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At least 1,207 records · Page 67

Tracking down hyper-boosted top quarks

The identification of hadronically decaying heavy states, such as vector bosons, the Higgs, or the top quark, produced with large transverse boosts has been and will continue to be a central focus of the jet physics program at the Large Hadron Collider (LHC). At a future hadron collider working at an order-of-magnitude larger energy than the LHC, these heavy states would be easily produced with transverse boosts of several TeV. At these energies, their decay products will be separated by angular scales comparable to individual calorimeter cells, making the current jet substructure identification techniques for hadronic decay modes not directly employable. In addition, at the high energy and luminosity projected at a future hadron collider, there will be numerous sources for contamination including initial- and final-state radiation, underlying event, or pile-up which must be mitigated. We propose a simple strategy to tag such "hyper-boosted" objects that defines jets with radii that scale inversely proportional to their transverse boost and combines the standard calorimetric information with charged track-based observables. By means of a fast detector simulation, we apply it to top quark identification and demonstrate that our method efficiently discriminates hadronically decaying top quarks from light QCD jets up to transverse boosts of 20 TeV. Lastly, our results open the way to tagging heavy objects with energies in the multi-TeV range at present and future hadron colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Evaluation of Machine Learning Techniques for Isotope Identification Contextualized by Training and Testing Spectral Similarity

Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset and evaluated on twelve other datasets with varying standoff distances, shielding, and background configurations. A tailored statistical approach was introduced to quantify the similarity between the training and testing configurations, which was then related to the predictive performance. Wilcoxon signed-rank tests revealed that the OVR-wrapped XGB significantly outperformed the other algorithms, with confidence levels of 99.0% or above for the 133Ba, 60Co, 137Cs, and 152Eu sources. The findings from this work are significant as they outline techniques to promote the development of robust ML-based approaches for isotope identification.

domain adaptation↗

The Atacama Cosmology Telescope: Extragalactic Sources at 148 GHz in the 2008 Survey

We report on extragalactic sources detected in a 455 square-degree map of the southern sky made with data at a frequency of 148 GHz from the Atacama Cosmology Telescope 2008 observing season. We provide a catalog of 157 sources with flux densities spanning two orders of magnitude: from 15 mJy to 1500 mJy. Comparison to other catalogs shows that 98% of the ACT detections correspond to sources detected at lower radio frequencies. Three of the sources appear to be associated with the brightest cluster galaxies of low redshift X-ray selected galaxy clusters. Estimates of the radio to mm-wave spectral indices and differential counts of the sources further bolster the hypothesis that they are nearly all radio sources, and that their emission is not dominated by re-emission from warm dust. In a bright (> 50 mJy) 148 GHz-selected sample with complete cross-identifications from the Australia Telescope 20 GHz survey, we observe an average steepening of the spectra between .5, 20, and 148 GHz with median spectral indices of alp[ha (sub 5-20) = -0.07 +/- 0.06, alpha (sub 20-148) -0.39 +/- 0.04, and alpha (sub 5-148) = -0.20 +/- 0.03. When the measured spectral indices are taken into account, the 148 GHz differential source counts are consistent with previous measurements at 30 GHz in the context of a source count model dominated by radio sources. Extrapolating with an appropriately rescaled model for the radio source counts, the Poisson contribution to the spatial power spectrum from synchrotron-dominated sources with flux density less than 20 mJy is C(sup Sync) = (2.8 +/- 0.3) x 1O (exp-6) micro K(exp 2).

