Difficulty Scaling in Proof of Work for Decentralized Problem Solving

We propose DIPS Difficulty-based Incentives for Problem Solving), a simple modification of the Bitcoin proof-of-work algorithm that rewards blockchain miners for solving optimization problems of scientific interest. The result is a blockchain which redirects some of the computational resources invested in hash-based mining towards scientific computation, effectively reducing the amount of energy `wasted' on mining. DIPS builds the solving incentive directly in the proof-of-work by providing a reduction in block hashing difficulty when optimization improvements are found. A key advantage of this scheme is that decentralization is preserved and no additional protocol layers are required on top of the standard blockchain. We study two incentivization schemes and provide simulation results showing that DIPS is able to reduce the amount of hash-power used in the network while generating solutions to optimization problems

VeRNAl: Mining RNA Structures for Fuzzy Base Pairing Network Motifs

RNA 3D motifs are recurrent substructures, modelled as networks of base pair interactions, which are crucial for understanding structure-function relationships. The task of automatically identifying such motifs is computationally hard, and remains a key challenge in the field of RNA structural biology and network analysis. State of the art methods solve special cases of the motif problem by constraining the structural variability in occurrences of a motif, and narrowing the substructure search space. Here, we relax these constraints by posing the motif finding problem as a graph representation learning and clustering task. This framing takes advantage of the continuous nature of graph representations to model the flexibility and variability of RNA motifs in an efficient manner. We propose a set of node similarity functions, clustering methods, and motif construction algorithms to recover flexible RNA motifs. Our tool, VeRNAl can be easily customized by users to desired levels of motif flexibility, abundance and size. We show that VeRNAl is able to retrieve and expand known classes of motifs, as well as to propose novel motifs

First-principles hyperfine tensors for GaAs and Si

An accurate description of the hyperfine interaction between electron spins and nuclear spins is crucial for understanding spin dynamics in semiconductor nanostructures. In this thesis, we study the hyperfine interactions in III-V semiconductors and Si. We use the Elk code to perform a density-functional-theory calculation of the contact hyperfine parameter for Si and the Ga and As sites in GaAs. Our result differs from the experimental values found with NMR by less than 3%, while the previous theoretical result differs from the same experimental values by more than 10%. To the best of our knowledge, the calculations in this thesis give the first theoretical estimate of the contact hyperfine coupling in GaAs derived from first principles. Additionally, we show how to go beyond usual methods to accurately determine hyperfine tensors in strongly spin-orbit coupled materials. We achieve this by combining density-functional theory and group theory, accounting for the full coupled spin-orbit structure of the associated single-particle states. Finally, we show how to verify the predicted electronic structure experimentally spectroscopically, by determining a set of allowed electric-dipole transitions.Une description précise de l'interaction hyperfine entre les spins électroniques et les spins nucléaires est nécessaire pour comprendre l'évolution des spins dans les nanostructures construites à partir de semiconducteur. Dans cette thèse, nous étudions l'interaction hyperfine dans les semiconducteurs III-V et Si. On utilise le code Elk pour faire un calcul de la théorie densité fonctionelle du paramètre hyperfin de contact pour le Si et pour le Ga et le As quiconstituent le GaAs. Nos résultats sont en accord avec des résultats expértimentaux obtenus par la RNM et sont plus proches de ces résultats que d'autres résultats théoriques. Au meilleur de nos connaissances, nos calculs pour le GaAs produisent les premiers résultats des paramètres hyperfins dans ce matériel. De plus, nous démontrons comment aller au-delà des méthodes de densité fonctionelle habituelles pour calculer les éléments du tensor hyperfin pour les matériaux qui ont un couplage spin-orbit fort. Notre méthode combine la théorie de densité fonctionelle avec la théorie de groupe en considérant la structure complète des états mono-particules. Finalement, nous démontrons comment vérifier la structure électronique prédite par des expériences spectroscopiques, en calculant les transitions dipolaires électriques permises

Recent advances in hole-spin qubits

In recent years, hole-spin qubits based on semiconductor quantum dots have advanced at a rapid pace. We first review the main potential advantages of these hole-spin qubits with respect to their electron-spin counterparts and give a general theoretical framework describing them. The basic features of spin–orbit coupling and hyperfine interaction in the valence band are discussed, together with consequences on coherence and spin manipulation. In the second part of the article, we provide a survey of experimental realizations, which spans a relatively broad spectrum of devices based on GaAs, Si and Si/Ge heterostructures. We conclude with a brief outlook

Simulation process flow for the implementation of industry-standard FD-SOI quantum dot devices

International audienceThe spin of an electron confined to a semiconductor quantum dot is one of the main technology platforms currently evaluated in the pursuit of qubit implementation. In this study, we developed and optimized a full simulation process flow used to model an Ultra-Thin Body and Buried oxide (UTBB) Fully Depleted Silicon-On-Insulator (FD-SOI) quantum dot device fabricated using STMicroelectronics&#39; standard manufacturing process. Here, we report optical, geometrical, electrical, and quantum numerical results that allowed us to assess the device performance before its eventual fabrication.</p

Interpretation of 28 nm FD-SOI quantum dot transport data taken at 1.4 K using 3D quantum TCAD simulations

International audienceReliable operation of nanoscale CMOS quantum dot devices at cryogenic temperatures fabricated with standard manufacturing techniques is of great importance for quantum computing applications. We investigated the very low temperature behavior of an Ultra Thin Body and Buried oxide (UTBB) Fully Depleted Silicon-On-Insulator (FD-SOI) quantum dot device fabricated using the standard fabrication process of STMicroelectronics. The performance of the quantum dot device is simulated and analyzed using the 3D Quantum Technology Computer Aided Design (QTCAD) software recently developed by Nanoacademic Technologies, achieving convergence down to 1.4&nbsp;K. In this paper we present preliminary simulation results and compare them with experimental data collected from the measurements on a device with the same geometry.</p

Interpretation of 28 nm FD-SOI quantum dot transport data taken at 1.4 K using 3D Quantum TCAD simulations

International audienceReliable operation of nanoscale CMOS quantum dot devices at cryogenic temperatures fabricated with standard manufacturing techniques is of great importance for quantum computing applications. We investigated the behavior of an Ultra Thin Body and Buried oxide (UTBB) Fully Depleted Silicon-On-Insulator (FD-SOI) quantum dot device fabricated using the standard fabrication process of STMicroelectronics at&nbsp; very low temperatures. The performance of the quantum dot device is simulated and analyzed using the 3D Quantum Technology Computer Aided Design (QTCAD) software recently developed by Nanoacademic Technologies, achieving convergence down to 1.4 K. In this paper we present preliminary simulation results of this work and compare them with actual experimental data collected from measurements of the same&nbsp; device.</p