Martin Ravn, Christian Glaser, Thorsten Glüsenkamp, Alan Coleman
Ultra-high-energy neutrinos and cosmic rays are excellent probes of astroparticle physics phenomena. For astroparticle physics analyses, robust and accurate reconstruction of signal parameters like arrival direction and energy is essential. Current reconstruction methods ignore bin-to-bin noise correlations, which limits reconstruction resolution and so far has prevented calculations of event-by-event uncertainties. In this work, we present a likelihood description of neutrino or cosmic-ray signals in a radio detector with correlated noise, as present in all neutrino and cosmic-ray radio detectors. We demonstrate with a toy-model reconstruction that signal parameters such as energy and direction, including event-by-event uncertainties with correct coverage, can be obtained. Additionally, by correctly accounting for correlations, the likelihood description constrains the best-fit parameters better than alternative methods and thus improves experimental reconstruction capabilities.
{"title":"Likelihood reconstruction of radio signals of neutrinos and cosmic rays","authors":"Martin Ravn, Christian Glaser, Thorsten Glüsenkamp, Alan Coleman","doi":"arxiv-2409.11888","DOIUrl":"https://doi.org/arxiv-2409.11888","url":null,"abstract":"Ultra-high-energy neutrinos and cosmic rays are excellent probes of\u0000astroparticle physics phenomena. For astroparticle physics analyses, robust and\u0000accurate reconstruction of signal parameters like arrival direction and energy\u0000is essential. Current reconstruction methods ignore bin-to-bin noise\u0000correlations, which limits reconstruction resolution and so far has prevented\u0000calculations of event-by-event uncertainties. In this work, we present a\u0000likelihood description of neutrino or cosmic-ray signals in a radio detector\u0000with correlated noise, as present in all neutrino and cosmic-ray radio\u0000detectors. We demonstrate with a toy-model reconstruction that signal\u0000parameters such as energy and direction, including event-by-event uncertainties\u0000with correct coverage, can be obtained. Additionally, by correctly accounting\u0000for correlations, the likelihood description constrains the best-fit parameters\u0000better than alternative methods and thus improves experimental reconstruction\u0000capabilities.","PeriodicalId":501163,"journal":{"name":"arXiv - PHYS - Instrumentation and Methods for Astrophysics","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Li Wang, O. Ivy Wong, Tobias Westmeier, Chandrashekar Murugeshan, Karen Lee-Waddell, Yuanzhi. Cai, Xiu. Liu, Austin Xiaofan Shen, Jonghwan Rhee, Helga Dénes, Nathan Deg, Peter Kamphuis
The data volumes generated by the WALLABY atomic Hydrogen (HI) survey using the Australiian Square Kilometre Array Pathfinder (ASKAP) necessitate greater automation and reliable automation in the task of source-finding and cataloguing. To this end, we introduce and explore a novel deep learning framework for detecting low Signal-to-Noise Ratio (SNR) HI sources in an automated fashion. Specfically, our proposed method provides an automated process for separating true HI detections from false positives when used in combination with the Source Finding Application (SoFiA) output candidate catalogues. Leveraging the spatial and depth capabilities of 3D Convolutional Neural Networks (CNNs), our method is specifically designed to recognise patterns and features in three-dimensional space, making it uniquely suited for rejecting false positive sources in low SNR scenarios generated by conventional linear methods. As a result, our approach is significantly more accurate in source detection and results in considerably fewer false detections compared to previous linear statistics-based source finding algorithms. Performance tests using mock galaxies injected into real ASKAP data cubes reveal our method's capability to achieve near-100% completeness and reliability at a relatively low integrated SNR~3-5. An at-scale version of this tool will greatly maximise the science output from the upcoming widefield HI surveys.
