Current Research Topics for DEVCOM ARL BAA 9 Dec2024.pdf

Current Research Topics for DEVCOM ARL BAA For Foundational Research

W911NF-23-S-0001

This document generated on 12/09/2024

This document generated on 12/09/2024

Current Research Topics for the DEVCOM ARL BAA For Foundational Research

Disclaimer

All current ARL research topics can be found at: https://www.arl.army.mil/opportunties/arl-baa.

Changes to these topics will be made using the website on an as needed basis. This document is a printed copy of the current ARL research topics as of the noted print date. ARL maintains a daily static snapshot of the ARL research topic website to ensure submissions are aligned with listed research topics on the day of submission. The available Army Research Office (ARO) topics are listed alphabetically followed by an alphabetical listing of the Army Research Directorate (ARD) topics. Interested parties are encouraged to continually browse the ARL research topic website and review the ARL BAA for instructions on submissions.

The DEVCOM ARL Broad Agency Announcement for Foundational Research, W911NF-23-S-0001, is available on https://www.grants.gov/ and https://sam.gov/

Link to all current ARL research topics https://www.grants.gov/ https://sam.gov/

This document generated on 12/09/2024

This document generated on 12/09/2024

Available Army Research Office (ARO) Research Topics

The available Army Research Office (ARO) topics are listed in alphabetical order.

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Army Research Office (ARO) Research Topic

Advanced Learning-Enabled Intelligent Cyber Physical SystemsTitle:

ARL-BAA-0032Announcement ID:

TPOC: MaryAnne Fields, PhD - mary.a.fields22.civ@army.mil - (919) 549-4350 ARL Office: Army Research Office (ARO) Discipline: Computer Science;Data Sciences and Informatics;Mathematics and Statistics ARL Foundational Research Competencies: Military Information Sciences;Network, Cyber, and Computational Sciences Army Modernization Priorities: Future Vertical Lift;Next Generation Combat Vehicle Keywords: Intelligent Systems, Interaction, Assured Operations, Online learning, Robust Intelligence, World Models, Memory Systems, Causality

Description:

Intelligent cyber physical systems play an increasingly important role in civilian and military settings. With few exceptions, current intelligent systems are restricted to highly constrained environments for short duration missions. Future systems will need to perform a variety of tasks in complex, possibly contested, open worlds for extended periods of time. One important characteristic of open worlds is that the intelligent system will encounter new contexts, activities, and objects that will require it to adapt previously trained algorithms. Advanced capabilities in learning, reasoning, interaction, and assured operations are essential to the development of intelligent systems that can greatly enhance the Army's mobility, agility, lethality, and survivability in future conflicts.

ON-LINE LEARNING THEORY, METHODOLOGY, AND TECHNIQUES

Over the past 50 years, machine learning has made great strides in classification, natural language processing, and task learning. However, machine learning still lacks the rigor, agility, and flexibility necessary to operate in complex, contested open worlds. This thrust focuses on establishing a theoretical foundation for on-line or continuous machine learning. New learning approaches will need to address both the dimensionality challenges and temporal characteristics that may be evolving continuously. In addition, new techniques must address robustness to enable the learning system to deal with novelty, noise, observation errors and potentially malicious input that aim to disrupt learning. Innovative approaches to continuous learning will allow systems to adapt to changing contexts and environments while maintaining previously learned knowledge. Under this thrust, we investigate approaches that help the intelligent systems deal with dynamic environments, devise new, transferable skills, and cope with unknown situations.

While end-to-end learning may be important for certain applications, it may not be an effective approach for the complex environments typical of most battlefields. Instead, there is a need for compositional learning systems in which each component may learn primitive actions that are later combined, and adapted, to solve complex long-horizon manipulation problems. Research is needed to understand how to express and learn the preconditions and post-conditions for each of the primitive actions. Linking elements from a library of primitives and adapting the ensemble to solve an existing problem is also an outstanding issue. Automated curriculum learning in which

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This document generated on 12/09/2024 the CPS devises its own learning strategy is an open research area. Important issues in this area include generating sample task environments from observation, memory and simulation;

sequencing those task into an effective curriculum; and transferring the learning as the tasks become more complex.

DECISION MAKING FOR THE OPEN WORLD

Long duration operations require CPSs to continually reason, make decisions, or take actions with very limited knowledge of the pertinent events or objects that could impact those decisions.

In real world missions, systems often address multiple near-simultaneous tasks to accomplish their objectives - on a battlefield, systems need to travel to a location while searching for potential adversaries and sharing information with teammates. Architectures that draw from psychological models for human decision making, such as Dual Process theory, may enable CPSs to effectively distribute the processing for near-simultaneous reasoning tasks. Advances in risk-aware online planning will enable autonomous systems to balance potentially conflicting objectives and operate safely in poorly understood environments. CPSs also need to develop a sense of "'causality" that discovers relationships between objects and events and allows the system to incorporate temporal and spatial information into the reasoning processes.

