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b129c6fe6a0852e34aa89556dd36d191fd1f8a24fe6d059d298b1db0e75e3ec0
2026-01-21T00:00:00-05:00
Riemannian Liquid Spatio-Temporal Graph Network
arXiv:2601.14115v1 Announce Type: new Abstract: Liquid Time-Constant networks (LTCs), a type of continuous-time graph neural network, excel at modeling irregularly-sampled dynamics but are fundamentally confined to Euclidean space. This limitation introduces significant geometric distortion when representing real-world graphs with inherent non-Euclidean structures (e.g., hierarchies and cycles), degrading representation quality. To overcome this limitation, we introduce the Riemannian Liquid Spatio-Temporal Graph Network (RLSTG), a framework that unifies continuous-time liquid dynamics with the geometric inductive biases of Riemannian manifolds. RLSTG models graph evolution through an Ordinary Differential Equation (ODE) formulated directly on a curved manifold, enabling it to faithfully capture the intrinsic geometry of both structurally static and dynamic spatio-temporal graphs. Moreover, we provide rigorous theoretical guarantees for RLSTG, extending stability theorems of LTCs to the Riemannian domain and quantifying its expressive power via state trajectory analysis. Extensive experiments on real-world benchmarks demonstrate that, by combining advanced temporal dynamics with a Riemannian spatial representation, RLSTG achieves superior performance on graphs with complex structures. Project Page: https://rlstg.github.io
https://arxiv.org/abs/2601.14115
Academic Papers
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6d7bf0ef0b6d604efcd44b323167207315adab98bbc37ef9ba5875cafe757768
2026-01-21T00:00:00-05:00
NewsRECON: News article REtrieval for image CONtextualization
arXiv:2601.14121v1 Announce Type: new Abstract: Identifying when and where a news image was taken is crucial for journalists and forensic experts to produce credible stories and debunk misinformation. While many existing methods rely on reverse image search (RIS) engines, these tools often fail to return results, thereby limiting their practical applicability. In this work, we address the challenging scenario where RIS evidence is unavailable. We introduce NewsRECON, a method that links images to relevant news articles to infer their date and location from article metadata. NewsRECON leverages a corpus of over 90,000 articles and integrates: (1) a bi-encoder for retrieving event-relevant articles; (2) two cross-encoders for reranking articles by location and event consistency. Experiments on the TARA and 5Pils-OOC show that NewsRECON outperforms prior work and can be combined with a multimodal large language model to achieve new SOTA results in the absence of RIS evidence. We make our code available.
https://arxiv.org/abs/2601.14121
Academic Papers
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8109acfd14246dcb2f00f9fdcd3a7107163a4b51c6fa4dabf768ff24d537ba02
2026-01-21T00:00:00-05:00
A Systematic Analysis of Chunking Strategies for Reliable Question Answering
arXiv:2601.14123v1 Announce Type: new Abstract: We study how document chunking choices impact the reliability of Retrieval-Augmented Generation (RAG) systems in industry. While practice often relies on heuristics, our end-to-end evaluation on Natural Questions systematically varies chunking method (token, sentence, semantic, code), chunk size, overlap, and context length. We use a standard industrial setup: SPLADE retrieval and a Mistral-8B generator. We derive actionable lessons for cost-efficient deployment: (i) overlap provides no measurable benefit and increases indexing cost; (ii) sentence chunking is the most cost-effective method, matching semantic chunking up to ~5k tokens; (iii) a "context cliff" reduces quality beyond ~2.5k tokens; and (iv) optimal context depends on the goal (semantic quality peaks at small contexts; exact match at larger ones).
https://arxiv.org/abs/2601.14123
Academic Papers
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7755a69e90a8fd2554e588cd5296d21923838b282050643e6e34e544d4596b4b
2026-01-21T00:00:00-05:00
Style Transfer as Bias Mitigation: Diffusion Models for Synthetic Mental Health Text for Arabic
arXiv:2601.14124v1 Announce Type: new Abstract: Synthetic data offers a promising solution for mitigating data scarcity and demographic bias in mental health analysis, yet existing approaches largely rely on pretrained large language models (LLMs), which may suffer from limited output diversity and propagate biases inherited from their training data. In this work, we propose a pretraining-free diffusion-based approach for synthetic text generation that frames bias mitigation as a style transfer problem. Using the CARMA Arabic mental health corpus, which exhibits a substantial gender imbalance, we focus on male-to-female style transfer to augment underrepresented female-authored content. We construct five datasets capturing varying linguistic and semantic aspects of gender expression in Arabic and train separate diffusion models for each setting. Quantitative evaluations demonstrate consistently high semantic fidelity between source and generated text, alongside meaningful surface-level stylistic divergence, while qualitative analysis confirms linguistically plausible gender transformations. Our results show that diffusion-based style transfer can generate high-entropy, semantically faithful synthetic data without reliance on pretrained LLMs, providing an effective and flexible framework for mitigating gender bias in sensitive, low-resource mental health domains.
https://arxiv.org/abs/2601.14124
Academic Papers
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b8eda0bdcaa6b1b34eea39818fe0a79f4558b2fcffdcbc7231b1ca09f6cb4942
2026-01-21T00:00:00-05:00
The Side Effects of Being Smart: Safety Risks in MLLMs' Multi-Image Reasoning
arXiv:2601.14127v1 Announce Type: new Abstract: As Multimodal Large Language Models (MLLMs) acquire stronger reasoning capabilities to handle complex, multi-image instructions, this advancement may pose new safety risks. We study this problem by introducing MIR-SafetyBench, the first benchmark focused on multi-image reasoning safety, which consists of 2,676 instances across a taxonomy of 9 multi-image relations. Our extensive evaluations on 19 MLLMs reveal a troubling trend: models with more advanced multi-image reasoning can be more vulnerable on MIR-SafetyBench. Beyond attack success rates, we find that many responses labeled as safe are superficial, often driven by misunderstanding or evasive, non-committal replies. We further observe that unsafe generations exhibit lower attention entropy than safe ones on average. This internal signature suggests a possible risk that models may over-focus on task solving while neglecting safety constraints. Our code and data are available at https://github.com/thu-coai/MIR-SafetyBench.
https://arxiv.org/abs/2601.14127
Academic Papers
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453daa3183d8f8341c5d66e92c5ed6f381906044762f1bc7216b8cce58f896bb
2026-01-21T00:00:00-05:00
SandWorm: Event-based Visuotactile Perception with Active Vibration for Screw-Actuated Robot in Granular Media
arXiv:2601.14128v1 Announce Type: new Abstract: Perception in granular media remains challenging due to unpredictable particle dynamics. To address this challenge, we present SandWorm, a biomimetic screw-actuated robot augmented by peristaltic motion to enhance locomotion, and SWTac, a novel event-based visuotactile sensor with an actively vibrated elastomer. The event camera is mechanically decoupled from vibrations by a spring isolation mechanism, enabling high-quality tactile imaging of both dynamic and stationary objects. For algorithm design, we propose an IMU-guided temporal filter to enhance imaging consistency, improving MSNR by 24%. Moreover, we systematically optimize SWTac with vibration parameters, event camera settings and elastomer properties. Motivated by asymmetric edge features, we also implement contact surface estimation by U-Net. Experimental validation demonstrates SWTac's 0.2 mm texture resolution, 98% stone classification accuracy, and 0.15 N force estimation error, while SandWorm demonstrates versatile locomotion (up to 12.5 mm/s) in challenging terrains, successfully executes pipeline dredging and subsurface exploration in complex granular media (observed 90% success rate). Field experiments further confirm the system's practical performance.
https://arxiv.org/abs/2601.14128
Academic Papers
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bcd17aa87bf30f0dcc9463bbbc9ac9888ec0710a84bb5015ef2967776c0ddd2b
2026-01-21T00:00:00-05:00
"Range as a Key" is the Key! Fast and Compact Cloud Block Store Index with RASK
arXiv:2601.14129v1 Announce Type: new Abstract: In cloud block store, indexing is on the critical path of I/O operations and typically resides in memory. With the scaling of users and the emergence of denser storage media, the index has become a primary memory consumer, causing memory strain. Our extensive analysis of production traces reveals that write requests exhibit a strong tendency to target continuous block ranges in cloud storage systems. Thus, compared to current per-block indexing, our insight is that we should directly index block ranges (i.e., range-as-a-key) to save memory. In this paper, we propose RASK, a memory-efficient and high-performance tree-structured index that natively indexes ranges. While range-as-a-key offers the potential to save memory and improve performance, realizing this idea is challenging due to the range overlap and range fragmentation issues. To handle range overlap efficiently, RASK introduces the log-structured leaf, combined with range-tailored search and garbage collection. To reduce range fragmentation, RASK employs range-aware split and merge mechanisms. Our evaluations on four production traces show that RASK reduces memory footprint by up to 98.9% and increases throughput by up to 31.0x compared to ten state-of-the-art indexes.
https://arxiv.org/abs/2601.14129
Academic Papers
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7d185804760b911d0507aca1d5226d463ee64fa9a730ddc1d459761205028cb2
2026-01-21T00:00:00-05:00
GIC-DLC: Differentiable Logic Circuits for Hardware-Friendly Grayscale Image Compression
arXiv:2601.14130v1 Announce Type: new Abstract: Neural image codecs achieve higher compression ratios than traditional hand-crafted methods such as PNG or JPEG-XL, but often incur substantial computational overhead, limiting their deployment on energy-constrained devices such as smartphones, cameras, and drones. We propose Grayscale Image Compression with Differentiable Logic Circuits (GIC-DLC), a hardware-aware codec where we train lookup tables to combine the flexibility of neural networks with the efficiency of Boolean operations. Experiments on grayscale benchmark datasets show that GIC-DLC outperforms traditional codecs in compression efficiency while allowing substantial reductions in energy consumption and latency. These results demonstrate that learned compression can be hardware-friendly, offering a promising direction for low-power image compression on edge devices.
https://arxiv.org/abs/2601.14130
Academic Papers
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df29718504ae6a12138271798e8b5696bc0835aa13ca0d6640121497c4947196
2026-01-21T00:00:00-05:00
Practitioner Views on Mobile App Accessibility: Practices and Challenges
arXiv:2601.14131v1 Announce Type: new Abstract: As mobile applications (apps) become ubiquitous in everyday life, it is crucial for developers to prioritize accessibility for users with diverse abilities. While previous research has identified widespread accessibility issues and raised awareness of developer challenges, there remains a lack of cross-platform, globally representative insights into how practitioners approach accessibility in practice. This paper presents findings from a mixed-methods survey of 110 mobile app developers across 43 countries, examining how platform ecosystems (iOS vs. Android) and developer experience shape accessibility practices. Results show that while developers recognize the importance of accessibility, they often rely on platform-specific guidelines and typically perform compliance testing late in the development process. Developers primarily implement text-focused features while struggling with API limitations and organizational constraints. Through systematic cross-platform comparison, we identify novel platform-specific barriers and demonstrate how accessibility practices differ across developer experience levels. Our findings offer new insights into the challenges of achieving accessibility in practice and provide actionable steps for various stakeholders to promote more consistent and inclusive app development.
https://arxiv.org/abs/2601.14131
Academic Papers
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6dbcff29dcb8697a36bdf76c968bce9b5a97f41fc39da5981404387c39937221
2026-01-21T00:00:00-05:00
Toward self-coding information systems
arXiv:2601.14132v1 Announce Type: new Abstract: In this extended abstract, we propose a novel research topic in the field of agentic AI, which we refer to as self-coding information systems. These systems will be able to dynamically adapt their structure or behavior by evaluating potential adaptation decisions, generate source code, test, and (re)deploy their source code autonomously, at runtime, reducing the time to market of new features. Here we motivate the topic, provide a formal definition of self-coding information systems, discuss some expected impacts of the new technology, and indicate potential research directions.
https://arxiv.org/abs/2601.14132
Academic Papers
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9adafe014fb627013f8bddf9bdc4423aa333db8ca6a4bb1667265a828b5196f0
2026-01-21T00:00:00-05:00
TwinBrainVLA: Unleashing the Potential of Generalist VLMs for Embodied Tasks via Asymmetric Mixture-of-Transformers
arXiv:2601.14133v1 Announce Type: new Abstract: Standard Vision-Language-Action (VLA) models typically fine-tune a monolithic Vision-Language Model (VLM) backbone explicitly for robotic control. However, this approach creates a critical tension between maintaining high-level general semantic understanding and learning low-level, fine-grained sensorimotor skills, often leading to "catastrophic forgetting" of the model's open-world capabilities. To resolve this conflict, we introduce TwinBrainVLA, a novel architecture that coordinates a generalist VLM retaining universal semantic understanding and a specialist VLM dedicated to embodied proprioception for joint robotic control. TwinBrainVLA synergizes a frozen "Left Brain", which retains robust general visual reasoning, with a trainable "Right Brain", specialized for embodied perception, via a novel Asymmetric Mixture-of-Transformers (AsyMoT) mechanism. This design allows the Right Brain to dynamically query semantic knowledge from the frozen Left Brain and fuse it with proprioceptive states, providing rich conditioning for a Flow-Matching Action Expert to generate precise continuous controls. Extensive experiments on SimplerEnv and RoboCasa benchmarks demonstrate that TwinBrainVLA achieves superior manipulation performance compared to state-of-the-art baselines while explicitly preserving the comprehensive visual understanding capabilities of the pre-trained VLM, offering a promising direction for building general-purpose robots that simultaneously achieve high-level semantic understanding and low-level physical dexterity.
https://arxiv.org/abs/2601.14133
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2be1800caed399c69dfa4d98ec67da75f855d074826d44ea46f9d706ea75a273
2026-01-21T00:00:00-05:00
CREATE: Cross-Layer Resilience Characterization and Optimization for Efficient yet Reliable Embodied AI Systems
arXiv:2601.14140v1 Announce Type: new Abstract: Embodied Artificial Intelligence (AI) has recently attracted significant attention as it bridges AI with the physical world. Modern embodied AI systems often combine a Large Language Model (LLM)-based planner for high-level task planning and a reinforcement learning (RL)-based controller for low-level action generation, enabling embodied agents to tackle complex tasks in real-world environments. However, deploying embodied agents remains challenging due to their high computation requirements, especially for battery-powered local devices. Although techniques like lowering operating voltage can improve energy efficiency, they can introduce bit errors and result in task failures. In this work, we propose CREATE, a general design principle that leverages heterogeneous resilience at different layers for synergistic energy-reliability co-optimization. For the first time, we conduct a comprehensive error injection study on modern embodied AI systems and observe an inherent but heterogeneous fault tolerance. Building upon these insights, we develop an anomaly detection and clearance mechanism at the circuit level to eliminate outlier errors. At the model level, we propose a weight-rotation-enhanced planning algorithm to improve the fault tolerance of the LLM-based planner. Furthermore, we introduce an application-level technique, autonomy-adaptive voltage scaling, to dynamically adjust the operating voltage of the controllers. The voltage scaling circuit is co-designed to enable online voltage adjustment. Extensive experiments demonstrate that without compromising task quality, CREATE achieves 40.6% computational energy savings on average over nominal-voltage baselines and 35.0% over prior-art techniques. This further leads to 29.5% to 37.3% chip-level energy savings and approximately a 15% to 30% improvement in battery life.
https://arxiv.org/abs/2601.14140
Academic Papers
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8d36acca8518bcbe3eadad05d12ff1bd92e24c5bc93c938679794eea3dfe3a44
2026-01-21T00:00:00-05:00
Vector Coded Caching Multiplicatively Boosts MU-MIMO Systems Under Practical Considerations
arXiv:2601.14142v1 Announce Type: new Abstract: This work presents a first comprehensive analysis of the impact of vector coded caching (VCC) in multi-user multiple-input multiple-output (MU-MIMO) systems with multiple receive antennas and variable pathloss -- two key factors that critically influence systems with inherent MU unicasting behavior. We investigate two widely adopted precoding strategies: (i) blockdiagonalization (BD) at the transmitter combined with maximal ratio combining (MRC) at the receivers, and (ii) zero-forcing (ZF) precoding. Our analysis explicitly accounts for practical considerations such as channel fading, channel state information (CSI) acquisition overhead, and fairness-oriented power allocation. Our contributions span both analytical and simulation-based fronts. On the analytical side, we derive analytical expressions for the achievable throughput under BD-MRC and ZF, highlighting the performance benefits of equipping multi-antenna users with cache-aided interference management. Specifically, we develop a low-complexity BD-MRC optimization method that leverages matrix structure to significantly reduce the dimensionality involved in precoding computation, followed by solving the associated maxmin fairness problem through an efficient one-dimensional search. In the massive MIMO regime, an asymptotic expression for the achievable throughput over Rayleigh fading channels is also derived. Simulations validate our theoretical results, confirming that VCC delivers substantial performance gains over optimized cacheless MU-MIMO systems. For example, with 32 transmit antennas and 2 receive antennas per user, VCC yields throughput improvements exceeding 300%. These gains are further amplified under imperfect CSI at the transmitter, where VCC's ability to offload interference mitigation to the receivers ensures robust performance even in the face of degraded CSI quality and elevated acquisition costs.
