We provide an extensive overview of a wide range of quantum games and interactive tools that have been employed by the quantum community in recent years. We present selected tools as described by their developers, including "Hello Quantum, Hello Qiskit, Particle in a Box, Psi and Delta, QPlayLearn, Virtual Lab by Quantum Flytrap, Quantum Odyssey, ScienceAtHome, and the Virtual Quantum Optics Laboratory."In addition, we present events for quantum game development: hackathons, game jams, and semester projects. Furthermore, we discuss the Quantum Technologies Education for Everyone (QUTE4E) pilot project, which illustrates an effective integration of these interactive tools with quantum outreach and education activities. Finally, we aim at providing guidelines for incorporating quantum games and interactive tools in pedagogic materials to make quantum technologies more accessible for a wider population. @en

Quantum computers process information stored in quantum bits (qubits), which must be controlled and read out by a traditional electronic interface. Co-designing and cooptimizing such a quantum-classical complex system requires efficient simulators to emulate the qubits and their interaction with classical electronics. For spin-qubit readout, a single electron transistor (SET) is often employed. To build a toolset that can co-simulate the spin qubit system with the classical control and readout interface, a compact and efficient SET model is needed. This paper presents a new compact empirical SET model based on state-of-the-art SET measurement and extracted by a custom function-fitting python program. Within the target source-drain voltage range of ±1000μV , the model is accurate for circuit (SPICE) simulation. Furthermore, the empirical model is represented by a set of equations that enables instantaneous output response requiring a negligible simulation time. With this new SET model, a quantum-electronics co-simulator such as SPINE can now be enhanced to simulate the readout in addition to the control circuits of spin qubits, thus enabling the design of the complete integrated circuit (IC) required for large-scale quantum computers.@en

Brownian circuits are based on a novel computing approach that exploits quantum fluctuations to increase the efficiency of information processing in nanoelectronic paradigms. This emerging architecture is based on Brownian cellular automata, where signals propagate randomly, driven by local transition rules, and can be made to be computationally universal. The design aims to efficiently and reliably perform primitive logic operations in the presence of noise and fluctuations; therefore, a Single Electron Transistor (SET) device is proposed to be the most appropriate technologybase to realize these circuits, as it supports the representation of signals that are token-based and subject to fluctuations due to the underlying tunneling mechanism of electric charge. In this paper, we study the physical limitations on the energy efficiency of the Single-Electron Transistor (SET)-based Brownian circuit elements proposed by Peper et al. using SIMON 2.0 simulations. We also present a novel two-bit sort circuit designed using Brownian circuit primitives, and illustrate how circuit parameters and temperature affect the fundamental energy-efficiency limitations of SET-based realizations. The fundamental lower bounds are obtained using a physical-information-theoretic approach under idealized conditions and are compared against SIMON 2.0 simulations. Our results illustrate the advantages of Brownian circuits and the physical limitations imposed on their SET-realizations.@en

In this paper, we provide a rigorous quantum mechanical derivation for the coherent photon transport characteristics of a two-level atom coupled to a waveguide without linearizing the coupling coefficient between the light and the atom. We propose a novel single frequency sampling method utilizing a UV-cutoff that allows us to treat the singularities in real space scattering potential despite the non-convergence property. We also study the conditions under which the linearization of the coupling coefficient is an accurate assumption and find the resulting spontaneous emission and transport characteristics taking the radiative and non-radiative decay rates into account. This allows us to confirm and expand on the findings of the existing literature while obtaining the dynamic electronic polarizability for the two-level atom confined to a 1D waveguide while using an interaction Hamiltonian with rotating-wave approximation.@en

Architecture-based heat dissipation analyses allow us to reveal fundamental sources of inefficiency in a given processor and thereby provide us with road-maps to design less dissipative computing schemes independent of technology-base used to implement them. In this work, we study architectural-level contributions to energy dissipation in an Artificial Neural Network (ANN)-based processor that is trained to perform edge-detection task. We compare the training and information processing cost of ANN to that of conventional architectures and algorithms using 64-pixel binary image. Our results reveal the inherent efficiency advantages of an ANN network trained for specific tasks over general-purpose processors based on von Neumann architecture. We also compare the proposed performance improvements to that of Cellular Array Processors (CAPs) and illustrate the reduction in dissipation for special purpose processors. Lastly, we calculate the change in dissipation as a result of input data structure and show the effect of randomness on energetic cost of information processing. The results we obtained provide a basis for comparison for task-based fundamental energy efficiency analyses for a range of processors and therefore contribute to the study of architecture-level descriptions of processors and thermodynamic cost calculations based on physics of computation. @en

The saturation in the efficiency and performance scaling of conventional electronic technolo-gies brings about the development of novel computational paradigms. Brownian circuits are among the promising alternatives that can exploit fluctuations to increase the efficiency of information processing in nanocomputing. A Brownian cellular automaton, where signals propagate randomly and are driven by local transition rules, can be made computationally universal by embedding arbitrary asynchronous circuits on it. One of the potential realizations of such circuits is via single electron tunneling (SET) devices since SET technology enable simulation of noise and fluctuations in a fashion similar to Brownian search. In this paper, we perform a physical-information-theoretic analysis on the efficiency limitations in a Brownian NAND and half-adder circuits implemented using SET technology. The method we employed here estab-lishes a solid ground that enables studying computational and physical features of this emerging technology on an equal footing, and yield fundamental lower bounds that provide valuable insights into how far its efficiency can be improved in principle. In order to provide a basis for comparison, we also analyze a NAND gate and half-adder circuit implemented in complementary metal oxide semiconductor technology to show how the fundamental bound of the Brownian circuit compares against a conventional paradigm.@en