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Correlation Between UAV Multispectral Imagery and Spectroradiometer Measurements in Sunflower Developmental Stages
No full textOilseed crops are among the product groups with a supply deficit in the world. The sunflower oil crisis experienced after 2020 ha increased the importance of sunflower cultivation. The most important stages in agricultural applications are to understand whether the plant is healthy in the early stages before it is formed and to prevent negative results in harvest. With the developing technology, the use of unmanned aerial vehicles (UAVs) and multispectral cameras in agricultural applications has gained enormous importance. Thanks to UAVs, agricultural temporal resolution can be adjusted according to the user's request, and spatial resolution can be adjusted according to the ability of the sensor used and the flight altitude. Spectral resolution is directly proportional to the number of bands and the band wavelength. We performed correlation analysis in this study by comparing the accuracy of the band values with ground measurements made with a spectroradiometer. We measured the sunflower in its vegetative, R-3, and R-5 phases and found that there was a strong correlation (r=0.894) in the green band, r=0.845 in the red, r=0.789 in the red edge (RE) band, and r=0.725 in the near infrared band (NIR). The results show a strong connection between the spectral bands and the spectroradiometer measurements, especially in the green and red bands
Distribution of Fibers Originating From Natural Asbestos-Containing Rocks in the Atmospheric Environment, Environmental Effects and Risks (Konya, Turkey)
No full textThe presence of asbestos in many rural areas in T ; uuml;rkiye is a well-known issue. Recently, it has been proved that inhaling asbestos fibers can cause asbestosis, lung cancer, or mesothelioma and adversely affect human health. Dangerous fibers may be found in the soil content resulting from the decomposition, dispersion, and use of asbestos-containing rocks by natural or anthropogenic activities. In this study, the effects of using naturally occurring asbestos containing rocks as road material on the environment and human health in the Alt ; imath;nekin district, Ko ; ccedil;yaka, and Ak ; ccedil;a ; scedil;ar neighborhoods were evaluated. Chrysotile, tremolite, and actinolite minerals were found in mineralogical analysis of the samples taken from the rocks used for road construction. In areas where naturally occurring asbestos containing rocks are extracted, the amount of fiber in the air varies between 0.038 and 0.3 f/m3. The amount of fiber measured in road dust is between 0.050 and 0.1 f/m3. Individuals may be exposed to road dust during transportation to agricultural areas in the region located in the arid climate zone. The proximity of naturally occurring asbestos containing rocks to settlements, and the transport of weathered fibers here with wind, poses a threat to people living in these regions.This study was supported by the Scientific Research Coordinatorship (BAP) of Selcuk University with the projects numbered 22402005, 22402006 and 23402005. The authors thank the BAP coordinator.Scientific Research Coordinatorship (BAP) of Selcuk University [22402005, 22402006, 23402005
Core-Shell Doping of Cerium Oxide With (Cr-Fe/Co)-b Catalyst for Enhanced Hydrogen Evolution in Borohydride Hydrolysis Systems: Performance and Catalytic Efficiency
No full textHerein, we successfully synthesized a CeO2@(Cr-Fe/Co)-B catalyst for hydrogen generation via NaBH4 and KBH4 hydrolysis using a hydrothermal method. To investigate the catalytic activity and hydrogen generation rate (HGR) of the catalyst, various parameters, including the catalyst amount, temperature, reusability, and the concentrations of MOH and MBH4 (M = Na, K), were tested. The catalyst was comprehensively characterized using FE-SEM, EDX, XRD, BET, TEM, XPS, and FTIR. The CeO2@(Cr-Fe/Co)-B catalyst exhibited a non-uniform, highly agglomerated, spherical morphology. TEM analysis revealed a core-shell structure with CeO2 as the core and an 8-16 nm (Cr-Fe/Co)-B shell. BET analysis confirmed the mesoporous nature of the catalyst, with a 27.19 nm pore diameter enabling efficient diffusion and interaction during reactions. The catalyst demonstrated excellent performance, achieving an HGR of 13.05 L g(metal)(-)(1) min(-)(1) for NaBH4 hydrolysis with an activation energy of 18.59 kJ mol(-)(1) and 9.06 L g(metal)(-)(1) min(-)(1) for KBH4 hydrolysis with an activation energy of 30.02 kJ mol(-)(1). Five consecutive experiments were conducted to evaluate the reusability of CeO2@(Cr-Fe/Co)-B for catalytic hydrolysis of NaBH4 and KBH4.Open access funding provided by the Scientific and Technological Research Council of Turkiye (TUBITAK). This study was supported by Konya Technical University's Scientific Research Projects (BAP) Coordination Unit (Project No.: 221116033).Scientific and Technological Research Council of Turkiye (TUBITAK); Konya Technical University's Scientific Research Projects (BAP) Coordination Unit [221116033