https://arxiv.org/abs/2601.14142
Academic Papers
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7d0cd0e0bfb3a38b84c1ea334226454edea425f09c6d95b067e594d0002b8af1
2026-01-21T00:00:00-05:00
The Quest for Reliable AI Accelerators: Cross-Layer Evaluation and Design Optimization
arXiv:2601.14148v1 Announce Type: new Abstract: As the CMOS technology pushes to the nanoscale, aging effects and process variations have become increasingly pronounced, posing significant reliability challenges for AI accelerators. Traditional guardband-based design approaches, which rely on pessimistic timing margin, sacrifice significant performance and computational efficiency, rendering them inadequate for high-performance AI computing demands. Current reliability-aware AI accelerator design faces two core challenges: (1) the lack of systematic cross-layer analysis tools to capture coupling reliability effects across device, circuit, architecture, and application layers; and (2) the fundamental trade-off between conventional reliability optimization and computational efficiency. To address these challenges, this paper systematically presents a series of reliability-aware accelerator designs, encompassing (1) aging and variation-aware dynamic timing analyzer, (2) accelerator dataflow optimization using critical input pattern reduction, and (3) resilience characterization and novel architecture design for large language models (LLMs). By tightly integrating cross-layer reliability modeling and AI workload characteristics, these co-optimization approaches effectively achieve reliable and efficient AI acceleration.
https://arxiv.org/abs/2601.14148
Academic Papers
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b1d33ac08d3fbf879735c89bc066c31d8f621baffe7b1cfbd616a75dcc84df12
2026-01-21T00:00:00-05:00
Lost in the Prompt Order: Revealing the Limitations of Causal Attention in Language Models
arXiv:2601.14152v1 Announce Type: new Abstract: Large language models exhibit surprising sensitivity to the structure of the prompt, but the mechanisms underlying this sensitivity remain poorly understood. In this work, we conduct an in-depth investigation on a striking case: in multiple-choice question answering, placing context before the questions and options (CQO) outperforms the reverse order (QOC) by over 14%p, consistently over a wide range of models and datasets. Through systematic architectural analysis, we identify causal attention as the core mechanism: in QOC prompts, the causal mask prevents option tokens from attending to context, creating an information bottleneck where context becomes invisible to options.
https://arxiv.org/abs/2601.14152
Academic Papers
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8ba86b7eddf001ec8391b2345e2087b1d97d0d227187ecd75aa8dc8d349af9a5
2026-01-21T00:00:00-05:00
LLM Augmented Intervenable Multimodal Adaptor for Post-operative Complication Prediction in Lung Cancer Surgery
arXiv:2601.14154v1 Announce Type: new Abstract: Postoperative complications remain a critical concern in clinical practice, adversely affecting patient outcomes and contributing to rising healthcare costs. We present MIRACLE, a deep learning architecture for prediction of risk of postoperative complications in lung cancer surgery by integrating preoperative clinical and radiological data. MIRACLE employs a hyperspherical embedding space fusion of heterogeneous inputs, enabling the extraction of robust, discriminative features from both structured clinical records and high-dimensional radiological images. To enhance transparency of prediction and clinical utility, we incorporate an interventional deep learning module in MIRACLE, that not only refines predictions but also provides interpretable and actionable insights, allowing domain experts to interactively adjust recommendations based on clinical expertise. We validate our approach on POC-L, a real-world dataset comprising 3,094 lung cancer patients who underwent surgery at Roswell Park Comprehensive Cancer Center. Our results demonstrate that MIRACLE outperforms various traditional machine learning models and contemporary large language models (LLM) variants alone, for personalized and explainable postoperative risk management.
https://arxiv.org/abs/2601.14154
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3341ccdf175cf8fd06e20dcf2ad8cd61bd71a2944fff943a4361e63a7ca58622
2026-01-21T00:00:00-05:00
ConceptCaps -- a Distilled Concept Dataset for Interpretability in Music Models
arXiv:2601.14157v1 Announce Type: new Abstract: Concept-based interpretability methods like TCAV require clean, well-separated positive and negative examples for each concept. Existing music datasets lack this structure: tags are sparse, noisy, or ill-defined. We introduce ConceptCaps, a dataset of 23k music-caption-audio triplets with explicit labels from a 200-attribute taxonomy. Our pipeline separates semantic modeling from text generation: a VAE learns plausible attribute co-occurrence patterns, a fine-tuned LLM converts attribute lists into professional descriptions, and MusicGen synthesizes corresponding audio. This separation improves coherence and controllability over end-to-end approaches. We validate the dataset through audio-text alignment (CLAP), linguistic quality metrics (BERTScore, MAUVE), and TCAV analysis confirming that concept probes recover musically meaningful patterns. Dataset and code are available online.
https://arxiv.org/abs/2601.14157
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896f001290740d96a84fa5b0657d1a0c33537c10fe80b15b95d7ba70bd8a51ad
2026-01-21T00:00:00-05:00
Multi-Partner Project: Multi-GPU Performance Portability Analysis for CFD Simulations at Scale
arXiv:2601.14159v1 Announce Type: new Abstract: As heterogeneous supercomputing architectures leveraging GPUs become increasingly central to high-performance computing (HPC), it is crucial for computational fluid dynamics (CFD) simulations, a de-facto HPC workload, to efficiently utilize such hardware. One of the key challenges of HPC codes is performance portability, i.e. the ability to maintain near-optimal performance across different accelerators. In the context of the \textbf{REFMAP} project, which targets scalable, GPU-enabled multi-fidelity CFD for urban airflow prediction, this paper analyzes the performance portability of SOD2D, a state-of-the-art Spectral Elements simulation framework across AMD and NVIDIA GPU architectures. We first discuss the physical and numerical models underlying SOD2D, highlighting its computational hotspots. Then, we examine its performance and scalability in a multi-level manner, i.e. defining and characterizing an extensive full-stack design space spanning across application, software and hardware infrastructure related parameters. Single-GPU performance characterization across server-grade NVIDIA and AMD GPU architectures and vendor-specific compiler stacks, show the potential as well as the diverse effect of memory access optimizations, i.e. 0.69$\times$ - 3.91$\times$ deviations in acceleration speedup. Performance variability of SOD2D at scale is further examined on the LUMI multi-GPU cluster, where profiling reveals similar throughput variations, highlighting the limits of performance projections and the need for multi-level, informed tuning.
https://arxiv.org/abs/2601.14159
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399757fe0954ba1e6dd335698588b3137eb1e26e278ca18a29278ed026f327d3
2026-01-21T00:00:00-05:00
Gouy phase-assisted Zeno effect for protecting light structure in random media
arXiv:2601.11591v1 Announce Type: new Abstract: Identifying physical mechanisms that protect the information carried by various forms of structured light is one of the cornerstones of today's classical and quantum communications. Here we show that the purity of orbital angular momentum (OAM) modes can be protected against degradation in random media by leveraging two fundamental features of their own Schr\"odinger Hamiltonian dynamics, namely, Zeno effect -- frequent observations slow down the evolution -- , and Gouy phase -- the back-action of the observation. Repeated, OAM-dependent Gouy phase kicks imparted along the disturbing path by simple imaging systems trigger the optical Zeno effect that protects the input OAM mode against mode cross-talk that would broaden the OAM spectrum. Given the universality of the mechanism, the Gouy phase-assisted Zeno effect would protect propagation modes other than those of OAM, and the diverse forms of structured light built with them.
https://arxiv.org/abs/2601.11591
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589113fa638df5e185b5e59cf11f7d8e67f1366a50af073c303d85948b9feaf6
2026-01-21T00:00:00-05:00
Low-Dimensional Interaction Spaces Impose Geometric Constraints On Collective Organization
arXiv:2601.11592v1 Announce Type: new Abstract: Collective organization in physical, biophysical, and biological systems often emerges from many weak, local interactions, yet the resulting global structures display striking regularities and apparent limits in diversity. Existing theoretical approaches typically emphasize specific mechanisms, detailed dynamics, or energetic optimization, making it difficult to identify constraints that are independent of microscopic realization. Here we develop a general theoretical framework showing that, when effective interactions among system components compress into a low-dimensional interaction space, global organization is governed by geometric constraints rather than detailed dynamics. We formalize interaction spaces as metric manifolds derived from coarse-grained effective couplings and show that low interaction dimensionality imposes upper bounds on the number, separability, and robustness of distinct collective organizations. These results yield impossibility statements: many conceivable macroscopic organizations are excluded a priori, even when locally compatible interactions exist. The framework applies across equilibrium and nonequilibrium systems without assuming specific symmetries or conservation laws. By shifting the explanatory focus from generative mechanisms to structural constraints, this work establishes a general, geometry-based perspective on collective organization.
https://arxiv.org/abs/2601.11592
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358ab4b5156a108b283e7b019bdd774b071018918f24be2aa45a2a2a9b3899f1
2026-01-21T00:00:00-05:00
The physics of cranberry bogs
arXiv:2601.11593v1 Announce Type: new Abstract: The common New England sight of a cranberry bog presents a rich tapestry of fluid dynamics and soft matter phenomena. Here, we present four connected problems exploring the behavior of cranberries in their stages of harvest: the buoyant rise of a cranberry in a flooded bog, the stable floating configuration of a cranberry on the surface, the aggregation and interaction between many floating cranberries collected with a boom, and the piling of cranberries onto a truck for transportation. We model these phenomena from first principles and develop simple computational simulations of their collective behaviors. Additionally, we describe tabletop experiments to accompany these problems, either as in-class demonstrations or lab activities. Throughout, we draw connections to broader physical principles in soft condensed matter and fluids, allowing the real-world example of the cranberry bog to serve as a bridge between the undergraduate curriculum and topics in soft matter research.
https://arxiv.org/abs/2601.11593
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4f0045957b3c02c39492bce403babee0dcb5d191fb61e08e8274108a43606ef4
2026-01-21T00:00:00-05:00
Multi-Scale Negative Coupled Information Systems (MNCIS): A Unified Spectral Topology Framework for Stability in Turbulence, AI, and Biology
arXiv:2601.11594v1 Announce Type: new Abstract: Complex dynamical systems frequently encounter a recurrent structural instability: the collapse of the spectral gap, driving the system toward a low-dimensional "Zero-Mode Attractor" (e.g., spectral pile-up or over-smoothing). Building upon recent global well-posedness estimates [Hou, arXiv:2601.00638], this work generalizes the Multi-Scale Negative Coupled Information System (MNCIS) framework. We postulate that global stability requires an active topological operator -- Adaptive Spectral Negative Coupling (ASNC) -- functioning as a state-dependent high-pass filter that penalizes entropy accumulation at spectral boundaries. We validate this unified framework via three implementations:(1) Hydrodynamics: In 3D Navier-Stokes turbulence ($N=256^3$), ASNC acts as a global-enstrophy adaptive sub-grid scale (SGS) model, stabilizing the inviscid limit and preserving the Kolmogorov $-5/3$ inertial range without artificial hyper-viscosity.(2) Artificial Intelligence: Addressing Over-smoothing in Graph Neural Networks (GNNs), we implement ASNC as a parameter-free topological constraint. Unlike baselines (e.g., DeepGCNs) relying on dense residual connections to bypass signal decay, our framework enables the training of ultra-deep 64-layer networks without residual connections, maintaining perfectly stationary feature variance ($\sigma^2 \equiv 1.0$) on the ogbn-arxiv benchmark. (3) Biological Physics: In reaction-diffusion morphogenesis, it stabilizes Turing patterns against diffusive washout in high-entropy regimes. Our results suggest that the MNCIS framework provides a base-independent topological condition for distinguishing viable complex systems from those collapsing into thermal equilibrium, bridging physical stability and information persistence.
https://arxiv.org/abs/2601.11594
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afecb9153ebf2d7113a7cd045926d21aa78faef7fab79410bc9e6d6ba9e163d6
2026-01-21T00:00:00-05:00
Is it possible to describe an electron by the evolution of a single point?
arXiv:2601.11597v1 Announce Type: new Abstract: The answer to the title-question is positive. The analysis of the geometry of continuous and differentiable curves in three-dimensional Euclidean space suggests that the point represents the location of the center of charge of the electron, satisfies a system of ordinary differential equations of fourth order, and moves at the speed of light. The center of mass of the electron is a different point and will be determined by the evolution of the center of charge. It is the relative motion of the center of charge around the center of mass that gives rise to the spin and magnetic properties.
https://arxiv.org/abs/2601.11597
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ce1afcd91bd51951ed47ad0276375ef3ed8544aa530584cfd3c954886740dba5
2026-01-21T00:00:00-05:00
Computation as Organisation
arXiv:2601.11599v1 Announce Type: new Abstract: Computation is commonly defined as the execution of abstract algorithms over symbolic representations, with physical systems treated as substrates that realise predefined operations. While effective for engineered machines, this separation becomes problematic when applied to living systems, where persistence, adaptation, and failure occur without symbolic instruction or central control. Here, computation is reformulated as a structural property of organised matter. Organisation is defined as the persistence of relational constraints that delimit admissible state transitions. Information is not encoded content but relational invariance: differences that influence future behaviour by reshaping what transitions remain possible. Computation is identified with the ongoing enactment of such organisation, integrating memory, processing, and execution as inseparable aspects of material dynamics. Within this framework, algorithms correspond to internally embedded regularities enabled by constraint, and computational limits arise from organisation itself. The account provides experimentally accessible criteria for computation based on persistence, recovery, and structural failure under perturbation.
https://arxiv.org/abs/2601.11599
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f604c3be33176c9f812fe41d5a6a9fe3695af6c594ec16c7c9f9643e56ec6146
2026-01-21T00:00:00-05:00
The use of spectral indices in environmental monitoring of smouldering coal-waste dumps
arXiv:2601.11603v1 Announce Type: new Abstract: The study aimed to evaluate the applicability of environmental indices in the monitoring of smouldering coal-waste dumps. A dump located in the Upper Silesian Coal Basin served as the research site for a multi-method analysis combining remote sensing and field-based data. Two UAV survey campaigns were conducted, capturing RGB, infrared, and multispectral imagery. These were supplemented with direct ground measurements of subsurface temperature and detailed vegetation mapping. Additionally, publicly available satellite data from the Landsat and Sentinel missions were analysed. A range of vegetation and fire-related indices (NDVI, SAVI, EVI, BAI, among others) were calculated to identify thermally active zones and assess vegetation conditions within these degraded areas. The results revealed strong seasonal variability in vegetation indices on thermally active sites, with evidence of disrupted vegetation cycles, including winter greening in moderately heated root zones - a pattern indicative of stress and degradation processes. While satellite data proved useful in reconstructing the fire history of the dump, their spatial resolution was insufficient for detailed monitoring of small-scale thermal anomalies. The study highlights the diagnostic potential of UAV-based remote sensing in post-industrial environments undergoing land degradation but emphasises the importance of field validation for accurate environmental assessment.
https://arxiv.org/abs/2601.11603
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28362cff27ce6c6e303c89cb75951dc8823be7eb9bce4b17b325b779b51643f7
2026-01-21T00:00:00-05:00
Level set-based topology optimization of micropolar solids under thermo-mechanical loading
arXiv:2601.11607v1 Announce Type: new Abstract: We propose a novel level set-based topology optimization for micropolar solids subjected to thermo-mechanical loading. To capture the size effects, we have incorporated the microstructural length-scale information into the level set-based topology optimization method by adopting a micropolar theory. The proposed non-local topology optimization method can provide accurate topology optimization for size-dependent solids under thermo-mechanical loading. We have demonstrated the effectiveness of the proposed method through a few representative two-dimensional benchmark problems. The numerical results reveal the substantial influence of underlying micro-structures, incorporated in the model through micropolar parameters, and temperature on topology optimization, highlighting the necessity of the proposed thermo-mechanical micropolar formulation for materials with pronounced non-local effects. For the numerical implementation of the proposed model, we have used open-source finite element libraries, \texttt{Gridap.jl}, and \texttt{GridapTopOpt.jl}, available in Julia, to ensure transparency and reproducibility of the reported computational results.
