Defense Research Sciences

The Perceptually-Enabled Task Guidance (PTG) program developed artificial intelligence (AI) technology that guides users in the performance of a range of cognitively challenging physical tasks. PTG leveraged recent advances in machine perception, automated reasoning, and augmented reality. The program connects perception to reasoning and reasoning to augmented reality (AR) to create personalized, real-time feedback and contextualized assistance. To connect perception and reasoning, PTG developed AI technologies for (1) perceptual grounding, to create a shared vocabulary for perception and reasoning, and (2) perceptual attention, to select important information from large volumes of perceptual data. To connect reasoning with AR, PTG developed AI technologies for (3) knowledge transfer, to derive task models from instructions intended for humans, and (4) user modeling, to determine if, when, and how to best convey task information to the user. Together, PTG technologies laid the foundation for perceptually-enabled guidance and a qualitatively new type of AI device that enables mechanics and medics to perform physical tasks within and beyond their skillsets with greater accuracy and efficiency.

The Guaranteeing AI Robustness against Deception (GARD) program developed techniques to defend against deception and other adversarial attacks on machine learning (ML) and artificial intelligence (AI) systems. GARD addressed the need to defend against deception attacks, whereby an adversary inputs engineered data into an ML system intending to cause the system to produce erroneous results. Deception attacks can enable adversaries to take control of autonomous systems, alter conclusions of ML-based decision support applications, and compromise tools and systems that rely on ML and AI technologies. Previous techniques for defending ML and AI were brittle due to a focus on individual attack methods and weak methods for testing and evaluation. The GARD program developed techniques that addressed the limitations of defenses and produced ML and AI systems suitable for use in adversarial environments. The GARD program also developed theory regarding potential fundamental limits on achievable ML robustness.

The social and behavioral sciences provided essential theories and models to enable deeper understanding of human social/behavioral systems relevant to national security such as mental health, humanitarian aid, disaster relief, and stability support missions, as well as tactical, operational, strategic, and policy-level decision-making across the Department of Defense (DoD). However, limitations to the speed, scalability, and reproducibility of empirical social science research continued to hamper its practical use by the DoD. Additionally, social behavioral models often failed to accurately interpret social behaviors because they did not sufficiently capture diversity of context. The Human Social Systems thrust addressed these limitations by focusing on the following technical challenges: (1) development and validation of new methods, models and tools to perform rigorous, reproducible experimental research at scales necessary to understand emergent properties of human social/behavioral systems; (2) identification methods to better characterize and quantify properties, dynamics, and behaviors of different social/behavioral systems to enable better and more confident forecasting of changes in such systems, particularly when under stress; (3) development of an understanding of the complex effect of context and incorporating these effects into models; and (4) development of strategic forecasting and operational decision aiding capabilities to account for local contextual and cultural factors to assess the likely effectiveness of and/or responses to actions within an Area of Operations. This research thrust endeavored to provide DoD with new, reliable strategies to better understand and respond to social/behavioral system issues at multiple scales (from small group to cities and/or regions) and to significantly improve DoD stabilization, deterrence, and/or gray zone mission outcomes.

The Advanced Tools for Modeling and Simulation thrust is developing foundational mathematical, computational, and multi-physics theories, approaches, and tools to better represent, quantify, and model complex Department of Defense (DoD) systems from multimodal data analysis through part/system design and fabrication. One focus area of this thrust is developing is a unified mathematical framework to enable better visualization and analysis of massive, complex data sets. Rigorous mathematical theories are also being developed to address uncertainty in the modeling and design of complex multi-scale physical and engineering systems, incorporating capabilities to handle noisy data and model uncertainty that were well beyond the scope of capabilities that existed at the time. Other work in this thrust focuses on developing the mathematical and computational tools required to generate and better manage the enormous complexity of design, ultimately allowing designers to more easily discover non-intuitive (yet realizable) designs that fully leverage new materials and advanced manufacturing approaches now available. Outcomes from this thrust seek to improve the speed and accuracy of modeling and simulation, as well as enable management of complexity across DoD devices, parts, and systems. Another focus area of this thrust is the development of quantum-assisted approaches for predicting behavior and non-intuitive failure pathways for complex, dynamic physical systems. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-01.

