Tootfinder

Good article on some of the UK developments enabling aggregators (virtual lead parties) to unlock more demand side flexibility, including residential (heat pumps, batteries, EVs).
https://www.greenexecutives.com/post/unlocking-th…

Unlocking the Future of Energy: How UK Flex Markets Are Reshaping the Grid
With more renewable energy—especially wind and solar—being integrated than ever before, maintaining balance between supply and demand in real time is a growing challenge. That’s where flex markets come in - and everyone from business to consumers is invited to have a seat at the table.

This https://arxiv.org/abs/2502.08766 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Unlocking Mental Health: Exploring College Students' Well-being through Smartphone Behaviors
The global mental health crisis is a pressing concern, with college students particularly vulnerable to rising mental health disorders. The widespread use of smartphones among young adults, while offering numerous benefits, has also been linked to negative outcomes such as addiction and regret, significantly impacting well-being. Leveraging the longest longitudinal dataset collected over four college years through passive mobile sensing, this study is the first to examine the relationship betwe…

Unlocking my own understanding of and ability to build #Swift macros feels like a superpower.
…something something great responsibility, though.
Synthesizing boilerplate and statically-verifiable elements like custom function calls based on macro input… is magic—the good kind.
`@GET("/logs/{userId}/{timing}")`
↘️

Agile Orchestration at Will: An Entire Smart Service-Based Security Architecture Towards 6G
Zhuoran Duan, Guoshun Nan, Rushan Li, Zijun Wang, Lihua Xiong, Chaoying Yuan, Guorong Liu, Hui Xu, Qimei Cui, Xiaofeng Tao, Tony Q. S. Quek
https://arxiv.org/abs/2505.22963

Agile Orchestration at Will: An Entire Smart Service-Based Security Architecture Towards 6G
The upcoming 6G will fundamentally reshape mobile networks beyond communications, unlocking a multitude of applications that were once considered unimaginable. Meanwhile, security and resilience are especially highlighted in the 6G design principles. However, safeguarding 6G networks will be quite challenging due to various known and unknown threats from highly heterogeneous networks and diversified security requirements of distinct use cases, calling for a comprehensive re-design of security a…

Subwavelength Phase Engineering Deep Inside Silicon
Mehmet B\"ut\"un, Alperen Saltik, Onur Tokel
https://arxiv.org/abs/2507.20824 https://arxiv.o…

Subwavelength Phase Engineering Deep Inside Silicon
Recent advances in three-dimensional laser writing have enabled direct nanostructuring deep within silicon, unlocking a volumetric design space previously inaccessible to surface-bound nanophotonic devices. Here, we introduce subwavelength phase engineering inside crystalline silicon, offering a novel strategy for integrated photonics. We design and numerically demonstrate a volumetric metaoptic monolithically embedded within the bulk, achieving full 2$π$ phase control at telecommunication wav…

from my link log —
Unlocking sudoku's secrets with graph theory and abstract algebra.
https://chalkdustmagazine.com/features/unlocking-sudokus-secrets/
saved 2025-04-14

Unlocking sudoku's secrets - Chalkdust
Sara Logsdon looks to graph theory and abstract algebra for help on the puzzle page

Chain-of-Experts: Unlocking the Communication Power of Mixture-of-Experts Models
Zihan Wang, Rui Pan, Jiarui Yao, Robert Csordas, Linjie Li, Lu Yin, Jiajun Wu, Tong Zhang, Manling Li, Shiwei Liu
https://arxiv.org/abs/2506.18945

Chain-of-Experts: Unlocking the Communication Power of Mixture-of-Experts Models
We propose Chain-of-Experts (CoE), a new Mixture-of-Experts (MoE) architecture that introduces sequential expert communication within each layer. Unlike traditional MoE models, where experts operate independently in parallel, CoE processes tokens iteratively across a chain of experts inside a layer. To support dynamic expert selection across iterations, CoE employs a dedicated router at each iteration step within a layer. This design allows tokens to re-evaluate and select different experts dur…

May the Feedback Be with You! Unlocking the Power of Feedback-Driven Deep Learning Framework Fuzzing via LLMs
Shaoyu Yang, Chunrong Fang, Haifeng Lin, Xiang Chen, Zhenyu Chen
https://arxiv.org/abs/2506.17642

May the Feedback Be with You! Unlocking the Power of Feedback-Driven Deep Learning Framework Fuzzing via LLMs
Artificial Intelligence (AI) Infrastructures, represented by Deep Learning (DL) frameworks, have served as fundamental DL systems over the last decade. However, the bugs in DL frameworks could lead to catastrophic consequences in some critical scenarios (e.g., healthcare and autonomous driving). A simple yet effective way to find bugs in DL frameworks is fuzz testing (Fuzzing). Unfortunately, existing fuzzing techniques have not comprehensively considered multiple types of feedback. Additionall…

A Lyapunov-Guided Diffusion-Based Reinforcement Learning Approach for UAV-Assisted Vehicular Networks with Delayed CSI Feedback
Zhang Liu (Sherman), Lianfen Huang (Sherman), Zhibin Gao (Sherman), Xianbin Wang (Sherman), Dusit Niyato (Sherman), Xuemin (Sherman), Shen
https://arxiv.org/abs/2507.20524…