Storing and accessing information is vital to long term mission. Not all pertinent information is collected at the same time: new research in memory systems will enable cyber physical systems to determine what information, in what form, it needs to store to support future actions that may or may not relate to its current action. Memory systems are not simply information stores -processes like reflection, abstraction, and learning enable CPSs to develop new information.

Retrieval mechanisms are very important - information is not useful unless the system can recall it when it is needed. Research to understand effective memory structure and processes will benefit from a collaboration with cognitive scientists to understand memory in biological systems. New approaches are needed to address potential issues with memory systems such as catastrophic or forgetting, limited storage capacity, and development of new methods to efficiently use external knowledge stores.

INTERACTION

Future autonomous systems must interact physically with humans and other intelligent systems operating in the same space, remotely with spatially distant entities, and virtually in cyberspace with intelligent software agents. New research in human-robot interaction and robot-robot teaming will enable humans and robots to share the same space and work together on complex tasks. Research in Ad-hoc teamwork will enable entities (human and systems) to dynamically join together to address a specific problem, then pursue separate tasks after the problem is solved. In this type of teaming, there is no prior coordination between agents and we cannot assume that the entities share the same types of learning algorithms or reward structures or that they have prior agreements regarding action coordination and information sharing. Some of the important research problems within ad-hoc teaming are: ensuring that actions are understandable to fellow teammates; modeling the capabilities of team members; including humans in the ad-hoc teams, and dynamically modeling the performance of both the team and the individuals.

Explicit Human-Robot interaction has been extensively explored throughout the last decade.

Implicit Human-Robot interaction, on the other hand, is relatively unexplored. In this case, humans may not directly interact with an intelligent system but instead take actions that the system could use as input. The human actions may be intentional, unintentional or even

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This document generated on 12/09/2024 unconscious but they are a rich source of signals for learning or cooperative actions. These implicit actions may also provide context information that could be used to adapt a previously learned behavior to a new environment. Some important research topics in this area include:

identifying implicit signals, the value of implicit robot-human signals, and context-aware interaction.

ASSURED OPERATIONS

Assured operations require a deep understanding of how a complex system composed of several components, including mechanical systems, computational hardware, and software algorithms operates as a coordinated system. In much the same way as the community is trying to understand the behavior of neural networks, which are composed of layers of mathematical functions, this topic seeks to understand how information and actions flow from the lowest levels of the system to system level decisions and actions. Along those lines, new theory and principles are needed to understand the impact of both gradual and abrupt changes at the component level on the evolution of the entire system. Investigating modularity and compositionality will enable the system to address the multiple near-simultaneous problems it is likely to encounter in long term operations. New theories in information sharing in dynamic environments will lay the foundation for accountability and provide clear criteria for component-level and global input/output specification (in terms of computation, rate, semantics, ..) that can be used to: train a learning component, optimize outputs of a planning component, and test individual and systems level components. As these areas mature, they will provide a firm mathematical foundation for systems-level research in learning-based design, performance guarantees, and robustness to degraded components.

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Atomic and Molecular Physics (AMP)Title:

ARL-BAA-0022Announcement ID:

TPOC: Margaret E Shea, PhD - margaret.e.shea6.civ@army.mil ARL Office: Army Research Office (ARO) Discipline: Computer Science;Materials Science;Physics ARL Foundational Research Competencies: Network, Cyber, and Computational Sciences;Photonics, Electronics, and Quantum Sciences;Weapons Sciences Army Modernization Priorities: Assured PNT;Long Range Precision Fires;Network/C3I Keywords:

Description:

Topics of interest within Atomic and Molecular Physics (AMP) include:

Quantum degenerate atomic gases, both Bose and Fermi, their excitations and properties, including mixed species, mixed state, and molecular;

Quantum enhanced precision metrology;

Nonlinear processes;

Quantum systems in cavities;

Collective and many-body states of matter; and Emerging areas.

There is an interest in emerging areas of AMO physics such as collective states of matter, emergent lattices in quantum gases, non-equilibrium many body dynamics, advanced quantum simulation, and metrology in non-ideal environments. Research efforts within the AMP fall within two thrust areas: Advanced Quantum Capabilities and Novel Quantum Methods. It is anticipated that research efforts within these areas will lead to applications including novel materials, efficient computational platforms, and exquisite quantum sensors.

Advanced Quantum Many-body Dynamics The focus of this thrust is the development and study of strongly correlated many-body systems.

The quantum simulator portion of the thrust seeks research on novel techniques and studies that leverage our control and understanding of simple quantum mechanical systems to explore more complex quantum effects and materials. The effort seeks the validation of many-body quantum theories through the development of experimental tools including quantum gas microscopes, atom-array experiments, synthetic gauge fields, mixed species, and novel interactions.

