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CHILLING: Continuum Halos in LVHIS Local Irregular Nearby Galaxies - Radio continuum spectral behavior of dwarf galaxies
No full textDwarf galaxies, due to their shallow gravitational potentials, provide critical environments for studying feedback mechanisms from star formation and its impacts on dwarf galaxy evolution. In particular, radio continuum (RC) observations offer valuable insights into cosmic ray dynamics, which play a significant role in shaping these processes. This study investigates the detectability and spectral characteristics of RC emission in a sample of 15 dwarf galaxies (11 gas-rich, star forming dwarfs and 4 blue compact dwarfs) spanning a broad range of stellar masses and star formation histories. Using multi-band RC data (L/S-, C-, and X-band) from the Australia Telescope Compact Array, we analyse the physical conditions responsible for RC emission and explore the dominant emission mechanisms within these systems. RC emission is detected in 11 out of the 15 galaxies. Our results indicate that RC emission correlates strongly with star formation rate, far-infrared, and stellar mass, while dynamic parameters such as HI and rotational velocity exhibit no significant correlation with RC detectability. Spectral analysis reveals that the RC spectral energy distribution in these galaxies frequently deviate from a simple power-law behavior, instead displaying curvature that suggests more complex underlying physical processes. Statistical model comparison confirms that a single power-law model is inadequate to capture the observed spectral shapes, emphasising the necessity of more sophisticated approaches. Additionally, the observed radio-far-infrared correlation indicates that cosmic ray electrons in lower-mass dwarf galaxies cool more rapidly than they can escape (e.g. via galactic winds), resulting in a measurable RC deficit.ST, BA, DJB and MS acknowledge the support from the DFG via the Collaborative Research Center SFB1491 Cosmic Interacting Matters - From Source to Signal. PK acknowledge the support of the BMBF project 05A23PC1 for D-MeerKAT. The Australia Telescope Compact Array is part of the Australia Telescope National Facility (https://ror.org/05qajvd42) which is funded by the Australian Government for operation as a National Facility managed by CSIRO. We acknowledge the Gomeroi people as the Traditional Owners of the Observatory site.http://arxiv.org/abs/2510.1477
INTEGRAL detection of renewed activity from BHC IGR J17091-3624: Developing towards a state transition?
No full textAuthors: Rodriguez (CEA, F), C. Ferrigno (ISDC, CH), T. Bouchet (CEA/AIM, F), F. Cangemi (APC, F), V. Grinberg (ESA, NL), P. Laurent (CEA/AIM, F), K. Pottschmidt (CRESST/NASA/UMBC, USA), P. Thalhammer (Remeis Observatory, D), J. Wilms (Remeis Observatory, D)https://www.astronomerstelegram.org/?read=1703
Multi-timescale frequency-phase matching for high-yield nonlinear photonics
No full textIntegrated nonlinear photonic technologies, even with state-of-the-art fabrication with only a few nanometer geometry variations, face significant challenges in achieving wafer-scale yield of functional devices. A core limitation lies in the fundamental constraints of energy and momentum conservation laws. Imposed by these laws, nonlinear processes are subject to stringent frequency and phase matching (FPM) conditions that cannot be satisfied across a full wafer without requiring a combination of precise device design and active tuning. Motivated by recent theoretical and experimental advances in integrated multi-timescale nonlinear systems, we revisit this long-standing limitation and introduce a fundamentally relaxed and passive framework: nested frequency-phase matching. As a prototypical implementation, we investigate on-chip multi-harmonic generation in a two-timescale lattice of commercially available silicon nitride (SiN) coupled ring resonators, which we directly compare with conventional single-timescale counterparts. We observe distinct and striking spatial and spectral signatures of nesting-enabled relaxation of FPM. Specifically, for the first time, we observe simultaneous fundamental, second, third, and fourth harmonic generation, remarkable 100 percent multi-functional device yield across the wafer, and ultra-broad harmonic bandwidths. Crucially, these advances are achieved without constrained geometries or active tuning, establishing a scalable foundation for nonlinear optics with broad implications for integrated frequency conversion and synchronization, self-referencing, metrology, squeezed light, and nonlinear optical computing.http://arxiv.org/abs/2506.1501
XRISM/Resolve View of Abell 2319: Turbulence, Sloshing, and ICM Dynamics