A Lyapunov-Guided Diffusion-Based Reinforcement Learning Approach for UAV-Assisted Vehicular Networks with Delayed CSI Feedback
Low altitude uncrewed aerial vehicles (UAVs) are expected to facilitate the development of aerial-ground integrated intelligent transportation systems and unlocking the potential of the emerging low-altitude economy. However, several critical challenges persist, including the dynamic optimization of network resources and UAV trajectories, limited UAV endurance, and imperfect channel state information (CSI). In this paper, we offer new insights into low-altitude economy networking by exploring i…

Antibonding and Electronic Instabilities in GdRu2X2 (X = Si, Ge, Sn): A New Pathway Toward Developing Centrosymmetric Skyrmion Materials
Dasuni N. Rathnaweera, Xudong Huai, K. Ramesh Kumar, Sumanta Tewari, Micha{\l} J. Winiarski, Richard Dronskowski, Thao T. Tran
https://arxiv.org/abs/2507.18904

Antibonding and Electronic Instabilities in GdRu2X2 (X = Si, Ge, Sn): A New Pathway Toward Developing Centrosymmetric Skyrmion Materials
Chemical bonding is key to unlocking the potential of magnetic materials for future information technology. Magnetic skyrmions are topologically protected nano-sized spin textures that can enable high-density low-power spin-based electronics. Despite increasing interest in the discovery of new skyrmion hosts and their characterization, the electronic origins of the skyrmion formation remain unknown. Here, we study GdRu2X2 (X = Si, Ge, Sn) as a model system to study the connection among chemical…

Model Predictive Control for Unlocking Energy Flexibility of Heat Pump and Thermal Energy Storage Systems: Experimental Results
Weihong Tang, Yun Li, Shalika Walker, Tamas Keviczky
https://arxiv.org/abs/2507.17552

Model Predictive Control for Unlocking Energy Flexibility of Heat Pump and Thermal Energy Storage Systems: Experimental Results
Increasing penetration of renewable energy sources (RES) and electrification of energy systems necessitates the engagement of demand-side management (DSM) to help alleviate congestion in electricity grid. Heat pump and thermal energy storage (HPTES) systems, being energy efficient solutions, are becoming popular in modern buildings and are promising to contribute to demand-side management (DSM) due to their significant share in household electricity consumption. For typical HPTES systems, this …

Unlocking Musical Understanding - Practising the Piano https://practisingthepiano.com/unlocking-musical-understanding-keyboard-harmony/?utm_sourc…

Unlocking Musical Understanding - Practising the Piano
Learn how to use keyboard harmony as a means of developing essential musical skills such as theory, ear training and analysis!

Unlocking Surfactant Synergies for Fluorine Replacements: A Microfluidic Exploration of Emulsion Stability and Coalescence Dynamics
Rana Bachnak, Cari Dutcher
https://arxiv.org/abs/2507.17894

Unlocking Surfactant Synergies for Fluorine Replacements: A Microfluidic Exploration of Emulsion Stability and Coalescence Dynamics
Fluorinated surfactants are widely utilized in various applications, including firefighting foams, coatings, and lubricants. Their wide utility is due to their unique properties, such as their ability to effectively lower surface/interfacial tension. However, the excessive use of fluorinated surfactants has raised environmental and health concerns due to their persistence in the environment and potential toxicity. The need for effective and sustainable surfactant replacements has therefore beco…

Remember to cover your phone with the other hand while unlocking it. Don't let others see your fingerprint.

Unlocking the Hodge Conjecture: A Spectral Fingerprint Approach via Gauss-Manin Derivatives
Bita Hajebi, Pooya Hajebi
https://arxiv.org/abs/2507.13064 http…

Unlocking the Hodge Conjecture: A Spectral Fingerprint Approach via Gauss-Manin Derivatives
We present a symbolic analytic framework for addressing the Hodge Conjecture, based on a refined invariant called the Hermitian spectral fingerprint. By projecting out $(k,k)$ components from holomorphic forms and their Gauss Manin derivatives, we define a fingerprint functional that vanishes identically for any rational cohomology class of type $(k,k)$. We prove unconditionally that the projected derivatives span the entire orthogonal complement of $H^{k,k}(X)$ in $H^{2k}(X,\mathbb{C})$, imply…

Exploring Strategies for Personalized Radiation Therapy Part I Unlocking Response-Related Tumor Subregions with Class Activation Mapping
Hao Peng, Steve Jiang, Robert Timmerman
https://arxiv.org/abs/2506.17536

Exploring Strategies for Personalized Radiation Therapy Part I Unlocking Response-Related Tumor Subregions with Class Activation Mapping
Personalized precision radiation therapy requires more than simple classification, it demands the identification of prognostic, spatially informative features and the ability to adapt treatment based on individual response. This study compares three approaches for predicting treatment response: standard radiomics, gradient based features, and convolutional neural networks enhanced with Class Activation Mapping. We analyzed 69 brain metastases from 39 patients treated with Gamma Knife radiosurge…

On using AI for EEG-based BCI applications: problems, current challenges and future trends
Thomas Barbera, Jacopo Burger, Alessandro D'Amelio, Simone Zini, Simone Bianco, Raffaella Lanzarotti, Paolo Napoletano, Giuseppe Boccignone, Jose Luis Contreras-Vidal
https://arxiv.org/abs/2506.16168

