arXiv subjects

Liang Ma

Publications and source records attributed to Liang Ma.

At least 37 records · Page 2Linked to original sources

arXiv2026

Pressure-Induced Metal-Insulator and Paramagnet-Altermagnet Transitions in Rutile OsO2 Single Crystals

Altermagnets with compensated spin structures and nonrelativistic spin splitting have emerged as a new class of magnetic materials. Rutile OsO2 has been theoretically predicted to be altermagnetic, but experimental studies have been limited by synthesis challenges. We have succeeded in synthesizing high-quality single crystals of rutile OsO2. Electrical transport studies reveal that OsO2 is highly conductive and exhibits clear Fermi liquid behavior, indicating strong electron-electron scattering. Magnetic measurements show that the crystals are isotropically paramagnetic. Density-functional theory calculations indicate that bulk OsO2 is semimetallic with coexisting electron and hole pockets, with its magnetic ground state strongly dependent on the on-site Coulomb correlation U. Angle-resolved photoemission spectroscopy studies unveil that the bulk bands do not yet show altermagnetic spin splitting. Interestingly, resistivity is rather pressure sensitive: at 44 GPa, a clear metal-insulator transition occurs. Hybrid functional calculations reveal that applying pressure significantly increases the Hubbard U value, driving a phase transition from a paramagnetic metal to an altermagnetic metal, and eventually to an altermagnetic insulator. These findings suggest that tuning external pressure effectively modulates the magnetic ground state of OsO2, providing a pathway to realize altermagnetism in this material.

cond-mat.mes-hall↗

arXiv2026

Reply to "Threefold error in the reported zero-field cooled magnetic moment of single crystal $La_2SmNi_2O_7$ (arXiv: 2602.23240)"

We respond to the critique by Aleksandr V. Korolev and Evgeny F. Talantsev on the superconducting phase fraction ($f$) calculations in Li et al. Nature 649, 871-878 (2026). First, the weak upturn in the low-temperature tail of our data has been confirmed to originate from the background, and the paramagnetic Meissner effect is absent in our case; thus, field-cooled (FC) data can be used for superconducting phase fraction calculations. Second, demagnetization effect must be calculated based on the actual measured moment as a function of $f$, which has been well-established and routinely employed in the superconductivity community. In contrast, Korolev and Talantsev treated the demagnetization field as a constant; thus, their calculation underestimates $f$ by a factor of $(1-Nχ_{meas})(1-N)$. This factor is close to 1/3, given $N$ = 0.849, $χ_{meas}$ = -1.313 in our study, which explains the origin of their deviated result (nearly three times smaller than our results). Third, our sample is a homogeneous high-quality bulk single crystal, evidenced by various techniques, making the existence of multiple discrete superconducting regions highly unlikely. We conclude that the superconducting phase fraction calculations reported in Li et al. Nature 649, 871-878 (2026) are not invalidated by the analyses presented in Korolev et al. arXiv: 2602.23240 (2026).

cond-mat.supr-con↗

arXiv2026

Black Hole Thermodynamic Ensembles, Euclidean Action and Legendre Transformation

In thermodynamics, a Legendre transformation of the free energy provides a mapping between different statistical ensembles. In this work, we demonstrate that performing a Legendre transformation of the black hole on-shell action is equivalent to imposing different boundary conditions on the fields. Consequently, the choice of ensemble must be consistent with, and cannot contradict, the imposed boundary conditions. From this perspective, it follows that for four-dimensional dyonic black holes, the on-shell action can only be expressed either as a function of the electric charge and the magnetic potential, or alternatively as a function of the magnetic charge and the electric potential. Inspired by the Legendre transformation of the Maxwell field, we argue that for purely gravitational theories whose metric geometries admit a $U(1)$ fiber bundle structure, i.e.\ rotating, boosted, or Kaluza-Klein monopole configurations, one can similarly introduce appropriate Legendre terms, in the sense of dimensional reduction, to modify the thermodynamic ensemble of the black hole. Within the dimensional reduction framework, we study the on-shell action of black holes in five-dimensional minimal supergravity with a Chern-Simons term, analyze the corresponding Legendre transformation procedure, and show how the resulting formulation remains consistent with the Wald formalism.