Marriage, T. A.↗

Laboratory simulation of interstellar grain chemistry and the production of complex organic molecules

During the past 15 years considerable progress in observational techniques has been achieved in the middle infrared (5000 to 500 cm(-1), 2 to 20 microns m), the spectral region most diagnostic of molecular vibrations. Spectra of many different astronomical infrared sources, some deeply embedded in dark molecular clouds, are now available. These spectra provide a powerful probe, not only for the identification of interstellar molecules in both the gas solid phases, but also of the physical and chemical conditions which prevail in these two very different domains. By comparing these astronomical spectra with the spectra of laboratory ices one can determine the composition and abundance of the icy materials frozen on the cold (10K) dust grains present in the interior of molecular clouds. These grains and their ice mantles may well be the building blocks from which comets are made. As an illustration of the processes which can take place as an ice is irradiated and subsequently warmed, researchers present the infrared spectra of the mixture H2O:CH3OH:CO:NH3:C6H14 (100:50:10:10:10). Apart from the last species, the ratio of these compounds is representative of the simplest ices found in interstellar clouds. The last component was incorporated into this particular experiment as a tracer of the behavior of a non-aromatic hydrocarbon. The change in the composition that results from ultraviolet photolysis of this ice mixture using a UV lamp to simulate the interstellar radiation field is shown. Photolysis produces CO, CO2, CH4, HCO, H2CO, as well as a family of moderately volatile hydrocarbons. Less volatile carbonaceous materials are also produced. The evolution of the infrared spectrum of the ice as the sample is warmed up to room temperature is illustrated. Researchers believe that the changes are similar to those which occur as ice is ejected from a comet and warmed up by solar radiation. The warm-up sequence shows that the nitrile or iso-nitrile bearing compound produced during photolysis evaporates between 200 and 250K, suggesting that it is carried by a small molecular species. These molecules could be similar to the source material in Comet Halley that is ejected in grains into the coma, freed by sublimation, and photolyzed by solar radiation to produce the observed jets.

Allamandola, L. J.↗

Spectral line identification from a photoionised silicon plasma in emission

Next-generation X-ray satellite telescopes such as XRISM, NewAthena and Lynx will enable observations of exotic astrophysical sources at unprecedented spectral and spatial resolution. Proper interpretation of these data demands that the accuracy of the models is at least within the uncertainty of the observations. One set of quantities that might not currently meet this requirement is transition energies of various astrophysically relevant ions. Current databases are populated with many untested theoretical calculations. Accurate laboratory benchmarks are required to better understand the coming data. We obtained laboratory spectra of X-ray lines from a silicon plasma at an average spectral resolving power of ∼7500 with a spherically bent crystal spectrometer on the Z facility at Sandia National Laboratories. Many of the lines in the data are measured here for the first time. We report measurements of 53 transitions originating from the K-shells of He-like to B-like silicon in the energy range between ∼1795 and 1880 eV (6.6–6.9 Å). The lines were identified by qualitative comparison against a full synthetic spectrum calculated with ATOMIC. The average fractional uncertainty (uncertainty/energy) for all reported lines is ∼5.4 × 10 −5 . We compare the measured quantities against transition energies calculated with RATS and FAC as well as those reported in the NIST ASD and XSTAR’s uaDB. Average absolute differences relative to experimentally measured values are 0.20, 0.32, 0.17 and 0.38 eV, respectively. All calculations/databases show good agreement with the experimental values; NIST ASD shows the closest match overall.

astrophysical plasmas↗

Application of Fireworks Algorithm in Gamma-Ray Spectrum Fitting for Radioisotope Identification

We present that identification of radioisotopic signature patterns in gamma-ray spectra is of paramount importance in various applications of gamma spectroscopy. Therefore, there are several active research efforts to develop accurate and precise methods to perform automated spectroscopic analysis and subsequently recognize gamma-ray signatures. In this work, the authors present a new method for radioisotope identification in gamma-ray spectra obtained with a low resolution radiation detector. The method fits the obtained spectrum with a linear combina-tion of known template signature patterns. Coefficients of the linear combination are evaluated by computing the solution of a single objective optimization problem, whose objective is the Theil-1 inequality coefficient. Optimization of the problem is performed by the Fireworks Algorithm, which identifies a set of coefficients that minimize the Theil-1 value. The computed coefficients are statistically tested for being significantly different than zero or not, and if at least one is found to be zero then the Fireworks Algorithm is used to reiterate fitting using the non-zero templates. Fitting iterations are continued up to the point that no linear coefficients are found to be zero. The output of the method is a list that contains the radioisotopes that have been identified in the measured spectrum. The method is tested on a set of both simulated and real experimental gamma-ray spectra comprised of a variety of isotopes, and compared to a multiple linear regression fitting, and genetic algorithm Theil-1 based fitting. Finally, results demonstrate the potentiality of the Fireworks Algorithm based method, expressed as higher accuracy and similar precision over the other two tested methodologies for radioisotope signature pattern identification in the framework of gamma-ray spectrum fitting.