On using AI for EEG-based BCI applications: problems, current challenges and future trends
Imagine unlocking the power of the mind to communicate, create, and even interact with the world around us. Recent breakthroughs in Artificial Intelligence (AI), especially in how machines "see" and "understand" language, are now fueling exciting progress in decoding brain signals from scalp electroencephalography (EEG). Prima facie, this opens the door to revolutionary brain-computer interfaces (BCIs) designed for real life, moving beyond traditional uses to envision Brain-to-Speech, Brain-to-…

Learning Deliberately, Acting Intuitively: Unlocking Test-Time Reasoning in Multimodal LLMs
Yahan Yu, Yuyang Dong, Masafumi Oyamada
https://arxiv.org/abs/2507.06999

Learning Deliberately, Acting Intuitively: Unlocking Test-Time Reasoning in Multimodal LLMs
Reasoning is a key capability for large language models (LLMs), particularly when applied to complex tasks such as mathematical problem solving. However, multimodal reasoning research still requires further exploration of modality alignment and training costs. Many of these approaches rely on additional data annotation and relevant rule-based rewards to enhance the understanding and reasoning ability, which significantly increases training costs and limits scalability. To address these challeng…

Unlocking time-dependent $CP$ violation without signal vertexing at $B$ factories
Mirco Dorigo, Sebastiano Raiz, Diego Tonelli, Radek Zlebcik
https://arxiv.org/abs/2506.11196

Unlocking time-dependent $CP$ violation without signal vertexing at $B$ factories
We present a novel method to measure, without reconstructing the signal decay vertex, time-dependent $CP$ violation in $B^0$ mesons produced in energy-asymmetric electron-positron collisions near the $Υ(4S)$ resonance. The method relies on quantum-entangled $B^0\overline{B}^0$ pair-production making the decay time of the partner meson sensitive to $CP$ violation of the signal. We derive analytical expressions for the relevant time-evolution and study, as a use case, an application to $B^0\toπ…

EME-TTS: Unlocking the Emphasis and Emotion Link in Speech Synthesis
Haoxun Li, Leyuan Qu, Jiaxi Hu, Taihao Li
https://arxiv.org/abs/2507.12015 https://

EME-TTS: Unlocking the Emphasis and Emotion Link in Speech Synthesis
In recent years, emotional Text-to-Speech (TTS) synthesis and emphasis-controllable speech synthesis have advanced significantly. However, their interaction remains underexplored. We propose Emphasis Meets Emotion TTS (EME-TTS), a novel framework designed to address two key research questions: (1) how to effectively utilize emphasis to enhance the expressiveness of emotional speech, and (2) how to maintain the perceptual clarity and stability of target emphasis across different emotions. EME-TT…

First Detection of Circular Polarization in Radio Continuum Toward a Massive #Protostar: https://iopscience.iop.org/article/10.3847/2041-8213/ade99b -> Unlocking cosmic secrets of stellar birth - first glimpse of magnetism near an infant massive star: https://www.iist.ac.in/massive_star

Replaced article(s) found for cs.MA. https://arxiv.org/list/cs.MA/new
[1/1]:
- Agent-Based Triangle Counting: Unlocking Truss Decomposition, Triangle Centrality, and Local Clus...
Prabhat Kumar Chand, Apurba Das, Anisur Rahaman Molla

Unlocking the mystery of Sr synthesis in the early Galaxy through analysis of barium isotopes in very metal-poor stars
T. M. Sitnova, L. Lombardo, L. I. Mashonkina, F. Rizzuti, G. Cescutti, C. J. Hansen, P. Bonifacio, E. Caffau, A. Koch-Hansen, G. Meynet, R. Fernandes de Melo
https://arxiv.org/abs/2506.10193

Unlocking the mystery of Sr synthesis in the early Galaxy through analysis of barium isotopes in very metal-poor stars
We determine the contributions of the rapid (r) and slow (s) neutron capture processes to the Ba isotope mixture, along with Ba, Eu, and Sr NLTE abundances, in a sample of very metal-poor stars. The selected stars formed before the contribution from the main s-process in low- and intermediate-mass stars became significant. Some of our sample stars are enhanced in Sr, with [Sr/Ba] reaching up to 0.7. These stars gained their high Sr abundance from a poorly understood process, which may appear to…

Aethorix v1.0: AI-Driven Inverse Design of Inorganic Materials for Scalable Industrial Innovation
Yingjie Shi, Runtian Miao
https://arxiv.org/abs/2506.16609

Aethorix v1.0: AI-Driven Inverse Design of Inorganic Materials for Scalable Industrial Innovation
Artificial intelligence for Science (AI4S) is poised to transform industrial manufacturing by enabling the accelerated discovery and optimization of advanced (bio)materials, dramatically reducing development cycles, and unlocking novel high-performance solutions. We introduce Aethorix v1.0, a platform that integrates large language models for objective mining, diffusion-based generative models for zero-shot inorganic crystal design, and machine-learned interatomic potentials for rapid property …

Unlocking Altermagnetism in Antiferromagnetic 2D Films via Adsorption
Dong Liu, Sike Zeng, Ji-Hai Liao, Yu-Jun Zhao
https://arxiv.org/abs/2507.09518 https:…