Investigation of Fracture Behaviour of Hybrid Composite Materials Under Compact Tension
No full textThis study examines the fracture behavior of hybrid composite materials by analyzing the relationship between stress intensity factors, crack opening displacement, and critical energy release rates for compact tension specimens. Five types of composite laminates-Basalt/Epoxy (BE), Carbon/Epoxy (CE), Glass/Epoxy (GE), BasaltGlass/Epoxy (BGE), and Basalt-Carbon-Glass/Epoxy (BCGE)-were fabricated using the Vacuum Assisted Resin Transfer Molding (VARTM) method. Compact tension (CT) tests were conducted using a Universal Testing Machine (Instron 8801), recording load and displacement data to calculate fracture toughness and energy release rates. The results revealed that hybrid composites (BGE and BCGE) showed better fracture toughness (29.73 MPa \/ and 30.95 MPa m \/ m , respectively), energy dissipation (220 kJ/m2 and 230 kJ/m2, respectively), and crack resistance than mono-fiber composites (GE). However, the BE composite exhibits the highest toughness (KQ of 37.7 MPa\/) and critical energy release rate (GQ of about 260 kJ/m2) among the mono-fiber composites, m attributed to strong fiber-matrix bonding. The GE composite has the lowest value of critical energy release rate of 150 kJ/m2 and stress intensity factor of 17.02 MPa\/m, Indicating that glass fibers have a lower capability to dissipate energy during crack propagation. The crack propagation behavior differed among the composites, with BE, CE, and GE showing linear crack paths, whereas the hybrid composites exhibited mixed-mode fracture patterns, improving energy dissipation and enhancing crack propagation resistance.The authors would like to thank the Konya Technical University Scientific Research Projects Coordinator for supporting this research with project number 201110022.Konya Technical University [201110022
Web Tabanlı Gnss Değerlendirme Yazılımlarının Performansları
No full textWeb-based GNSS processing software has been developed as an alternative to classical processing methods, which have recently attracted the attention of researchers and have been the subject of many scientific studies. Web-based GNSS software allows users to obtain coordinates with cm/dm accuracy. At the same time, many advantages such as the fact that these software are generally free of charge, can be accessed anywhere with an internet browser and connection, do not require users to have a high level of GNSS knowledge, and have a very simple user interface make these software preferred. In this study, the performance of web-based and open source GNSS software have been investigated. Five IGS stations (NOT1, SULP, ANK2, BOR1 and MIKL) at different latitudes/longitudes were selected for the study. Firstly, the effect of the Space Weather Condition indices which have a negative effect on GNSS measurements (Kp, Dst, F10.7, Bz (GSE, GSM)) was investigated. It was observed that all of the Space Weather conditions remained generally quiet during the selected date range. As a result, 24-hour RINEX data were divided into 6- and 12-hour segments using measurements at IGS stations and processed with web-based (CSRS-PPP, MagicGNSS, APPS, Trimble-RTX, IBGE-PPP, IGN-PPP, AUSPOS, OPUS) and open source (raPPPid, PPPH) processing software. In the evaluations, the coordinates obtained were compared with reference values for accuracy and the results were interpreted. Comparing the evaluations in all hourly periods, it was observed that the web-based CSRS-PPP and APPS software and the open source raPPPid software gave more successful results than other software. As a result, it was seen that web-based GNSS processing software is easier to use than open source software, and the calculated coordinates show better approximation to the reference