Quantum information theory and the second quantum revolution have brought us within grasping distance of quantum computers, the building block of which is the qubit. Like their classical counter parts---the bit---they are two-dimensional, reaching their power when embedded in an network of many interacting qubits. However, many quantum systems are not two-dimensional in nature, but high dimensional. In this thesis, I explore---both experimentally and theoretically---several applications of encoding and processing information in high dimensional quantum systems. I consider information encoded in the spatial, temporal, and phase space distributions of optical systems. I further analyse the evolution of these systems using the theory of closed and open quantum systems, conditional dynamics and Fock state master equations. These results highlight the unique advantages of high dimensional quantum systems in the sub-disciplines quantum foundations, quantum simulation and quantum sensing. Our results clearly demonstrate that high dimensional quantum information presents many unique applications that could be fostered into new technology.
Quantum information theory and the second quantum revolution have brought us within grasping distance of quantum computers, the building block of which is the qubit. Like their classical counter parts---the bit---they are two-dimensional, reaching their power when embedded in an network of many interacting qubits. However, many quantum systems are not two-dimensional in nature, but high dimensional. In this thesis, I explore---both experimentally and theoretically---several applications of encoding and processing information in high dimensional quantum systems. I consider information encoded in the spatial, temporal, and phase space distributions of optical systems. I further analyse the evolution of these systems using the theory of closed and open quantum systems, conditional dynamics and Fock state master equations. These results highlight the unique advantages of high dimensional quantum systems in the sub-disciplines quantum foundations, quantum simulation and quantum sensing. Our results clearly demonstrate that high dimensional quantum information presents many unique applications that could be fostered into new technology.
Over the last few decades, quantum cryptography has been one of the most important quantum technologies developed. It holds the promise of communicating secure information over untrusted channels. In particular, quantum cryptography is immune to the eventual threats posed by large-scale quantum computers, which is not the case for our current classical cryptography infrastructures. In a world where information, communication and privacy are of paramount importance, the development of secure quantum communication infrastructures becomes imperative. So far, most of the quantum cryptographic systems developed to date are based on two-dimensional encoding schemes, analogous to classical bits, known as qubits. Nevertheless, other than for the polarization of light, photonic degrees of freedom, i.e. position, momentum, time and frequency, naturally occur as high-dimensional quantum systems. Moreover, by considering high-dimensional encoding schemes beyond qubits, advantages in terms of information capacity and noise tolerance are predicted in theory. In this thesis, the basic components of a high-dimensional quantum cryptographic system are investigated. We begin by reviewing important developments in quantum cryptography and high-dimensional quantum information. As a starting point, two different quantum information tasks, i.e. optimal quantum cloning and quantum metrology, are experimentally investigated for high-dimensional quantum systems in order to demonstrate the numerous advantages of performing quantum tasks beyond qubits. The photonic degree of freedom used in these experiments, known as transverse spatial modes, is obtained by combining the position and momentum photonics degrees of freedom. Thus, we develop a novel method to measure high-dimensional quantum states encoded in arbitrary spatial modes. Using a similar characterization technique, several high-dimensional quantum communication channels are characterized to perform high-dimensional quantum cryptography. The tools developed in the laboratory are then brought to realistic conditions in order to test the feasibility of high-dimensional quantum cryptography. Two different types of quantum channels are experimentally investigated, namely an intra-city 300 m long free-space link and a short 3 m outdoor underwater link. Finally, we investigate and compare novel high-dimensional protocols to overcome current limitations.
In this thesis, Quantum Key Distribution and quantum communication methods based on high-dimensional spatial coding of light are developed. Their security is based on the fundamental quantum nature of light and profits from the highdimensional Hilbert spaces offered intrinsically by imaging optics. An overview of classical information theory and quantum information is given to introduce the field of quantum cryptography. The advantages of larger dimensional alphabets and the security of the standard two-bases BB84 protocol is shown. The spatial states used for encoding are introduced. An analytic expression for the upper bound on the mutual information for these states is derived, including multiphoton states, detector noise and beam broadening. High-dimensional encoding of single photons is experimentally realized, reaching 10.5 bit per received photon. The dependence of the mutual information on the number of detector pixels is discussed and the experimental values are compared with the theoretical upper bound. It was shown that a standard error-correcting LDPC code is sufficient to achieve practically error-free communication. By adding a second mutually unbiased basis, a large-alphabet QKD system is experimentally realized and characterized. The security of this BB84-like protocol is analyzed in terms of intercept-resend and collective attacks. The key rate after postprocessing is analyzed under realistic circumstances, including finite key length. Finally, a new quantum communication method is demonstrated, which is based on encoding information into wavefronts decomposed over guided modes of a multimode fiber. At the end a step back is made and the similarities and differences of several quantum authentication and quantum cryptography schemes as well as Quantum Data Locking are discussed. This involves comparison of the characteristics of the classical channel, the quantum channel and the necessary dimension of the Hilbert space.
