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.

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.

Due to anthropogenic climate change, the frequency and intensity of natural disasters is only increasing. As supercomputing capabilities increase in an era of computational geosciences, artificial intelligence has emerged as a key tool in assessing the progression and impact of these disasters. Recovery from extreme weather events is aided by machine learning-based systems trained on multitemporal satellite imagery data. We work on shifting paradigms by seeking to understand the inner decision-making process (interpretability) of convolutional neural networks (CNNs) for damage assessment in buildings after natural disasters, as these deep learning algorithms are typically black boxes. We compare the efficacy of models trained on different input modalities, including combinations of the pre-disaster image, the post-disaster image, the disaster type, and the ground truth of neighboring buildings. Furthermore, we experiment with different loss functions, and find that ordinal cross entropy loss is the most effective criterion for optimization. Finally, we visualize inputs by creating gradient-weighted class activation mapping (Grad-CAM) on the data, with the end goal of deployment. Earth observation data harnessed by deep learning and computer vision is not only useful for disaster assessment, but also in understanding the other impacts of our changing climate from marine ecology to agriculture in the Global South.

The integration of Artificial Intelligence (AI) in climate research has emerged as a pivotal development in understanding and addressing the multifaceted challenges of climate change. This survey talk explores the diverse applications of AI in this field, highlighting how these technologies are reshaping our approach to environmental stewardship and sustainable development. At the forefront of this integration is the use of machine learning algorithms in climate modeling and forecasting. AI's ability to process vast datasets has significantly enhanced the accuracy of climate models, enabling more precise predictions of weather patterns, temperature fluctuations, and atmospheric changes. This improvement is crucial in formulating effective climate policies and disaster response strategies. Another notable application is in the domain of environmental monitoring. AI-driven tools are increasingly employed to analyze satellite imagery and sensor data, offering unprecedented insights into deforestation, ocean health, and biodiversity loss. Such comprehensive environmental surveillance aids in the timely detection of ecological anomalies, facilitating prompt intervention. AI also plays a critical role in energy efficiency. Through smart grid technologies and predictive maintenance of renewable energy systems, AI optimizes energy use and promotes the adoption of sustainable energy sources. This is vital in reducing greenhouse gas emissions and advancing towards a low-carbon economy. Furthermore, the talk discusses the use of AI in climate risk assessment and management. By analyzing patterns in climate data, AI assists in identifying regions vulnerable to extreme weather events, guiding resource allocation and infrastructure planning to mitigate potential impacts. In conclusion, the survey study underscores AI's transformative potential in climate science. While acknowledging the challenges in AI deployment, such as data quality and ethical considerations, the paper advocates for a collaborative approach, integrating AI innovations with traditional climate research methodologies to achieve holistic and effective solutions to climate change.

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.

With growing interest from the aviation and satellite industries, and for NASA's upcoming Artemis lunar missions, the need for improved scientific understanding and accurate forecasting of solar energetic particle events has never been stronger.In this paper we discuss the observational, validation and model transition support required to achieve these goals.Well-calibrated, high-quality energetic electron, proton, and ion measurements are essential.Expansions to the fields of view offered by current X-ray, extreme ultraviolet and coronagraph instruments, to obtain increased coverage of the solar corona and heliosphere, from vantage points off the Sun-Earth line, are desired for model input.New observations of suprathermal particles are needed to characterize seed particle distributions and low latency space-based observations of solar radio emissions are also desired.Together, this observational suite should offer high cadence, low latency, reliable and accurate space weather data streams.SEP models are a critical part of both understanding and predicting SEP radiation hazards.Consistent, extensive and quantitative validation is required to assess scientific understanding of SEP sources and pave the way for models transitioning to real-time forecast operations.Model performance and skill should be compared to observations and to current operational forecasting baselines.Finally, resources are required to support the significant effort of transitioning mature models into forecast operations.Visualization of CME and SEPs.

While the near-term Interstellar Probe mission will revolutionize our understanding of the astrosphere in which we live, it will provide only a snapshot of the history of the heliosphere.Trans-Neptunian objects (TNOs), with numerous options conveniently located along whichever Interstellar Probe trajectory would ultimately be chosen, provide an opportunity to examine the history of the heliosphere measurable in the colors, spectra, and geologies of their surfaces.Interstellar Probe with a planetary augmentation would enable a scientifically rich close flyby of a TNO along with "remote" observations.The spacecraft can function as an in situ observatory to study TNOs up to 2 -3 au away, an order of magnitude closer than they are to the Earth.

The current operational dimension available for space weather analysis and operations is not suitable for deep space exploration.As NASA plans for missions beyond the Low Earth Orbit (LEO), new advancements in modeling, observations, and communications are needed to establish a suitable monitoring and protection environment for the missions and the crew.The initial step is to establish multiple observational points that will improve the current analysis/modeling capabilities and extend them to deep space exploration missions.We summarize the value of multiple observational points, outline the current gaps (with examples) in providing operational space weather support for deep space exploration, and propose ideas for missions and international collaborations that will address these existing gaps.These proposed missions and collaborations will be essential to ensure a successful future for deep space exploration.

We outline specific steps that NASA and the space science community can take to advance collaboration and coordination between the communities represented by the four NASA Science Mission Directorate Divisions. It is important to note that the only way that this effort can succeed is if NASA initiates and supports it through directed resources.

