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Optical bistability in nonlinear periodic structures : from bragg gratings to photonic crystal

Yosia Yosia

Published Jan 1, 2009• 0 citations
Publisher

Abstract

In the era of advanced communications technology, the demand for bandwidth is ever increasing due to the larger number of users and the expectation for a better Quality of Services (QoS). In present communications network, optical signal still have to experience electronic conversion for processing as it propagates from the transmitter to the receiver. The conversion to electrical signal introduces speed bottleneck, and therefore results in low QoS from user's point of view. To overcome bottleneck of bandwidth requirements, the signal is expected to remain in optical domain as it propagates from transmitter to receiver without experiencing conversion to electrical domain. Consequently, there is a need to do signal processing purely in optical domain to enable all-optical technology.

DOI
10.32657/10356/46843

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In this Internet era, rapid transitioning of many aspects of medical, defense and commercial applications to digital platforms dictates their heavy reliance on optical communication systems. This trend places severe challenges on contemporary communication systems, expected to provide wide-bandwidth services and high degree of information security, with minimum energy dissipation. To meet the rising bandwidth demand, current bandwidth limited technology requires implementation of parallel processing; however, energy dissipation of such a system is globally and environmentally significant. A solution to this problem is envisioned in a form of an optical processor, a device recognized for its high speed, low loss and signal quality preservation. In this dissertation we investigate two optical processor roles: direct signal processing role (all-optical switching) and preprocessing role in preamplified few photon detection. \tIn the direct signal processing role, an optical switch controls the state of one wave by a low-energy control signal. It is realized in a highly nonlinear fiber, a medium acclaimed for its inherent femtosecond response time, a low loss and a high figure of merit. The switching functionality is implemented by employing the four wave mixing process in the depleted pump regime. To maximize the energy exchange, we revisit the saturated parametric mixer phase matching condition and propose a novel dispersion engineering method enhancing the performance. This study advances the understanding of the phase-matched interaction in the saturated parametric mixer and enables the first realization of a few-photon controlled silica-fiber-based device. \tIn the preprocessing role, the all-fiber photonic sampler is implemented prior to detection of a preamplified few photon signal with a low duty cycle; the sampler function is limited to amplified spontaneous emission noise alleviation. The proposed few photon detection method shows an order of magnitude improvement in the Bit Error Ratio and detection efficiency with respect to conventional preamplified receiver, and operates at speed beyond the reach of current single photon detector technology.

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An overview of quantum computing and quantum communication systems

