March 2023 - news - Mailing lists@ IFISC

IFISC News - Design of a method to prevent the spread of infectious diseases in airports
by ifisc＠ifisc.uib-csic.es 21 Mar '23

21 Mar '23

Design of a method to prevent the spread of infectious diseases in airports CSIC researchers lead the development of a mathematical model that identifies the areas with the highest risk of contagion in means of transport. Implementing disinfection measures in crowded areas of airports, such as bars or restaurants, could reduce the risk of spreading viruses such as SARS-CoV-2. In 2022, more than 61 million people transited through Europe's busiest airport, London Heathrow. That means that, every day, more than 160,000 people from different parts of the world shared the same space. To prevent the first undetected cases of viruses such as SARS-CoV-2 or H1N1 influenza from becoming an epidemiological problem, a study led by the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC, CSIC-UIB) proposes a mathematical model that identifies the areas with the highest risk of contagion in means of transport and provides recommendations to prevent its spread. The results are published in the journal Nature Communications. When a person coughs, speaks, and even breathes, emits small respiratory droplets into the surrounding air. These airborne particles, known as aerosols, can carry viral particles from an infected person. Thus, the relationship between the number of people and the space available is critical when it comes to curbing the spread of contagious diseases. "Close social interactions are critical in the transmission of infectious pathologies, so crowds and crowds are a serious risk for triggering super-propagation events. There are occasions when maintaining interpersonal distance can be a challenge, such as, for example, in transportation hubs," highlights José Javier Ramasco, IFISC researcher who participated in the study. As the researcher points out, "these places are designed to optimize logistical efficiency, not to reduce crowding," so identifying the busiest areas can be key to mitigating the risk of spreading new infectious diseases. According to the study, this objective is achieved through a mathematical model capable of detecting those spaces within the airport most likely to transmit diseases. The researchers applied the new system to study how viruses such as H1N1 flu, SARS-CoV-1 and SARS-CoV-2, which caused the covid-19 pandemic, spread. By analyzing the itineraries of more than 200,000 anonymous individuals, collected at London's Heathrow airport between February and August 2017, they determined the areas with the highest risk of contagion: bars and restaurants. This is caused by connecting many people, in the same place and for long periods of time. "The dangerousness of the areas for contagion arises as a balance between the number of people passing by and the time they stay together. Those places are not always the most crowded, but it takes time in contacts to transmit the disease," Ramasco explains. Once the hot spots of contagion have been identified, it is possible to develop a spatial immunization policy to prevent or reduce the risk of the pathogen spreading beyond the first undetected cases. This would be achieved through the use of ultraviolet rays, surface disinfection or air filtering. In addition, the researchers point out that the method can be applied to control any other uncharacterized pathogen (emerging diseases) and is generalizable to other modes of transport. "It can be used in train stations, subway stations, bus stations or other crowded places where it is not possible to maintain interpersonal distances, such as shopping malls or convention centers," he remarks. The project is the result of an international multidisciplinary collaboration developed within the Plataformas Temáticas Interdisciplinares del CSIC Salud Global i Mobility 2030. Along with IFISC, a joint center of CSIC and the University of the Balearic Islands, the French National Institute of Health and Medical Research (Inserm), the Bruno Kessler Foundation in Italy, and the company Cuebiq Inc, which collects users' locations and integrates them anonymously, have also participated in the project. "Implementing spatial immunization measures in the highest risk areas would help to contain and/or delay the spread of infectious agents in airports around the world, and would be particularly useful in the early stages of a pandemic, when drugs have not yet been developed," the researchers conclude. Mattia Mazzoli et al. Spatial immunization to abate disease spreading in transportation hubs. Nature Communications. DOI: https://doi.org/10.1038/s41467-023-36985-0 CSIC http://ifisc.uib-csic.es/en/news/design-method-prevent-spread-infectious-di…

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IFISC News - IFISC researchers propose a new protocol for data processing with Quantum Reservoir Computing
by ifisc＠ifisc.uib-csic.es 17 Mar '23