The Scientific Feasibility (SciFy) program is developing computational methods to measure the feasibility of claims to enable accurate assessments of scientific content. Automated scientific content generation, via rapidly improving large pre-trained models, has the potential to disrupt the U.S. technology base in times of crisis and to distort the global race for technological dominance in key areas. Similarly, false capability claims can have significant negative implications for national security and international relations. To address these threats, SciFy focuses on methods for assessing the scientific feasibility of claims by using automated reasoning to decompose claims into constituent, verifiable parts. Assessing each component involves referencing existing technological advancements, foundational scientific principles, data, software, models, simulation results, and industry standards or benchmarks. SciFy will create methods that go beyond automated fact-checking by addressing complex component interactions and operational constraints, and evaluating logical consistency, system integration, and compatibility considerations. If successful, SciFy will enable the U.S. to reliably determine whether claimed scientific and technological capabilities are practical and realistic when considered as a whole, even when theoretically possible in parts. The SciFy program is also funded in PE 0602303E, Project IT-04. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-01 and PE 0602025E, Project MSL-05.

The Enhanced SBOM for Optimized Software Sustainment (E-BOSS) program is creating enhanced software bill of materials (eSBOM) technologies with new types of rich metadata and is developing cyber reasoning algorithms and tools that leverage eSBOMs to defend against potential flaws during the software development process and to triage and remediate flaws found in operation. The global impacts of flawed software deployed at scale, such as the Log4Shell vulnerability found in Log4j cloud and web app deployments, where mitigations took from one week to months, motivated new SBOM requirements in Executive Order 14028. SBOMs alone, however, cannot enable identification and mitigation of the flow of hostile data to the flaws in the code. E-BOSS is developing software technologies integrated with modern software build chains to enable rapid triage and remediation of vulnerabilities at enterprise scale. The enhanced metadata incorporated in the eSBOMs will enable trace back of discovered flaw evidence to derive the vulnerability triggers, starting from a crash and tracing back through complex inter-component interactions, transfers, and transformations. If successful, E-BOSS technologies will enable cyber-reasoning for improved remediation and sustainment of large-scale software systems. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-01.

The Intrinsic Cognitive Security (ICS) program is extending computational formal methods with cognitive guarantees and models to protect mixed reality (MR) users from cognitive attack. MR integrates virtual and real worlds in real time and will be ubiquitous in future military missions, including missions involving dismounted soldiers. Currently, users of MR systems are vulnerable to a wide variety of adversary attacks that exploit the intimate connection between users and MR equipment. Formal methods are rigorous, mathematics-based approaches that provide guarantees about computer-based systems, such as the absence of exploitable weaknesses. Cognitive models represent aspects of human perception, action, memory, and reasoning. The ICS program extends formal methods by explicitly creating and analyzing cognitive models as part of MR system development to protect the user from cognitive attacks. ICS will create cognitive guarantees that address mixed reality vulnerabilities and are expressed in languages suitable for proofs from models; will build cognitive models for reasoning about users of mixed reality systems with sufficient fidelity relative to human behaviors; and will evaluate model, proof, and guarantee validity using automated reasoning tools and prototype implementations of proved guarantees. The cognitive protections to be developed under ICS will prevent exploitation of MR systems by adversaries. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-01.

The goal of the Young Faculty Award (YFA) program is to encourage junior faculty at universities and their equivalent at non-profit science and technology research institutions to participate in sponsored research programs that will augment capabilities for future defense systems. This program focuses on cutting-edge technologies for greatly enhancing microsystems technologies, biological technologies, and defense sciences. The long-term goal for this program is to develop the next generation of scientists, engineers, and mathematicians in key disciplines who will focus a significant portion of their careers on Department of Defense (DoD) and national security issues. The aim is for YFA recipients to receive deep interactions with DARPA program managers, programs, performers, and the user community. Current activities include research in fifteen topic areas spanning from Machine Learning and Many Body Physics, to Wideband Transmitter-Antenna Interfaces and Multi-Scale Models of Infectious Disease Dynamics. A key aspect of the YFA program is DARPA-sponsored military visits; all YFA Principal Investigators are expected to participate in one or more military site visits to help them better understand DoD needs. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-01.