Theil Coefficient↗

Blood cadmium concentrations and environmental exposure sources in newcomer South and East Asian women in the Greater Toronto Area, Canada

Background: Immigrant women are often identified as being particularly vulnerable to environmental exposures and health effects. The availability of biomonitoring data on newcomers is limited, thus, presenting a challenge to public health practitioners in the identification of priorities for intervention. Objectives: In fulfillment of data needs, the purpose of this study was to characterize blood concentrations of cadmium (Cd) among newcomer women of reproductive age (19–45 years of age) living in the Greater Toronto Area (GTA), Canada and to assess potential sources of environmental exposures. Methods: A community-based model, engaging peer researchers from the communities of interest, was used for recruitment and follow-up purposes. Blood samples were taken from a total of 211 newcomer women from South and East Asia, representing primary, regional origins of immigrants to the GTA, and environmental exposure sources were assessed via telephone survey. Metal concentrations were measured in blood samples (diluted with 0.5% (v/v) ammonium hydroxide and 0.1% (v/v) octylphenol ethoxylate) using a quadrupole ICP-MS. Survey questions addressed a wide range of environmental exposure sources, including dietary and smoking patterns and use of nutritional supplements, herbal products and cosmetics. Results: A geometric mean (GM) blood Cd concentration of 0.39 µg/L (SD:±2.07 µg/L) was determined for study participants (min/max: <0.045 µg /L (LOD)/2.36 µg/L). Several variables including low educational attainment (Relative Ratio (RR) (adjusted)=1.50; 95% CI 1.17–1.91), milk consumption (RR (adjusted)=0.86; 95% CI 0.76–0.97), and use of zinc supplements (RR (adjusted)=0.76; 95% CI 0.64–0.95) were observed to be significantly associated with blood Cd concentrations in the adjusted regression model. The variable domains socioeconomic status (R{sup 2}{sub adj}=0.11) and country of origin (R{sup 2}{sub adj}=0.236) were the strongest predictors of blood Cd. Conclusion: Blood Cd concentrations fell below those generally considered to be of human health concern. However, negative health effects cannot be entirely excluded, especially for those that fall in the upper percentile range of the distribution, given the mounting evidence for negative health outcomes at low environmental exposure concentrations. - Highlights: • Blood Cd and exposure sources were assessed for 211 newcomer women in Toronto. • Blood Cd was slightly elevated compared to that in Canadian-born populations. • SES and country of origin were the strongest predictors of blood Cd. • Intake of essential micronutrients is a likely important modulator of blood Cd. • Identified need for more research on newcomers as a function of country of origin.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity of the GAPS experiment to low-energy cosmic-ray antiprotons

The General Antiparticle Spectrometer (GAPS) is an upcoming balloon mission to measure low-energy cosmic-ray antinuclei during at least three ~35-day Antarctic flights. With its large geometric acceptance and novel exotic atom-based particle identification, GAPS will detect ~500 cosmic antiprotons per flight and produce a precision cosmic antiproton spectrum in the kinetic energy range of ~0.07–0.21 GeV/n at the top of the atmosphere. With these high statistics extending to lower energies than any previous experiment, and with complementary sources of experimental uncertainty compared to traditional magnetic spectrometers, the GAPS antiproton measurement will be sensitive to dark matter, primordial black holes, and cosmic ray propagation. The antiproton measurement will also validate the GAPS antinucleus identification technique for the antideuteron and antihelium rare-event searches. Finally, this analysis demonstrates the GAPS sensitivity to cosmic-ray antiprotons using a full instrument simulation and event reconstruction, and including solar and atmospheric effects.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

