Search

Solar flares and coronal mass ejections are interrelated phenomena that together are known as solar eruptive events. These are the main drivers of space weather and understanding their origins is a primary goal of Heliophysics. In this white paper, we advocate for the allocation of sufficient resources to bring together experts in observations and modeling to construct and test next generation data-driven models of solar eruptive events. We identify the key components necessary for constructing comprehensive end-to-end models including global scale 3D MHD resolving magnetic field evolution and reconnection, small scale simulations of particle acceleration in reconnection exhausts, kinetic scale transport of flare-accelerated particles into the lower solar atmosphere, and the radiative and hydrodynamics responses of the solar atmosphere to flare heating. Using this modeling framework, long-standing questions regarding how solar eruptive events release energy, accelerate particles, and heat plasma can be explored. To address open questions in solar flare physics, we recommend that NASA and NSF provide sufficient research and analysis funds to bring together a large body of researchers and numerical tools to tackle the end-to-end modeling framework that we outline. Current dedicated theory and modeling funding programs are relatively small scale and infrequent; funding agencies must recognize that modern space physics demands the use of both observations and modeling to make rapid progress., Comment: White paper submitted to the Decadal Survey for Solar and Space Physics (Heliophysics) 2024-2033; 9 pages, 4 figures

Understanding the nature of energetic particles in the solar atmosphere is one of the most important outstanding problems in heliophysics. Flare-accelerated particles compose a huge fraction of the flare energy budget; they have large influences on how events develop; they are an important source of high-energy particles found in the heliosphere; and they are the single most important corollary to other areas of high-energy astrophysics. Despite the importance of this area of study, this topic has in the past decade received only a small fraction of the resources necessary for a full investigation. For example, NASA has selected no new Explorer-class instrument in the past two decades that is capable of examining this topic. The advances that are currently being made in understanding flare-accelerated electrons are largely undertaken with data from EOVSA (NSF), STIX (ESA), and NuSTAR (NASA Astrophysics). This is despite the inclusion in the previous Heliophysics decadal survey of the FOXSI concept as part of the SEE2020 mission, and also despite NASA's having invested heavily in readying the technology for such an instrument via four flights of the FOXSI sounding rocket experiment. Due to that investment, the instrumentation stands ready to implement a hard X-ray mission to investigate flare-accelerated electrons. This white paper describes the scientific motivation for why this venture should be undertaken soon., Comment: White paper submitted to the Decadal Survey for Solar and Space Physics (Heliophysics) 2024-2033; 15 pages, 5 figures

The climate crisis and the degradation of the world's ecosystems require humanity to take immediate action. The international scientific community has a responsibility to limit the negative environmental impacts of basic research. The HECAP+ communities (High Energy Physics, Cosmology, Astroparticle Physics, and Hadron and Nuclear Physics) make use of common and similar experimental infrastructure, such as accelerators and observatories, and rely similarly on the processing of big data. Our communities therefore face similar challenges to improving the sustainability of our research. This document aims to reflect on the environmental impacts of our work practices and research infrastructure, to highlight best practice, to make recommendations for positive changes, and to identify the opportunities and challenges that such changes present for wider aspects of social responsibility., Comment: 158 pages, 21 figures; comments welcome. Revisions included in Version 2.0 are detailed on page 3 of the pdf. If you would like to endorse this document please visit: https://sustainable-hecap-plus.github.io/. An HTML version of this document is available at: https://sustainable-hecap-plus.github.io/

Solar flares are among the most powerful and disruptive events in our solar system, however the physical mechanisms driving and transporting this energetic release are not fully understood. An important signature associated with flare energy release is highly variable emission on timescales of sub-seconds to minutes which often exhibit oscillatory behaviour, features collectively known as quasi-periodic pulsations (QPPs). To fully identify the driving mechanism of QPPs, exploit their potential as a diagnostic tool, and incorporate them into our understanding of solar and stellar flares, new observational capabilities and initiatives are required. There is a clear community need for flare-focused, rapid cadence, high resolution, multi-wavelength imaging of the Sun, with high enough sensitivity and dynamic range to observe small fluctuations in intensity in the presence of a large overall intensity. Furthermore, multidisciplinary funding and initiatives are required to narrow the gap between numerical models and observations. QPPs are direct signatures of the physics occurring in flare magnetic reconnection and energy release sites and hence are critical to include in a unified flare model. Despite significant modelling and theoretical work, no single mechanism or model can fully explain the presence of QPPs in flares. Moreover, it is also likely that QPPs fall into different categories that are produced by different mechanisms. At present we have insufficient information to observationally distinguish between mechanisms. The motivation to understand QPPs is strengthened by the geo-effectiveness of flares on the Earth's ionosphere, and by the fact that stellar flares exhibit similar QPP signatures. QPPs present a golden opportunity to better understand flare physics and exploit the solar-stellary analogy, benefiting both astrophysics, heliophysics, and the solar-terrestrial connection., Comment: White paper submitted to the Decadal Survey for Solar and Space Physics (Heliophysics) 2024-2033. 8 pages, 3 figures, 1 table