https://arxiv.org/abs/2601.11607
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7c21b37107dcbe8837e72023b81f6129d477067615d4fc10a176fb8c91c42fac
2026-01-21T00:00:00-05:00
Wattnet: matching electricity consumption with low-carbon, low-water footprint energy supply
arXiv:2601.11623v1 Announce Type: new Abstract: The environmental impact of electricity consumption is commonly assessed through its carbon footprint (CF), while water-related impacts are often overlooked despite the strong interdependence between energy and water systems. This is particularly relevant for electricity-intensive activities such as data center (DC) operations, where both carbon emissions and water use occur largely off-site through electricity consumption. In this work, we present Wattnet, an open-source tool that jointly assesses the CF and water footprint (WF) of electricity consumption across Europe with high temporal resolution. Wattnet implements an electricity flow-tracing methodology that accounts for local generation mixes, as well as for cross-border electricity imports and exports at a 15-minute resolution. Operational and life-cycle impact factors are used to quantify and compare local (generation-based) and global (consumption-based) footprints for multiple European regions during 2024. The results demonstrate that neglecting electricity flows and temporal variability can lead to significant misestimations of both CF and WF, particularly in countries with high levels of electricity trade or hydropower dependence. Furthermore, the joint analysis reveals trade-offs between decarbonisation and water use, highlighting the prominent role of reservoir-based hydropower in increasing WF even in low-carbon systems. Wattnet facilitates informed decision-making for workload scheduling and energy-aware operation of DCs, while also enhancing transparency regarding the environmental impacts of electricity consumption for end users and policymakers.
https://arxiv.org/abs/2601.11623
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c5a40535488d32d9acf810e3cd24772605f8190ad5beb2cc39af485957fff599
2026-01-21T00:00:00-05:00
Developing a Machine-Learning Interatomic Potential for Non-Covalent Interactions in Proteins
arXiv:2601.11628v1 Announce Type: new Abstract: Machine learning interatomic potentials (MLIPs) enable efficient modeling of molecular interactions with quantum mechanical (QM) accuracy. However, constructing robust and representative training datasets that capture subtle, system-specific interaction motifs remains challenging. We introduce PANIP (PAirwise Non-covalent Interaction Potential), an ensemble MLIP model built upon the NequIP framework and trained on non-covalent interactions (NCIs) between protein-derived fragments. PANIP is trained using an automated multi-fidelity active learning (MFAL) workflow, in which a representative training subset, termed PDB-FRAGID (PDB Fragment Interaction Dataset), was distilled from an otherwise prohibitively large pool of fragment dimers extracted from the Protein Data Bank (PDB). PANIP retains {\omega}B97X-D3BJ/def2-TZVPP-level accuracy and achieves mean absolute errors below 0.2 kcal/mol on out-of-distribution systems, demonstrating excellent transferability across diverse NCI motifs. Compared to the widely used ANI-2x potential, PANIP delivers substantially lower errors, particularly for charged and strongly interacting dimers. Coupled with a fragmentation-based energy decomposition scheme, PANIP estimates protein-ligand binding energies at near force-field computational cost yet QM-level accuracy, enabling its use as a fragment-based scoring function that rivals specialized docking scoring functions.
https://arxiv.org/abs/2601.11628
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6289b992797cfa4e31fce26281631b5b6d9f7f94db24bdf4786f437b7d054170
2026-01-21T00:00:00-05:00
Large Language Model Agent for User-friendly Chemical Process Simulations
arXiv:2601.11650v1 Announce Type: new Abstract: Modern process simulators enable detailed process design, simulation, and optimization; however, constructing and interpreting simulations is time-consuming and requires expert knowledge. This limits early exploration by inexperienced users. To address this, a large language model (LLM) agent is integrated with AVEVA Process Simulation (APS) via Model Context Protocol (MCP), allowing natural language interaction with rigorous process simulations. An MCP server toolset enables the LLM to communicate programmatically with APS using Python, allowing it to execute complex simulation tasks from plain-language instructions. Two water-methanol separation case studies assess the framework across different task complexities and interaction modes. The first shows the agent autonomously analyzing flowsheets, finding improvement opportunities, and iteratively optimizing, extracting data, and presenting results clearly. The framework benefits both educational purposes, by translating technical concepts and demonstrating workflows, and experienced practitioners by automating data extraction, speeding routine tasks, and supporting brainstorming. The second case study assesses autonomous flowsheet synthesis through both a step-by-step dialogue and a single prompt, demonstrating its potential for novices and experts alike. The step-by-step mode gives reliable, guided construction suitable for educational contexts; the single-prompt mode constructs fast baseline flowsheets for later refinement. While current limitations such as oversimplification, calculation errors, and technical hiccups mean expert oversight is still needed, the framework's capabilities in analysis, optimization, and guided construction suggest LLM-based agents can become valuable collaborators.
https://arxiv.org/abs/2601.11650
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af6c6cd55059c46748e73aff270a9bd428569b0d070eab4bb6fa16cee69baa50
2026-01-21T00:00:00-05:00
AllShowers: One model for all calorimeter showers
arXiv:2601.11716v1 Announce Type: new Abstract: Accurate and efficient detector simulation is essential for modern collider experiments. To reduce the high computational cost, various fast machine learning surrogate models have been proposed. Traditional surrogate models for calorimeter shower modeling train separate networks for each particle species, limiting scalability and reuse. We introduce AllShowers, a unified generative model that simulates calorimeter showers across multiple particle types using a single generative model. AllShowers is a continuous normalizing flow model with a Transformer architecture, enabling it to generate complex spatial and energy correlations in variable-length point cloud representations of showers. Trained on a diverse dataset of simulated showers in the highly granular ILD detector, the model demonstrates the ability to generate realistic showers for electrons, photons, and charged and neutral hadrons across a wide range of incident energies and angles without retraining. In addition to unifying shower generation for multiple particle types, AllShowers surpasses the fidelity of previous single-particle-type models for hadronic showers. Key innovations include the use of a layer embedding, allowing the model to learn all relevant calorimeter layer properties; a custom attention masking scheme to reduce computational demands and introduce a helpful inductive bias; and a shower- and layer-wise optimal transport mapping to improve training convergence and sample quality. AllShowers marks a significant step towards a universal model for calorimeter shower simulations in collider experiments.
https://arxiv.org/abs/2601.11716
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14b49cbfbb53e12ee4ed9a7dc7a365df4bf53b69b74a6b581d89d0800e9c6b36
2026-01-21T00:00:00-05:00
Coupled two-phase flow and surfactant/PFAS transport in porous media with angular pores: From pore-scale physics to Darcy-scale modeling
arXiv:2601.11721v1 Announce Type: new Abstract: Two-phase surfactant-laden flow and transport in porous media are central to many natural and engineering applications. Surfactants alter two-phase flow by modifying interfacial tension and wettability, while two-phase flow controls surfactant transport pathways and interfacial adsorption. These coupled processes are commonly modeled using Darcy-type two-phase flow equations combined with advection--dispersion--adsorption transport equations, with capillary pressure--saturation relationships scaled by the Leverett $J$-function. However, the Leverett $J$-function idealizes porous media as bundles of cylindrical tubes and decouples interfacial tension and wettability, limiting its ability to represent angular pore geometries and interfacial tension--wettability coupling effects. We present a modeling framework that explicitly incorporates pore angularity and interfacial tension--wettability coupling into Darcy-scale surfactant-laden flow and transport models. Two-phase flow properties are derived for angular pores, upscaled across pore size distributions, and formulated as explicit and closed-form expressions. These upscaled relationships are integrated into a coupled flow--transport model to simulate transient two-phase flow and surfactant transport. Results reveal a nonlinear and nonmonotonic dependence of two-phase flow properties on pore angularity, pore size distribution, and interfacial tension. Example simulations of water flow and PFAS migration in unsaturated soils indicate that surfactant-induced flow effects on PFAS leaching are generally minor under typical conditions, whereas pore angularity strongly controls water flow, interfacial area, and PFAS retention. Overall, the proposed framework provides a more physically grounded approach for modeling two-phase surfactant-laden flow and transport in porous media.
https://arxiv.org/abs/2601.11721
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d37afeece954e52ad1379423adc7d739b2a2492ef807909eb693dd95dae8bc39
2026-01-21T00:00:00-05:00
Dose-LET Interactions Predict Capsular Contracture After Proton Postmastectomy Radiation Therapy
arXiv:2601.11731v1 Announce Type: new Abstract: Pencil beam scanning (PBS) proton therapy provides highly conformal dose distributions that are increasingly leveraged for postmastectomy radiation therapy (PMRT) to reduce cardiopulmonary exposure. However, implant-based reconstruction in the setting of PMRT remains vulnerable to capsular contracture, and biological mechanisms of possible high linear energy transfer (LET) in PBS have not been well characterized. A retrospective case-control study was conducted on consecutive breast cancer patients who underwent mastectomy followed by implant-based reconstruction and proton PMRT (50 Gy in 25 fractions) between 2015 and 2021. Dose-LET volume histograms (DLVHs) were calculated for peri-implant tissue (5-mm shell around the implant). Generalized linear mixed-effects regression (GLMER) was employed to identify DLVH indices significantly associated with capsular contracture. Spearman correlation analysis was used to eliminate redundance. DLVCs were derived from receiver operating characteristic (ROC) analysis and validated using support vector machine (SVM)-based normal tissue complication probability (NTCP) model. Eight capsular contracture and 16 matched controls patients were analyzed. Three independent and significant DLVH indices were identified(p 96.98%. The SVM-based NTCP model achieved an area under the ROC curve (AUROC) of 0.867, with 91.7% accuracy, 87.5% sensitivity, and 93.8% specificity. Capsular contracture following proton PMRT is significantly associated with the synergistic interplay between dose and LETd in peri-implant tissue. The derived DLVCs provide actionable dosimetric constraints that can be integrated into treatment planning to minimize capsular contracture risk in proton PMRT.
https://arxiv.org/abs/2601.11731
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61bfe613bbb11a080286e57a00d79ba6e56565cec4082d1421f465829bc099d3
2026-01-21T00:00:00-05:00
Ultra-broadband Mid to Long-wave Infrared Spintronic Poisson Bolometer
arXiv:2601.11733v1 Announce Type: new Abstract: Infrared detectors have traditionally been divided into two fundamental classes, mid-wave (MWIR, 3-5 um) and long-wave (LWIR, 8-14 um). Integrating MWIR and LWIR within a single device is challenging due to distinct materials, cooling needs, and detection mechanisms, while such integration is critical for improved object recognition, temperature estimation, and environmental sensing. In this work, we demonstrate a Spintronic Poisson (SP) bolometer enabling room-temperature ultra-broadband sensing across 3-14 um. Unlike conventional bolometers that rely on continuous analog signals, the SP bolometer implements a Poisson-counting detection paradigm, encoding temperature in discrete stochastic events, which turns thermal noise from a limitation into the basis of the estimator itself. We fabricate the SP bolometer using a spintronic transduction layer integrated with a plasmonic nanoantenna array to enhance broadband infrared absorption. Using spintronic transduction, the device achieves the noise-equivalent temperature difference (NETD, thermal sensitivity metric) of 80-100 mK at 300 K, surpassing uncooled detectors and approaching cooled technologies. This work establishes a statistical detection paradigm for room-temperature infrared sensing with broad application potential.
https://arxiv.org/abs/2601.11733
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608c756353023953c55e7cc1fa643ad97c0a23326a6a9a386c3b85467900e74a
2026-01-21T00:00:00-05:00
A 25 THz bandwidth THz spectroscopy system exploiting BNA crystals and a tunable single-ring-fiber pulse compressor
arXiv:2601.11764v1 Announce Type: new Abstract: We present a terahertz time-domain spectroscopy (THz-TDS) system which accesses a broadband spectrum, efficiently covering the so-called "new THz gap" between 5 and 15 THz and extending beyond 25 THz. The system exploits nonlinear interactions within the organic crystal BNA (N-benzyl-2-methyl-4-nitroaniline) to generate and detect THz radiation upon excitation by a near-infrared (NIR) pulse centered at 1.03 $\mu$m. To enable broadband THz spectral monitoring, the NIR pulse from a Yb-based solid-state laser undergoes spectral broadening in a gas-filled single-ring hollow-core photonic crystal fiber, followed by a pulse compression to achieve durations as short as 31 fs. This approach paves the way for broadband spectroscopy in hard-to-access THz regions using widely available near-infrared ultrafast sources.
https://arxiv.org/abs/2601.11764
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66b758f459e7f43c1586bc05984c2c4d9b2ecb0f9d6f156211bb0c6b4b19efed
2026-01-21T00:00:00-05:00
A wafer-scale ultrasensitive programmable chiroptical sensor
arXiv:2601.11774v1 Announce Type: new Abstract: Chiroptical enantioselective sensing is gaining traction across various applications. However, intrinsic molecular chiroptical responses are weak, and existing amplification approaches add synthesis, manufacturing, or operational complexity that limits sensitivity, scalability, and dynamic control. Here, we present a fundamentally new sensing paradigm merging adsorption-driven chirality induction with wafer-scale optical transduction in a programmable heterostructure containing twisted aligned carbon nanotubes (CNTs) and phase change materials (PCMs). Chiral molecules adsorb onto CNTs to form chiroptically active composites that are macroscopically assembled by alignment and rotational stacking, yielding large ultraviolet circular dichroism (CD). We resolve molecule concentration and handedness in a single device without lithography, hotspot delivery, or differential protocols, achieving sub-$\mu$M sensitivity for CD-silent glucose and chiral amino acids enabled by $>10^5\,\mathrm{M^{-1}}$ adsorption constants. We validate adsorption using molecular dynamics simulations, reproduce experimental results using chiral transfer matrix simulations, and realize sensor programmability by tuning the PCM layer. This platform enables cost-effective in-situ enantiomer monitoring in aqueous environments.
https://arxiv.org/abs/2601.11774
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323c81a9ff8d1457acb5c5f97edd8544a0308bb9cb818e7e6ebe23f95cf55ac5
2026-01-21T00:00:00-05:00
Time-dependent density functional theory study of strong-field laser-induced coulomb explosion of the HCl dimer
arXiv:2601.11823v1 Announce Type: new Abstract: We present a channel-resolved interpretation of laser-driven Coulomb explosion of the HCl dimer from an ensemble of trajectories. Three dominant outcomes are identified: a minor three-body channel and two four-body channels (sequential and near-simultaneous dissociation of both molecules). The key result is that pathway selection is strongly correlated with the degree of ionization during the laser interaction, which is in turn strongly modulated by laser-molecule orientation. Higher early-time ionization predisposes the system toward near-simultaneous four-body breakup, whereas lower ionization favors sequential and three-body fragmentation; for low-ionization cases, a fragment-resolved charge metric further differentiates three-body and sequential behavior. These charge-dependent trends consistently map onto experimentally accessible observables: the simultaneous mechanism dominates the high-energy tail of the kinetic energy release (KER) spectrum and populate distinct regions of the emission-angle distributions, while sequential events concentrate at lower KER. Overall, early-time charge evolution provides a unifying explanation for channel branching and for the channel-resolved fragmentation signatures.
https://arxiv.org/abs/2601.11823
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36cd7f8775db56e83e38c216b3ad512b41ae97cd500af55bf2bbf4119ed743e4
2026-01-21T00:00:00-05:00
Sub-Doppler rubidium atom cooling using a programmable agile integrated PZT-on-SiN resonator
arXiv:2601.11834v1 Announce Type: new Abstract: Programmability and precise control of laser frequency are essential for quantum experiments and applications such as atomic clocks, quantum computers, and cold-atom sensors. Current systems use bulky, power-hungry modulators and frequency shifters which are difficult to integrate and limit portability and scalability. We report an electrically controllable, agile optical frequency source based on a semiconductor laser stabilized to a photonic-integrated, lead zirconate titanate (PZT)-actuated resonator cavity. We demonstrate this approach with precision programmable frequency control of a 780-nm laser that can periodically reference to rubidium spectroscopy followed by fast, programmable, arbitrary frequency tuning sequences for quantum control. We use this approach to demonstrate sub-Doppler cooling of rubidium-87 without any external modulators, achieving atom-cloud temperatures as low as 16 $\mu$K. The device achieves a tuning strength up to 1 GHz/V with 11 MHz modulation bandwidth while consuming only 10 nW of electrical power. This work establishes a route toward compact, low-power, and chip-scale laser systems for next-generation quantum and atomic sensing technologies.