The Atomic-Photonic Integration (A-PhI) program is reducing the size, weight, and power of atomic clocks and gyroscopes for position, navigation, and timing (PNT) applications through the development of integrated photonics. Specifically, A-PhI will demonstrate that a compact photonic integrated chip can replace the optical assembly for trapped atomic gyroscopes and clocks without degrading the performance of the device. PNT is a critical resource for all DoD missions such as communications, navigation, reconnaissance, and electronic warfare. While PNT needs usually are met by using the global positioning system (GPS), GPS signals are vulnerable to disruption and a fallback from GPS is essential. In the absence of GPS, tactical-grade clocks and tactical/navigation grade inertial measurement units (IMUs) currently can provide GPS-like accuracy only for the short term, and longer-term GPS-independent strategies are highly desirable. A-PhI will enable long-term GPS independence and enable better-than-GPS PNT accuracy for short durations.

The Joint University Microelectronics Program 2.0 (JUMP 2.0) program is developing and demonstrating innovative next-generation microelectronics technologies through a public-private consortium with universities, the defense industrial base, and the semiconductor industry. The JUMP 2.0 program addresses the grand technical challenges of our increasingly connected world that must be overcome including: the need for innovation in analog hardware, increasing demand for more memory and data storage, the imbalance between data generation and communication capacity, the emerging security vulnerabilities in highly interconnected Artificial Intelligence systems, and the unsustainable growth in energy demands for computing. Therefore, the JUMP 2.0 program sponsors academic research teams focused on related key technology areas that will not only impact future defense and national security capabilities but also strengthen U.S. leadership in information and communication technology. The JUMP 2.0 program will push fundamental technology research themes in cognition, communications, sensing to action, computing and processing, memory and storage, integration and packaging, and high-performance energy efficient devices to enable key disruptive advances in microelectronic technology. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-02.

The Compartmentalization and Privilege Management (CPM) program is developing new system frameworks, architectures, and tooling to provide fine-grained, least-privileged compartmentalization that enables prevention and containment of cyber attacks. Today's information systems are structured around a monolithic core, the kernel, that operates within a single protection domain at a single high privilege-level. A monolithic kernel contains many separate components without protection boundaries between them. A single compromise anywhere in the system allows attackers effectively unlimited access through an extended sequence of exploits, privilege escalation, and lateral motion. CPM is developing technologies and tools to compartmentalize large, legacy software systems automatically and designing processor architectures and system software to enforce a compartment and privilege-level regime. CPM tools and architectures will prevent initial penetrations from propagating into successful cyber attacks. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-02.

The Advanced Microsystems Manufacturing Technologies Studies and Concepts will examine the infrastructure needed to bring sustainability to advanced microsystems. Studies will examine technologies that reduce the cost and time-to-market footprint of microsystems manufacturing as well as foundational ecosystem enhancements that could provide far-reaching impact. This program will also examine ways to take advantage of commercial scaling while building in superior capabilities for defense systems through design and integration. These studies may lead to the development of new programs in these areas.

The Low Temperature Logic Technology (LTLT) program exploited the unique device and material performance characteristics of state-of-the-art silicon transistors at cryogenic temperatures. Current silicon transistors were performance and power limited when operating at room temperature or higher. This program removed these limitations through modifying the design of existing silicon transistors to optimize their performance at cryogenic temperatures. The resulting devices are compatible with current complementary metal-oxide-semiconductor (CMOS) fabrication process flows and offer significant increases in performance and power efficiency over room temperature devices. This program has applied research efforts funded in PE 0602716E, Project ELT-02.

Understanding the Fundamental Limits (i.e., achievable boundaries) of scientific principles, processes and technologies is critical to better anticipate technological surprise for our adversaries and ourselves. This thrust explores boundaries across fields such as physics, chemistry, mathematics, biology, and engineering to address critical questions for national security, addressing foundational theory and approaches that include, for example, the fundamental limitations of optical technologies, potential implications for basic biology on national security, and the ability for modeling and simulation to provide a better understanding of complex systems. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-03.

The Molecular Systems and Materials Assembly thrust is exploring new approaches for the synthesis, assembly, characterization and application of molecules and materials for a variety of DoD applications from the atomic to the product scale. Ultimately, materials and methods developed in this thrust will support a wide range of DoD applications that will leverage novel materials to extend the range, duration, and capabilities of DoD systems and the warfighter. Through control of the arrangement, interactions, and assembly of atoms and molecules, new materials and manufacturing processes are being developed to address long-standing challenges in supply chains, logistics, and sustainment while simultaneously enhancing the warfighter's capabilities on the battlefield. Efforts in this thrust range from fundamental science to better understand the chemistry and physics related to each application, to developing means to utilize such capabilities in future test systems and prototype devices. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-03.

