dataesr/scientific-paragraphs-categorization huggingface dataset:
The SM-only hypothesis still describes the data relatively well, with χ 2 SM /ν dof 1. 4 (ν dof = 102 -62 = 40), FIG. 2. The constraints on ULD scalar in the α φ , m φ plane, with purple-shaded 1, 2, 3, 4 σ CL regions favored by the DATA22 dataset (black dot is the best-fit point). Exclusions are by SN1987a  [50, 51]  (below the pink line, absent if φ invisible decay dominates), NA62 K + → π + Xinv search  [52]  (green, the dashed line is a naive NNLO estimate), stellar cooling  [53]  (gray), and E137  [54, 55]  (between yellow dashed lines, absent if φ invisible decay dominates). despite known tensions in the proton charge radius puzzle data and the recent hydrogen 2S 1/2 -8D 5/2 transition  [20]. Figure  1  shows the 95 % confidence level (CL) upper bounds on α φ as function of m φ for the NP benchmark models, Sec.
S2. THE CODATA18 DATASET The CODATA 2018 dataset contains all the inputs from Ref. [1]  related to the determination of the Rydberg constant R ∞ , the proton and deuteron radii, r p and r d , respectively, the fine-structure constant α, and the relative atomic masses of the electron, proton, and deuteron: A r (e), A r (p) and A r (d), respectively. The other observables and parameters included in the CODATA 2018 adjustment are very weakly correlated with the selected data, and can be neglected for our purposes. The selected data include atomic transitions and non-spectroscopic observables, which depend on the main fundamental constants as follows. The inputs primarily used to determine R ∞ , r p , and r d are: A) measurements of transition frequencies in electronic hydrogen and deuterium, labeled as Ai, i = 1,.
, 29, and listed in Table  S1 ,     S3. Input data of the muonic hydrogen and deuterium Lamb shifts (LS), as well as the proton and deuteron charge radii from the electron-proton and electron-deuteron scatterings for the CODATA18 dataset, taken from Table XVIII of Ref. [1]. For the additive corrections C7 and C8, the relative uncertainty is with respect to the value of the corresponding theoretical quantity. B) the additive theory uncertainties on theory predictions for the relevant energy levels, labeled by Bi, i = 1,. , 25, listed in Table  S2 , and C) the inputs for muonic hydrogen and deuterium and electron scattering, labeled by Ci, with i = 1, 2, 7, 8 and i = 9, 10, respectively (see Table  S3 ). The dependence of an electronic transition frequency ν i SM on physical constants is described, within the SM, by the   simplified expression ν i SM = 2cR ∞ a i 1 + m e /m N + b i (α) + c i (r N ) , ( S8 ) where a i ≡ 1/n 2 i -1/n 2 i , with n i , n i the principal quantum numbers of the initial and the final state, respectively, while m N is the mass of the nucleus, and i runs over all the transitions in Table  S1.
Following Ref. [1] , the CODATA 2018 dataset therefore also includes the values of relative atomic masses for the relevant atoms. These are taken from the 2016 Atomic Mass Evaluation (AME)  [60, 61]  (see Table  S4 ). The electron relative atomic mass is obtained from the measurements of spin-flip and cyclotron frequencies in a hydrogenic ion A using a theoretical calculation of the bound-electron g-factor g e (A). The atomic masses of the ions are deduced from the AME 2016 values of their neutral counterparts by subtracting the mass of the missing electrons and theoretically correcting for their binding energies  [62]. The relative atomic mass of proton is extracted from the AME 2016 value of the hydrogen atom (using the theoretical binding energy) along with the more recent measurement  [63] ; for the relative atomic mass of deuteron, only the most recent measurement  [64]  is taken into account.
