dataesr/scientific-paragraphs-categorization huggingface dataset:
This estimate is comparable to the hourly H average of ≈-1060 nT in  Gonzalez et al. (2011)  and later summarized as min Dst ≈-900 (-150, +50) nT in  Cliver and Dietrich (2013). However, the Colaba data had persistent problems, such as a chronological discrepancy of ≈40 min between  Tsurutani et al. (2003)  and  Kumar et al. (2015b). Fortunately,  Hayakawa et al. (2022a)  recently located copies of a published Colaba yearbook  (Fergusson 1860)  in several libraries. This yearbook presented regular hourly measurements and disturbance spot measurements for three geomagnetic components: the horizontal (H) component, the eastward declination (D), and the vertical component (Z). Hayakawa et al. (2022a)  calibrated the scale reading values to modern units, converted the timestamps in the astronomical time of Göttingen Mean Time (GöMT) to the civil UT, and showed significant preconditioning after the August storm (Fig.
Morley and Budnik (2007)  reported an abrupt increase in VEX signal noise shortly after 1300 UT on 5 December through the end of 6 December. They also noted numerous error detection and correction events in the VEX data management system on 5 and 7 December. These reports are consistent with SEPs causing persistent upsets on VEX's data system after the 5 and 6 December eruptions. The Ulysses spacecraft, with a great-circle angular separation of ≈77 • between its foot point and the flare site, recorded the SEP event  (Malandraki et al. 2009). Despite the spacecraft's backside, south-pole location, and the 2. 8-AU heliocentric distance, 100-MeV protons reached Ulysses and the GOES-11 spacecraft at Earth at about the same time  (Heber et al. 2008) , clearly illustrating that the SEP propagation extended to a 3D non-Parker-spiral geometry (see Sect.
2009). Shortly after 0300 UT, the SOHO Coronagraph images (C2 and C3) were contaminated by SEPs. Real-time data from the ACE particle and plasma detectors were unavailable from 0340 to 1800 UT  (McKenna-Lawlor et al. 2008). As tabulated by  Crosby (2009) , three of the four ESA Cluster spacecraft in the magnetosphere experienced anomalies on 13 December. Notably, Cluster 2 lost power in the Attitude and Orbit Control unit resulting in an autonomous switch-over to its redundant unit; and the High-Power Amplifier on Cluster 4 switched itself off. An experiment on the INTEGRAL spacecraft was affected: An imager was manually switched off to avoid overexposure. Science investigations with the Advanced CCD Imaging Spectrometer (ACIS) at the Chandra X-ray Observatory were suspended. Industry operators of geosynchronous spacecraft reported enhanced noise in attitude control sensors -however, the noise was filtered out and did not cause any disruption of operations.
There were a number of other additional minor incidents on other satellites which were presumed to be associated with the event. These include a spontaneous switch off of a reaction wheel and a spontaneous change in the gain setting of a Traveling Wave Tube Amplifier. Both of these anomalies were corrected with a reset command so there was no permanent damage. Hardware systems at LEO altitudes also felt the particle effects. For example, ESA's polar-orbiting Envisat (≈800 km altitude) autonomously suspended its Payload Module Computer. Further, proton intensity data at the lowest rigidity (0. 4-1 GV) from the PAMELA instrument became unavailable shortly after the peak fluxes were recorded. The data loss was due to an onboard system reset caused by the high trigger rate that occurred during the event  (Munini et al.
2018). Bentoutou and Bensikaddour (2015)  reported ≈300 single-bit upsets in the non-hardened, high-density memory devices operating on the LEO Algerian micro-satellite, AlSAT, in a roughly circular orbit at ≈700 km on 13 December 2006. This was the third-highest daily upset rate of the 11-year AlSAT mission. The space radiation environment monitors on the Project for On-Board Autonomy-1 (PROBA-1) spacecraft orbiting at 382 km were unable to process some data during the event  (Marinov et al. 2009 ). The CALIPSO payload controller, which had been reactivated on 12 December, was again shut down on 13 December. Astronauts outside the ISS quickly made their way to safe haven, entering the ISS airlock at 0309 UT. Later, in response to the new spike in SEPs, astronauts aboard the ISS were told to sleep in protected areas of the spacecraft  (Malik 2006b).