No full textWe present results from XRISM/Resolve observations of the core of the galaxy cluster Abell 2319, focusing on its kinematic properties. The intracluster medium (ICM) exhibits temperatures of approximately 8 keV across the core, with a prominent cold front and a high-temperature region (∼11 keV) in the northwest. The average gas velocity in the 3 arcmin × 4 arcmin region around the brightest cluster galaxy (BCG) covered by two Resolve pointings is consistent with that of the BCG to within 40 km s⁻¹ and we found modest average velocity dispersion of 230-250 km s⁻¹. On the other hand, spatially-resolved spectroscopy reveals interesting variations. A blueshift of up to ∼230 km s⁻¹ is observed around the east edge of the cold front, where the gas with the lowest specific entropy is found. The region further south inside the cold front shows only a small velocity difference from the BCG; however, its velocity dispersion is enhanced to ∼400 km s⁻¹, implying the development of turbulence. These characteristics indicate that we are observing sloshing motion with some inclination angle following BCG and that gas phases with different specific entropy participate in sloshing with their own velocities, as expected from simulations. No significant evidence for a high-redshift ICM component associated with the subcluster Abell 2319B was found in the region covered by the current Resolve pointings. These results highlight the importance of sloshing and turbulence in shaping the internal structure of Abell 2319. Further deep observations are necessary to better understand the mixing and turbulent processes within the cluster.We gratefully acknowledge the hard work over many years of all of the engineers and scientists who made the XRISM mission possible. Part of this work was performed under the auspices of the U.S. This work was supported by the JSPS Core-to-Core Program, JPJSCCA20220002. The material is based on work supported by the Strategic Research Center of Saitama University. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. The material is based upon work supported by NASA under award numbers 80GSFC21M0002 and 80GSFC24M0006. This work was supported by JSPS KAKENHI grant numbers JP19K14762, JP19K21884, JP20H00157, JP20H01946, JP20H01947, JP20H05857, JP20K04009, JP20K14491, JP20KK0071, JP21H01095, JP21H04493, JP21K03615, JP21K13958, JP21K13963, JP22H00158, JP22H01268, JP22K03624, JP23H00121, JP23H00151, JP23H01211, JP23H04899, JP23K03454, JP23K03459, JP23K13154, JP23K20239, JP23K20850, JP23K22548, JP24H00253, JP24K00638, JP24K00672, JP24K00677, JP24K17093, JP24K17104, and JP24K17105. This work was supported by NASA grant numbers 80NSSC22K1922, 80NSSC18K0978, 80NSSC18K0988, 80NSSC18K1684, 80NSSC20K0733, 80NSSC20K0737, 80NSSC20K0883, 80NSSC23K0650, 80NSSC23K1656, 80NSSC24K0678, 80NSSC24K1148, 80NSSC24K1774. LC acknowledges support from NSF award 2205918. CD acknowledges support from STFC through grant ST/T000244/1. LG acknowledges financial support from Canadian Space Agency grant 18XARMSTMA. NO acknowledges partial support by the Organization for the Promotion of Gender Equality at Nara Women’s University. MS acknowledges the support by the RIKEN Pioneering Project Evolution of Matter in the Universe (r-EMU) and Rikkyo University Special Fund for Research (Rikkyo SFR). AT and the present research are in part supported by the Kagoshima University postdoctoral research program (KU-DREAM). SY acknowledges support by the RIKEN SPDR Program. TY acknowledges support by NASA under award number 80GSFC24M0006. IZ acknowledges partial support from the Alfred P. Sloan Foundation through the Sloan Research Fellowship. SE acknowledges the financial contribution from the contracts Prin-MUR 2022 supported by Next Generation EU (M4.C2.1.1, n.20227RNLY3 The concordance cosmological model: stress-tests with galaxy clusters), ASI-INAF Athena 2019-27-HH.0, “Attività di Studio per la comunità scientifica di Astrofisica delle Alte Energie e Fisica Astroparticellare” (Accordo Attuativo ASI-INAF n. 2017-14- H.0), and from the European Union’s Horizon 2020 Programme under the AHEAD2020 project (grant agreement n. 871158). LL acknowledges the financial contribution from the INAF grant 1.05.12.04.01. YO would like to take this opportunity to thank the “Nagoya University Interdisciplinary Frontier Fellowship” supported by Nagoya University and JST, the establishment of university fellowships towards the creation of science technology innovation, Grant Number JPMJFS2120. Y.O. was supported by the Sasakawa Scientific Research Grant from The Japan Science Societyhttp://arxiv.org/abs/2508.0506
Enabling Edge-Optimized AI Acceleration through Energy-Recycling Clocks and Compute-in-Memory Architectures
