Advanced Resource Estimation through Lattice Surgery Compilation and Logical Error Modeling
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This is a final report, which supports NASA's PECSEE (Persistent Cognizant Software Engineering Environment) effort and complements the Kestrel Institute project "Inference System Integration via Logic Morphism". The ultimate purpose of the project is to develop a superior logical inference mechanism by combining the diverse abilities of multiple cooperating theorem provers. In many years of research, a number of powerful theorem-proving systems have arisen with differing capabilities and strengths. Resolution theorem provers (such as Kestrel's KITP or SRI's, SNARK) deal with first-order logic with equality but not the principle of mathematical induction. The Boyer-Moore theorem prover excels at proof by induction but cannot deal with full first-order logic. Both are highly automated but cannot accept user guidance easily. The PVS system (from SRI) in only automatic within decidable theories, but it has well-designed interactive capabilities: furthermore, it includes higher-order logic, not just first-order logic. The NuPRL system from Cornell University and the STeP system from Stanford University have facilities for constructive logic and temporal logic, respectively - both are interactive. It is often suggested - for example, in the anonymous "QED Manifesto"-that we should pool the resources of all these theorem provers into a single system, so that the strengths of one can compensate for the weaknesses of others, and so that effort will not be duplicated. However, there is no straightforward way of doing this, because each system relies on its own language and logic for its success. Thus. SNARK uses ordinary first-order logic with equality, PVS uses higher-order logic. and NuPRL uses constructive logic. The purpose of this project, and the companion project at Kestrel, has been to use the category-theoretic notion of logic morphism to combine systems with different logics and languages. Kestrel's SPECWARE system has been the vehicle for the implementation.
Generic structures have been conceived for multiplexer blocks to be implemented in field-programmable gate arrays (FPGAs) based on four-gate field-effect transistors (G(sup 4)FETs). This concept is a contribution to the continuing development of digital logic circuits based on G4FETs and serves as a further demonstration that logic circuits based on G(sup 4)FETs could be more efficient (in the sense that they could contain fewer transistors), relative to functionally equivalent logic circuits based on conventional transistors. Results in this line of development at earlier stages were summarized in two previous NASA Tech Briefs articles: "G(sup 4)FETs as Universal and Programmable Logic Gates" (NPO-41698), Vol. 31, No. 7 (July 2007), page 44, and "Efficient G4FET-Based Logic Circuits" (NPO-44407), Vol. 32, No. 1 ( January 2008), page 38 . As described in the first-mentioned previous article, a G4FET can be made to function as a three-input NOT-majority gate, which has been shown to be a universal and programmable logic gate. The universality and programmability could be exploited to design logic circuits containing fewer components than are required for conventional transistor-based circuits performing the same logic functions. The second-mentioned previous article reported results of a comparative study of NOT-majority-gate (G(sup 4)FET)-based logic-circuit designs and equivalent NOR- and NAND-gate-based designs utilizing conventional transistors. [NOT gates (inverters) were also included, as needed, in both the G(sup 4)FET- and the NOR- and NAND-based designs.] In most of the cases studied, fewer logic gates (and, hence, fewer transistors), were required in the G(sup 4)FET-based designs. There are two popular categories of FPGA block structures or architectures: one based on multiplexers, the other based on lookup tables. In standard multiplexer- based architectures, the basic building block is a tree-like configuration of multiplexers, with possibly a few additional logic gates such as ANDs or ORs. Interconnections are realized by means of programmable switches that may connect the input terminals of a block to output terminals of other blocks, may bridge together some of the inputs, or may connect some of the input terminals to signal sources representing constant logical levels 0 or 1. The left part of the figure depicts a four-to-one G(sup 4)FET-based multiplexer tree; the right part of the figure depicts a functionally equivalent four-to-one multiplexer based on conventional transistors. The G(sup 4)FET version would contains 54 transistors; the conventional version contains 70 transistors.
Electronic logic gates that operate using N logic state levels, where N is greater than 2, and methods of operating such gates. The electronic logic gates operate according to truth tables. At least two input signals each having a logic state that can range over more than two logic states are provided to the logic gates. The logic gates each provide an output signal that can have one of N logic states. Examples of gates described include NAND/NAND gates having two inputs A and B and NAND/NAND gates having three inputs A, B, and C, where A, B and C can take any of four logic states. Systems using such gates are described, and their operation illustrated. Optical logic gates that operate using N logic state levels are also described.