https://arxiv.org/abs/2601.11834
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6b5992486f906c5117ba7feb2d69701ac758b8459940d8cceee1d2329aa20d25
2026-01-21T00:00:00-05:00
High-Voltage Performance Testing in LAr of the PMMA Cathode Connection for the DarkSide-20k Experiment
arXiv:2601.11837v1 Announce Type: new Abstract: DarkSide--20k (DS--20k) is a next--generation dual--phase liquid argon (LAr) time projection chamber (TPC) devoted to the direct--detection of dark matter. The detector is currently under construction in Hall--C at the Laboratori Nazionali del Gran Sasso, Italy, at a depth of approximately 3500 m water equivalent. The detector will instrument 49.7~t of low--radioactivity underground LAr contained within an acrylic TPC and is designed to reach a WIMP--nucleon spin--independent cross--section sensitivity down to $10^{-48}\,\mathrm{cm}^{2}$ for a WIMP mass of $0.1\,\mathrm{TeV}/c^{2}$ in a 200~tonne--year run. In DS--20k a uniform electric drift field is established in the active volume to transport ionization electrons toward the electroluminescence region, with the required high voltage delivered to the TPC cathode through a custom cable and stress--cone assembly. At the University of California, Davis, a dedicated test setup was developed to reproduce the DS--20k cathode high--voltage connection in LAr, matching the local electric--field conditions. This work summarizes the results of a comprehensive test campaign validating the operation of the DS--20k cathode HV system in LAr up to $-100$~kV.
https://arxiv.org/abs/2601.11837
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52abb6aaee58ebdba41f7616643031dd01f1a3f2931e06b0e18f9a3048ca3bbb
2026-01-21T00:00:00-05:00
Extension of the CIPSI-Driven CC($P$;$Q$) Approach to Excited Electronic States
arXiv:2601.11856v1 Announce Type: new Abstract: We extend the CIPSI-driven CC($P$;$Q$) methodology [K. Gururangan et al., J. Chem. Phys. 155 (2021) 174114], in which the leading higher-than-doubly excited determinants are identified using the selected configuration interaction (CI) approach abbreviated as CIPSI, to excited electronic states via the equation-of-motion (EOM) coupled-cluster (CC) formalism. By examining vertical excitations in CH+ at equilibrium and stretched geometries, adiabatic excitations in CH, and ground- and excited-state potential cuts of water, we demonstrate that the CIPSI-driven CC($P$;$Q$) method converges parent CC/EOMCC singles, doubles, and triples energetics from relatively inexpensive Hamiltonian diagonalizations in CI spaces smaller than the corresponding triples manifolds.
https://arxiv.org/abs/2601.11856
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e51765dc645bad785dff5309dfb12a8c7f8cd99ea3d80958654f06729fc20267
2026-01-21T00:00:00-05:00
Integrated nano electro-optomechanical spiking neuron
arXiv:2601.11857v1 Announce Type: new Abstract: Neuromorphic computing offers a pathway toward energy-efficient processing of data, yet hardware platforms combining nanoscale integration and multimodal functionality remain scarce. Here we demonstrate a gallium-phosphide electro-optomechanical spiking neuron that integrates optical and electromechanical interfaces within a single nanostructure on a silicon photonic chip operating at telecommunication wavelengths (1550 nm) and exploiting a 3 gigahertz-frequency mechanical mode. Our device displays excitable dynamics, generating optical spikes at its output, as in the spiking activity of neurons and cardiac cells and defined by the calibrated all-or-none response to external perturbations. This dynamic is consistent with the saddle-node on invariant circle scenario and associated features are demonstrated including control of excitable threshold, temporal summation and refractory period. Our device compact footprint and its CMOS-compatible platform make it well suited for edge-computing applications requiring low latency and establish a foundation for versatile brain-inspired optomechanical computing and advanced on-chip optical pulse sources.
https://arxiv.org/abs/2601.11857
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d957bbf03fadd6250ab92338546834f95d948ddffbd4d933cd0657d4dac35067
2026-01-21T00:00:00-05:00
Study of the energy calibration of the DEAP-3600 detector using Na-22 source data and simulations
arXiv:2601.11858v1 Announce Type: new Abstract: DEAP--3600 is a single--phase liquid argon (LAr) direct--detection dark matter experiment operating 2~km underground at SNOLAB (Sudbury, Canada). The detector consists of 3.3~tons of LAr contained in a spherical acrylic vessel. At a WIMP mass of 100~GeV, DEAP--3600 has a projected sensitivity of $10^{-46}\,\mathrm{cm}^{2}$ for the spin--independent elastic scattering cross section of WIMPs. Radioactive sources have been used for the energy calibration and to test the detector performance. One of the most effective calibration runs has been taken with a $^{22}\mathrm{Na}$ source deployed in a tube located around the DEAP--3600 steel shell. The simultaneous emission of three $\gamma$'s by the source provides an excellent tagging for the $^{22}\mathrm{Na}$ decay. The results concerning the energy response of the detector and the agreement between data and Monte Carlo simulations in DEAP--3600 are investigated in this study.
https://arxiv.org/abs/2601.11858
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a56fe1e92dca86b8b3cc9b0026ddb05fbd9f876d50780990ee8bee5d9191dd20
2026-01-21T00:00:00-05:00
Plasmonic Bi-Cavity Nanostructure for Efficient Light Collection and Localization
arXiv:2601.11870v1 Announce Type: new Abstract: Tip-enhanced Raman spectroscopy (TERS) typically relies on high-NA excitation to generate a strong axial field at the tip apex, which shortens the working distance and constrains sample geometries. We show that a plasmonic bi-cavity tip, the plasmon-tunable tip pyramid (PTTP), co-tuned in nanopyramid length L and plateau length W, supports a hybrid antenna-cavity mode that funnels energy to the apex under radially polarized, on-axis excitation, even with a dry objective of NA = 0.75. Finite-element simulations identify W as a design-critical parameter that sets an in-plane surface-plasmon-polariton (SPP) Fabry-P\'erot-like resonance; co-tuning (L,W) yields a periodic series of maximal apex |E|^2. Experiments on monolayer graphene confirm near-field enhancement and reproduce the characteristic annular TERS point spread function (PSF) with NA = 0.75. Relaxing the NA requirement increases working distance and compatibility with constrained environments, pointing to practical, deployment-ready nano-Raman instrumentation.
https://arxiv.org/abs/2601.11870
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9e5937fa4e3ec68d948fe54655c28dd853ecda39d09298fa97f710b6ad9507ba
2026-01-21T00:00:00-05:00
Revealing the long-range coupling for multi-dimensional metasurface multiplexer
arXiv:2601.11875v1 Announce Type: new Abstract: Metasurface coupling constitutes a fundamental yet intricate electromagnetic interaction that occurs within a lattice of artificial subwavelength unit cells. Despite its prevalence, such coupling is typically ignored in conventional metasurface design frameworks due to the high characterization complexity, leading to suboptimal device performance. Here, we reveal a distinctive long-range coupling that exceeds an order of magnitude compared with the interaction range of evanescent waves, substantially enriching the metasurface design landscapes. This coupling exhibits pronounced graph topological features, and we design a graph neural network (GNN) to accurately abstract its inherent physics. Through strategic enhancement of the coupling effects, the discrete metasurface responses are transformed into continuous states, thereby unlocking diverse multiplexing channels. By further integrating the GNN into an inverse design agent, we tailor the multi-channel global response of metasurface to support simultaneous multiplexing across angle, frequency, and polarization domains. Experimentally, we demonstrate a compact metasurface multiplexer with eight independent channels, showcasing its potential for next-generation vehicular networks. This work establishes a new paradigm for highly integrated multifunctional metasurfaces, with promising prospects for high-density optical storage, information encryption, and high-capacity wireless communication.
https://arxiv.org/abs/2601.11875
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cf5cca1eae25b89e2cea4cd2fd50f36b88048836b82152fe99a2471b57f888d5
2026-01-21T00:00:00-05:00
Towards accurate predictions of bond-selective fluorescence spectra
arXiv:2601.11902v1 Announce Type: new Abstract: Vibrational-encoded fluorescence spectro-microscopies are emerging as powerful tools for studying molecular vibrations with the unparalleled sensitivity of fluorescence spectroscopy. We recently described one such technique, termed bond-selective fluorescence-detected infrared-excited (BonFIRE) spectro-microscopy. Currently, prospects of BonFIRE towards rational molecular design are limited, but they have the potential to be assisted by computational tools. In this Perspective, we provide a brief overview of the theory of BonFIRE spectroscopy. We then describe a fully automated computational pipeline for calculating BonFIRE spectra, reproducing key features of experimental results. Finally, we highlight a few potential applications of computational methods for vibrational-encoded fluorescence spectro-microscopies and their broader implications for chemistry and biology.
https://arxiv.org/abs/2601.11902
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65421f66a651ba245c811c8b733ccc7fb54a79130af81f1a6ed0a63f41489857
2026-01-21T00:00:00-05:00
Structure of Pitch-Pattern Motifs in Major League Baseball
arXiv:2601.11904v1 Announce Type: new Abstract: Baseball consists of two teams alternating between batting and fielding while competing to score runs through sequential pitching events. Recent advances in tracking technology have enabled all Major League Baseball (MLB) clubs to record every pitch with high resolution, yet most quantitative studies have primarily emphasized single-pitch metrics, leaving the role of sequential structure less explored. Here, we examine pitch-pattern motifs of multiple lengths using approximately 12.4 million Statcast pitch recordings from the 2008-2025 MLB regular seasons at two complementary scales. At the macroscale, we quantify pitch-sequence diversity using the Shannon entropy and inverse Simpson index and examine their relationships with earned run average and win totals. At the microscale, we compare hit and out frequencies across pitch-pattern motifs. Rather than identifying outcome-determining sequences, we find that motif usage exhibits stable, non-random organization, as reflected in Zipf s and Heaps' laws, while showing limited association with conventional performance measures. While language-like scaling (Zipf's and Heaps' laws) clearly reveals an underlying 'grammar' of MLB pitch sequences, that grammar alone is insufficient to account for performance indicators such as ERA or wins. These results suggest that sequence-based analyses clarify the structural organization of pitch usage, while also delineating the limits of motif-based approaches for explaining performance without richer contextual information.
https://arxiv.org/abs/2601.11904
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b6e908f4dc2448ba8bef4917178dff3c7026556f89551120524dd68325874c88
2026-01-21T00:00:00-05:00
Full Reaction Pathway Dynamics for Atmospheric Decomposition Reactions: The Photodissociation of H$_2$COO
arXiv:2601.11936v1 Announce Type: new Abstract: Branching ratios for fragmentation channels of important meta- and unstable species are essential for a molecular-level characterization of atmospheric chemistry. Here, the molecular product channels for the decomposition dynamics of the smallest Criegee intermediate, H$_2$COO, are quantitatively investigated. Using a high-quality, full-dimensional machine learned potential energy surface (CASPT2/aug-cc-pVTZ), the translational, rotational, and vibrational energy distributions of the CO$_2$+H$_2$, H$_2$O+CO, and HCO+OH fragmentation channels were analyzed to elucidate partitioning of the available energy. The CO$_2$ + H$_2$ product forms through two different pathways that bifurcate after formation of the OCH$_2$O intermediate. Along the direct pathway, CO$_2$ is preferentially vibrationally excited with H$_2$in its vibrational ground state, whereas for the indirect pathway going through formic acid, H$_2$ can populate levels with $v > 0$. For all product channels passing through energized formic acid, the lifetime distributions are described by stretched exponentials with $\beta$ ranging from 1.1 to 1.7. This is a clear signature of non-RRKM effects and suggests that the explicit molecular dynamics needs to be followed for a quantitative and realistic description of the photodissociation dynamics.
https://arxiv.org/abs/2601.11936
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895e7fcd01f1fb54d4547db1bcfe05d2a4e443482063550fa973faa630e13884
2026-01-21T00:00:00-05:00
A Convolutional Neural Network Based Framework for Linear Fluid Dynamics
arXiv:2601.11946v1 Announce Type: new Abstract: Fluid dynamics, for its strength in describing physical phenomena across vastly different scales from the cheerios effect on the breakfast table to the evolution of cosmic and quantum systems, has been called the 'queen mother' of science (Bush, 2015). However, a central challenge remains: ensuring the generalisability, interpretability and reliability of the machine learned models when applied to physical systems. To address this, we present a transparent approach that provides insights into how data-driven fluid dynamics and machine learning (ML) work. This is achieved by training a convolutional neural network (CNN) on data from a simple laminar fluid flow to behave as an operator that exactly matches the finite-difference numerics. Importantly, the model demonstrates strong generalisation capability by reproducing the dynamics for a wide range of distinct and unseen flow conditions within the same flow category. The CNN learns the forward Euler three-point stencil weights, capturing physical principles such as consistency and symmetry despite having only three tunable weights. Going beyond pure numerical training (numCNN), the approach is shown to work when trained on analytical (anCNN) and even molecular dynamics (mdCNN) data. In some cases, the physics is not captured, and thanks to the simple and interpretable form, these CNNs provide insight into the limits, pitfalls and best practice of data-driven fluid models. Because the approach is based on finite-difference operators and demonstrated with diffusive flow, it naturally extends to many structured-grid computational fluid dynamics (CFD) problems, including turbulent, multiphase, and multiscale flows.
https://arxiv.org/abs/2601.11946
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f6e297af0db272fadb75dbc5c5e6901214253749f6ee67a4e5d15fed68781003
2026-01-21T00:00:00-05:00
Intelligent Nano-Fingerprinting: An Efficient and Precise Approach for Liquid Biopsy
arXiv:2601.11947v1 Announce Type: new Abstract: Biological matrices are rich in information related to life processes, serving as invaluable media for assessing an individual's overall physiological status and its dynamic fluctuations, as well as crucial foundations for disease diagnosis. However, the inherent complexity of these matrices, coupled with our incomplete understanding of their full composition, presents significant challenges for comprehensive analysis and accurate diagnostic interpretation. The advent of single-molecule technologies has revolutionized biomedical research, enabling the direct observation of life processes at the molecular scale. We have proposed an Intelligent Nano-Fingerprinting strategy based on single-molecule nanopore technology, designed to capture the global molecular fingerprints of complex plasma matrices. Furthermore, we developed an intelligent algorithmic model capable of achieving precise classification of plasma samples. This approach is characterized by its simplicity, efficiency, and considerable potential for large-scale adoption and transferable applications.
https://arxiv.org/abs/2601.11947
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f7b368e37055c01eb11b4c86764b63fc11dbe222ce05fc5defacf0d578b6aff0
2026-01-21T00:00:00-05:00
Broadband silicon polarization beam splitter based on Floquet engineering
arXiv:2601.11955v1 Announce Type: new Abstract: A broadband silicon polarization beam splitter (PBS) is proposed and experimentally demonstrated based on Floquet-engineered directional couplers. The total length of the coupling structure is 20 um . By periodically modulating the waveguide width of the directional couplers, the power exchange between the two waveguides for the transverse-electric (TE) mode is suppressed, whereas the power coupling for the transverse-magnetic (TM) mode is enhanced. The fabricated PBS exhibits polarization extinction ratios (PERs) > 20 dB for both polarizations over a broad wavelength range of 1483 nm-1620 nm. Additionally, the measured insertion losses (ILs) are 0.15 dB and 1.2 dB at 1550 nm for TE and TM polarizations, respectively.
https://arxiv.org/abs/2601.11955
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d630d840c8b513fe522853f1668dbdde8190dc21d223727b18a3e1ec36fbc6e5
2026-01-21T00:00:00-05:00
Minimal seed in supersonic boundary layer at $M=3$
arXiv:2601.11964v1 Announce Type: new Abstract: This study investigates the minimal seed for laminar-to-turbulent transition in a supersonic boundary layer at $M=3.0$ and $Re=300$ using adjoint-based nonlinear non-modal analysis. While linear theory identifies oblique waves as the optimal disturbances for transient growth, we demonstrate that nonlinear effects fundamentally alter the optimal perturbation structure as the initial amplitude exceeds a critical threshold. Our analysis reveals that the nonlinear optimal perturbation exhibits a distinctive spatial distribution characterized by flattened structures in the outer layer and streamwise vortices near the wall, leading to a more rapid transition compared to the linear counterpart. A key finding is that this nonlinear amplification mechanism remains robust even under wall-cooled conditions ($T_w = 0.6 T_{ad}$), where the disappearance of the generalized inflection point (GIP) suppresses linear instabilities of Mack's first mode. This rapid growth is driven by the nonlinear interaction between two-dimensional planar waves near the wall and staggered vortex patterns in the outer layer, facilitating streak formation through vortex self-induction. Although the late-stage evolution eventually converges to the classical oblique breakdown scenario as characterized by the formation of $\Lambda$-vortices, the identified nonlinear path significantly reduces the disturbance energy required for transition.