利用澳大利亚平方公里阵列探路者（ASKAP）进行的瓦拉比原子氢（HI）探测所产生的数据量要求在寻找源和编目任务中实现更高的自动化和可靠的自动化。为此，我们引入并探索了一种新型深度学习框架，用于以自动化方式检测低信噪比（SNR）HI 信号源。具体来说，我们提出的方法提供了一个自动流程，用于将真正的 HI 检测从假阳性中分离出来，并与信号源查找应用程序（SoFiA）输出的候选目录结合使用。利用三维卷积神经网络（CNN）的空间和深度能力，我们的方法专门设计用于识别三维空间中的模式和特征，因此非常适合在传统线性方法产生的低信噪比情况下剔除假阳性信号源。因此，与以前基于线性统计的源探测算法相比，我们的方法在源探测方面要准确得多，误探测也少得多。利用注入真实ASKAP数据立方体的模拟星系进行的性能测试表明，我们的方法能够在相对较低的综合信噪比（SNR）~3-5的条件下实现接近100%的完整性和可靠性。这一工具的大规模版本将大大提高即将开展的宽视场高频探测的科学产出。
{"title":"WALLABY Pilot Survey: HI source-finding with a machine learning framework","authors":"Li Wang, O. Ivy Wong, Tobias Westmeier, Chandrashekar Murugeshan, Karen Lee-Waddell, Yuanzhi. Cai, Xiu. Liu, Austin Xiaofan Shen, Jonghwan Rhee, Helga Dénes, Nathan Deg, Peter Kamphuis","doi":"arxiv-2409.11668","DOIUrl":"https://doi.org/arxiv-2409.11668","url":null,"abstract":"The data volumes generated by the WALLABY atomic Hydrogen (HI) survey using\u0000the Australiian Square Kilometre Array Pathfinder (ASKAP) necessitate greater\u0000automation and reliable automation in the task of source-finding and\u0000cataloguing. To this end, we introduce and explore a novel deep learning\u0000framework for detecting low Signal-to-Noise Ratio (SNR) HI sources in an\u0000automated fashion. Specfically, our proposed method provides an automated\u0000process for separating true HI detections from false positives when used in\u0000combination with the Source Finding Application (SoFiA) output candidate\u0000catalogues. Leveraging the spatial and depth capabilities of 3D Convolutional\u0000Neural Networks (CNNs), our method is specifically designed to recognise\u0000patterns and features in three-dimensional space, making it uniquely suited for\u0000rejecting false positive sources in low SNR scenarios generated by conventional\u0000linear methods. As a result, our approach is significantly more accurate in\u0000source detection and results in considerably fewer false detections compared to\u0000previous linear statistics-based source finding algorithms. Performance tests\u0000using mock galaxies injected into real ASKAP data cubes reveal our method's\u0000capability to achieve near-100% completeness and reliability at a relatively\u0000low integrated SNR~3-5. An at-scale version of this tool will greatly maximise\u0000the science output from the upcoming widefield HI surveys.","PeriodicalId":501163,"journal":{"name":"arXiv - PHYS - Instrumentation and Methods for Astrophysics","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alina Sabyr, Carlos Sierra, J. Colin Hill, Jeffrey J. McMahon
Deviations of the cosmic microwave background (CMB) energy spectrum from a perfect blackbody uniquely probe a wide range of physics, ranging from fundamental physics in the primordial Universe ($mu$-distortion) to late-time baryonic feedback processes (y-distortion). While the y-distortion can be detected with a moderate increase in sensitivity over that of COBE/FIRAS, the $Lambda$CDM-predicted $mu$-distortion is roughly two orders of magnitude smaller and requires substantial improvements, with foregrounds presenting a serious obstacle. Within the standard model, the dominant contribution to $mu$ arises from energy injected via Silk damping, yielding sensitivity to the primordial power spectrum at wavenumbers $k approx 1-10^{4}$ Mpc$^{-1}$. Here, we present a new instrument concept, SPECTER, with the goal of robustly detecting $mu$. The instrument technology is similar to that of LiteBIRD, but with an absolute temperature calibration system. Using a Fisher approach, we optimize the instrument's configuration to target $mu$ while robustly marginalizing over foreground contaminants. Unlike Fourier-transform-spectrometer-based designs, the specific bands and their individual sensitivities can be independently set in this instrument, allowing significant flexibility. We forecast SPECTER to observe the $Lambda$CDM-predicted $mu$-distortion at $approx 5sigma$ (10$sigma$) assuming an observation time of 1 (4) year(s) (corresponding to mission duration of 2 (8) years), after foreground marginalization. Our optimized configuration includes 16 bands spanning 1-2000 GHz with degree-scale angular resolution at 150 GHz and 1046 total detectors. SPECTER will additionally measure the y-distortion at sub-percent precision and its relativistic correction at percent-level precision, yielding tight constraints on the total thermal energy and mean temperature of ionized gas.