No full textEnergy-efficient high-performance computing has been a pivotal factor in driving the microprocessor industry. This rising demand necessitates addressing the immense computational requirements of growing AI advancements while maintaining low energy consumption. This work addresses the significant dynamic power consumption in two critical microprocessor systems: clock architecture and cache architecture. First, we propose a low-power, wideband energy-recycling clock architecture utilizing resonant flip-flops (FFs) with series LC resonance and an inductor tuning technique. This inductor tuning technique reduces clock skew and increases the robustness of the clock networks. Our design saves over 43% power and reduces skew by 90% in clock tree networks, and 44% power with 90% skew reduction in mesh networks, across a 1–5 GHz range, compared to industry-standard primarysecondary FF-based networks. To enhance edge artificial intelligence (AI) computational efficiency, we introduce two Compute-in-Memory (CiM) architectures that minimize costly data transfers between memory and CPU. The first architecture, an energy-recycling resonant 10T Compute-in-Memory SRAM (rCiM) macro, integrates Boolean logic computations within the memory, reducing core-cache data movement. Additionally, this work proposes an automation tool that generates energy and latency-optimized rCiM implementations for given logic circuits and memory constraints. When provided with a combinational circuit, the tool aims to generate an energy-efficient implementation strategy tailored to the specified input memory and latency constraints. An 8KB rCiM evaluated on the EPFL combinational benchmark suite showcased 55.42% average lower energy consumption than standard Von-Neuamnn architectures, achieving 88.2-106.6 GOPS throughput and 8.64-10.45 TOPS/W energy efficiency. The proposed combinational logic operation mapping methodology demonstrates that a three-topology macro strategy further cuts energy by 40.52% compared to single-macro designs. The second architecture is a resonant time-domain CiM (rTD-CiM) for Convolutional Neural Networks (CNNs) that avoids Analog-to-Digital converters (ADCs) by using a low-overhead time-to-digital converter (TDC) to digitize Multiply-Accumulate (MAC) operations, mitigating area, power, and non-linearity issues of traditional ADCs. In addition, a weight stationary data mapping strategy combined with an automated SRAM macro selection algorithm optimizes memory usage for quantized CNNs. Demonstrated across six CNNs and nine SRAM configurations, our algorithm achieves an 87.5% reduction in latency for ResNet-18 when mapped to a 256 KB SRAM macro and improves energy efficiency by 8× over a 32 KB SRAM. The rTD-CiM achieves 320 GOPS throughput and 38.46 TOPS/W on an 8 KB macro
The physiological functions of the Cbp2D and Cbp2E proteins are important for insoluble cellulose-dependent growth in Cellvibrio japonicus
No full textMicrobial deconstruction of plant polysaccharides is important for environmental nutrient cycling, and bacteria proficient at this process have extensive suites of polysaccharide-specific enzymes. In the gram-negative saprophyte Cellvibrio japonicus, genome annotation suggests that 17 genes are predicted to encode Carbohydrate-Active enZymes (CAZymes) with roles in cellulose degradation; however, previous work suggested that only a subset of these genes is essential. Building upon that work, here, we identify the required and minimally sufficient set of enzymes for complete degradation of cellulose using a combination of transcriptomics, gene deletion analysis, heterologous expression studies, and metabolite analysis. We identified six CAZyme-encoding genes required for cellulose deconstruction in C. japonicus, which are cel3B, cel5B, cel6A, lpmo10B, cbp2D, and cbp2E. These genes encode for a β-glucosidase, an endoglucanase, a cellobiohydrolase, a lytic polysaccharide mono-oxygenase, and two carbohydrate-binding proteins, respectively. These CAZyme-encoding genes are essential for growth using insoluble cellulose by C. japonicus and sufficient for using soluble cellulose when heterologously expressed in Escherichia coli. Moreover, during C. japonicus growth using insoluble cellulose, we detected no cellodextrins in the medium, which suggested that cello-oligosaccharide uptake is highly efficient. RNA-seq analysis corroborates these results as we observed several genes significantly upregulated during growth using cellulose that encode TonB-dependent and ABC transporters. Our revised model of cellulose utilization by C. japonicus suggests a greater importance for the Cbp2D and Cbp2E proteins than previously thought and that rapid cellodextrin uptake by C. japonicus is a mechanism to maximize the energetic return on investment for the production and secretion of CAZymes.This work was supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, under award number DE-SC0014183 and the National Science Foundation, Division of Environmental Biology, under award number 2038304.https://journals.asm.org/doi/10.1128/aem.00818-2