The correlation coefficients for the A, B and D datasets are listed in Table  IX  and Table XXII of Ref. [1] , respectively. Finally, for the ease of comparison we follow Ref. [1] , and add expansion factors for the CODATA18 analysis, in the case where no new physics is considered. The expansion factors reduce the tension in the data: we multiply by a factor of 1. 6 the quoted errors for the proton radius data, i. e. , to all the A, B, and C inputs, and a factor of 1. 7 for the proton mass data, i. e. , the D15 and D19 items. In the DATA22 analysis, on the other hand, we do not use the expansion factors. Extracted values of g SM using CODATA18 data and assuming no new physics contributions are listed in Table  S5.
S3. THE DATA22 DATASET The DATA22 dataset contains the CODATA18 inputs, but with updated values for both the experimental and theoretical inputs, Table  S7 , as well as the additional input data, Table  S6. Together these then provide an improved sensitivity to NP effects. To the list of hydrogen atom observables we added the two latest measurements of the 1S 1/2 -3S 1/2  [21]  and 2S 1/2 -8D 5/2  [20]  transition frequencies, and took into account recent theory improvements in the calculation of nS 1/2 energy levels  [65] [66] [67] [68]. The resulting slightly reduced theoretical uncertainties and their correlation coefficients are provided in Tables  S7  and S8 , respectively. Among the data related to α determination, the recoil measurement of Ref. [69]  was replaced by the improved measurement from the same group  [58] , and the measurement of the electron magnetic moment of Ref.
Examples of such models are the Higgs portal and the hadrophilic scalar, introduced in Section II in the main text. This feature has been exploited to constrain Yukawa-type forces between hadrons  [11, 14] , and is the major benefit of including the HD + data in the DATA22 dataset. Similarly, the pHe spectroscopy leads to the determination of the antiproton-toelectron mass ratio (or, equivalently, the m p /m e ratio, assuming CPT symmetry) with an uncertainty slightly below 10 -9  [37]. Although the achieved precision is lower, these data provide useful constraints on NP models for higher mediator masses relative to the HD + constraints, due to the smaller average distance between the nuclei  [14]. The pHe energy levels depend on additional parameters, i. e. , the masses and charge radii of the α particle and the helion.
Th ir masses are deduced from the AME 2020 values of helium-3 and helium-4 masses and their theoretical binding ((v, L) -(v , L )) corresponds to the spin-averaged frequency of the transition between rovibrational states (v, L) and (v , L ) of HD + , where v (v ) denote the initial (final) vibrational state, and L (L ) the initial (final) orbital angular momentum quantum number. Similarly, νpHe((n, l) -(n , l )) is the frequency of the transition between states (n, l) and (n , l ) of pHe , where n (n ) and l (l ) respectively denote the principal and orbital quantum numbers of the antiproton in the initial (final) state. The "---" symbol indicates that the input datum has been removed from the CODATA18 dataset. Label Input datum Value (kHz) Rel. uncert. B1 δH(1S 1/2 )/h 0. 0(1. 3) 4. 0 × 10 -13 B2 δH(2S 1/2 )/h 0.
00(16) 2. 0 × 10 -13 B3 δH(3S 1/2 )/h 0. 000(49) 1. 3 × 10 -13 B4 δH(4S 1/2 )/h 0. 000(21) 1. 0 × 10 -13 B5 δH(6S 1/2 )/h 0. 000(11) 1. 2 × 10 -13 B6 δH(8S 1/2 )/h 0. 0000(47) 9. 2 × 10 -14 B17 δD(1S 1/2 )/h 0. 0(1. 2) 3. 5 × 10 -13 B18 δD(2S 1/2 )/h 0. 00(15) 1. 8 × 10 -13 B19 δD(4S 1/2 )/h 0. 000(18) 9. 0 × 10 -14 B20 δD(8S 1/2 )/h 0. 0000(46) 8. 9 × 10 -14 TABLE S7. Updated input data for the additive energy corrections accounting for missing contributions to the theoretical description of H and D energy levels. Uncertainties of non-S energy levels are not given here as they are unchanged with respect to Table VIII of  [1]. energies. The charge radii are determined from the muonic helium spectroscopy data  [78, 79] , which we therefore added to the DATA22 dataset. The new inputs for the DATA22 dataset are listed in Table  S6.
