The potential of quantum communications lies in the phenomena called "entanglement." It involves entangling two or more subatomic particles, like photons, which are connected even at vast distances. Moreover, these subatomic particles have correlated behaviors, such as polarization and spin. And if you know the state of one particle, you know the state of the other connected particle, no matter how far away it is. Thus, quantum entanglement portends huge advances for communications and cryptography.
Entangling two photons is much easier in a lab than when using two quantum nodes kilometers apart and connected by fiber network. The two photons must arrive at the third node within a fraction of the time the photons need for entanglement; depending on conditions, this can be several nanoseconds, picoseconds, or even femtoseconds.
To synchronize the two nodes, NIST researchers used an Ethernet-based time transfer system called "White Rabbit," with a "leader rabbit' and "follower rabbit" at the two nodes. The White Rabbit system repeatedly helped synchronize the two nodes to within four picoseconds and enabled photon entanglement with greater than 90 percent probability. Additionally, the experiments showed that quantum and White Rabbit signals can coexist on the same fiber.
In the Internet, laser light is used to carry signals to intended destinations. Such optical communications enabled the establishment of the global Internet and made broadband affordable. However, with the transmission of huge amounts of data, the optical backbone for global networks is approaching a "capacity crunch."
To help address this problem, NIST, University, and Joint Quantum Institute researchers demonstrated a potentially more efficient way of doing optical communications, which is described in Energy and bandwidth efficiency optimization of quantum-enabled optical communication channels, published in Nature's npj Quantum Information. Specifically, researchers assessed quantum-enabled optical communications, relative to current optical communications.
Researchers developed three different laser pulse modulations which were quantum-enabled, meaning they were intended to be energy and bandwidth efficient. In a testbed designed for this experiment, researchers transmitted these modulations, carrying messages with varying lengths of alphabetic letters. These were sent to a quantum receiver, which continuously estimates the reliability of messages and corrects errors in them. Researchers then assessed the three laser pulse modulations for message accuracies and energy and bandwidth efficiencies and compared them to current optical communications.
Researchers found that quantum-enhanced optical communications transmitting long messages showed significant advantage over current optical communications. Of the three quantum-enabled, laser pulse modulations, the one termed "hybrid frequency-phase shift keying" (HFPSK) achieved the greatest accuracy in terms of long messages and greatest energy and bandwidth efficiencies. Researchers believe this work can aid further development of quantum-enabled optical communication systems and a better understanding of the properties of the quantum measurement.
In June 2022, NIST's Conrad Bock proposed upgrades for the Systems Modeling Language (SysML 2) to the standards development organization, Object Management Group (OMG), which is responsible for its upgrade. SysML 2 is widely used to specify requirements, design and testing of complex systems.
As part of this upgrade to SysML 2, Bock proposed modeling spatial relationships within a system – but without committing to specific geometries or shapes for objects. For example, requirements for landing gear to be inside or outside a plane at given periods could be captured early in development and later refined with topologies, geometries, and behaviors in detailed designs. This proposed language upgrade includes a library of basic geometrical shapes, defined topologically with quantitative attributes, for assembly into more complex shapes. The proposed upgrade also would enable the modeling language to translate topology and geometry to and from ISO STEP 242 Managed model-based 3D engineering.
The proposed spatial modeling upgrades also integrate with time models in SysML 2, under a NIST-developed, four-dimensional framework. The integrated model enables specification and simulation of non-colliding paths for objects, such as those occurring in assembly and disassembly, as well as for transportation safety, such as when autonomous vehicles negotiate street intersections.
Since March 2018, Bock has presented quarterly to the OMG on SysML 2 and the logical architecture it uses. Bock and colleagues at NIST and OMG developed the architecture in earlier work, leveraging ontology-based languages, such as the OWL 2 Web Ontology Language (OWL 2) and NIST’s Process Specification Language (PSL), a first-order axiomatization processes, supporting automated, consistency checking of process rules and specifications.