This white paper recognizes gaps in observations that will, when addressed, much improve solar radiation hazard and geomagnetic storm forecasting. Radiation forecasting depends on observations of the entire "Solar Radiation Hemisphere" that we will define. Mars exploration needs strategic placement of radiation-relevant observations. We also suggest an orbital solution that will improve geomagnetic storm forecasting through improved in situ and solar/heliospheric remote sensing.

Extreme solar radio bursts can impact several areas of human activity, but there remain many gaps in our understanding of what leads to their occurrence.This paper discusses such events, focusing on three different emission mechanisms, which correspond to three different frequency ranges.Bright decimetric bursts in particular are dangerous because they could affect the use of global navigation systems for landing commercial passenger aircraft.The properties of extreme bursts are discussed, and shortcomings in our understanding of such events are presented.

The critical observational unknown that links the magnetosphere, ionosphere and atmosphere is the conductivity.This parameter requires detailed observation of the ionospheric E-and F-layer densities and heights, plus some understanding of the atmospheric density and other parameters.At present the conductivity is poorly observed.Here we argue that distributed HF remote sensing is the best means of achieving the required observational coverage of this parameter, due to its relatively low cost, proven success in operational applications, and scalability.Theoretically it is possible to determine the conductivity unambiguously from HF remote sensing, though in practice it may be necessary to use models or supporting data to constrain the collision frequencies.We present simulations to illustrate potential high-latitude HF networks, cite existing low-and mid-latitude networks and show ionospheric retrievals based on these data.This avenue of research is timely as it targets radio frequency applications relevant to the global electromagnetic spectrum challenge, which is a major area of technological development and growth (see e.g.5G and 6G competition).Many recent developments have occurred in our field that facilitate this approach, notably the transition to modern software-defined radio systems by many SuperDARN radars and other systems, the development of HF electromagnetic vector sensors, and the acquisition of HAARP by the National Science Foundation.

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.

In this white paper, we demonstrate the scientific value of interdisciplinary research on highenergy solar and stellar activity and advocate for programmatic implementation that facilitates and encourages interdisciplinary collaboration.Solar eruptive events are the most energetic events in our solar system; they provide insight into energy release mechanisms in the solar corona and are a key source of energetic particles and space weather.This also holds true in the stellar context; moreover, the energy released by events in the stellar domain can be orders of magnitude greater than on our Sun.Interdisciplinary research on solar/stellar activity leverages the combination of spatially-resolved measurements from the Sun with the variety of sources and extreme conditions from stellar observations to provide a more complete picture than either discipline could present on its own.In this white paper, we explore the enhanced insight gained from solar-stellar investigations of high-energy activity, including: flares, coronal mass ejections (CMEs), coronal heating, young stellar objects and planet formation, and stellar impacts on exoplanet habitability.We recommend that proposals engaging in interdisciplinary solar-stellar science be encouraged and facilitated.We additionally recommend the implementation of a cross-disciplinary approach to guest observer/investigator opportunities in order to further leverage the synergies in solar and stellar research goals.

We highlight the importance of magnetic reconnection at the heliopause, both as one of the key processes driving the interaction between solar and interstellar media, but also as an element of the definition of the heliopause itself. We highlight the main observations that have fed the current debates on the definition, location and shape of the heliopause. We explain that discriminating between the current interpretations of plasma and magnetic field structures near the heliopause necessitates appropriate measurements which are lacking on Voyager 1 and 2, and describe some of the ensuing requirements for thermal plasma measurements on a future Interstellar Probe. The content of this article was submitted as a white paper contribution to the Decadal Survey for Solar and Space Physics 2024–2033 of the National Academy of Sciences.

One of the top scientific objectives of the Interstellar Probe mission is the investigation of the complex interactions of the plasma, and the resulting particle acceleration.The Voyagers and their in-situ measurements provided us with a glimpse of the phenomena that happen in the distant heliosphere.These observations of charged particles at large distances and in the Very Local InterStellar Medium (VLISM) are sometimes of low resolution, leaving us with an incomplete picture of the complex processes and role of thermal and suprathermal ion populations in the generation of anomalous cosmic rays (ACRs) and galactic cosmic rays (GCRs).This paper should highlight criticality and importance of proper instrumentation of the Interstellar Probe mission to fill these gaps and complete our understanding of particle acceleration in the heliosphere and beyond.

We discuss a suite of instruments cable of carrying out the next generation of in situ cosmic dust measurements from the heliosphere into interstellar space in support of the Interstellar Probe mission concept.A Dust Analyzer should be considered as the highest priority for its coverage of both compositional and dynamical information of the bulk of interstellar dust (ISD) and interplanetary dust particle (IDP) populations, essential to address the major science questions.A PVDF Dust Counter and Plasma Wave Antenna instrument could additionally provide critical improvement through the detection of larger, rarer dust populations, to constraining the mass density of ISD as well as providing additional directionality coverage.A Neutral Mass Spectrometer bridges the measurement gap between microscopic dust grains and gas species, potentially relevant for understanding the nature and interactions of the very local interstellar medium and our heliosphere.The Dust Analyzer, PVDF Dust Counter, and Plasma Wave Antenna instruments can be calibrated using dust accelerator facilities (University of Colorado, USA, see Shu et al., 2012; and Universität Stuttgart, Germany) with ISD-relevant materials at realistic mass and speed ranges.

Synopsis: (limit of 400 characters)The current infrastructure in heliophysics acts as a barrier towards progress due to the lack of intelligent connections between the many valuable resources in our field.Due to the large scale of this problem, the path to a productive infrastructure requires community collaboration towards a common vision.This white paper presents a broad overview of what that vision could be and a path forward.

Active region scale FOVActive region scale FOV Active region scale FOV