Myagkova et al. (2009) , who analyzed data from the Universitetskiy-Tatiana micro-satellite at 900 km, and  Adriani et al. (2011 Adriani et al. ( , 2016)) , who analyzed data from the PAMELA experiment (in a quasi-polar orbit between 360 km and 600 km) verified that SEPs had access to mid-geomagnetic latitudes by early on 15 December and noted that a few of the SEP ions had energies of 500-600 MeV. The invigorated SEPs led to another NOAA S2 radiation storm, thus, the astronauts worked swiftly to finish their EVA tasks. They returned to the ISS at 0041 UT on 15 December (about one hour ahead of the original schedule). The advisory for 100-MeV particles lasted until 0325 UT on 15 December (NOAA-RSGA-16-December 2006). The late 14 December SEP event illustrates the intricacies of energetic particle interaction with geospace.
The 13 December ICME was responsible for a significant equatorward expansion of the polar cap and also a large Forbush decrease (Fig. 49c ). Thus, a substantial Forbush decrease shielded geospace from a fraction of the GCR flux, while the expanded polar cap allowed for additional SEP radiation exposure to polar and quasi-polar orbiting spacecraft. Some members of the space community have associated the final SEP enhancement with ISS control anomalies reported on 15 December. 10  The balance of these factors remains to be explored. The twin STEREO satellites recorded a rapid SEP flux increase following the flare (prominent at 60-100 MeV range). The SEPs likely were injected into the eastern leg of the 13 December ICME, which was still attached to the  Sun. von Rosenvinge et al. (2009)  found significant differences in SEP flux and timing when comparing data from the near-Earth STEREO spacecraft and spacecraft upstream of Earth at the L1 location.
Active Region 10930's SEPs in Context 'Super'-active region 10930 produced modest SEP fluxes compared to the ESPEs in Fig. 28. Even so, the disruptive effects on space-based technologies, regional-and worldwidecommunication systems required active monitoring and mitigation. Planetary atmospheres also responded to the onslaught of high-energy particles. We collect the SEP effects here and then briefly comment on the effects of similar (or higher) intensity events for developing levels of technology. For brevity, we have tabulated the associated flare effects in Tables  6  and 7. During AR 10930 activity near the eastern solar limb, data streams from the ACE solar wind monitor were disrupted for hours at a time. Spacecraft at Mars and Venus recorded high SEP fluxes in instruments not intended as particle detectors.
Data from the VEX mission required active error detection and correction over the course of two days. Moreover, the MEX mission detected a significant Martian atmosphere outflow caused by high-energy particles. Remarkably, SEP detectability extended to the Ulysses spacecraft flying near the Sun's southern pole at ∼3 AU. The Sun was magnetically better connected to Earth during and after the second major eruption that produced an S3 radiation storm. The INTEGRAL mission and Chandra X-ray Observatory, both in highly inclined Earth orbits, required active intervention to keep instruments in safe conditions; their observing schedules were modified. The low Earth orbiting CALIPSO mission was essentially 'safed' for a week while SEP fluxes were high. Excess ionization in the ionosphere and extending to the mesosphere caused long-lasting absorption and anomalous radio propagation on VLF and HF paths.
Over-the-pole flights were re-routed to lower latitudes for at least two days. AR 10930's activity dropped to relatively low levels as it transited much of the Earthfacing solar disk (E60 → W20). Then on 13 December, while NASA astronauts were finishing their first EVA at ISS, a re-energized AR 10930 produced GLE#70. During the event, the SOHO coronagraph monitoring the situation suffered SEP contamination. Again, realtime ACE data were contaminated, although eventually recovered. In the magnetosphere several spacecraft were impacted: There were anomalies on Cluster constellation spacecraft, including at least one attitude control system and one high-power amplifier. INTEGRAL instruments switched to safe mode and Chandra X-ray Observatory observations requiring the charge-coupled imaging system were also suspended.
At geosynchronous orbit, operators reported increased noise in at least one GEO attitude control system and switch-off of a reaction wheel and a change-of-gain in a travelling wave tube amplifier. These reported GEO effects were mitigated before permanent damage occurred. Closer to Earth in the LEO CALIPSO remained 'safed'; Envisat suspended Payload Module PROBA-1 was temporarily unable to process some data; and lightly shielded LEO ALSat reported more than 300 single-bit upsets. Notably, some of the PAMELA instruments for measuring such high-energy events were overwhelmed for hours. In the Earth-ionosphere waveguide for VLF radio propagation, there was significant nightside VLF absorption caused by SEP penetration into the dark polar cap and auroral zones. Scientists monitoring Earth's global lightning activity noticed a short minor burst of intense lightning activity within 20 min of the GLE start.
