arXiv subjects

Christoph Simon

Publications and source records attributed to Christoph Simon.

At least 37 records · Page 2Linked to original sources

arXiv2025

Satellites promise global-scale quantum networks

Academia, governments, and industry around the world are on a quest to build long-distance quantum communication networks for a future quantum internet. Using air and fiber channels, quantum communication quickly faced the daunting challenge of exponential photon loss with distance. Quantum repeaters were invented to solve the loss problem by probabilistically establishing entanglement over short distances and using quantum memories to synchronize the teleportation of such entanglement to long distances. However, due to imperfections and complexities of quantum memories, ground-based proof-of-concept repeater demonstrations have been restricted to metropolitan-scale distances. In contrast, direct photon transmission from satellites through empty space faces almost no exponential absorption loss and only quadratic beam divergence loss. A single satellite successfully distributed entanglement over more than 1,200 km. It is becoming increasingly clear that quantum communication over large intercontinental distances (e.g. 4,000-20,000 km) will likely employ a satellite-based architecture. This could involve quantum memories and repeater protocols in satellites, or memory-less satellite-chains through which photons are simply reflected, or some combination thereof. Rapid advancements in the space launch and classical satellite communications industry provide a strong tailwind for satellite quantum communication, promising economical and easier deployment of quantum communication satellites.

quant-ph↗

arXiv2025

Magnetic Field-dependent Isotope Effect Supports Radical Pair Mechanism in Tubulin Polymerization

Weak magnetic fields and isotopes have been shown to influence biological processes; however, the underlying mechanisms remain poorly understood, particularly because the corresponding interaction energies are far below thermal energies, making classical explanations challenging or impossible. Microtubules, dynamic cytoskeletal fibers, offer an ideal system to test weak magnetic field effects due to their self-assembling capabilities, sensitivity to magnetic fields, and their central role in cellular processes. In this study, we use a combination of experiments and simulations to explore how nuclear spin dynamics affect microtubule polymerization by examining interactions between magnesium isotope substitution and weak magnetic fields. Our experiments reveal an isotope-dependent effect, which can be explained via a radical pair mechanism, explicitly arising from nuclear spin properties rather than isotopic mass differences. This nuclear spin-driven isotope effect is notably enhanced under an applied weak magnetic field of approximately 3 mT. Our theoretical model based on radical pairs achieves quantitative agreement with our experimental observations. These results establish a direct connection between quantum spin dynamics and microtubule assembly, providing new insights into how weak magnetic fields influence cellular and biomolecular functions.

physics.bio-ph↗

arXiv2024

Quantum Active Learning for Structural Determination of Doped Nanoparticles -- a Case Study of 4Al@Si$_{11}$

Active learning (AL) has been widely applied in chemistry and materials science. In this work we propose a quantum active learning (QAL) method for automatic structural determination of doped nanoparticles, where quantum machine learning (QML) models for regression are used iteratively to indicate new structures to be calculated by DFT or DFTB and this new data acquisition is used to retrain the QML models. The QAL method is implemented in the Quantum Machine Learning Software/Agent for Material Design and Discovery (QMLMaterial), whose aim is using an artificial agent (defined by QML regression algorithms) that chooses the next doped configuration to be calculated that has a higher probability of finding the optimum structure. The QAL uses a quantum Gaussian process with a fidelity quantum kernel as well as the projected quantum kernel and different quantum circuits. For comparison, classical AL was used with a classical Gaussian process with different classical kernels. The presented QAL method was applied in the structural determination of doped Si$_{11}$ with 4 Al (4Al@Si$_{11}$) and the results indicate the QAL method is able to find the optimum 4Al@Si$_{11}$ structure. The aim of this work is to present the QAL method -- formulated in a noise-free quantum computing framework -- for automatic structural determination of doped nanoparticles and materials defects.

quant-ph↗

arXiv2024

Master equation-based model for infrared-based magnetometry with nitrogen-vacancy centers in diamond cavities: a path to sub-picotesla sensitivity at sub-millimeter scales

Our study aims to increase the spatial resolution of high-sensitivity magnetometry based on singlet-transition infrared (IR) absorption using nitrogen-vacancy (NV) centers in diamonds in monolithic cavities, with potential applications in bio-magnetic field detection. We develop a master-equation treatment of optically detected magnetic resonance, incorporating IR light saturation effects. This master equation provides the singlet population, which is then utilized to calculate the reflectivity and ultimately derive the magnetic field sensitivity taking into account photon and spin shot noise. We further show that our model is compatible with experiments of IR-based NV center magnetometry. Through optimization in a high-parameter space, we uncover the potential to achieve sensitivities in the order of sub-pico tesla, even for sub-millimeter scales.

