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At least 577 records · Page 32

Synergism of Saturn, Enceladus and Titan and Formation of HCNO Exobiological Molecules

Saturn as a system has two very exotic moons Titan and Enceladus. Titan with energy input from Saturn's magnetosphere, solar UV irradiation, and cosmic rays can make HCN based molecules as discussed in earlier paper by [1]. Space radiation effects at both moons, and as coupled by the Saturn magnetosphere could cause an unexpected series of events leading to the evolution of biological models at Titan composed of HCNO with oxygen as the new ingredient. The "Old Faithful" model by [2] suggests that Enceladus, highly irradiated by Saturn magnetospheric electrons, has episodic ejections of water vapor driven by radiolytic oxidation gas products into Saturn's magnetosphere. At Titan Cassini discovered 1) that keV oxygen ions, evidently from Enceladus, are bombarding Titan's upper atmosphere [3] and 2) the discovery of heavy positive and negative ions within Titan's upper atmosphere [4]. Initial models of heavy ion formation in Titan's upper atmosphere invoked polymerization of aromatics such as Benzenes and their radicals to make PAHs [5], while a more recent model by [6] has raised the possibility of carbon chains forming from the polymerization of acetylene and its radicals to eventually make fullerenes. Laboratory measurements indicate that fullerenes, which are hollow carbon shells, can trap the keV oxygen and with the clustering of fullerenes and possible mixture with PAHs, some with nitrogen molecules, can make the larger aerosols with oxygen within them. Then with further ionizing irradiation from cosmic rays deep in the atmosphere "tholin" molecules are produced with all the molecular components present from which organic molecules can form. Among the molecular components are amino acids, the fundamental building blocks of life as we know it. This process maybe a common chemical pathway, both at the system level and at the molecular level, to form prebiotic and perhaps even biotic molecules. Such processes can be occurring throughout our universe, such as molecular clouds in the ISM.

Sittler, Edward C., Jr.↗

Molecular-Based Optical Measurement Techniques for Transition and Turbulence in High-Speed Flow

High-speed laminar-to-turbulent transition and turbulence affect the control of flight vehicles, the heat transfer rate to a flight vehicle's surface, the material selected to protect such vehicles from high heating loads, the ultimate weight of a flight vehicle due to the presence of thermal protection systems, the efficiency of fuel-air mixing processes in high-speed combustion applications, etc. Gaining a fundamental understanding of the physical mechanisms involved in the transition process will lead to the development of predictive capabilities that can identify transition location and its impact on parameters like surface heating. Currently, there is no general theory that can completely describe the transition-to-turbulence process. However, transition research has led to the identification of the predominant pathways by which this process occurs. For a truly physics-based model of transition to be developed, the individual stages in the paths leading to the onset of fully turbulent flow must be well understood. This requires that each pathway be computationally modeled and experimentally characterized and validated. This may also lead to the discovery of new physical pathways. This document is intended to describe molecular based measurement techniques that have been developed, addressing the needs of the high-speed transition-to-turbulence and high-speed turbulence research fields. In particular, we focus on techniques that have either been used to study high speed transition and turbulence or techniques that show promise for studying these flows. This review is not exhaustive. In addition to the probe-based techniques described in the previous paragraph, several other classes of measurement techniques that are, or could be, used to study high speed transition and turbulence are excluded from this manuscript. For example, surface measurement techniques such as pressure and temperature paint, phosphor thermography, skin friction measurements and photogrammetry (for model attitude and deformation measurement) are excluded to limit the scope of this report. Other physical probes such as heat flux gauges, total temperature probes are also excluded. We further exclude measurement techniques that require particle seeding though particle based methods may still be useful in many high speed flow applications. This manuscript details some of the more widely used molecular-based measurement techniques for studying transition and turbulence: laser-induced fluorescence (LIF), Rayleigh and Raman Scattering and coherent anti-Stokes Raman scattering (CARS). These techniques are emphasized, in part, because of the prior experience of the authors. Additional molecular based techniques are described, albeit in less detail. Where possible, an effort is made to compare the relative advantages and disadvantages of the various measurement techniques, although these comparisons can be subjective views of the authors. Finally, the manuscript concludes by evaluating the different measurement techniques in view of the precision requirements described in this chapter. Additional requirements and considerations are discussed to assist with choosing an optical measurement technique for a given application.