coordinates when the space weather conditions remain calm and the selected stations are taken into consideration.Web tabanlı GNSS değerlendirme yazılımları son zamanlarda araştırmacıların ilgisini çeken ve birçok bilimsel çalışmaya konu olan, klasik değerlendirme yöntemlerine bir seçenek olarak geliştirilmiştir. Web tabanlı GNSS yazılımları kullanıcıların cm/dm doğrulukta koordinat elde etmesini sağlamaktadır. Aynı zamanda, bu yazılımların genel olarak ücretsiz olması, internet tarayıcısı ve bağlantısının olduğu her yerde erişim imkanı sağlaması, kullanıcıların yüksek düzeyde GNSS bilgisine sahip olmasını gerektirmemesi, son derece basit kullanıcı arayüzüne sahip olmaları gibi birçok avantaj bu yazılımların tercih edilmesini sağlamaktadır. Bu çalışmada web tabanlı ve açık kaynak kodlu GNSS yazılımlarının performansları araştırılmıştır. Çalışma kapsamında farklı enlemlerde/boylamlarda beş adet IGS istasyonu (NOT1, SULP, ANK2, BOR1 ve MIKL) seçilmiştir. İlk olarak, GNSS ölçüleri üzerine olumsuz etkisi olan Uzay İklim Koşulları indislerinden Kp, Dst, F10.7, Bz (GSE, GSM)' nın etkisi araştırılmıştır. Seçilen tarih aralığında Uzay İklim koşullarının hepsinin genel olarak sakin kaldığı görülmüştür. Bunun sonucunda, IGS noktalarındaki ölçüler kullanılarak 24 saatlik RINEX verileri 6 ve 12 saatlik dilimlere ayrılarak, web tabanlı (CSRS-PPP, MagicGNSS, APPS, Trimble-RTX, IBGE-PPP, IGN-PPP, AUSPOS, OPUS) ve açık kaynak kodlu değerlendirme yazılımları (raPPPid, PPPH) ile değerlendirilmiştir. Değerlendirmelerde, elde edilen koordinatlar, referans değerlerle doğruluk açısından karşılaştırılmış ve sonuçlar yorumlanmıştır. Tüm saatlik dilimlerde yapılan değerlendirmeler karşılaştırıldığında web tabanlı CSRS-PPP ve APPS yazılımları ile açık kaynak kodlu raPPPid yazılımının diğer yazılımlara kıyasla daha başarılı sonuçlar verdiği görülmüştür. Sonuç olarak, Uzay İklim Koşullarının sakin kaldığı ve seçilen istasyon noktaları dikkate alındığında web tabanlı GNSS değerlendirme yazılımlarının açık kaynak kodlu yazılımlara göre kullanımının kolay olduğu, hesaplanan koordinatların referans koordinatlara daha iyi yaklaşım gösterdiği görülmüştür
Improving the Wear and Corrosion Resistance of New Generation Cast Irons (SSFF) With HVOF Thermal Spray Coating Method
No full textIn this thesis, it is aimed to develop a wear and corrosion resistant, high hardness surface on solid solution strengthened ferritic ductile cast iron (SSF) by using HVOF (High Velocity Oxy Fuel Spraying) thermal spray coating method which offers better surface properties compared to conventional coating methods. Solid solution strengthened ferritic ductile cast iron (SSF) is a new (second) generation of cast iron and is considered as an alternative to forged and cast steels. Although they have advantages such as relatively low cost, low melting point, light weight, fluidity, castability, machinability and homogeneous mechanical properties throughout the part, they have relatively poor wear, corrosion and fatigue resistance under harsh conditions. At this point, it is necessary to develop parts with high surface quality. In this context, wear and corrosion resistant, high hardness surfaces are developed by using HVOF thermal spray coating method which offers high quality surface properties. In the proposed study, it is aimed to develop parts with high surface hardness, high wear and corrosion resistance by coating WC-Co and WC-Co(Cr) with HVOF method on new generation cast irons with EN-GJS-600-10 standard. WC-Co and WC-Co(Cr) coatings applied to SSF cast irons using the HVOF thermal spray coating method have provided significant performance improvements compared to the base material. A noticeable increase in hardness has been observed; the WC-Co coating achieved a hardness value of 1176 HV, while the WC-Co(Cr) coating reached 1248 HV, providing approximately six times the hardness of the base material (~199 HV). In terms of wear resistance, while a wear mark 200 μm deep formed on the uncoated sample, only superficial scratches were detected on the coated samples, and SEM-EDS analyses confirmed that the substrate material (Fe) was not reached in the wear areas. The WC-Co coating stood out particularly in terms of corrosion resistance. With an open-circuit potential (OCP) of -0,230 V, it exhibited more noble behavior compared to the substrate (-0,481 V), and PDP and EIS analyses also demonstrated superior protection by showing low corrosion current