NIST has aided manufacturing's transition from paper-based representations – like 2D blueprints – to digital representations, such as 3D graphics, as well as their digital flow – or "digital thread" – across manufacturing processes. But this digital transition has also given rise to digital threats, which seek to maliciously change designs and corrupt files. NIST has worked with stakeholders to develop a forthcoming web-based application called "EasyTrust," which will provide easy to implement solutions for countering and mitigating threats.
The panel addressed the problem with ensuring trust. Krima pointed out that solutions exist, but are very complex, hard to understand, and expensive to implement, deploy, maintain. He also said that 75 percent of the 250,000 manufacturers in the U.S. have 20 employees or less. Smaller companies often do not have resources to invest in building and ensuring trust. Providing all with access to easy to implement solutions was the motivation for NIST's EasyTrust project, stated Krima.
The panel also discussed the costs of inaction – which Krima noted are high. It is more than tampering with a part that causes a dishwater not to work, he said. It may result in a faulty part that leads to an aircraft losing power at 10,000 feet.
Additionally, the panel considered solutions ensuring safety. However, a state of complete safety is unachievable, said Krima. Manufacturers are facing state sponsored adversaries, with significant means. Meeting these threats means having mitigation strategies and technical solutions for protecting data.
NIST's "Digital Thread" project promotes the transmission of standardized digital information across engineering domains: design, simulation, manufacturing, inspection, business, and marketing. It is a big challenge. Each domain has varying digital information needs and unique data representations. The challenge is seen in geometric modeling – computer-aided representations of objects – used across these domains. And geometric modeling is facing demands to show more than just graphic representations and information related to shape. Users also need accompanying semantic data about a product, like its material compositions, finishes, and more.
In late June, the 2022 AIAA Aviation Forum focused on this challenge in its panel on Geometry Modeling to Support the Digital Thread. Panel participants included NIST collaborator Ben Urick, president of nVariante Inc. and recognized expert in geometric modeling, who is funded through a NIST Cooperative Agreement to lead the ISO 10303 (STEP) T1 group on geometric and topological representation. Urick pointed out what must be done to ensure that geometric modeling – or computer aided technologies – can move standardized digital data across manufacturing domains:
Understand the use cases of computer-aided technologies across engineering domains, determining what is being generated and consumed across domains.
Ensure computer-aided technologies are generating representations that are "fit-for-purpose" when most are known to be derived from representations originating from another domain.
Determine digital information needs for each engineering domain and reconcile data differences, to achieve standardization – which will be a very tenuous task.
Determine unique data that does not require transmission to all engineering domains
Define the fundamental relationship between metadata and geometric modeling – failing to do so prevents engineering domains from incorporating artificial intelligence and machine learning capabilities in computer-aided technologies.
Map the needs for metadata and semantic product manufacturing information across engineering domains – which are presently unknown.
Develop a formal approach to generating "digital twins" – digital representations of a physical object – for each domain's use
Energy IoT for residential consumers (Smart Grid): This involves modernizing the electric grid and adding more renewables, such as residential rooftop solar photovoltaic (PV) systems; enabling the grid and home systems to coordinate energy use; and achieving decentralized edge control.
Automated Driving Systems (ADS) and Automated Vehicles: These monitor conditions and control real-time driving functions and behaviors for safe operation, using onboard and off-board communications, sensor data fusion, and analysis.
While these publications identify key interfaces for DER cybersecurity involving relevant parties such as local utilities, third party aggregators, and PV owners, Wollman pointed out that some entities, such as homeowners, may lack sufficient cybersecurity knowledge to understand and fulfill their end-user cybersecurity responsibilities. In these and other cases, an organizational-focused approach to ensuring cybersecurity may need to rely on other entities (utilities, aggregators/operators) to step up and help carry out these responsibilities.