Complimenting this effort will be the inclusion of foundational investigations into quantum mechanics, such as entanglement, many-body localization, collective modes, and entropy. To take advantage of the precision inherent in future quantum devices, these systems will need to connect to the classical world in such a manner that allows them to sample the signal of interest while remaining robust to noisy environments. Consequently, studies of how the quantum system interacts with classical world, and the quantum-to-classical boundary are also of interest.

Investigating how to maximize both the quality and quantity of entanglement within these systems will be a priority. General issues of quantum coherence, quantum interference, This document generated on 12/09/2024

This document generated on 12/09/2024 entanglement growth, entanglement purity, and non-equilibrium phenomena, as well as discovering new scientific opportunities are also of interest.

Novel Quantum Metrology The AMP Program has a general interest in exploring fundamental AMP that may impact future Army capabilities. This thrust is divided into two main areas: precision metrology beyond the standard limit and harnessing collective many-body states to improve quantum sensing. The Novel Quantum Metrology efforts will expand the foundations of quantum measurement into new areas that seek to exploit entanglement, spin-squeezing, harnessing collective-spin states, developing back-action avoidance measurements, and other areas that increase fundamental precision through interactions, including cavities and Rydberg atoms. It is expected that research in this thrust will complement efforts in the Advanced Quantum Many-body Dynamics thrust and vice versa. For example, collective many body states could be studied in optical lattices or quantum gas microscopes and foundational research of entanglement are anticipated to provide new metrological capabilities in non-ideal environments.

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BiochemistryTitle:

ARL-BAA-0017Announcement ID:

TPOC: Stephanie A McElhinny, PhD - stephanie.a.mcelhinny.civ@army.mil - (919) 549-4240 ARL Office: Army Research Office (ARO) Discipline: Biological Sciences;Chemistry;Materials Science ARL Foundational Research Competencies: Biological and Biotechnology Sciences;Sciences of Extreme Materials Army Modernization Priorities:

Keywords: Biotechnology, Bioengineering, Biomaterials

Description:

This program emphasizes basic research focused on understanding and controlling the activity and assembly of biomolecules. Scientific advances supported by this program are anticipated to enable the development of novel systems, materials and processes that enhance Soldier protection and performance. Overarching goals of the program are to provide the scientific foundations to expand the chemical diversity accessible by biomolecules and to support biological activity outside of the cellular environment, including integration of biological systems with synthetic systems.

The Biomolecular Specificity and Regulation thrust is focused on novel approaches to engineer the specificity and regulation of biomolecules, either via modulation of natural mechanisms or via design of non-natural mechanisms. Approaches to expand the chemical diversity of ligands/substrates that are recognized/accepted by biomolecules and/or the products of biocatalytic reactions beyond elements and chemical bonds common to natural biological systems are of particular interest. This includes both individual enzymatic reactions as well as multi-step biocatalytic pathways. The goal of this thrust is to develop novel engineered approaches to modulate and control biomolecular activity, with emphasis on expanding the chemical diversity accessible by biomolecules and achieving biomolecular control in non-cellular contexts.

The Biomolecular Assembly and Organization thrust is focused on understanding the molecular interactions and design rules that govern self-assembly of biomolecules into both naturally occurring biomolecular structures and non-natural human-designed architectures. This thrust aims to elucidate fundamental understanding of sequence-structure-property relationships in natural biomolecular assemblies, biomaterials, and biological composites to enable rational design of biological and hybrid biological/abiological assemblies with tailored properties and functions. Biomolecular assembly across length scales is of interest, including discrete multi-protein complexes or nucleic acid structures, as well as hierarchical protein or nucleic acid assemblies and biological composites. This thrust includes homogeneous assemblies utilizing a single building block, as well as heterogeneous systems in which a mixture of different biomolecules and/or non-biological species (e.g., minerals, synthetic polymers) self-assemble.

Of particular interest are approaches to expand the chemical diversity of biomolecular architectures beyond elements and chemical bonds common to natural biological systems. This research thrust also includes the design of self-assembled biomolecular or hybrid

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This document generated on 12/09/2024 biological/abiological architectures that provide control over the chemical environment and spatial organization necessary to support complex biomolecular function in non-cellular contexts, including artificial cells and cell-free systems.

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BiogeochemistryTitle:

ARL-BAA-0005Announcement ID:

TPOC: Elizabeth K. King-Doonan, PhD - elizabeth.k.king-doonan.civ@army.mil - (919) 549-4386 ARL Office: Army Research Office (ARO) Discipline: Biological Sciences;Chemistry;Earth and Environmental Sciences ARL Foundational Research Competencies: Biological and Biotechnology Sciences;Energy Sciences;Humans in Complex Systems;Military Information Sciences Army Modernization Priorities:

Keywords: Environment, Chemistry, Fate, Transport, Climate, Arctic

Description:

The Biogeochemistry program seeks to support transformative research to enable unprecedented detection, prediction, manipulation, and mitigation strategies in complex environmental matrices.