density and high charge transfer resistance. Adhesion strength was clearly evident in scratch tests; the WC-Co(Cr) coating reached a critical load value of 30,1 N, demonstrating the positive effect of Cr addition on fracture resistance. In conclusion, both HVOF coatings comprehensively improved the surface performance of SSF cast iron in terms of hardness, wear resistance, and corrosion resistance.Bu tez çalışmasında katı çözelti ile güçlendirilmiş yeni nesil ferritik sünek dökme demirlerde (SSF) geleneksel kaplama yöntemlerine kıyasla daha kaliteli yüzey özellikleri sunan HVOF (Yüksek Hızda Oksi Yakıt Püskürtme, High Velocity Oygen Fuel) termal sprey kaplama yöntemi kullanılarak aşınmaya ve korozyona karşı dirençli, yüksek sertliğe sahip yüzey geliştirilmesi amaçlanmıştır. SSF (Solid solution strengthened ferritic ductile cast iron) olarak adlandırılan katı çözelti ile güçlendirilmiş ferritik sünek dökme demirler yeni (ikinci) nesil dökme demirler olup dövme ve döküm çeliklere alternatif olarak düşünülmektedir. Nispeten düşük maliyet, düşük erime noktası, hafiflik, akışkanlık, dökülebilirlik, işlenebilirlik ve parça boyunca homojen mekanik özellikler gibi üstünlüklere sahip olmalarına rağmen zorlayıcı koşullarda aşınma, korozyon ve yorulma direnci nispeten zayıftır. Bu noktada yüksek yüzey kalitesine sahip parçaların geliştirilmesi gerekmektedir. Bu kapsamda yüksek kaliteli yüzey özellikleri sunan HVOF termal sprey kaplama yöntemi kullanılarak aşınmaya ve korozyona karşı dirençli, yüksek sertliğe sahip yüzeyler geliştirilmektedir. Önerilen çalışmada EN-GJS-600-10 standardına sahip yeni nesil dökme demirlere HVOF yöntemi ile WC-Co ve WC-Co(Cr) kaplama yapılarak yüksek yüzey sertliğine, yüksek aşınma ve korozyon direncine sahip parçaların geliştirilmesi amaçlanmıştır. HVOF termal sprey kaplama yöntemiyle SSF dökme demirlere uygulanan WC-Co ve WC-Co(Cr) kaplamalar, altlık malzemeye kıyasla önemli performans iyileştirmeleri sağlamıştır. Sertlikte belirgin bir artış gözlemlenmiştir; WC-Co kaplaması 1176 HV, WC-Co(Cr) kaplaması ise 1248 HV sertlik değerine ulaşarak, altlık malzemenin (~199 HV) yaklaşık 6 katı sertlik sağlamıştır. Aşınma direnci açısından, kaplamasız numunede 200 μm derinliğinde aşınma izi oluşurken, kaplamalı numunelerde yalnızca yüzeysel çizikler tespit edilmiş ve SEM-EDS analizleri aşınma bölgelerinde altlık malzemeye (Fe) ulaşılmadığını doğrulamıştır. Korozyon direncinde özellikle WC-Co kaplama öne çıkmıştır. -0,230 V açık devre potansiyeli (OCP) ile altlığa (-0,481 V) kıyasla daha asil davranış sergilemiş, PDP ve EIS analizleri de düşük korozyon akım yoğunluğu ve yüksek yük transfer direnci göstererek üstün koruma sağladığını kanıtlamıştır. Yapışma dayanımı çizik testlerinde net olarak görülmüştür; WC-Co(Cr) kaplama 30,1 N kritik yük değerine ulaşarak kırılma direncinde Cr katkısının olumlu etkisini ortaya koymuştur. Sonuç olarak, her iki HVOF kaplaması da SSF dökme demirin yüzey performansını sertlik, aşınma ve korozyon direnci açısından bütüncül bir şekilde geliştirmiştir
Evaluation of Carbon Footprint Effect in Land Consolidation for Sustainable Agricultural Planning: A Research on Transportation and Intra-Parcel Tractor Maneuvers
No full textCarbon emission is a major driver to climate change, posing significant challenges to global sustainability efforts. Agriculture, as a key sector, plays a substantial role in greenhouse gas (GHG) emissions, with land fragmentation further exacerbating this issue by increasing fuel consumption and CO2 emissions during farming activities. Land consolidation (LC) has emerged as an effective strategy to mitigate these impacts by reducing the spatial dispersion of parcels and improving mechanization efficiency. This study focuses on a consolidation area in Konya, a vital agricultural region in T ; uuml;rkiye. It examines the effects of changes in routes and tractor maneuvers before and after LC on the fuel consumption of tractors and, accordingly, the carbon footprint (CF). Using network analysis and the Tier-1 method for CF calculations, the study found a 40% reduction in total CO2 emissions due to decreased transportation distances. The average CF per enterprise decreased by 38.26%, demonstrating the potential of LC to make a substantial contribution to GHG reduction. These findings highlight LC's role in fostering sustainable agricultural planning and environmental conservation, providing a pathway for long-term carbon reduction and climate resilience. Further research is recommended to develop region-specific LC models integrating socio-economic and climatic variables for enhanced sustainability outcomes