The grounds for strategic surprise are often realized through the discovery of unifying principles, novel fundamental limits, and unexpected connections between nominally disparate fields. Examples include new fundamental limits of sensing and information gathering capabilities enabled by multimodal sensor networks and new avenues to high performance information processing by encoding information within dynamical physical or biological systems. This thrust explores emergent capabilities and universal themes at the interface of quantum science, mathematics, nanoscience, and materials science to develop novel approaches to critical national security needs. Focus areas include harnessing the universal principles of turbulence from new forms of simulation for high complexity physical systems; systemic discovery of materials with desired properties; the analysis of new scientific and technological ideas of importance to national security. Beginning in FY 2026, this program will be funded as Materials Sciences Studies and Concepts in PE 0601122E, Project EMR-03.

The Rapid Healing for Warfighter Injuries effort addressed the DoD need for improving warfighter recovery from injury by developing technologies that can accelerate the restoration and repair of complex wounds. This program developed approaches that combine high-resolution biosensors to track the healing process in real-time with bioactuators to stimulate restoration where and when needed. The primary challenge to achieving this was the lack of a closed-loop interface that can manipulate highly complex signaling pathways in wounds and the developmental interdependencies that scale from cell to tissue. The program developed new methods to convert dense multi-modal information into the body's native repair processes and leveraged artificial intelligence to guide the delivery of the signals necessary for healing. Advances from this program produced bioactuators that can release diverse stimuli with high spatial and temporal resolution, and biosensors that provided the requisite in situ measurement to guide the healing process.

The Engineering Functional Materials with Biology program pursued new approaches to engineer complex biological systems for enhanced capabilities and functional materials to improve military infrastructure design and logistics, sensors, and platforms. Complex biological materials and systems have unique properties (e.g., controlled porosity, high strength-to-weight ratios, tunable magnetic and optical properties, etc.) not only because of the inherent biological components but also because of how those components are assembled together from microscopic to macroscopic scales. Engineering biology tools and techniques are now at a stage to improve the production, organization, and function of biomaterial systems for a variety of expanded capabilities, including those that can help DoD address supply chain challenges. This program conducted research to enable information-driven assembly of hierarchical biological systems for materials as well as alternate approaches for the production of critical molecules and materials. Advances in this program impacted: next-generation material design for optical and electronic applications; military approaches to infrastructure design in austere environments; and established methods for the manufacture and maintenance of military platforms.

The Knowledge Management at Scale thrust is focused on the development of knowledge management tools that can efficiently capture, analyze and reason with expertise, experience and data. The technology development under this thrust will help address a critical need for assimilating and preserving critical national security knowledge and expertise that is currently being lost due to attrition and other factors. Specific objectives include the following: 1) effective, trustworthy, and easily accepted approaches for domain agnostic knowledge acquisition at scale; 2) capabilities to identify correlations or hidden factors relating to knowledge acquired from different sources; and 3) techniques for incorporating domain models and other data sources for more extensive reasoning-based applications. Example approaches towards achieving these objectives include identifying and demonstrating robust knowledge acquisition tools, exploiting Artificial Intelligence (AI) techniques to establish a framework for knowledge analysis and causal reasoning, and developing automation tools that effectively elicit and impart acquired knowledge via user friendly interfaces.

The Environment-driven Conceptual Learning (ECOLE) program is creating artificial intelligence (AI) agents capable of continually learning from linguistic and visual input to enable human-machine collaborative analysis of image, video, and multimedia documents during time-sensitive, mission-critical Department of Defense analytic tasks, where reliability and robustness are essential. ECOLE aims to transform current machine learning approaches by developing algorithms that can identify, represent, and ground the attributes that form the symbolic and contextual model for a particular object or activity through interactive learning with a human analyst. Knowledge of attributes and affordances, learned dynamically from data encountered within an analytic workflow, will enable joint reasoning with a human partner. The acquired knowledge will also enable the machine to recognize when an observed object or activity is novel rather than misclassifying the newly observed object or action as a member of a previously-learned class and to readily learn a new symbolic representation through interaction with its human partner.

