Machine Learning in High Energy Physics Community White Paper

Machine learning is an important applied research area in particle physics, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction in the 2010s. In this document we discuss promising future research and development areas in machine learning in particle physics with a roadmap for their implementation, software and hardware resource requirements, collaborative initiatives with the data science community, academia and industry, and training the particle physics community in data science. The main objective of the document is to connect and motivate these areas of research and development with the physics drivers of the High-Luminosity Large Hadron Collider and future neutrino experiments and identify the resource needs for their implementation. Additionally we identify areas where collaboration with external communities will be of great benefit

Machine Learning in High Energy Physics Community White Paper

Machine learning is an important applied research area in particle physics, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction in the 2010s. In this document we discuss promising future research and development areas in machine learning in particle physics with a roadmap for their implementation, software and hardware resource requirements, collaborative initiatives with the data science community, academia and industry, and training the particle physics community in data science. The main objective of the document is to connect and motivate these areas of research and development with the physics drivers of the High-Luminosity Large Hadron Collider and future neutrino experiments and identify the resource needs for their implementation. Additionally we identify areas where collaboration with external communities will be of great benefit

Matrix Models for Supersymmetric Chern-Simons Theories with an ADE Classification

We consider N=3 supersymmetric Chern-Simons (CS) theories that contain product U(N) gauge groups and bifundamental matter fields. Using the matrix model of Kapustin, Willett and Yaakov, we examine the Euclidean partition function of these theories on an S^3 in the large N limit. We show that the only such CS theories for which the long range forces between the eigenvalues cancel have quivers which are in one-to-one correspondence with the simply laced affine Dynkin diagrams. As the A_n series was studied in detail before, in this paper we compute the partition function for the D_4 quiver. The D_4 example gives further evidence for a conjecture that the saddle point eigenvalue distribution is determined by the distribution of gauge invariant chiral operators. We also see that the partition function is invariant under a generalized Seiberg duality for CS theories.Comment: 20 pages, 3 figures; v2 refs added; v3 conventions in figure 3 altered, version to appear in JHE

Software Challenges For HL-LHC Data Analysis

The high energy physics community is discussing where investment is needed to prepare software for the HL-LHC and its unprecedented challenges. The ROOT project is one of the central software players in high energy physics since decades. From its experience and expectations, the ROOT team has distilled a comprehensive set of areas that should see research and development in the context of data analysis software, for making best use of HL-LHC's physics potential. This work shows what these areas could be, why the ROOT team believes investing in them is needed, which gains are expected, and where related work is ongoing. It can serve as an indication for future research proposals and cooperations

Ketonuria after Fasting may be Related to the Metabolic Superiority

Obese individuals are less able to oxidize fat than non-obese individuals. Caloric reduction or fasting can detect ketonuria. We investigated the differences of metabolic parameters in the presence of ketonuria after a minimum 8 hr fast in a cross-sectional analysis of 16,523 Koreans (6,512 women and 10,011 men). The relationship between the presence of ketonuria of all subjects and prevalence of obesity, central obesity, metabolic syndrome, and obesity-related metabolic parameters were assessed. The ketonuria group had lower prevalence of obesity, central obesity, and metabolic syndrome than the non-ketonuria group. In addition, all metabolic parameters (including body weight, waist circumference, blood glucose, high-density lipoprotein, triglyceride, blood pressure, and insulin) were favorable in the ketonuria group than in the non-ketonuria group, even after adjustment for age, tobacco use, and alcohol consumption. The odds ratios of having obesity (odds ratio [OR]=1.427 in women, OR=1.582 in men, P<0.05), central obesity (OR=1.675 in women, OR=1.889 in men, P<0.05), and metabolic syndrome (OR=3.505 in women, OR=1.356 in men, P<0.05) were increased in the non-ketonuria group compared to the ketonuria group. The presence of ketonuria after at least an 8 hr fast may be indicative of metabolic superiority

The Galleria mellonella Hologenome Supports Microbiota-Independent Metabolism of Long-Chain Hydrocarbon Beeswax

The greater wax moth, Galleria mellonella, degrades wax and plastic molecules. Despite much interest, the genetic basis of these hallmark traits remains poorly understood. Herein, we assembled high-quality genome and transcriptome data from G. mellonella to investigate long-chain hydrocarbon wax metabolism strategies. Specific carboxylesterase and lipase and fatty-acid-metabolism-related enzymes in the G. mellonella genome are transcriptionally regulated during feeding on beeswax. Strikingly, G. mellonella lacking intestinal microbiota successfully decomposes long-chain fatty acids following wax metabolism, although the intestinal microbiome performs a supplementary role in short-chain fatty acid degradation. Notably, final wax derivatives were detected by gas chromatography even in the absence of gut microbiota. Our findings provide insight into wax moth adaptation and may assist in the development of unique wax-degradation strategies with a similar metabolic approach for a plastic molecule polyethylene biodegradation using organisms without intestinal microbiota. The evolutionarily expanded long-chain fatty acid degradation gene products of Galleria mellonella decompose long-chain hydrocarbons independently of intestinal microorganisms. Kong et al. show that beeswax and degradation products are detected equally in larvae in the presence or absence of intestinal microbes