Electronic logic gates that operate using N logic state levels, where N is greater than 2, and methods of operating such gates. The electronic logic gates operate according to truth tables. At least two input signals each having a logic state that can range over more than two logic states are provided to the logic gates. The logic gates each provide an output signal that can have one of N logic states. Examples of gates described include NAND/NAND gates having two inputs A and B and NAND/NAND gates having three inputs A, B, and C, where A, B and C can take any of four logic states. Systems using such gates are described, and their operation illustrated. Optical logic gates that operate using N logic state levels are also described.
How can we represent knowledge inside a computer? For formalized knowledge, classical logic seems to be the most adequate tool. Classical logic is behind all formalisms of classical mathematics, and behind many formalisms used in Artificial Intelligence. There is only one serious problem with classical logic: due to the famous Godel's theorem, classical logic is algorithmically undecidable; as a result, when the knowledge is represented in the form of logical statements, it is very difficult to check whether, based on this statement, a given query is true or not. To make knowledge representations more algorithmic, a special field of logic programming was invented. An important portion of logic programming is algorithmically decidable. To cover knowledge that cannot be represented in this portion, several extensions of the decidable fragments have been proposed. In the spirit of logic programming, these extensions are usually introduced in such a way that even if a general algorithm is not available, good heuristic methods exist. It is important to check whether the already proposed extensions are sufficient, or further extensions is necessary. In the present paper, we show that one particular extension, namely, logic programming with classical negation, introduced by M. Gelfond and V. Lifschitz, can represent (in some reasonable sense) an arbitrary first order logical theory.
The annual report on telerobotic control of a mobile coordinated robotic server is presented. The goal of this effort is to develop advanced control methods for flexible space manipulator systems. As such, an adaptive fuzzy logic controller was developed in which model structure as well as parameter constraints are not required for compensation. The work builds upon previous work on fuzzy logic controllers. Fuzzy logic controllers have been growing in importance in the field of automatic feedback control. Hardware controllers using fuzzy logic have become available as an alternative to the traditional PID controllers. Software has also been introduced to aid in the development of fuzzy logic rule-bases. The advantages of using fuzzy logic controllers include the ability to merge the experience and intuition of expert operators into the rule-base and that a model of the system is not required to construct the controller. A drawback of the classical fuzzy logic controller, however, is the many parameters needed to be turned off-line prior to application in the closed-loop. In this report, an adaptive fuzzy logic controller is developed requiring no system model or model structure. The rule-base is defined to approximate a state-feedback controller while a second fuzzy logic algorithm varies, on-line, parameters of the defining controller. Results indicate the approach is viable for on-line adaptive control of systems when the model is too complex or uncertain for application of other more classical control techniques.
Logic elements are provided that permit reductions in layout size and avoidance of hazards. Such logic elements may be included in libraries of logic cells. A logical function to be implemented by the logic element is decomposed about logical variables to identify factors corresponding to combinations of the logical variables and their complements. A pass transistor network is provided for implementing the pass network function in accordance with this decomposition. The pass transistor network includes ordered arrangements of pass transistors that correspond to the combinations of variables and complements resulting from the logical decomposition. The logic elements may act as selection circuits and be integrated with memory and buffer elements.
Described herein are various technologies pertaining to randomizing logic associated with dangling nodes in a digital circuit design. A dangling node is an input to or output from a logic gate in the digital circuit design that is identified as not impacting a desired output of the digital circuit design. Randomizing the logic associated with a dangling node can include deleting a logic gate, adding a logic gate, replacing a logic gate with another logic gate, etc. Randomizing the logic associated with the dangling node prevents hardware trojans that may have been inserted into the circuit design from being implemented in a circuit that is generated based upon the design.
