SMEFT probes in future precision DIS experiments

We analyze the potential of future high-energy deep-inelastic scattering (DIS) experiments to probe new physics within the framework of the Standard Model Effective Field Theory (SMEFT). We perform a detailed study of SMEFT probes at a future Large Hadron-electron Collider (LHeC) and a Future Circular lepton-hadron Collider (FCC-eh) machine, and extend previous simulations of the potential of a Electron-Ion Collider (EIC) to include Z-boson vertex corrections. Precision Z-pole constraints on vertex corrections suffer from numerous degeneracies in the Wilson-coefficient parameter space. We find that both the LHeC and the FCC-eh can help remove these degeneracies present in the existing global fits of precision Z-pole observables and LHC data. The FCC-eh and LHeC will in many cases improve upon the existing precision electroweak bounds on the SMEFT parameter space. This highlights the important role of precision DIS measurements for new physics studies.Comment: 21 pages, 14 figure

Extraction of Pion Transverse Momentum Distributions from Drell-Yan data

We map the distribution of unpolarized quarks inside a unpolarized pion as a function of the quark's transverse momentum, encoded in unpolarized Transverse Momentum Distributions (TMDs). We extract the pion TMDs from available data of unpolarized pion-nucleus Drell-Yan processes, where the cross section is differential in the lepton-pair transverse momentum. In the cross section, pion TMDs are convoluted with nucleon TMDs that we consistently take from our previous studies. We obtain a fairly good agreement with data. We present also predictions for pion-nucleus scattering that is being measured by the COMPASS Collaboration

Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study.

PURPOSE: As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS: This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS: Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION: Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Phenomenology of Transverse Momentum Distributions in hadronic observables

One of the main aims of hadronic physics is to describe the internal structure of the nucleon in terms of its constituents, quarks and gluons (collectively called partons). A lot of information has been collected over the past forty years concerning the distribution of partons in one dimension, encoded in the well–known collinear Parton Distribution Functions (PDFs). In the last years, we are extending the study to the distribution of partons in full three–dimensional momentum space, encoded in the so–called Transverse Momentum Distributions (TMDs). This thesis describes a suite of computing tools for the extraction of TMDs, entirely developed by our research group over the last three years, and presents a state–of–the–art extraction of these functions from experimental data. The thesis first summarizes the theoretical framework for the extraction of TMDs in two types of scattering processes: the Drell–Yan process (pp → llX), and Semi—Inclusive Deep Inelastic Scattering (lp → lhX). The thesis then presents the numerical framework we implemented to study TMDs. It consists of a suite of tools, which we called NangaParbat. It is written in C++ and is publicly available. NangaParbat can be used to extract TMDs, to produce grids for TMDs and TMD–related observables, and to have easy access to TMD extractions, through interpolation and convolution tools. Therefore, NangaParbat can be a very useful asset for the scientific community working on the phenomenology of hadronic physics. Finally, the thesis presents our most recent extraction of TMDs, which reached the unprecedented accuracy of Next–to–Next–to–Next–to–Leading Logarithm (N3LL). We used Drell–Yan data from various experiments, including those at the LHC, and spanning a wide kinematic range. We obtained a very good description of both the shape and the normalization of the data without introducing normalization coefficients as it was done in the literature before: this result was made possible only through the unsurpassed perturbative accuracy of the fit and the optimized numerical and analytical integration techniques that we used.One of the main aims of hadronic physics is to describe the internal structure of the nucleon in terms of its constituents, quarks and gluons (collectively called partons). A lot of information has been collected over the past forty years concerning the distribution of partons in one dimension, encoded in the well–known collinear Parton Distribution Functions (PDFs). In the last years, we are extending the study to the distribution of partons in full three–dimensional momentum space, encoded in the so–called Transverse Momentum Distributions (TMDs). This thesis describes a suite of computing tools for the extraction of TMDs, entirely developed by our research group over the last three years, and presents a state–of–the–art extraction of these functions from experimental data. The thesis first summarizes the theoretical framework for the extraction of TMDs in two types of scattering processes: the Drell–Yan process (pp → llX), and Semi—Inclusive Deep Inelastic Scattering (lp → lhX). The thesis then presents the numerical framework we implemented to study TMDs. It consists of a suite of tools, which we called NangaParbat. It is written in C++ and is publicly available. NangaParbat can be used to extract TMDs, to produce grids for TMDs and TMD–related observables, and to have easy access to TMD extractions, through interpolation and convolution tools. Therefore, NangaParbat can be a very useful asset for the scientific community working on the phenomenology of hadronic physics. Finally, the thesis presents our most recent extraction of TMDs, which reached the unprecedented accuracy of Next–to–Next–to–Next–to–Leading Logarithm (N3LL). We used Drell–Yan data from various experiments, including those at the LHC, and spanning a wide kinematic range. We obtained a very good description of both the shape and the normalization of the data without introducing normalization coefficients as it was done in the literature before: this result was made possible only through the unsurpassed perturbative accuracy of the fit and the optimized numerical and analytical integration techniques that we used

Extraction of Pion Transverse Momentum Distributions from Drell-Yan data

We map the distribution of unpolarized quarks inside a unpolarized pion as a function of the quark's transverse momentum, encoded in unpolarized Transverse Momentum Distributions (TMDs). We extract the pion TMDs from available data of unpolarized pion-nucleus Drell-Yan processes, where the cross section is differential in the lepton-pair transverse momentum. In the cross section, pion TMDs are convoluted with nucleon TMDs that we consistently take from our previous studies. We obtain a fairly good agreement with data. We present also predictions for pion-nucleus scattering that is being measured by the COMPASS Collaboration

Unpolarized Transverse Momentum Distributions from a global fit of Drell-Yan and Semi-Inclusive Deep-Inelastic Scattering data

We present an extraction of unpolarized transverse-momentum-dependent parton distribution and fragmentation functions based on more than two thousands data points from several experiments for two different processes: semi-inclusive deep-inelastic scattering and Drell-Yan production of lepton pairs. The baseline analysis is performed with a Monte Carlo replica method resumming large logarithms at N3LL accuracy. The resulting description of the data is very good ($\chi^2/N_{\rm dat} = 1.06$). For semi-inclusive deep-inelastic scattering, predictions for multiplicities are normalized by factors that cure the discrepancy with data introduced by higher-order perturbative corrections

Global Fits of Unpolarized TMDs at N3LL Accuracy

International audienceWe review the recent progress on the extraction of unpolarized TMD PDFs and TMD FFs from global data sets of Semi-Inclusive Deep-Inelastic Scattering, Drell–Yan and Z boson production. In particular, we address the tension between the low-energy SIDIS data and the theory predictions, and explore the impact of the very precise LHC data on the fit results