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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., Comment: Accepted by TMLR

The eigenfunctions of the Laplace operator are essential in mathematical physics, engineering, and geometry processing. Typically, these are computed by discretizing the domain and performing eigendecomposition, tying the results to a specific mesh. However, this method is unsuitable for continuously-parameterized shapes. We propose a novel representation for eigenfunctions in continuously-parameterized shape spaces, where eigenfunctions are spatial fields with continuous dependence on shape parameters, defined by minimal Dirichlet energy, unit norm, and mutual orthogonality. We implement this with multilayer perceptrons trained as neural fields, mapping shape parameters and domain positions to eigenfunction values. A unique challenge is enforcing mutual orthogonality with respect to causality, where the causal ordering varies across the shape space. Our training method therefore requires three interwoven concepts: (1) learning $n$ eigenfunctions concurrently by minimizing Dirichlet energy with unit norm constraints; (2) filtering gradients during backpropagation to enforce causal orthogonality, preventing earlier eigenfunctions from being influenced by later ones; (3) dynamically sorting the causal ordering based on eigenvalues to track eigenvalue curve crossovers. We demonstrate our method on problems such as shape family analysis, predicting eigenfunctions for incomplete shapes, interactive shape manipulation, and computing higher-dimensional eigenfunctions, on all of which traditional methods fall short.

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., Comment: The document consists of 6 figures and spans 22 pages, including detailed appendices

We explore the chiral dynamics in a parity-time-symmetric system consisting of a giant Kerr cavity nonlocally coupled to a one-dimensional waveguide. By tuning the phase difference between the two coupling points to match the propagation phase at the driving frequency, chiral cavity-waveguide interactions are achieved, enabling the deterministic generation of photons with nontrivial statistics only for a single incident direction. This nontrivial-statistical photons can be produced even in the strong dissipation regime due to the interference between reflected and transmitted photons propagating between the coupling points. Our investigation encompasses a broad range of distances between the coupling points, incorporating non-Markovian effects. Notably, at a phase difference of $\pi/2$, the system's dynamics become exactly Markovian, while the output field retains non-Markovian characteristics. Under these conditions, we analyze nonreciprocal dissipative phase transitions driven by a strong external field and elucidate the influence of the non-Markovian effect. Our results offer valuable insights for the advancement of nonreciprocal photon devices and deterministic photon generations, providing a deeper understanding of dissipative phase transitions., Comment: 11 pages, 3 figures

We propose accelerating the simulation of Lagrangian dynamics, such as fluid flows, granular flows, and elastoplasticity, with neural-operator-based reduced-order modeling. While full-order approaches simulate the physics of every particle within the system, incurring high computation time for dense inputs, we propose to simulate the physics on sparse graphs constructed by sampling from the spatially discretized system. Our discretization-invariant reduced-order framework trains on any spatial discretizations and computes temporal dynamics on any sparse sampling of these discretizations through neural operators. Our proposed approach is termed Graph Informed Optimized Reduced-Order Modeling or \textit{GIOROM}. Through reduced order modeling, we ensure lower computation time by sparsifying the system by 6.6-32.0$\times$, while ensuring high-fidelity full-order inference via neural fields. We show that our model generalizes to a range of initial conditions, resolutions, and materials. The code and the demos are provided at \url{https://github.com/HrishikeshVish/GIOROM}

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. However, deviations in larger input-power scenarios underscore the importance of considering pump field attenuation, which leads to uniformly distributed light shift that behaves as an inhomogeneous magnetic field.

We investigate the magnetic excitations of the trimerized Heisenberg models with intra-trimer interaction $J_1$ and inter-trimer interaction $J_2$ on four different two-dimensional lattices using a combination of stochastic series expansion quantum Monte Carlo (SSE QMC) and stochastic analytic continuation methods (SAC), complemented by cluster perturbation theory (CPT). These models exhibit quasi-particle-like excitations when $g=J_2/J_1$ is small, characterized by low-energy magnons, intermediate-energy doublons, and high-energy quartons. The low-energy magnons are associated with the magnetic ground states. They can be described by the linear spin wave theory (LSWT) of the effective block spin model and the original spin model. Doublons and quartons emerge from the corresponding internal excitations of the trimers with distinct energy levels, which can be effectively analyzed using perturbation theory when the ratio of exchange interactions $g$ is small. In this small $g$ regime, we observe a clear separation between the magnon and higher-energy spectra. However, as $g$ increases, these three spectra gradually merge into the magnon modes or continua. Nevertheless, the LSWT fails to provide quantitative descriptions of the higher-energy excitation bands due to significant quantum fluctuations. Notably, in the Collinear II and trimerized hexagon lattice, a broad continuum emerges above the single-magnon spectrum, originating from the quasi-1D physics due to the dilute connections between chains. Our numerical analysis of these 2D trimers yields valuable theoretical predictions and explanations for the inelastic neutron scattering (INS) spectra of 2D magnetic materials featuring trimerized lattices.

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.

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., Comment: 9 pages, 9 figures

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., Comment: 10 pages for manuscript with 4 figures, 16 pages for Supplementary information with 7 figures and 2 tables

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

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., Comment: 29 pages, 30 figures, 6 tables. This is the Accepted Manuscript version of an article accepted for publication in Journal of Instrumentation. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at https://doi.org/10.1088/1748-0221/17/11/P11027

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.