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While the commercial deployment of 5G networks and beyond is a reality, the first work for the definition and study of 6G networks has started. The scientific community agrees that these networks will be characterised by a very high spatial density of access points, heterogeneity of access technologies, an increased number of users per access point, and demand for ubiquitous connectivity that must combine ultra-low latency, very high bandwidth, and high energy efficiency [1, 2]. Among the emerging challenges, holographic communications, high-precision manufacturing, the ubiquitous introduction of intelligence, and the incorporation of new technologies based on sub-terahertz (THz) or Visible Light Communications (VLC) are real issues. These are taking place in a truly three-dimensional coverage framework, integrating terrestrial and aerial radio to meet the needs with cloud-based capabilities where and when needed (on-demand). Radio frequencies are used in wireless telecommunications, but the need for very high throughput requires wider bandwidths, hence very high frequencies, in particular THz bands. Moving to a higher frequency range—from 100 GHz to 10 THz—is expected to significantly increase the bandwidth of the radio channel, which will make it possible to serve a significant number of users. In this case, we are not talking about the connection of cell phones, tablets, or computers (and even smart cars)—we are considering the use of Internet of Things (IoT) devices, which within one base station can be quite a lot. Therefore, the technologies for beamforming, device location, etc., developed for the 5G generation that is just being implemented now should also remain but will be used at higher frequencies [3]. For which 6G is primarily intended, IoT solutions have been given a particular name: ‘human-machine-things’. They involve three elements in the system: a person as a physical carrier; an intelligent device with which the person interacts; collects data and executes commands from an application running on the person's device [4]. The 6G radio networks will provide the means of communication and data gathering necessary to accumulate information. Still, a system's approach will be required for the 6G technology market as a whole involving data analytics, artificial intelligence (AI), and next-generation computation capabilities via HPC and quantum computing [3, 5]. This tremendous amount of data may be harnessed, with strong processing and learning capabilities, to manage the network at different levels. To this end, quantum computing methods can play a significant enabling role and can provide a guaranteed security platform. Towards provisioning this massive connectivity and efficiently processing the voluminous data available at the user and network sides, quantum-powered computing methods have a strong potential in realising the ambitions of a service-driven, fully intelligent 6G communication network. There is every reason to believe that the integration of quantum technology can improve the throughput, efficiency, and security of 6G networks. In addition to the advantages mentioned above, this technology also has benefits in computing speed, guaranteed security, and minimal storage requirements. This makes it ideally suited for various future quantum communication network applications. Research is needed on many fronts to evaluate the potential opportunities of quantum computing in 6G applications. In 5G, a functional division is operated in both the RAN and core networks to meet the ultra-low latency and ultra-high efficiency requirements of 5G verticals. Notably, RAN functions are split into cloud-deployed services with interfacing capabilities. This new architecture has a significant impact on the efficient implementation of security processes [6]. One of the key challenges in deploying secure 5G networks is analysing how current cryptographic algorithms for secure authentication and data transmission can adapt to provide secure authentication between services and secure data encryption while ensuring that stringent efficiency requirements are met [7]. The powerful parallel processing capability of quantum search algorithms can be leveraged to solve large-scale wireless optimisation problems. (1) Is this ‘beyond 5G?’ This topic is highly exploratory and undoubtedly beyond the boundaries of core 5G R&D. (2) What are the new features and key challenges? Classically, the mutual information between the channel input and output must be maximised. For quantum channels, the capacity must be redefined. Quantum channels can increase the achievable capacity. As a result, error correction without redundancy is possible on noisy channels. Quantum computers can enable exponentially complex combinatorial ML decoding in classical systems [5, 6]. To cope with latency-critical scenarios such as automated cars and medical applications, communication must be accomplished in a concise time. Achieving latency of only a few milliseconds is a real challenge. To achieve low latency and ultra-high reliability, it is essential to develop powerful high-end processors that consume little power. Quantum computing seems to be a reliable solution to this issue [8]. With variable quality of service (QoS) requirements, a variable radio resource must be allocated to the user. This can be of variable bandwidth, variable power, or both. Another challenging aspect of 6G is that with the propagation frequency, the signal can attenuate quickly and have a high penetration loss at high frequencies [9]. The signal is also automatically attenuated when accessing homes, residences, or workplaces. As the frequency increases, radio waves attenuate and may have difficulty penetrating the walls of buildings and homes while affecting users' QoS requirements. Therefore, it is very important to develop stable, fast and accurate quantum algorithms to handle 6G communication requirements by dynamically allocating variable resources [10]. The current 5G standard does not address the issue of quantum computing but relies on traditional cryptography. The development towards cloud and edge native infrastructures is expected to continue in 6G networks. While large-scale quantum computing can be expected to take a longer duration, it is time to prepare for the shift to cryptography that is secure in the post-quantum world. According to current knowledge, contemporary symmetric cryptography remains secure for the most part, even after the advent of quantum computing. Furthermore, authentication by a physical layer signature, such as RF fingerprinting, and some other technologies, such as randomisation of MIMO transmission coefficients, coding, etc., could potentially be used in 6G [5, 11]. Whether it is for the optimisation of heterogeneous resources in 6G networks that result in the solution of ‘NP-complete’ combinatorial problems, for the compensation of non-linear effects of a communication chain or the optimisation of MIMO transmitter pre-coding matrix, future network nodes and devices will have to be equipped with learning and decision-making capabilities through AI and machine learning, so that they autonomously optimise their operation in response to changes in the environment [5]. In this context, the use of optimisation techniques based on quantum computing and AI applied to the field of 6G networks could be of considerable interest. Besides, quantum computing allows NP-hard optimisation problems to be solved in linear time, making it possible to solve and execute network optimisation problems in a much faster time, even in real-time [5, 11]. Regulatory and standardisation work will impact our future technology solutions in 5G networks and beyond. Protecting individual privacy and identity has long been a challenge for standards bodies, as countries have very different perspectives and regulations in this area. International standards bodies such as JTC 1 have committees working on privacy frameworks and are making progress, but there is still much to be done [13]. To conclude, we believe that our readers will find this opinion piece useful in giving an overview of the importance of Quantum Computing/communications in shaping the next communication systems and its security platforms. This is a technology in its infancy and a lot of research remains to be carried out to achieve sustainable solutions and overcome the current challenges. The use of intelligent systems (AI, ML and other techniques) will be essential in achieving solutions faster and providing sustainable outcomes. But IoT devices as well as cloud and edges nodes must be AI-ready and be able to support the use of intelligent algorithms.

