4 research outputs found

    Π£ΡΡ‚ΡŒ-ишимская ΠΊΠΎΡΡ‚ΡŒ: минСралогогСохимичСскиС свойства ΠΊΠ°ΠΊ источник палСонтологичСской, палСоантропологичСской ΠΈ палСоэкологичСской ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ

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    Ust-Ishim man was the representative of one of the ancestral groups of the Homo sapiens, Neanderthals and Denisovans. The first results of a comprehensive mineralogical and geochemical study of fossil bones using a wide range of physical, chemical and physico-chemical methods: thermal analysis, optical microscopy, scanning electron microscopy, atomic-force microscopy, nitrogen capillary condensation method, X-ray fluorescence analysis, ISP-MS, gas chromatography method, amino acid chromatography analysis’s, X-ray microprobe method, X-ray diffraction method, Raman and infrared spectroscopy, isotope spectrometry are presented in this article. The studied fragment of the skeleton is of higher preservation rate than the common bone detritus of this age and even the fossils of younger Pleistocene animals that allowed determining almost all its primary properties. The unique preservation presumably was provided by the favorable environment and a special way the Ust-Ishim man originally was buried. Results of study of the chemical and mineral composition of the bone fossils allowed a reconstruction of the Ust-Ishim man life history.Π’ΠΏΠ΅Ρ€Π²Ρ‹Π΅ ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ΠΎ ΠΌΠΈΠ½Π΅Ρ€Π°Π»ΠΎΠ³ΠΎ-гСохимичСскоС исслСдованиС ископаСмой кости с использованиСм ΡˆΠΈΡ€ΠΎΠΊΠΎΠ³ΠΎ комплСкса физичСских, Ρ„ΠΈΠ·ΠΈΠΊΠΎ-химичСских ΠΈ химичСских ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ²: тСрмичСского Π°Π½Π°Π»ΠΈΠ·Π°, оптичСской, ΡΠΊΠ°Π½ΠΈΡ€ΡƒΡŽΡ‰Π΅ΠΉ элСктронной, ΡΠΊΠ°Π½ΠΈΡ€ΡƒΡŽΡ‰Π΅ΠΉ Π·ΠΎΠ½Π΄ΠΎΠ²ΠΎΠΉ микроскопии, капиллярной кондСнсации Π°Π·ΠΎΡ‚Π°, рСнтгСнфлуорСсцСнтного Π°Π½Π°Π»ΠΈΠ·Π°, ИБП-МБ, Π³Π°Π·ΠΎΠ²ΠΎΠΉ Ρ…Ρ€ΠΎΠΌΠ°Ρ‚ΠΎΠ³Ρ€Π°Ρ„ΠΈΠΈ, Ρ€Π΅Π½Ρ‚Π³Π΅Π½ΠΎΡΠΏΠ΅ΠΊΡ‚Ρ€Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ ΠΌΠΈΠΊΡ€ΠΎΠ·ΠΎΠ½Π΄ΠΎΠ²ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π°, рСнтгСновской Π΄ΠΈΡ„Ρ€Π°ΠΊΡ†ΠΈΠΈ, инфракрасной ΠΈ КР спСктроскопии, ΠΈΠ·ΠΎΡ‚ΠΎΠΏΠ½ΠΎΠΉ спСктромСтрии. Π˜Π·ΡƒΡ‡Π΅Π½Π½Ρ‹ΠΉ Π½Π°ΠΌΠΈ Ρ„Ρ€Π°Π³ΠΌΠ΅Π½Ρ‚ кости ΡƒΡΡ‚ΡŒΠΈΡˆΠΈΠΌΡΠΊΠΎΠ³ΠΎ Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ° Π½Π° Ρ„ΠΎΠ½Π΅ костного Π΄Π΅Ρ‚Ρ€ΠΈΡ‚Π° соврСмСнных Π΅ΠΌΡƒ ΠΈ Π΄Π°ΠΆΠ΅ Π·Π½Π°Ρ‡ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎ Π±ΠΎΠ»Π΅Π΅ ΠΌΠΎΠ»ΠΎΠ΄Ρ‹Ρ… плСйстоцСновых промысловых ΠΆΠΈΠ²ΠΎΡ‚Π½Ρ‹Ρ… характСризуСтся аномально высокой ΡΡ‚Π΅ΠΏΠ΅Π½ΡŒΡŽ сохранности практичСски ΠΏΠΎ всСм своим свойствам. Π€Π΅Π½ΠΎΠΌΠ΅Π½ ΡΡ‚ΠΎΠ»ΡŒ аномальной сохранности ΠΌΠΎΠΆΠ½ΠΎ ΠΎΠ±ΡŠΡΡΠ½ΠΈΡ‚ΡŒ Ρ‚Π΅ΠΌ, Ρ‡Ρ‚ΠΎ ΡƒΡΡ‚ΡŒΠΈΡˆΠΈΠΌΡΠΊΠΈΠΉ Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊ ΠΏΠ΅Ρ€Π²ΠΎΠ½Π°Ρ‡Π°Π»ΡŒΠ½ΠΎ Π±Ρ‹Π» Π·Π°Ρ…ΠΎΡ€ΠΎΠ½Π΅Π½ Π»ΠΈΠ±ΠΎ Π² особом мСстС, Π»ΠΈΠ±ΠΎ особСнным способом