Bathel, Brett F.↗

Data-Driven Operator Theoretic Methods for Phase Space Learning and Analysis

This paper uses data-driven operator theoretic approaches to explore the global phase space of a dynamical system. In this work, we defined conditions for discovering new invariant subspaces in the state space of a dynamical system starting from an invariant subspace based on the spectral properties of the Koopman operator. When the system evolution is known locally in several invariant subspaces in the state space of a dynamical system, a phase space stitching result is derived that yields the global Koopman operator. Additionally, in the case of equivariant systems, a phase space stitching result is developed to identify the global Koopman operator using the symmetry properties between the invariant subspaces of the dynamical system and time-series data from any one of the invariant subspaces. Finally, these results are extended to topologically conjugate dynamical systems; in particular, the relation between the Koopman tuple of topologically conjugate systems is established. The proposed results are demonstrated on several second-order nonlinear dynamical systems including a bistable toggle switch. Our method elucidates a strategy for designing discovery experiments: experiment execution can be done in many steps, and models from different invariant subspaces can be combined to approximate the global Koopman operator.

42 ENGINEERING↗

Radioisotope Identification with List-Mode Gamma-Ray Data

This work explores the potential of utilizing temporal data from gamma-ray detectors, known as list-mode data, to enhance radioisotope identification. Traditional identification methods, which rely on full gamma-ray spectrum analysis, often require long dwell times and struggle with spectra containing similarly spaced spectral peaks. We hypothesize that by leveraging the probabilistic nature of nuclear decay and the time-encoded information from decay sequences and interactions with surrounding materials, we can improve classification accuracy over static spectral analysis. This research examines the temporal content of list-mode data through exploratory data analysis via correlation discovery and qualitative distribution analysis. Additionally, we propose a probabilistic classification model that can utilize spectral data, temporal data, or both to determine if the incorporation of temporal information improves radioisotope identification. Our findings suggest that the temporal information present in list-mode gamma-ray data has merit and should be further investigated to develop more robust and optimal methods for utilizing this temporal information in applications requiring radioisotope identification.

List-mode data↗

CVEVOLVE

CVEvolve is an agentic AI system for autonomous algorithm discovery for scientific data processing. It creates workflows where large language model agents freely set up and configure development environments and evaluation harnesses, develop and improve data processing algorithms with designed exploration-exploitation balancing mechanisms, log history and findings in a structured database, and run holdout testing to ensure algorithm generalizability. CVEvolve offers a zero-code interface and does not require users to provide structured data and evaluation scripts.

Cherukara, MatthewJoseph [Argonne National Laborat↗

Discovery of Innovative Polymers for Next-Generation Gas-Separation Membranes using Interpretable Machine Learning

Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research on membrane technologies, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine-learning (ML) implementation for the discovery of innovative polymers with ideal separation performance. Specifically, multitask ML models are trained on available experimental data to link polymer chemistry to gas permeabilities of He, H2, O2, N2, CO2, and CH4. Here, we interpret the ML models and extract chemical heuristics for membrane design, through Shapley Additive exPlanations (SHAP) analysis. We then screen over nine million hypothetical polymers through our models and identify thousands of candidates that lie well above current performance upper bounds. Notably, we discover hundreds of never-before-seen ultrapermeable polymer membranes with O2 and CO2 permeability greater than 104 and 105 Barrer, respectively. These hypothetical polymers are capable of overcoming undesirable trade-off relationship between permeability and selectivity, thus significantly expanding the currently limited library of polymer membranes for highly efficient gas separations. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.