The updates of theoretical uncertainties for hydrogen and deuterium levels, based on Refs. [65] [66] [67] [68] , and the correlation matrix (calculated following the method of Ref. [1] ) are collected in Tables  S7  and S8 , respectively. Moreover, an expansion factor of 2. 4 is applied for the fine-structure constant data, i. e. , datapoints D3 and D4, because in this case the discrepancies cannot be due to NP, and are most     S9. Input data for the additive energy corrections accounting for missing contributions to the theoretical description of energy levels of three-body systems, HD + (F) and pHe (H), and the Lamb shift of muonic helium ions (I). likely due to overlooked or underestimated systematics. Note that in the DATA22 inputs, we do not include newer input values for r p from e-p scattering.
The values of g SM determined from the fit to DATA22 data under the hypothesis of just SM, i. e. , no new physics contributions, are listed in Table  S5. We reiterate that in this adjustment the experimental errors were not increased by expansion factors, unlike in the CODATA18 dataset, except for the input data D3 and D4. The extraction of SM and NP parameters in the case of new physics is discussed in the main text and in Sections S5 and S6.
e. , for a 0 m φ ∼ O(α). The least-squares adjustment also reveals that the DATA22 dataset favors the scalar photon model over the SMonly hypothesis at the 4. 8σ level, with the best-fit point at m φ = 0. 2 keV and α φ = 2. 7 × 10 -13. The 1σ, 2σ, 3σ, and 4σ CL contours are shown as orange shaded regions in Fig. S2  (right panel), along with the exclusions from stellar cooling (grey), SN1987a cooling (red), NA62 search for K + → π + +inv (green) and E137 (dark green). The overlap of all the bounds excludes the region favored by the adjustment. Note that even if the SN cooling does not apply  [109]  the favored region is still excluded by the combination of other constraints. Figure  S1  (left panel) shows the allowed range for α φ at 99% CL assuming a given scalar photon mass (orange shaded region), with the solid line showing the best fit α φ for each value of m φ.
S5. NEW PHYSICS IMPROVEMENTS RELATIVE TO THE SM The fit to DATA22 dataset assuming only the SM, i. e. , no NP, gives the minimum χ 2 per degree of freedom χ 2 SM /ν dof 1. 4 (ν dof = 102 -62 = 40). Ignoring correlations, the largest contributions to the χ 2 are from the hydrogen observables A12-A15, A23 and A31 in Tables  S1  and S6 , see also Fig. S3. The adjustments exhibit no significant (> 2σ) preference over the SM for the gauged B -L, dark photon and hadrophilic scalar models, see Fig. S4. The ULD scalar and the Higgs portal, on the other hand, show a preference over the SM for m φ a 0 m µ /m e. This NP evidence can already be anticipated from the bounds on α φ shown in Fig. 1. For masses heavier than m φ a 0 m µ /m e the main constraint is from muonic hydrogen, so that one would expect, due to enhanced couplings of φ to muons, the bounds on ULD scalar and Higgs portal to be stronger by a factor O(m µ /m e ) relative to all the other models we consider, in which q e = q µ.
The bounds in Fig. 1 , however, are found   and the NP coupling constant α φ for a 300 keV ULD scalar, using the DATA22 dataset. The x-axis is shifted by x SM i , the extracted value of xi for the SM-only hypothesis, and normalized by its uncertainty. -4 -2 0 2 4 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 A16 A17 A18 A19 A20 A21 A22 A23 A24 A25 A26 A27 A28 A29 A30 A31 R i SM -4 -2 0 2 4 B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11 B12 B13 B14 B15 B16 B17 B18 B19 B20 B21 B22 B23 B24 B25 R i SM -4 -2 0 2 4 C1 C2 C7 C8 C9 C10 D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 D11 D12 D13 D14 D15 D19 D21 R i SM -4 -2 0 2 4 E1 E2 E3 F1 F2 F3 F4 F5 G1 G2 G3 G4 4 -2 0 2 4 A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 A13 A14 A15 A16 A17 A18 A19 A20 A21 A22 A23 A24 A25 A26 A27 A28 A29 A30 A31 Δ i -4 -2 0 2 4 B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11 B12 B13 B14 B15 B16 B17 B18 B19 B20 B21 B22 B23 B24 B25 Δ i -4 -2 0 2 4 C1 C2 C7 C8 C9 C10 D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 D11 D12 D13 D14 D15 D19 D21 Δ i -4 -2 0 2 4 E1 E2 E3 F1 F2 F3 F4 F5 G1 G2 G3 G4 for the ULD and Higgs portal models to be weaker by a factor of O(20) than the naive expectations, for heavy φ.