    The MIGDAL experiment: measuring a rare atomic process to aid the search for dark matter

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    We present the Migdal In Galactic Dark mAtter expLoration (MIGDAL) experiment aiming at the unambiguous observation and study of the so-called Migdal effect induced by fast-neutron scattering. It is hoped that this elusive atomic process can be exploited to enhance the reach of direct dark matter search experiments to lower masses, but it is still lacking experimental confirmation. Our goal is to detect the predicted atomic electron emission which is thought to accompany nuclear scattering with low, but calculable, probability, by deploying an Optical Time Projection Chamber filled with a low-pressure gas based on CF4. Initially, pure CF4 will be used, and then in mixtures containing other elements employed by leading dark matter search technologies β€” including noble species, plus Si and Ge. High resolution track images generated by a Gas Electron Multiplier stack, together with timing information from scintillation and ionisation readout, will be used for 3D reconstruction of the characteristic event topology expected for this process β€” an arrangement of two tracks sharing a common vertex, with one belonging to a Migdal electron and the other to a nuclear recoil. Different energy-loss rate distributions along both tracks will be used as a powerful discrimination tool against background events. In this article we present the design of the experiment, informed by extensive particle and track simulations and detailed estimations of signal and background rates. In pure CF4 we expect to observe 8.9 (29.3) Migdal events per calendar day of exposure to an intense D–D (D–T) neutron generator beam at the NILE facility located at the Rutherford Appleton Laboratory (UK). With our nominal assumptions, 5Οƒ median discovery significance can be achieved in under one day with either generator

    The MIGDAL experiment : Measuring a rare atomic process to aid the search for dark matter

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    We present the Migdal In Galactic Dark mAtter expLoration (MIGDAL) experiment aiming at the unambiguous observation and study of the so-called Migdal effect induced by fast-neutron scattering. It is hoped that this elusive atomic process can be exploited to enhance the reach of direct dark matter search experiments to lower masses, but it is still lacking experimental confirmation. Our goal is to detect the predicted atomic electron emission which is thought to accompany nuclear scattering with low, but calculable, probability, by deploying an Optical Time Projection Chamber filled with a low-pressure gas based on CF. Initially, pure CF will be used, and then in mixtures containing other elements employed by leading dark matter search technologies β€” including noble species, plus Si and Ge. High resolution track images generated by a Gas Electron Multiplier stack, together with timing information from scintillation and ionisation readout, will be used for 3D reconstruction of the characteristic event topology expected for this process β€” an arrangement of two tracks sharing a common vertex, with one belonging to a Migdal electron and the other to a nuclear recoil. Different energy-loss rate distributions along both tracks will be used as a powerful discrimination tool against background events. In this article we present the design of the experiment, informed by extensive particle and track simulations and detailed estimations of signal and background rates. In pure CF we expect to observe 8.9 (29.3) Migdal events per calendar day of exposure to an intense D–D (D–T) neutron generator beam at the NILE facility located at the Rutherford Appleton Laboratory (UK). With our nominal assumptions, 5 median discovery significance can be achieved in under one day with either generator.Peer reviewe

    Transforming a rare event search into a not-so-rare event search in real-time with deep learning-based object detection

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    Deep learning-based object detection algorithms enable the simultaneous classification and localization of any number of objects in image data. Many of these algorithms are capable of operating in real-time on high resolution images, attributing to their widespread usage across many fields. We present an end-to-end object detection pipeline designed for real-time rare event searches for the Migdal effect, using high-resolution image data from a state-of-the-art scientific CMOS camera in the MIGDAL experiment. The Migdal effect in nuclear scattering, crucial for sub-GeV dark matter searches, has yet to be experimentally confirmed, making its detection a primary goal of the MIGDAL experiment. Our pipeline employs the YOLOv8 object detection algorithm and is trained on real data to enhance the detection efficiency of nuclear and electronic recoils, particularly those exhibiting overlapping tracks that are indicative of the Migdal effect. When deployed online on the MIGDAL readout PC, we demonstrate our pipeline to process and perform the rare event search on 2D image data faster than the peak 120 frame per second acquisition rate of the CMOS camera. Applying these same steps offline, we demonstrate that we can reduce a sample of 20 million camera frames to around 1000 frames while maintaining nearly all signal that YOLOv8 is able to detect, thereby transforming a rare search into a much more manageable search. Our studies highlight the potential of pipelines similar to ours significantly improving the detection capabilities of experiments requiring rapid and precise object identification in high-throughput data environments
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