{"title":"SPECTER: An Instrument Concept for CMB Spectral Distortion Measurements with Enhanced Sensitivity","authors":"Alina Sabyr, Carlos Sierra, J. Colin Hill, Jeffrey J. McMahon","doi":"arxiv-2409.12188","DOIUrl":"https://doi.org/arxiv-2409.12188","url":null,"abstract":"Deviations of the cosmic microwave background (CMB) energy spectrum from a\u0000perfect blackbody uniquely probe a wide range of physics, ranging from\u0000fundamental physics in the primordial Universe ($mu$-distortion) to late-time\u0000baryonic feedback processes (y-distortion). While the y-distortion can be\u0000detected with a moderate increase in sensitivity over that of COBE/FIRAS, the\u0000$Lambda$CDM-predicted $mu$-distortion is roughly two orders of magnitude\u0000smaller and requires substantial improvements, with foregrounds presenting a\u0000serious obstacle. Within the standard model, the dominant contribution to $mu$\u0000arises from energy injected via Silk damping, yielding sensitivity to the\u0000primordial power spectrum at wavenumbers $k approx 1-10^{4}$ Mpc$^{-1}$. Here,\u0000we present a new instrument concept, SPECTER, with the goal of robustly\u0000detecting $mu$. The instrument technology is similar to that of LiteBIRD, but\u0000with an absolute temperature calibration system. Using a Fisher approach, we\u0000optimize the instrument's configuration to target $mu$ while robustly\u0000marginalizing over foreground contaminants. Unlike\u0000Fourier-transform-spectrometer-based designs, the specific bands and their\u0000individual sensitivities can be independently set in this instrument, allowing\u0000significant flexibility. We forecast SPECTER to observe the\u0000$Lambda$CDM-predicted $mu$-distortion at $approx 5sigma$ (10$sigma$)\u0000assuming an observation time of 1 (4) year(s) (corresponding to mission\u0000duration of 2 (8) years), after foreground marginalization. Our optimized\u0000configuration includes 16 bands spanning 1-2000 GHz with degree-scale angular\u0000resolution at 150 GHz and 1046 total detectors. SPECTER will additionally\u0000measure the y-distortion at sub-percent precision and its relativistic\u0000correction at percent-level precision, yielding tight constraints on the total\u0000thermal energy and mean temperature of ionized gas.","PeriodicalId":501163,"journal":{"name":"arXiv - PHYS - Instrumentation and Methods for Astrophysics","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chenxi ShanSchool of Physics and Astronomy, Shanghai Jiao Tong University, Haiguang XuSchool of Physics and Astronomy, Shanghai Jiao Tong University, Yongkai ZhuSchool of Physics and Astronomy, Shanghai Jiao Tong University, Yuanyuan ZhaoSchool of Physics and Astronomy, Shanghai Jiao Tong University, Sarah V. WhiteDepartment of Physics and Electronics, Rhodes University, Jack L. B. LineInternational Centre for Radio Astronomy Research, Curtin UniversityARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions, Dongchao ZhengSchool of Physics and Astronomy, Shanghai Jiao Tong University, Zhenghao ZhuShanghai Astronomical Observatory, Chinese Academy of Sciences, Dan HuDepartment of Theoretical Physics and Astrophysics, Faculty of Science, Masaryk University, Zhongli ZhangShanghai Astronomical Observatory, Chinese Academy of SciencesKey Laboratory of Radio Astronomy and Technology, Chinese Academy of Sciences, Xiangping WuNational Astronomical Observatories, Chinese Academy of Sciences
Twenty-one-centimetre signals from the Epoch of Reionization (EoR) are expected to be detected in the low-frequency radio window by the next-generation interferometers, particularly the Square Kilometre Array (SKA). However, precision data analysis pipelines are required to minimize the systematics within an infinitesimal error budget. Consequently, there is a growing need to characterize the sources of errors in EoR analysis. In this study, we identify one such error origin, namely source blending, which is introduced by the overlap of objects in the densely populated observing sky under SKA1-Low's unprecedented sensitivity and resolution, and evaluate its two-fold