Yang, Jason↗

Monsoon Extremes: Impacts, Metrics, and Synoptic-Scale Drivers

This project was led by UC Berkeley with a subcontract to UC Davis and collaborative funding at the Lawrence Berkeley National Lab (LBNL). It produced new understanding of transient atmospheric disturbances in monsoon regions, the precipitation extremes they produce, and the sensitivity of precipitation and monsoon winds to fine-scale orography (i.e., the narrow mountain ranges that are difficult to represent in conventional Earth system models). Fundamental research undertaken as part of this project led to discovery of new mechanisms that control the generation of extreme weather events and that govern the spatial patterns of intense precipitation in monsoon climates—including the North American monsoon. These research accomplishments are summarized below and documented in a series of 23 publications, 20 of which were led by project personnel (the others were collaborative work led by staff of other projects). One of the publications produced by this project was in Nature, where it was selected for the main cover image, and another was in PNAS. The project also produced two datasets and a tracking algorithm, both of which are publicly available and listed below. The project trained three Ph.D. students and four postdoctoral scientists, the vast majority of whom have progressed to more advanced positions in their scientific careers. Although the university funding for this project ended in 2022, the LBNL component of the project proceeded for almost one year longer; this report is being provided after completion of all components of the project.

54 ENVIRONMENTAL SCIENCES↗

Bridging the Gap Between Astronomical Datasets: From Proof-of-Concept to AI Model Deployment with Domain Adaptation

Artificial Intelligence is transforming astrophysics, from studying stars and galaxies to analyzing cosmic large-scale structures. However, a critical challenge arises when AI models trained on simulations or past observational data are applied to new observation— leading to domain shifts, reduced robustness, and increased uncertainty of model predictions. This talk will explore these issues, highlighting examples such as galaxy morphology classification and cosmological parameter inference, where AI struggles to adapt across different datasets. We will discuss domain adaptation as a strategy to improve model generalization and mitigate biases—essential for making AI-driven discoveries reliable. Notably, these challenges extend beyond astrophysics, affecting AI applications across physics and other scientific domains. Addressing them is essential for maximizing AI’s impact in advancing scientific research.

Ćiprijanović, Aleksandra [Fermilab]↗

Editorial: Structure and mechanism of microbial membrane active transporters

Membrane active transporters play essential roles in microbial physiology. They couple energy transduction to conformational changes that drive translocation of nutrients, substrates and ions, as well as molecular communication. The structure and function of microbial membrane active transporters are highly diverse. Typical examples include the primary active transporters in the ATP-binding cassette (ABC) superfamily (Thomas and Tampé, 2020; Davidson et al., 2008; Locher et al., 2002), the secondary active transporters in the Major Facilitator Superfamily (MFS) (Drew et al., 2021; Kaback and Guan, 2019), and the ligand-gated porins in the TonB-dependent transporter (TBDT) family (Klebba et al., 2021). As structural, proteogenomic, and computational methods advance, active transporters are increasingly recognized as dynamic molecular machines whose mechanisms can now be visualized and modeled with remarkable precision, building on decades of biochemical and biophysical discovery that established the foundations of this field. The transporter studies recruited in this Research Topic provide us with new insights into the field including structure-function of sugar transporters in yeast, structural prediction and classification of ABC complexes in Bacillus subtilis, Type VI Secretion System (T6SS) in Bacteroides fragilis, amino acids uptake in Escherichia coli and bacterial spore germination.

mechanism↗

Chemical Complexity of Phosphorous-bearing Species in Various Regions of the Interstellar Medium

