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News from the Department of Physics.

older | 1 | .... | 7 | 8 | (Page 9)

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  • 07/10/19--23:28: Women in STEM: Holly Pacey
  • My ambition to have a career in physics research began when I was at school. I grew up in Nottingham, where my Dad was the main homemaker and worked from home; and my Mum worked in a hospital pharmacy. I attended my local comprehensive and sixth form before moving to Cambridge to study Natural Sciences at King’s College.

    I spent two summers working in the Cambridge Institute of Astronomy, and this sparked a desire to work in particle physics. After graduating with my MSc, I began working towards a PhD in high energy physics with the ATLAS experiment. What strikes me most about the environment in Cambridge, compared to other institutions, is the atmosphere of collaboration. Improving your understanding of your subject and exploring new and creative research ideas with everyone in the group is always prioritised above rank – there is no such thing as a stupid question here.

    Having the opportunity to work with CERN is incredible. The diversity of people, with a huge range of ideas, all working towards a common goal is very inspiring. The calibre of research at both institutions motivates you to become the best researcher you can, but with enough support that you aren’t overwhelmed.

    On a grand scale, my field is trying to understand what the universe is made of at a fundamental level. We are looking at how the constituent parts – called particles - can interact and combine to take us from the high energy Big Bang to the universe we see today. My research aims to find evidence for new particles in the data taken with the ATLAS detector at the Large Hadron Collider, which would allow our current Standard Model of particle physics to be extended. For example, I have focused on searches for new particles predicted by a model called Supersymmetry, currently the most popular extension to the standard model that could explain phenomena such as dark matter.

    A key moment for me was attending my first ATLAS conference focusing on the collaboration of the different new-physics groups. The many innovative analysis techniques being presented were very interesting and I learned a lot in the plentiful discussions, both about the work I had contributed to the conference and that of others. In the long term, I hope my research will contribute to our understanding of the universe, and lead to an exciting career in academia.

    Part of my research involves reconstructing ‘missing’ particles that ATLAS isn’t designed to detect. These are either neutrinos or new physics particles and measuring them well involves carefully balancing all aspects of the detector. Generally, I spend my days doing data analysis. This can involve using computer simulations of background and signal events, using statistics and techniques like machine learning techniques to optimise where to look in the data to find new physics.

    My most interesting project so far is a new project looking for signs of new physics or behaviour in a data-data comparison of oppositely charged electron-muon events. This idea is very exciting, as a deviation from the Standard Model expectation could be explained by many different new models. It also doesn’t rely on simulated data, which is getting more important now that ATLAS has taken such vast amounts of data that simulation is struggling to keep up computationally.

    If you are passionate about a subject and have the drive to work hard on it then that should speak for itself. There will be challenges in your career whatever you choose to do, but the more women that follow their ambitions into STEM now, the easier it will be for the next generation of aspiring scientists.

    Holly Pacey is a PhD candidate in the High Energy Physics Group based at the Cavendish Laboratory, and works on the ATLAS experiment. She spent the 2017-18 academic year working at CERN in Geneva, which operates the largest particle physics laboratory in the world. 

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  • 08/07/19--23:00: Women in STEM: Dr Anita Faul
  • I think the most fun I’ve probably had at work was when I programmed a movable camera to follow me around the room. I’m a mathematician by training and now work as a Teaching Associate in Scientific Computing, specialising in algorithms. I will soon be starting at the British Antarctic Survey as a Data Scientist, to which I am immensely looking forward to.

    Artificial Intelligence and Machine Learning are very popular now. These are also algorithms, with the difference that often the numbers are interpreted as probabilities. So computers do not necessarily give an exact answer, but the answer that is the most probable in some setting.  Computer vision has developed a lot in recent years. I've also worked in industry on various applications and particularly enjoy making connections between different fields. The challenge is to express the problem in mathematical terms. Then it can be tackled by algorithms.

    With human learning, experiences change how we interpret our world. A levitation act will not fascinate a small child if it has not learned about gravity yet. Once it knows about gravity, it does seem to like throwing things down again and again, as any frustrated parent will tell you!  Similarly, machine learning lets the computer have experiences in the form of data - lots and lots of data. While a human child can distinguish between a cat and a dog after seeing a few examples, a computer needs far more.

    The most important question is not how a computer arrives at a result, but why. Deep neural networks have had great success lately. However, their structure is so complex that a human cannot understand how they arrived at their answer. How can we then trust the answer? This can also lead to computers being easily fooled where a human would not be. This is something else that we don’t yet understand why. I'm interested in developing algorithms which are self-improving, learning from new data.

    The students are my teachers. They ask interesting, challenging questions. It is best to be open, if I do not know the answer, and go on a journey of discovery together. I might not know it, but I surely will find out. Students learn in different ways and I enjoy the challenge to find ways to make a topic accessible. Artificial intelligence makes the headlines often enough to be able to remain topical.