17 Mar '23

IFISC researchers propose a new protocol for data processing with Quantum Reservoir Computing Researchers at IFISC (UIB-CSIC) propose a new protocol for processing sequential data using quantum machine learning.The study proposes a way to efficiently include quantum measurement while preserving the quantum advantage that characterises these systems. Researchers at the Institute for Cross-Disciplinary Physics and Complex Systems, IFISC (UIB-CSIC), in Mallorca, propose the first protocol that includes the effect of measurement in the processing of temporal data sequences using quantum systems. Examples of these computational tasks are handwriting recognition or the prediction of chaotic series. The advantage of using quantum systems for these purposes lies in the large processing power provided by the Hilbert space of quantum states, an exponential advantage over classical systems. Moreover, it has now been shown that this advantage can be achieved even in non-ideal situations, where the effect of quantum measurement is taken into account. The implementation of quantum reservoir computing as a computational method for processing time series data has a lot of potential, but faces several challenges. One of them, common to all quantum computing, is that, due to its stochastic nature, it is necessary to repeat the processing of the information several times and to calculate averages with the results obtained in order to improve accuracy. The other problem is that quantum systems are strongly affected by measurements, i.e. the process of obtaining the processed information. In an implementation of quantum reservoir computing this is especially relevant, as it can impair the quality of the processing at different times. To prevent the next steps from being affected by past measurements, the experiment would have to be restarted by reintroducing the data into the system from the beginning, which is clearly inefficient. In addition, it would be necessary to store the data in an external memory. The researchers have analysed different protocols for time series processing, including the rewinding and restarting protocols, and have proposed an alternative based on weak measurements that allows continuous online monitoring of the data without external storing, operating in real time. This online protocol proposed by the researchers, presented in the journal npj Quantum Information, introduces the effect of the measurement on data processing. Typically, weak measurements provide less information and are noisier, but in this way of obtaining processing results the quantum system does not "collapse" as a whole, making it possible to identify situations in which effective data processing is achieved in both accuracy and resources. The study establishes the advantage of quantum reservoirs in realistic scenarios and is expected to pave the way for efficient experimental implementations involving continuous time series processing with quantum systems. In addition, this research may also contribute to the development of concrete applications such as quantum time tomography, quantum recurrent neural networks or quantum neuromorphic computing, among other advances.Image: Schematic of the protocol proposed by the researchers. The measurements of the quantum reservoir that processes the time series are weak, so the quantum system does not "collapse" in its entirety.Mujal, P., Martínez-Peña, R., Giorgi, G.L., Soriano, M.C., Zambrini, R., Time-series quantum reservoir computing with weak and projective measurements. npj Quantum Inf 9, 16 (2023). https://doi.org/10.1038/s41534-023-00682-zEl diari de la UIB http://ifisc.uib-csic.es/en/news/ifisc-researchers-propose-new-protocol-dat…

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IFISC News - Simulation of collective effects between the qubits of a quantum computer
by ifisc＠ifisc.uib-csic.es 10 Mar '23

10 Mar '23

Simulation of collective effects between the qubits of a quantum computer An international team, involving researchers from IFISC (UIB-CSIC) in collaboration with the University of Helsinki, Aalto University and the startup Algorithmiq (Finland), has successfully simulated the collective and dissipative dynamics of two qubits in a real quantum computer. These results may pave the way for quantum simulation of more complex collective dynamics on currently available quantum computers and establish a procedure for comparing the results of quantum simulations with the noise properties of experimental devices. The research represents the first fully quantum digital simulation of dissipative collective effects on a quantum computer.The study, published in the prestigious journal PRX Quantum, consisted of simulating the dynamics of quantum systems with the smallest possible dimension and which form the basis of quantum computing: qubits. By simulating a global bath between two qubits, the researchers were able to see how their emissions interfere, both constructively (superradiance) and destructively (subradiance). These two qubits form a structured quantum system whose dynamics is "open" and "collective". The researchers also studied theoretically and experimentally the properties of the noise and established relationships between its characteristics and the accuracy of the simulation. Current quantum computers are inevitably noisy, constrained by short coherence times. This means that there are strong constraints on the depth of quantum circuits that can be implemented.The concept behind quantum simulation is based on the idea of simulating quantum systems on a controllable physical platform whose dynamics are driven by the laws of quantum mechanics. This makes it possible to explore and obtain solutions to quantum dynamics that would otherwise be impossible to obtain on a classical computer. Controlling these quantum simulations is crucial to understand the properties of noise in real quantum computers and to explore intriguing phenomena such as dissipative quantum phase transitions, quantum synchronization or dissipative time crystals. Furthermore, characterizing the noise in quantum computers can help to understand the limitations of the devices and thus to design possible countermeasures.Image: Schematic of the simulated system. A particle generator (gray) collides a particle with the qubit Q1 (green), then with Q2 (red) and again with Q1. These collisions generate a global interaction represented by the cloud (blue).Cattaneo, Marco, et al. “Quantum Simulation of Dissipative Collective Effects on Noisy Quantum Computers.” PRX Quantum, vol. 4, no. 1, 2023, https://doi.org/10.1103/prxquantum.4.010324. http://ifisc.uib-csic.es/en/news/simulation-collective-effects-between-qubi…

