Analogue computing with metamaterials

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Designing novel materials is greatly dependent on understanding the design principles, physical mechanisms, and modeling methods of material microstructures, requiring experienced designers with expertise and several rounds of trial and error. Although rec ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

This paper presents a solution to overcome the inherently limited bandwidth of substrate-integrated waveguide (SIW) slot antennas. It is analytically shown that by decreasing the permittivity of a dielectric loaded slot antenna, the resulting bandwidth inc ...

Since the advent of internet and mass communication, two public-key cryptographic algorithms have shared the monopoly of data encryption and authentication: Diffie-Hellman and RSA. However, in the last few years, progress made in quantum physics -- and mo ...

This paper presents the new 2D electrostatic particle -in -cell code FENNECS developed to study the formation of magnetized non -neutral plasmas in geometries with azimuthal symmetry. This code has been developed in the domain of gyrotron electron gun desi ...

We introduce a Lamb-wave medium with tunable propagation velocities, which are controlled by a two-dimensional heating pattern produced by a laser beam. We utilized it to demonstrate that waves in an appropriately designed medium can propagate in the form ...

Mitigating the energy requirements of artificial intelligence requires novel physical substrates for computation. Phononic metamaterials have vanishingly low power dissipation and hence are a prime candidate for green, always-on computers. However, their u ...

Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

In this thesis work, we propose to exploit an innovative micro/nano-fabrication process, based on controlled fluid instabilities of a thin viscous film of chalcogenide glass. Amorphous selenium and arsenic triselenide were used in this thesis work, and com ...

The invention relates to an Imaging sensor device in a stacked arrangement comprising: - a pixel array tier comprising a plurality of pixel segments each having a plurality of pixels for photon detection each providing a digital pixel output; - a processin ...

Billions of people now have conversations daily over the Internet. A large portion of this communication takes place via secure messaging protocols that offer "end-to-end encryption'" guarantees and resilience to compromise like the widely-used Double Ratc ...

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

Quantum computing not only holds the potential to solve long-standing problems in quantum physics, but also to offer speed-ups across a broad spectrum of other fields. Access to a computational space that incorporates quantum effects, such as superposition ...

Multiple tensor-times-matrix (Multi-TTM) is a key computation in algorithms for computing and operating with the Tucker tensor decomposition, which is frequently used in multidimensional data analysis. We establish communication lower bounds that determine ...

In a recent discovery (Wen et al 2022 Phys. Rev. Lett. 129 045001), streaming waves were found in multipactor-induced plasma discharges. However, due to the limitations of a 1D simulation setup, these waves displayed only transverse dynamics. In this lette ...

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

Recent successes in deep learning for vision and natural language processing are attributed to larger models but come with energy consumption and scalability issues. Current training of digital deep-learning models primarily relies on backpropagation that ...

Multi-Scale computing systems aim at bringing the computing as close as possible to the data sources, to optimize both computation and networking. These systems are composed of at least three computing layers: the terminal layer, the edge layer, and the cl ...

Controlling audible sound requires inherently broadband and subwavelength acoustic solutions, which are to date, crucially missing. This includes current noise absorption methods, such as porous materials or acoustic resonators, which are typically ineffic ...

Analogue computing with metamaterials

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Text-to-Microstructure Generation Using Generative Deep Learning

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Enabling Wide Bandwidth in Substrate-Integrated Waveguide Slot Antennas by Using Low-Index Metamaterials

Secure and Efficient Cryptographic Algorithms in a Quantum World

FENNECS: a novel particle-in-cell code for simulating the formation of magnetized non-neutral plasmas trapped by electrodes of complex geometries

Optothermal shaping of lamb waves with square and spiral phase fronts

In-Sensor Passive Speech Classification with Phononic Metamaterials

Secure Interface Design Leveraging Hardware/Software Support

All-Dielectric Nanophotonic via Glass Fluid Instabilities

Imaging sensor device using an array of single-photon avalanche diode photodetectors

On the Theory and Practice of Modern Secure Messaging

EdgeAI-Aware Design of In-Memory Computing Architectures

Scalable Quantum Algorithms for Noisy Quantum Computers

COMMUNICATION LOWER BOUNDS AND OPTIMAL ALGORITHMS FOR MULTIPLE TENSOR-TIMES-MATRIX COMPUTATION

Oblique streaming waves observed in multipactor-induced plasma discharge above a dielectric surface

Predicting the long-term collective behaviour of fish pairs with deep learning

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

Backpropagation-free training of deep physical neural networks

Special Session: Challenges and Opportunities for Sustainable Multi-Scale Computing Systems

Ultrabroadband sound control with deep-subwavelength plasmacoustic metalayers