The Foundational Artificial Intelligence (AI) Science thrust is developing a fundamental scientific basis for understanding and quantifying performance expectations and limits of AI technologies. Current AI technologies are challenged in handling uncertainty and incompleteness of training protocols and data. This has prevented the successful integration of AI technology into many transformative Department of Defense (DoD) applications. To address these limitations, the Foundational AI Science thrust focuses on the development of new learning architectures that enhance AI systems' ability to handle uncertainty, reduce vulnerabilities, and improve robustness for Department of Defense AI systems. One focus area of this thrust is the ability to detect and accommodate novelty - i.e., violations of implicit or explicit assumptions - in AI applications. Another focus area is the development of a model framework for quantifying performance expectations and limits of AI systems as trusted human partners and collaborators. A third focus area is the development of new tools and methodologies that enable AI approaches for accelerated scientific discovery. The technology advances achieved under the Foundational AI Science thrust will ultimately remove technical barriers to exploiting AI technologies for scientific discovery, human-AI collaboration, accommodating novelty, and other DoD relevant applications.

The Fostering Research and Growth in Emerging Artificial Intelligence (AI FORGE) project aims to capture and solve pre-competitive AI research challenges to accelerate the development and fielding of frontier AI for national security. At present, a relatively small number of frontier AI companies drive most innovation in AI with a strong focus on commercialization and return-on-investment. AI FORGE seeks to make national security considerations more prominent in the generative AI development lifecycle. These considerations primarily involve the life- and mission-critical nature of national security generative AI use cases, which span information-centric intelligence analysis to grounded planning of logistics and tactical operations to embodiment in autonomous systems, and the highly adversarial nature of battlefield operational environments. For such use cases and environments, challenges of assurance, predictability, reliability, resilience, and transparency are of heightened importance. AI FORGE will conduct high-risk, high-reward efforts that address cross-cutting challenges that arise when using frontier AI for national security applications, systems, and missions. AI FORGE will combine the talents of universities with resources from frontier AI companies to create an R&D ecosystem focused on national security. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-01.

The Exponentiating Mathematics (expMath) program will to develop and apply artificial intelligence (AI) techniques to enable breakthrough advances in national security-related mathematical fields. At present, important problems in mathematics take decades or centuries to resolve, but recent advances in generative AI (genAI) and large language models (LLMs) offer the promise of accelerating advances in mathematics. expMath aims to use AI to automate the discovery of new mathematical knowledge. Creating an AI with these mathematical capabilities will require advances along two fronts: decomposition/abstraction and formalization/informalization. expMath will focus on mathematical domains of particular importance for national security. If successful, expMath will provide the basis for potential leap-ahead mathematical capabilities for the U.S. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-01.

The Translating All C To Rust (TRACTOR) program aims to automate the process of transitioning legacy C to Rust, with the same quality and style that a skilled Rust developer would employ. At present, buffer overflow vulnerabilities and other related memory safety software flaws allow an attacker to inject messages that hijack control of a computer. TRACTOR combines programming language and machine learning techniques, including large language models, to eliminate memory safety vulnerabilities. TRACTOR researchers are building C to Rust translation systems for single-threaded application translation, and, with this experience, will then address multi-threaded application translation. If successful, TRACTOR will enable the wholesale translation of C programs to Rust, thereby eliminating memory safety vulnerabilities in mission-critical and other high-priority software-reliant systems. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-01.

This thrust will develop new mathematical tools for analyzing large data sets for the discovery of new/hidden relationships, for the prediction of phenomena and (rare) events, for the disentanglement of multimodal data, as well as for the discrimination between valuable and invaluable information. This thrust includes the development of novel algorithms to search data, identify and quantify their relationships for task-specific applications and enable the generalizable abstractions directly from experimental data. Emerging opportunities in this thrust will explore quantum algorithms for modeling complex systems for the simulation of highly correlated materials and systems that are intractable with current classical approaches, i.e. modeling magnetism, superconductivity and nature. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-01.