IET Quantum Communication•Sep 1, 2021•13 citations
In the era of advanced communications technology, the demand for bandwidth is ever increasing due to the larger number of users and the expectation for a better Quality of Services (QoS). In present communications network, optical signal still have to experience electronic conversion for processing as it propagates from the transmitter to the receiver. The conversion to electrical signal introduces speed bottleneck, and therefore results in low QoS from user's point of view. To overcome bottleneck of bandwidth requirements, the signal is expected to remain in optical domain as it propagates from transmitter to receiver without experiencing conversion to electrical domain. Consequently, there is a need to do signal processing purely in optical domain to enable all-optical technology.
The transmission of information as optical signals encoded on light waves traveling through optical fibers and optical networks is increasingly moving to shorter and shorter distance scales. In the near future, optical networking is poised to supersede conventional transmission over electric wires and electronic networks for computer-to-computer communications, chip-to-chip communications, and even on-chip communications. The ever-increasing demand for faster and more reliable devices to process the optical signals offers new opportunities in developing all-optical signal processing systems (systems in which one optical signal controls another, thereby adding "intelligence" to the optical networks). All-optical switches, two-state and many-state all-optical memories, all-optical limiters, all-optical discriminators and all-optical transistors are only a few of the many devices proposed during the last two decades. The "all-optical" label is commonly used to distinguish the devices that do not involve dissipative electronic transport and require essentially no electrical communication of information. The all-optical transistor action was first observed in the context of optical bistability [1] and consists in a strong differential gain regime, in which, for small variations in the input intensity, the output intensity has a very strong variation. This analog operation is for all-optical input what transistor action is for electrical inputs.
In this Internet era, rapid transitioning of many aspects of medical, defense and commercial applications to digital platforms dictates their heavy reliance on optical communication systems. This trend places severe challenges on contemporary communication systems, expected to provide wide-bandwidth services and high degree of information security, with minimum energy dissipation. To meet the rising bandwidth demand, current bandwidth limited technology requires implementation of parallel processing; however, energy dissipation of such a system is globally and environmentally significant. A solution to this problem is envisioned in a form of an optical processor, a device recognized for its high speed, low loss and signal quality preservation. In this dissertation we investigate two optical processor roles: direct signal processing role (all-optical switching) and preprocessing role in preamplified few photon detection. \tIn the direct signal processing role, an optical switch controls the state of one wave by a low-energy control signal. It is realized in a highly nonlinear fiber, a medium acclaimed for its inherent femtosecond response time, a low loss and a high figure of merit. The switching functionality is implemented by employing the four wave mixing process in the depleted pump regime. To maximize the energy exchange, we revisit the saturated parametric mixer phase matching condition and propose a novel dispersion engineering method enhancing the performance. This study advances the understanding of the phase-matched interaction in the saturated parametric mixer and enables the first realization of a few-photon controlled silica-fiber-based device. \tIn the preprocessing role, the all-fiber photonic sampler is implemented prior to detection of a preamplified few photon signal with a low duty cycle; the sampler function is limited to amplified spontaneous emission noise alleviation. The proposed few photon detection method shows an order of magnitude improvement in the Bit Error Ratio and detection efficiency with respect to conventional preamplified receiver, and operates at speed beyond the reach of current single photon detector technology.