quant-ph↗

arXiv2024

Frequency- and dissipation-dependent entanglement advantage in spin-network Quantum Reservoir Computing

We study the performance of an Ising spin network for quantum reservoir computing (QRC) in linear and non-linear memory tasks. We investigate the extent to which quantumness enhances performance by monitoring the behaviour of quantum entanglement, which we quantify by the partial transpose of the density matrix. In the most general case where the effects of dissipation are incorporated, our results indicate that the strength of the entanglement advantage depends on the frequency of the input signal; the benefit of entanglement is greater with more rapidly fluctuating signals, whereas a low-frequency input is better suited to a non-entangled reservoir. This may be understood as a condition for an entanglement advantage to manifest itself: the system's quantum memory must survive for long enough for the temporal structure of the input signal to reveal itself. We also find that quantum entanglement empowers a spin-network quantum reservoir to remember a greater number of temporal features.

quant-ph↗

arXiv2024

Exploring Quantum Active Learning for Materials Design and Discovery

The meeting of artificial intelligence (AI) and quantum computing is already a reality; quantum machine learning (QML) promises the design of better regression models. In this work, we extend our previous studies of materials discovery using classical active learning (AL), which showed remarkable economy of data, to explore the use of quantum algorithms within the AL framework (QAL) as implemented in the MLChem4D and QMLMaterials codes. The proposed QAL uses quantum support vector regressor (QSVR) or a quantum Gaussian process regressor (QGPR) with various quantum kernels and different feature maps. Data sets include perovskite properties (piezoelectric coefficient, band gap, energy storage) and the structure optimization of a doped nanoparticle (3Al@Si11) chosen to compare with classical AL results. Our results revealed that the QAL method improved the searches in most cases, but not all, seemingly correlated with the roughness of the data. QAL has the potential of finding optimum solutions, within chemical space, in materials science and elsewhere in chemistry.

quant-ph↗

arXiv2024

The Radical Pair Mechanism Cannot Explain Telecommunication Frequency Effects on Reactive Oxygen Species

In order to investigate whether the radical pair mechanism (RPM) can explain the effects of telecommunication frequency radiation on reactive oxygen species production, we modelled the effects of oscillating magnetic fields on radical pair systems. Our analysis indicates that the RPM cannot account for the biological effects observed under exposure to telecommunication frequencies due to negligible effects under low-amplitude conditions used in experimental setups. Observable effects on radical pairs at these frequencies would require hyperfine coupling constants that are precisely fine-tuned to large values that far exceed those naturally occurring within biological systems. We conclude that some other mechanism must be responsible for the effects of telecommunication frequency fields in biological systems.

physics.bio-ph↗

arXiv2024

Quantum theory of a potential biological magnetic field sensor: radical pair mechanism in flavin adenine dinucleotide biradicals

Recent studies in vitro and in vivo suggest that flavin adenine dinucleotide (FAD) on its own might be able to act as a biological magnetic field sensor. Motivated by these observations, in this study, we develop a detailed quantum theoretical model for the radical pair mechanism (RPM) for the flavin adenine biradical within the FAD molecule. We perform molecular dynamics simulations to determine the distance between the radicals on FAD, which we then feed into a quantum master equation treatment of the RPM. In contrast to previous semi-classical models which are limited to the low-field and high-field cases, our quantum model can predict the full magnetic field dependence of the transient absorption signal. Our model's predictions are consistent with experiments.

physics.bio-ph↗

arXiv2024

Quantumness and Learning Performance in Reservoir Computing with a Single Oscillator

We explore the power of reservoir computing with a single oscillator in learning time series using quantum and classical models. We demonstrate that this scheme learns the Mackey--Glass (MG) chaotic time series, a solution to a delay differential equation. Our results suggest that the quantum nonlinear model is more effective in terms of learning performance compared to a classical non-linear oscillator. We develop approaches for measuring the quantumness of the reservoir during the process, proving that Lee-Jeong's measure of macroscopicity is a non-classicality measure. We note that the evaluation of the Lee-Jeong measure is computationally more efficient than the Wigner negativity. Exploring the relationship between quantumness and performance by examining a broad range of initial states and varying hyperparameters, we observe that quantumness in some cases improves the learning performance. However, our investigation reveals that an indiscriminate increase in quantumness does not consistently lead to improved outcomes, necessitating caution in its application. We discuss this phenomenon and attempt to identify conditions under which a high quantumness results in improved performance.

