Strong Logic for Weak Memory: Reasoning About Release-Acquire Consistency in Iris (Artifact)

This artifact provides the soundness proofs for the encodings in Iris the RSL and GPS logics, as well as the verification for all standard examples known to be verifiable in those logics. All of these proofs are formalized in Coq, which is the main content of this artifact. The formalization is provided in a virtual machine for the convenience of testing, but can also be built from source

First Steps Toward an Autonomous Accelerator, a Common Project Between DESY and KIT

Reinforcement Learning algorithms have risen in popularity in recent years in the accelerator physics community, showing potential in beam control and in the optimization and automation of tasks in accelerator operation. The Helmholtz AI project "Machine Learning toward Autonomous Accelerators" is a collaboration between DESY and KIT that works on investigating and developing RL applications for the automatic start-up of electron linear accelerators. The work is carried out in parallel at two similar research accelerators: ARES at DESY and FLUTE at KIT, giving the unique opportunity of transfer learning between facilities. One of the first steps of this project is the establishment of a common interface between the simulations and the machine, in order to test and apply various optimization approaches interchangeably between the two accelerators. In this paper we present the first results on the common interface and its application to beam focusing in ARES, and the idea of laser shaping with spatial light modulators at FLUTE

Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous Tuning

Online tuning of real-world plants is a complex optimisation problem that continues to require manual intervention by experienced human operators. Autonomous tuning is a rapidly expanding field of research, where learning-based methods, such as Reinforcement Learning-trained Optimisation (RLO) and Bayesian optimisation (BO), hold great promise for achieving outstanding plant performance and reducing tuning times. Which algorithm to choose in different scenarios, however, remains an open question. Here we present a comparative study using a routine task in a real particle accelerator as an example, showing that RLO generally outperforms BO, but is not always the best choice. Based on the study's results, we provide a clear set of criteria to guide the choice of algorithm for a given tuning task. These can ease the adoption of learning-based autonomous tuning solutions to the operation of complex real-world plants, ultimately improving the availability and pushing the limits of operability of these facilities, thereby enabling scientific and engineering advancements.Comment: 17 pages, 8 figures, 2 table

The Roland von Glasow Air-Sea-Ice Chamber (RvG-ASIC): an experimental facility for studying ocean–sea-ice–atmosphere interactions

Sea ice is difficult, expensive, and potentially dangerous to observe in nature. The remoteness of the Arctic Ocean and Southern Ocean complicates sampling logistics, while the heterogeneous nature of sea ice and rapidly changing environmental conditions present challenges for conducting process studies. Here, we describe the Roland von Glasow Air-Sea-Ice Chamber (RvG-ASIC), a laboratory facility designed to reproduce polar processes and overcome some of these challenges. The RvG-ASIC is an open-topped 3.5 m3 glass tank housed in a cold room (temperature range: −55 to +30 ∘C). The RvG-ASIC is equipped with a wide suite of instruments for ocean, sea ice, and atmospheric measurements, as well as visible and UV lighting. The infrastructure, available instruments, and typical experimental protocols are described. To characterise some of the technical capabilities of our facility, we have quantified the timescale over which our chamber exchanges gas with the outside, τl=(0.66±0.07)  d, and the mixing rate of our experimental ocean, τm=(4.2±0.1)  min. Characterising our light field, we show that the light intensity across the tank varies by less than 10 % near the centre of the tank but drops to as low as 60 % of the maximum intensity in one corner. The temperature sensitivity of our light sources over the 400 to 700 nm range (PAR) is (0.028±0.003) W m−2 ∘C−1, with a maximum irradiance of 26.4 W m−2 at 0 ∘C; over the 320 to 380 nm range, it is (0.16±0.1) W m−2 ∘C−1, with a maximum irradiance of 5.6 W m−2 at 0 ∘C. We also present results characterising our experimental sea ice. The extinction coefficient for PAR varies from 3.7 to 6.1 m−1 when calculated from irradiance measurements exterior to the sea ice and from 4.4 to 6.2 m−1 when calculated from irradiance measurements within the sea ice. The bulk salinity of our experimental sea ice is measured using three techniques, modelled using a halo-dynamic one-dimensional (1D) gravity drainage model, and calculated from a salt and mass budget. The growth rate of our sea ice is between 2 and 4 cm d−1 for air temperatures of (−9.2±0.9)  ∘C and (−26.6±0.9)  ∘C. The PAR extinction coefficients, vertically integrated bulk salinities, and growth rates all lie within the range of previously reported comparable values for first-year sea ice. The vertically integrated bulk salinity and growth rates can be reproduced well by a 1D model. Taken together, the similarities between our laboratory sea ice and observations in nature, as well as our ability to reproduce our results with a model, give us confidence that sea ice grown in the RvG-ASIC is a good representation of natural sea ice. How to cite. Thomas, M., France, J., Crabeck, O., Hall, B., Hof, V., Notz, D., Rampai, T., Riemenschneider, L., Tooth, O. J., Tranter, M., and Kaiser, J.: The Roland von Glasow Air-Sea-Ice Chamber (RvG-ASIC): an experimental facility for studying ocean–sea-ice–atmosphere interactions, Atmos. Meas. Tech., 14, 1833–1849, https://doi.org/10.5194/amt-14-1833-2021, 2021

Biological Effects of Antiprotons Are Antiprotons a Candidate for Cancer Therapy?