Phosphorus-related species are not known to be as omnipresent in space as hydrogen, carbon, nitrogen, oxygen, and sulfur-bearing species. Astronomers spotted very few P-bearing molecules in the interstellar medium and circumstellar envelopes. Limited discovery of the P-bearing species imposes severe constraints in modeling the P-chemistry. In this paper, we carry out extensive chemical models to follow the fate of P-bearing species in diffuse clouds, photon-dominated or photodissociation regions (PDRs), and hot cores/corinos. We notice a curious correlation between the abundances of PO and PN and atomic nitrogen. Since N atoms are more abundant in diffuse clouds and PDRs than in the hot core/corino region, PO/PN reflects <1 in diffuse clouds, ≪1 in PDRs, and >1 in the late warm-up evolutionary stage of the hot core/corino regions. During the end of the post-warm-up stage, we obtain PO/PN > 1 for hot core and <1 for its low-mass analog. We employ a radiative transfer model to investigate the transitions of some of the P-bearing species in diffuse cloud and hot core regions and estimate the line profiles. Our study estimates the required integration time to observe these transitions with ground-based and space-based telescopes. We also carry out quantum chemical computation of the infrared features of PH{sub 3}, along with various impurities. We notice that SO{sub 2} overlaps with the PH{sub 3} bending-scissoring modes around ∼1000–1100 cm{sup −1}. We also find that the presence of CO{sub 2} can strongly influence the intensity of the stretching modes around ∼2400 cm{sup −1} of PH{sub 3}.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Infrared observations of asteroids from earth and space

Infrared reflectances at wavelength between 1 and 4 micrometers are used for determining asteroid surface mineralogy, surface composition, diameters, and albedos. Thermal models were developed for analyzing infrared observations at longer wavelengths. The discovery of a spectral feature due to water of hydration on Ceres seems to contradict the mineralogy inferred from spectrophotometry.

Matson, D. L.↗

On-Board Propulsion System Analysis of High Density Propellants

The impact of the performance and density of on-board propellants on science payload mass of Discovery Program class missions is evaluated. A propulsion system dry mass model, anchored on flight-weight system data from the Near Earth Asteroid Rendezvous mission is used. This model is used to evaluate the performance of liquid oxygen, hydrogen peroxide, hydroxylammonium nitrate, and oxygen difluoride oxidizers with hydrocarbon and metal hydride fuels. Results for the propellants evaluated indicate that the state-of-art, Earth Storable propellants with high performance rhenium engine technology in both the axial and attitude control systems has performance capabilities that can only be exceeded by liquid oxygen/hydrazine, liquid oxygen/diborane and oxygen difluoride/diborane propellant combinations. Potentially lower ground operations costs is the incentive for working with nontoxic propellant combinations.

Schneider, Steven J.↗

Northern Hemisphere Gullies on Mars: Analysis of Spacecraft Data and Implications for Formation Mechanisms

The origin of geologically recent gullies on Mars has remained controversial since the discovery of these features by Malin and Edgett in 2000. Numerous models have been proposed which invoke various physical processes as well as various agents of erosion to explain the origin of the Martian gullies. Hypotheses to explain the formation of the gullies invoke shallow liquid water aquifers, deep liquid water aquifers, melting ground ice, snowmelt, dry landslides, and carbon dioxide aquifers. We test the validity of such gully formation mechanisms by analyzing data from the Mars Global Surveyor and Mars Odyssey spacecrafts to uncover trends in the dimensional and physical properties of the gullies and their surrounding terrain. A similar study has previously been completed for gullies located in the southern hemisphere of Mars. The work presented here focuses exclusively on gullies in the northern hemisphere based on the identification of 136 Mars Orbiter Camera (MOC) images containing clear evidence of gully landforms, distributed in the northern mid and high latitudes. These sites have been analyzed in combination with Mars Orbiter Laser Altimeter (MOLA), Thermal Emission Spectrometer (TES), and Gamma Ray Spectrometer (GRS) data to provide quantitative measurements of numerous gully characteristics. Parameters measured include apparent source depth and distribution, vertical and horizontal dimensions, slopes, compass orientations, near-surface ice content, and factors controlling present-day climatic conditions.