Unlocking Altermagnetism in Antiferromagnetic 2D Films via Adsorption
Altermagnets, characterized by zero net magnetization and momentum-dependent spin splitting, have recently garnered significant attention due to their potential applications in a variety of fields. Here, we propose a symmetry-engineering strategy to unlock altermagnetism in two dimensional (2D) antiferromagnetic systems via surface adsorption of atoms or molecules. By employing spin group theory, we systematically demonstrate that selectively breaking symmetry operations, specifically those pro…

DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training
Zhixin Wang, Tianyi Zhou, Liming Liu, Ao Li, Jiarui Hu, Dian Yang, Jinlong Hou, Siyuan Feng, Yuan Cheng, Yuan Qi
https://arxiv.org/abs/2507.13833

DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training
Reinforcement learning (RL) has become the pivotal post-training technique for large language model. Effectively scaling reinforcement learning is now the key to unlocking advanced reasoning capabilities and ensuring safe, goal-aligned behavior in the most powerful LLMs. Mainstream frameworks usually employ a hybrid-controller architecture where a single-controller dispatches the overall execution logic and manages overall data transfer and the multi-controller executes distributed computation.…

Unlocking the hidden potential of pulsar astronomy
D. Kaur, G. Hobbs, A. Zic, J. R. Dawson, J. Morgan, W. Ling, S. Camtepe, J. Pieprzyk, M. C. M. Cheung
https://arxiv.org/abs/2506.08056

Unlocking the hidden potential of pulsar astronomy
Pulsars have traditionally been used for research into fundamental physics and astronomy. In this paper, we investigate the expanding applications of radio pulsars in societal and industrial domains beyond their conventional scientific roles. We describe emerging applications in positioning, navigation, timing and synchronization, random number generation, space weather monitoring, public engagement, antenna calibration techniques, and leveraging extensive pulsar data sets generated by large-sc…

Unlocking high coercivity at room temperature in phase modified MoS$_2$
Zainab Chowdhry, Kushal Mazumder, Praveen Hegde, Pramoda K. Nayak, Vidya Praveen Bhallamudi
https://arxiv.org/abs/2507.04905

Unlocking high coercivity at room temperature in phase modified MoS$_2$
Two-dimensional (2D) materials showing room-temperature magnetism and high coercivity are desired for combining magnetism with semiconducting properties useful for spintronics. In this work, the magnetic properties of the 1T phase of MoS$_2$ have been studied at room temperature. We observe ferromagnetism with a coercivity of ~0.3 T and a maximum saturation magnetization of 0.26 emu/g at room temperature. This is the highest among coercivities reported so far in 2D magnets at room temperature. …

Those of you out there facing ICE/DHS - you may want to consider temporarily disabling face recognition login on your iPhone.
Here's from Apple:
Temporarily disable Face ID
You can temporarily prevent Face ID from unlocking your iPhone.
Press and hold the side button and either volume button for 2 seconds.
After the sliders appear, press the side button to immediately lock iPhone.
iPhone locks automatically if you don’t touch the screen for…

It's like a 3D puzzle. This 18th-century Italian safe has the most unique unlocking sequences ever.

Beyond DNS: Unlocking the Internet of AI Agents via the NANDA Index and Verified AgentFacts
Ramesh Raskar, Pradyumna Chari, John Zinky, Mahesh Lambe, Jared James Grogan, Sichao Wang, Rajesh Ranjan, Rekha Singhal, Shailja Gupta, Robert Lincourt, Raghu Bala, Aditi Joshi, Abhishek Singh, Ayush Chopra, Dimitris Stripelis, Bhuwan B, Sumit Kumar, Maria Gorskikh

Beyond DNS: Unlocking the Internet of AI Agents via the NANDA Index and Verified AgentFacts
The Internet is poised to host billions to trillions of autonomous AI agents that negotiate, delegate, and migrate in milliseconds and workloads that will strain DNS-centred identity and discovery. In this paper, we describe the NANDA index architecture, which we envision as a means for discoverability, identifiability and authentication in the internet of AI agents. We present an architecture where a minimal lean index resolves to dynamic, cryptographically verifiable AgentFacts that supports …

The future of gravitational wave science unlocking LIGO potential: AI-driven data analysis and exploration
Yong Xiao, Li, Zin Nandar Win, He Wang, Hla Myo Tun, Win Thu Zar
https://arxiv.org/abs/2506.04584

The future of gravitational wave science unlocking LIGO potential: AI-driven data analysis and exploration
The advent of gravitational wave astronomy (GW) has revolutionized the observation of cataclysmic cosmic events, such as black hole mergers and neutron star collisions. The Laser Interferometer Gravitational-Wave Observatory (LIGO) has been at the forefront of these discoveries. However, the immense volume and complexity of gravitational wave data present significant challenges for traditional analysis methods. This paper investigates the growing synergy between artificial intelligence (AI) and…

A Neural-Guided Variational Quantum Algorithm for Efficient Sign Structure Learning in Hybrid Architectures
Mengzhen Ren, Yu-Cheng Chen, Yangsen Ye, Min-Hsiu Hsieh, Alice Hu, Chang-Yu Hsieh
https://arxiv.org/abs/2507.07555