The storage wavelength of quantum nodes based on atomic systems does not match the wavelength of optical fiber communication, which requires the establishment of an efficient conversion system between flying bits and storage bits. In this paper, based on the nonlinear wavelength conversion technology of the periodically poled lithium niobate waveguide, a low-noise conversion of 852-nm photons to 1560-nm photons was achieved by a 1878-nm pump laser. The generation mechanism and transmission mechanism of noise due to nonlinear process are analyzed theoretically. The noise photons introduced by the spontaneous parameter downconversion and spontaneous Raman scattering process of a strong pump laser are experimentally studied. The noise suppression near 1560 nm is realized by the fiber Bragg grating (FBG) filter. In the experiment, when the FBG bandwidth is reduced from 0.257 nm to 0.130 nm, the signal-to-noise ratio (SNR) increases from 52 to 90. Our results show that the SNR can be greatly improved by using a narrower band filter. Therefore, the quantum node is connected to the fiber channel, and the signal can be transmitted over long distances with low loss and high fidelity.
While the commercial deployment of 5G networks and beyond is a reality, the first work for the definition and study of 6G networks has started. The scientific community agrees that these networks will be characterised by a very high spatial density of access points, heterogeneity of access technologies, an increased number of users per access point, and demand for ubiquitous connectivity that must combine ultra-low latency, very high bandwidth, and high energy efficiency [1, 2]. Among the emerging challenges, holographic communications, high-precision manufacturing, the ubiquitous introduction of intelligence, and the incorporation of new technologies based on sub-terahertz (THz) or Visible Light Communications (VLC) are real issues. These are taking place in a truly three-dimensional coverage framework, integrating terrestrial and aerial radio to meet the needs with cloud-based capabilities where and when needed (on-demand). Radio frequencies are used in wireless telecommunications, but the need for very high throughput requires wider bandwidths, hence very high frequencies, in particular THz bands. Moving to a higher frequency range—from 100 GHz to 10 THz—is expected to significantly increase the bandwidth of the radio channel, which will make it possible to serve a significant number of users. In this case, we are not talking about the connection of cell phones, tablets, or computers (and even smart cars)—we are considering the use of Internet of Things (IoT) devices, which within one base station can be quite a lot. Therefore, the technologies for beamforming, device location, etc., developed for the 5G generation that is just being implemented now should also remain but will be used at higher frequencies [3]. For which 6G is primarily intended, IoT solutions have been given a particular name: ‘human-machine-things’. They involve three elements in the system: a person as a physical carrier; an intelligent device with which the person interacts; collects data and executes commands from an application running on the person's device [4]. The 6G radio networks will provide the means of communication and data gathering necessary to accumulate information. Still, a system's approach will be required for the 6G technology market as a whole involving data analytics, artificial intelligence (AI), and next-generation computation capabilities via HPC and quantum computing [3, 5]. This tremendous amount of data may be harnessed, with strong processing and learning capabilities, to manage the network at different levels. To this end, quantum computing methods can play a significant enabling role and can provide a guaranteed security platform. Towards provisioning this massive connectivity and efficiently processing the voluminous data available at the user and network sides, quantum-powered computing methods have a strong potential in realising the ambitions of a service-driven, fully intelligent 6G communication network. There is every reason to believe that the integration of quantum technology can improve the throughput, efficiency, and security of 6G networks. In addition to the advantages mentioned above, this technology also has benefits in computing speed, guaranteed security, and minimal storage requirements. This makes it ideally suited for various future quantum communication network applications. Research is needed on many fronts to evaluate the potential opportunities of quantum computing in 6G applications. In 5G, a functional division is operated in both the RAN and core networks to meet the ultra-low latency and ultra-high efficiency requirements of 5G verticals. Notably, RAN functions are split into cloud-deployed services with interfacing capabilities. This new architecture has a significant impact on the efficient implementation of security processes [6]. One of the key challenges in deploying secure 5G networks is analysing how current cryptographic algorithms for secure authentication and data transmission can adapt to provide secure authentication between services and secure data encryption while ensuring that stringent efficiency requirements are met [7]. The powerful parallel processing capability of quantum search algorithms can be leveraged to solve large-scale wireless optimisation problems. (1) Is this ‘beyond 5G?’ This topic is highly exploratory and undoubtedly beyond the boundaries of core 5G R&D. (2) What are the new features and key challenges? Classically, the mutual information between the channel input and output must be maximised. For quantum channels, the capacity must be redefined. Quantum channels can increase the achievable capacity. As a result, error correction without redundancy is possible on noisy channels. Quantum computers can enable exponentially complex combinatorial ML decoding in classical systems [5, 6]. To cope with latency-critical scenarios such as automated cars and medical applications, communication must be accomplished in a concise time. Achieving latency of only a few milliseconds is a real challenge. To achieve low latency and ultra-high reliability, it is essential to develop powerful high-end processors that consume little power. Quantum computing seems to be a reliable solution to this issue [8]. With variable quality of service (QoS) requirements, a variable radio resource must be allocated to the user. This can be of variable bandwidth, variable power, or both. Another challenging aspect of 6G is that with the propagation frequency, the signal can attenuate quickly and have a high penetration loss at high frequencies [9]. The signal is also automatically attenuated when accessing homes, residences, or workplaces. As the frequency increases, radio waves attenuate and may have difficulty penetrating the walls of buildings and homes while affecting users' QoS requirements. Therefore, it is very important to develop stable, fast and accurate quantum algorithms to handle 6G communication requirements by dynamically allocating variable resources [10]. The current 5G standard does not address the issue of quantum computing but relies on traditional cryptography. The development towards cloud and edge native infrastructures is expected to continue in 6G networks. While large-scale quantum computing can be expected to take a longer duration, it is time to prepare for the shift to cryptography that is secure in the post-quantum world. According to current knowledge, contemporary symmetric cryptography remains secure for the most part, even after the advent of quantum computing. Furthermore, authentication by a physical layer signature, such as RF fingerprinting, and some other technologies, such as randomisation of MIMO transmission coefficients, coding, etc., could potentially be used in 6G [5, 11]. Whether it is for the optimisation of heterogeneous resources in 6G networks that result in the solution of ‘NP-complete’ combinatorial problems, for the compensation of non-linear effects of a communication chain or the optimisation of MIMO transmitter pre-coding matrix, future network nodes and devices will have to be equipped with learning and decision-making capabilities through AI and machine learning, so that they autonomously optimise their operation in response to changes in the environment [5]. In this context, the use of optimisation techniques based on quantum computing and AI applied to the field of 6G networks could be of considerable interest. Besides, quantum computing allows NP-hard optimisation problems to be solved in linear time, making it possible to solve and execute network optimisation problems in a much faster time, even in real-time [5, 11]. Regulatory and standardisation work will impact our future technology solutions in 5G networks and beyond. Protecting individual privacy and identity has long been a challenge for standards bodies, as countries have very different perspectives and regulations in this area. International standards bodies such as JTC 1 have committees working on privacy frameworks and are making progress, but there is still much to be done [13]. To conclude, we believe that our readers will find this opinion piece useful in giving an overview of the importance of Quantum Computing/communications in shaping the next communication systems and its security platforms. This is a technology in its infancy and a lot of research remains to be carried out to achieve sustainable solutions and overcome the current challenges. The use of intelligent systems (AI, ML and other techniques) will be essential in achieving solutions faster and providing sustainable outcomes. But IoT devices as well as cloud and edges nodes must be AI-ready and be able to support the use of intelligent algorithms.