quant-ph↗

arXiv2024

QEYSSat 2.0 -- White Paper on Satellite-based Quantum Communication Missions in Canada

We present the white paper developed during the QEYSSat 2.0 study, which was undertaken between June 2021 and March 2022. The study objective was to establish a technology road-map for a Canada-wide quantum network enabled by satellites. We survey the state-of-art in quantum communication technologies, identify the main applications and architectures, review the technical readiness levels and technology bottlenecks and identify a future mission scenario. We report the findings of a dedicated one-day workshop that included Canadian stakeholders from government, industry and academia to gather inputs and insights for the applications and technical road-map. We also provide an overview of the Quantum EncrYption and Science Satellite (QEYSSat) mission expected to launch in 2024-2025 and its anticipated outcomes. One of the main outcomes of this study is that developing the main elements for a Canada-wide quantum internet will have the highest level of impact, which includes Canada-wide entanglement distribution and teleportation. We present and analyze a possible future mission ('QEYSSat 2.0') that would enable a long range quantum teleportation across Canada as an important step towards this vision.

quant-ph↗

arXiv2023

Towards a Realistic Model for Cavity-Enhanced Atomic Frequency Comb Quantum Memories

Atomic frequency comb (AFC) quantum memory is a favorable protocol in long distance quantum communication. Putting the AFC inside an asymmetric optical cavity enhances the storage efficiency but makes the measurement of the comb properties challenging. We develop a theoretical model for cavity-enhanced AFC quantum memory that includes the effects of dispersion, and show a close alignment of the model with our own experimental results. Providing semi quantitative agreement for estimating the efficiency and a good description of how the efficiency changes as a function of detuning, it also captures certain qualitative features of the experimental reflectivity. For comparison, we show that a theoretical model without dispersion fails dramatically to predict the correct efficiencies. Our model is a step forward to accurately estimating the created comb properties, such as the optical depth inside the cavity, and so being able to make precise predictions of the performance of the prepared cavity-enhanced AFC quantum memory.

quant-ph↗

arXiv2023

Radical pairs and superoxide amplification can explain magnetic field effects on planarian regeneration

Weak magnetic field exposure can affect many biological processes across a wide range of living organisms. Recently, it has been observed that weak magnetic fields can modulate reactive oxygen species (ROS) concentration, affecting regeneration in planaria. These effects show unusual nonlinear dependence on magnetic field strength, including a sign change. In another study by the same group, superoxide is identified as the particular ROS being modulated. We propose a radical pair mechanism based on a flavin-superoxide radical pair to explain the modulation of superoxide production and its effect on planarian regeneration. The results of our calculations favor a triplet-born radical pair. Our yield calculations can reproduce the observed magnetic field dependence, including the sign change. Moreover, to explain the size of the effect on ROS concentration, we suggest a simple amplification model inspired by known biochemical mechanisms and lay out the conditions for such a model to work. Further, we also make empirical predictions concerning the hypomagnetic field effects on planarian regeneration.

physics.bio-ph↗

arXiv2023

The Power of One Clean Qubit in Supervised Machine Learning

This paper explores the potential benefits of quantum coherence and quantum discord in the non-universal quantum computing model called deterministic quantum computing with one qubit (DQC1) in supervised machine learning. We show that the DQC1 model can be leveraged to develop an efficient method for estimating complex kernel functions. We demonstrate a simple relationship between coherence consumption and the kernel function, a crucial element in machine learning. The paper presents an implementation of a binary classification problem on IBM hardware using the DQC1 model and analyzes the impact of quantum coherence and hardware noise. The advantage of our proposal lies in its utilization of quantum discord, which is more resilient to noise than entanglement.

quant-ph↗

arXiv2023

Radical Pair Model for Magnetic Field Effects on NMDA Receptor Activity

The N-methyl-D-aspartate receptor is a prominent player in brain development and functioning. Perturbations to its functioning through external stimuli like magnetic fields can potentially affect the brain in numerous ways. Various studies have shown that magnetic fields of varying strengths affect these receptors. We propose that the radical pair mechanism, a quantum mechanical process, could explain some of these field effects. Radicals of the form $[\mbox{RO}^\bullet \mbox{ Mg($\mbox{H}_2$O$)_n$}^{+\bullet}]$, where R is a protein residue that can be Serine or Tyrosine, are considered for this study. The variation in the singlet fractional yield of the radical pairs, as a function of magnetic field strength, is calculated to understand how the magnetic field affects the products of the radical pair reactions. Based on the results, the radical pair mechanism is a likely candidate for explaining the magnetic field effects observed on the receptor activity. The model predicts changes in the behaviour of the system as magnetic field strength is varied and also predicts certain isotope effects. The results further suggest that similar effects on radical pairs could be a plausible explanation for various magnetic field effects within the brain.