Geant4 Simulations of Geometry Factor and Interaction and Energy Losses for TIGERISS
No full text39th International Cosmic Ray Conference (ICRC2025), July 15–24 2025,Geneva, SwitzerlandAuthors list: TIGERISS Collaboration, H. Allen, R. F. Borda, R. G. Bose, D. L. Braun, J. Calderon, Z. Campbell, N. W. Cannady, R. M. Caputo, M. Clark, J. Coldsmith, S. Coutu, G. A. de Nolfo, T. Forstmeier, M. Fratta, P. Ghosh, , S. Graham, J. F. Krizmanic, W. Labrador, L. Lisalda, J. V. Martins, M. P. McPherson, J. G. Mitchell, J. W. Mitchell, S. I. Mognet, A. Moiseev, T. L. Ng, S. Nutter, N. Osborn, M. Pant, I. M. Pastrana, D. Radomski, B. F. Rauch, H. Salmani, M. Sasaki, , G. E. Simburger, S. Smith, H. A. Tolentino, Y. Tufail, D. Washington, T. Widmyer, L. Williams, W. V. ZoberThe Trans-Iron Galactic Element Recorder for the International Space Station (TIGERISS) is an ultra-heavy galactic cosmic ray (UHGCR) detector planned for installation at the Columbus SOX location of the International Space Station (ISS) in 2027. TIGERISS will improve on previous instruments by using silicon strip detectors (SSDs) to achieve greater linearity in signal response over an expanded dynamic range 5B and 82Pb and silicon photomultipliers (SiPMs) for a more compact readout profile and to avoid the need for a high voltage. A Geant4-based instrument simulation has been useful in the design phase and in predicting instrument performance and various measurement corrections. Studies performed include a calculation of the top-of-instrument survival fraction corrections by element and incident angle, ionization energy loss simulations with a specific focus on the energy needed to be above threshold in the acrylic (325 MeV/Nuc) and silica aerogel (2.34 GeV/Nuc) Cherenkov detectors by element and incident angle. Additional studies focus on the instrument geometry factor, accounting for possible obstructions present in the instrument field of view on the ISS, as well as simulations of instrument response to isotopes and energies in preparation for a planned beam test at Brookhaven National Laboratory NASA Space Research Laboratory facility.https://pos.sissa.it/501/063
Aerosol Effective Radiative Forcing Accelerates Earth’s Energy Imbalance In Recent Decades
No full textEarth's energy imbalance (EEI), a key driver of climate change, has risen markedly over the last two decades and continues to accelerate in recent years. Greenhouse gas forcing, aerosol forcing, and cloud feedback all contribute to this increase. However, the role of aerosol forcing, particularly effective radiative forcing through aerosol-cloud interactions (ERF ACI), remains highly uncertain and closely intertwined with cloud feedback. Here we estimate ERF ACI using satellite observations and show it has been an important contributor to the EEI increase over the past two decades. The ERF ACI exhibits a significant warming trend of 0.33 ± 0.03 Wm⁻² averaged over oceans between 60°S and 60°N. The warming trend of (ERF ACI stems from a global decline in cloud droplet number concentration driven by decreasing anthropogenic aerosol emissions. It is similar to the combined instantaneous forcing from greenhouse gases and aerosol-radiation interactions estimated by radiative kernel calculations. Our results can close the gap between simulated and observed EEI trends while implying a weak total cloud feedback. Our findings have important implications for studying decadal changes, cloud feedback, and mitigation.We acknowledge funding support from NASA MEaSUREs and TASNPP programs (grant numbers 80NSSC24K0458, 80NSSC24M0014 and 80NSSC24M0045), NOAA ERB program(grant NA23OAR4310299), and DOE ASR program(grant DE-SC0024078).https://www.researchsquare.com/article/rs-7755051/v
Toward improved property prediction of 2D materials using many-body quantum Monte Carlo methods