This is an interdisciplinary program that incorporates recent discoveries in chemical, biological, and physical principles to enhance national security.

Current focus areas for this portfolio include, but are not limited to, the following:

Transport and transformation aims to elucidate and characterize novel biogeochemical mechanisms that drive (or prevent) the release and/or transformation of chemical and biological compounds of Army relevance within or across environmental reservoirs. Environmental reservoirs of interest include the lithosphere (e.g., soils and sediments), biosphere (e.g., plants and microbiome), hydrosphere, and atmosphere.

Biogeochemistry and the built environment supports research to understand the biogeochemical interactions that are unique to built and urban environments. The reactions in these environments are a function of the structure and partitioning of the compounds present, the chemical and physical properties of the built/artificial materials, and the microenvironments that form at the natural-built interface. Topics of interest include (but are not limited to) environmental/biofilm formation on Army-relevant built materials, biological and chemical transport in subterranean environments, and transport and transformation of chemical and biological compounds through diverse urban interfaces.

Environmental forensics strives to develop cutting-edge approaches to enable novel techniques for detection, tracking, source partitioning, and prediction of molecules of interest at military-relevant scales. Research that leverages recent discoveries in other scientific fields such as biochemistry, physics, network and data science, and computational modeling are encouraged.

Topics that focus on instrument/sensor development and materials design are not supported.

Biogeochemistry to inform national security characterizes the role of biogeochemistry on resource competition (e.g., critical resource recovery), environmental security (e.g., permafrost degradation), and stability (e.g., water availability).

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BiomathematicsTitle:

ARL-BAA-0021Announcement ID:

TPOC: Virginia B. Pasour, PhD - virginia.b.pasour.civ@army.mil - (919) 602-8348 ARL Office: Army Research Office (ARO) Discipline: Biological Sciences;Data Sciences and Informatics;Earth and Environmental Sciences;Mathematics and Statistics;Network Science;Physics;Social Science ARL Foundational Research Competencies: Biological and Biotechnology Sciences;Humans in Complex Systems Army Modernization Priorities: Soldier Lethality Keywords: biomathematics, mathematical biology, theoretical ecology, theoretical epidemiology, modeling

Description:

The introduction of Biomathematics as a separate area of basic research recognizes the importance and specialized nature of quantitative methods, specifically mechanistic modeling, in the biological sciences. Biology involves a large number of entities that interact with each other and their environment in complex ways, and at multiple spatial and temporal scales.

Understanding how dynamics at different spatial scales come together to form a biological system and understanding the dynamics of a system at intermediate timescales, as opposed to its long term, asymptotic behavior, are critically important in biology, more so than in many other fields.

This complexity makes biomathematics a highly interdisciplinary field that requires unique and highly specialized mathematical competencies to quantify structure in these relationships. In fact, progress in mathematical models of biological systems has traditionally been achieved by making convenient simplifications; major advances in Biomathematics research continue to require removing these assumptions (for example, stationarity, ergodicity and deterministic nature) and finding ways to effectively model the essential complexity. Modeling techniques currently utilized in the field range from agent-based approaches for determining the results of individual behavior, whether those individuals be molecules, zooplankton, or humans, to multi-compartmental modeling in physiology, epidemiology and neurobiology, to network models involved in understanding ecosystem and human social dynamics, as well as encompassing both deterministic and stochastic approaches. Research in control techniques is also valuable for its potential application in militarily important areas such as bio warfare and disease spread. Exciting new opportunities to advance the field are found in high risk attempts to develop modeling techniques in areas of mathematics, such as algebra and topology, not traditionally brought to bear on biological problems, advances in Bayesian statistics, a growing recognition that the diffusion approximation is not necessarily adequate for many systems, and the availability of large amounts of complex biological data.

The ultimate goal of the Biomathematics Program focuses on adapting existing mathematics and creating new mathematical techniques to uncover fundamental relationships in biology, spanning different biological systems as well as multiple spatial and temporal scales. One area of special interest to the program is Neuromathematics, the mechanistic mathematical modeling of neural

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This document generated on 12/09/2024 processes. Recent advances in neuroscience provide important foundations to begin understanding how the brain works. Combined with experimental data, innovative mathematical modeling provides an unparalleled opportunity to gain a revolutionary new understanding of brain physiology, cognition (including sensory processing, attention, decision-making, etc.), and neurological disease. With this new understanding, improved soldier performance, as well as treatments for Post-Traumatic Stress Disorder, Traumatic Brain Injury, and other brain-related disorders suffered by the warfighter will be able to be achieved more effectively, efficiently, and ethically than via experimentation alone.

