A 3.3-Gb/s SPAD-Based Quantum Random Number Generator

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Adaptive variational low-rank dynamics for open quantum systems

Vincenzo Savona, Luca Gravina

We introduce a model-independent method for the efficient simulation of low-entropy systems, whose dynamics can be accurately described with a limited number of states. Our method leverages the time-dependent variational principle to efficiently integrate ...

Amer Physical Soc2024

Lithium tantalate photonic integrated circuits for volume manufacturing

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Electro-optical photonic integrated circuits (PICs) based on lithium niobate (LiNbO3) have demonstrated the vast capabilities of materials with a high Pockels coefficient1,2. They enable linear and high-speed modulators operating at complementary metal–oxi ...

2024

Strain relaxation and multidentate anchoring in n-type perovskite transistors and logic circuits

Mohammad Khaja Nazeeruddin, Olga Syzgantseva

The engineering of tin halide perovskites has led to the development of p-type transistors with field-effect mobilities of over 70 cm2 V-1 s-1. However, due to their background hole doping, these perovskites are not suitable for n-type transistors. Ambipol ...

Nature Portfolio2024

Modelling and design of CMOS SPAD sensors for quantum random number generation

Pouyan Keshavarzian

Modern digital connectivity has necessitated the creation of robust methods for securely storing and transferring data. At the heart of all security infrastructure is the random number generator (RNG). While random numbers find use in a variety of applicat ...

EPFL2023

Evaluating, Exploiting, and Hiding Power Side-Channel Leakage of Remote FPGAs

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The pervasive adoption of field-programmable gate arrays (FPGAs) in both cyber-physical systems and the cloud has raised many security issues. Being integrated circuits, FPGAs are susceptible to fault and power side-channel attacks, which require physical ...

EPFL2023

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

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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 ...

EPFL2023

Unraveling the Electrochemical Electrode Coupling in Integrated Organic Electrochemical Transistors

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Organic electrochemical transistors (OECTs) have gained enormous attention due to their potential for bioelectronics and neuromorphic computing. However, their implementation into real-world applications is still impeded by a lack of understanding of the c ...

WILEY-V C H VERLAG GMBH2023

Pressure-freezing of dodecane: exploring the crystal structures, formation kinetics and phase diagrams for colossal barocaloric effects in n-alkanes

Tomasz Poreba

Barocaloric (BC) materials provide cheaper and more energy efficient alternatives to traditional refrigerants. Some liquid alkanes were recently shown to exhibit a colossal BC effect, matching the entropy changes in commercial vapour-liquid refrigerants. D ...

Royal Soc Chemistry2023

Green Cryptography and Other Optimisations

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The spectral decomposition of cryptography into its life-giving components yields an interlaced network of tangential and orthogonal disciplines that are nonetheless invariably grounded by the same denominator: their implementation on commodity computing p ...

EPFL2023

Exploring brain-inspired multi-core heterogeneous hardware templates for low-power biomedical embedded systems

Benoît Walter Denkinger

The miniaturization of integrated circuits (ICs) and their higher performance and energy efficiency, combined with new machine learning algorithms and applications, have paved the way to intelligent, interconnected edge devices. In the medical domain, they ...

EPFL2023

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Pressure-freezing of dodecane: exploring the crystal structures, formation kinetics and phase diagrams for colossal barocaloric effects in n-alkanes

Tomasz Poreba

Royal Soc Chemistry2023

Green Cryptography and Other Optimisations

Andrea Felice Caforio

EPFL2023

Exploring brain-inspired multi-core heterogeneous hardware templates for low-power biomedical embedded systems

Benoît Walter Denkinger

EPFL2023