Understanding the fundamental quantum and classical properties of photons is crucial in a wide range of applications. Photons exhibit quantum entanglement, the strongest form of correlation that has been observed between subsystems. Entanglement is perhaps the most valuable resource for many quantum information and quantum computation tasks, empowering them to be superior to their classical counterparts. Undoubtedly, understanding how entanglement can be generated, manipulated, and measured are among the most pre-eminent research questions in quantum information processing. However, the realm of influence of photons is not just limited to information technologies. Photons are, surprisingly, being produced constantly in biological systems as well. Modeling and characterizing the involvement of photons in various biological processes are active areas of research. In the first part of my Ph.D. program, I focused on the problem of quantifying multi-partite entanglement in a solid, an atomic frequency comb (AFC) crystal, using a single photon. We proposed a novel entanglement witness and showed that our witness is well suited for demonstrating and quantifying multi-partite entanglement in AFC systems. Our results are the first demonstration of multi-partite entanglement in a solid between over two hundred ensembles each containing a billion atoms. The second project of my Ph.D. was motivated by the question of why brain cells are producing biophotons. Photons are known as perfect carriers for information. The brain is the computation centre where all the learning and decision makings are happening. Learning, in theory, is an informational task, and its biological realization in the brain is not completely understood. We asked if photons could play a role in the process of learning in the brain. A common form of learning involves multiple cycles of training, evaluating, and receiving feedback. Both forward and backward parts of these cycles require an information flow. Existing theories mainly focus on neural electrochemical signals. We proposed that biophotons can propagate the feedback teaching signals required for learning in the brain. By multiple numerical experiments simulated on an artificial neural network, we demonstrated that stochastic emissions of biophotons carrying partial backward information enable learning in the network.
Understanding the fundamental quantum and classical properties of photons is crucial in a wide range of applications. Photons exhibit quantum entanglement, the strongest form of correlation that has been observed between subsystems. Entanglement is perhaps the most valuable resource for many quantum information and quantum computation tasks, empowering them to be superior to their classical counterparts. Undoubtedly, understanding how entanglement can be generated, manipulated, and measured are among the most pre-eminent research questions in quantum information processing. However, the realm of influence of photons is not just limited to information technologies. Photons are, surprisingly, being produced constantly in biological systems as well. Modeling and characterizing the involvement of photons in various biological processes are active areas of research. In the first part of my Ph.D. program, I focused on the problem of quantifying multi-partite entanglement in a solid, an atomic frequency comb (AFC) crystal, using a single photon. We proposed a novel entanglement witness and showed that our witness is well suited for demonstrating and quantifying multi-partite entanglement in AFC systems. Our results are the first demonstration of multi-partite entanglement in a solid between over two hundred ensembles each containing a billion atoms. The second project of my Ph.D. was motivated by the question of why brain cells are producing biophotons. Photons are known as perfect carriers for information. The brain is the computation centre where all the learning and decision makings are happening. Learning, in theory, is an informational task, and its biological realization in the brain is not completely understood. We asked if photons could play a role in the process of learning in the brain. A common form of learning involves multiple cycles of training, evaluating, and receiving feedback. Both forward and backward parts of these cycles require an information flow. Existing theories mainly focus on neural electrochemical signals. We proposed that biophotons can propagate the feedback teaching signals required for learning in the brain. By multiple numerical experiments simulated on an artificial neural network, we demonstrated that stochastic emissions of biophotons carrying partial backward information enable learning in the network.
Photons, the fundamental quanta of the electromagnetic field, travel at the fastest possible speed, and interact relatively weakly with the environment. These features make them ideal for several practical applications, particularly in the transport of both classical and quantum information. One could also wonder whether nature itself realized the usefulness of these unique entities and through evolution made living beings rely on them for some physiological functions. In my thesis, I cover an example for each of these roles a photon can take. As the first example, I describe our theoretical work pertaining to an important practical application where photons can carry quantum information and mediate entanglement between distant quantum computing nodes. We designed a novel quantum repeater architecture using superconducting processors and optical links, which we believe is the first concrete proposal towards this goal. We compared our repeater’s performance with a few other promising approaches and showed that ours could yield higher entanglement distribution rates with good fidelities in appropriate regimes. Such an architecture could be pertinent to envision a quantum internet in the future, something that would be analogous to, but much more secure and powerful in certain aspects than today’s classical internet. As the second example, I describe our theoretical work where we speculate on the potential role of photons observed in mammalian brains. Could we be using these photons as information carriers in addition to the well-known electrochemical signals? We show, based on detailed theoretical modelling, that myelinated axons could serve as good optical waveguides in the brain, which can answer this question in the affirmative. Ours is the first proposal identifying myelinated axons as potential optical waveguides. There is indirect experimental evidence to support this hypothesis, and we propose precise experiments to test the waveguide capabilities directly. Since these photons can also in principle carry quantum information, we further speculate on the existence of quantum networks in the brain. Our work could help develop a better understanding of some of the biggest unsolved problems in neuroscience, possibly including the generation of our subjective conscious experience.