No full textThe field of 2D materials has grown dramatically in the past two decades. 2D materials can be utilized for a variety of next-generation optoelectronic, spintronic, clean energy, and quantum computing applications. These 2D structures, which are often exfoliated from layered van der Waals materials, possess highly inhomogeneous electron densities and can possess short- and long-range electron correlations. The complexities of 2D materials make them challenging to study with standard mean-field electronic structure methods such as density functional theory (DFT), which relies on approximations for the unknown exchange-correlation functional. To overcome the limitations of DFT, highly accurate many-body electronic structure approaches such as diffusion Monte Carlo (DMC) can be utilized. In the past decade, DMC has been used to calculate accurate magnetic, electronic, excitonic, and topological properties in addition to accurately capturing interlayer interactions and cohesion and adsorption energetics of 2D materials. This approach has been applied to 2D systems of wide interest, including graphene, phosphorene, MoS₂, CrI₃, VSe₂, GaSe, GeSe, borophene, and several others. In this review article, we highlight some successful recent applications of DMC to 2D systems for improved property predictions beyond standard DFT.This manuscript has been authored by UT-Battelle LLC under contract DE-AC05-00OR22725 with the U.S. Department of Energy (DOE). The U.S. government retains, and the publisher, by accepting the article for publication, acknowledges that the U.S. government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for U.S. government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https:// www.energy.gov/doe-public-access-plan). This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy, Office of Science, under contract number DEAC02-06CH11357. D.W. acknowledges the National Institute of Standards and Technology for funding and support. J.A., A.B., P.R.C.K., J.T.K., L.M., B.R., and H.S. were supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division as part of the Computational Materials Sciences Program and the Center for Predictive Simulation of Functional Materials. L.M. also received support (excitonic effects in 2D) from the U.S. National Science Foundation (Grant No. DMR-2316007). Y.K. was supported by the Basic Science Research Program (Grant No. 2018R1D1A1B07042443) through the National Research Foundation of Korea, funded by the Ministry of Education. I.S. acknowledges the support by APVV-21- 0272, VEGA 2/0133/25, and VEGA 2/0131/23 and by the H2020 TREX GA 952165 projects and Funding by the EU NextGenerationEU through the Recovery and Resilience Plan for Slovakia (Project Nos. 09I02-03-V01-00012 and 09I05-03-V02-00055). K.S. and F.A.R. were supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division. C.A. acknowledges funding from the National Science Foundation (Grant No. NSF DMR-2213398) and the U.S. Department of Energy (Grant No. DE-SC0024236). Please note that certain equipment, instruments, software, or materials are identified in this paper to specify the experimental procedure adequately. Such identification is not intended to imply the recommendation or endorsement of any product or service by the National Institute of Standards and Technology, nor is it intended to imply that the materials or equipment identified is necessarily the best available for the purposehttps://pubs.aip.org/aip/apr/article/12/3/031317/3360256/Toward-improved-property-prediction-of-2
Federated Learning for Internet of Underwater Things Based on Lightweight Distillation and Data Refinement
No full textUnderwater federated learning (UFL) is an emerging technology to realize distributed intelligent collaboration in the Internet of Underwater Things (IoUT), but its application faces two challenges: the limited bandwidth of underwater communication leads to low model transmission efficiency, and the data is characterized by low quality and high heterogeneity due to environmental interference. In this paper, an underwater federated learning framework with dual-path collaborative optimization is proposed to solve the above problems systematically through the joint design of knowledge distillation and data quality enhancement. Specifically, to optimize the transmission efficiency, a knowledge distillation mechanism is designed, and the complex model is compressed into a simplified model suitable for low-bandwidth transmission by using the collaborative distillation of lightweight teacher-student models. To enhance data quality, a supervised data quality enhancement (S-DQE) method is proposed. The integration of traditional methods with deep learning-based approaches optimizes feature representation through the joint application of contrastive learning and adversarial training, thereby effectively addressing the issue of low-quality underwater data. Finally, numerical results are given to compare the final scheme with the initial federated learning scheme, lightweight model scheme, and lightweight-data quality enhancement scheme, clearly demonstrating its performance gains.This work was supported in part by Taishan Scholar Foundation under Grant
tsqnz20230602 and Natural Science Foundation of Shandong Province under
Grant ZR2024MF115.https://ieeexplore.ieee.org/document/1114661