impact in both the spatial and frequency domains using a novel hybrid evaluation (HEVAL) pipeline combining end-to-end simulation with an analytic method to mimic EoR analysis pipelines. Sky models corrupted by source blending induce small but severe frequency-dependent calibration errors when coupled with astronomical foregrounds, impeding EoR parameter inference with strong additive residuals in the two-dimensional power spectrum space. We report that additive residuals from poor calibration against sky models with blending ratios of 5 and 0.5 per cent significantly contaminate the EoR window. In contrast, the sky model with a 0.05 per cent blending ratio leaves little residual imprint within the EoR window, therefore identifying a blending tolerance at approximately 0.05 per cent. Given that the SKA observing sky is estimated to suffer from an extended level of blending, strategies involving de-blending, frequency-dependent error mitigation, or a combination of both, are required to effectively attenuate the calibration impact of source-blending defects.
{"title":"An evaluation of source-blending impact on the calibration of SKA EoR experiments","authors":"Chenxi ShanSchool of Physics and Astronomy, Shanghai Jiao Tong University, Haiguang XuSchool of Physics and Astronomy, Shanghai Jiao Tong University, Yongkai ZhuSchool of Physics and Astronomy, Shanghai Jiao Tong University, Yuanyuan ZhaoSchool of Physics and Astronomy, Shanghai Jiao Tong University, Sarah V. WhiteDepartment of Physics and Electronics, Rhodes University, Jack L. B. LineInternational Centre for Radio Astronomy Research, Curtin UniversityARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions, Dongchao ZhengSchool of Physics and Astronomy, Shanghai Jiao Tong University, Zhenghao ZhuShanghai Astronomical Observatory, Chinese Academy of Sciences, Dan HuDepartment of Theoretical Physics and Astrophysics, Faculty of Science, Masaryk University, Zhongli ZhangShanghai Astronomical Observatory, Chinese Academy of SciencesKey Laboratory of Radio Astronomy and Technology, Chinese Academy of Sciences, Xiangping WuNational Astronomical Observatories, Chinese Academy of Sciences","doi":"arxiv-2409.11691","DOIUrl":"https://doi.org/arxiv-2409.11691","url":null,"abstract":"Twenty-one-centimetre signals from the Epoch of Reionization (EoR) are\u0000expected to be detected in the low-frequency radio window by the\u0000next-generation interferometers, particularly the Square Kilometre Array (SKA).\u0000However, precision data analysis pipelines are required to minimize the\u0000systematics within an infinitesimal error budget. Consequently, there is a\u0000growing need to characterize the sources of errors in EoR analysis. In this\u0000study, we identify one such error origin, namely source blending, which is\u0000introduced by the overlap of objects in the densely populated observing sky\u0000under SKA1-Low's unprecedented sensitivity and resolution, and evaluate its\u0000two-fold impact in both the spatial and frequency domains using a novel hybrid\u0000evaluation (HEVAL) pipeline combining end-to-end simulation with an analytic\u0000method to mimic EoR analysis pipelines. Sky models corrupted by source blending\u0000induce small but severe frequency-dependent calibration errors when coupled\u0000with astronomical foregrounds, impeding EoR parameter inference with strong\u0000additive residuals in the two-dimensional power spectrum space. We report that\u0000additive residuals from poor calibration against sky models with blending\u0000ratios of 5 and 0.5 per cent significantly contaminate the EoR window. In\u0000contrast, the sky model with a 0.05 per cent blending ratio leaves little\u0000residual imprint within the EoR window, therefore identifying a blending\u0000tolerance at approximately 0.05 per cent. Given that the SKA observing sky is\u0000estimated to suffer from an extended level of blending, strategies involving\u0000de-blending, frequency-dependent error mitigation, or a combination of both,\u0000are required to effectively attenuate the calibration impact of source-blending\u0000defects.","PeriodicalId":501163,"journal":{"name":"arXiv - PHYS - Instrumentation and Methods for Astrophysics","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. G. Bassa, F. Di Vruno, B. Winkel, G. I. G. Jozsa, M. A. Brentjens, X. Zhang
