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Physica Scripta

Enhanced signal-to-noise ratio in quantum plasmonic image sensing including loss and varying photon number

Kelvin Tafadzwa Mpofu, Patience T. Mthunzi-Kufa

Published Oct 4, 2023• 19 citations
Publisher

Abstract

Abstract The signal-to-noise ratio is an important quantity in signal and image analysis that gives information about the quality of the signal and/or image of interest. When plasmonic biosensors are used to study how molecules interact in intermolecular binding reactions, the output signal and/or image must be of the highest quality to get the best value from our biosensors. Images of interest in this work are images of the binding region at the metal surface of the plasmonic biosensor. Improving the signal-to-noise ratio of these signals and/or images is a key area of research that can help scientists learn more about how different molecules interact with each other. Because these molecular entities can include a wide range of biomolecules, we can investigate different types of binding interactions. In this paper, we look at a theoretical two-mode image sensing framework that we use to model the signal-to-noise ratio in images generated by a plasmonic image-based biosensor. A Krestchmann configuration-based surface resonance sensor is used as a plasmonic biosensor. In the model, an example of how BSA and an antibody called IgG1 bind to the surface of a plasmonic biosensor are examined. Traditionally, classical states of light are used as probe states in the Krestchman configuration; in this paper, quantum states of light are considered alternative probe states. The effect of using quantum states of light, such as the Fock state, squeezed displaced states, and squeezed vacuum states, on the signal-to-noise ratio of images is investigated. This work also looks at the effect of losses in the sensing environment and changes in photon numbers in the input signal on the average signal-to-noise ratio of the output of the plasmonic biosensor. The novelty in the described work lies in the exploration of using a variety quantum states of light as probe states in a plasmonic image-based biosensor, specifically in the context of improving the signal-to-noise ratio of images captured from the binding region at the metal surface accounting for the impact of losses. It was found that some quantum states improve the signal-to-noise ratio of the plasmonic biosensor output image.