*Previously part of Foundational Artificial Intelligence (AI) Science In the Moment (ITM) supports the development of algorithms that are trusted to make decisions independently in difficult domains. Military operations, such as mass casualty triage and disaster relief, require complex and rapid decision-making in dynamic situations where there is often no human consensus and no ground truth. The ITM program generates a quantitative alignment framework for trusted human decision-makers and algorithms. ITM investigates these decision-making problems in the context of medical triage in military environments. If the ITM program is successful, the alignment framework will support the development of algorithms that can be tuned to align with specific, trusted humans. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-01.

The grounds for strategic surprise are often realized through the discovery of unifying principles, novel fundamental limits, and unexpected connections between nominally disparate fields. This thrust explores emergent capabilities and universal themes at the interface of quantum science, mathematics, nanoscience, and materials science to develop novel approaches to critical national security needs. Emerging opportunities in this thrust will explore and analyze new scientific and technological ideas, seeking answers to high-risk/high-reward "what if?" questions, and assess the impact of further investment on problems of importance to national security. Understanding the complex interplay between Department of Defense (DoD) systems and their environment is critical in developing new platforms and in determining the limitations of current platforms. Current mathematical tools cannot capture the nonlinear, multiscale, high dimensional dynamics of the coupled/multiscale physics that describe these complex physical systems. Beginning in FY 2026, this program will be funded as Artificial Intelligence Studies and Concepts in PE 0601122E, Project EMR-01.

The Advanced Research Concepts (ARC) program will rapidly explore revolutionary, nascent high-risk/high-reward ideas to accelerate the discovery of paradigm-shifting technologies. The program will focus on answering fundamental research questions to investigate the boundaries of what is possible and push the state of the art of science and technology. By exploring a high volume of ideas through targeted and limited-scope investments, this program will identify promising ideas early and assess the impact of further investment on problems of importance to the Department of Defense. The program will cover a broad spectrum of science and engineering disciplines that have applications for national security research. Individual efforts will explore numerous emerging technologies in various thrusts including, but not limited to, artificial intelligence and machine learning, mathematics, biology, chemistry, quantum technologies, social science, material science, electronics, sensing and measurement, and modeling. Beginning in FY 2026, this program will be funded in PE 0601122E, Project EMR-01.

The Pipelined Reasoning of Verifiers Enabling Robust Systems (PROVERS) program is creating the basic science and technology needed for continuous reasoning about complex systems that can support software development pipelines. These mathematically based techniques, or formal methods, enable rigorous modeling, reasoning, and proving diverse properties of software code or design models, for example, the absence of a specific type of defect or security vulnerability. PROVERS integrates formal methods into a modern incremental and iterative development process by running tools at each code commit and delivering results to developers when they can most effectively remediate discovered issues. To achieve this, PROVERS is focusing on creating and sustaining a body of evidence that can co-evolve with the system under change to support continuous assessment and ensure that the system remains free of identified categories of defects and security vulnerabilities through its lifetime. Key PROVERS objectives include enabling proof maintenance and repair capabilities at a cost that is proportionate to code change; integration of formal methods with code, properties, and proofs in a single workflow that reduces human involvement; providing improved explanations to facilitate proof repair; and automating formal methods-based software analysis to support software developers that are not formal methods experts. PROVERS science and technology will facilitate the agile development and continuous improvement of mission-critical software systems that meet the high security and quality standards required by the Department of Defense (DoD). Beginning in FY 2025, this program is funded in PE 0602303E, Project IT-03.

The Alternative Computing thrust explored and developed new computational primitives for modeling and simulating complex systems. Despite decades of rapid advancement in electronic computing, there remained important national security relevant challenge problems that did not lend themselves to achieving tractable solutions under size, weight, and power (SWaP) constrained conditions. For example, simulation of complex nonlinear phenomena such as turbulence, fluid flow, and plasma dynamics can be challenging even using currently available high-power computing resources. Built on technologies developed under the Advanced Tools for Modeling and Simulation thrust, also in this PE/Project, the goal of the Alternative Computing thrust was to develop novel architectural and algorithmic approaches to enable fast and accurate simulations for problems that are practically intractable using electronic computers. Approaches considered under this thrust included the following: (1) analog computing substrates for efficiently simulating systems governed by complex non-linear phenomena; (2) multi-functional spin-based devices for scalable, efficient neuromorphic computing; (3) computing approaches that exploit the capacity of nonlinear systems to simulate nonlinear dynamical systems; and (4) quantum enabled optimization of complex systems.