https://arxiv.org/abs/2601.11964
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a0fec39e5a3b149caf370e54ace444dfb29c7c5f97a13e96199629daabb2b0ca
2026-01-21T00:00:00-05:00
Comprehensive study of cosmogenic neutron production in large liquid scintillator detectors
arXiv:2601.11980v1 Announce Type: new Abstract: Neutrons produced by cosmic ray muons constitute a significant background for underground experiments investigating neutron oscillations, neutrinoless double beta decay, dark matter, and other rare event signals. This work benchmarks measured neutron yields and neutron multiplicities--with a focus on data from the Daya Bay Reactor Neutrino Experiment--against comprehensive simulations using three GEANT4 hadronic physics lists. These simulations are further refined via a TALYS-based adjustment of hadronic cross sections. For the BERT-based models, the adjustment reduces the discrepancy in the total neutron yield from about 20% to approximately 6%, while for the BIC-based models it improves the agreement from roughly 13% to the sub-percent level (~0.3%), indicating a markedly better consistency of the BIC-based models with the experimental data. Nevertheless, a clear tension persists: simulations systematically underproduce single-neutron events while overproducing multi-neutron events. The study establishes a reproducible benchmark for cosmogenic neutron modeling and proposes a targeted refinement strategy--including channel-specific reweighting and intranuclear cascade parameter tuning--to guide future model development.
https://arxiv.org/abs/2601.11980
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375c6c02c91a02d274534f75c3777e378ccf86d85b5f47c74d8066c9a586f3d1
2026-01-21T00:00:00-05:00
Topological aspects of zero modes in cavity resonators
arXiv:2601.11989v1 Announce Type: new Abstract: We discuss the relationship between the zero modes of electromagnetic fields in a cavity resonator and the cavity's topological characteristics. We show that the dimension of the electromagnetic zero-mode space coincides with the dimension of the corresponding homology group of the cavity. Moreover, we prove that the alternating sum of the dimensions of the electromagnetic zero-mode spaces is closely related to the Euler characteristic of the cavity boundary, and hence to the integral of the curvature.
https://arxiv.org/abs/2601.11989
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d6131ebcab06186978700773efbae7ac2336d0f3ce76581bd345dae0f00a7768
2026-01-21T00:00:00-05:00
Observing rurality of a geographical area from road graph geometry -- a qualitative study
arXiv:2601.12006v1 Announce Type: new Abstract: In this paper we analyze the Finnish road network as a graph in order to measure whether the "rurality" or "urbanity" of an area correlates with local geometrical properties of the graph. Our primary motivation is the observation that the road systems in rural areas look similar to hyperbolic graphs, while in large cities they resemble more the Cayley graph of $\mathbb{Z}^2$. We do not aim for a comprehensive analysis, but rather wish to demonstrate that this observation can be measured and analyzed through looking at various "hyperbolicity measures" of randomly sampled geodesic triangles in the road graph.
https://arxiv.org/abs/2601.12006
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b6fd2a3636f2f35d1fd452c2950ad7cca320d41b736ece21ad7761cdf9733e8e
2026-01-21T00:00:00-05:00
A prototype gas cell for the stopping, extraction and neutralization of radioactive nuclei from the SPIRAL2 Super Separator Spectrometer (S$^3$)
arXiv:2601.12009v1 Announce Type: new Abstract: We present the design and simulation of a prototype gas cell for in-gas-jet laser-ionization and spectroscopy studies using the low energy branch of the SPIRAL2-S$^3$ radioactive-ion-beam facility. The prototype aims to demonstrate the possibility to reduce the extraction time of radioactive ions from the gas cell, while implementing a controlled neutralization mechanism, necessary for laser-spectroscopy studies. Different simulation methods of ion processes in gas are comparatively discussed. Design considerations and detailed simulations of the ion extraction time and efficiency are presented. A study of the dynamics of electrons obtained in the gas cell by ionization is also performed to assess the achievable electron densities.
https://arxiv.org/abs/2601.12009
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78b066b2302892b4ab08f5e859962b12492d23c2105554914ef2bd11c0a1ebac
2026-01-21T00:00:00-05:00
Pad\'e Approximation and Partition Function Zeros
arXiv:2601.12018v1 Announce Type: new Abstract: Fisher zeros play a central role in the theoretical understanding of phase transitions. However, their computation requires knowledge of the density of states, which limits their practical applicability. Alternative approaches based on the Energy Probability Distribution (EPD) and Moment Generating Function (MGF) alleviate the computational cost but suffer from convergence issues in the two-dimensional \textbf{anisotropic Heisenberg} model (XY model). In this work, we introduce a Pad\'e approximation to systematically reduces the number of zeros required in the Fisher, EPD, and MGF formulations without loss of accuracy. Moreover, since the Fisher zeros formulation does not rely on a convergence algorithm, their combination with a Pad\'e approximation enables a reliable analysis of the XY model while significantly reducing computational cost. Applications to the two-dimensional Ising and XY models demonstrate substantial reductions in polynomial degree and computation time while preserving accurate estimates of the critical temperature.
https://arxiv.org/abs/2601.12018
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d6731d063e865d3c3eb16ec3d4d5f890931edf583253f464f1e344636f3349a8
2026-01-21T00:00:00-05:00
Temporal Beam Self-Cleaning in Second-Harmonic Generation
arXiv:2601.12025v1 Announce Type: new Abstract: The spatial-temporal beam quality of laser sources is crucial for applications such as nonlinear spectroscopy and master oscillator power amplification systems. However, the temporal stability remains challenged by issues like line-width broadening and high-power demand in efforts to improve it. In this work, we investigate the effect of the second-harmonic generation process on the laser characteristics under three longitudinal mode regimes: single-longitudinal-mode, dual-longitudinal-mode, and multi-longitudinal-mode. The results demonstrate that the second-harmonic generation process effectively stabilizes the temporal characteristics of the laser and enhances its correlation, leading to a temporally clean output beam. The physical mechanism of the observed temporal stabilization effect can be attributed to a high-peak-pulse attenuation effect, jointly induced by nonuniform longitudinal-mode depletion and phase preservation in the residual fundamental wave. Statistical analysis indicates that at the maximum fundamental-wave power in the multi-longitudinal-mode regime, the standard deviation and peak-to-valley values derived from the normalized temporal profile decrease from 0.6122 and 5.6846 for the fundamental wave to 0.189 and 0.8847 for the residual fundamental wave. Meanwhile, the background level of the intensity auto-correlation function rises from ~0.72 to ~0.96, revealing its evolution toward a more coherent state. To the best of our knowledge, this research presents the first demonstration of laser temporal stabilization and correlation enhancement via second-harmonic generation. It not only deepens the comprehension of second-harmonic generation mechanisms, but also opens up a new avenue for realizing temporal beam self-cleaning of light.
https://arxiv.org/abs/2601.12025
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26052f92ce387e80229907d915c3e4411b0ad908a81cf5a6ad89b4677486880f
2026-01-21T00:00:00-05:00
Second- and Third-Harmonic Backscatter Through a Bandstop Filter Using Defected Ground Structure
arXiv:2601.12087v1 Announce Type: new Abstract: In this brief, a novel harmonic-backscatter-rectifier (HBR) is introduced for simultaneous rectification and harmonic-based uplink. The proposed (HBR) employs a rectifier to generate both DC power and the harmonic carriers for backscattering communication, and a dual-band reconfigurable band-stop filter using defected ground structure(DGS) to modulate the second and third harmonics with low-power consumption and same input impedance at f0 all the time. As a proof of concept, an HBR prototype operating at 1.85 GHz was designed and experimented. An uplink data rate of 8Mbps (4Mbps x 2 ) was achieved when the HBR was fed with -10 dBm RF power, and the data modulation consumed less than 27.7pJ/bit. In addition, a passive harmonic tag was implemented with the proposed HBR and a low-power binary sequence generator, which demonstrated a continuous uplink of 12 kbps at -6 dBm RF power.
https://arxiv.org/abs/2601.12087
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bd2aa396a98ec68f2c8db6b8a34d04e83ee8f259c46bfc397886729d0b0c056e
2026-01-21T00:00:00-05:00
Efficient O(N^1.5) Electronic Structure Computation of Million-Atom Systems
arXiv:2601.12098v1 Announce Type: new Abstract: The exploration of quantum phenomena in complex materials such as moir\'e superlattices is limited by the O(N^3) scaling of conventional electronic structure methods. Here we introduce a high-performance tight-binding framework that reduces the complexity to O(N^1.5) by transforming the Hamiltonian into a real symmetric form and combining Sylvester's inertia law with LDL decomposition. This approach enables efficient band structure calculations for large systems: solving magic angle twisted bilayer graphene in minutes on a laptop and scaling to 1.5 million atoms within days on a workstation. We apply it to the previously inaccessible ultra-low twist-angle regime (less than 0.16 degree) with mechanical strain relaxation and find robust flat bands persisting down to 0.09 degree. Our framework bridges density functional theory accuracy with large-scale quantum simulation, opening a route to systematic data-driven exploration of mesoscale quantum materials.
https://arxiv.org/abs/2601.12098
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91a509a2662e955a4d195ce17852fd8e35dcf44f1121a125dd50d92a550e3d28
2026-01-21T00:00:00-05:00
Evolutionary vaccination dynamics under higher-order reinforcement pressure
arXiv:2601.12114v1 Announce Type: new Abstract: Vaccination games in higher-order settings remain underexplored, despite their importance in shaping opinions and collective decisions. Here, we introduce a parsimonious behavioral-epidemiological model to evaluate how peer reinforcement pressure influences vaccination uptake. The framework consists of a two-layer multiplex: an epidemic layer governed by the SIR process on a square lattice, and a behavioral layer represented by a hypergraph of triadic interactions. Individuals update their vaccination strategy via imitation, modulated by a reinforcement parameter $\alpha$ when peer support is present. We find that higher-order structure alone induces clusters of vaccinated individuals that act as protective barriers. Low but nonzero reinforcement ($\alpha \approx 0.5$) maximizes coverage and suppresses outbreaks, while both negligible ($\alpha \approx 0$) and moderate ($\alpha > 0.1$) reinforcement reduce uptake, as excessive confirmation lowers adaptability and enables non-vaccinators to re-emerge. Our work bridges complex contagion theory with evolutionary game dynamics, offering insights into how contact structure and peer reinforcement jointly shape vaccination behavior.
https://arxiv.org/abs/2601.12114
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c0b37f6d02a5e81466004ac050d775ccec815311c9ca659fa09a83d73f346b7d
2026-01-21T00:00:00-05:00
Four-dimensional video imaging via generative deep learning and a diffuser-encoded image sensor
arXiv:2601.12162v1 Announce Type: new Abstract: Light carries rich information across space, spectrum, polarization, and time, yet conventional cameras capture only a narrow projection of this multidimensional structure. A thin diffuser encodes wavelength-dependent information into single-shot scatterograms, captured by a polarization-resolving CMOS sensor that simultaneously measures four linear polarization states. We use 4DCam to image a live Betta splendens fish, uncovering polarization-dependent color modulations that remain invisible to conventional cameras. We experimentally show that the 4D information encoded in the scatterograms markedly improves material discrimination, achieving 96% accuracy for textile classification and 90% for camouflage detection, compared with 70% and 80%, respectively, using 3D hyperspectral imaging alone. Built entirely from passive optics, 4DCam seamlessly integrates physical encoding, generative decoding, and direct inference, enabling real-time, information-complete optical sensing.
https://arxiv.org/abs/2601.12162
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88f04501efcd90816635e786332f3966669fd1cbf15b5bb908c0a689be3061bd
2026-01-21T00:00:00-05:00
Wave Phenomena and Wave Equations
arXiv:2601.12176v1 Announce Type: new Abstract: For any kind of wave phenomenon one can find ways to derive the respective dispersion relation from experimental observations and measurements. This dispersion relation determines the structure of the wave equation and thus characterizes the dynamics of the respective wave. Different wave phenomena are thus governed by different differential equations. Here we want to emphasize the experimental approach to matter waves, but before doing so we will discuss and test the procedure for other types of waves, in particular water waves.
https://arxiv.org/abs/2601.12176
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573aebd189fda036a914380b1b64692adc985d8a0fe539c7cda46a09217d7475
2026-01-21T00:00:00-05:00
Simplified Range-Separation Tuning as a Practical Starting Point for G0W0 and Bethe-Salpeter Calculations
arXiv:2601.12188v1 Announce Type: new Abstract: The accuracy of one-shot $G_0W_0$ and the Bethe-Salpeter equation (BSE) is well known to be highly sensitive to the choice of the starting-point eigensystem, typically obtained from mean-field theory. A highly effective method explored is the use of density functional approximation (DFA) with a range-separated hybrid (RSH) approach. In this work, we evaluate the performance of $G_0W_0$ in predicting ionization potentials and the BSE for describing neutral excitations, employing a recently proposed, broadly applicable, and computationally efficient range-separation tuning scheme [Singh \textit{et. al.}, Journal of Physical Chemistry Letters, 16, 32, 8198-8208, (2025)]. Our results demonstrate that this simplified tuning protocol provides an accurate starting point for many-body perturbation theory, thereby eliminating the need for conventional, multi-step optimally tuned RSH optimization procedure. The resulting quasiparticle energies from $G_0W_0$ closely reproduce reference ionization potentials, while BSE calculations based on the same tuned RSH orbitals yield quantitatively accurate optical absorption spectra and excitonic properties across a range of molecular systems and clusters.
https://arxiv.org/abs/2601.12188
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60f00c80e3addd76e3908f5c543f03a327d844d7dcc3c427358b33cb7de4dbc8
2026-01-21T00:00:00-05:00
Hitchhiker's guide to second-generation Car-Parrinello ab-initio molecular dynamics
arXiv:2601.12191v1 Announce Type: new Abstract: In a recent letter [T. D. K\"uhne, M. Krack, F. Mohamed and M. Parrinello, Phys. Rev. Lett. 98, 066401 (2007)], we outlined a new Car-Parrinello-like approach to Born-Oppenheimer molecular dynamics. Here, we provide a guide to performing actual calculations using our method and demonstrate this on liquid water at ambient conditions. We do not go into methodological details beyond those necessary for applying this approach, but focus on practical details pertinent to our particular implementation within the CP2K/Quickstep code [T. D. K\"uhne et al., J. Chem. Phys. 152, 194103 (2020)].
https://arxiv.org/abs/2601.12191
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05b5bb7fbce7bd65939dbf87883f7c45462e706583eabc1bb7e1fea8959934f6
2026-01-21T00:00:00-05:00
Explicit and Implicit Finite Difference Solvers Implemented in JAX for Shock Wave Physics
arXiv:2601.12204v1 Announce Type: new Abstract: Shock dynamics and nonlinear wave propagation are fundamental to computational fluid dynamics (CFD) and high-speed flow modeling. In this study, we developed explicit and implicit finite-difference solvers for the one-dimensional Burgers viscous equation to model shock formation, propagation, and dissipation. The governing equation, which incorporates convective and diffusive effects, serves as a simplified analogue of the Navier-Stokes equations. Using the Finite-JAX framework, each solver is implemented with upwind and central finite-difference schemes for the convective and diffusive terms, respectively. Time integration is performed using explicit forward Euler and implicit backward-time central space (BTCS) schemes under periodic and Dirichlet boundary conditions. Stability is ensured by the Courant-Friedrichs-Lewy (CFL) criteria for the convective and diffusive components. Numerical experiments quantify the accuracy, convergence, and real-time performance of JAX across CPUs, GPUs, and TPUs, demonstrating that JAX maintains fidelity while achieving portability. The results show that the explicit scheme captures impact accurately under strict time-step constraints, while the implicit formulation provides greater stability and accuracy at a higher computational cost. Taken together, these results establish a reproducible dataset for benchmarking CFD solvers and training machine learning models for nonlinear transport and impact-driven phenomena. Our new implementation of FiniteJAX enhances the portability, scalability, and performance of solvers based on the JAX framework developed by Google DeepMind.