BATSE observations of gamma-ray bursts

Gamma-ray bursts are being detected with unprecedented sensitivity by the Burst and Transient Source Experiment (BATSE) on the Compton Gamma Ray Observatory since its launch in April, 1991. The experiment is detecting about one gamma-ray burst per day. A brief description is presented of the on-orbit performance of BATSE, the methods of identification of bursts, and examples of the diverse time profiles of the gamma-ray bursts observed. The most significant finding thus far is the apparent isotropy of the bursts together with the observed inhomogeneity of the sources.

Fishman, Gerald J.↗

Automatically generated model for light alkene combustion

Light alkenes are common combustion intermediates for a variety of fuels. Therefore, understanding their oxidation and pyrolysis chemistry is key to building detailed mechanisms for heavier fuels. This work was focused on the development and evaluation of a detailed kinetic mechanism suitable for the combustion of light alkenes up to C 4 without the use of tuned parameters, instead, the parameter values come from first principles or direct measurements. The generated mechanism accurately estimates the laminar burning velocity (S u ) and ignition delay time (IDT) of light alkenes available in the literature, which represent fundamental combustion properties at a wide range of conditions. Because each parameter is thought to have a physically realistic value, not tuned to these measurements, the new model could be used as a sub-mechanism in models for other applications. The reaction network was generated with the open-source Reaction Mechanism Generator (RMG) software. Sensitivity analyses were performed under wide ranges of temperatures and pressures, allowing for the identification of the most impactful species and reactions. Based on these, a comprehensive thermochemistry database, including calculations on 550 molecules performed in this work at the CBS-QB3 level of theory, and a kinetic library, including theoretically-derived reaction rates retrieved from the literature, were built and used in the mechanism generation. The developed mechanism was compared against several existing detailed kinetic mechanisms for ethene, propene, 1-butene, 2-butene, and isobutene. Here, the newly generated model is the most accurate among the ones analyzed, in terms of fractional bias and normalized mean square error. Hence, this new model was used to analyze the chemistry of alkene combustion. Key rate coefficients were compared, to identify the cause of deviations between the models and possible areas for further improvements.

09 BIOMASS FUELS↗

WPEC SG50: Developing an Automatically Readable, Comprehensive and Curated Experimental Nuclear Reaction Database

The Organisation for Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) Working Party on International Nuclear Data Evaluation Co-operation (WPEC) subgroup (SG) 50 was formed in 2020 to develop an automatically readable, comprehensive and curated experimental nuclear reaction database. This database is called MEDUSAL (Machine-readable Experimental Data User Application & Library), and will draw from EXFOR. The EXFOR database preserves experimental nuclear reaction data true to its original documentation and information from the authors of the data. MEDUSAL will deviate from EXFOR by storing additional information from users of the data for their fields of work (evaluation, model development, validation, etc.). This includes expert judgment on the data sets, identification of data points as outliers, renormalization of the data to the newest monitor reactions, and estimations of missing uncertainty sources. The format for MEDUSAL is being developed to enable easy automatic parsing of large amounts of data. Here, we will summarize the use cases, high-level requirements and first steps towards developing the database MEDUSAL and the API to access it.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

KM3NeT

KM3NeT is a large research infrastructure, that will consist of a network of deep-sea neutrino telescopes in the Mediterranean Sea. The main objective of KM3NeT is the discovery and subsequent observation of high-energy neutrino sources in the Universe. A further physics perspective is the measurement of the mass hierarchy of neutrinos. A corresponding study, ORCA, is ongoing within KM3NeT. A cost effective technology for (very) large water Cherenkov detectors has been developed based on a new generation of low price 3-inch photo-multiplier tubes. Following the successful deployment and operation of two prototypes, the construction of the KM3NeT research infrastructure has started. The prospects of the different phases of the implementation of KM3NeT are summarised.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Characterizing a supernova’s standing accretion shock instability with neutrinos and gravitational waves