We report on the detection of unintended electromagnetic radiation (UEMR) from the second-generation of Starlink satellites. Observations with the LOFAR radio telescope between 10 to 88MHz and 110 to 188MHz show broadband emission covering the frequency ranges from 40 to 70MHz and 110 to 188MHz from the v2-Mini and v2-Mini Direct-to-Cell Starlink satellites. The spectral power flux density of this broadband UEMR varies from satellite to satellite, with values ranging from 15Jy to 1300Jy, between 56 and 66MHz, and from 2 to 100Jy over two distinct 8MHz frequency ranges centered at 120 and 161MHz. We compared the detected power flux densities of this UEMR to that emitted by the first generation v1.0 and v1.5 Starlink satellites. When correcting for the observed satellite distances, we find that the second-generation satellites emit UEMR that is up to a factor of 32 stronger compared to the first generation. The calculated electric field strengths of the detected UEMR exceed typical electromagnetic compatibility standards used for commercial electronic devices as well as recommended emission thresholds from the Radiocommunication Sector of the International Telecommunications Union (ITU-R) aimed at protecting the 150.05-153MHz frequency range allocated to radio astronomy. We characterize the properties of the detected UEMR with the aim of assisting the satellite operator with the identification of the cause of the UEMR.
{"title":"Bright unintended electromagnetic radiation from second-generation Starlink satellites","authors":"C. G. Bassa, F. Di Vruno, B. Winkel, G. I. G. Jozsa, M. A. Brentjens, X. Zhang","doi":"arxiv-2409.11767","DOIUrl":"https://doi.org/arxiv-2409.11767","url":null,"abstract":"We report on the detection of unintended electromagnetic radiation (UEMR)\u0000from the second-generation of Starlink satellites. Observations with the LOFAR\u0000radio telescope between 10 to 88MHz and 110 to 188MHz show broadband emission\u0000covering the frequency ranges from 40 to 70MHz and 110 to 188MHz from the\u0000v2-Mini and v2-Mini Direct-to-Cell Starlink satellites. The spectral power flux\u0000density of this broadband UEMR varies from satellite to satellite, with values\u0000ranging from 15Jy to 1300Jy, between 56 and 66MHz, and from 2 to 100Jy over two\u0000distinct 8MHz frequency ranges centered at 120 and 161MHz. We compared the\u0000detected power flux densities of this UEMR to that emitted by the first\u0000generation v1.0 and v1.5 Starlink satellites. When correcting for the observed\u0000satellite distances, we find that the second-generation satellites emit UEMR\u0000that is up to a factor of 32 stronger compared to the first generation. The\u0000calculated electric field strengths of the detected UEMR exceed typical\u0000electromagnetic compatibility standards used for commercial electronic devices\u0000as well as recommended emission thresholds from the Radiocommunication Sector\u0000of the International Telecommunications Union (ITU-R) aimed at protecting the\u0000150.05-153MHz frequency range allocated to radio astronomy. We characterize the\u0000properties of the detected UEMR with the aim of assisting the satellite\u0000operator with the identification of the cause of the UEMR.","PeriodicalId":501163,"journal":{"name":"arXiv - PHYS - Instrumentation and Methods for Astrophysics","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christopher Cox, Jakob Haynes, Christopher Duffey, Christopher Bennett, Julie Brisset