S6. EXTRACTION OF FUNDAMENTAL CONSTANTS IN THE PRESENCE OF NP In this section we discuss the effect of NP on the uncertainty of extracted fundamental constants. Figure  3  in the main text shows the 68% CL region for simultaneous determinations of the proton charge radius r p and the Rydberg constant R ∞ , assuming the SM-only hypothesis, using either the CODATA18 or DATA22 datasets, as well as for the ULD and the Higgs portal models (DATA22 only). As expected, the extracted values of r p and R ∞ are highly correlated regardless of the existence of NP. NP induces significant shifts in the extracted values of R ∞ and r p , notably when the data shows evidence for nonzero α φ. Furthermore, the larger the shift in the extracted value of the fundamental constant, the more important is the correlation with α φ , see Fig.
ACKNOWLEDGMENTS We would like to thank  Dmitry Budker  and  Gilad Perez  for useful discussions and comments on the manuscript. The work of CD is supported by the  CNRS IRP NewSpec. The work of TK is supported by the  Japan Society for the Promotion of Science (JSPS)   Grant-in-Aid for Early-Career Scientists  (Grant No. 19K14706 ) and the  JSPS Core-to-Core Program  (Grant No. JPJSCCA20200002 ). The work of YS is supported by grants from the  NSF-BSF  (No. 2018683 ), the  ISF  (No. 482/20 ), the  BSF  (No. 2020300 ) and by the  Azrieli foundation. JZ acknowledges support in part by the  DOE  grant  de-sc0011784. This work was also supported in part by the  European Union 's  Horizon 2020 research and innovation programme , project  STRONG2020 , under grant agreement No. 824093.
NP i ) 2 is the contribution of each input datum i to the χ 2 difference between SM and NP ignoring correlations with other input data. R NP i are the normalized residuals of the scalar photon (orange) and the ULD scalar (purple) models, evaluated at their respective best-fit points. Darker colors indicate input data with |δR 2 i | ≥ 2. Input data satisfying |R SM i | ≥ 2 are indicated in red. H1 H2 H3 H4 H5 H6 H7 I1 I2 I3 I4 Δ i FIG. S5. Difference of squared normalized residuals, ∆i ≡ sign(δR 2 i ) |δR 2 i |, of individual input data within the DATA22 dataset, where δR 2 i ≡ (R SM i ) 2 -(R α 8 10 α 4 6 ϕ ×10 11 2 R∞ rp rd ULD scalar 0 Ar(e) 0 10 20 30 mϕ=300keV 40 (x i -x i SM )/u(x i SM ) FIG. S6. The 68 % CL covariance ellipses of the fundamental constants xi = α, R∞, rp, r d , Ar(e) (color coding as indicated).
Observations In order to secure polarization measurements before any potential merger, we used specialized photo-and spectro-polarimeters to acquire fast and reliable broadband polarimetric measurements. For the remainder of this paper, q and u are the normalized Stokes parameters, p is the linear polarization degree, and θ is the polarization position angle measured north to east according to the IAU convention  (IAU Commission 1974). J1430+2303 (Fig. 1 ) is located at high galactic latitude (b = 66 • ), in a region where the extinction is low, namely A V = 0. 085 (from the NASA/IPAC Extragalactic Database 1 ), indicating a low interstellar polarization, p  Serkowski et al. 1975; Panopoulou et al. 2019). The polarization of stars at angular distances of smaller than 2 • is low (see Table  1 ), in agreement with the value derived from extinction.