Here, we perform a novel multi-messenger analysis for the identification and parameter estimation of the Standing Accretion Shock Instability (SASI) in a core collapse supernova with neutrino and gravitational wave (GW) signals. In the neutrino channel, this method performs a likelihood ratio test for the presence of SASI in the frequency domain. For gravitational wave signals we process an event with a modified constrained likelihood method. Using simulated supernova signals, the properties of the Hyper-Kamiokande neutrino detector, and O3 LIGO Interferometric data, we produce the two-dimensional probability density distribution (PDF) of the SASI activity indicator and calculate the probability of detection P D as well as the false identification probability P FI . We discuss the probability to establish the presence of the SASI as a function of the source distance in each observational channel, as well as jointly. Compared to a single-messenger approach, the joint analysis results in P D (at P FI = 0.1) of SASI activities that is larger by up to ≈ 40% for a distance to the supernova of 5 kpc. We also discuss how accurately the frequency and duration of the SASI activity can be estimated in each channel separately. Our methodology is suitable for implementation in a realistic data analysis and a multi-messenger setting.

79 ASTRONOMY AND ASTROPHYSICS↗

Expression profiles of cell-wall related genes vary broadly between two common maize inbreds during stem development

The cellular machinery for cell wall synthesis and metabolism is encoded by members of large multi-gene families. Maize is both a genetic model for grass species and a potential source of lignocellulosic biomass from crop residues. Genetic improvement of maize for its utility as a bioenergy feedstock depends on identification of the specific gene family members expressed during secondary wall development in stems. High-throughput sequencing of transcripts expressed in developing rind tissues of stem internodes provided a comprehensive inventory of cell wall-related genes in maize ( Zea mays , cultivar B73). Of 1239 of these genes, 854 were expressed among the internodes at =95 reads per 20 M, and 693 of them at =500 reads per 20 M. Grasses have cell wall compositions distinct from non-commelinid species; only one-quarter of maize cell wall-related genes expressed in stems were putatively orthologous with those of the eudicot Arabidopsis. Using a slope-metric algorithm, five distinct patterns for sub-sets of co-expressed genes were defined across a time course of stem development. For the subset of genes associated with secondary wall formation, fifteen sequence motifs were found in promoter regions. The same members of gene families were often expressed in two maize inbreds, B73 and Mo17, but levels of gene expression between them varied, with 30% of all genes exhibiting at least a 5-fold difference at any stage. Although presence-absence and copy-number variation might account for much of these differences, fold-changes of expression of a CADa and a FLA11 gene were attributed to polymorphisms in promoter response elements. Large genetic variation in maize as a species precludes the extrapolation of cell wall-related gene expression networks even from one common inbred line to another. Elucidation of genotype-specific expression patterns and their regulatory controls will be needed for association panels of inbreds and landraces to fully exploit genetic variation in maize and other bioenergy grass species.

09 BIOMASS FUELS↗

Studies for the selection of fully contained muon neutrino CC events in the ICARUS T600 detector at Fermilab

The ICARUS T600 LAr-TPC detector has started its new physics runs in June 2022 at Fermilab within the SBN program. This detector is recording neutrino interactions from the Booster BNB neutrino beam in order to definitively clarify the open questions related to the possible existence of sterile neutrinos, as suggested by numerous observed experimental anomalies. In addition the neutrinos events recorded from the NuMI off-axis beam are under study in order to perform neutrino-Argon cross section measurements. At Fermilab, ICARUS is facing a challenging experimental condition: the detector is presently installed essentially at Earth surface where cosmic ray particles can become a serious source of background for the neutrino event search. This condition makes it necessary to deploy suitable automatic tools for the identification, selection, and measurement of the neutrino events among the millions of events triggered by cosmics. In this contribution, two automatic selection procedures devoted to the identification of fully contained muon neutrino interactions in the BNB neutrino beam will be presented, together with the first results of their application on simulated and on recently recorded events in the T600 detector.