hep-th↗

arXiv2026

Consistent Four-derivative Heterotic Truncations and the Kerr-Sen Solution

Four-derivative heterotic supergravity (without gauge fields) reduced on a $p$-dimensional torus leads to half-maximal supergravity coupled to $p$ vector multiplets, and it is known that removing the vector multiplets is a consistent truncation of the theory. We find a new consistent truncation of four-derivative heterotic supergravity on a torus that keeps the vector multiplets and precisely reproduces the bosonic action of heterotic supergravity (with heterotic gauge fields). We show that both truncations have an $O(d+p,d)$ symmetry when reduced on a $d$-dimensional torus and demonstrate how this embeds in the $O(d+p,d+p)$ symmetry that one gets from reducing on a $(d+p)$-dimensional torus without truncation. We then use our new truncation to obtain four-derivative corrections to the Kerr-Sen solution and compute thermodynamic quantities and multipole moments. Finally, we compare the Kerr-Sen solutions of the actions corresponding to the two different choices of truncation with the Kerr solution, the Kerr-Newman solution, and each other, and show that they have distinct four-derivative multipole structures.

hep-th↗

arXiv2025

Deep Deterministic Nonlinear ICA via Total Correlation Minimization with Matrix-Based Entropy Functional

Blind source separation, particularly through independent component analysis (ICA), is widely utilized across various signal processing domains for disentangling underlying components from observed mixed signals, owing to its fully data-driven nature that minimizes reliance on prior assumptions. However, conventional ICA methods rely on an assumption of linear mixing, limiting their ability to capture complex nonlinear relationships and to maintain robustness in noisy environments. In this work, we present deep deterministic nonlinear independent component analysis (DDICA), a novel deep neural network-based framework designed to address these limitations. DDICA leverages a matrix-based entropy function to directly optimize the independence criterion via stochastic gradient descent, bypassing the need for variational approximations or adversarial schemes. This results in a streamlined training process and improved resilience to noise. We validated the effectiveness and generalizability of DDICA across a range of applications, including simulated signal mixtures, hyperspectral image unmixing, modeling of primary visual receptive fields, and resting-state functional magnetic resonance imaging (fMRI) data analysis. Experimental results demonstrate that DDICA effectively separates independent components with high accuracy across a range of applications. These findings suggest that DDICA offers a robust and versatile solution for blind source separation in diverse signal processing tasks.

stat.ME↗

arXiv2025

Quadratic Curvature Correction to 5D Myers-Perry Metric

We consider quadratic curvature perturbation to the Myers-Perry black hole in five dimensions at the linear level in the coupling constant. The solution can then be solved order by order in terms of two dimensionless angular momentum parameters up to an arbitrary order. We present the results up to tenth order. The perturbed solution allows us to obtain the higher-derivative correction to the black hole thermodynamics, which we find is in complete agreement with the Reall-Santos method.

hep-th↗

arXiv2025

PhyBlock: A Progressive Benchmark for Physical Understanding and Planning via 3D Block Assembly

While vision-language models (VLMs) have demonstrated promising capabilities in reasoning and planning for embodied agents, their ability to comprehend physical phenomena, particularly within structured 3D environments, remains severely limited. To close this gap, we introduce PhyBlock, a progressive benchmark designed to assess VLMs on physical understanding and planning through robotic 3D block assembly tasks. PhyBlock integrates a novel four-level cognitive hierarchy assembly task alongside targeted Visual Question Answering (VQA) samples, collectively aimed at evaluating progressive spatial reasoning and fundamental physical comprehension, including object properties, spatial relationships, and holistic scene understanding. PhyBlock includes 2600 block tasks (400 assembly tasks, 2200 VQA tasks) and evaluates models across three key dimensions: partial completion, failure diagnosis, and planning robustness. We benchmark 21 state-of-the-art VLMs, highlighting their strengths and limitations in physically grounded, multi-step planning. Our empirical findings indicate that the performance of VLMs exhibits pronounced limitations in high-level planning and reasoning capabilities, leading to a notable decline in performance for the growing complexity of the tasks. Error analysis reveals persistent difficulties in spatial orientation and dependency reasoning. Surprisingly, chain-of-thought prompting offers minimal improvements, suggesting spatial tasks heavily rely on intuitive model comprehension. We position PhyBlock as a unified testbed to advance embodied reasoning, bridging vision-language understanding and real-world physical problem-solving.

