Quantum computing and post-quantum cryptography

One of the main practical implications of quantum mechanical theory is quantum computing, and therefore the quantum computer. Quantum computing (for example, with Shor’s algorithm) challenges the computational hardness assumptions, such as the factoring problem and the discrete logarithm problem, that anchor the safety of cryptosystems. So the scientific community is studying how to defend cryptography; there are two defense strategies: the quantum cryptography (which involves the use of quantum cryptographic algorithms on quantum computers) and the post-quantum cryptography (based on classical cryptographic algorithms, but resistant to quantum computers). For example, National Institute of Standards and Technology (NIST) is collecting and standardizing the post-quantum ciphers, as it established DES and AES as symmetric cipher standards, in the past. In this thesis an introduction on quantum mechanics was given, in order to be able to talk about quantum computing and to analyze Shor’s algorithm. The differences between quantum and post-quantum cryptography were then analyzed. Subsequently the focus was given to the mathematical problems assumed to be resistant to quantum computers. To conclude, post-quantum digital signature cryptographic algorithms selected by NIST were studied and compared in order to apply them in today’s life.

Quantum error correction with the IBM quantum experience

Mentre si svolgono operazioni su dei qubit, possono avvenire vari errori, modificando così l’informazione da essi contenuta. La Quantum Error Correction costruisce algoritmi che permettono di tollerare questi errori e proteggere l’informazione che si sta elaborando. Questa tesi si focalizza sui codici a 3 qubit, che possono correggere un errore di tipo bit-flip o un errore di tipo phase-flip. Più precisamente, all’interno di questi algoritmi, l’attenzione è posta sulla procedura di encoding, che punta a proteggere meglio dagli errori l’informazione contenuta da un qubit, e la syndrome measurement, che specifica su quale qubit è avvenuto un errore senza alterare lo stato del sistema. Inoltre, sfruttando la procedura della syndrome measurement, è stata stimata la probabilità di errore di tipo bit-flip e phase-flip su un qubit attraverso l’utilizzo della IBM quantum experience.

Quantum phase estimation algorithms

Al contrario dei computer classici, i computer quantistici lavorano tramite le leggi della meccanica quantistica, e pertanto i qubit, ovvero l'unità base di informazione quantistica, possiedono proprietà estremamente interessanti di sovrapposizione ed entanglement. Queste proprietà squisitamente quantistiche sono alla base di innumerevoli algoritmi, i quali sono in molti casi più performanti delle loro controparti classiche. Obiettivo di questo lavoro di tesi è introdurre dal punto di vista teorico la logica computazionale quantistica e di riassumere brevemente una classe di tali algoritmi quantistici, ossia gli algoritmi di Quantum Phase Estimation, il cui scopo è stimare con precisione arbitraria gli autovalori di un dato operatore unitario. Questi algoritmi giocano un ruolo cruciale in vari ambiti della teoria dell'informazione quantistica e pertanto verranno presentati anche i risultati dell'implementazione degli algoritmi discussi sia su un simulatore che su un vero computer quantistico.

Variational Quantum Splines: Moving Beyond Linearity for Quantum Activation Functions

Activation functions within neural networks play a crucial role in Deep Learning since they allow to learn complex and non-trivial patterns in the data. However, the ability to approximate non-linear functions is a significant limitation when implementing neural networks in a quantum computer to solve typical machine learning tasks. The main burden lies in the unitarity constraint of quantum operators, which forbids non-linearity and poses a considerable obstacle to developing such non-linear functions in a quantum setting. Nevertheless, several attempts have been made to tackle the realization of the quantum activation function in the literature. Recently, the idea of the QSplines has been proposed to approximate a non-linear activation function by implementing the quantum version of the spline functions. Yet, QSplines suffers from various drawbacks. Firstly, the final function estimation requires a post-processing step; thus, the value of the activation function is not available directly as a quantum state. Secondly, QSplines need many error-corrected qubits and a very long quantum circuits to be executed. These constraints do not allow the adoption of the QSplines on near-term quantum devices and limit their generalization capabilities. This thesis aims to overcome these limitations by leveraging hybrid quantum-classical computation. In particular, a few different methods for Variational Quantum Splines are proposed and implemented, to pave the way for the development of complete quantum activation functions and unlock the full potential of quantum neural networks in the field of quantum machine learning.

Algoritmi quantistici e classi di complessità

Solitamente il concetto di difficoltà è piuttosto soggettivo, ma per un matematico questa parola ha un significato diverso: anche con l’aiuto dei più potenti computer può essere impossibile trovare la soluzione di un sudoku, risolvere l’enigma del commesso viaggiatore o scomporre un numero nei suoi fattori primi; in questo senso le classi di complessità computazionale quantificano il concetto di difficoltà secondo le leggi dell’informatica classica. Una macchina quantistica, però, non segue le leggi classiche e costituisce un nuovo punto di vista in una frontiera della ricerca legata alla risoluzione dei celebri problemi del millennio: gli algoritmi quantistici implementano le proprietà straordinarie e misteriose della teoria dei quanti che, quando applicate lucidamente, danno luogo a risultati sorprendenti.

Computational study on the asymmetric aminocatalysed Michael addition reaction of cyclohexanone to trans–β–nitrostyrene

Asymmetric organocatalysed reactions are one of the most fascinating synthetic strategies which one can adopt in order to induct a desired chirality into a reaction product. From all the possible practical applications of small organic molecules in catalytic reaction, amine–based catalysis has attracted a lot of attention during the past two decades. The high interest in asymmetric aminocatalytic pathways is to account to the huge variety of carbonyl compounds that can be functionalized by many different reactions of their corresponding chiral–enamine or –iminium ion as activated nucleophile and electrophile, respectively. Starting from the employment of L–Proline, many useful substrates have been proposed in order to further enhance the catalytic performances of these reaction in terms of enantiomeric excess values, yield, conversion of the substrate and turnover number. In particular, in the last decade the use of chiral and quasi–enantiomeric primary amine species has got a lot of attention in the field. Contemporaneously, many studies have been carried out in order to highlight the mechanism through which these kinds of substrates induct chirality into the desired products. In this scenario, computational chemistry has played a crucial role due to the possibility of simulating and studying any kind of reaction and the transition state structures involved. In the present work the transition state geometries of primary amine–catalysed Michael addition reaction of cyclohexanone to trans–β–nitrostyrene with different organic acid cocatalysts has been studied through different computational techniques such as density functional theory based quantum mechanics calculation and force–field directed molecular simulations.

Diagnosing criticality in symmetric and chiral clock models

Quantum clock models are statistical mechanical spin models which may be regarded as a sort of bridge between the one-dimensional quantum Ising model and the one-dimensional quantum XY model. This thesis aims to provide an exhaustive review of these models using both analytical and numerical techniques. We present some important duality transformations which allow us to recast clock models into different forms, involving for example parafermions and lattice gauge theories. Thus, the notion of topological order enters into the game opening new scenarios for possible applications, like topological quantum computing. The second part of this thesis is devoted to the numerical analysis of clock models. We explore their phase diagram under different setups, with and without chirality, starting with a transverse field and then adding a longitudinal field as well. The most important observables we take into account for diagnosing criticality are the energy gap, the magnetisation, the entanglement entropy and the correlation functions.