DOI
10.1088/1402-4896/acfffc

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Abstract The signal-to-noise ratio is an important quantity in signal and image analysis that gives information about the quality of the signal and/or image of interest. When plasmonic biosensors are used to study how molecules interact in intermolecular binding reactions, the output signal and/or image must be of the highest quality to get the best value from our biosensors. Images of interest in this work are images of the binding region at the metal surface of the plasmonic biosensor. Improving the signal-to-noise ratio of these signals and/or images is a key area of research that can help scientists learn more about how different molecules interact with each other. Because these molecular entities can include a wide range of biomolecules, we can investigate different types of binding interactions. In this paper, we look at a theoretical two-mode image sensing framework that we use to model the signal-to-noise ratio in images generated by a plasmonic image-based biosensor. A Krestchmann configuration-based surface resonance sensor is used as a plasmonic biosensor. In the model, an example of how BSA and an antibody called IgG1 bind to the surface of a plasmonic biosensor are examined. Traditionally, classical states of light are used as probe states in the Krestchman configuration; in this paper, quantum states of light are considered alternative probe states. The effect of using quantum states of light, such as the Fock state, squeezed displaced states, and squeezed vacuum states, on the signal-to-noise ratio of images is investigated. This work also looks at the effect of losses in the sensing environment and changes in photon numbers in the input signal on the average signal-to-noise ratio of the output of the plasmonic biosensor. The novelty in the described work lies in the exploration of using a variety quantum states of light as probe states in a plasmonic image-based biosensor, specifically in the context of improving the signal-to-noise ratio of images captured from the binding region at the metal surface accounting for the impact of losses. It was found that some quantum states improve the signal-to-noise ratio of the plasmonic biosensor output image.
Abstract Our research aims to create a theoretical framework that may be used to improve phase-based surface plasmon resonance (SPR) biosensor precision beyond the shot noise limit by utilizing quantum states including squeezed states and NOON states. For this work, a two-mode phase sensing setup model is created. One of the two arms of the two mode model of this model has an integrated SPR system based on the Krestchmann arrangement. An experiment involving phase-based plasmonic biosensing is modeled using the two-mode setup. The state preparation, the biosensing component, and the measurement comprise the three main components of the model. The measurement varies depending on the particular input state. Quantum noise reduction for quantum states results from the combination of the sub-Poissonian statistical structure of a single mode and the non-classical correlation of the photon number between the two modes (entanglement). We show that when combined with the high sensitivity of the SPR sensor, the use of two-mode quantum states of light considerably increases the estimation precision of the refractive index of an analyte. Here, we use distilled water diluted BSA solutions at different concentrations that correlate to different refractive indices to reproduce a static phase-based SPR biosensor. Both lossless and lossy circumstances were taken into consideration for the model. The NOON state and the product coherent squeezed vacuum (PCSV) state are the two main quantum states taken into consideration in this work. The PCSV state exhibited the better limit of detection (LOD) among the states that we measured, suggesting that it is a promising candidate for the development of quantum biosensing systems. The effect of losses will require more investigation, but this work enables us to identify a precise course of action for enhancing the performance of the phase-based surface plasmon resonance sensor even further. Phase-based quantum SPR sensors have yet to be thoroughly examined, but intensity-based quantum SPR sensors have previously been extensively researched in the biochemical and medical sensing domains.
Quantum states of light allow for highly sensitive biosensing configurations, surpassing the limitations imposed by shot-noise. In this theoretical study, we focus on optical plasmonic sensors, which have extensive applications in disease diagnostics, including detection of diseases like HIV. Our investigation involves simulating the impact of quantum states of light, such as the NOON state and squeezed states, on enhancing the limit of detection in a plasmonic phase-sensing biosensor, surpassing coherent light states’ shot-noise limit. Specifically, we explore the use of quantum states to improve the limit of detection in phase-based biosensors for HIV detection, operating below the shot-noise limit. Through our analysis, we demonstrate that incorporating quantum states of light in surface plasmon resonance (SPR) biosensing leads to enhanced performance compared to classical states. Moreover, we take into account the impact of environmental losses in the biosensing setup, considering the real-world challenges in practical implementation. Our findings emphasize the potential of quantum SPR biosensors in the development of novel disease diagnostics devices.
Kinetic models are essential for describing how molecules interact in a variety of biochemical processes. The estimation of a model’s kinetic parameters by experiment enables researchers to understand how pathogens, such as viruses, interact with other entities like antibodies and trial drugs. In this work, we report a simple proof-of-principle experiment that uses quantum sensing techniques to give a more precise estimation of kinetic parameters than is possible with a classical approach. The interaction we study is that of bovine serum albumin (BSA) binding to gold via an electrostatic mechanism. BSA is an important protein in biochemical research as it can be conjugated with other proteins and peptides to create sensors with a wide range of specificity. We use single photons generated via parametric down-conversion to probe the BSA–gold interaction in a plasmonic resonance sensor. We find that sub-shot-noise-level fluctuations in the sensor signal allow us to achieve an improvement in the precision of up to 31.8% for the values of the kinetic parameters. This enhancement can, in principle, be further increased in the setup. Our work highlights the potential use of quantum states of light for sensing in biochemical research.
Analyzing the kinetics of biological processes plays a significant role in understanding fundamental cellular functions. Many physics-based technologies used to study such processes are limited by the shot noise inherent to the coherent states of light. These technologies can greatly benefit from leveraging quantum probes to improve the sensitivity of measurements in cellular biology. The surface plasmon resonance technique has been used effectively to achieve label-free, real-time measurements of protein binding kinetics, which constitutes an important biological phenomenon occurring near the cell membrane. Here, we demonstrate the integration of this technique with the two-mode bright squeezed state having fewer fluctuations as compared to the coherent state to improve the sensitivity of measurement in studying a protein-gold adsorption process. We show 4 dB of squeezing as we record the signal-to-noise ratio as the function of time, and it is maintained throughout the kinetic process. The improved signal-to-noise ratio leads to a 60 % improvement in the sensitivity of measuring the observable rate constant k s . The quantum advantage as shown in terms of squeezing is achieved despite the total absorption of 74 % from the source until the final detection after the sensor. Overall, we provide the most practical setup for improving the sensitivity of the time-dependent measurements involved in various biological processes at the molecular level.
The measurement of parameters that describe kinetic processes is important in the study of molecular interactions. It enables a deeper understanding of the physical mechanisms underlying how different biological entities interact with each other, such as viruses with cells, vaccines with antibodies, or new drugs with specific diseases. In this work, we study theoretically the use of quantum sensing techniques for measuring the kinetic parameters of molecular interactions. The sensor we consider is a plasmonic resonance sensor---a label-free photonic sensor that is one of the most widely used in research and industry. The first type of interaction we study is the antigen BSA interacting with antibody IgG1, which provides a large sensor response. The second type is the enzyme carbonic anhydrase interacting with the tumor growth inhibitor benzenesulfonamide, which produces a small sensor response. For both types of interaction we consider the use of two-mode Fock states, squeezed vacuum states, and squeezed displaced states. We find that these quantum states offer an enhancement in the measurement precision of kinetic parameters when compared to that obtained with classical light. The results may help in the design of more precise quantum-based sensors for studying kinetics in the life sciences.
We investigate the use of twin-mode quantum states of light with symmetric statistical features in their photon number for improving intensity-sensitive surface plasmon resonance (SPR) sensors. For this purpose, one of the modes is sent into a prism setup where the Kretschmann configuration is employed as a sensing platform and the analyte to be measured influences the SPR excitation conditions. This influence modifies the output state of light that is subsequently analyzed by an intensity-difference measurement scheme. We show that quantum noise reduction is achieved not only as a result of the sub-Poissonian statistical nature of a single mode, but also as a result of the nonclassical correlation of the photon number between the two modes. When combined with the high sensitivity of the SPR sensor, we show that the use of twin-mode quantum states of light notably enhances the estimation precision of the refractive index of an analyte. With this we are able to identify a clear strategy to further boost the performance of SPR sensors, which are already a mature technology in biochemical and medical sensing applications.