physics.bio-ph↗

arXiv2023

Coarse-graining and criticality in the human connectome

In the face of the stupefying complexity of the human brain, network analysis is a most useful tool that allows one to greatly simplify the problem, typically by approximating the billions of neurons comprising the brain by means of a coarse-grained picture with a practicable number of nodes. But even such relatively small and coarse networks, such as the human connectome with its 100-1000 nodes, may present challenges for some computationally demanding analyses that are incapable of handling networks with more than a handful of nodes. With such applications in mind, we set out to further coarse-grain the human connectome by taking a modularity-based approach, the goal being to produce a network of a relatively small number of modules. We applied this approach to study critical phenomena in the brain; we formulated a hypothesis based on the coarse-grained networks in the context of criticality in the Wilson-Cowan and Ising models, and we verified the hypothesis, which connected a transition value of the former with the critical temperature of the latter, using the original networks. We found that the qualitative behavior of the coarse-grained networks reflected that of the original networks, albeit to a less pronounced extent. This, in principle, allows for the drawing of similar qualitative conclusions by analysing the smaller networks, which opens the door for studying the human connectome in contexts typically regarded as computationally intractable, such Integrated Information Theory and quantum models of the human brain.

q-bio.NC↗

arXiv2023

Proposal for room-temperature quantum repeaters with nitrogen-vacancy centers and optomechanics

We propose a quantum repeater architecture that can operate under ambient conditions. Our proposal builds on recent progress towards non-cryogenic spin-photon interfaces based on nitrogen-vacancy centers, which have excellent spin coherence times even at room temperature, and optomechanics, which allows to avoid phonon-related decoherence and also allows the emitted photons to be in the telecom band. We apply the photon number decomposition method to quantify the fidelity and the efficiency of entanglement established between two remote electron spins. We describe how the entanglement can be stored in nuclear spins and extended to long distances via quasi-deterministic entanglement swapping operations involving the electron and nuclear spins. We furthermore propose schemes to achieve high-fidelity readout of the spin states at room temperature using the spin-optomechanics interface. Our work shows that long-distance quantum networks made of solid-state components that operate at room temperature are within reach of current technological capabilities.

quant-ph↗

arXiv2023

Quantum Optical Memory for Entanglement Distribution

Optical photons are powerful carriers of quantum information, which can be delivered in free space by satellites or in fibers on the ground over long distances. Entanglement of quantum states over long distances can empower quantum computing, quantum communications, and quantum sensing. Quantum optical memories can effectively store and manipulate quantum states, which makes them indispensable elements in future long-distance quantum networks. Over the past two decades, quantum optical memories with high fidelity, high efficiencies, long storage times, and promising multiplexing capabilities have been developed, especially at the single photon level. In this review, we introduce the working principles of commonly used quantum memory protocols and summarize the recent advances in quantum memory demonstrations. We also offer a vision for future quantum optical memory devices that may enable entanglement distribution over long distances.

quant-ph↗

arXiv2023

Optical polarization evolution and transmission in multi-Ranvier-node axonal myelin-sheath waveguides

In neuroscience, it is of interest to consider all possible modes of information transfer between neurons in order to fully understand processing in the brain. It has been suggested that photonic communication may be possible along axonal connections, especially through the myelin sheath as a waveguide, due to its high refractive index. There is already a good deal of theoretical and experimental evidence for light guidance in the myelin sheath; however, the question of how the polarization of light is transmitted remains largely unexplored. It is presently unclear whether polarization-encoded information could be preserved within the myelin sheath. We simulate guided mode propagation through a myelinated axon structure with multiple Ranvier nodes. This allows both to observe polarization change and to test the assumption of exponentiated transmission loss through multiple Ranvier nodes for guided light in myelin sheath waveguides. We find that the polarization can be well preserved through multiple nodes and that transmission losses through multiple nodes are approximately multiplicative. These results provide an important context for the hypothesis of neural information transmission facilitated by biophotons, strengthening the possibility of both classical and quantum photonic communication within the brain.

physics.bio-ph↗