Our current sampling of the near-Earth space environment is wholly insufficient to measure the highly variable processes therein and make predictions on par with lower atmospheric weather. We sketch out the scientific rationale for a network of radio instruments delivering dense observations of the near-Earth space environment and the broad steps necessary to implement wide-scale coverage in the next 30 years., Comment: Heliophysics 2050 Workshop

Solar sails enable missions to observe the solar environment from unique vantage points, such as sustained observations away from the Sun-Earth line; sub-L1 station keeping; high inclination solar orbits; Earth polar-sitting and polar-viewing observatories; fast transit missions to study heliosphere to interstellar medium transition, as well as missions of interest across a broad user community. Recent and planned demonstration missions make this technology ready for use on near-term science missions., Comment: Heliophysics 2050 White Paper

We recommend that NASA maintain and fund science platforms that enable interactive and scalable data analysis in order to maximize the scientific return of data collected from space-based instruments., Comment: Heliophysics 2050 White Paper

Traditionally, data analysis and theory have been viewed as separate disciplines, each feeding into fundamentally different types of models. Modern deep learning technology is beginning to unify these two disciplines and will produce a new class of predictively powerful space weather models that combine the physical insights gained by data and theory. We call on NASA to invest in the research and infrastructure necessary for the heliophysics' community to take advantage of these advances., Comment: Heliophysics 2050 White Paper

The fundamental nature of Dark Matter is a central theme of the Snowmass 2021 process, extending across all Frontiers. In the last decade, advances in detector technology, analysis techniques and theoretical modeling have enabled a new generation of experiments and searches while broadening the types of candidates we can pursue. Over the next decade, there is great potential for discoveries that would transform our understanding of dark matter. In the following, we outline a road map for discovery developed in collaboration among the Frontiers. A strong portfolio of experiments that delves deep, searches wide, and harnesses the complementarity between techniques is key to tackling this complicated problem, requiring expertise, results, and planning from all Frontiers of the Snowmass 2021 process., Comment: 10 pages, 5 figures. Version prepared for inclusion in the Snowmass Book. Extended version at arXiv:2210.01770. v2: fixed authors and affiliations

The Snowmass 2021 strategic planning process provided an essential opportunity for the United States high energy physics and astroparticle (HEPA) community to come together and discuss upcoming physics goals and experiments. As this forward-looking perspective on the field often reaches far enough into the future to surpass the timescale of a single career, consideration of the next generation of physicists is crucial. The 2021 Snowmass Early Career (SEC) organization aimed to unite this group, with the purpose of both educating the newest generation of physicists while informing the senior generation of their interests and opinions. SEC is the latest in a series of the previously dubbed "Snowmass Young" organizations, from 2013 and 2001. This iteration has expanded on these efforts to significantly increase involvement and broaden the representation of the early career community in the process. Early career physicists are the future of the field. They will design, build, and operate next-generation experiments, and put in the work to usher in new discoveries. They are also disproportionately involved in work to improve the climate within HEPA. This document summarizes the work of SEC in consolidating a huge variety of physics perspectives and community opinions towards a bright, strategic future., Comment: 27 pages, 11 figures. arXiv admin note: substantial text overlap with arXiv:2203.07328

The fundamental nature of Dark Matter is a central theme of the Snowmass 2021 process, extending across all frontiers. In the last decade, advances in detector technology, analysis techniques and theoretical modeling have enabled a new generation of experiments and searches while broadening the types of candidates we can pursue. Over the next decade, there is great potential for discoveries that would transform our understanding of dark matter. In the following, we outline a road map for discovery developed in collaboration among the frontiers. A strong portfolio of experiments that delves deep, searches wide, and harnesses the complementarity between techniques is key to tackling this complicated problem, requiring expertise, results, and planning from all Frontiers of the Snowmass 2021 process., Comment: v3: fixed authorlist (on arXiv only)