Thrust areas of the Biomathematics Program are as follows:

Fundamental Laws of Biology The field of physics has long been "'mathematized" so that fundamental principles such as Newton's Laws are not considered the application of mathematics to physics but physics itself.

The field of biology is far behind physics in this respect; a similar process of mathematization is a basic and high-risk goal of the ARO Biomathematics Program. The identification and mathematical formulation of the fundamental principles of biological structure, function, and development applying across systems and scales will not only revolutionize the field of biology but will motivate the creation of new mathematics that will contribute in as-yet-unforeseen ways to biology and the field of mathematics itself. For example, heterogeneity/stochasticity is ubiquitous in biological systems; is heterogeneity necessary for tipping points that result in diseased individuals and epidemics and if so, what is its role? More generally, is heterogeneity in biological systems necessary for their functioning or a problem to be overcome, or is the answer system/function dependent?

Multiscale Modeling/Inverse Problems Biological systems function through diversity, with large scale function emerging from the collective behavior of smaller scale heterogeneous elements. This "'forward" problem includes creating mechanistic mathematical models at different biological scales and synchronizing their connections from one level of organization to another, as well as an important sub problem, how to represent the heterogeneity of individual elements and how much heterogeneity to include in the model. For example, the currently increasing ability to generate large volumes of molecular data provides a significant opportunity for biomathematical modelers to develop advanced analytical procedures to elucidate the fundamental principles by which genes, proteins, cells, etc., are integrated and function as systems through the use of innovative mathematical and statistical techniques. The task is complicated by the fact that data collection methods are noisy, many biological mechanisms are not well understood, and, somewhat ironically, large volumes of data tend to obscure meaningful relationships. However, traditionally "'pure" mathematical fields such as differential geometry, algebra and topology, integration of Bayesian statistical methods with mathematical methods, and the new field of topological data analysis, among others, show promise in approaching these problems. Solutions to these types of multiscale problems will elucidate the connection, for example, of stem cells to tissue and organ development or of disease processes within the human body to the behavior of epidemics.

The "'inverse" problem is just as important as the forward problem. From an understanding of the overall behavior of a system, is it possible to determine the nature of the individual elements?

For example, from knowledge of cell signaling, can we go back and retrieve information about the cell? Although inverse problems have been studied for a long time, significant progress has

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This document generated on 12/09/2024 been elusive. This thrust area involves innovations in spatial and/or temporal modeling of multi-level biological elements with the goal of achieving a deeper understanding of biological systems and eventually connecting top-down (data-driven) and bottom-up (model-based) approaches.

Hybrid Modeling While the Biomathematics Program has primarily been concerned with developing and using mathematical modeling techniques to understand the mechanisms behind biological system function, future predictions about a system have typically been achieved through statistical modeling using available data; these methods are limited by their ability to make trustworthy predictions only under the same situations under which the data was collected. This thrust seeks to develop new methods that will take advantage of the strengths of both types of modeling, still allowing the hypothesis and testing of biological mechanism while also allowing prediction under an expanded set of conditions. These new methods will facilitate the utilization of the increasingly available data in many areas of biology to expand our ability to understand and predict biological systems and may be furthered through the use and development of existing and new data analysis techniques. For example, can we develop a mechanistic model to understand a cell's ability to repair damage to its DNA by incorporating Machine Learning?

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Bionic ElectronicsTitle:

ARL-BAA-0069Announcement ID:

TPOC: Albena NMN Ivanisevic, PhD - albena.ivanisevic.civ@army.mil - (919) 549-4314 ARL Office: Army Research Office (ARO) Discipline: Biological Sciences;Chemistry;Electronics;Materials Science;Physics ARL Foundational Research Competencies: Biological and Biotechnology Sciences;Humans in Complex Systems Army Modernization Priorities:

Keywords: bioelectronics, biotronics, bionic

Description:

This research area focuses on the discovery and manipulation of phenomena and the creation of new processes where electronics and biology overlap at the cellular / sub-cellular level. This length scale is where the amplitudes of many types of energies (e.g., electrostatic, mechanical, and chemical terms) converge, and correspondingly, where electronics can have fundamental biological impacts and where leveraging electronics capabilities at the nanoscale can yield unique new understanding of the cellular and intracellular processes.