cs.RO↗

arXiv2025

Higher-derivative Heterotic Kerr-Sen Black Holes

We obtain the four-derivative corrections to the Kerr-Sen solution in heterotic supergravity, which includes the Gibbons-Maeda-Garfinkle-Horowitz-Strominger solution as a limiting case. In particular, we first embed the Kerr solution into heterotic supergravity and compute the higher-derivative corrections. We then obtain the corrections to the Kerr-Sen solution by performing an $O(2,1)$ boost of the Kerr solution, which, in contrast to the two-derivative case, requires field redefinitions to make the $O(2,1)$ invariance of the action manifest. Finally, we compute the multipole moments and find that they are distinct from those of the Kerr solution at the four-derivative level. We also find that the multipole moments are distinct from those of the Kerr-Newman solution in Einstein-Maxwell theory at the four-derivative level, even for the most general choice of four-derivative corrections. This gives a way to experimentally distinguish traces of string theory in gravitational wave data.

hep-th↗

arXiv2025

High Pressure Superconducting transition in Dihydride BiH$_2$ with Bismuth Open-Channel Framework

Metal hydrides MHx with low hydrogen content are not expected to show high-Tc superconductivity owing to the low hydrogen-derived electronic density of states at Fermi level and the limited hydrogen contribution to electron-phonon coupling strength. In this work, we report on the successful synthesis of a novel bismuth dihydride superconductor, Cmcm-BiH$_2$, at approximately 150 GPa, and the discovery of superconductivity with Tc about 62 K at 163 GPa, marking the first instance of superconductor among the MH$_2$-type metal dihydrides. Cmcm-BiH$_2$ adopts a unique host-guest type structure, in which the Bi atoms via weak Bi-Bi covalent bonds form a three-dimensional open-channel framework that encapsulates H$_2$-like molecules as guests, thereby broadening the structural diversity of hydrides under high pressures. The occurrence of superconductivity is evidenced by a sharp drop of resistivity to zero and the characteristic downward shift of Tc under applied magnetic fields. Notably, Cmcm-BiH$_2$ remains stable down to at least 97 GPa during decompression, with the calculated lowest pressure for dynamic stability of 10 GPa. In-depth analysis reveals that the covalent bismuth open-channel structure forms metallic conduction channels, dominates the electronic states near the Fermi level, and contributes approximately 51% of the total $lambda$ in Cmcm-BiH$_2$, distinguishing it from known high-pressure hydride superconductors. These findings highlight the critical role of non-hydrogen elements in producing superconductivity and open new avenues for the design and optimization of high-Tc hydride superconductors.

cond-mat.supr-con↗

arXiv2025

Constraining Cubic Curvature Corrections to General Relativity with Quasi-Periodic Oscillations

We investigate observational constraints on cubic curvature corrections to general relativity by analyzing quasi-periodic oscillations (QPOs) in accreting black hole systems. In particular, we study Kerr black hole solution corrected by cubic curvature terms parameterized by $β_5$ and $β_6$. While $β_6$ corresponds to a field-redefinition invariant structure, the $β_5$ term can in principle be removed via a field redefinition. Nonetheless, since we work in the frame where the accreting matter minimally couples to the metric, $β_5$ is in general present. Utilizing the corrected metric, we compute the QPO frequencies within the relativistic precession framework. Using observational data from GRO J1655$-$40 and a Bayesian analysis, we constrain the coupling parameters to $-12.31<\frac{β_5}{(5 M_\odot)^4}<24.15$ and $-1.99<\frac{β_6}{(5 M_\odot)^4}<0.30$ at 2-$σ$. These bounds improve upon existing constraints from big-bang nucleosynthesis and the speed of gravitational waves.