A Neural-Guided Variational Quantum Algorithm for Efficient Sign Structure Learning in Hybrid Architectures
Variational quantum algorithms hold great promise for unlocking the power of near-term quantum processors, yet high measurement costs, barren plateaus, and challenging optimization landscapes frequently hinder them. Here, we introduce sVQNHE, a neural-guided variational quantum algorithm that decouples amplitude and sign learning across classical and quantum modules, respectively. Our approach employs shallow quantum circuits composed of commuting diagonal gates to efficiently model quantum pha…

PyVision: Agentic Vision with Dynamic Tooling
Shitian Zhao, Haoquan Zhang, Shaoheng Lin, Ming Li, Qilong Wu, Kaipeng Zhang, Chen Wei
https://arxiv.org/abs/2507.07998

PyVision: Agentic Vision with Dynamic Tooling
LLMs are increasingly deployed as agents, systems capable of planning, reasoning, and dynamically calling external tools. However, in visual reasoning, prior approaches largely remain limited by predefined workflows and static toolsets. In this report, we present PyVision, an interactive, multi-turn framework that enables MLLMs to autonomously generate, execute, and refine Python-based tools tailored to the task at hand, unlocking flexible and interpretable problem-solving. We develop a taxonom…

Internal Heat Flux and Energy Imbalance of #Uranus: https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025GL115660 -> Discovery is Unlocking Planetary Mysteries to Advance Space Exploration and Earth Science: https://uh.edu/news-events/stories/2025/july/07142025-uranus-internal-heat-study.php

ExPO: Unlocking Hard Reasoning with Self-Explanation-Guided Reinforcement Learning
Ruiyang Zhou, Shuozhe Li, Amy Zhang, Liu Leqi
https://arxiv.org/abs/2507.02834

ExPO: Unlocking Hard Reasoning with Self-Explanation-Guided Reinforcement Learning
Recent advances in large language models have been driven by reinforcement learning (RL)-style post-training, which improves reasoning by optimizing model outputs based on reward or preference signals. GRPO-style approaches implement this by using self-generated samples labeled by an outcome-based verifier. However, these methods depend heavily on the model's initial ability to produce positive samples. They primarily refine what the model already knows (distribution sharpening) rather than ena…

Unlocking Quantum Control and Multi-Order Correlations via Terahertz Two-Dimensional Coherent Spectroscopy
Chuankun Huang, Martin Mootz, Liang Luo, Ilias E. Perakis, Jigang Wang
https://arxiv.org/abs/2507.02116

Unlocking Quantum Control and Multi-Order Correlations via Terahertz Two-Dimensional Coherent Spectroscopy
Terahertz two-dimensional coherent spectroscopy (THz-2DCS) is transforming our ability to probe, visualize, and control quantum materials far from equilibrium. This emerging technique brings multi-dimensional resolution to the ultrafast dynamics of nonequilibrium phases of matter, enabling new capabilities demanding precise coherent control and measurement of many-body dynamics and multi-order correlations. By mapping complex excitations across time and frequency dimensions, THz-2DCS delivers c…

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[3/5]:
Unlocking Neural Transparency: Jacobian Maps for Explainable AI in Alzheimer's Detection

Replaced article(s) found for cs.SD. https://arxiv.org/list/cs.SD/new
[1/1]:
- Instruct-MusicGen: Unlocking Text-to-Music Editing for Music Language Models via Instruction Tuning
Zhang, Ikemiya, Choi, Murata, Mart\'inez-Ram\'irez, Lin, Xia, Liao, Mitsufuji, Dixon

Levels of Autonomy for AI Agents
K. J. Kevin Feng, David W. McDonald, Amy X. Zhang
https://arxiv.org/abs/2506.12469 https://arxiv.org…

Levels of Autonomy for AI Agents
Autonomy is a double-edged sword for AI agents, simultaneously unlocking transformative possibilities and serious risks. How can agent developers calibrate the appropriate levels of autonomy at which their agents should operate? We argue that an agent's level of autonomy can be treated as a deliberate design decision, separate from its capability and operational environment. In this work, we define five levels of escalating agent autonomy, characterized by the roles a user can take when interac…

QuGrav: Bringing gravitational waves to light with Qumodes
Dmitri E. Kharzeev, Azadeh Maleknejad, Saba Shalamberidze
https://arxiv.org/abs/2506.09459 https…

QuGrav: Bringing gravitational waves to light with Qumodes
We propose using qumodes, quantum bosonic modes, for detecting high-frequency gravitational waves via the inverse Gertsenshtein effect, where a gravitational wave resonantly converts into a single photon in a magnetized cavity. For an occupation number $n$ of the photon field in a qumode, the conversion probability is enhanced by a factor of $n+1$ due to Bose-Einstein statistics. Unlocking this increased sensitivity entails the ability to continuously prepare the qumode and perform non-demoliti…

High Proton Conductivity of HxWO3 at Intermediate Temperatures: Unlocking Its Application as a Mixed Ionic-Electronic Conductor
Rantaro Matsuo, Tomoyuki Yamasaki, Takahisa Omata
https://arxiv.org/abs/2507.06488