New electronic structures and materials are now able to focus localized static electric and magnetic fields and electromagnetic fields at the nanoscale, which presents the opportunity to selectively address and manipulate the organelles and membranes making up the structure of the cell. Moreover, cell constituents can have a frequency dependent response to mechanical and electromagnetic excitation, resulting in unique electronically enabled and controlled biological experiments. Molecular and subcellular events at the biological interfaces or surfaces are key to downstream biological dynamics. The stimulation or manipulation of these events by electronic means provides the opportunity for unique control and experimentation that are orthogonal to existing biochemical or genetic approaches. Ion flow, which is fundamental to inter- and intra-cellular signaling and process control, is susceptible to electromagnetic influence and produces electromagnetic signatures of cellular processes. The dynamics of charged and polarized cellular components also produces minute displacement currents, and can produce very large field distributions in a confined nanoscale space (e.g., within a protein scaffold or across a lipid bilayer); both of which are subject to electromagnetic probing and analysis. The different geometries of organelles within a cell result in different electromagnetic signatures and sensitivities which can be leveraged for selective control of cellular processes. Proteins play a role in almost every cellular process. As extremely large and complex molecules, they should have electromagnetic and mechanical responses that can be exploited for control. The skeletal protein assemblies of the cell, in particular, may offer a highway for the introduction of electrical currents or mechanical vibrations. Bio-chemical or genetic alteration of the interface of the cell and its components can introduce new electromagnetic properties, for example a new capability for photosynthesis in bacteria or new electromagnetic responses. Cellular engineering of membranes, cellular organelles, and proteins by the introduction of nano-particles and bio-molecules can introduce new sensitivities and new functionality. Opto-genetics is a well-established procedure for interrogating cells. Early attempts at "'magneto-genetics" have been controversial, however "'electro- or RF-genetics" may offer new opportunities. There may

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This document generated on 12/09/2024 also be inherently non-trivial quantum mechanical mechanisms linked to biological behaviors, such as navigation. Inherently quantum phenomena such as the tunneling of electrons and protons play a critical role in many intracellular processes and can be modulated or manipulated with nanoscale electric fields. This research area seeks understanding and control of inter- and intra-cellular phenomena at the micro- and nano-scale. The program facilitates highly innovative extensions of techniques based on the unique capabilities of electronics as well as totally new, complementary methods, addressing the internal function and electrical processes within a living entity. Biotronics seeks to accomplish this with unprecedented spatial and temporal resolution and with minimal disruption of "'normal" living cell function. The basic science questions being addressed by the Biotronics program are geared to achieve a natural evolution into bionic electronics. Through this evolution the goal is to us

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Complex Dynamics and SystemsTitle:

ARL-BAA-0018Announcement ID:

TPOC: Dean R Culver, PhD - dean.r.culver.civ@army.mil - (412) 680-2591 ARL Office: Army Research Office (ARO) Discipline: Data Sciences and Informatics;Materials Science;Mathematics and Statistics;Mechanics;Physics ARL Foundational Research Competencies: Biological and Biotechnology Sciences;Energy Sciences;Humans in Complex Systems;Mechanical Sciences;Military Information Sciences;Network, Cyber, and Computational Sciences;Photonics, Electronics, and Quantum Sciences;Sciences of Extreme Materials;Terminal Effects;Weapons Sciences Army Modernization Priorities: Air and Missile Defense;Future Vertical Lift;Network/C3I;Next Generation Combat Vehicle;Synthetic Training Environment Keywords: nonlinear dynamics; mechanics; high dimensional; morphological computation;

chaos; embodied intelligence; hierarchical mechanics; heterogeneous systems; stochastic control;

stochastic learning

Description:

The Complex Dynamics and Systems program emphasizes fundamental understanding of the dynamics, both physical and information theoretic, of nonlinear and nonconservative systems as well as innovative scientific approaches for engineering and exploiting nonlinear and nonequilibrium physical and information theoretic dynamics for a broad range of future capabilities (e.g. novel energetic and entropic transduction, agile motion, and force generation).

The program seeks to understand how information, momentum, energy, and entropy flows and transforms in nonlinear systems due to interactions with the system's surroundings or within the system itself. Research efforts are not solely limited to descriptive understanding, however.

Central to the mission of the program is the additional emphasis on pushing beyond descriptive understanding toward engineering and exploiting time-varying interactions, fluctuations, inertial dynamics, phase space structures, modal interplay, practical control opportunities, and other consequences of nonlinearity in novel ways to enable the generation of useful work, agile motion, and engineered energetic and entropic transformations. Further information on the current scientific thrust areas are detailed in the paragraphs that follow.

High-Dimensional Nonlinear Dynamics Classical dynamics has produced limited fundamental insight and theoretical methods concerning strongly nonlinear, high-dimensional, dissipative, and time-varying systems. For over a century, qualitative geometric approaches in low-dimensions have dominated research in dynamics. These approaches of reduced-order-modeling of high-dimensional dynamics are often premised on empirical and statistical model fitting and are incapable of capturing the effects of slowly growing instabilities and memory. The program seeks to develop novel theoretical and experimental methods for understanding the physical and information dynamics of driven dissipative continuous systems. It also seeks novel reduced-order-modeling methodologies capable of retaining time-dependent and global nonlinearities. Novel research pertaining to the analysis and fundamental physics of time-varying nonlinear systems and transient dynamics is a high-priority.