https://arxiv.org/abs/2601.12204
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27531cb3a843c07433d1a5a12932a9f73ab67a84329e53db0dd25779a5919226
2026-01-21T00:00:00-05:00
Bio-Inspired Photonic Spectral Encoders
arXiv:2601.12228v1 Announce Type: new Abstract: Compact spectrometers promise to revolutionize sensing applications, offering a unique pathway to laboratory-grade analysis within a miniaturized footprint. Central to their performance is the encoding strategy to unknown spectra, which determines the efficiency, accuracy, and adaptability of spectral reconstruction. However, the absence of a unified spectral encoding framework has hindered the realization of optimal, high-performance compact spectrometers. We propose a transformative approach: an information-theoretic framework grounded in bio-inspired Bayesian expected information gain that defines the first generic light encoder for computational spectrometers. By optimizing three fundamental attributes at the lowest level of physical hierarchy, (1) orthogonality, (2) completeness, and (3) sparsity, we establish a design paradigm that transcends conventional encoding hardware limitations. We validate this paradigm with the first generic encoder capable of dynamically reconfiguring its response matrices. Experiments show superior reconstruction fidelity across diverse spectral regimes, enabling tunable spectral encoding tailored to varied input features. An ultra-high resolution of 6 pm and a broad measurable bandwidth of 30 nm are experimentally validated. By bridging the gap between theoretical encoding principles and reconfigurable hardware, our framework defines a coherent basis for future advances in compact spectrometry.
https://arxiv.org/abs/2601.12228
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0a3a6e86a02cbffdaab363e1de3a486a4a415ff43df9556093e561c6bdea4084
2026-01-21T00:00:00-05:00
Rotational flow underlying coupled surface and internal waves. I: Eulerian perspective
arXiv:2601.12229v1 Announce Type: new Abstract: In this paper we examine the flow generated by coupled surface and internal small-amplitude water waves in a two-fluid layer model, where we take the upper layer to be rotational (constant vorticity) and the lower layer to be irrotational. The presence of vorticity greatly complicates the underlying analysis, yet it generates a rich array of otherwise unobservable phenomena such as the presence of critical layers, and stagnation points, in the fluid interior. We employ a phase-plane analysis to elucidate the qualitative behaviour of streamlines for a range of different coupled-wave, and vorticity, regimes. Although the water waves considered are linear in the fluid dynamics sense, the dynamical systems which govern their motion are nonlinear.
https://arxiv.org/abs/2601.12229
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da30e88a6c3d9d04e3990305933fcd8e46ed9fe3ee68926174b9ccb78f3e7a73
2026-01-21T00:00:00-05:00
Long-term prediction of ENSO with physics-guided Deep Echo State Networks
arXiv:2601.12251v1 Announce Type: new Abstract: The El Ni\~{n}o-Southern Oscillation (ENSO) is a dominant mode of interannual climate variability, yet the mechanisms limiting its long-lead predictability remain unclear. Here we develop a physics-guided Deep Echo State Network (DESN) that operates on physically interpretable climate modes selected from the extended recharge oscillator (XRO) framework. DESN achieves skillful Ni\~{n}o3.4 predictions up to 16-20 months ahead with minimal computational cost. Mechanistic experiments show that extended predictability arises from nonlinear coupling between warm water volume and inter-basin climate modes. Error-growth analysis further indicates a finite ENSO predictability horizon of approximately 30 months. These results demonstrate that physics-guided reservoir computing provides an efficient and interpretable framework for diagnosing and predicting ENSO at long lead times.
https://arxiv.org/abs/2601.12251
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eb7f8453840aea39aedeb36c9befa2c99cdc0fdcd1da7a0ce2fb8eb92f52550f
2026-01-21T00:00:00-05:00
Learning to Dock: Geometric Deep Learning for Predicting Supramolecular Host-Guest Complexes
arXiv:2601.12268v1 Announce Type: new Abstract: Predicting non-covalent host-guest recognition remains challenging due to the complex interplay of electrostatics, dispersion, and steric effects, and the limited transferability of existing docking approaches to synthetic supramolecular systems. Here we present DeepHostGuest, a geometric deep-learning framework that learns generalizable recognition principles directly from experimentally resolved host-guest structures. Hosts are encoded as electrostatic surfaces and guests as molecular graphs, enabling transferable learning across diverse supramolecular systems. DeepHostGuest achieves high-accuracy predictions (RMSD $\leq 2$ Angstrom for 80.8% of test cases), substantially outperforming classical docking without case-specific tuning. Notably, the method generalizes beyond its training domain to crystalline sponge systems, accurately capturing the binding of large amphiphilic molecules within metal-organic cages. Beyond predicting binding conformations, the structures generated by DeepHostGuest serve as a reliable basis for accurate binding free-energy calculations. Density Functional Theory (DFT)-calculated affinities correlate well with experiment, enabling structure-property relationships across 876 host-guest complexes spanning 34 host families. Interpretable feature analysis reveals that binding strength arises from a cooperative interplay of host polarity, guest hydrophobicity, and geometric complementarity, with distinct design regimes across supramolecular classes. Together, these results establish data-driven molecular recognition as a practical route to predictive supramolecular design, enabling high-throughput virtual screening and rational optimization of functional host-guest systems.
https://arxiv.org/abs/2601.12268
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93a2817fc2d6858e76a89d835ba41a90743338d9909798c5fc6933adce238f62
2026-01-21T00:00:00-05:00
Logarithmic scaling and stochastic criticality in collective attention
arXiv:2601.12306v1 Announce Type: new Abstract: We uncover a universal scaling law governing the dispersion of collective attention and identify its underlying stochastic criticality. By analysing large-scale ensembles of Wikipedia page views, we find that the variance of logarithmic attention grows ultraslowly, $\operatorname{Var}[\ln{X(t)}]\propto\ln{t}$, in sharp contrast to the power-law scaling typically expected for diffusive processes. We show that this behaviour is captured by a minimal stochastic differential equation driven by fractional Brownian motion, in which long-range memory ($H$) and temporal decay of volatility ($\eta$) enter through the single exponent $\xi\equiv H-\eta$. At marginality, $\xi=0$, the variance grows logarithmically, marking the critical boundary between power-law growth ($\xi>0$) and saturation ($\xi<0$). By incorporating article-level heterogeneity through a Gaussian mixture model, we further reconstruct the empirical distribution of cumulative attention within the same framework. Our results place collective attention in a distinct class of non-Markovian stochastic processes, with close affinity to ageing-like and ultraslow dynamics in glassy systems.
https://arxiv.org/abs/2601.12306
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f08f10a59b79df684e7327680bd1f465c351a4fbb2446fa201dbb1fe193ea6f5
2026-01-21T00:00:00-05:00
Optical Self-Trapping and Nonlinear Light-Matter Interactions in Biological Soft Matter
arXiv:2601.12333v1 Announce Type: new Abstract: Low-scattering, deep-penetration light transport in biological media remains a pivotal challenge for biophotonic technologies, including biomedical imaging, optical diagnostics, and photodynamic therapy. This review builds upon and extends our earlier studies of nonlinear optical self-trapping and optically induced waveguiding in biological suspensions, such as human erythrocytes and cyanobacteria, where light-matter coupling is governed by optical-force-mediated particle redistribution. Recent progress has revealed increasingly rich and complex regimes, including the propagation and nonlinear self-action of structured (vortex) beams in biological environments, as well as nonlinear responses dominated by thermally driven mechanisms in absorptive biomolecular solutions (e.g., heme and chlorophyll). We place particular emphasis on distinctive nonlinear phenomena observed in these systems, including spatial self-phase modulation, optical-force-induced sculpturing of effective energy landscapes, and quasi-waveguide formation in soft, heterogeneous biological media. We conclude by highlighting emerging opportunities to harness these nonlinear behaviors for deep-tissue imaging, label-free biosensing, and the realization of biocompatible photonic structures and devices assembled directly from living or hybrid biological matter.
https://arxiv.org/abs/2601.12333
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d5ec1064c7bd5de4ca67680fc656e21ce5284ab00d197a4f2b3f62024d425e89
2026-01-21T00:00:00-05:00
Some ways parameter calculation curvilinear uniformly accelerated motion
arXiv:2601.12363v1 Announce Type: new Abstract: The parameters of uniformly accelerated reference frame s three equivalent ways is calculated. The article also found explicitly transformation to uniformly accelerated reference frame and proved the assertion that Thomas precession and Wigner rotation s in opposite directions and cancel each other out.
https://arxiv.org/abs/2601.12363
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8dbd811726f9a198e1a39badbe7e91d97bd74e8a8e48d8f2b08a29ac4b7382fe
2026-01-21T00:00:00-05:00
Performance Test and Circuit Simulation for R12699-406-M4 Photomultiplier Tube Base
arXiv:2601.12364v1 Announce Type: new Abstract: The next-generation liquid xenon experiments like PandaX-xT target an energy range from sub-keV to multi-MeV to address the requirement of multiple physics searches. The Hamamatsu R12699-406-M4 photomultiplier tubes (PMTs) were developed and selected as photon sensors for PandaX-xT. Their voltage-divider base is optimized for a broad dynamic range, from single-photoelectron (SPE) sensitivity to 30~nC collected charge (matching the 2.5~MeV Q-value of $^{136}$Xe neutrinoless double beta decay~(NLDBD)). Using a dedicated test bench, we characterize the saturation and suppression responses of R12699-406-M4 PMTs with this base design. Based on measured PMT-base responses, we develop a circuit simulation model that accurately reproduces the physical mechanisms underlying these effects with key parameters tuned via experimental data. The combined simulation and bench-test approach guides base design and optimization, enabling improved detector dynamic range and supporting future saturation and suppression correction studies in data analysis.
https://arxiv.org/abs/2601.12364
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79972527b823e72ba8bbb911e1111ae8f546ec641245b997ebdaf39cf96f1143
2026-01-21T00:00:00-05:00
A Novel Numerical Algorithms Optimization Method with Machine Learning Frameworks: Application on Real-time Plasmas Equilibrium Reconstruction in EXL-50U Spherical Torus
arXiv:2601.12378v1 Announce Type: new Abstract: This work proposes for the first time a novel optimization method for numerical algorithms, which takes advantages of machine learning frameworks PyTorch and TensorRT, leveraging their modularity, low development threshold, and automatic tuning characteristics to achieve a real-time plasmas reconstruction algorithm called PTEFIT as an application in tokamak-based controlled fusion that combines performance, flexibility, and usability. The algorithm has been deployed and routinely operated on the EXL-50U spherical tokamak, with an average inference time of only 0.268ms per time slice at $129\times 129$ resolution, and has successfully driven feedback control of the maximum radial position of plasmas and isoflux control. We believe that its design philosophy has sufficient potential to accelerate development and optimization in GPU parallel computing, and is expected to be extended to other numerical algorithms.
https://arxiv.org/abs/2601.12378
Academic Papers
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1b929c07a67402c0f49d08ac5303c776a8ca214d0e1119ed8978c0bb2d0f4b35
2026-01-21T00:00:00-05:00
A C-band microwave rectifier without capacitors for microwave power transmission
arXiv:2601.12386v1 Announce Type: new Abstract: A microwave rectifier at 5.8 GHz without any capacitors is presented, which owns a measured MW-to-DC conversion efficiency of 68.1%. A harmonic rejection filter and a DC pass filter, which replace lumped capacitors in conventional microwave rectifiers, are applied to suppressing the harmonics produced by an HSMS-286 Schottky diode during rectifying. At the fundamental frequency, a microstrip impedance transformer which contains a shunt {\lambda}g/8 short-ended microstrip transmission line and two short series microstrip transmission lines are applied to compensating the imaginary impedance of the diode and matching the input impedance of the rectifier. The measured MW-to-DC conversion efficiency agrees well to the simulated results. The novel rectifier without any lumped passive elements may be applied for power transmission system at higher microwave frequencies.
https://arxiv.org/abs/2601.12386
Academic Papers
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3e63264f791a77e00aebf4eb331878a9dd2cc610947bc34cd64514ae154804ed
2026-01-21T00:00:00-05:00
Bridging Photon Statistics and Phase Transitions in Random Fiber Lasers
arXiv:2601.12404v1 Announce Type: new Abstract: Complex systems exhibit rich equilibrium states, yet the universal principles governing these systems remain unrevealed, motivating the search for novel experimental platforms. Random fiber lasers (RFLs), which generate partially-coherent light-wave through feedback from Rayleigh scattering, provide a photonic realization of such systems. Here we report a comprehensive theoretical and experimental investigation of photon statistics for RFLs based on classical second-order temporal correlation function \( g^{(2)}(\tau) \), revealing unique statistical properties and introduce a two-dimensional framework for controlling photon statistics. Remarkably, we establish a unified landscape between photon correlation, intensity statistics governed by Levy statistics, and phase transitions with replica symmetry breaking. This multifaceted relationship, observed for the first time, bridges disordered photonics with statistical physics of complex system. Our results offer new pathways for engineering laser emission with controllable photon statistics, and more broadly, this work positions RFLs as a fertile land for exploring emergent behaviors in disordered systems.
https://arxiv.org/abs/2601.12404
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dd0cd863997cf0991390d7bbc8e4ecb8175bcb5315e8c3e285fd9bd88388b766
2026-01-21T00:00:00-05:00
Cryogenic enhancement of phononic four-wave mixing in AlScN/SiC
arXiv:2601.12418v1 Announce Type: new Abstract: Surface acoustic wave platforms based on piezoelectric thin-film heterostructures provide sub-wavelength acoustic confinement, making them attractive for compact nonlinear phononic systems with applications including frequency conversion, parametric interactions, and nonlinear signal processing. Here, we investigate guided surface acoustic wave phononic four-wave mixing at gigahertz frequencies in an aluminum scandium nitride/4H-silicon carbide heterostructure operated at both room temperature (295 K) and cryogenic temperature (4 K). The 500 nm thick aluminum scandium nitride film supports guided Rayleigh and Sezawa modes with distinct displacement and strain energy density distributions, allowing a direct comparison of mode-dependent nonlinear behavior within the same device. Continuous-wave four-wave mixing measurements reveal an enhancement in the extracted modal nonlinear coefficient at 4 K relative to 295 K for both modes. In addition, the Rayleigh mode exhibits a modal nonlinearity approximately two orders of magnitude larger than that of the Sezawa mode across both temperature regimes. These results demonstrate that phononic four-wave mixing is strongly influenced by temperature, mode confinement, and strain localization while establishing aluminum scandium nitride on silicon carbide heterostructures as a promising platform for engineering enhanced nonlinear phononic interactions for future classical and quantum acoustic on-chip signal processing systems.
https://arxiv.org/abs/2601.12418
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6cf95549757462a1028c05d3df2a92d338a7c709897323c1158d9759c0a0d8ac
2026-01-21T00:00:00-05:00
Saturable absorption in NV-doped diamond studied by femtosecond Z-scan
arXiv:2601.12421v1 Announce Type: new Abstract: We investigate nonlinear optical absorption in diamond crystals containing high densities of nitrogen vacancy (NV) centers using open-aperture Z-scan measurements with 230 fs laser pulses at 1032 nm, within the transparency window of diamond. While high-purity electronic-grade diamond exhibits third-order nonlinear absorption, NV-doped samples display pronounced saturable absorption that strengthens with increasing defect concentration. Linear transmission spectroscopy reveals that, in addition to NV centers, the crystals host significant populations of H2 (NVN-) defect complexes whose absorption band partially overlaps the excitation wavelength. By correlating spectroscopic data with nonlinear measurements and modeling the response using an effective two-level system, we show that the observed saturation cannot be attributed solely to NV centers but arises from the combined contribution of NV-related and H2 defects. For the highly doped sample, we determine an effective linear absorption coefficient of alpha0 = 6.52 cm-1 and a saturation intensity of Is = 40.0 GW/cm2. These findings highlight the critical role of the complex defect landscape in governing the nonlinear optical response of NV-doped diamond and underscore the necessity of accounting for ancillary defect species in the design of diamond-based nonlinear and quantum photonic devices.
