Covid-19 and the Role of Intellectual Property - Position Statement of the Max Planck Institute for Innovation and Competition of 7 May 2021

In this Statement, the authors take a position on the waiver of intellectual property (IP) protection currently being considered by the members of the World Trade Organisation. The waiver was initiated by India and South Africa as a measure to enable rapid access to affordable medical products that are necessary to combat Covid-19. The initiative gained momentum after the US decided to support it. The authors do not consider this path to be expedient. The Statement presents factual and legal arguments why a comprehensive waiver of IP protection is unlikely to be a necessary and suitable measure towards the pursued objective. Overall, it argues that IP rights may so far have played an enabling and facilitating rather than hindering role in overcoming Covid-19. The global community might not be better off if IP rights are waived, neither during nor after the pandemic. There are more efficient and direct ways to supply developing countries with vaccines quickly – if the industrialised countries are willing to do their share

Simulations and analysis tools for charge-exchange (d,2He)(d,{}^{2}\text{He}) reactions in inverse kinematics with the AT-TPC

Charge-exchange $(d,{}^{2}\text{He})$ reactions in inverse kinematics at intermediate energies are a very promising method to investigate the Gamow-Teller transition strength in unstable nuclei. A simulation and analysis software based on the $\rm{\scriptsize ATTPCROOT}$ package was developed to study these type of reactions with the active-target time projection chamber (AT-TPC). The simulation routines provide a realistic detector response that can be used to understand and benchmark experimental data. Analysis tools and correction routines can be developed and tested from simulations in $\rm{\scriptsize ATTPCROOT}$, because they are processed in the same way as the real data. In particular, we study the feasibility of using coincidences with beam-like particles to unambiguously identify the $(d,{}^{2}\text{He})$ reaction channel, and to develop a kinematic fitting routine for future applications. More technically, the impact of space-charge effects in the track reconstruction, and a possible correction method are investigated in detail. This analysis and simulation package constitutes an essential part of the software development for the fast-beams program with the AT-TPC

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies

Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC

The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of the TPC, especially for the induction planes. This paper describes the characteristics and mitigation of the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase LArTPC comprises two induction planes and one collection sense wire plane with a total of 8256 wires. Current induced on each TPC wire is amplified and shaped by custom low-power, low-noise ASICs immersed in the liquid argon. The digitization of the signal waveform occurs outside the cryostat. Using data from the first year of MicroBooNE operations, several excess noise sources in the TPC were identified and mitigated. The residual equivalent noise charge (ENC) after noise filtering varies with wire length and is found to be below 400 electrons for the longest wires (4.7 m). The response is consistent with the cold electronics design expectations and is found to be stable with time and uniform over the functioning channels. This noise level is significantly lower than previous experiments utilizing warm front-end electronics.Comment: 36 pages, 20 figure

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.Comment: Preprint to be submitted to The European Physical Journal

Determination of muon momentum in the MicroBooNE LArTPC using an improved model of multiple Coulomb scattering

We discuss a technique for measuring a charged particle's momentum by means of multiple Coulomb scattering (MCS) in the MicroBooNE liquid argon time projection chamber (LArTPC). This method does not require the full particle ionization track to be contained inside of the detector volume as other track momentum reconstruction methods do (range-based momentum reconstruction and calorimetric momentum reconstruction). We motivate use of this technique, describe a tuning of the underlying phenomenological formula, quantify its performance on fully contained beam-neutrino-induced muon tracks both in simulation and in data, and quantify its performance on exiting muon tracks in simulation. Using simulation, we have shown that the standard Highland formula should be re-tuned specifically for scattering in liquid argon, which significantly improves the bias and resolution of the momentum measurement. With the tuned formula, we find agreement between data and simulation for contained tracks, with a small bias in the momentum reconstruction and with resolutions that vary as a function of track length, improving from about 10% for the shortest (one meter long) tracks to 5% for longer (several meter) tracks. For simulated exiting muons with at least one meter of track contained, we find a similarly small bias, and a resolution which is less than 15% for muons with momentum below 2 GeV/c. Above 2 GeV/c, results are given as a first estimate of the MCS momentum measurement capabilities of MicroBooNE for high momentum exiting tracks

Evidence for t\bar{t}\gamma Production and Measurement of \sigma_t\bar{t}\gamma / \sigma_t\bar{t}

Using data corresponding to 6.0/fb of ppbar collisions at sqrt(s) = 1.96 TeV collected by the CDF II detector, we present a cross section measurement of top-quark pair production with an additional radiated photon. The events are selected by looking for a lepton, a photon, significant transverse momentum imbalance, large total transverse energy, and three or more jets, with at least one identified as containing a b quark. The ttbar+photon sample requires the photon to have 10 GeV or more of transverse energy, and to be in the central region. Using an event selection optimized for the ttbar+photon candidate sample we measure the production cross section of, and the ratio of cross sections of the two samples. Control samples in the dilepton+photon and lepton+photon+\met, channels are constructed to aid in decay product identification and background measurements. We observe 30 ttbar+photon candidate events compared to the standard model expectation of 26.9 +/- 3.4 events. We measure the ttbar+photon cross section to be 0.18+0.08 pb, and the ratio of the cross section of ttbar+photon to ttbar to be 0.024 +/- 0.009. Assuming no ttbar+photon production, we observe a probability of 0.0015 of the background events alone producing 30 events or more, corresponding to 3.0 standard deviations.Comment: 9 pages, 3 figure

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level

Precision Top-Quark Mass Measurements at CDF

We present a precision measurement of the top-quark mass using the full sample of Tevatron $\sqrt{s}=1.96$ TeV proton-antiproton collisions collected by the CDF II detector, corresponding to an integrated luminosity of 8.7 $fb^{-1}$. Using a sample of $t\bar{t}$ candidate events decaying into the lepton+jets channel, we obtain distributions of the top-quark masses and the invariant mass of two jets from the $W$ boson decays from data. We then compare these distributions to templates derived from signal and background samples to extract the top-quark mass and the energy scale of the calorimeter jets with {\it in situ} calibration. The likelihood fit of the templates from signal and background events to the data yields the single most-precise measurement of the top-quark mass, \mtop = 172.85 \pm$0.71 (stat)$\pm$0.85 (syst) GeV/c^{2}.$Comment: submitted to Phys. Rev. Let