This research investigates the potential of utilizing quantum entanglement to simulate information encoding and decoding mechanisms within biological neural networks. The core premise is that quantum phenomena, specifically entanglement, may play a more significant role in biological neuronal processing than previously acknowledged. This work proposes a novel approach employing quantum bits (qubits) to represent individual neurons, with connections between neurons established through quantum entanglement. The simulation aims to mimic the processes of synaptic transmission and signal propagation observed in biological neural networks. Mathematical formulations describe the evolution of the entangled qubit states under influence of simulated neuronal inputs, and the measurement processes are modeled to represent the observed output signals. This research offers a theoretical framework for exploring the interplay between quantum mechanics and biological neural systems, potentially leading to a deeper understanding of the fundamental principles governing brain function. The study utilizes a discrete-time simulation approach, allowing for a detailed analysis of the dynamics of the entangled neural network. Key performance indicators, such as the fidelity of information transfer and the robustness of the simulated network, are explored. The results suggest that quantum entanglement can provide a viable model for simulating complex neural processes, warranting further investigation into the potential for quantum computing to revolutionize our understanding of the brain.
Major efforts in quantum information science are devoted to the development of methods that are superior to the one of classical information processing, for example the quantum computer or quantum simulations. For these purposes, superposition and entangled states are considered a decisive resource. Furthermore, since the early days of quantum mechanics, entanglement has revealed the discrepancy between the quantum mechanical and the everyday life perception of the physical world. This combination of fundamental science and application-oriented research makes the realization, characterization, and application of entanglement a challenge pursued by many researchers. In this work, the observation of entangled states of polarization encoded photonic qubits is pushed forward in two directions: flexibility in state observation and increase in photon rate. To achieve flexibility two different schemes are developed: setup-based and entanglement-based observation of inequivalent multi-photon states. The setup-based scheme relies on multi-photon interference at a polarizing beam splitter with prior polarization manipulations. It allows the observation of a family of important four-photon entangled states. The entanglement-based scheme exploits the rich properties of Dicke states under particle projections or loss in order to obtain inequivalent multi-photon entangled states. The observed states are characterized using the fidelity and entanglement witnesses. An increase in photon rate is crucial to achieve entanglement of higher photon numbers. This holds especially, when photon sources are utilized that emit photons spontaneously. To this end, a new photon source is presented based on a femtosecond ultraviolet enhancement cavity and applied to the observation of the six-photon Dicke state with three excitations. The implemented schemes not only allow the observation of inequivalent types of entanglement, but also the realization of various quantum information tasks. In this work, the four-photon GHZ state has been used in a quantum simulation of a minimal instance of the toric code. This code enables the demonstration of basic properties of anyons, which are quasiparticles distinct from bosons and fermions. Further, the six-photon Dicke state has been applied for quantum metrology: It allows one to estimate a phase shift with a higher precision than by using only classical resources. Altogether, a whole series of experiments for observing inequivalent multi-photon entangled states can now be substituted by a single experimental setup based on the designs developed in this work. In addition to this new approach of photon processing, a novel photon source has been implemented, paving the way to realizations of applications requiring higher photon numbers.
Quantum information has emerged as a transformative technology with the potential to revolutionize various fields, and biological neural networks, with their intricate complexity and dynamic nature, represent a particularly promising area for exploration. This paper investigates the potential of quantum information to enhance learning mechanisms within biological neural networks, leveraging quantum entanglement and quantum computation to improve efficiency and model expressiveness. We propose a novel quantum neural network architecture that employs quantum entanglement to stabilize learning and optimize network parameters, addressing the limitations of conventional neural network learning. This research explores the fundamental principles behind such a system and highlights its potential for advancing our understanding of biological brain function. The core claim is that quantum information can significantly improve learning efficiency and model representation capabilities in biological neural networks.