The Investigation of Metallic Silver Dissolution Kinetics Using DL-Malic Acid With Hydrogen Peroxide Solution as an Eco-Friendly Leaching System: The Rotating Disc Method
No full textAlthough cyanidation remains widely employed for silver recovery due to its cost-effectiveness, it presents serious environmental and health hazards. In this study, the dissolution kinetics of silver were investigated in an environmentally benign leaching system composed of DL-malic acid and hydrogen peroxide, employing the rotating disc method. High-purity silver discs (99.99 pct) were used to examine the effects of rotation speed, disc surface area, temperature, and the concentrations of DL-malic acid and hydrogen peroxide on the leaching rate. X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR) were conducted to characterize the silver surface before and after leaching. Additionally, contact angle measurements were performed to evaluate the interfacial interaction between the leaching solution and the silver surface. The results demonstrated that the dissolution rate increased with temperature, rotation speed, hydrogen peroxide concentration, and surface area. However, elevated concentrations of DL-malic acid resulted in the formation of a passivating layer on the silver surface, likely due to chelation effects, which significantly impeded the access of protons (H+) to the silver surface, thereby reducing the dissolution rate. Contact angle analysis further indicated reduced wettability at higher DL-malic acid concentrations, with values reaching up to 87.80 deg. XRD analysis confirmed the partial oxidation of the silver surface, forming Ag2O. The reaction was determined to be chemically controlled, with an activation energy of 44.14 kJ/mol
Determination of the Strong Coupling and Its Running from Measurements of Inclusive Jet Production
No full textForthomme, Laurent/0000-0002-3302-336X; Tapper, Alexander/0000-0003-4543-864X; Csanad, Mate/0000-0002-3154-6925; Mitra, Soureek/0000-0002-3060-2278; Hall, Geoffrey/0000-0002-6299-8385; D'Anzi, Brunella/0000-0002-9361-3142; Garcia, Francisco/0000-0002-4023-7964; Zhang, Yousen/0000-0002-6812-761X; Grandi, Claudio/0000-0001-5998-3070; Kyberd, Paul/0000-0002-7353-7090; Smith, Nicholas/0000-0002-0324-3054; Wilson, Graham/0000-0003-0917-4763; Pasztor, Gabriella/0000-0003-0707-9762; Vannerom, David/0000-0002-2747-5095; Chatterjee, Suman/0000-0003-2660-0349; Yazgan, Efe/0000-0001-5732-7950; Giacomelli, Paolo/0000-0002-6368-7220; Pesaresi, Mark/0000-0002-9759-1083; Barroso Ferreira, Mapse/0000-0003-3904-0571The value of the strong coupling alpha(S) is determined in a comprehensive analysis at next-to-next-to-leading order accuracy in quantum chromodynamics. The analysis uses double-differential cross section measurements from the CMS Collaboration at the CERN LHC of inclusive jet production in proton-proton collisions at centre-of-mass energies of 2.76, 7, 8, and 13 TeV, combined with inclusive deep-inelastic data from HERA. The value alpha(S)(m(Z)) = 0.1176(-0.0016)(+0.0014) is obtained at the scale of the Z boson mass. By using the measurements in different intervals of jet transverse momentum, the running of alpha(S) is probed for energies between 100 and 1600GeV.We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centres and personnel of the Worldwide LHC Computing Grid and other centres for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC, the CMS detector, and the supporting computing infrastructure provided by the following funding agencies: SC (Armenia), BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MOST, and NSFC (China); Minciencias (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG, RVTT3 and MoER TK202 (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); SRNSF (Georgia); BMBF, DFG, and HGF (Germany); GSRI (Greece); NKFIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LMTLT (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, Conahcyt, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MES and NSC (Poland); FCT (Portugal); MESTD (Serbia); MCIN/AEI and PCTI (Spain); MoSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); MHESI and NSTDA (Thailand); TUBITAK and TEN-MAK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-Curie programme and The