Summary Here, a brief overview of the current state of the art in the field of extreme solar events is presented. The very existence of such extreme events was not known ten years ago, but after the discovery of the first event, dated back to 774/5 CE  (Miyake et al. 2012) , this field has been boosted. The statistics of and knowledge about these events is sufficient to establish a solid paradigm of such events as being caused by very rare (about once-per-millennium) extreme solar eruptions or short recurrent sequence of those leading to enormous enhancements of the flux of energetic particles bombarding the Earth's atmosphere. The whole bulk of the available datasets forms a basis for this research. Yet, many details of the events are unknown but the general paradigm is robustly set. While the solar origin of the ESPEs is beyond it still unknown how such fluxes of energetic particles can accelerated and propagated.
Important information on extremely strong solar events can be also found in historical sources such as chronicles and archives, as wrapped up in Sect. 7. The data for the 19th century can be obtained from the newly invented magnetic observatories and suggest several extreme geomagnetic storms, including the famous Carrington storm on 02-Sep-1859. Several other storms of comparable strength have been also identified. In the pre-instrumental era, this mostly relates to the recorded observations aurorae at middle and low The geographical of the auroral display can be interpreted as the of the related geomagnetic storm. Although historical records are not easy to interpret, there are shreds of evidence of very strong geomagnetic storms in the past, with the oldest known candidate being dated to the sixth century BCE, including a record in the Babylonian Astronomical Diaries.
However, for the former, we missing the understanding of the development active regions of producing ESPEs. For the latter, more events are needed establish a robust statistical relation between, e. g. , the size and phase of a solar cycle and ESPE occurrence. In summary, we are still at the beginning of the long journey towards an understanding of extreme solar eruptive events. We know that they do occur but do not yet fully understand what they are. Funding Open Access funding provided by University of Oulu (including Oulu University Hospital). This work was supported by the International Space Science Institute (ISSI) in Bern, through ISSI International Team project # 510 (Solar Extreme Events: Setting Up a Paradigm -SEESUP) and Visiting Scientist program for I. U. This work was partly supported by the Academy of  Finland (project ESPERA No.
H. H. was supported by  JSPS  Grant-in -Aids JP15H05812 ,  JP20K20918 ,  JP20H05643 ,  JP21K13957 ,  JP20KK0072 ,  JP21H01124 ,  JP21H04492 , and  JP22K02956. H. H. was partly funded by  JSPS   Overseas Challenge Program for Young Researchers ,  JSPS   Overseas Challenge Program for Young Researchers, NIHU Multidisciplinary Collaborative Research Projects NINJAL unit "Rediscovery of Citizen Science Culture in the Regions and Today " ( H421042227 ), the  ISEE  director's leadership fund for  FYs 2021 , 2022 and 2023,  Young Leader Cultivation (YLC)   programme  of  Nagoya University ,  Tokai Pathways to Global Excellence (Nagoya University)  of the  Strategic Professional Development Program   for Young Researchers (MEXT) , and the young researcher units for the advancement of new and undeveloped fields,  Institute for Advanced Research, Nagoya University  of the Program for Promoting the  Enhancement of Research Universities.
H. H. thanks the  Local Meteorological Offices at Niigata  for allowing him studying and reproducing the Japanese auroral drawing in Feb 1958 (Figure 33), the  Ulugh Beg Astronomical Institute of the Uzbekistan Academy of Sciences  for allowing him studying and reproducing the Tashkent Hα flare drawing in March 1946 (Figure 35),  Zentralbibliothek Zuürich  ( Department of Prints  and Drawings/Photo Archive) for allowing him studying and reproducing ZB  Graphische Sammlung  ( GSB ),  PAS II 19 /4 (Figure 42), and  Yasuyuki Mitsuma  for sharing his trace copies in Figures 44 and45. Work by E. R. and T. S. was partially funded by the  Government of the Russian Federation  under the agreement [ 075-15-2021-583 ]. The work of T. S. was also supported by the  Karbacher Fonds, Graubünden, Switzerland.