Farnese, Christian [INFN, Padua] (ORCID:0000000163↗

Studies for the Selection of Fully Contained Muon Neutrino CC Events in the ICARUS T600 Detector at Fermilab

The ICARUS T600 LAr-TPC detector has started its new physics runs in June 2022 at Fermilab within the SBN program. This detector is recording neutrino interactions from the Booster BNB neutrino beam in order to definitively clarify the open questions related to the possible existence of sterile neutrinos, as suggested by numerous observed experimental anomalies. In addition the neutrinos events recorded from the NuMI off-axis beam are under study in order to perform neutrino-Argon cross section measurements. At Fermilab, ICARUS is facing a challenging experimental condition: the detector is presently installed essentially at Earth surface where cosmic ray particles can become a serious source of background for the neutrino event search. This condition makes it necessary to deploy suitable automatic tools for the identification, selection, and measurement of the neutrino events among the millions of events triggered by cosmics. In this contribution, two automatic selection procedures devoted to the identification of fully contained muon neutrino interactions in the BNB neutrino beam will be presented, together with the first results of their application on simulated and on recently recorded events in the T600 detector.

Farnese, Christian [INFN, Padua]↗

The search for extraterrestrial life: Recent developments; Proceedings of the Symposium, Boston University, MA, June 18-21, 1984

The conference presents papers on the history of the search for extraterrestrial life, the scientific rationale and methods used in the search for other planetary systems, the detection of distant planets with the Space Telescope, planetary searches using optical astrometric interferometers, and infrared spectral identification of complex organic molecules in interstellar grains. Also considered are universal protein ancestors from hydrogen cyanide and water, astronomical sources of polarized light and their role in determining molecular chirality on earth, the universal diagrams and life in the universe, the precambrian evolution of terrestrial life and a thermodynamic approach to the occurrance and appearance of galactic life forms. Papers are also presented on the Ohio Seti program, lunar reflections of terrestrial radio leakage, the multichannel spectrum analyzer, software implementation of detection algorithms for the MCSA, the Serendip II design, galactic colonization and competition in a young galactic disk, implications of ancient and future migrations, extraterrestrial intelligence, the ineviability and the possible structures of supercivilizations, planetary, interplanetary and interstellar organic matter, and universal aspects of biological evolution.

Papagiannis, M. D.↗

Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data

This technique enhances the detection capability of the autonomous Real-Nose system from MIT to detect odorants and their concentrations in noisy and transient environments. The lowcost, portable system with low power consumption will operate at high speed and is suited for unmanned and remotely operated long-life applications. A deterministic mathematical model was developed to detect odorants and calculate their concentration in noisy environments. Real data from MIT's NanoNose was examined, from which a signal conditioning technique was proposed to enable robust odorant detection for the RealNose system. Its sensitivity can reach to sub-part-per-billion (sub-ppb). A Space Invariant Independent Component Analysis (SPICA) algorithm was developed to deal with non-linear mixing that is an over-complete case, and it is used as a preprocessing step to recover the original odorant sources for detection. This approach, combined with the Cascade Error Projection (CEP) Neural Network algorithm, was used to perform odorant identification. Signal conditioning is used to identify potential processing windows to enable robust detection for autonomous systems. So far, the software has been developed and evaluated with current data sets provided by the MIT team. However, continuous data streams are made available where even the occurrence of a new odorant is unannounced and needs to be noticed by the system autonomously before its unambiguous detection. The challenge for the software is to be able to separate the potential valid signal from the odorant and from the noisy transition region when the odorant is just introduced.

Duong, Tuan A.↗