7,985 research outputs found
Towards a more just refuge regime: quotas, markets and a fair share
The international refugee regime is beset by two problems: Responsibility for refuge falls
disproportionately on a few states and many owed refuge do not get it. In this work, I explore
remedies to these problems. One is a quota distribution wherein states are distributed
responsibilities via allotment. Another is a marketized quota system wherein states are free to buy
and sell their allotments with others. I explore these in three parts. In Part 1, I develop the prime
principles upon which a just regime is built and with which alternatives can be adjudicated. The
first and most important principle – ‘Justice for Refugees’ – stipulates that a just regime provides
refuge for all who have a basic interest in it. The second principle – ‘Justice for States’ – stipulates
that a just distribution of refuge responsibilities among states is one that is capacity considerate. In
Part 2, I take up several vexing questions regarding the distribution of refuge responsibilities
among states in a collective effort. First, what is a state’s ‘fair share’? The answer requires the
determination of some logic – some metric – with which a distribution is determined. I argue that
one popular method in the political theory literature – a GDP-based distribution – is normatively
unsatisfactory. In its place, I posit several alternative metrics that are more attuned with the
principles of justice but absent in the political theory literature: GDP adjusted for Purchasing
Power Parity and the Human Development Index. I offer an exploration of both these. Second,
are states required to ‘take up the slack’ left by defaulting peers? Here, I argue that duties of help
remain intact in cases of partial compliance among states in the refuge regime, but that political
concerns may require that such duties be applied with caution. I submit that a market instrument
offers one practical solution to this problem, as well as other advantages. In Part 3, I take aim at
marketization and grapple with its many pitfalls: That marketization is commodifying, that it is
corrupting, and that it offers little advantage in providing quality protection for refugees. In
addition to these, I apply a framework of moral markets developed by Debra Satz. I argue that a
refuge market may satisfy Justice Among States, but that it is violative of the refugees’ welfare
interest in remaining free of degrading and discriminatory treatment
Full stack development toward a trapped ion logical qubit
Quantum error correction is a key step toward the construction of a large-scale quantum computer, by preventing small infidelities in quantum gates from accumulating over the course of an algorithm. Detecting and correcting errors is achieved by using multiple physical qubits to form a smaller number of robust logical
qubits. The physical implementation of a logical qubit requires multiple qubits, on which high fidelity gates
can be performed.
The project aims to realize a logical qubit based on ions confined on a microfabricated surface trap. Each
physical qubit will be a microwave dressed state qubit based on 171Yb+ ions. Gates are intended to be realized through RF and microwave radiation in combination with magnetic field gradients. The project vertically integrates software down to hardware compilation layers in order to deliver, in the near future, a fully functional small device demonstrator.
This thesis presents novel results on multiple layers of a full stack quantum computer model. On the hardware level a robust quantum gate is studied and ion displacement over the X-junction geometry is demonstrated.
The experimental organization is optimized through automation and compressed waveform data transmission. A new quantum assembly language purely dedicated to trapped ion quantum computers is introduced. The demonstrator is aimed at testing implementation of quantum error correction codes while preparing for larger
scale iterations.Open Acces
Combinatorics and Stochasticity for Chemical Reaction Networks
Stochastic chemical reaction networks (SCRNs) are a mathematical model which serves as a first approximation to ensembles of interacting molecules. SCRNs approximate such mixtures as always being well-mixed and consisting of a finite number of molecules, and describe their probabilistic evolution according to the law of mass-action. In this thesis, we attempt to develop a mathematical formalism based on formal power series for defining and analyzing SCRNs that was inspired by two different questions. The first question relates to the equilibrium states of systems of polymerization. Formal power series methods in this case allow us to tame the combinatorial complexity of polymer configurations as well as the infinite state space of possible mixture states. Chapter 1 presents an application of these methods to a model of polymerizing scaffolds. The second question relates to the expressive power of SCRNs as generators of stochasticity. In Chapter 2, we show that SCRNs are universal approximators of discrete distributions, even when only allowing for systems with detailed-balance. We further show that SCRNs can exactly simulate Boltzmann machines. In Chapter 3, we develop a formalism for defining the semantics of SCRNs in terms of formal power series which grew as a result of work included in the previous chapters. We use that formulation to derive expressions for the dynamics and stationary states of SCRNs. Finally, we focus on systems that satisfy complex balance and conservation of mass and derive a general expressions for their factorial moments using generating function methods
Hunting Wildlife in the Tropics and Subtropics
The hunting of wild animals for their meat has been a crucial activity in the evolution of humans. It continues to be an essential source of food and a generator of income for millions of Indigenous and rural communities worldwide. Conservationists rightly fear that excessive hunting of many animal species will cause their demise, as has already happened throughout the Anthropocene. Many species of large mammals and birds have been decimated or annihilated due to overhunting by humans. If such pressures continue, many other species will meet the same fate. Equally, if the use of wildlife resources is to continue by those who depend on it, sustainable practices must be implemented. These communities need to remain or become custodians of the wildlife resources within their lands, for their own well-being as well as for biodiversity in general. This title is also available via Open Access on Cambridge Core
Secure authentication and key agreement via abstract multi-agent interaction
Authentication and key agreement are the foundation for secure communication over the Internet. Authenticated Key Exchange (AKE) protocols provide methods for communicating parties to authenticate each other, and establish a shared session key by which they can encrypt messages in the session. Within the category of AKE protocols, symmetric AKE protocols rely on pre-shared master keys for both services. These master keys can be transformed after each session in a key-evolving scheme to provide the property of forward secrecy, whereby the compromise of master keys does not allow for the compromise of past session keys.