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IFISC News - Analysing how the introduction of renewables affects the electricity grid on islands
by ifisc＠ifisc.uib-csic.es 02 Mar '23

02 Mar '23

Analysing how the introduction of renewables affects the electricity grid on islands A study carried out by IFISC researchers proposes a model that emulates the behaviour of the electricity grid with high renewable production.The researchers used the increase in wind power generation on Gran Canaria as a case study. A new study by IFISC (CSIC-UIB) scientists, developed in the context of the European Project VPP4ISLANDS and published in IEEE Transactions on Sustainable Energy, proposes a model that emulates how the electricity grid behaves when a large amount of variable renewable generation is introduced into it. The researchers validated the model based on current data from Gran Canaria and analysed the increase in the island's wind farm capacity. The frequency of an electricity grid constitutes a good indicator of the balance at any time between electricity generation and consumption demand. In the absence of efficient storage methods, the present scenario is one in which generation is adapted to demand in real time. This poses many technological challenges, especially if the percentage of electricity generated from variable renewable sources such as the sun or wind is to be increased. One of the difficulties in increasing the share of renewable generation is that production depends on environmental factors and is not instantly available whenever it is needed. Knowing how the grid, and specifically its frequency, will respond to an increasing variable renewable generation is key to considering a transition to a more sustainable world. To study how the frequency will behave with these changes, the researchers proposed a model that reproduces the electricity grid in Gran Canaria as a paradigmatic example of an island. In this model, a network is proposed in which each node corresponds to a power plant or substation. The power stations are assumed to have conventional power generation including control capacity. Specifically, in the case of Gran Canaria, they are combined cycle, gas and steam turbines and diesel engines. The model has been validated on the basis of real data on demand, generation and frequency fluctuations. To test how the introduction of renewables would affect the grid stability, the researchers simulated what would happen in a scenario with increased wind generation, i.e. increasing the installed wind farm capacity. In doing so, they observed that fluctuations in grid frequency would be well above the established limits. These limits, regulated by law, exist to ensure the integrity of the infrastructure, which could be damaged if the grid frequency variations exceed a certain value. In such a case, the supply and generation of some parts of the grid would have to be shut down to avoid collapse. In order to reduce frequency variations, the researchers increased the secondary control of conventional plants. In this way, it can be estimated what measures should be taken in a future scenario to prevent an increase in the wind farm from affecting the grid infrastructure. These estimates are made for both summer and winter. In addition to checking what controls would need to be implemented, the model allows checking which transmission lines need to be upgraded or reinforced to be prepared for a scenario with increased wind adoption. The model can be generalized and the authors are working in its application to the case of the Balearic Islands in order to move towards more sustainable electricity generation. M. Martínez-Barbeito, D. Gomila and P. Colet, "Dynamical Model for Power Grid Frequency Fluctuations: Application to Islands with High Penetration of Wind Generation", IEEE Transactions on Sustainable Energy, doi: 10.1109/TSTE.2022.3231975. http://ifisc.uib-csic.es/en/news/analysing-how-introduction-renewables-affe…

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