Heldmann, J. L.↗

Analyzers Measure Greenhouse Gases, Airborne Pollutants

In complete darkness, a NASA observatory waits. When an eruption of boiling water billows from a nearby crack in the ground, the observatory s sensors seek particles in the fluid, measure shifts in carbon isotopes, and analyze samples for biological signatures. NASA has landed the observatory in this remote location, far removed from air and sunlight, to find life unlike any that scientists have ever seen. It might sound like a scene from a distant planet, but this NASA mission is actually exploring an ocean floor right here on Earth. NASA established a formal exobiology program in 1960, which expanded into the present-day Astrobiology Program. The program, which celebrated its 50th anniversary in 2010, not only explores the possibility of life elsewhere in the universe, but also examines how life begins and evolves, and what the future may hold for life on Earth and other planets. Answers to these questions may be found not only by launching rockets skyward, but by sending probes in the opposite direction. Research here on Earth can revise prevailing concepts of life and biochemistry and point to the possibilities for life on other planets, as was demonstrated in December 2010, when NASA researchers discovered microbes in Mono Lake in California that subsist and reproduce using arsenic, a toxic chemical. The Mono Lake discovery may be the first of many that could reveal possible models for extraterrestrial life. One primary area of interest for NASA astrobiologists lies with the hydrothermal vents on the ocean floor. These vents expel jets of water heated and enriched with chemicals from off-gassing magma below the Earth s crust. Also potentially within the vents: microbes that, like the Mono Lake microorganisms, defy the common characteristics of life on Earth. Basically all organisms on our planet generate energy through the Krebs Cycle, explains Mike Flynn, research scientist at NASA s Ames Research Center. This metabolic process breaks down sugars for energy to fuel cellular functions. "We think this chemical process did not exist when life first formed on Earth," he says, "because it is based on oxygen being available, and there was little oxygen available on the early Earth." It is possible that there are anaerobic regions beneath the sea floor in which life forms like those early non-Krebs Cycle microbes may yet exist. To detect and potentially collect samples of life emerging from hydrothermal vents, Flynn and his colleagues created Medusa, a multi-sensor instrument designed for long-term observation of diked vents on the ocean floor. When the vents erupt, Medusa assesses indicators of life within the expelled water. If the results are positive, the observatory collects samples and detaches from the ocean floor, making the long journey to the surface for retrieval by scientists. One of the indicators Medusa measures is the ratio of carbon isotopes in the water, namely carbon-12 and carbon-13. Living organisms preferentially take up carbon-12, Flynn says, so examining the ratio of these isotopes can help to determine the source of carbon in an environment as either biological or non-biological. "On Mars, there is evidence of localized methane in the atmosphere, and that methane could come from biological sources or from geochemical ones," Flynn says. "Determining the background planetary carbon isotope ratios and then evaluating the specific carbon ratios in this methane would help to determine how it was formed." A long-duration observatory similar to Medusa could one day provide essential evidence for or against the presence of life on the Red Planet or beneath the ice-crusted oceans of Europa.

Source record↗

Foundational Women in Planetary Geomorphology: Some Contributions in Fluvial, Aeolian, and (Cryo)Volcanic Subdisciplines

Despite undeserved challenges to participation in the field of planetary geomorphology, women have made significant contributions in the fluvial, aeolian, and (cryo)volcanic subdisciplines. In this work, some women—in particular, women of color—are highlighted to show a part of these foundational contributions. We focused on women scientists who were working in the latter half of the 20th century, a revolutionary time for terrestrial geomorphology and the inception of the discipline of planetary geomorphology. We also focused on women working in our scientific subdisciplines so that we could provide proper context for their work. These contributions have occurred both as discoveries in terrestrial geomorphology leading to follow-on discoveries in planetary geomorphology and through serving as educators and role models. With women increasingly achieving positions of influence both in the geo- and planetary sciences as in American society, this research allows us to celebrate these contributions of women and particularly women of color while looking forward to a more complete record of their past contributions and greater future achievements.