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Embodied and Distributed Control, Sensing, and Actuation This thrust develops deeper understanding, through supporting theory and experiment, of the role of embodiment and dynamics on a physical system's capability to process information and transform energy. Proposals emphasizing the mechanics and control of soft, continuous bodies are encouraged along with novel experimental paradigms leveraging programmable printed matter. Generally, this thrust strongly leverages advances in, and approaches from, sensory biomechanics, neuromechanics, underactuated systems theory, and mechanical locomotion dynamics to understand the motion of both articulated and continuum dynamical systems operating in highly-dynamic environments. The scientific principles sought, however, are not limited to biological movement and manipulation. Proposals are strongly encouraged that view morphology in an abstract sense. For example, understanding morphology as a system's symmetry, its confinement (e.g. chemical reactions), or its coupling topology.

Statistical Physics of Control and Learning The program seeks to lay the foundations for an algorithmic theory of control and learning that goes significantly beyond the state of-the-art in model predictive control and integrates novel learning methodologies that are not mere variations of artificial neural networks and deep learning. Additional goals of this program is to develop an experimentally tested theoretical framework for controlling and creating new types of critical dynamics, phase transitions, and universality classes by bringing together theory and physical principles in statistical dynamics with control and dynamical systems theory (controlling statistical dynamics).

Topics of interest relating to this include: nonlinear control of distributions with non-Gaussian uncertainty; non-Gaussian uncertainty representations; understanding relationships between work absorption and dynamics in the presence of fluctuations leading to emergent prediction and emergent centralization; steering multi-critical interacting dynamical systems toward desired universal scaling behaviors; externally controlling the strength of stochastic fluctuations and intrinsic noise in systems that are driven far from thermal equilibrium and display generic scale invariance; and selectively targeting and stabilizing specific self-generated spatio-temporal patterns in strongly fluctuating reaction-diffusion systems. Stochastic control at the microscale to enable novel manipulation of the dynamics of synthetic and natural biomolecular machines is also of interest.

Mechanics of Hierarchical and Heterogeneous Systems Recent experimental, theoretical, and computational advancements have made it possible to challenge macroscopic, continuum representations of inherently hierarchical systems like never before - acknowledging that desirable macroscopic characteristics arise as a function of architecture and interaction between scales cascading all the way down to the nanoscopic environments within. This thrust in part seeks to develop reduced order and component-level models of nano-scale mechanisms in order to identify principles of physical interaction in these intricate (and in most cases only stochastically or empirically understood) systems. In addition to understanding the capabilities of component and mechanism design at the nano-scale, the program encourages the characterization of energy and information passing from one "'scale" to the next, as well as sensing and control strategies that tap into hierarchical and complex systems at different scales and locations.

Topics of interest include, but are certainly not limited to: magnetohydrodynamics; the control of

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This document generated on 12/09/2024 plasmas; frontiers of dynamical systems theory exploring turbulence; modeling biochemical mechanisms in order to identify design principles that exceed their capabilities; locomotion at micro- and sub-micro-scales. The program highly encourages studies that approach these problems from the perspective of hierarchical structures as assemblies of known base units rather than continua whose emergent properties can be modeled by approximating the complexity of the structure within.

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Computational MathematicsTitle:

ARL-BAA-0034Announcement ID:

TPOC: Radhakrishnan Balu, PhD - radhakrishnan.balu.civ@army.mil - (301) 394-4302 ARL Office: Army Research Office (ARO) Discipline: Mathematics and Statistics;Physics ARL Foundational Research Competencies: Mechanical Sciences;Network, Cyber, and Computational Sciences;Photonics, Electronics, and Quantum Sciences;Weapons Sciences Army Modernization Priorities: Assured PNT;Network/C3I Keywords: Mathematical modeling, Scientific computation, Fractional order methods, Mathematics of QIS, Atmospheric physics, Embedded simulation

Description:

The research strategy of this program is to focus on the following opportunities for crucial discoveries: innovative methodologies for solving currently intractable problems that take advantage of symmetry, conservation, and recurrence, that can adapt to both the evolving solution and to the evolving run-time resource allocation of modern computer architectures;

novel algorithms that accommodate different mathematical models at different scales, interacting subsystems, and coupling between models and scales; methods that incorporate nonlocality through integral operators with advantageous representations. Research in this area will ultimately lead to the development of new mathematical principles that enable faster and higher fidelity computational methods, and new methods that will enable modeling of future problems.

Scientific computation is an essential component of scientific inquiry, complementing theory and experiment, and is also an essential element of engineering in both design and in failure autopsy.