https://arxiv.org/abs/2601.12421
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6db2cc3a32359c5137f17b496c460fc44ab02451dfc26fff4426a6a7a1fdf89e
2026-01-21T00:00:00-05:00
Wavefront Shaping of Ultrasound Vortex through the Human Skull Enabled by Binary Acoustic Metasurfaces
arXiv:2601.12437v1 Announce Type: new Abstract: Ultrasound vortices have rapidly expanded their applications to areas like particle trapping, contactless manipulation, acoustic communications. In ultrasonic imaging and therapy involving bone tissues, these vortex beams offer intriguing possibilities but transmitting them through bone (especially the skull) poses challenges. Traditional acoustic lenses were engineered to rectify skull-induced beam aberration, and their capacity was limited to generating only static ultrasound fields within the brain. To overcome this constraint, our study presents a novel method for transcranially steering focused ultrasound vortex using 3D printed binary acoustic metasurfaces (BAMs) with a thickness of 0.8 {\lambda}. We tackled the challenge of skull-induced phase aberration by computing the phase distribution via a time reversal technique, which concurrently enabled the generation of a steerable focused vortex inside an ex vivo human skull by adjusting the operating frequency. Both numerical and simulations experiments were conducted to validate the capabilities of BAMs. Furthermore, we explored the generation of higher-order topological charge acoustic vortices within the brain utilizing the BAM. This development paves the way for designing cost-effective particle-trapping systems, facilitating clot manipulation, and applying acoustic-radiation forces and torques within or across bone structures, thus presenting a new frontier for potential biomedical applications.
https://arxiv.org/abs/2601.12437
Academic Papers
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e46964ab5a49bff92dbbc38fa183dcd12e8ccc69bcb2fb917ea8f5a843a27af0
2026-01-21T00:00:00-05:00
Mixtenna: A Self-Biased Nonlinear Patch Antenna for Passive Third-Harmonic Radiation
arXiv:2601.12462v1 Announce Type: new Abstract: A nonlinear rectangular patch antenna (RPA) is presented in which back-to-back Schottky diodes are embedded at high-field regions to enable passive, bias-free harmonic generation. The self-biased diodes introduce a power-dependent impedance that drives efficient frequency up-conversion and selective third-harmonic radiation. A tailored matching network enhances third-harmonic excitation and coupling while preserving radiation efficiency at the fundamental frequency. Analytical modeling combined with SPICE-assisted full-wave time-domain simulations predicts strong odd-harmonic content, and measurements on RPA prototypes employing SMS7630 diodes confirm these results. Simulated and measured S-parameters and far-field patterns at 925 MHz and 2.775 GHz show excellent agreement. The demonstrated approach establishes nonlinear loading as an effective mechanism for passive harmonic control in compact radiators, enabling frequency-agile and spectrum-efficient antenna systems.
https://arxiv.org/abs/2601.12462
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1063f43e4da0d4b321b53bb7749c616a3a0eb3ab69673123851d7756d58fc5fb
2026-01-21T00:00:00-05:00
Plasmoid formation via competing lower-hybrid drift and Kelvin-Helmholtz instabilities: A hybrid kinetic-gyrokinetic simulation study
arXiv:2601.12466v1 Announce Type: new Abstract: We investigate the nonlinear formation of plasmoids in 2D low-beta current sheets through the interplay between the Kelvin-Helmholtz instability (KHI) and the lower-hybrid drift instability (LHDI). Using a hybrid kinetic-gyrokinetic model-based Super Simple Vlasov (ssV) code with fully kinetic ions and drift-kinetic electrons, we simulate Harris-type current sheets and velocity shear layers with strong cross-field density gradients. Our central hypothesis is that steep density gradients drive LHDI, which can grow faster than KHI and initiate an inverse cascade from kinetic to fluid scales, potentially suppressing KHI. Our simulations confirm that, in thin current sheets, LHDI develops rapidly at the sheet edges and nonlinearly merges into larger-scale magnetic islands before KHI can evolve. These LHDI-driven structures distort the velocity shear and suppress classical KH vortices. In contrast, for thicker current sheets or weaker density gradients, KHI dominates and produces the expected rolled-up vortices and associated plasmoids. These findings demonstrate that LHDI-induced turbulence can act as both a seed and a regulator of plasmoid-generating instabilities, mediating cross-scale energy transfer. This mechanism is relevant to thin boundary layers in space plasmas, such as the solar wind magnetosphere interface, and suggests that microturbulence can govern large-scale magnetic topology during collisionless reconnection.
https://arxiv.org/abs/2601.12466
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2666d1b361ecf645da2277823d312105b26933a1702e1546e2093d2c667ac9a2
2026-01-21T00:00:00-05:00
SPARC Tokamak Error Field Expectations and Physics-Based Correction Coil Design
arXiv:2601.12469v1 Announce Type: new Abstract: Non-axisymmetric magnetic field coils have been designed to provide efficient error field correction and suppress edge localized modes in SPARC - a compact high-field tokamak that is presently under construction at Commonwealth Fusion Systems. These designs utilize the Generalized Perturbed Equilibrium Code's (GPEC's) representation of the multi-modal, non-axisymmetric plasma response to optimize the geometric coupling between 3D coil arrays and the desired core or edge plasma response. Error field correction coils are designed to couple to the plasma-amplified kink that dominates the drive of core resonances. The maximum allowable error field is projected to SPARC using an empirical scaling that is consistent with linear and nonlinear MHD modeling expectations. Asymmetric construction and assembly tolerances are then balanced against the corresponding kA-turns needed for correction to levels below the allowable limit. These physics-driven coil designs provide confidence in our ability to operate SPARC in new high field tokamak regimes without error field induced locked modes.
https://arxiv.org/abs/2601.12469
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cadf6e2b96cd0ef4c719e2b172223f015354a72905d3490a4aa86adf29150863
2026-01-21T00:00:00-05:00
Stabilizing van der Waals NbOI2 by SiO2 encapsulation for Photonic Applications
arXiv:2601.12470v1 Announce Type: new Abstract: Niobium oxide diiodide (NbOI2) is an emerging material for photonics and electronics, distinguished by its exceptional second-order nonlinearity and pronounced in-plane ferroelectricity, both originating from its highly anisotropic ABC-stacked crystal structure. Its broken inversion symmetry enables its optical nonlinear efficiency to scale with thickness, making multilayer NbOI2 highly promising for nonlinear frequency conversion like second harmonic generation or and spontaneous parametric down-conversion in bulk or waveguides. However, under ambient conditions NbOI2 degrades into an amorphous oxide within weeks, severely diminishing its nonlinear response. To overcome this, we investigate SiO2 encapsulation via physical vapor deposition to protect NbOI2 multilayers from environmental degradation. Our systematic study reveals that encapsulation preserves structural integrity and nonlinear optical performance, establishing NbOI2 as a stable candidate for heterogeneous integration in foundry-compatible photonic platforms and quantum technologies.
https://arxiv.org/abs/2601.12470
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fcd387ee6df31c1510bdd76479945faed51297d8de3630c30675eb820e9f7653
2026-01-21T00:00:00-05:00
Development of a novel compact and fast SiPM-based RICH detector for the future ALICE 3 PID system at LHC
arXiv:2601.12472v1 Announce Type: new Abstract: A dedicated R\&amp;D is ongoing for the charged particle identification system of the \mbox{ALICE 3} experiment proposed for the LHC Run 5 and beyond. One of the subsystems for the high-energy charged particle identification will be a Ring-Imaging Cherenkov (RICH) detector. The possibility of integrating Cherenkov-based charged particle timing measurements is currently under study. The proposed system is based on a proximity-focusing RICH configuration including an aerogel radiator separated from a SiPM array layer by an expansion gap. A thin high-refractive index window of transparent material, acting as a second Cherenkov radiator, is glued on the SiPM array to enable time-of-flight measurements of charged particles by exploiting the yield of Cherenkov photons in the thin window. We assembled a small-scale prototype instrumented with different Hamamatsu SiPM array sensors with pitches ranging from 1 to 3 mm, readout by custom boards equipped with the front-end Petiroc 2A ASICs to measure charges and times. The primary Cherenkov radiator consisted of a 2 cm thick aerogel tile, while various window materials, including SiO$_2$ and MgF$_2$, were used as secondary Cherenkov radiators. The prototype was successfully tested in a campaign at the CERN PS T10 beam line with pions and protons. This paper summarizes the results achieved in the 2023 test beam campaign.
https://arxiv.org/abs/2601.12472
Academic Papers
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c86f813a2e87d51d86d99a99a3d79ef256c02f878ee894027ed898efa26d2a10
2026-01-21T00:00:00-05:00
Test beam performance of a novel RICH detector with timing capabilities for the future ALICE~3 PID system at LHC
arXiv:2601.12492v1 Announce Type: new Abstract: The ALICE Collaboration is proposing a completely new apparatus, ALICE 3, for the LHC Run 5 and beyond. A key subsystem for charged particle identification will be a Ring-Imaging Cherenkov (RICH) detector consisting of an aerogel radiator and a photosensitive surface based on Silicon Photomultiplier (SiPM) arrays in a proximity-focusing configuration. A thin high-refractive index slab of transparent material (window), acting as a second Cherenkov radiator, is glued on the entrance face of the SiPM arrays to achieve precise charged particle timing. Requiring time matching between aerogel Cherenkov photon and track hits leads to an improvement of pattern recognition by discarding the uncorrelated SiPM dark count hits. In this work we present the current status of the R\&amp;D performed for the ALICE 3 RICH detector prototype and the expected full scale system performance. A special focus will be given to the beam test results obtained with a small-scale prototype instrumented with various array of Hamamatsu SiPMs with pitches ranging from 1 to 3 mm. The Cherenkov radiator consisted of a 2 cm thick aerogel tile with a refractive index of 1.03 at 400 nm wavelength. For timing measurements SiPM arrays coupled with two different window materials (SiO$_2$ and MgF$_2$) were used. The prototype was successfully tested in beam test campaigns at the CERN PS T10 beam line. The data were collected with a complete chain of front-end and readout electronics based on the Petiroc 2A and Radioroc 2 together with a picoTDC to measure charges and times. We measured a charged particle detection efficiency above 99\% and a single photon angular resolution better than 4.2 mrad at the Cherenkov angle saturation with a time resolution better than 70 ps for charged particles.
https://arxiv.org/abs/2601.12492
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ad24af887db3fc895eb4026036093b6b43cfb4e02bfac1a2949b68cf51a6c589
2026-01-21T00:00:00-05:00
Beam test studies for a SiPM-based RICH detector prototype for the future ALICE~3 experiment
arXiv:2601.12511v1 Announce Type: new Abstract: The ALICE Collaboration is proposing a completely new apparatus, ALICE~3, for the LHC Runs~5 and beyond. In this context, a key subsystem for high-energy charged particle identification will be a proximity-focusing ring-imaging Cherenkov detector using aerogel as radiator and silicon photomultipliers (SiPMs) as photon sensors. We assembled a small-scale prototype instrumented with Hamamatsu S13352 and S13361-3075AE-08 SiPM arrays, readout by custom boards equipped with front-end Petiroc 2A ASICs. The Cherenkov radiator consisted of a 2 cm thick hydrophobic aerogel tile with a refractive index of 1.03 separated from the SiPM plane by a 23 cm expansion gap. The prototype was successfully tested in a campaign at the CERN PS T10 beam line with the goal of validating the design bRICH specifications in terms to achieve the target separation power. We measured a single photon angular resolution of 3.8~mrad at the Cherenkov angle saturation value of 242~mrad, as well as the expected scaling of the angular resolution with the increasing number of detected photons. We also studied the contribution of uncorrelated and correlated background sources with respect to the signal and proved the effectiveness of time matching between charged tracks and photon hits to achieve efficient suppression of the SiPM dark count rate background. In this paper, the detector concept, the description of the tested prototype layout and the main beam test results are reported.
https://arxiv.org/abs/2601.12511
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47c75732550421f815bdfb5bd72be1f841e64a3df7406d245c314147d505e628
2026-01-21T00:00:00-05:00
Unified multifractal description of longitudinal and transverse intermittency in fully developed turbulence
arXiv:2601.12528v1 Announce Type: new Abstract: Small-scale intermittency is a defining feature of fully developed fluid turbulence, marked by rare and extreme fluctuations of velocity increments and gradients that defy mean-field descriptions. Existing multifractal descriptions of intermittency focus primarily on longitudinal increments and gradients, despite mounting evidence that transverse components exhibit distinct and stronger intermittency. Here, we develop a unified multifractal framework that jointly prescribes longitudinal and transverse velocity increments, and extends to gradients. We derive explicit relations linking inertial-range scaling exponents of structure functions to moments of velocity gradients in dissipation range. Our results reveal that longitudinal gradient scaling is solely prescribed by longitudinal structure functions, as traditionally expected; however, transverse gradient scaling is prescribed by mixed longitudinal-transverse structure functions. Validation with high-resolution direct numerical simulations of isotropic turbulence, at Taylor-scale Reynolds number up to $1300$ demonstrates excellent agreement, paving way for a more complete and predictive description of intermittency faithful to the underlying turbulence dynamics.
https://arxiv.org/abs/2601.12528
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aae1fcdbebd00e5db59423a896bd3f79e99e6cad6786ef592c1b6fe88ae80910
2026-01-21T00:00:00-05:00
Design Optimization of Triple Gas Electron Multiplier for Superior Gain and Reduced Ion Backflow
arXiv:2601.12553v1 Announce Type: new Abstract: Micro-Pattern Gas Detectors (MPGDs) are extensively employed in modern high-energy and nuclear Physics experiments because of their excellent spatial resolution, high rate capability, and operational stability. Among these, the Gas Electron Multiplier (GEM) has emerged as one of the most widely adopted MPGD technologies. Despite their widespread adoption, GEM detectors based on the conventional bi-conical hole geometry do not always achieve optimal performance, particularly in maximizing effective gain while suppressing ion backflow. One of the primary factors limiting a GEM's performance is ion backflow. The accumulation and gradual discharge of these ions might alter the local electric field, resulting in a temporary dead time and complicating responses to subsequent events. These limitations pose challenges for applications requiring high precision and stable long-term operation. In this work, we address these issues by investigating modified GEM geometries designed to enhance gain performance and reduce ion backflow, thereby improving overall detector performance. The current study investigates geometric optimization strategies for a triple-GEM detector to enhance performance, mitigate ion backflow, and augment gain. The detector structures were designed using the ANSYS Mechanical APDL, and the associated electrostatic field configurations were computed using the ANSYS Maxwell. A thorough investigation of gain and ion backflow calculations was carried out when the generated field maps were interfaced with Garfield$^{++}$. The potential enhancements in detector efficiency and stability that the proposed modifications to the GEM foil geometry offers a valuable insights for the design of next-generation gaseous detectors.
https://arxiv.org/abs/2601.12553
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d3d2e6e039ce4cbb9d8dd84be2e1a0473c88520a499729ab1d9efa2b983fc70b
2026-01-21T00:00:00-05:00
Minimal-footprint photonic crystal nanolasers for biointegration
arXiv:2601.12561v1 Announce Type: new Abstract: Photonic crystals allow unprecedented control over how light is confined, propagates, and interacts with matter. Their development has had a transformative impact on optics and physics, and they remain the central platform for both fundamental discoveries and practical photonic technologies. However, the relatively large footprint and substrate-bound nature of photonic crystal structures have so far strongly limited their use as miniature optical devices or biointegrated sensors. Here, we overcome these limitations by identifying the minimal size of a 2D photonic crystal array needed to achieve lasing and describe the fabrication of substrate-less hexagonal laser particles with an active area as small as 30 {\mu}m2. Massively parallel fabrication, robust detachment, and integration of the nanolaser particles into live cells is demonstrated. Crucially, by engineering spatial and spectral mode characteristics, we designed NIR-II probes with mode volumes on the order of tens of attolitres, an order of magnitude smaller than whispering gallery probes of similar dimensions. Such high light localization is comparable in scale to different organelles of eucaryotic cells. In the future, we expect that chemical or plasmonic functionalization of the device will enable label-free sensing of nanoscale intracellular processes, and that it shall serve as a miniature platform to exploit developments in optical and quantum sensing for chemical and biological applications.
https://arxiv.org/abs/2601.12561
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32bf6a0aaf8e19db3565544f79b4d6df4c0c3fbe60111123fca95a04bb30e774
2026-01-21T00:00:00-05:00
Thermodynamic principles of emerging cryopreservation technologies
arXiv:2601.12573v1 Announce Type: new Abstract: Modern cryopreservation exists at the convergence of diverse disciplines--materials science, physical chemistry, mechanical engineering, biological engineering, etc.--and emerging technologies often draw from many of these disciplines simultaneously. Thermodynamics, as one of the foundational theories underlying both physical and biological science, provides a framework through which to understand these interdisciplinary technologies, yet the full kit of requisite thermodynamic tools is not housed within any one discipline. This Chapter aims to articulate a foundational thermodynamic approach to the description, interrogation, and design of modern cryopreservation technologies, and to review the state of the art in emerging cryopreservation technologies through the lens of this approach. We focus in particular on the management of phase change across equilibrium-driven techniques (e.g., liquidus tracking, partial freezing, isochoric freezing), kinetics-driven techniques (e.g. supercooling, ice seeding), and transport-driven techniques (e.g. directional freezing, droplet approaches), and we hope to equip the reader with a self-consistent theoretical toolkit that enables meaningful comparison of these techniques from a thermodynamic perspective.