2009 Status Report of AD-4 Experimen

The Fermi energy as common parameter to describe charge compensation mechanisms: A path to Fermi level engineering of oxide electroceramics

Chemical substitution, which can be iso- or heterovalent, is the primary strategy to tailor material properties. There are various ways how a material can react to substitution. Isovalent substitution changes the density of states while heterovalent substitution, i.e. doping, can induce electronic compensation, ionic compensation, valence changes of cations or anions, or result in the segregation or neutralization of the dopant. While all these can, in principle, occur simultaneously, it is often desirable to select a certain mechanism in order to determine material properties. Being able to predict and control the individual compensation mechanism should therefore be a key target of materials science. This contribution outlines the perspective that this could be achieved by taking the Fermi energy as a common descriptor for the different compensation mechanisms. This generalization becomes possible since the formation enthalpies of the defects involved in the various compensation mechanisms do all depend on the Fermi energy. In order to control material properties, it is then necessary to adjust the formation enthalpies and charge transition levels of the involved defects. Understanding how these depend on material composition will open up a new path for the design of materials by Fermi level engineering

Lassie: HOL4 Tactics by Example

Proof engineering efforts using interactive theorem proving have yielded several impressive projects in software systems and mathematics. A key obstacle to such efforts is the requirement that the domain expert is also an expert in the low-level details in constructing the proof in a theorem prover. In particular, the user needs to select a sequence of tactics that lead to a successful proof, a task that in general requires knowledge of the exact names and use of a large set of tactics. We present Lassie, a tactic framework for the HOL4 theorem prover that allows individual users to define their own tactic language by example and give frequently used tactics or tactic combinations easier-to-remember names. The core of Lassie is an extensible semantic parser, which allows the user to interactively extend the tactic language through a process of definitional generalization. Defining tactics in Lassie thus does not require any knowledge in implementing custom tactics, while proofs written in Lassie retain the correctness guarantees provided by the HOL4 system. We show through case studies how Lassie can be used in small and larger proofs by novice and more experienced interactive theorem prover users, and how we envision it to ease the learning curve in a HOL4 tutorial

Mechanical design of the optical modules intended for IceCube-Gen2

IceCube-Gen2 is an expansion of the IceCube neutrino observatory at the South Pole that aims to increase the sensitivity to high-energy neutrinos by an order of magnitude. To this end, about 10,000 new optical modules will be installed, instrumenting a fiducial volume of about 8 km3. Two newly developed optical module types increase IceCube’s current sensitivity per module by a factor of three by integrating 16 and 18 newly developed four-inch PMTs in specially designed 12.5-inch diameter pressure vessels. Both designs use conical silicone gel pads to optically couple the PMTs to the pressure vessel to increase photon collection efficiency. The outside portion of gel pads are pre-cast onto each PMT prior to integration, while the interiors are filled and cast after the PMT assemblies are installed in the pressure vessel via a pushing mechanism. This paper presents both the mechanical design, as well as the performance of prototype modules at high pressure (70 MPa) and low temperature (−40∘C), characteristic of the environment inside the South Pole ice

The next generation neutrino telescope: IceCube-Gen2

The IceCube Neutrino Observatory, a cubic-kilometer-scale neutrino detector at the geographic South Pole, has reached a number of milestones in the field of neutrino astrophysics: the discovery of a high-energy astrophysical neutrino flux, the temporal and directional correlation of neutrinos with a flaring blazar, and a steady emission of neutrinos from the direction of an active galaxy of a Seyfert II type and the Milky Way. The next generation neutrino telescope, IceCube-Gen2, currently under development, will consist of three essential components: an array of about 10,000 optical sensors, embedded within approximately 8 cubic kilometers of ice, for detecting neutrinos with energies of TeV and above, with a sensitivity five times greater than that of IceCube; a surface array with scintillation panels and radio antennas targeting air showers; and buried radio antennas distributed over an area of more than 400 square kilometers to significantly enhance the sensitivity of detecting neutrino sources beyond EeV. This contribution describes the design and status of IceCube-Gen2 and discusses the expected sensitivity from the simulations of the optical, surface, and radio components