This thesis contributes a symmetric AKE protocol named AMI (Authentication via Multi-Agent Interaction). The AMI protocol is a novel formulation of authentication and key agreement as a multi-agent system, where communicating parties are treated as autonomous agents whose behavior within the protocol is governed by private agent models used as the master keys. Parties interact repeatedly using their behavioral models for authentication and for agreeing upon a unique session key per communication session. These models are evolved after each session to provide forward secrecy. The security of the multi-agent interaction process rests upon the difficulty of modeling an agent's decisions from limited observations about its behavior, a long-standing problem in AI research known as opponent modeling. We conjecture that it is difficult to efficiently solve even by a quantum computer, since the problem is fundamentally one of missing information rather than computational hardness.
We show empirically that the AMI protocol achieves high accuracy in correctly identifying legitimate agents while rejecting different adversarial strategies from the security literature. We demonstrate the protocol's resistance to adversarial agents which utilize random, replay, and maximum-likelihood estimation (MLE) strategies to bypass the authentication test. The random strategy chooses actions randomly without attempting to mimic a legitimate agent. The replay strategy replays actions previously observed by a legitimate client. The MLE strategy estimates a legitimate agent model using previously observed interactions, as an attempt to solve the opponent modeling problem.
This thesis also introduces a reinforcement learning approach for efficient multi-agent interaction and authentication. This method trains an authenticating server agent's decision model to take effective probing actions which decrease the number of interactions in a single session required to successfully reject adversarial agents. We empirically evaluate the number of interactions required for a trained server agent to reject an adversarial agent, and show that using the optimized server leads to a much more sample-efficient interaction process than a server agent selecting actions by a uniform-random behavioral policy.
Towards further research on and adoption of the AMI protocol for authenticated key-exchange, this thesis also contributes an open-source application written in Python, PyAMI. PyAMI consists of a multi-agent system where agents run on separate virtual machines, and communicate over low-level network sockets using TCP. The application supports extending the basic client-server setting to a larger multi-agent system for group authentication and key agreement, providing two such architectures for different deployment scenarios
International Conference on Mathematical Analysis and Applications in Science and Engineering – Book of Extended Abstracts
The present volume on Mathematical Analysis and Applications in Science and Engineering - Book of
Extended Abstracts of the ICMASC’2022 collects the extended abstracts of the talks presented at the
International Conference on Mathematical Analysis and Applications in Science and Engineering –
ICMA2SC'22 that took place at the beautiful city of Porto, Portugal, in June 27th-June 29th 2022 (3 days).
Its aim was to bring together researchers in every discipline of applied mathematics, science, engineering,
industry, and technology, to discuss the development of new mathematical models, theories, and
applications that contribute to the advancement of scientific knowledge and practice. Authors proposed
research in topics including partial and ordinary differential equations, integer and fractional order
equations, linear algebra, numerical analysis, operations research, discrete mathematics, optimization,
control, probability, computational mathematics, amongst others.
The conference was designed to maximize the involvement of all participants and will present the state-of-
the-art research and the latest achievements.info:eu-repo/semantics/publishedVersio
- …