Quantum information processing (QIP) studies the representation, manipulation, and transmission of information using quantum systems. By leveraging counterintuitive quantum phenomena such as superposition and entanglement, QIP enables new paradigms for computation, communication, and learning that can surpass classical limits in certain regimes. Foundational tasks in QIP include quantum data compression, quantum communication, and quantum learning and optimization, which together form the basis for scalable quantum technologies. This thesis develops new frameworks and algorithms at the intersection of quantum information theory, quantum learning, and quantum-inspired modeling. The thesis is organized into three parts. The first part studies quantum compression problems; the second addresses quantum communication; and the third develops quantum learning and optimization frameworks with applications to complex systems. In the first part, a new formulation for lossy quantum-classical source coding, termed rate-channel theory, is introduced, replacing the conventional distortion-based formulation with a posterior-channel-based framework under a block-error criterion. The framework is further generalized to incorporate quantum side information at the decoder. A connection between rate-channel theory and classical rate-distortion theory is also established, showing that optimal rate-distortion performance can be recovered under suitable conditions. These results provide a unified and flexible framework for data compression, which is essential for scalable quantum computing infrastructure, enabling efficient storage of quantum data, such as outputs from quantum sensors (e.g., MRI) and information encoded in photonic systems for satellite and optical communication. In the second part, the problem of computing functions of distributed sources over classical-quantum multiple access channels is studied. A new coding framework is developed that combines algebraic structured codes with unstructured random coding techniques, enabling efficient communication of functions without reconstructing individual sources. The resulting achievable conditions, expressed in terms of single-letter quantum information quantities, strictly enlarge the class of sources for which reliable computation is possible. These results contribute to the theoretical foundations of quantum network communication and are directly relevant to deep-space satellite-based quantum communication, distributed quantum computing, and the design of scalable quantum network infrastructures. In the final part, new approaches to quantum learning and optimization are developed. A geometry-aware quantum optimization framework is proposed based on a novel quantum information metric and an unbiased estimator constructed from single-shot measurements. This leads to an optimization method with constant sample complexity per iteration and provable exponential convergence under mild conditions, while avoiding saddle points and local minima. Such advances are particularly relevant for challenging optimization tasks in quantum sensing and quantum computational modeling of many-body systems. Building on this optimization framework, a Hamiltonian learning approach is introduced to infer interaction structures from time-resolved measurement data, with finite-sample guarantees and polynomial scaling with system size. This framework is further extended to develop a quantum-inspired generative model for gene regulatory network inference, where interactions are encoded as a parameterized Hamiltonian evolving over pseudotime. The proposed methods demonstrate strong performance on synthetic benchmarks and reveal biologically meaningful structures in real-world data, with applications to multi-omics integration, cancer genomics, and systems biology. Overall, this thesis advances the theoretical and algorithmic foundations of quantum information processing, with contributions spanning compression, communication, and learning. These developments support the design of resource-efficient and scalable quantum technologies, enabling applications in quantum sensing, quantum networks, distributed quantum computation, and the modeling of complex physical and biological systems.
All the data stored and processed by our computers is encoded as sequences of zeros and ones, called bits. Quantum computers offer an alternative to this traditional way of encoding and manipulating information. The information in a collection of qubits can be a combination, also called a superposition, over many possible sequences of zeros and ones. Where classical computation consists of flipping zeros and ones, quantum computation consists of manipulating high-dimensional vectors called quantum states. Researchers have found ways to use this to engineer quantum algorithms that solve some tasks much faster than any classical computer would. These are called quantum advantages, and are proven for specific tasks, such as breaking some encryption schemes and solving certain large linear systems. The goal of this thesis was to find new tasks for which quantum computers provably have an advantage over classical computers. In this thesis, I present two such advantages and associated results. The first one revolves around a physically relevant learning task. In other words, I explore how quantum computers can be used to help solve specialized machine learning tasks. The second one addresses the simulation of classical systems. One of the first high-potential and natural uses of quantum computers was the simulation of quantum systems. A lot of real-world problems, however, are ruled by classical physics. It turns out that quantum computers are well suited for the simulation of some exponentially large classical systems. In this thesis, I add a new problem to this list.
Photons can carry quantum information not only in two-level systems (qubits) but also in d-level systems known as qudits. A single photon distributed across d optical modes can encode up to log2(d) qubits of information, allowing for more efficient use of quantum resources and increased resilience to noise. This advantage, however, comes at a price: implementing quantum gates and performing measurements in high-dimensional Hilbert spaces is significantly more demanding than in the qubit case. To tackle these challenges, I will present our recent work developing new protocols and optical hardware that enable quantum communication and computation with high-dimensional qudits encoded in the temporal or spatial modes of single and entangled photons. I will discuss our experimental implementations of quantum key distribution using weak coherent pulses [Sulimany et al., NPJ Quantum Information 11, 16 (2025)], single photons from quantum dots [Halevi et al., Optica Quantum 2, 351 (2024)], and entangled photon pairs [Lib et al., Optica Quantum 3, 182 (2025)]. In the latter, we demonstrated projective measurements in two mutually unbiased bases for d=25 using a multi-plane light converter (MPLC). I will also show how the same MPLC platform can be used to perform elementary operations in measurement-based quantum computation with high-dimensional cluster states [Lib and Bromberg, Nat. Photonics 18, 1218 (2024)]. Throughout the talk, I will discuss the tradeoffs between qubit- and qudit-based approaches and highlight the regimes where high-dimensional systems offer a practical advantage.
In the first part of this thesis we extensively review the general theory of open quantum systems. We introduce new approaches to describe, in a hopefully more transparent way, some aspects which are usually misleading in a broad range of the literature. In addition, we revise new concepts and methods developed in recent years that complement the general theory mainly developed in the 1970s. In the second part, we focus our attention on the so-called Markovian processes which have been described in the previous part. We study the validity of typical equations used in simple systems such as harmonic oscillators, and propose and check different strategies to describe Markovian dynamics in more complicated interacting systems. Finally we propose a counter-intuitive situation where some level of noise can be actually useful for information tasks. In the third and last part, we approach the problem of the non-Markovian description of open quantum systems. To quantify how non-Markovian an open quantum system is we introduce a computable measure and apply it to some relevant situations. We also propose a way of probing the complexity of an environment by visualizing properties of a pair of qubits embedded in it. In addition, we develop a technique based on orthogonal polynomial theory to transform a wide range of environments into simple chains of particles which can be efficiently simulated with numerical techniques.