The understanding of the formation and evolution of the solar system still has many unanswered questions. Formation of solids in the solar system, mineral and organic mixing, and planetary body creation are all topics of interest to the community. Studying these phenomena is often performed through observations, remote sensing, and in-situ analysis, but there are limitations to the methods. Limitations such as IR diffraction limits, spatial resolution issues, and spectral resolution issues can prevent detection of organics, detection and identification of cellular structures, and the disentangling of granular mixtures. Optical-PhotoThermal InfraRed (O-PTIR) spectroscopy is a relatively new method of spectroscopy currently used in fields other than planetary sciences. O-PTIR is a non-destructive, highly repeatable, and fast form of measurement capable of reducing these limitations. Using a dual laser system with an IR source tuned to the mid-IR wavelength we performed laboratory O-PTIR measurements to compare O-PTIR data to existing IR absorption data and laboratory FTIR measurements for planetary materials. We do this for the purpose of introducing O-PTIR to the planetary science community. The technique featured here would serve to better measurements of planetary bodies during in-situ analysis. We find that, unlike other fields where O-PTIR produces almost one-to-one measurements with IR absorption measurements of the same material, granular materials relevant to planetary science do not. However, we do find that the materials compared were significantly close and O-PTIR was still capable of identifying materials relevant to planetary science.
{"title":"Photothermal Spectroscopy for Planetary Sciences: Mid-IR Absorption Made Easy","authors":"Christopher Cox, Jakob Haynes, Christopher Duffey, Christopher Bennett, Julie Brisset","doi":"arxiv-2409.11626","DOIUrl":"https://doi.org/arxiv-2409.11626","url":null,"abstract":"The understanding of the formation and evolution of the solar system still\u0000has many unanswered questions. Formation of solids in the solar system, mineral\u0000and organic mixing, and planetary body creation are all topics of interest to\u0000the community. Studying these phenomena is often performed through\u0000observations, remote sensing, and in-situ analysis, but there are limitations\u0000to the methods. Limitations such as IR diffraction limits, spatial resolution\u0000issues, and spectral resolution issues can prevent detection of organics,\u0000detection and identification of cellular structures, and the disentangling of\u0000granular mixtures. Optical-PhotoThermal InfraRed (O-PTIR) spectroscopy is a\u0000relatively new method of spectroscopy currently used in fields other than\u0000planetary sciences. O-PTIR is a non-destructive, highly repeatable, and fast\u0000form of measurement capable of reducing these limitations. Using a dual laser\u0000system with an IR source tuned to the mid-IR wavelength we performed laboratory\u0000O-PTIR measurements to compare O-PTIR data to existing IR absorption data and\u0000laboratory FTIR measurements for planetary materials. We do this for the\u0000purpose of introducing O-PTIR to the planetary science community. The technique\u0000featured here would serve to better measurements of planetary bodies during\u0000in-situ analysis. We find that, unlike other fields where O-PTIR produces\u0000almost one-to-one measurements with IR absorption measurements of the same\u0000material, granular materials relevant to planetary science do not. However, we\u0000do find that the materials compared were significantly close and O-PTIR was\u0000still capable of identifying materials relevant to planetary science.","PeriodicalId":501163,"journal":{"name":"arXiv - PHYS - Instrumentation and Methods for Astrophysics","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We review the advantages of fitting with a Two Component Advective Flow (TCAF) which uses only four physical parameters. We then present the results of hydrodynamic simulations to highlight the fact that the primary component of a black hole accretion remains the sub-Keplerian or the low angular momentum flow independent of whether we have a high, intermediate or low mass X-ray binary. Every aspect of spectral and timing properties, including the disk-jet connection could be understood well only if such a component is present along with a Keplerian component of variable size and accretion rate.