European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207, and COST Action CA16108 (European Union); the Leventis Foundation; The Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Science Committee, project no. 22rl-037 (Armenia); the Belgian Federal Science Policy Office; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the "Excellence of Science - EOS'' - be.h project n. 30820817; the Beijing Municipal Science ; Technology Commission, No. Z191100007219010 and Fundamental Research Funds for the Central Universities (China); The Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Shota Rustaveli National Science Foundation, grant FR-22985 (Georgia); the Deutsche Forschungsgemeinschaft (DFG), among others, under Germany's Excellence Strategy - EXC 2121 "Quantum Universe'' - 390833306, and under project number 400140256 - GRK2497; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288 (Greece); the Hungarian Academy of Sciences, the New National Excellence Program - UNKP, the NK-FIH research grants K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, TKP2021-NKTA-64, and 2021-4.1.2-NEMZ_KI-2024-00036 (Hungary); the Council of Science and Industrial Research, India; ICSC - National Research Centre for High Performance Computing, Big Data and Quantum Computing and FAIR - Future Artificial Intelligence Research, funded by the NextGenerationEU program (Italy); the Latvian Council of Science; the Ministry of Education and Science, project no. 2022/WK/14, and the National Science Center, contracts Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552 (Poland); the Fundacao para a Ciencia e a Tecnologia, grant CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; MCIN/AEI/10.13039/501100011033, ERDF "a way of making Europe'', and the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu, grant MDM-2017-0765 and Programa Severo Ochoa del Principado de Asturias (Spain); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project, and the National Science, Research and Innovation Fund via the Program Management Unit for Human Resources ; Institutional Development, Research and Innovation, grant B39G670016 (Thailand); the Kavli Foundation; the Nvidia Corporation; the Super-Micro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA).FWF; FNRS; FWO (Belgium); CNPq; CAPES; FAPERJ; FAPERGS; FAPESP (Brazil); BNSF (Bulgaria); MOST; NSFC (China); CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG [MoER TK202]; Academy of Finland; MEC; CEA; CNRS/IN2P3 (France); SRNSF; BMBF; DFG; HGF (Germany); NKFIH (Hungary); DAE; DST; IPM; SFI (Ireland); INFN (Italy); NRF (Republic of Korea); MES (Latvia); MOE; UM (Malaysia); BUAP; UASLP-FAI (Mexico); PAEC (Pakistan); FCT (Portugal); MESTD (Serbia); PCTI (Spain); Swiss Funding Agencies (Switzerland); NSTDA; TUBITAK; DOE; NSF (USA); Marie-Curie programme; European Research Council; Horizon 2020 Grant [675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207]; COST Action [CA16108]; Leventis Foundation; Alfred P. Sloan Foundation; Alexander von Humboldt Foundation; Science Committee [22rl-037]; Belgian Federal Science Policy Office; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); FWO (Belgium) under the "Excellence of Science - EOS [30820817]; Beijing Municipal Science ; Technology Commission [Z191100007219010]; Fundamental Research Funds for the Central Universities (China); Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; Shota Rustaveli National Science Foundation [FR-22985]; Deutsche Forschungsgemeinschaft (DFG) [EXC 2121, 390833306, 400140256 - GRK2497]; Hellenic Foundation for Research and Innovation (HFRI) [2288]; Hungarian Academy of Sciences; NK-FIH [K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K 147048, 2020-2.2.1-ED-2021-00181, TKP2021-NKTA-64, 2021-4.1.2-NEMZ_KI-2024-00036]; Council of Science and Industrial Research, India - NextGenerationEU program (Italy); Latvian Council of Science; Ministry of Education and Science [2022/WK/14]; National Science Center [Opus 2021/41/B/ST2/01369, 2021/43/B/ST2/01552]; Fundacao para a Ciencia e a Tecnologia [CEECIND/01334/2018]; National Priorities Research Program by Qatar National Research Fund; ERDF "a way of making Europe [MDM-2017-0765]; Programa Severo Ochoa del Principado de Asturias (Spain); National Science, Research and Innovation Fund via the Program Management Unit for Human Resources ; Institutional Development, Research and Innovation [B39G670016]; Kavli Foundation; Nvidia Corporation; Welch Foundation [C-1845]; Weston Havens Foundation (USA
