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The power of quantum random number generation is more than just the ability to create truly random numbers$\unicode{x2013}$it can also enable self-testing, which allows the user to verify the implementation integrity of certain critical…

Neuromorphic Computing promises orders of magnitude improvement in energy efficiency compared to traditional von Neumann computing paradigm. The goal is to develop an adaptive, fault-tolerant, low-footprint, fast, low-energy intelligent…

Neural and Evolutionary Computing · Computer Science 2024-03-19 Md Sakib Hasan , Catherine D. Schuman , Zhongyang Zhang , Tauhidur Rahman , Garrett S. Rose

Machine learning has recently developed novel approaches, mimicking the synapses of the human brain to achieve similarly efficient learning strategies. Such an approach retains the universality of standard methods, while attempting to…

We present a semi-device-independent quantum random number generator (QRNG) based on the violation of a contextuality inequality, implemented by the integration of two silicon photonic chips. Our system combines a heralded single-photon…

Random number generation is a key technology that is useful in a variety of ways. Random numbers are often used to generate keys for data encryption. Random numbers generated at a sufficiently long length can encrypt sensitive data and make…

Hardware Architecture · Computer Science 2022-09-12 Jacob Hammond

Photonic methods of radio-frequency waveform generation and processing provide performance and flexibility over electronic methods due to the ultrawide bandwidth offered by the optical carriers. However, they suffer from lack of integration…

There exists a significant scale gap between photonic neural network integrated chips and neural networks, which hinders the deployment and application of photonic neural network. Here, we propose hardware-aware lightweight spiking neural…

Photonic technologies offer great prospects for novel ultrafast, energy-efficient and hardware-friendly neuromorphic (brain-like) computing platforms. Moreover, neuromorphic photonic approaches based upon ubiquitous, technology-mature and…

Emerging Technologies · Computer Science 2022-11-23 Dafydd Owen-Newns , Joshua Robertson , Matej Hejda , Antonio Hurtado

A design framework to implement non-unitary input-output operations to a practical unitary photonic integrated circuit is described. This is achieved by utilising the cosine-sine decomposition to recover the unitarity of the original…

Optics · Physics 2025-01-15 Hussein Talib , Phillip D. Sewell , Ana Vukovic , Sendy Phang

We shall review the cellular automaton(CA)-based pseudorandom-number generators (PRNGs), and show that one of these PRNGs can generate high-quality random numbers which can pass all of the statistical tests provided by the National…

Chaotic Dynamics · Physics 2007-05-23 Song-Ju Kim , Ken Umeno

We present a fast learning-based algorithm for deformable, pairwise 3D medical image registration. Current registration methods optimize an objective function independently for each pair of images, which can be time-consuming for large…

Computer Vision and Pattern Recognition · Computer Science 2019-03-14 Guha Balakrishnan , Amy Zhao , Mert R. Sabuncu , John Guttag , Adrian V. Dalca

Quantum technologies, such as quantum communication, sensing and imaging, need a platform which is flexible, miniaturizable and works at room temperature. Integrated photonics is a promising and fast-developing platform. This requires to…

Quantum Physics · Physics 2021-10-12 Andrei-Emanuel Dragomir , Cristian George Ivan , Radu Ionicioiu

Quantum systems combining indistinguishable photon generation and spin-based quantum information processing are essential for remote quantum applications and networking. However, identification of suitable systems in scalable platforms…

With recent rapid advances in photonic integrated circuits, it has been demonstrated that programmable photonic chips can be used to implement artificial neural networks. Convolutional neural networks (CNN) are a class of deep learning…

Signal Processing · Electrical Eng. & Systems 2020-03-30 Jun Rong Ong , Chin Chun Ooi , Thomas Y. L. Ang , Soon Thor Lim , Ching Eng Png

The value of brain-inspired neuromorphic computers critically depends on our ability to program them for relevant tasks. Currently, neuromorphic hardware often relies on machine learning methods adapted from deep learning. However,…

Neural and Evolutionary Computing · Computer Science 2024-10-31 Steven Abreu , Jens E. Pedersen

Superconductor electronics (SCE) appear promising for low energy applications. However, the achieved and projected circuit densities are insufficient for direct competition with CMOS technology. Original algorithms and nontraditional…

Superconductivity · Physics 2024-12-24 Evan B. Golden , Vasili K. Semenov , Sergey K. Tolpygo

Physically Unclonable Functions (PUFs) are lightweight cryptographic primitives for generating unique signatures from minuscule manufacturing variations. In this work, we present lightweight, area efficient and low power adaptive multi-bit…

Hardware Architecture · Computer Science 2019-12-17 Sudarshan Sharma , Dhruv Thapar , Nikhil Bhelave , Mrigank Sharad

The concept of Secret Unknown Ciphers (SUCs) was introduced a decade ago as a new visionary concept without devising practical real-world examples. The major contribution of this work is to show the feasibility of "self-mutating" unknown…

Cryptography and Security · Computer Science 2019-08-13 Ayoub Mars , Wael Adi

The third-order non-linearity of silicon gives rise to a spontaneous four-wave mixing process in which correlated photon pairs are generated. Sources based on this effect can be used for quantum computation and cryptography, and can in…

Optics · Physics 2016-04-20 Momchil Minkov , Vincenzo Savona

This project develops a pseudo-random number generator (PRNG) using the logistic map, implemented in Verilog HDL on an FPGA and processes its output through a Central Limit Theorem (CLT) function to achieve a Gaussian distribution. The…