High Proton Conductivity of HxWO3 at Intermediate Temperatures: Unlocking Its Application as a Mixed Ionic-Electronic Conductor
Hydrogen tungsten bronzes (HxWO3), known for their mixed protonic-electronic conduction near room temperature, are extensively studied for electrochromic and gasochromic applications. However, their proton transport properties at elevated temperatures, particularly in the intermediate-temperature range (200-500 °C), remain unexplored. This study revealed the proton transport behavior of HxWO3, focusing on its potential as a proton-conducting mixed ionic-electronic conductor (MIEC) for intermed…

A Common Interface for Automatic Differentiation
Guillaume Dalle, Adrian Hill
https://arxiv.org/abs/2505.05542 https://arxiv.org/pdf/…

A Common Interface for Automatic Differentiation
For scientific machine learning tasks with a lot of custom code, picking the right Automatic Differentiation (AD) system matters. Our Julia package DifferentiationInterface.jl provides a common frontend to a dozen AD backends, unlocking easy comparison and modular development. In particular, its built-in preparation mechanism leverages the strengths of each backend by amortizing one-time computations. This is key to enabling sophisticated features like sparsity handling without putting addition…

Distillation of atomistic foundation models across architectures and chemical domains
John L. A. Gardner, Daniel F. Thomas du Toit, Chiheb Ben Mahmoud, Zo\'e Faure Beaulieu, Veronika Juraskova, Laura-Bianca Pa\c{s}ca, Louise A. M. Rosset, Fernanda Duarte, Fausto Martelli, Chris J. Pickard, Volker L. Deringer
https://arxiv.or…

Distillation of atomistic foundation models across architectures and chemical domains
Machine-learned interatomic potentials have transformed computational research in the physical sciences. Recent atomistic `foundation' models have changed the field yet again: trained on many different chemical elements and domains, these potentials are widely applicable, but comparably slow and resource-intensive to run. Here we show how distillation via synthetic data can be used to cheaply transfer knowledge from atomistic foundation models to a range of different architectures, unlocking mu…

SToFM: a Multi-scale Foundation Model for Spatial Transcriptomics
Suyuan Zhao, Yizhen Luo, Ganbo Yang, Yan Zhong, Hao Zhou, Zaiqing Nie
https://arxiv.org/abs/2507.11588

SToFM: a Multi-scale Foundation Model for Spatial Transcriptomics
Spatial Transcriptomics (ST) technologies provide biologists with rich insights into single-cell biology by preserving spatial context of cells. Building foundational models for ST can significantly enhance the analysis of vast and complex data sources, unlocking new perspectives on the intricacies of biological tissues. However, modeling ST data is inherently challenging due to the need to extract multi-scale information from tissue slices containing vast numbers of cells. This process require…

Experimental Efficient Influence Sampling of Quantum Processes
Hao Zhan, Zongbo Bao, Zekun Ye, Qianyi Wang, Minghao Mi, Penghui Yao, Lijian Zhang
https://arxiv.org/abs/2506.07103 …

Experimental Efficient Influence Sampling of Quantum Processes
Characterizing quantum processes paves the way for unlocking the full potential of quantum systems. However, quantum process tomography demands intensive resources and becomes infeasible on large-scale quantum devices. Other methods have explored advanced strategies, yet challenges in experimental feasibility and scalability persist. To address this issues, we introduce influence sampling that efficiently extracts the key \textit{influence} of a quantum process on qubit subsets using at most th…

GHz spiking neuromorphic photonic chip with in-situ training
Jinlong Xiang, Xinyuan Fang, Jie Xiao, Youlve Chen, An He, Yaotian Zhao, Zhenyu Zhao, Yikai Su, Min Gu, Xuhan Guo
https://arxiv.org/abs/2506.14272

GHz spiking neuromorphic photonic chip with in-situ training
Neuromorphic photonic computing represents a paradigm shift for next-generation machine intelligence, yet critical gaps persist in emulating the brain's event-driven, asynchronous dynamics,a fundamental barrier to unlocking its full potential. Here, we report a milestone advancement of a photonic spiking neural network (PSNN) chip, the first to achieve full-stack brain-inspired computing on a complementary metal oxide semiconductor-compatible silicon platform. The PSNN features transformative i…

Quantum Index Report 2025
Jonathan Ruane, Elif Kiesow, Johannes Galatsanos, Carl Dukatz, Edward Blomquist, Prashant Shukla
https://arxiv.org/abs/2506.04259

Quantum Index Report 2025
The inaugural edition of the MIT Quantum Index Report (QIR). Quantum technologies are evolving from theoretical concepts into tangible technologies with commercial promise. Their rapid progress is capturing global attention and suggests we stand on the cusp of a second quantum revolution. Unlocking the quantum opportunity is not simple. One challenge is that quantum technologies can present a high barrier to understanding for nonexperts because they often rely on complex principles and concepts…

Is It Time To Treat Prompts As Code? A Multi-Use Case Study For Prompt Optimization Using DSPy
Francisca Lemos (ALGORITMI Research Centre/LASI, University of Minho), Victor Alves (ALGORITMI Research Centre/LASI, University of Minho), Filipa Ferraz (ALGORITMI Research Centre/LASI, University of Minho)
https://arxiv.org/abs/2507.0…