This is the Snowmass2021 Energy Frontier (EF) Beyond the Standard Model (BSM) report. It combines the EF topical group reports of EF08 (Model-specific explorations), EF09 (More general explorations), and EF10 (Dark Matter at Colliders). The report includes a general introduction to BSM motivations and the comparative prospects for proposed future experiments for a broad range of potential BSM models and signatures, including compositeness, SUSY, leptoquarks, more general new bosons and fermions, long-lived particles, dark matter, charged-lepton flavor violation, and anomaly detection., Comment: 108 pages + 38 pages references and appendix, 37 figures, Report of the Topical Group on Beyond the Standard Model Physics at Energy Frontier for Snowmass 2021. The first nine authors are the Conveners, with Contributions from the other authors

Cosmic Probes of Fundamental Physics take two primary forms: Very high energy particles (cosmic rays, neutrinos, and gamma rays) and gravitational waves. Already today, these probes give access to fundamental physics not available by any other means, helping elucidate the underlying theory that completes the Standard Model. The last decade has witnessed a revolution of exciting discoveries such as the detection of high-energy neutrinos and gravitational waves. The scope for major developments in the next decades is dramatic, as we detail in this report., Comment: Report of theTopical Group on Cosmic Probes of Fundamental Physics, for the U.S. decadal Particle Physics Planning Exercise (Snowmass 2021)

The mechanism(s) driving the early- and late-time accelerated expansion of the Universe represent one of the most compelling mysteries in fundamental physics today. The path to understanding the causes of early- and late-time acceleration depends on fully leveraging ongoing surveys, developing and demonstrating new technologies, and constructing and operating new instruments. This report presents a multi-faceted vision for the cosmic survey program in the 2030s and beyond that derives from these considerations. Cosmic surveys address a wide range of fundamental physics questions, and are thus a unique and powerful component of the HEP experimental portfolio., Comment: Submitted to the Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021); Topical Group Report for CF06 (Cosmic Frontier Topical Group on Dark Energy and Cosmic Acceleration: Complementarity of Probes and New Facilities

Cosmological and astrophysical observations currently provide the only robust, positive evidence for dark matter. Cosmic probes of dark matter, which seek to determine the fundamental properties of dark matter through observations of the cosmos, have emerged as a promising means to reveal the nature of dark matter. This report summarizes the current status and future potential of cosmic probes to inform our understanding of the fundamental nature of dark matter in the coming decade., Comment: Report of the CF3 Topical Group for Snowmass 2021; 35 pages, 10 figures, many references. V3 updates Fig 3-2 and the author list

This report summarizes the findings of the CF1 Topical Subgroup to Snowmass 2021, which was focused on particle dark matter. One of the most important scientific goals of the next decade is to reveal the nature of dark matter (DM). To accomplish this goal, we must delve deep, to cover high priority targets including weakly-interacting massive particles (WIMPs), and search wide, to explore as much motivated DM parameter space as possible. A diverse, continuous portfolio of experiments at large, medium, and small scales that includes both direct and indirect detection techniques maximizes the probability of discovering particle DM. Detailed calibrations and modeling of signal and background processes are required to make a convincing discovery. In the event that a candidate particle is found through different means, for example at a particle collider, the program described in this report is also essential to show that it is consistent with the actual cosmological DM. The US has a leading role in both direct and indirect detection dark matter experiments -- to maintain this leading role, it is imperative to continue funding major experiments and support a robust R\&D program., Comment: Submitted 30 pages, 11 figures, many references, Report of the CF1 Topical Group for Snowmass 2021

We summarize progress made in theoretical astrophysics and cosmology over the past decade and areas of interest for the coming decade. This Report is prepared as the TF09 "Astrophysics and Cosmology" topical group summary for the Theory Frontier as part of the Snowmass 2021 process., Comment: 57 pages