{"title":"Black Hole Accretion is all about Sub-Keplerian Flows","authors":"Sandip Kumar Chakrabarti","doi":"arxiv-2409.11994","DOIUrl":"https://doi.org/arxiv-2409.11994","url":null,"abstract":"We review the advantages of fitting with a Two Component Advective Flow\u0000(TCAF) which uses only four physical parameters. We then present the results of\u0000hydrodynamic simulations to highlight the fact that the primary component of a\u0000black hole accretion remains the sub-Keplerian or the low angular momentum flow\u0000independent of whether we have a high, intermediate or low mass X-ray binary.\u0000Every aspect of spectral and timing properties, including the disk-jet\u0000connection could be understood well only if such a component is present along\u0000with a Keplerian component of variable size and accretion rate.","PeriodicalId":501163,"journal":{"name":"arXiv - PHYS - Instrumentation and Methods for Astrophysics","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We introduce adaptive particle refinement for compressible smoothed particle hydrodynamics (SPH). SPH calculations have the natural advantage that resolution follows mass, but this is not always optimal. Our implementation allows the user to specify local regions of the simulation that can be more highly resolved. We test our implementation on practical applications including a circumbinary disc, a planet embedded in a disc and a flyby. By comparing with equivalent globally high resolution calculations we show that our method is accurate and fast, with errors in the mass accreted onto sinks of less than 9 percent and speed ups of 1.07-6.62 times for the examples shown. Our method is adaptable and easily extendable, for example with multiple refinement regions or derefinement.
{"title":"Adaptive particle refinement for compressible smoothed particle hydrodynamics","authors":"Rebecca Nealon, Daniel Price","doi":"arxiv-2409.11470","DOIUrl":"https://doi.org/arxiv-2409.11470","url":null,"abstract":"We introduce adaptive particle refinement for compressible smoothed particle\u0000hydrodynamics (SPH). SPH calculations have the natural advantage that\u0000resolution follows mass, but this is not always optimal. Our implementation\u0000allows the user to specify local regions of the simulation that can be more\u0000highly resolved. We test our implementation on practical applications including\u0000a circumbinary disc, a planet embedded in a disc and a flyby. By comparing with\u0000equivalent globally high resolution calculations we show that our method is\u0000accurate and fast, with errors in the mass accreted onto sinks of less than 9\u0000percent and speed ups of 1.07-6.62 times for the examples shown. Our method is\u0000adaptable and easily extendable, for example with multiple refinement regions\u0000or derefinement.","PeriodicalId":501163,"journal":{"name":"arXiv - PHYS - Instrumentation and Methods for Astrophysics","volume":"85 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Lastufka, M. Drozdova, V. Kinakh, S. Voloshynovskyy
Vision foundation models, which have demonstrated significant potential in many multimedia applications, are often underutilized in the natural sciences. This is primarily due to mismatches between the nature of domain-specific scientific data and the typical training data used for foundation models, leading to distribution shifts. Scientific data often differ substantially in structure and characteristics; researchers frequently face the challenge of optimizing model performance with limited labeled data of only a few hundred or thousand images. To adapt foundation models effectively requires customized approaches in preprocessing, data augmentation, and training techniques. Additionally, each vision foundation model exhibits unique strengths and limitations, influenced by differences in architecture, training procedures, and the datasets used for training. In this work, we evaluate the application of various vision foundation models to astrophysics data, specifically images from optical and radio astronomy. Our results show that using features extracted by specific foundation models improves the classification accuracy of optical galaxy images compared to conventional supervised training. Similarly, these models achieve equivalent or better performance in object detection tasks with radio images. However, their performance in classifying radio galaxy images is generally poor and often inferior to traditional supervised training results. These findings suggest that selecting suitable vision foundation models for astrophysics applications requires careful consideration of the model characteristics and alignment with the specific requirements of the downstream tasks.