Quantum error correction (QEC) is essential for the realization of large-scale quantum computers. However, owing to the complexity of operating on the encoded ‘logical’ qubits, understanding the physical principles for building fault-tolerant quantum devices and combining them into efficient architectures is an outstanding scientific challenge. Here we use reconfigurable arrays of up to 448 neutral atoms to implement the key elements of a universal, fault-tolerant quantum processing architecture and experimentally explore their underlying working mechanisms. We first use surface codes to study how repeated QEC suppresses errors, demonstrating 2.14(13)x below-threshold performance in a four-round characterization circuit by leveraging atom loss detection and machine learning decoding. We then investigate logical entanglement using transversal gates and lattice surgery and extend it to universal logic through transversal teleportation with three-dimensional [[15,1,3]] codes, enabling arbitrary-angle synthesis with polylogarithmic overhead. Finally, we develop mid-circuit qubit reuse16, increasing experimental cycle rates by two orders of magnitude and enabling deep-circuit protocols with dozens of logical qubits and hundreds of logical teleportations with [[7,1,3]] and high-rate [[16,6,4]] codes while maintaining constant internal entropy. Our experiments show key principles for efficient architecture design, involving the interplay between quantum logic and entropy removal, judiciously using physical entanglement in logic gates and magic state generation, and leveraging teleportations for universality and physical qubit reset. These results establish foundations for scalable, universal error-corrected processing and its practical implementation in neutral atom systems.
Abstract Recent compositionality results in logic have highlighted the advantages of enlarging the traditional notion of logical matrix semantics, namely by incorporating non-determinism and partiality. Still, several important properties which are known to be computable for finite logical matrices have not been studied in the wider context of partial non-deterministic matrices (PNmatrices). In this paper, we study how incorporating non-determinism and/or partiality in logical matrices impacts on the computational properties of some natural problems regarding their induced logics and concretely their sets of theorems. We show that, while for some of these problems there is no relevant computational impact, there are problems whose computational complexity increases and still other problems that simply become undecidable. In particular, we show that the problem of checking whether the logics characterized by two finite PNmatrices have the same set of theorems is not decidable. This undecidability result explores the connection between PNmatrices and term-DAG-automata, where the universality problem is known to be undecidable. This link also motivates a final contribution, in the form of a pumping-like lemma, which can be used, in some cases, to show that a given logic cannot be characterized by a finite PNmatrix.
Quantum computing stands at the threshold of a transformative decade, where the field will evolve from small-scale demonstrations toward practical scientific computing at scale. This Blueprint identifies fault-tolerant quantum computers (FTQCs) as a viable, scalable, and broadly applicable path to achieving “quantum scientific utility,” defined as solving scientifically valuable problems beyond the reach of conventional, classical computers. This capability is expected to show scientific demonstrations in the late 2020s and to mature in the early-to-mid 2030s. This Blueprint outlines a strategy to prepare the U.S. Department of Energy (DOE) for FTQCs and their integration into the U.S. national scientific computing infrastructure. Its purpose is to identify the steps, milestones, and research directions necessary for DOE to enable initial deployment of FTQCs in 2028 as a scientific tool for the nation and mature this capability into the 2030s. DOE has a long history of supporting quantum information science and technology, contributing significantly to research advancements, training a quantum-ready workforce, and providing access to early small-scale quantum hardware. Given recent demonstrations of logical operations on error-corrected logical qubits and the advancement of commercial hardware roadmaps, DOE should begin preparations for large-scale, fault-tolerant quantum computing deployment for DOE science missions. This Blueprint proposes that DOE focus on (1) deploying first-generation scientifically relevant quantum computers with at least 100 logical qubits and performing at least 10,000 to 100,000 hard logical operations in scientifically relevant calculations; (2) developing essential FTQC programming competencies, system software, and facility readiness; and (3) investing in cutting edge focused R&D that fosters breakthroughs in scientific applications, algorithms, and logical architectures needed to accelerate the advent of scientific utility. This effort will position DOE to transition to larger systems: production-scale quantum computers that comprise 1,000 to 10,000 logical qubits, perform 1 to 10 billion hard logical operations, and execute scientifically useful computations at scale. Achieving these goals will require DOE facilities to evolve with urgency to support scientific campaigns that integrate quantum and classical computing resources into efficient workflows, novel software and firmware environments for compiling and routing quantum programs on FTQC machines, and suitable infrastructure for quantum hardware. It will also require further development and optimization of scientific applications from the fields of materials science, quantum chemistry, and high-energy and nuclear physics. The Blueprint calls for transformative R&D and collective action to accelerate the advent of scientific quantum utility and bring it within reach by 2028.