Events (Update Since 2019) 4. 2. 1 Large 14 C Increases During the Holocene Discovered to Date: 7176 BCE and 5259 BCE About a decade after the discovery of the 774 CE event in 2012, Brehm et al. (2022)  andPaleari et al. (2022a)  reported two strong cosmogenic-isotope increases dated to 7176 BCE and 5259 BCE that were comparable to or even exceed the 774 CE event. Interestingly, while the14 C increase corresponding to the 774 CE events was notable even in the IntCal reference data (Reimer et al. 2020)  with the decadal resolution (Usoskin and Kovaltsov 2012), the14 C increases at these two other dates were not significant in the IntCal dataset. The 7176 BCE event was discovered from prominent peaks in the 10 Be data with 5-6 years resolution, and the 5259 BCE event was discovered from discrepancies in radiocarbon dating in the surrounding ages (Brehm et al.
II. THE CUPID-0 EXPERIMENT The CUPID-0 experiment collected data from 2017 to 2020 at the underground Laboratori Nazionali del Gran Sasso (LNGS, L'Aquila, Italy). It is the first demonstrator for CUPID (CUORE Upgrade with Particle IDentification), the next generation experiment for the search for 0νββ with scintillating cryogenic calorimeters (also called bolometers)  [40] [41] [42]. These detectors consist of crystals containing the isotope candidate for the decay. The working principle of cryogenic calorimeters relies on the detection of the temperature increase, i. e. , heat release, due to an energy deposit in the crystal. This can be achieved thanks to the very low temperature reached in dedicated cryogenic facilities. The conversion of the temperature increase into an electric pulse happens through a cryogenic sensor, which is a Neutron Transmutation Doped germanium  [43]  thermistor.
III. DATA ANALYSIS The set of data analyzed in this work is based on the CUPID-0 phase I (running from June 2017 to December 2018), in which we collected a total Zn 82 Se exposure of 9. 95 kg × yr (i. e. , 3. 41 × 10 25 82 Se nuclei, 8. 74 kg of 82 Se active mass and a livetime of 1. 14 yr). The detailed data processing and selection is described in  [64]. As a quantity of interest for this work, we only report here that the selections to exclude nonparticles events led to a total efficiency of ϵ ¼ ð95. 7 AE 0. 5Þ%, constant above 150 keV  [63]. As a starting point for this analysis we needed to reconstruct the background sources contribution to the CUPID-0 energy spectrum. This study was performed in Ref. [63]  by using the JAGS software. For this work we reproduced these results, obtaining consistent results for all the sources, by means of a different software, i.
We took into account the effect of the presence of these contaminants in our results as a systematic uncertainty (see Sec. III A). Finally, to account for the environmental background, we included the cosmic muons as a source, while the γ-ray and neutron contributions are expected to be negligible  [65]. The energy spectrum of the sources was simulated with a Monte Carlo (MC) method. The model we used to describe the data consists in a set of 33 scaling parameters corresponding to each background source. The scaling parameters work as weights to the MC spectra. In particular we normalized the MC spectrum so that the value of the scaling parameter corresponds to the number of events produced by a given source. It follows that the activity of each source in the CUPID-0 array is directly related to the corresponding scaling parameter through the livetime, the number of emitting nuclei and the detector efficiency.
Moreover, we set a Gaussian prior on the bulk-to-surface events ratio of Th by constraining these from parent-daughter nuclei time correlated events  [66]. In order to better constrain the sources activities, we split the CUPID-0 data into four sets, each used to build an energy spectrum. First, we identified coincident events triggered in multiple crystals of the array within a time window of 20 ms. The choice of the time window was optimized by identifying events from the 2615 keV line (from a 232 Th source) that trigger two ZnSe crystals. In this way, we obtained M 1 and M 2 spectra for single and double hit events, respectively. Then, exploiting the particle identification capabilities of the detector  [64] , we divided M 1 by identifying events due to β=γ (M 1β=γ see Fig. 2 ) and α particles (M 1α ).