https://arxiv.org/abs/2601.12573
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5e1ec1e3670cfb96b66da036e0453747da31fe3b0d1956f8ebfeeaf67ebf62de
2026-01-21T00:00:00-05:00
onepot CORE -- an enumerated chemical space to streamline drug discovery, enabled by automated small molecule synthesis and AI
arXiv:2601.12603v1 Announce Type: new Abstract: The design-make-test-analyze cycle in early-stage drug discovery remains constrained primarily by the "make" step: small-molecule synthesis is slow, costly, and difficult to scale or automate across diverse chemotypes. Enumerated chemical spaces aim to reduce this bottleneck by predefining synthesizable regions of chemical space from available building blocks and reliable reactions, yet existing commercial spaces are still limited by long turnaround times, narrow reaction scope, and substantial manual decision-making in route selection and execution. Here we present the first version of onepot CORE, an enumerated chemical space containing 3.4B molecules and corresponding on-demand synthesis product enabled by an automated synthesis platform and an AI chemist, Phil, that designs, executes, and analyzes experiments. onepot CORE is constructed by (i) selecting a reaction set commonly used in medicinal chemistry, (ii) sourcing and curating building blocks from supplier catalogs, (iii) enumerating candidate products, and (iv) applying ML-based feasibility assessment to prioritize compounds for robust execution. In the current release, the space is supported by seven reactions. We describe an end-to-end workflow - from route selection and automated liquid handling through workup and purification. We further report validation across operational metrics (success rate, timelines, purity, and identity), including NMR confirmation for a representative set of synthesized compounds and assay suitability demonstrated using a series of DPP4 inhibitors. Collectively, onepot CORE illustrates a path toward faster, more reliable access to diverse small molecules, supporting accelerated discovery in pharmaceuticals and beyond.
https://arxiv.org/abs/2601.12603
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ed59aea61fe9847b4806244b99d5473642b9aa1b22637fe09bd3861469670a5b
2026-01-21T00:00:00-05:00
Deterministic and probabilistic neural surrogates of global hybrid-Vlasov simulations
arXiv:2601.12614v1 Announce Type: new Abstract: Hybrid-Vlasov simulations resolve ion-kinetic effects for modeling the solar wind-magnetosphere interaction, but even 5D (2D + 3V) simulations are computationally expensive. We show that graph-based machine learning emulators can learn the spatiotemporal evolution of electromagnetic fields and lower order moments of ion velocity distribution in the near-Earth space environment from four 5D Vlasiator runs performed with identical steady solar wind conditions. The initial ion number density is systematically varied, while the grid spacing is held constant, to scan the ratio of the characteristic ion skin depth to the numerical grid size. Using a graph neural network architecture operating on the 2D spatial simulation grid comprising 670k cells, we demonstrate that both a deterministic forecasting model (Graph-FM) and a probabilistic ensemble forecasting model (Graph-EFM) based on a latent variable formulation are capable of producing accurate predictions of future plasma states. A divergence penalty is incorporated during training to encourage divergence-freeness in the magnetic fields and improve physical consistency. For the probabilistic model, a continuous ranked probability score objective is added to improve the calibration of the ensemble forecasts. When trained, the emulators achieve more than two orders of magnitude speedup in generating the next time step relative to the original simulation on a single GPU compared to 100 CPUs for the Vlasiator runs, while closely matching physical magnetospheric response of the different runs. These results demonstrate that machine learning offers a way to make hybrid-Vlasov simulation tractable for real-time use while providing forecast uncertainty.
https://arxiv.org/abs/2601.12614
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fe48606abfe11a65e5a9b47c5b47d910bf2afb56df5e063c07ebc78b5b335a01
2026-01-21T00:00:00-05:00
Direct in-chamber radon-220 (thoron) emanation measurements for rare-event physics experiments
arXiv:2601.12622v1 Announce Type: new Abstract: Measuring radon emanation from detector materials is a key method for controlling radon, a significant background in rare-event physics experiments. Methods for measuring radon emanation are well-established but have predominantly focused on the 222Rn isotope, the dominant radon isotope for these backgrounds. However, measurements of 220Rn (thoron), the second most abundant radon isotope, remain relatively unexplored. 220Rn emanation measurements are challenging because the 220Rn must be transferred from the emanation chamber to the active detector within its short 55 s half-life. In this study, a direct in-chamber approach for measuring 220Rn emanation is presented in which the sample is placed directly within the active detector chamber, thereby minimising losses during transfer. The method was demonstrated with a DURRIDGE RAD8 electrostatic radon detector, which measured 220Rn emanation from low-activity thoriated rods with an activity of 76 +/- 20 mBq. Compared with a conventional flowthrough 220Rn emanation setup, the in-chamber method increased sensitivity by a factor of 3. Using helium as the carrier gas provided a further sensitivity increase, giving an overall sensitivity gain of ~5. These results indicate that in-chamber 220Rn emanation measurements provide an effective tool for low-background experiments and have the potential to accelerate radon studies by exploiting the shorter half-life of 220Rn.
https://arxiv.org/abs/2601.12622
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dfae23f936109b2b0da405e2299b953465fc7e086415a27e2ad873baae6575b9
2026-01-21T00:00:00-05:00
Reorienting off-path Nudged Elastic Bands (RONEB) via Minimum Mode Following
arXiv:2601.12630v1 Announce Type: new Abstract: Accurate determination of transition states remains central to understanding reaction kinetics. Double-ended methods like the Nudged Elastic Band (NEB) ensure relevant transition states and paths, but incur high computational costs and suffer stagnation on flat or rough potential energy surfaces. Conversely, single-ended eigenmode-following techniques offer efficiency but cannot often be constrained between specific states. Here, we present the Reorienting Off-path Nudged Elastic Bands (RONEB), an adaptive hybrid algorithm that integrates the double ended nature of the NEB with the acceleration of single ended Min-Mode Following methods. RONEB provides stability based on the history of the path optimization, relative force triggering, and an alignment-based back-off penalty to dynamically decouple the climbing image from the elastic band constraints. We benchmark the method against the standard Climbing Image NEB (CI-NEB) across the Baker-Chan transition state test set using the PET-MAD machine-learned potential and the OptBench Pt(111) heptamer island surface diffusion set. A Bayesian analysis of the performance data quantifies a median reduction in gradient calls of 46.3% [95% CrI: -54.7%, -36.9%] relative to the baseline, while surface diffusion tests reveal a 28% reduction across 59 metallic rearrangement mechanisms. These results establish RONEB as a highly effective tool for high-throughput automated chemical discovery.
https://arxiv.org/abs/2601.12630
Academic Papers
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7ff5b6e6c0f772d8227cde826cad1935ec56d65b2071e75fe514378d6eac21b6
2026-01-21T00:00:00-05:00
In Vivo Quantification of Arterial Active Mechanics Using Deep Learning-Assisted Pressure-Area Analysis
arXiv:2601.12631v1 Announce Type: new Abstract: Active arterial mechanics, governed by vascular smooth muscle contraction, are critical to physiological regulation, cardiovascular disease progression, and clinical diagnosis. Although various in vivo methods have been developed to assess arterial stiffness, most cannot distinguish the contribution of smooth muscle tone; therefore, quantitative characterization of arterial activity remains challenging. In this study, we developed a pressure-area analysis framework integrating ultrasound imaging, blood pressure measurement, neural network-based segmentation of arterial cross-sectional area, and biomechanical model-driven inversion to infer active mechanical properties. A total of 233 volunteers (aged 18-65 year) were recruited to acquire cross-sectional ultrasound videos of the right common carotid artery for training the neural network. The segmentation results demonstrate good spatial and temporal performance of the neural network. We further recruited 10 additional volunteers (aged 25 +/- 3 year) to perform a 1-minute step test, followed by pressure-area measurements over a 30-minute recovery period. Using the proposed approach, we quantified post-exercise changes in carotid arterial active mechanics relative to baseline (i.e., the resting state). Results showed that active mechanics remained elevated for approximately 15 minutes compared to baseline (p < 0.05), whereas systolic pressure differed significantly only within the first approximately 5 minutes post-exercise (p < 0.001). These results indicate a dissociation between blood pressure and smooth muscle recovery, which may offer new insight into vascular smooth muscle regulation during physiological stress.
https://arxiv.org/abs/2601.12631
Academic Papers
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2dfd58c70853cbf882a2efee47812ecee5970b906e7d6808855770cccf46a5c2
2026-01-21T00:00:00-05:00
Inertia-Dilatancy Interplay Governs Shear-Thickening Drop Impact
arXiv:2601.12642v1 Announce Type: new Abstract: Combining high-speed photography with direct force measurements, we investigate the impact dynamics of drops of cornstarch-water mixtures -- a premier example of shear-thickening fluids -- across a wide range of impact conditions. Our study identifies three distinct impact regimes. In addition to the liquid-like and solid-like behaviors generally expected for the impact-induced response of shear-thickening fluids, we uncover a counterintuitive regime in which high-concentration cornstarch-water mixtures display a liquid-like response at the onset of impact when shear rates are high and only transition to a solid-like behavior at later times as shear rates reduce. By integrating the classic drop-impact theory with the Reynolds-Darcy mechanism for dilatancy, we develop a unified model that quantitatively describes the impact dynamics of shear-thickening drops across all regimes. Our work reveals the unexpected response of shear-thickening fluids to ultra-fast deformation and advances fundamental understanding of drop impact for complex fluids.
https://arxiv.org/abs/2601.12642
Academic Papers
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126f2ae019c8bd8822a23dc3cb9f004df5f6c6012e631c2255fe6145459810fe
2026-01-21T00:00:00-05:00
Radio-frequency pulse design in local rotating frame in magnetic resonance imaging
arXiv:2601.12645v1 Announce Type: new Abstract: The problem of spatially selective radio-frequency (RF) pulse design in magnetic resonance imaging (MRI) is typically stated in the form of determining, analytically or numerically, RF waveforms to be applied in synchrony with one or more predetermined gradient waveforms. In most cases, the dynamics of the nuclear spin magnetization under the RF and gradient fields is described in a global rotating frame that cancels the effect of the static (main) magnetic field B0. In this work, we consider an alternative frame of reference, which can be called a local rotating frame where total longitudinal magnetic field (B0 plus gradient) in every voxel is zero. In this frame, the effect of time-dependent gradient field is integrated out, and the remaining magnetization dynamics, governed by much weaker RF fields, becomes both simpler and slower. We show that recasting existing RF design methods in such a frame provides useful insights and techniques that are not obvious in the conventional description. The methods we consider include (i) two-dimensional spatial RF pulse design in the excitation k-space, (ii) Shinnar-Le Roux RF design, (iii) residual phase calculation in slice-selective excitation, and (iv) iterative and numerical solutions for multi-coil RF pulse design. In particular, we show that the new formalism can substantially reduce the Bloch simulation time which can greatly benefit iterative pulse designs in parallel transmit. In all, the proposed framework provides considerable theoretical insights and practical utility for RF pulse design in MRI.
https://arxiv.org/abs/2601.12645
Academic Papers
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2afc6e6b34208b28e4033c69a9693bc15fe03ba3679e2e715c3dda026cb9ab43
2026-01-21T00:00:00-05:00
Emergence of Structural Disparities in theWeb of Scientific Citations
arXiv:2601.12665v1 Announce Type: new Abstract: Scientific attention is unevenly distributed, creating inequities in recognition and distorting access to opportunities. Using citations as a proxy, we quantify disparities in attention by gender and institutional prestige. We find that women receive systematically fewer citations than men, and that attention is increasingly concentrated among authors from elite institutions -- patterns not fully explained by underrepresentation alone. To explain these dynamics, we introduce a model of citation network growth that incorporates homophily (tendency to cite similar authors), preferential attachment (favoring highly cited authors) and group size (underrepresentation). The model shows that disparities arise not only from group size imbalances but also from cumulative advantage amplifying biased citation preferences. Importantly, increasing representation alone is often insufficient to reduce disparities. Effective strategies should also include reducing homophily, amplifying the visibility of underrepresented groups, and supporting equitable integration of newcomers. Our findings highlight the challenges of mitigating inequities in asymmetric networks like citations, where recognition flows in one direction. By making visible the mechanisms through which attention is distributed, we contribute to efforts toward a more responsible web of science that is fairer, more transparent, and more inclusive, and that better sustains innovation and knowledge production.
https://arxiv.org/abs/2601.12665
Academic Papers
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feeccbdfea6c49eb85aa8fb55a2c15cc6c5580db7b4a1c7bae0021c0a19a109b
2026-01-21T00:00:00-05:00
General Relativistic Quantum Mechanics deriving Electroweak and Gravitational Interactions
arXiv:2601.12668v1 Announce Type: new Abstract: A gauge theory with an indefinite metric without negative probabilities is given by extending quantum mechanics, where a general metric is introduced, and the invariance under the general linear transformation is imposed on the space of quantum states. On this basis, we construct and investigate a chiral sextet model, which has one more Lorentz symmetry in the gauge space, to derive much properties of the standard electroweak theory, and also Einstein gravity, when the double Lorentz symmetry spontaneously fuses into one.
https://arxiv.org/abs/2601.12668
Academic Papers
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55f0156c86917facc1cc86c41b3f032f97b3e640f83a48dff82ab46dae150fc5
2026-01-21T00:00:00-05:00
Purely equatorial lasing in spherical liquid crystal polymer microlasers with engineered refractive index gradient
arXiv:2601.12673v1 Announce Type: new Abstract: Liquid crystal whispering gallery mode microlasers show high sensitivity to external stimuli and distinct spectral features, rendering them ideally suited for various sensing applications. They also offer intrinsic anisotropic optical properties, which can be used to shape and manipulate light even inside spatially highly symmetric structures. Here, we report the synthesis and detailed optical characterization of a spherical bipolar liquid crystal polymer microlaser that tightly confines the optical path of whispering gallery modes to the equatorial plane. By controlled anchoring of the liquid crystal mesogens followed by polymerization, a fixed refractive index gradient is formed within the spherical microcavity. Consequently, only transverse electric (TE) modes oscillating in the equatorial plane experience the high extraordinary refractive index, allowing to confine lasing into a single plane. Furthermore, we observe that the refractive index gradient causes a characteristic splitting of the TE modes. By combining hyperspectral imaging and analytical modeling, we demonstrate that the observed splitting is caused by lifting of the energy degeneracy of higher order azimuthal laser modes, enabling direct insights into the complex interplay of refractive index gradients and resulting whispering gallery mode confinement. In addition, the unique ability to confine lasing of a spherical microbead into only a single plane makes these microlasers independent of the exact position of the pump beam, which allows consistent localized sensing especially in combination with fast point scanning microscopes or inside highly dynamic biological environments.
https://arxiv.org/abs/2601.12673
Academic Papers
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6678a02140644cf5bb7b9c0003d81a2acb9fd028a1265c5f6ef34bdd61ed6a97
2026-01-21T00:00:00-05:00
An efficient numerical method for simulating two-dimensional non-periodic metasurfaces
arXiv:2601.12674v1 Announce Type: new Abstract: Metasurfaces are extremely useful for controlling and manipulating electromagnetic waves. Full-wave numerical simulation is highly desired for their design and optimization, but it is notoriously difficult, even for two-dimensional metasurfaces, when they comprise a huge number of subwavelength elements. This paper focuses on two-dimensional non-periodic metasurfaces that contain only a relatively small number of distinct subwavelength elements. We develop an efficient numerical method based on Neumann-to-Dirichlet operators, the finite element method and local function expansions. Our method drastically reduces the total number of unknowns and is capable of simulating two-dimensional metasurfaces with $10^{5}$ subwavelength elements on a personal computer. Numerical examples demonstrate that the method maintains high accuracy while offering significant advantages in both computational time and memory usage compared to the classical full-domain finite element method, making it particularly suited for the analysis of large metasurfaces.
https://arxiv.org/abs/2601.12674
Academic Papers
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