Devon M Burr↗

The fate of organic carbon in marine sediments - New insights from recent data and analysis

Organic carbon in marine sediments is a critical component of the global carbon cycle, and its degradation influences a wide range of phenomena, including the magnitude of carbon sequestration over geologic timescales, the recycling of inorganic carbon and nutrients, the dissolution and precipitation of carbonates, the production of methane and the nature of the seafloor biosphere. Although much has been learned about the factors that promote and hinder rates of organic carbon degradation in natural systems, the controls on the distribution of organic carbon in modern and ancient sediments are still not fully understood. In this review, we summarize how recent findings are changing entrenched perspectives on organic matter degradation in marine sediments: a shift from a structurally-based chemical reactivity viewpoint towards an emerging acceptance of the role of the ecosystem in organic matter degradation rates. That is, organic carbon has a range of reactivities determined by not only the nature of the organic compounds, but by the biological, geochemical, and physical attributes of its environment. This shift in mindset has gradually come about due to a greater diversity of sample sites, the molecular revolution in biology, discoveries concerning the extent and limits of life, advances in quantitative modeling, investigations of ocean carbon cycling under a variety of extreme paleo-conditions (e.g. greenhouse environments, euxinic/anoxic oceans), the application of novel analytical techniques and interdisciplinary efforts. Adopting this view across scientific disciplines will enable additional progress in understanding how marine sediments influence the global carbon cycle.

Organic carbon↗

DOE Repository Metadata Profile (DRMP): A Metadata Framework for Advancing Interoperability and AI Readiness Across Scientific Repositories

The Department of Energy (DOE) funds a diverse and distributed ecosystem of repositories that steward scientific data, publications, and software across its research programs, user facilities, and national laboratories. While significant progress has been made in standardizing dataset-level metadata, the metadata describing repositories themselves (their identity, governance, access interfaces, policies, and technical capabilities) remains inconsistent and fragmented across DOE-funded systems. This variability limits discoverability, interoperability, automated validation, and AI-driven analysis, all of which are increasingly essential for modern scientific workflows. To address this gap, the DOE Data Curation Working Group (DCWG) developed the DOE Repository Metadata Profile (DRMP). The DRMP is a practical, community-driven framework that defines how repositories can describe themselves in a consistent, machine-actionable, and scalable manner. The DRMP is not a new metadata schema. Instead, it is a mapping profile and structured element set capturing the essential characteristics of DOE repositories. It harmonizes repository-level metadata across six widely adopted community schemas: RE3Data; DCAT-US v3; Schema.org; Dublin Core; DataCite 4.6; and PREMIS 3.0. This harmonization eliminates reinvention and enables interoperability within DOE and across the broader scientific ecosystem. A core objective of the DRMP is to reduce burden on repositories by allowing them to reuse their existing metadata through a Rosetta-style crosswalk rather than redesigning local implementations. The profile introduces a three-level conformance model that supports incremental adoption: • Level 1 – Minimum Viable Record (MVR): foundational identification elements required for workflows, project registration, and basic repository presence. • Level 2 – Interoperable: structured metadata enabling alignment with national and international discovery systems. • Level 3 – AI-Ready: enhanced provenance, policy transparency, fixity, semantic context, and capabilities that support automated reasoning, model training governance, and machine-assisted curation. To support implementation, the DRMP includes JSON Schema definitions, OpenAPI patterns, and MCP templates that allow repositories to publish machine-readable metadata directly within existing platforms. These resources are modular and lightweight, enabling adoption without major architectural change. Adopting the DRMP enables repositories to: • Enhance discoverability and interoperability by aligning identifiers, classifications, and descriptive elements across widely used schema standards. • Support federated discovery and cross-registration across DOE systems, Data.gov, and international catalogs. • Enable AI agents and workflow orchestration systems to interpret repository-level metadata within the American Science Cloud (AmSC) through Model Context Protocol (MCP)-based context publication. • Demonstrate alignment with DOE’s open science, stewardship, and FAIR data priorities. This guidance represents a community-driven step forward. Through voluntary adoption and continued feedback, the DRMP advances a cohesive, machine-actionable description of DOE repositories that supports FAIR data practices, preparing the infrastructure for AI-enabled research, and strengthening the discoverability and reuse of DOE’s scientific outputs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