We sampled the joint posterior probability with a Markov chain Monte Carlo method exploiting the Metropolis algorithm implemented in the Bayesian Analysis Toolkit software. We performed the fit with a low energy threshold of 500 keV and a variable step size binning in order to contain any peak present in the data spectrum in a single bin  [63]. This choice helps in mitigating the effect of the detector response on the model. As a figure of merit for the result of the fit, we show in Fig. 2  the distribution of the residuals for each bin of the four fitted spectra. We define the residual as the difference between the data and the model number of events in each bin normalized to the associated uncertainty. We evaluated the uncertainty for each bin combining a Poissonian contribution with the properly propagated scaling parameters uncertainties from the fit result.
We added a free parameter, with a flat and non-negative prior, to the background model previously described to account for the 0νββχ 0 together with the background sources. We performed the fit considering an energy threshold of 700 keV for the M 1β=γ spectrum. This choice removes the possible contribution of most of the pure β emitter contamination, which is correlated with the signal and highly anticorrelated with the 2νββ. Nevertheless, we studied how the low energy threshold affects the result of this search. We performed the fit moving the threshold to 500, 300, and 200 keV and we found that the actual upper limit, on the specific dataset considered, decreases with the fit threshold (see "Threshold" in Table  I ). As in the background only hypothesis, we choose a variable step size binning.
ACKNOWLEDGMENTS This work was partially supported by the  European Research Council  (Grant No. FP7/2007-2013) under Lowbackground Underground Cryogenic Installation For Elusive Rates Contract No. 247115. This work was supported by the  Academy of Finland , Grants No. 314733 , No. 320062 , and No. 345869. We are particularly grateful to  M. Iannone  for the help in all the stages of the detector construction,  A. Pelosi  for the construction of the assembly line,  M. Guetti  for the assistance in the cryogenic operations,  R. Gaigher  for the calibration system mechanics,  M. Lindozzi  for the development of cryostat monitoring system,  M. Perego  for his invaluable help, the mechanical workshop of LNGS ( E. Tatananni ,  A. Rotilio ,  A. Corsi , and  B. Romualdi ) for the continuous help in the overall setup design.
Collision data and simulation samples The dataset used for the searches consists of the LHC proton-proton collision data recorded by the ATLAS experiment at √ s = 13 TeV during the period from 2015 to 2018. Events are selected for analysis only if they are of good quality and if all the relevant detector components are known to have been in good operating condition  [41]. The total integrated luminosity of the analysed data is 138 fb -1. The events considered were accepted by singlelepton or dilepton triggers  [42] [43] [44] [45]. The p T thresholds of the single-lepton triggers were p e T > 27  (25)  GeV and p µ T > 27. 3  (21)  GeV for the  2016-2018 (2015)  data-taking period. The p T thresholds of the dilepton triggers were p e T > 18 GeV and p µ T > 14. 7 GeV. 1. Overview of the MC generators used for the main signal and background samples.
Each normalisation factor is determined during the signal extraction. The Z → τ τ events account for 23% (11%) of the total background in the non-VBF (VBF ) SR. For each category, the Z → τ τ simulation is validated with data in a Z → τ τ CR, statistically independent of the SRs. These CRs are defined by requiring 35 GeV < p 1 T < 45 GeV, and the Z → τ τ process contributes ∼65% (∼32%) of all events in the non-VBF (VBF ) Z → τ τ CR. Good modelling in the Z → τ τ CRs is illustrated for the non-VBF case in figure  2 (c, d ). In the statistical analysis, the Z → τ τ CRs are used jointly with two independent normalisation factors to constrain the Z → τ τ normalisation in the SRs. Diboson events form 19%-32% of the total background, depending on the category. The shape and normalisation of diboson process distributions are estimated from the simulation and validated with data in a dedicated validation region, where the diboson processes contribute ∼67% of the total background.
Symmetry-based τ channel The data-driven e/µ-symmetry method was first employed in ref. [90]. This method is sensitive to the difference between B(H → eτ ) and B(H → µτ ), and it is based on the following two assumptions: 1. SM processes are symmetric under the exchange of prompt electrons with prompt muons to a good approximation. As a consequence, the kinematic distributions of prompt electrons and prompt muons are approximately the same; 2. Flavour-violating decays of the Higgs boson break this symmetry. According to the e/µ-symmetry assumption, the SM background is split equally between the µτ e and eτ µ datasets. However, the H → µτ signal is mostly present in the µτ e dataset, since the p T of the muon originating from the Higgs boson is typically larger than the p T of the electron originating from the decay of the τ -lepton.