For this reason, we only consider VLT/FORS2 data in the remainder of the article, as they are the most precise (larger integration time, lower instrumental polarization, larger telescope). Nevertheless, in all cases, the polarization we observed in the B band is higher than in the V and R bands, with a comparable polarization angle. The polarization angle is close to the host galaxy position angle (≈20 • ; see Fig. 1 ).
Acknowledgements. This research has made use of data from the  RoboPol programme, a Collaboration between Caltech , the  University of Crete ,  IA-FORTH, IUCAA , the  MPIfR , and the  Nicolaus Copernicus University , which was conducted at  Skinakas Observatory in Crete, Greece. The data in this study include observations made with the  Nordic Optical Telescope , owned in collaboration by the  University of Turku and Aarhus University , and operated jointly by  Aarhus University , the  University of Turku  and the  University of Oslo , representing  Denmark, Finland and Norway , the  University of Iceland and Stockholm University at the Observatorio del Roque de los Muchachos, La Palma, Spain , of the  Instituto de Astrofisica de Canarias. The data presented here were obtained in part with  ALFOSC , which is provided by the  Instituto de Astrofísica de Andalucía (IAA)  under a joint agreement with the  University of Copenhagen  and NOT.
E. L. was supported by  Academy of Finland  projects  317636  and  320045. D. B. and N. M. , acknowledge support from the  European Research Council (ERC)  under the European Unions  Horizon 2020 research and innovation programme  under grant agreement No. 771282. D. H. is research director at the  Fonds de la Recherche Scientifique F. R. S. -FNRS (Belgium). D. H. and D. S. acknowledge support from the  F. R. S. -FNRS (Belgium)  under grants  PDR T. 0116. 21  and No. 4. 4503. 19.
The accelerating structure, described in some detail in Section 2. 1, is called ElectronFlash (EF)  [17, 18]. It operates at 5 and 7 MeV, and it can irradiate in conventional and FLASH modalities by changing the pulse width, the pulse repetition frequency, and the number of pulses. The flexibility of the machine allows the investigation of the FLASH effect on small animals or cell samples, with uniform dose profiles. The characterization of the electron beam in terms of doses was necessary to calibrate the data obtained in the radiobiological and pre-clinical experiments performed at Institut Curie.
The conversion of the ionization chamber signal to the absorbed dose follows the general TRS-398  [26]  formalism. For PDD FLASH measurements, films placed parallel to the beam axis in the PMMA phantom were irradiated with both 5 MeV and 7 MeV beams, with applicators A-d120 and A-d30 and a pulse width of 4 µs. In addition, three films were irradiated for each energy-applicator combination in correspondence with the dose peak value depth (R100), 80% depth (R80), and 50% depth (R50). Twenty-four hours after the irradiation, the films were scanned using an Epson 800, 48-bit color scanner, and the dose maps were analyzed with FilmQA Pro software [25], with triple-channel and reference dose protocols.
Monte-Carlo Dose Simulations Experimental measurements were compared with simulations obtained by means of the MC software 2020. 0. 10 FLUKA version  [27, 28]. In particular, the accelerator beam optics from the titanium window (at the end of the linac) to the end of the applicator was simulated. As mentioned previously, the A-d30 and A-d120 applicators were chosen to validate the EF dosimetric proprieties according to the foreseen radio-biology experiments. In the simulations, the electron beam exits from the linac and goes through a 55 µmthick titanium window that seals the linac vacuum. Depending on the applicator, the sourceto-surface distances (SSDs) are 55 cm and 110 cm for the A-d30 and A-d120, respectively, (Figures  2  and 3 ). The A-d120 applicator was modeled as a series of three PMMA cylinders centered on the beam axis (z axis), with diameters of 50, 120, and 120.