    Collaborations are easy if one is willing. A lot of high tech companies working in this field have settled in Cambridge or have opened offices here. Additionally, exciting research is conducted in many departments across Cambridge using machine learning techniques. I enjoy pointing these out to the students who can then see what they have learned in action. 

    Have a go, you never know what you might achieve. When I was 15, I took part in a maths competition aimed at pupils two years above me at school, since my brother took part. I placed higher than him. He bore it gracefully. For me, it was a start to more and more opportunities opening up. If you do not try, you cannot succeed. Yes, there is failure, but then one readjusts and carries on. Lately, I have become more interested in post-graduate education in general, policies and procedures, funding and finances. The information is too dispersed, especially for those considering a post-graduate degree. I'm working on linking different sources of information. 

    Dr Anita Faul is a Teaching Associate at the Cavendish Laboratory and a Fellow of Selwyn College, where she specialises in algorithms. Here, she tells us about what it's like to teach at Cambridge and whether we can trust the answers that computers give us. 

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    The material, developed by researchers from the University of Cambridge, is made of tiny particles of gold coated in a polymer shell, and then squeezed into microdroplets of water in oil. When exposed to heat or light, the particles stick together, changing the colour of the material. The results are reported in the journal Advanced Optical Materials.

    In nature, animals such as chameleons and cuttlefish are able to change colour thanks to chromatophores: skin cells with contractile fibres that move pigments around. The pigments are spread out to show their colour, or squeezed together to make the cell clear.

    The artificial chromatophores developed by the Cambridge researchers are built on the same principle, but instead of contractile fibres, their colour-changing abilities rely on light-powered nano-mechanisms, and the ‘cells’ are microscopic drops of water.

    When the material is heated above 32C, the nanoparticles store large amounts of elastic energy in a fraction of a second, as the polymer coatings expel all the water and collapse. This has the effect of forcing the nanoparticles to bind together into tight clusters. When the material is cooled, the polymers take on water and expand, and the gold nanoparticles are strongly and quickly pushed apart, like a spring.

    “Loading the nanoparticles into the microdroplets allows us to control the shape and size of the clusters, giving us dramatic colour changes,” said Dr Andrew Salmon from Cambridge’s Cavendish Laboratory, the study’s co-first author.

    The geometry of the nanoparticles when they bind into clusters determines which colour they appear as: when the nanoparticles are spread apart they are red and when they cluster together they are dark blue. However, the droplets of water also compress the particle clusters, causing them to shadow each other and make the clustered state nearly transparent.

    At the moment, the material developed by the Cambridge researchers is in a single layer, so is only able to change to a single colour. However, different nanoparticle materials and shapes could be used in extra layers to make a fully dynamic material, like real chameleon skin.

    The researchers also observed that the artificial cells can ‘swim’ in simple ways, similar to the algae Volvox. Shining a light on one edge of the droplets causes the surface to peel towards the light, pushing it forward. Under stronger illumination, high pressure bubbles briefly form to push the droplets along a surface.

    “This work is a big advance in using nanoscale technology to do biomimicry,” said co-author Sean Cormier. “We’re now working to replicate this on roll-to-roll films so that we can make metres of colour changing sheets. Using structured light we also plan to use the light-triggered swimming to ‘herd’ droplets. It will be really exciting to see what collective behaviours are generated.”

    The research was funded by the European Research Council (ERC) and the Engineering and Physical Sciences Research Council (EPSRC).

    Reference:
    Andrew R Salmon et al. ‘Motile Artificial Chromatophores: Light-Triggered Nanoparticles for Microdroplet Locomotion and Color Change.’ Advanced Optical Materials (2019). DOI: 10.1002/adom.201900951

    Researchers have developed artificial ‘chameleon skin’ that changes colour when exposed to light and could be used in applications such as active camouflage and large-scale dynamic displays.

    This work is a big advance in using nanoscale technology to do biomimicry
    Sean Cormier

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  • 08/28/19--23:00: Women in STEM: Verity Allan
  • I came to Cambridge from a town in the Midlands to study Anglo-Saxon, Norse and Celtic. My parents were the first in their families to go to university, and I was the first in my extended family to get an Oxbridge degree. I then tried to get a doctorate from Oxford, but this didn't go to plan - I eventually left with an MLitt and an urgent need to get a job.

    While job hunting I realised that the really interesting jobs required a numerate degree. So, I enrolled at The Open University to study Computing and Mathematical Sciences. I graduated with a First Class Honours degree five years later. While I was studying I got my first job in tech, doing tech support and technical writing for CARET, a technology innovation unit within Cambridge University. I then expanded my range and starting to do technical management work and software testing, before I moved on to my current job.