XXVIIth International Conference on Supersymmetry and Unification of Fundamental Interactions (SUSY 2019) (Final Report)

Supersymmetry (SUSY) is one of most elegant extensions of the Standard Model (SM) and explains the puzzles of the SM by providing a candidate to explain the dark matter content of the universe, allowing scientists to understand the origin of the electroweak scale requiring the top mass to be around 170 GeV and leading to the unification of forces at a grand unified scale. Further the minimal supersymmetric standard model (MSSM) predicts the Higgs boson mass to be less than 135 GeV. The discovery of the Higgs Boson with mass around 125 GeV at the LHC has provided a major support to SUSY ideas. Searches for SUSY are ongoing at the Large Hadron Collider (LHC). Direct and indirect dark matter experiments are searching for a particle dark matter candidate which arises most naturally in SUSY models. Proton decay predicted by SUSY grand unified theories is being searched for at deep underground experiments. In addition, recent advances in neutrino and dark matter physics, observational astrophysics, precision cosmology and the promising new window into the cosmos opened by the direct detection of gravitational waves, have brought new ideas on the potential connections between new fundamental particles and our understanding of their impact on the early universe and its evolution. At present, the major questions include: Is SUSY still the best candidate for models beyond the SM? Do we have any well motivated alternative to SUSY? Have we exhausted all possibilities to search for new physics at high and low energy scales? XXVIIth International Conference on Supersymmetry and Unification of Fundamental Interactions (SUSY 2019), hosted by Texas A&M University – Corpus Christi during May 20-24, 2019, provided a unique venue to discus and understand the status of SUSY, connection between particle physics and cosmology, supersymmetry and its alternative, Higgs sector, neutrino sector, flavor sector, dark matter, electroweak phase transition, astroparticle physics, gravitational waves and string theory. Discussion of results from the LHC, recent neutrino experiments and observations, direct and indirect dark matter detection experiments, detection of gravitational waves, data from particle colliders, as well as measurements of the CMB and Large Scale Structure were an integral part of SUSY 2019. To ensure the younger participants will benefit from the conference the most, the conference was preceded by the 4 day long pre-SUSY summer school for graduate students and postdocs. The invited speakers were leading scientists in the fields of SUSY interest. The school took place on Texas A&M University – Corpus Christi campus during the week prior the SUSY 2019 conference (May 15 – 18, 2019). Since its inception in 1993, SUSY has become one of the most important and widely attended international meetings in high energy physics, devoted to new ideas in fundamental particle physics. SUSY 2019 brought together approximately 250 scientists, theorists, phenomenologists, experimentalists and cosmologists, (including over 60 graduate students and 70 postdocs) representing 22 nations: Australia, Belgium, Canada, Chile, China, Colombia, France, Germany, India, Italy, Japan, Mexico, Peru, Portugal, Romania, South Korea, Spain, Sweden, Switzerland, Taiwan, United Kingdom and United States. SUSY 2019 provided a stimulating venue for the exchange of scientific ideas among experts in dark matter, neutrino physics, particle physics, astrophysics and cosmology. The following scientific topics were delivered during SUSY 2019 in form of 44 plenary talks and over 200 parallel talks: Unification of Forces; Electroweak, Top and Higgs Physics; Precision Calculations and MC tools; BSM in Flavor Physics; Neutrino Masses: Models and Phenomenology; Cosmology and Gravitational Waves; Dark Matter, Astroparticle Physics; Formal Field Theory and Strings; Alternatives to Supersymmetry; Quantum Information: Machine Learning/Big Data. 28 talks were given during the pre-SUSY program related to the following topics: Neutrino Physics; Big Data; Collider Physics & SUSY; String Phenomenology; Cosmology; Dark Matter; SUSY Models and Phenomenology

43 PARTICLE ACCELERATORS↗