Is It Time To Treat Prompts As Code? A Multi-Use Case Study For Prompt Optimization Using DSPy
Although prompt engineering is central to unlocking the full potential of Large Language Models (LLMs), crafting effective prompts remains a time-consuming trial-and-error process that relies on human intuition. This study investigates Declarative Self-improving Python (DSPy), an optimization framework that programmatically creates and refines prompts, applied to five use cases: guardrail enforcement, hallucination detection in code, code generation, routing agents, and prompt evaluation. Each …

This https://arxiv.org/abs/2505.16422 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Unlocking Smarter Device Control: Foresighted Planning with a World Model-Driven Code Execution Approach
The automatic control of mobile devices is essential for efficiently performing complex tasks that involve multiple sequential steps. However, these tasks pose significant challenges due to the limited environmental information available at each step, primarily through visual observations. As a result, current approaches, which typically rely on reactive policies, focus solely on immediate observations and often lead to suboptimal decision-making. To address this problem, we propose \textbf{For…

Unlocking the hybrid piezo and pyroelectric nanogenerators performance by SiO2 nanowires confinement in poly(vinylidene fluoride)
Juan Delgado-Alvarez, Hari Krishna Mishra, Francisco J. Aparicio, Xabier Garcia-Casas, Angel Barranco, Juan R. Sanchez-Valencia, Victor Lopez-Flores, Ana Borras
https://arxiv.org/abs/2506.01580…

Unlocking the hybrid piezo and pyroelectric nanogenerators performance by SiO2 nanowires confinement in poly(vinylidene fluoride)
We report on the development of a novel flexible piezo/pyro-electric nanogenerator (PPNG) that combines a uniform film of poly(vinylidene fluoride) (PVDF) infiltrated over vertically supported SiO2 nanowires (NWs) to enhance both piezoelectric and pyroelectric energy harvesting capabilities. The synthetic procedure involves a low-temperature multi-step approach, including the soft-template formation of SiO2 NWs on a flexible substrate, followed by the infiltration of a PVDF thin film (TF). The …

This https://arxiv.org/abs/2505.18132 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

BiggerGait: Unlocking Gait Recognition with Layer-wise Representations from Large Vision Models
Large vision models (LVM) based gait recognition has achieved impressive performance. However, existing LVM-based approaches may overemphasize gait priors while neglecting the intrinsic value of LVM itself, particularly the rich, distinct representations across its multi-layers. To adequately unlock LVM's potential, this work investigates the impact of layer-wise representations on downstream recognition tasks. Our analysis reveals that LVM's intermediate layers offer complementary properties a…

Ultrafast and reliable domain-wall and skyrmion logic in a chirally coupled ferrimagnet
Yifei Ma, Dihua Wu, Fengbo Yan, Xiaoxiao Fang, Peixin Qin, Leran Wang, Li Liu, Laichuan Shen, Zhiqi Liu, Wenyun Yang, Jie Zhang, Yan Zhou, Feng Luo, Jinbo Yang, Hyunsoo Yang, Kaiming Cai, Shuai Ning, Zhaochu Luo
https://arxiv.org/abs/2507.070…

Ultrafast and reliable domain-wall and skyrmion logic in a chirally coupled ferrimagnet
Unlocking the spin degree of freedom in addition to the electron's charge, spin-based logic offers an in-memory computing architecture beyond-CMOS technology. Here, we encode information into chiral spin textures (e.g., chiral domain-wall and skyrmion) and achieve an ultrafast and reliable all-electrical logic by exploiting the Dzyaloshinskii-Moriya interaction-induced chiral coupling. Taking advantage of fast spin dynamics in antiferromagnetically coupled systems, we achieved a fast domain-wal…

Fractional Fourier Sound Synthesis
Esteban Guti\'errez, Rodrigo C\'adiz, Carlos Sing Long, Frederic Font, Xavier Serra
https://arxiv.org/abs/2506.09189

Fractional Fourier Sound Synthesis
This paper explores the innovative application of the Fractional Fourier Transform (FrFT) in sound synthesis, highlighting its potential to redefine time-frequency analysis in audio processing. As an extension of the classical Fourier Transform, the FrFT introduces fractional order parameters, enabling a continuous interpolation between time and frequency domains and unlocking unprecedented flexibility in signal manipulation. Crucially, the FrFT also opens the possibility of directly synthesizi…

Nonlinear Nonlocal Metasurface for Harmonic Generation and Manipulation
Hooman Barati Sedeh, Yuruo Zheng, Jiaren Tan, Luca Carletti, Danilo Gomes Pires, Anna R. Finkelstein, Maria Antonietta Vicenti, Ivan Kravchenko, Michael Scalora, Natalia M. Litchinitser
https://arxiv.org/abs/2507.06180…

Nonlinear Nonlocal Metasurface for Harmonic Generation and Manipulation
The discovery of second harmonic generation in 1961 marked the birth of nonlinear optics, unlocking a range of applications from frequency conversion to quantum light generation. Yet, phase matching in bulk nonlinear crystals remains a key bottleneck. Thinning nonlinear media eases this constraint but severely reduces nonlinear efficiency due to limited interaction length. Photonic metasurfaces, planar arrays of subwavelength meta atoms, offer a compelling alternative by supporting resonant mod…