The particle and radiation environment in cis-lunar space is becoming increasingly important as more hardware and human assets occupy various orbits around the Earth and space exploration efforts turn to the Moon and beyond. Since 2020, the total number of satellites in orbit has approximately doubled, highlighting the growing dependence on space-based resources. Through NASA's upcoming Artemis missions, humans will spend more time in cis-lunar space than ever before supported by the expansive infrastructure required for extended missions to the Moon, including a surface habitat, a communications network, and the Lunar Gateway. This paper focuses on galactic cosmic rays (GCRs) and solar energetic particles (SEPs) that create a dynamic and varying radiation environment within these regions. GCRs are particles of hundreds of MeV/nucleon (MeV/n) and above generated in highly energetic astrophysical environments in the Milky Way Galaxy, such as supernovae and pulsars, and beyond. These particles impinge isotropically on the heliosphere and are filtered down to 1 AU, experiencing modulation in energy and intensity on multiple timescales, from hours to decades, due to the solar magnetic cycle and other transient phenomena. SEPs are particles with energies up to thousands of MeV/n that are accelerated in eruptive events on the Sun and flood the inner heliosphere causing sudden and drastic increases in the particle environment on timescales of minutes to days. This paper highlights a current and prospective future gap in energetic particle measurements in the hundreds of MeV/n. We recommend key observations near Earth to act as a baseline as well as distributed measurements in the heliosphere, magnetosphere, and lunar surface to improve the scientific understanding of these particle populations and sources., Comment: 14 pages, 1 figure. White Paper submitted to Decadal Survey for Solar and Space Physics (Heliophysics) 2024-2033

We summarize evidence that multiple supernovae exploded within 100 pc of Earth in the past few Myr. These events had dramatic effects on the heliosphere, compressing it to within ~20 au. We advocate for cross-disciplinary research of nearby supernovae, including on interstellar dust and cosmic rays. We urge for support of theory work, direct exploration, and study of extrasolar astrospheres., Comment: White paper submitted to the Solar and Space Physics 2024 Decadal Survey

Estimating uncertainty is at the core of performing scientific measurements in HEP: a measurement is not useful without an estimate of its uncertainty. The goal of uncertainty quantification (UQ) is inextricably linked to the question, "how do we physically and statistically interpret these uncertainties?" The answer to this question depends not only on the computational task we aim to undertake, but also on the methods we use for that task. For artificial intelligence (AI) applications in HEP, there are several areas where interpretable methods for UQ are essential, including inference, simulation, and control/decision-making. There exist some methods for each of these areas, but they have not yet been demonstrated to be as trustworthy as more traditional approaches currently employed in physics (e.g., non-AI frequentist and Bayesian methods). Shedding light on the questions above requires additional understanding of the interplay of AI systems and uncertainty quantification. We briefly discuss the existing methods in each area and relate them to tasks across HEP. We then discuss recommendations for avenues to pursue to develop the necessary techniques for reliable widespread usage of AI with UQ over the next decade., Comment: Submitted to the Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021)

The growing role of data science (DS) and machine learning (ML) in high-energy physics (HEP) is well established and pertinent given the complex detectors, large data, sets and sophisticated analyses at the heart of HEP research. Moreover, exploiting symmetries inherent in physics data have inspired physics-informed ML as a vibrant sub-field of computer science research. HEP researchers benefit greatly from materials widely available materials for use in education, training and workforce development. They are also contributing to these materials and providing software to DS/ML-related fields. Increasingly, physics departments are offering courses at the intersection of DS, ML and physics, often using curricula developed by HEP researchers and involving open software and data used in HEP. In this white paper, we explore synergies between HEP research and DS/ML education, discuss opportunities and challenges at this intersection, and propose community activities that will be mutually beneficial., Comment: Contribution to Snowmass 2021

Finding a balance between professional responsibilities and personal priorities is a great challenge of contemporary life and particularly within the HEPAC community. Failure to achieve a proper balance often leads to different degrees of mental and physical issues and affects work performance. In this paper, we discuss some of the main causes that lead to the imbalance between work and personal life in our academic field. We present some recommendations in order to establish mechanisms to create a healthier and more equitable work environment, for the different members of our community at the different levels of their careers.

This paper summarizes the modeling, statistics, simulation, and computing needs of direct dark matter detection experiments in the next decade., Comment: Contribution to Snowmass 2021

Exploring dark matter via observations of extreme astrophysical environments -- defined here as heavy compact objects such as white dwarfs, neutron stars, and black holes, as well as supernovae and compact object merger events -- has been a major field of growth since the last Snowmass process. Theoretical work has highlighted the utility of current and near-future observatories to constrain novel dark matter parameter space across the full mass range. This includes gravitational wave instruments and observatories spanning the electromagnetic spectrum, from radio to gamma-rays. While recent searches already provide leading sensitivity to various dark matter models, this work also highlights the need for theoretical astrophysics research to better constrain the properties of these extreme astrophysical systems. The unique potential of these search signatures to probe dark matter adds motivation to proposed next-generation astronomical and gravitational wave instruments., Comment: Contribution to Snowmass 2021 -- CF3. Dark Matter: Cosmic Probes