Reweighting Simulated Events Using Machine-Learning Techniques in the CMS Experiment
No full textChatterjee, Suman/0000-0003-2660-0349; Sahasransu, Abanti Ranadhir/0000-0003-1505-1743; Grandi, Claudio/0000-0001-5998-3070; Bortignon, Pierluigi/0000-0002-5360-1454; Mitselmakher, Guenakh/0000-0001-5745-3658; Csanad, Mate/0000-0002-3154-6925; Papageorgakis, Christos/0000-0003-4548-0346; De Moor, Alexandre/0000-0001-5964-1935; Ivanov, Andrew/0000-0002-9270-5643; Sculac, Ana/0000-0001-7938-7559; Navarro-Tobar, Alvaro/0000-0003-3606-1780; Gomez Espinosa, Tirso Alejandro/0000-0002-9443-7769; De La Cruz Burelo, Eduard/0000-0002-7469-6974; Heredia De La Cruz, Ivan/0000-0002-8133-6467; Karneyeu, Anton/0000-0001-9983-1004; Barroso Ferreira, Mapse/0000-0003-3904-0571; Hernandez Calama, Jose Maria/0000-0001-6436-7547; Reichert, Joseph/0000-0003-2110-8021; /0000-0002-6047-4211; Moureaux, Louis/0000-0002-2310-9266; Azzi, Patrizia/0000-0002-3129-828X; Colaleo, Anna/0000-0002-0711-6319; Ecklund, Karl/0000-0002-6976-4637; Usai, Emanuele/0000-0001-9323-2107; Dozen, Candan/0000-0002-4301-634X; Mrenna, Stephen/0000-0001-8731-160X; Delgado Peris, Antonio/0000-0002-8511-7958; Tapper, Alexander/0000-0003-4543-864X; Garcia, Francisco/0000-0002-4023-7964; Mitra, Soureek/0000-0002-3060-2278; Vannerom, David/0000-0002-2747-5095; Pasztor, Gabriella/0000-0003-0707-9762; Grunewald, Martin/0000-0002-5754-0388; Bruschini, Davide/0000-0001-7248-2967; Schwandt, Joern/0000-0002-0052-597X; Kunnawalkam Elayavalli, Raghav/0000-0002-9202-1516; Klyukhin, Vyacheslav/0000-0002-8577-6531; Yazgan, Efe/0000-0001-5732-7950; Singh, Jasbir/0000-0001-9029-2462; Hall, Geoffrey/0000-0002-6299-8385; Kyberd, Paul/0000-0002-7353-7090; D'Anzi, Brunella/0000-0002-9361-3142; Pesaresi, Mark/0000-0002-9759-1083; Tytgat, Michael/0000-0002-3990-2074; Ferencek, Dinko/0000-0001-9116-1202; Geurts, Frank/0000-0003-2856-9090; Zhang, Yousen/0000-0002-6812-761X; Wilson, Graham/0000-0003-0917-4763; Ruiz, Jose/0000-0002-3306-0363; Hussain, Priya Sajid/0000-0002-4825-5278; D'Enterria, David/0000-0002-5754-4303; Perez Adan, Danyer/0000-0003-3416-0726; Al Kadhim, Ali/0000-0003-3490-8407; You, Zhengyun/0000-0001-8324-3291; Kontaxakis, Pantelis/0000-0002-4860-5979; Legger, Federica/0000-0003-1400-0709; Diaz, Daniel/0000-0001-6834-1176; Gutsche, Oliver/0000-0002-8015-9622; Smith, Nicholas/0000-0002-0324-3054; Fouz Iglesias, Maria Cruz/0000-0003-2950-976X; Giacomelli, Paolo/0000-0002-6368-7220Data analyses in particle physics rely on an accurate simulation of particle collisions and a detailed simulation of detector effects to extract physics knowledge from the recorded data. Event generators together with a geant-based simulation of the detectors are used to produce large samples of simulated events for analysis by the LHC experiments. These simulations come at a high computational cost, where the detector simulation and reconstruction algorithms have the largest CPU demands. This article describes how machine-learning (ML) techniques are used to reweight simulated samples obtained with a given set of parameters to samples with different parameters or samples obtained from entirely different simulation programs. The ML reweighting method avoids the need for simulating the detector response multiple times by incorporating the relevant information in a single sample through event weights. Results are presented for reweighting to model variations and higher-order calculations in simulated top quark pair production at the LHC. This ML-based reweighting is an important element of the future computing model of the CMS experiment and will facilitate precision measurements at the High-Luminosity LHC.Finally, we acknowledge the enduring support for the construction and operation of the LHC, the CMS detector, and the supporting computing infrastructure provided by the following funding agencies: SC (Armenia), BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MoST, and NSFC (China); MINCIENCIAS (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG, RVTT3 and MoER TK202 (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); SRNSF (Georgia); BMBF, DFG, and HGF (Germany); GSRI (Greece); NKFIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LMTLT (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MES and NSC (Poland); FCT (Portugal); MESTD (Serbia); MCIN/AEI and PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); MHESI and NSTDA (Thailand); TUBITAK and TENMAK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-Curie programme and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Science Committee, project no. 22rl-037 (Armenia); the Belgian Federal Science Policy Office; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the "Excellence of Science - EOS" - be.h project n. 30820817; the Beijing Municipal Science ; Technology Commission, No. Z191100007219010 and Fundamental Research Funds for the Central Universities (China); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Shota Rustaveli National Science Foundation, grant FR-22-985 (Georgia); the Deutsche Forschungsgemeinschaft (DFG), among others, under Germany's Excellence Strategy - EXC 2121 "Quantum Universe" - 390833306, and under project number 400140256 - GRK2497; the Hellenic Foundation for Research and Innovation (HFRI), Project Number 2288 (Greece); the Hungarian Academy of Sciences, the New National Excellence Program - UNKP, the NKFIH research grants K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K147048, 2020-2.2.1-ED-2021-00181, and TKP2021-NKTA64 (Hungary); the Council of Science and Industrial Research, India; ICSC - National Research Centre for High Performance Computing, Big Data and Quantum Computing and FAIR - Future Artificial Intelligence Research, funded by the NextGenerationEU program (Italy); the Latvian Council of Science; theMinistry of Education and Science, project no. 2022/WK/14, and the National Science Center, contracts Opus 2021/41/B/ST2/01369 and 2021/43/B/ST2/01552 (Poland); the Fundacao para a Ciencia e a Tecnologia, grant CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; MCIN/AEI/10. 13039/501100011033, ERDF "a way of making Europe", and the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia Maria de Maeztu, grant MDM-2017-0765 and Programa Severo Ochoa del Principado de Asturias (Spain); the Chulalongkorn Academic into Its 2nd Century Project Advancement Project, and the National Science, Research and Innovation Fund via the Program Management Unit for Human Resources; InstitutionalDevelopment, Research and Innovation, grant B39G670016 (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C1845; and the Weston Havens Foundation (USA).FWF; FNRS; FWO (Belgium); CNPq; CAPES; FAPERJ; FAPERGS; FAPESP (Brazil); BNSF (Bulgaria); MoST; NSFC (China); CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG [MoER TK202]; Academy of Finland; MEC; CEA; CNRS/IN2P3 (France); SRNSF; BMBF; DFG; HGF (Germany); NKFIH (Hungary); DAE; DST; IPM; SFI (Ireland); INFN (Italy); NRF (Republic of Korea); MES (Latvia); MOE; UM (Malaysia); BUAP; CONACYT; UASLP-FAI (Mexico); PAEC (Pakistan); FCT (Portugal); MESTD (Serbia); PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); NSTDA; TUBITAK; DOE; NSF (USA); Marie-Curie programme; European Research Council; Horizon 2020 Grant [675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207]; COST Action [CA16108]; Leventis Foundation; Alfred P. Sloan Foundation; Alexander von Humboldt Foundation; Science Committee [22rl-037]; Belgian Federal Science Policy Office; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); FWO (Belgium) under the "Excellence of Science - EOS [30820817]; Beijing Municipal Science ; Technology Commission [Z191100007219010]; Fundamental Research Funds for the Central Universities (China); Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; Shota Rustaveli National Science Foundation [FR-22-985]; Deutsche Forschungsgemeinschaft (DFG) [EXC 2121, 390833306, 400140256 - GRK2497]; Hellenic Foundation for Research and Innovation (HFRI) [2288]; Hungarian Academy of Sciences [K 131991, K 133046, K 138136, K 143460, K 143477, K 146913, K 146914, K147048, 2020-2.2.1-ED-2021-00181, TKP2021-NKTA64]; Council of Science and Industrial Research, India - NextGenerationEU program (Italy); Latvian Council of Science [2022/WK/14]; National Science Center [Opus 2021/41/B/ST2/01369, 2021/43/B/ST2/01552]; Fundacao para a Ciencia e a Tecnologia [CEECIND/01334/2018]; National Priorities Research Program by Qatar National Research Fund; ERDF "a way of making Europe [MDM-2017-0765]; Programa Severo Ochoa del Principado de Asturias (Spain); National Science, Research and Innovation Fund via the Program Management Unit for Human Resources; Research and Innovation [B39G670016]; Kavli Foundation; Nvidia Corporation; SuperMicro Corporation; Welch Foundation [C1845]; Weston Havens Foundation (USA