The panel asked Wollman to explain use of NIST Special Publication 1500-201 Framework for Cyber-Physical Systems: Volume 1, Overview for managing risk and achieving interoperability. Wollman clarified that IoT and Cyber-Physical Systems (CPS) concepts have converged, and that the Framework provides a systems engineering methodology in which groups of concerns, including trustworthiness– security, safety, resilience, reliability, and privacy – are identified and addressed throughout any systems engineering process. This balanced approach provides the ability to address IoT security and other trustworthiness concerns in a broader operational technology context.
In late June 2022, NIST's David Holmberg and Cuong Nguyen participated on a panel, “Regulations in the U.S. and Germany and Their Impact on the Research Agenda,” in the Workshop on Bridging International Societal Differences in Autonomous and Digitized Energy Systems, Hybrid Hub at ACM e-Energy 2022. The panel focused on transitioning energy technologies into use, with Holmberg and Nguyen addressing the following challenges:
Gaining Social Acceptance: This requires dialogue at multiple levels, said Holmberg. Views and expectations vary with social environments and cultures. In the U.S., the Smart Electric Power Alliance aids collaborations with utility representatives, regulators, vendors, and other electric industry stakeholders like NIST.
Showing Value: Dialogues should include economists, said Nguyen. They must make a business case, showing an initiative's value. Also, there is a need to consider income levels, how much income goes to energy, and how to curb costs. However, modeling of energy initiatives does not yet consider income levels.
Considering Equity, Inclusion: We must look at disparity, said Nguyen, and how to level the playing field. Power companies are going beyond basic connect-and-serve, and adding other services – electric vehicle charging, solar panels – which may widen the disparity gap. In the U.S., equity and inclusion are getting attention in research related to energy services.
Getting to Decisions: In the U.S., legislation often provides timelines, said Holmberg, which drive different groups with different processes and leadership to make decisions. To succeed, vendors must understand political directions, social interaction, and regulatory impacts.
Implementing Standards: Standards are consensus-based and often allow many implementation options, said Nguyen. That makes testing and certification and interoperability hard to achieve. NIST, therefore, is developing "interoperability profiles" – proposing narrower ways of implementing, which can help industry pursue economies of scale.
NIST's Cuong Nguyen participated on the energy panel at the 2022 SelectUSA Investment Summit, held at National Harbor, Maryland, in late June 2022. Conducted annually, the Summit promotes foreign direct investment in US economic development and has attracted investors from 80 international markets. Based on NIST research, Nguyen offered two potential energy areas for investment:
Distributed Energy Resources (DER): These include wind and solar renewables, which generate power locally, thus reducing transmission and losses. Nguyen said NIST has aided their integration with the grid by working on standards for inverter-based resources, which convert power to and from AC and DC currents. NIST also developed a path for achieving interoperability in its IEC 61850 Profile for Distributed Energy Resources Supporting IEEE 1547, which proposes a focused way of implementing standards. NIST's intent is to enable common requirements that industry can build and test to and leverage economy of scale.
Electric Vehicle Charging Infrastructure: This is aided by the Infrastructure Investment and Jobs Act, noted Nguyen, resulting in the federal government funding state energy offices to build infrastructure for electric vehicle adoption. To aid interoperability with the grid, Nguyen said that a NIST-led effort with the Smart Electric Power Alliance produced Interoperability Profile for Electric Vehicle Fleet Managed Charging. It seeks to help manage electric vehicle charging so as not overtax the grid. Such interoperability also will enable electric vehicles to provide ancillary services to the grid. And to facilitate economy of scale, this profile focuses on electric vehicle fleets.
NIST personnel interacted with the public on these interoperability profiles, which prompted interest and questions. Summit participants also expressed interest in understanding federal and state energy regulations, which the National Association of Regulated Utility Commissioners is addressing with NIST's help.