This https://arxiv.org/abs/2501.02469 has been replaced.
link: https://scholar.google.com/scholar?q=a

LoRaConnect: Unlocking HTTP Potential on LoRa Backbones for Remote Areas and Ad-Hoc Networks
The minimal infrastructure requirements of LoRa make it suitable for deployments in remote and disaster-stricken areas. Concomitantly, the modern era is witnessing the proliferation of web applications in all aspects of human life, including IoT and other network services. Contemporary IoT and network solutions heavily rely on web applications to render services. However, despite the recent research and development pivoted around LoRa, there is still a lack of studies focusing on web applicatio…

Intrinsic defects explain n-type conductivity in CrSBr
Timur Biktagirov, Wolf Gero Schmidt, Karl Jakob Schiller, Michele Capra, Jonah Elias Nitschke, Lasse Sternemann, Anna Isaeva, Mirko Cinchetti
https://arxiv.org/abs/2506.06553

Intrinsic defects explain n-type conductivity in CrSBr
Understanding and controlling native defects is essential for unlocking the full potential of two-dimensional magnetic semiconductors. Here, angle-resolved photoemission spectroscopy (ARPES) and first-principles calculations are used to explore the electronic properties of bulk CrSBr. ARPES measurements reveal clear signatures of conduction band filling in as-grown crystals, indicative of unintentional doping. An analysis of intrinsic defects based on density functional theory (DFT) identifies …

This https://arxiv.org/abs/2411.01824 has been replaced.
initial toot: https://mastoxiv.page/@a…

Imprinting electrically switchable scalar spin chirality by anisotropic strain in a Kagome antiferromagnet
Topological chiral antiferromagnets, such as Mn$_{3}$Sn, are emerging as promising materials for next-generation spintronic devices due to their intrinsic transport properties linked to exotic magnetic configurations. Here, we demonstrate that anisotropic strain in Mn$_{3}$Sn thin films offers a novel approach to manipulate the magnetic ground state, unlocking new functionalities in this material. Anisotropic strain reduces the point group symmetry of the manganese (Mn) Kagome triangles from $C…

Towards Network Data Analytics in 5G Systems and Beyond
Marcos Lima Romero, Ricardo Suyama
https://arxiv.org/abs/2506.04860 https://a…

Towards Network Data Analytics in 5G Systems and Beyond
Data has become a critical asset in the digital economy, yet it remains underutilized by Mobile Network Operators (MNOs), unlike Over-the-Top (OTT) players that lead global market valuations. To move beyond the commoditization of connectivity and deliver greater value to customers, data analytics emerges as a strategic enabler. Using data efficiently is essential for unlocking new service opportunities, optimizing operational efficiency, and mitigating operational and business risks. Since Rele…

Switchable polarization in non-ferroelectric SrTiO$_3$
Wahib Aggoune, Matthias Scheffler
https://arxiv.org/abs/2506.01433 https://arx…

Switchable polarization in non-ferroelectric SrTiO$_3$
Perovskites with tunable and switchable polarization hold immense promise for unlocking novel functionalities. Using density-functional theory, we reveal that intrinsic defects can induce, enhance, and control polarization in non-ferroelectric perovskites, with SrTiO$_3$ as our model system. At high defect concentrations, these systems exhibit strong spontaneous polarization - comparable to that of conventional ferroelectrics. Crucially, this polarization is switchable, enabled by the inherent …

Hybrid antiferroelectric-ferroelectric domain walls in noncollinear antipolar oxides
Ivan N. Ushakov, Mats Topstad, Muhammad Z. Khalid, Niyorjyoti Sharma, Christoph Grams, Ursula Ludacka, Jiali He, Kasper A. Hunnestad, Mohsen Sadeqi-Moqadam, Julia Glaum, Sverre M. Selbach, Joachim Hemberger, Petra Becker, Ladislav Bohat\'y, Amit Kumar, Jorge \'I\~niguez-Gonz\'alez, Antonius T. J. van Helvoort, Dennis Meier

Hybrid antiferroelectric-ferroelectric domain walls in noncollinear antipolar oxides
Antiferroelectrics are emerging as advanced functional materials and are fertile ground for unusual electric effects. For example, they enhance the recoverable energy density in energy storage applications and give rise to large electromechanical responses. Here, we demonstrate noncollinearity in dipolar order as an additional degree of freedom, unlocking physical properties that are symmetry-forbidden in classical antiferroelectrics. We show that noncollinear order of electric dipole moments i…

About the Strain-Coupled Molecular Dynamics in the Ferroelastic Phase Transition of TMACd(N$_3$)$_3$
A. Nonato, R. X. Silva, C. C. Santos, A. P. Ayala, C. W. A. Paschoal
https://arxiv.org/abs/2507.01179

About the Strain-Coupled Molecular Dynamics in the Ferroelastic Phase Transition of TMACd(N$_3$)$_3$
Tetramethylammonium (TMA) cadmium azide, is a new perovskite-like compound which undergoes a series of first-order phase transitions, including a ferroelastic transition above room temperature. Understanding the order-disorder structural phase transition (SPT) mechanism in hybrid organic--inorganic perovskites (HOIPs) is crucial for designing new compounds with enhanced barocaloric efficiency, as well as unlocking other multifunctional properties. In this paper, we employed the energy fluctuati…