonance gyroscopes is theoretically studied. We find that, when the constant $C_q$ is small compared to the characteristic decay rate of the system, as the strength of the feedback-driving field increases, the quadrupole shift monotonically decreases, regardless of the sign of $C_q$. In large $C_q$ regime, more than one precession frequency exists, and the nuclear spins may precess with a single frequency or multi-frequencies depending on initial conditions. In this regime, with large driving amplitudes, the nuclear spin can restore the single-frequency-precession. These results are obtained by solving an effective master equation of the nuclear spins in a rotating frame, from which both the steady-state solutions and dynamics of the system are shown.

quant-ph↗