A general method of automated modal logic theorem proving is discussed and illustrated. This method is based on the substitutional framework for the development of systems for hybrid reasoning. Sentences in modal logic are translated into a constraint logic in which the constraints represent the connections between worlds in the possible world semantics for modal logic. Deduction in the constraint logic is performed by a non-modal deductive system which has been systematically enhanced with special-purpose constraint processing mechanisms. The result is a modal logic theorem prover, whose soundness and completeness is an immediate consequence of the correctness of the non-modal deductive system and some general results on constraint deduction. The framework achieves significant generality in that it provides for the extension of a wide range of non-modal systems to corresponding modal systems and that can be done for a wide range of modal logics.
The goal of the research was to develop formal guidelines for the design of hazard avoidance systems. An alerting system is automation designed to reduce the likelihood of undesirable outcomes that are due to rare failures in a human-controlled system. It accomplishes this by monitoring the system, and issuing warning messages to the human operators when thought necessary to head off a problem. On examination of existing and recently proposed logics for alerting it appears that few commonly accepted principles guide the design process. Different logics intended to address the same hazards may take disparate forms and emphasize different aspects of performance, because each reflects the intuitive priorities of a different designer. Because performance must be satisfactory to all users of an alerting system (implying a universal meaning of acceptable performance) and not just one designer, a proposed logic often undergoes significant piecemeal modification before gamma general acceptance. This report is an initial attempt to clarify the common performance goals by which an alerting system is ultimately judged. A better understanding of these goals will hopefully allow designers to reach the final logic in a quicker, more direct and repeatable manner. As a case study, this report compares three alerting logics for collision prevention during independent approaches to parallel runways, and outlines a fourth alternative incorporating elements of the first three, but satisfying stated requirements. Three existing logics for parallel approach alerting are described. Each follows from different intuitive principles. The logics are presented as examples of three "philosophies" of alerting system design.
We introduce the temporal logic Jeagle and its supporting tool for runtime verification of Java programs. A monitor for an Jeagle formula checks if a finite trace of program events satisfies the formula. Jeagle is a programming oriented extension of the rule-based powerful Eagle logic that has been shown to be capable of defining and implementing a range of finite trace monitoring logics, including future and past time temporal logic, real-time and metric temporal logics, interval logics, forms of quantified temporal logics, and so on. Monitoring is achieved on a state-by-state basis avoiding any need to store the input trace. Jeagle extends Eagle with constructs for capturing parameterized program events such as method calls and method returns. Parameters can be the objects that methods are called upon, arguments to methods, and return values. Jeagle allows one to refer to these in formulas. The tool performs automated program instrumentation using AspectJ. We show the transformational semantics of Jeagle.
An optically intraconnected computer and a reconfigurable holographic optical element employed therein. The basic computer comprises a memory for holding a sequence of instructions to be executed; logic for accessing the instructions in sequence; logic for determining for each the instruction the function to be performed and the effective address thereof; a plurality of individual elements on a common support substrate optimized to perform certain logical sequences employed in executing the instructions; and, element selection logic connected to the logic determining the function to be performed for each the instruction for determining the class of each function and for causing the instruction to be executed by those the elements which perform those associated the logical sequences affecting the instruction execution in an optimum manner. In the optically intraconnected version, the element selection logic is adapted for transmitting and switching signals to the elements optically.
Operational requirements of safety-critical systems are often written in restricted specification logics. These restricted logics are amenable to automated analysis techniques such as model-checking, but are not rich enough to express complex requirements of unmanned systems. This short paper advocates for the use of expressive logics, such as higher-order logic, to specify the complex operational requirements and safety properties of unmanned systems. These rich logics are less amenable to automation and, hence, require the use of interactive theorem proving techniques. However, these logics support the formal verification of complex requirements such as those involving the physical environment. Moreover, these logics enable validation techniques that increase con dence in the correctness of numerically intensive software. These features result in highly-assured software that may be easier to certify. The feasibility of this approach is illustrated with examples drawn for NASA's unmanned aircraft systems.