gr-qc↗

arXiv2025

MineAnyBuild: Benchmarking Spatial Planning for Open-world AI Agents

Spatial Planning is a crucial part in the field of spatial intelligence, which requires the understanding and planning about object arrangements in space perspective. AI agents with the spatial planning ability can better adapt to various real-world applications, including robotic manipulation, automatic assembly, urban planning etc. Recent works have attempted to construct benchmarks for evaluating the spatial intelligence of Multimodal Large Language Models (MLLMs). Nevertheless, these benchmarks primarily focus on spatial reasoning based on typical Visual Question-Answering (VQA) forms, which suffers from the gap between abstract spatial understanding and concrete task execution. In this work, we take a step further to build a comprehensive benchmark called MineAnyBuild, aiming to evaluate the spatial planning ability of open-world AI agents in the Minecraft game. Specifically, MineAnyBuild requires an agent to generate executable architecture building plans based on the given multi-modal human instructions. It involves 4,000 curated spatial planning tasks and also provides a paradigm for infinitely expandable data collection by utilizing rich player-generated content. MineAnyBuild evaluates spatial planning through four core supporting dimensions: spatial understanding, spatial reasoning, creativity, and spatial commonsense. Based on MineAnyBuild, we perform a comprehensive evaluation for existing MLLM-based agents, revealing the severe limitations but enormous potential in their spatial planning abilities. We believe our MineAnyBuild will open new avenues for the evaluation of spatial intelligence and help promote further development for open-world AI agents capable of spatial planning.

cs.AI↗

arXiv2025

Efficient Brain Network Estimation with Sparse ICA in Non-Human Primate Neuroimaging

Independent component analysis (ICA) is widely used to separate mixed signals and recover statistically independent components. However, in non-human primate neuroimaging studies, most ICA-recovered spatial maps are often dense. To extract the most relevant brain activation patterns, post-hoc thresholding is typically applied-though this approach is often imprecise and arbitrary. To address this limitation, we employed the Sparse ICA method, which enforces both sparsity and statistical independence, allowing it to extract the most relevant activation maps without requiring additional post-processing. Simulation experiments demonstrate that Sparse ICA performs competitively against 11 classical linear ICA methods. We further applied Sparse ICA to real non-human primate neuroimaging data, identifying several independent component networks spanning different brain networks. These spatial maps revealed clearly defined activation areas, providing further evidence that Sparse ICA is effective and reliable in practical applications.

stat.AP↗

arXiv2025

First principles study on the oxidation resistance of two-dimensional intrinsic and defective GeO2

Although two-dimensional (2D) oxide semiconductors exhibit remarkable oxidation resistance compared to conventional 2D materials, the microscopic physical processes that govern this behavior at the atomic scale remains elusive. Using first-principles calculations, we investigated the defect formation and oxidation dynamics of the GeO${_2}$ monolayer (ML). The investigations reveal that the intrinsic GeO${_2}$ ML is resistant to oxidation due to strong electrostatic repulsion between surface oxygen ions and approaching O$_2$ molecules, effectively suppressing chemisorption. In contrast, defective GeO$_2$ ML with surface O vacancies shows vulnerability to oxidation with the O$_2$ molecule occupying the vacancy through a low-energy activation energy ($E_a$) of 0.375 eV. Remarkably, the subsequent O$_2$ dissociation into atomic species faces a higher activation barrier ($E_a$ = 1.604 eV), suggesting self-limiting oxidation behavior. Electronic structure analysis demonstrates that oxidation primarily modifies the valence bands of defective GeO${_2}$ MLs through oxygen incorporation, while the conduction bands and electron effective mass recover to pristine-like characteristics. We further proved that the high O$_2$ pressure hinders the formation of the O vacancy, while high temperature increases the oxidation rate in GeO$_2$ ML. These atomic-level insights not only advance our understanding of oxidation resistance in 2D oxides but also provide guidelines for developing stable GeO${_2}$-based nanoelectronic devices.