Measurements of the Percentage Depth Dose (PDD) Curve and of the Dose Profiles Figure  6  (red dots) reports the experimental data of PDD measured along the beam axis as a function of the depth in the PMMA phantom, for A-d30 and A-d120, and for electron beams with the energy of 5 MeV. Figure  7  reports the data relative to the case of 7 MeV. Data concerning the depth-dose curves were normalized to their maximum value at a depth of 12 mm for the beam energy of 7 MeV and of 7 mm for the beam energy of 5 MeV. Starting from the data of the PDDs, the lateral dose profiles, at the points R100, R80, and R50, were obtained as shown in Figures  8  and 9  for the energies and applicator cases considered in this analysis. The lateral dose profiles were investigated at 12 mm (R100), 17 mm (R80), and 21 mm (R50) depth for 7 MeV and at 7 mm (R100), 11 mm (R80), 14 mm (R50) depth for 5 MeV.
ACKNOWLEDGMENTS V. E. A. gratefully acknowledges the support through a grant of the  Ministry of Research, Innovation and Digitization ,  CNCS -UEFISCDI , project number  PN-III-P1-1. 1-TE-2021-1707 , within  PNCDI III. The authors gratefully acknowledge support by the  European Union -NextGenerationEU  through grant No. 760079/23. 05. 2023 , funded by the  Romanian Ministry of Research, Innovation , and  Digitalization through Romania 's  National Recovery and Resilience Plan , call no. PNRR-III-C9-2022-I8 , during the revision and extension of this manuscript.
propose new onboard field-particle correlator instrumentation, designed to study these processes with greater capability than currently possible, that could be employed on a future kinetic plasma physics mission. This method will correlate particle detections with the observations of electromagnetic fields to measure, onboard the spacecraft, energization at multiple energies simultaneously and with much higher time resolution than ever before. It will allow downlink of high-resolution data on particle energization over long periods of a mission and enable event-based triggering. These approaches will further our understanding of energization in a variety of space plasma processes. Our Research Topic also describes novel analysis methods for space plasma data. The Methods Article by Bakrania et al.
explores the use of machine-learning (clustering) techniques to classify space plasma regimes. Applied to electron distribution functions observed by the Cluster mission, the method clearly identifies eight distinct plasma regions in the Earth's magnetotail. Automated classification methods are a useful and promising tool to analyse large amounts of plasma data. In the future, methods like this may even be used onboard spacecraft to reduce the dimensionality of datasets and thus the required telemetry. The difficulty of obtaining accurate three-dimensional electric field measurements is an important limitation of experimental space physics. For instance, in their Research Article, Wilson et al. discuss specific features of high-frequency electric field fluctuations at collisionless shocks.
The red curve refers to EPOS PDFs, the green one to CTEQ PDFs  [43] , and the black points are data from ZEUS  [44]  and H1  [45] [46] [47]. The two PDFs give very similar results, and both are close to the experimental data. Having checked the EPOS PDFs, I will use these functions to compute the jet (parton) cross section, using Eq. (  55 ), integrating out the momentum of the second parton and the azimuthal angle of the first parton, for pp at 13 TeV. I define the parton yield dn/d p t dy as the cross section, divided by the inelastic pp cross section, showing the result in Fig. 27. I show results based on EPOS PDFs (red full line), CTEQ PDFs  [43]  (green dashed line), the full EPOS simulation (blue circles), and experimental data from ATLAS  [48]  (black triangles). At large values of p t , all the different distribution agree, whereas at low p t the EPOS Monte Carlo simulation results (using the FIG.
ACKNOWLEDGMENTS I thank  T. Pierog  for many contributions during the past decade and in particular the important proposal (and first implementation) in 2015 of using a Pomeron definition as G ∝ G QCD (Q 2 sat ) with a parametrized G. He also did a first attempt in 2020 to take into account the "deformation", by using a correction factor being a ratio of a "theoretical" G theo and the same function G theo but with rescaled longitudinal momentum arguments.