LEGO-II. A 3 mm molecular line study covering 100 pc of one of the most actively star-forming portions within the Milky Way disc

The current generation of (sub)mm-telescopes has allowed molecular line emission to become a major tool for studying the physical, kinematic, and chemical properties of extragalactic systems, yet exploiting these observations requires a detailed understanding of where emission lines originate within the Milky Way. In this paper, we present 60 arcsec (∼3 pc) resolution observations of many 3 mm band molecular lines across a large map of the W49 massive star-forming region (∼100 pc × 100 pc at 11 kpc), which were taken as part of the ‘LEGO’ IRAM-30m large project. We find that the spatial extent or brightness of the molecular line transitions are not well correlated with their critical densities, highlighting abundance and optical depth must be considered when estimating line emission characteristics. We explore how the total emission and emission efficiency (i.e. line brightness per H2 column density) of the line emission vary as a function of molecular hydrogen column density and dust temperature. We find that there is not a single region of this parameter space responsible for the brightest and most efficiently emitting gas for all species. For example, we find that the HCN transition shows high emission efficiency at high column density (1022 cm−2) and moderate temperatures (35 K), whilst e.g. N2H+ emits most efficiently towards lower temperatures (1022 cm−2; <20 K). We determine XCO(1−0) ∼ 0.3 × 1020 cm−2 (K km s−1) −1, and αHCN(1−0) ∼ 30 M (K km s−1 pc2) −1, which both differ significantly from the commonly adopted values. In all, these results suggest caution should be taken when interpreting molecular line emission

Matrix Metalloproteinases in Cytotoxic Lymphocytes Impact on Tumour Infiltration and Immunomodulation

To efficiently combat solid tumours, endogenously or adoptively transferred cytotoxic T cells and natural killer (NK) cells, need to leave the vasculature, traverse the interstitium and ultimately infiltrate the tumour mass. During this locomotion and migration in the three dimensional environment many obstacles need to be overcome, one of which is the possible impediment of the extracellular matrix. The first and obvious one is the sub-endothelial basement membrane but the infiltrating cells will also meet other, both loose and tight, matrix structures that need to be overridden. Matrix metalloproteinases (MMPs) are believed to be one of the most important endoprotease families, with more than 25 members, which together have function on all known matrix components. This review summarizes what is known on synthesis, expression patterns and regulation of MMPs in cytotoxic lymphocytes and their possible role in the process of tumour infiltration. We also discuss different functions of MMPs as well as the possible use of other lymphocyte proteases for matrix degradation

Structural reorganization of cylindrical nanoparticles triggered by polylactide stereocomplexation

YesCo-crystallization of polymers with different configurations/tacticities provides access to materials with enhanced performance. The stereocomplexation of isotactic poly(L-lactide) and poly(D-lactide) has led to improved properties compared with each homochiral material. Herein, we report the preparation of stereocomplex micelles from a mixture of poly(L-lactide)-b-poly(acrylic acid) and poly(D-lactide)-b-poly(acrylic acid) diblock copolymers in water via crystallization-driven self-assembly. During the formation of these stereocomplex micelles, an unexpected morphological transition results in the formation of dense crystalline spherical micelles rather than cylinders. Furthermore, mixture of cylinders with opposite homochirality in either THF/H2O mixtures or in pure water at 65 °C leads to disassembly into stereocomplexed spherical micelles. Similarly, a transition is also observed in a related PEO-b-PLLA/PEO-b-PDLA system, demonstrating wider applicability. This new mechanism for morphological reorganization, through competitive crystallization and stereocomplexation and without the requirement for an external stimulus, allows for new opportunities in controlled release and delivery applications.University of Warwick, Swiss National Science Foundation and the EPSRC. The Royal Society - an Industry Fellowship to A.P.D. The Engineering and Physical Sciences Research Council (EP/G004897/1) - funding to support postdoctoral fellowships for A.P.B. as well as funding for J.S. and M.A.D. through the Warwick Centre for Analytical Science (EP/F034210/1). The Science City Research Alliance and the HEFCE Strategic Development Fund - funding support. Some items of equipment that were used in this research were funded by Birmingham Science City, with support from Advantage West Midlands and part-funded by the European Regional Development Fund