Simulations in support of inquiry, design, or autopsy often require expert knowledge in order to select methods that are compatible with the assumptions of the scenario at hand, require considerable skill to properly set up, require considerable time, memory, and storage on large scale parallel/distributed/heterogeneous systems to compute, and require considerable skill and effort to distill useful information from the massive data sets which result. Expert knowledge is also required to quantitatively estimate solution accuracy and to estimate the time and effort required to achieve a desired accuracy. Data has become ubiquitous and is potentially very valuable in increasing solution accuracy and/or decreasing the effort required to solve, but mathematically sound methods for incorporating data into accurate simulations are incomplete.

Simulations are not always timely, with results often not being available until after they are needed, for example in calculating failure of New Orleans levees during Katrina and in revising those estimates based on real time surge data.

The emphasis in the Computational Mathematics program is on mathematical research directed towards developing capabilities in these and related areas. For problems that are not time-limited, research areas of interest include but are not limited to the following:

Advances in Numerical Analysis. Novel methodologies are sought for solving currently intractable problems. New ways of taking advantage of symmetry, conservation, and recurrence are of interest, as are new ways of creating sparsity and new computational structures which can

This document generated on 12/09/2024

This document generated on 12/09/2024 adapt to both the evolving solution and to the evolving run-time resource allocation of modern computer architectures. Rigorous analysis is sought for each in order to enable error bounds, error distribution, and error control.

Mathematics for Quantum Information Systems (QIS). New mathematical constructs and understanding are sought in order to provide useful mathematical tools and language to others working to advance QIS. QIS goes far beyond quantum computing (QC), with focus also on quantum networking, quantum sensing, topological quantum computing, and topological phases of matter. Advances are sought in factors of von Neumann algebras, type II and type III, that are yet to be fully explored even after a century of studies from a QIS point of view. Topological quantum information processing going beyond anyons and in 3+1 spacetime dimensions are of interest. Exploration of noncommutative geometry from QIS point of view are important in pushing the field. Advances are sought in the language for quantum field theory as a basis for QIS and for the associated mathematical structures that are involved. New bases for QIS-based chemical and biological systems are just beginning; language and representations for these more-complex and messier-than-physics-based-systems are sought in order to enable new mathematical models. The QIS of metamaterials-based systems is very different from other systems, and new mathematics is sought that is capable of representing the unification of these disparate QIS themes.

Fractional Order Methods. As an alternative to high order methods and other less-local operators, fractional operators are another nonlocal operator that have proven to work well in modeling and have the advantage of not enforcing dubious assumptions of smoothness, especially at discontinuities and interfaces. However, the nonlocality of fractional operators also typically introduces a significant increase in computational load. Advances in novel efficient computational methods for these operators are of interest. Army systems often operate under rapidly-changing unpredictable and adverse conditions. It is desirable for models to be computationally simulated and fast enough to drive decision making, exercise control, and to help avoid disaster. Such simulations need to be created, run, and interpreted in better than real time. Research directed towards making this goal achievable is of interest, such as: Fast Methods for Atmospheric Physics. Modeling and prediction of local and mid-range atmospheric physics are a key part of the domain of operations. New exploratory efforts in fast algorithms for atmospheric physics have been identified as an area where new computational methods could make an important impact on problems of current and future Army interest. The emphasis of these efforts is on mathematical methods which have some promise of wider application rather than methods limited only to specific application areas.

Reduced Order Models. Full scale simulations are often not realizable in real time. In order to investigate the behavior of systems under a variety of possible scenarios, many runs are required.

Reduced order models are one way to enable this. Possible methods to create these models include adaptive simplification methods based on singular value decompositions and reduced order numerics. To be useful, all such models should be equipped with reliable estimates of accuracy.

Problem Solving Environments. To enable rapid decision making that is driven by simulation, it is necessary to set up simulations very quickly and obtain results in an understandable format.

Matlab is one current tool for such a problem solving environment. What are other approaches?

Embedded Simulation. As algorithms become more efficient and computational devices shrink, This document generated on 12/09/2024

This document generated on 12/09/2024 it will become increasingly possible to use real-time simulation to drive control systems. New methods which address this goal are welcome, especially those which permit user- controlled and/or adaptively-controlled tradeoffs between speed and accuracy. Decision Making. One valid criticism of numerical simulation is that it takes so long to set up, run, and post-process the results that they cannot be used in a timely manner to guide decision making. Mathematical ideas that help address this problem are of interest.

This document generated on 12/09/2024

Dynamical Influences on Social SystemsTitle:

ARL-BAA-0102Announcement ID:

TPOC: Gregory Ruark, PhD - gregory.a.ruark.civ@army.mil - (240) 890-3591 ARL Office: Army Research Office (ARO) Discipline: Computer Science;Mathematics and Statistics;Social Science ARL Foundational Research Competencies: Humans in Complex Systems;Military Information Sciences Army Modernization Priorities:

Keywords:

Description:

The overall goal of this program is to enhance fundamental understanding of the interdependent, reciprocal, and complex relationships across social systems accounting for environmental factors needed to enhance future warfighters' performance across operational contexts.