{"title":"Vision foundation models: can they be applied to astrophysics data?","authors":"E. Lastufka, M. Drozdova, V. Kinakh, S. Voloshynovskyy","doi":"arxiv-2409.11175","DOIUrl":"https://doi.org/arxiv-2409.11175","url":null,"abstract":"Vision foundation models, which have demonstrated significant potential in\u0000many multimedia applications, are often underutilized in the natural sciences.\u0000This is primarily due to mismatches between the nature of domain-specific\u0000scientific data and the typical training data used for foundation models,\u0000leading to distribution shifts. Scientific data often differ substantially in\u0000structure and characteristics; researchers frequently face the challenge of\u0000optimizing model performance with limited labeled data of only a few hundred or\u0000thousand images. To adapt foundation models effectively requires customized\u0000approaches in preprocessing, data augmentation, and training techniques.\u0000Additionally, each vision foundation model exhibits unique strengths and\u0000limitations, influenced by differences in architecture, training procedures,\u0000and the datasets used for training. In this work, we evaluate the application\u0000of various vision foundation models to astrophysics data, specifically images\u0000from optical and radio astronomy. Our results show that using features\u0000extracted by specific foundation models improves the classification accuracy of\u0000optical galaxy images compared to conventional supervised training. Similarly,\u0000these models achieve equivalent or better performance in object detection tasks\u0000with radio images. However, their performance in classifying radio galaxy\u0000images is generally poor and often inferior to traditional supervised training\u0000results. These findings suggest that selecting suitable vision foundation\u0000models for astrophysics applications requires careful consideration of the\u0000model characteristics and alignment with the specific requirements of the\u0000downstream tasks.","PeriodicalId":501163,"journal":{"name":"arXiv - PHYS - Instrumentation and Methods for Astrophysics","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jérémy Lebreton, Roland Brochard, Nicolas Ollagnier, Matthieu Baudry, Adrien Hadj Salah, Grégory Jonniaux, Keyvan Kanani, Matthieu Le Goff, Aurore Masson
Autonomous precision navigation to land onto the Moon relies on vision sensors. Computer vision algorithms are designed, trained and tested using synthetic simulations. High quality terrain models have been produced by Moon orbiters developed by several nations, with resolutions ranging from tens or hundreds of meters globally down to few meters locally. The SurRender software is a powerful simulator able to exploit the full potential of these datasets in raytracing. New interfaces include tools to fuse multi-resolution DEMs and procedural texture generation. A global model of the Moon at 20m resolution was integrated representing several terabytes of data which SurRender can render continuously and in real-time. This simulator will be a precious asset for the development of future missions.
登陆月球的自主精确导航依赖于视觉传感器。计算机视觉算法的设计、训练和测试都是通过合成模拟完成的。多个国家开发的月球轨道器已经生成了高质量的地形模型，其分辨率从全球的几十米或几百米到局部的几米不等。SurRender 软件是一个功能强大的模拟器，能够充分挖掘这些数据集在光线跟踪方面的潜力。新的界面包括融合多分辨率 DEM 和程序化纹理生成工具。一个 20 米分辨率的月球全球模型被整合在一起，代表了数 TB 的数据，SurRender 可以对这些数据进行连续和实时的渲染。该模拟器将成为未来任务开发的宝贵财富。
{"title":"High performance Lunar landing simulations","authors":"Jérémy Lebreton, Roland Brochard, Nicolas Ollagnier, Matthieu Baudry, Adrien Hadj Salah, Grégory Jonniaux, Keyvan Kanani, Matthieu Le Goff, Aurore Masson","doi":"arxiv-2409.11450","DOIUrl":"https://doi.org/arxiv-2409.11450","url":null,"abstract":"Autonomous precision navigation to land onto the Moon relies on vision\u0000sensors. Computer vision algorithms are designed, trained and tested using\u0000synthetic simulations. High quality terrain models have been produced by Moon\u0000orbiters developed by several nations, with resolutions ranging from tens or\u0000hundreds of meters globally down to few meters locally. The SurRender software\u0000is a powerful simulator able to exploit the full potential of these datasets in\u0000raytracing. New interfaces include tools to fuse multi-resolution DEMs and\u0000procedural texture generation. A global model of the Moon at 20m resolution was\u0000integrated representing several terabytes of data which SurRender can render\u0000continuously and in real-time. This simulator will be a precious asset for the\u0000development of future missions.","PeriodicalId":501163,"journal":{"name":"arXiv - PHYS - Instrumentation and Methods for Astrophysics","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142260557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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