There are both fundamental and practical motivations for studying whether quantum entanglement can exist in macroscopic systems. However, multiparty entanglement is generally fragile and difficult to quantify. Dicke states are multiparty entangled states where a single excitation is delocalized over many systems. Building on previous work on quantum memories for photons, we create a Dicke state in a solid by storing a single photon in a crystal that contains many large atomic ensembles with distinct resonance frequencies. The photon is re-emitted at a well-defined time due to an interference effect analogous to multi-slit diffraction. We derive a lower bound for the number of entangled ensembles based on the contrast of the interference and the single-photon character of the input, and we experimentally demonstrate entanglement between over two hundred ensembles, each containing a billion atoms. We also illustrate the fact that each individual ensemble contains further entanglement.Multipartite entanglement is of both fundamental and practical interest, but is notoriously difficult to witness and characterise. Here, Zarkeshian et al. demonstrate multipartite entanglement in an atomic frequency comb storing a single photon in a Dicke state spread over a macroscopic ensemble.
The past two decades have witnessed tremendous advances and breakthroughs in quantum information science and technology, due mainly to the use of quantum physical resources such as coherence and entanglement. The formalization of the concept of universal quantum computing by D. Deutsch in 1985 has matured into commercial initiatives that aim to accelerate the physical implementation of a practical quantum computer. So far, such quantum technology has been pushed forward as information processors that are mainly on superconducting quantum bits (qubits) based. Other developments make use of quantum states of photons in conjunctions with other quantum registers based on electrons, atoms, molecules, artificial systems, between others. Although in any case, multiple qubit technologies are still under intense research and developments and the temperature and size of the quantum register are essential issues. However, all possible physical implementation of quantum information processing devices have in common the fundamental properties of quantum systems: interference, coherence, and entanglement. In this thesis, we concerned the study of quantum coherence and entanglement in qubits (encoded on the polarisation basis) and quantum materials (operating at room temperature) to analyze the role of quantum correlations and decoherence for information processing purposes. The current research is divided into two main parts, the first one begins with the analysis of the influence of a birefringent medium over the entanglement of a photonic qubit state. We employ a polarisation maintaining fiber (PMF) as a decohering environment to test the theoretical model in which the symmetry of the coupling between the qubit and environment defines the death and revival of the information correlations. This finding establishes a tool to keep the entanglement independent of the fiber length employing the symmetry properties of the physical system. Additionally, to demonstrate that the entanglement is not the only crucial factor in information schemes, we employ the prisoner’s dilemma game (in a two parameters strategy space and extended up to three) to evidence that quantum advantages in this protocol are by the quantum superposition instead of the entanglement of the physical system. Here we also pose an experimental setup with photons to verify our findings with photonic qubits. The second part of the thesis examines a novel nanomaterial which could serve up a bridge to the interaction of photons and electrons toward a physical representation of photonic qubits conditioned by external registers (as electrons or ions). The first stage in this direction considers the implementation of single photon emitters. However, previous to it is necessary to recognize the photophysical capabilities of the Perovskites as structure selected. As a complement, the novelty of this nanostructure allow us to give answers to some open questions in this characterization direction in the frame of this research. The MA-halide (methylammonium-halide) perovskites are structurally composed by small domains which ranging from nano to micrometer sizes presenting strong photoluminescence intermittency (blinking). We attribute this response to the Auger- nonradiative recombination of additional electrons photogenerated in a trap-filling process due to defects or ion movement. We verified this through the application of an absorbing layer (quencher) of charges of PCBM (Phenyl-C61-butyric acid methyl ester) resulting in considerably decreases in blinking. We also provide a novel technique for real-time observation of the ion movement effect over this material. Additionally, this behavior indicates appropriate conditions for the existence of a few emitters which are useful in quantum protocols and become a motivation to analyze and explain this phenomenon. Then, we prepare two chemical compositions of inorganic Perovskites with a high structural order to explore the necessary conditions to produce single emitter with this material. We visualized the samples through electron microscopy, and both systems were spectrally characterized decreasing dilutions up to observe emission intermittency. We verified the nonclassical behavior of the emission employing a Hanbury Brown-Twiss interferometer by measuring the degree of the second-order coherence correlation function. Finally, but not less important, the additional information presents the laboratories implemented during this doctoral research and the prototype of signals counting device to analyze temporal coincidences in correlated photonic events.