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  1. A bstract In this work, we use Ising chain and Kitaev chain to check the validity of an earlier proposal in arXiv:2011.02859 that enriched fusion (higher) categories provide a unified categorical description of all gapped/gapless quantum liquid phases, including symmetry-breaking phases, topological orders, SPT/SET orders and CFT-type gapless quantum phases. In particular, we show explicitly that, in each gapped phase realized by these two models, the spacetime observables form a fusion category enriched in a braided fusion category such that its monoidal center is trivial. We also study the categorical descriptions of the boundaries of these models. In the end, we obtain a classification of and the categorical descriptions of all 1-dimensional (spatial dimension) gapped quantum phases with a bosonic/fermionic finite onsite symmetry.
    Free, publicly-accessible full text available March 1, 2023
  2. The security of manycore systems has become increasingly critical. In system-on-chips (SoCs), Hardware Trojans (HTs) manipulate the functionalities of the routing components to saturate the on-chip network, degrade performance, and result in the leakage of sensitive data. Existing HT detection techniques, including runtime monitoring and state-of-the-art learning-based methods, are unable to timely and accurately identify the implanted HTs, due to the increasingly dynamic and complex nature of on-chip communication behaviors. We propose AGAPE, a novel Generative Adversarial Network (GAN)-based anomaly detection and mitigation method against HTs for secured on-chip communication. AGAPE learns the distribution of the multivariate time series of a number of NoC attributes captured by on-chip sensors under both HT-free and HT-infected working conditions. The proposed GAN can learn the potential latent interactions among different runtime attributes concurrently, accurately distinguish abnormal attacked situations from normal SoC behaviors, and identify the type and location of the implanted HTs. Using the detection results, we apply the most suitable protection techniques to each type of detected HTs instead of simply isolating the entire HT-infected router, with the aim to mitigate security threats as well as reducing performance loss. Simulation results show that AGAPE enhances the HT detection accuracy by 19%, reducesmore »network latency and power consumption by 39% and 30%, respectively, as compared to state-of-the-art security designs.« less
    Free, publicly-accessible full text available March 14, 2023
  3. del Campo, Matias ; Leach, Neil (Ed.)
    Nature has always been the master of design skills to which humans only aspire to, but new approaches bring that aspiration closer to our reach than ever before. Through 4.5 billion years of iterations, nature has shown us its extraordinary craftsmanship, breeding a variety of species whose body structures have gradually evolved to adapt to natural phenomena and make full use of their unique characteristics. The dragonfly wing, among body structure is an extreme example of efficient use of materials and minimal weight while remaining strong enough to withstand the tremendous forces of flight. It has long been the object of scientific research examining its structural advantages to applying their principles to fabricated designs.1 We can imitate its form and create duplicates, but thoroughly understanding the dragonfly wing’s mechanism, behavior and design logic is no trivial task.
    Free, publicly-accessible full text available January 1, 2023
  4. Del Campo, Matias ; Leach, Neil (Ed.)
    Special Issue: Machine Hallucinations: Architecture and Artificial Intelligence Nature has always been the master of design skills to which humans only aspire, but new approaches bring that aspiration closer to our reach than ever before. Through 4.5 billion years of iterations, nature has shown us its extraordinary craftsmanship, breeding a variety of species whose body structures have gradually evolved to adapt to natural phenomena and make full use of their unique characteristics. The dragonfly wing, among body structures, is an extreme example of efficient use of materials and minimal weight while remaining strong enough to withstand the tremendous forces of flight. It has long been the object of scientific research examining its structural advantages to apply its principles to fabricated designs.1 We can imitate its form and create duplicates, but thoroughly understanding the dragonfly wing’s mechanism, behavior, and design logic is no trivial task.