cond-mat.mtrl-sci↗

arXiv2025

Instanton Moduli, Topology and the Bosonic/Heterotic String Origins

We construct new supersymmetric NS(-1)-branes supported by the $SU(2)\times SU(2)$ 't Hooft instantons in ${\cal N}=1$, $D=4$ supergravity. We show that although the magnetic 3-form string flux is invariant under the variation of instanton moduli, the string-frame metric can change topology, giving rise to either $\mathbb R^4$ or the new $\mathbb R\times S^3$ bolt topologies. We uplift the solutions to both heterotic and bosonic strings, where the instanton moduli become parameters of pure geometry. We find that the Killing spinors exist in both theories. The transformation of the Killing spinors from one theory to the other is consistent with the recently proposed bosonic/heterotic string duality. We further construct new BPS solutions in the $D=6$ Salam-Sezgin model, employing the technique developed in the paper.

hep-th↗

arXiv2025

Leading Higher Derivative Corrections to Multipole Moments of Kerr-Newman Black Hole

We study the (leading) 4-derivative corrections, including both parity even and odd terms, to electrically-charged Kerr-Newman black holes. The linear perturbative equations are then solved order by order in terms of two dimensionless rotating and charge parameters. The solution allows us to extract the multipole moments of mass and current from the metric as well as the electric and magnetic multipole moments from the Maxwell field. We find that all the multipole moments are invariant under the field redefinition, indicating they are well-defined physical observables in this effective theory approach to quantum gravity. We also find that parity-odd corrections can turn on the multipole moments that vanish in Einstein theory, which may have significant observational implications.

hep-th↗

arXiv2025

New BPS States from Bosonic/Heterotic Duality

In this paper, we consider the recently proposed bosonic/heterotic duality that relates the heterotic superstrings to the noncritical bosonic string. Although the latter is nonsupersymmetric, it can be viewed as pseudo-supersymmetric in that the theory admits a consistent set of Killing spinor equations whose integrability conditions are satisfied by the equations of motion. We construct two classes of the dual pairs of BPS and pseudo-BPS solutions in the respective heterotic and bosonic strings and obtain their explicit Killing spinors. The existence of such dual pairs lends support to the proposed duality.

hep-th↗

arXiv2025

Unbiased Evaluation of Large Language Models from a Causal Perspective

Benchmark contamination has become a significant concern in the LLM evaluation community. Previous Agents-as-an-Evaluator address this issue by involving agents in the generation of questions. Despite their success, the biases in Agents-as-an-Evaluator methods remain largely unexplored. In this paper, we present a theoretical formulation of evaluation bias, providing valuable insights into designing unbiased evaluation protocols. Furthermore, we identify two type of bias in Agents-as-an-Evaluator through carefully designed probing tasks on a minimal Agents-as-an-Evaluator setup. To address these issues, we propose the Unbiased Evaluator, an evaluation protocol that delivers a more comprehensive, unbiased, and interpretable assessment of LLMs.Extensive experiments reveal significant room for improvement in current LLMs. Additionally, we demonstrate that the Unbiased Evaluator not only offers strong evidence of benchmark contamination but also provides interpretable evaluation results.

cs.AI↗

arXiv2025

RoomTour3D: Geometry-Aware Video-Instruction Tuning for Embodied Navigation

Vision-and-Language Navigation (VLN) suffers from the limited diversity and scale of training data, primarily constrained by the manual curation of existing simulators. To address this, we introduce RoomTour3D, a video-instruction dataset derived from web-based room tour videos that capture real-world indoor spaces and human walking demonstrations. Unlike existing VLN datasets, RoomTour3D leverages the scale and diversity of online videos to generate open-ended human walking trajectories and open-world navigable instructions. To compensate for the lack of navigation data in online videos, we perform 3D reconstruction and obtain 3D trajectories of walking paths augmented with additional information on the room types, object locations and 3D shape of surrounding scenes. Our dataset includes $\sim$100K open-ended description-enriched trajectories with $\sim$200K instructions, and 17K action-enriched trajectories from 1847 room tour environments. We demonstrate experimentally that RoomTour3D enables significant improvements across multiple VLN tasks including CVDN, SOON, R2R, and REVERIE. Moreover, RoomTour3D facilitates the development of trainable zero-shot VLN agents, showcasing the potential and challenges of advancing towards open-world navigation.

cs.CV↗