The International Linear Collider (ILC) is on the table now as a new global energy-frontier accelerator laboratory taking data in the 2030s. The ILC addresses key questions for our current understanding of particle physics. It is based on a proven accelerator technology. Its experiments will challenge the Standard Model of particle physics and will provide a new window to look beyond it. This document brings the story of the ILC up to date, emphasizing its strong physics motivation, its readiness for construction, and the opportunity it presents to the US and the global particle physics community., Comment: 356 pages, Large pdf file (40 MB) submitted to Snowmass 2021; v2 references to Snowmass contributions added, additional authors; v3 references added, some updates, additional authors

Mentorship in the AI community is crucial to maintaining and increasing diversity, especially with respect to fostering the academic growth of underserved students. While the research process itself is important, there is not sufficient emphasis on the submission, presentation, and publication process, which is a cause for concern given the meteoric rise of predatory scientific conferences, which are based on profit only and have little to no peer review. These conferences are a direct threat to integrity in science by promoting work with little to no scientific merit. However, they also threaten diversity in the AI community by marginalizing underrepresented groups away from legitimate conferences due to convenience and targeting mechanisms like e-mail invitations. Due to the importance of conference presentation in AI research, this very specific problem must be addressed through direct mentorship. In this work, we propose PreDefense, a mentorship program that seeks to guide underrepresented students through the scientific conference and workshop process, with an emphasis on choosing legitimate venues that align with the specific work that the students are focused in and preparing students of all backgrounds for future successful, integrous AI research careers., Comment: 6 pages, published in Proceedings of Machine Learning Research (PMLR)

Natural disasters ravage the world's cities, valleys, and shores on a regular basis. Deploying precise and efficient computational mechanisms for assessing infrastructure damage is essential to channel resources and minimize the loss of life. Using a dataset that includes labeled pre- and post- disaster satellite imagery, we take a machine learning-based remote sensing approach and train multiple convolutional neural networks (CNNs) to assess building damage on a per-building basis. We present a novel methodology of interpretable deep learning that seeks to explicitly investigate the most useful modalities of information in the training data to create an accurate classification model. We also investigate which loss functions best optimize these models. Our findings include that ordinal-cross entropy loss is the most optimal criterion for optimization to use and that including the type of disaster that caused the damage in combination with pre- and post-disaster training data most accurately predicts the level of damage caused. Further, we make progress in the qualitative representation of which parts of the images that the model is using to predict damage levels, through gradient-weighted class activation mapping (Grad-CAM). Our research seeks to computationally contribute to aiding in this ongoing and growing humanitarian crisis, heightened by anthropogenic climate change., Comment: 8 pages; presented as Spotlight Talk at NeurIPS - Tackling Climate Change with Machine Learning workshop 2020

In recent years, the monarch butterfly's iconic migration patterns have come under threat from a number of factors, from climate change to pesticide use. To track trends in their populations, scientists as well as citizen scientists must identify individuals accurately. This is uniquely key for the study of monarch butterflies because there exist other species of butterfly, such as viceroy butterflies, that are "look-alikes" (coined by the Convention on International Trade in Endangered Species of Wild Fauna and Flora), having similar phenotypes. To tackle this problem and to aid in more efficient identification, we present MonarchNet, the first comprehensive dataset consisting of butterfly imagery for monarchs and five look-alike species. We train a baseline deep-learning classification model to serve as a tool for differentiating monarch butterflies and its various look-alikes. We seek to contribute to the study of biodiversity and butterfly ecology by providing a novel method for computational classification of these particular butterfly species. The ultimate aim is to help scientists track monarch butterfly population and migration trends in the most precise and efficient manner possible., Comment: 5 pages, 2 figures, Proceedings of NeurIPS 2020 - Learning Meaningful Representations of Life (LMRL) Workshop. The FASEB Journal

Macroscopic dark matter (or macro) provides a broad class of alternative candidates to particle dark matter. These candidates would transfer energy primarily through elastic scattering, and this linear energy deposition would produce observable signals if a macro were to traverse the atmosphere. We study the fluorescence emission produced by a macro passing through the atmosphere. We estimate the sensitivity of EUSO-SPB2 to constrain the two-dimensional parameter space ($\sigma$ vs. $M$), where $M$ is the macro mass and $\sigma$ its cross sectional area., Comment: To be published in the Proceedings of the 37th International Cosmic Ray Conference (ICRC 2012), Berlin, 12 -23 July 2021