    Free, publicly-accessible full text available January 1, 2023
  5. Alloying in two-dimensional (2D) transition metal dichalcogenides (TMD) has allowed bandgap engineering and phase transformation, which provide more flexibility and functionality for electronic and photonic devices. To date, many ternary TMD alloys with homogenous compositions have been synthesized. However, realization of bandgap modulation spatially within a single TMD nanosheet remains largely unexplored. In this work, we demonstrate the synthesis of spatially composition-graded WSe2xTe2-2x flakes using an in situ chemical vapor deposition method. The photoluminescence and Raman spectra line-scanning characterization indicate a spatially graded bandgap, which increases from 1.46 eV (center) to 1.61 eV (edge) within one monolayer flake. Furthermore, the electronic devices based on this spatially graded material exhibit tunable transfer characteristics.
  6. Free, publicly-accessible full text available February 1, 2023
  7. Free, publicly-accessible full text available January 1, 2023
  8. This research investigates the use of graphic statics in analyzing the structural geometry of a natural phenomenon to understand their performance and their relevant design parameters. Nature has always been inspiring for designers, engineers, and scientists. Structural systems in nature are constantly evolving to optimize themselves with their boundary conditions and the applied loads. Such phenomena follow certain design rules that are quite challenging for humans to formulate or even comprehend. A dragonfly wing is an instance of a high-performance, lightweight structure that has intrigued many researchers to investigate its geometry and its performance as one of the most light-weight structures designed by nature [1]. There are extensive geometrical and analytical studies on the pattern of the wing, but the driving design logic is not clear. The geometry of the internal members of the dragonfly wings mainly consists of convex cells which may, in turn, represent a compression-only network on a 2D plane. However, this phenomenon has never been geometrically analyzed from this perspective to confirm this hypothesis. In this research, we use the methods of 2D graphic statics to construct the force diagram from the given structural geometry of the wing. We use algebraic and geometric graphic statics tomore »unfold the topological and geometric properties of the form and force diagrams such as the degrees of indeterminacies of the network [2]. We then reconstruct the compression-only network of the wing for more than 300 cases for the same boundary conditions and the edge lengths of the independent edges of the network. Comparing the magnitude of the internal forces of the reconstructed network with the actual structure of the wing using the edge length of the force diagram will shed light on the performance of the structure. Multiple analytical studies will be provided to compare the results in both synthetic and natural networks and drive solid conclusions. The success in predicting the internal force flow in the natural structural pattern using graphic statics will expand the use of these powerful methods in reproducing the exact geometry of the natural structural system for use in many engineering and scientific problems. It will also ultimately help us understand the design parameters and boundary conditions for which nature produces its masterpieces.« less
  9. The increased computational capability in heterogeneous manycore architectures facilitates the concurrent execution of many applications. This requires, among other things, a flexible, high-performance, and energy-efficient communication fabric capable of handling a variety of traffic patterns needed for running multiple applications at the same time. Such stringent requirements are posing a major challenge for current Network-on-Chips (NoCs) design. In this paper, we propose Adapt-NoC, a flexible NoC architecture, along with a reinforcement learning (RL)-based control policy, that can provide efficient communication support for concurrent application execution. Adapt-NoC can dynamically allocate several disjoint regions of the NoC, called subNoCs, with different sizes and locations for the concurrently running applications. Each of the dynamically-allocated subNoCs is capable of adapting to a given topology such as a mesh, cmesh, torus, or tree thus tailoring the topology to satisfy application’s needs in terms of performance and power consumption. Moreover, we explore the use of RL to design an efficient control policy which optimizes the subNoC topology selection for a given application. As such, Adapt-NoC can not only provide several topology choices for concurrently running applications, but can also optimize the selection of the most suitable topology for a given application with the aim of improvingmore »performance and energy efficiency. We evaluate Adapt-NoC using both GPU and CPU benchmark suites. Simulation results show that the proposed Adapt-NoC can achieve up to 34% latency reduction, 10% overall execution time reduction and 53% NoC energy-efficiency improvement when compared to prior work.« less