In The growing cybersecurity threats in a smart grid environment, June 30, 2022, PowerGrid International reported on the proliferation of distributed energy resources – renewable energy systems – that generate and store power, such as wind turbines, rooftop solar, fuel cells and more. It further noted that, "Each new device entering the electrical grid is a potential access point for bad actors." With the grid's reliance on data networks, these actors can introduce a range of cyber threats: denial of service; malware propagation; eavesdropping and traffic analysis; and ransomware.
The news report also pointed out the significance of the NIST Framework and Roadmap for Smart Grid Interoperability Standards, Release 4.0. Quoting the Framework, the report states, "Its conceptual model 'supports a collective understanding of the actors, roles, and responsibilities needed to ensure effective day-to-day grid operations and control.'" The implication of this understanding is that it can help stakeholders develop a structured system security. Additionally, the report emphasized the Framework's call to action: “To realize the benefits of an interoperable smart grid, security practices will have to evolve beyond strategies of physical isolation or other overly restrictive access regimes.”
Annually, NIST selects students for Summer Undergraduate Research Fellowships (SURF) to work in areas that support its mission. NIST seeks to inspire students to serve in these fields. During their 11-week internship, students are exposed to cutting edge research areas and NIST researchers benefit from their fresh perspectives and thinking in these areas. The following are SURF students in the Smart Connected Systems Division and their projects:
Michael Belluscio: Sought to characterize the resilience of large segments of the electric grid during major disturbances that could interrupt customer service. This effort used and improved a Generator Fleet Characteristics Model, which helped the existing model deduce hourly generator allocations.
Ovidio Castillo: Simulated several manufacturing system configurations to determine their impact on the production line’s reliability, safety, speed, and product quality. Simulations also indicated the challenges and difficulties with configurations. Future research will pursue further optimization.
Hannah Covington: Focused on modeling appliance use to assess patterns and randomness in residential energy consumption. Notably, this modeling sought to distinguish income levels to assess fairness in energy consumption and cost. Findings included energy use and costs for given appliances.
Stephanie Estrella: Addressed issues against ISO 10303-2 Vocabulary, a part of the Standard for Exchange of Product Model Data (STEP), auto-generated from hundreds of STEP standards. She resolved duplicate terms and corrected definitions that did not meet ISO Directives, by editing intermediate files in an ISO git repository.
Prasun Guragain: Developed a cybersecurity awareness software that tracks assets and vulnerabilities in the infrastructure. Detection would allow a threat to be identified and contained. The software goal is to help business that do not have the resources to acquire complex solutions for cyber threats.
Benjamin Philipose: Conducted virtual testing of vehicles equipped with automated driving systems (ADS). This involved simulating three cases of ADS behaviors, as defined by scenarios. Future plans call for detection of swerving, hard braking acceleration, and shaky steering behaviors.
Aleysha Rachael Varghese: Assessed interoperability in smart grid operations, notably between Phasor Measurement Units (PMU), which monitor power systems, and a Phasor Data Concentrators, which aggregate data from PMUs. The assessment determined when data exchanges did and did not occur.
So much depends on tomorrow’s scientists, technologists, engineers, and mathematicians (STEM) – improved quality of life, equity and inclusion, and competitiveness. Thus, NIST seeks higher education institutions to partner in growing STEM careers. NIST Professional Research Experience Program (PREP) is accepting applications from accredited institutions of higher education that offer two- or four-year degrees in the U.S. and its territories in academic disciplines relevant to the technical programs of the NIST laboratories and major programs. Applications are due September 30, 2022.
Every year, NIST hosts hundreds of participants in its PREP program. It provides an opportunity for students, postdocs, and faculty to collaborate with NIST staff on research in advanced communications, artificial intelligence, physical sciences, science writing, science policy, and much more. The PREP program is a great launching point for STEM careers. For example, our Communications Technology Laboratory Director, Marla Dowell, started her NIST career as a postdoc in the NIST Boulder PREP program.