    Retraining is totally a thing. It's not as easy to do as it was when I did it as a result of the changes to funding and costs for part-time degrees. However, there are now a whole bunch of MOOCs out there, some of which offer qualifications at a more reasonable fee. But retraining opens a whole lot of opportunities in fields where you're likely to find some really interesting questions to work on or interesting projects to support. There are a lot of jobs in science that need project management and communications experience but that don't require you to do top-level research.

    I’m now part of the group writing software for Square Kilometre Array (SKA) project. This will be the world’s largest radio telescope, and I’m part of the team that is designing the supercomputer to do data processing for it. We are producing an architecture for this computer, and testing whether this architecture will work by writing and running prototype code. I get to work with people all over the world.

    This is a very interesting project to work on - it is stretching the limits of what a radio telescope can do. It's also exploring the limits of what can be done computationally; it requires a completely new way of dealing with astronomy data because there's just so much of it. I also do research as part of my PhD, which is aimed at providing astronomy researchers with a tool-kit for interacting with the ridiculous amounts of data that will be produced by the SKA and other next-generation telescopes.

    My work is pretty varied. It involves some research, some programming, some technical project management; and maintaining the collaborative tools used by the project I work on. I also maintain the wiki, the ticket tracking system (we use this so we have some way of recording what work needs to be done), and manage the code repositories for the project. (These days, I delegate a lot of this.) I also managed the formal documentation for the Science Data Processor (SDP) project. As I've learned more, I started chairing technical meetings - I did the project management for the SDP architecture work, and for one of the key software components of the SDP. This involves tracking work, helping people fix problems, note-taking, and helping people work out what's going well and what's not. As part of the architecture team, I also read our documentation, to ensure it makes sense and check that it says what we think it says. As the project has developed, I’ve done more programming and policy development. I go fairly often to the headquarters of the SKA at Jodrell Bank in Cheshire. I've also travelled to South Africa (where one of the SKA telescopes will be built), and to the Netherlands and Malta for SDP Conferences.

    I have an ‘academic-related’ support position, but I'm also doing a PhD as part of my job. This involves a lot of meetings, usually teleconferences, a lot of email, and a lot of writing (because if you don't write something down in an international project, it doesn't exist). Cambridge is a great place to be doing my PhD work, because I'm part of an active community of scholars working in my field, and in adjacent areas. The University leads the work on the supercomputer for the SKA, so we are a hub for a lot of international activity. The University also has a Top 100 supercomputer, so I have access to world-leading infrastructure for my work, as well as a specialist platform developed for the SKA, P3-Alaska.

    At the start of my PhD I visited Lord's Bridge, the location of the Mullard Radio Astronomy Observatory, with other first year PhD students. This is a fascinating site - there are traces all around of how the site was used as an ammunition store during the Second World War. Since the war, it's been used as a radio astronomy observatory, and you can see parts of several radio telescopes that had key roles in understanding the radio sky, winning Nobel Prizes in the process. (You can see the remains of the array that Dame Jocelyn Bell Burnell used to discover pulsars.) Now the site is used primarily as a testbed for new technology for radio telescopes - there are test antennas there for the HERA project, and for the SKA. But you can see dishes and equipment that describe the history of radio astronomy and interferometry. As a personal project, I’m also finding out about the women who were “computers” in the Cavendish Laboratory, and the programming techniques they used.

    Being diagnosed with a serious stress-related health condition meant I had to learn how to refactor my life to allow me to do what I want to do. This is a big part of my life that required major work to come to terms with. There are many compromises I have had to make in order to recover and be able to work full time. This includes discovering new things that can make my condition worse, and finding new ways to manage that. I rely on the support of my line manager to help keep things ticking over OK. 

    It’s important to be aware that in physics, computing, and mathematics, at the moment, women will have to get used to being in a minority. I am quite often the only woman or non-binary person in the room - this is something that's changing, but it is currently the case. This is compounded if you’re also a member of another marginalised group. However, there are lots of networks you can join in order to deal with the sensation of being outnumbered. Finally, just because you're finding the maths or science difficult doesn't mean that you're no good at it. Often, it will be hard, but as you work further, stuff that was previously hard will become quite easy to use. You don't have to understand this stuff instantly to be able to make a useful contribution.

     

     

    Verity Allan is a graduate of Cambridge, Oxford, and The Open University. She is a PhD candidate at the Cavendish Laboratory and works as a project manager and programmer on the software for the Square Kilometre Array, the world's largest radio telescope.

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    University of Cambridge researchers have shown that an algorithm can predict the outcomes of complex chemical reactions with over 90% accuracy, outperforming trained chemists. The algorithm also shows chemists how to make target compounds, providing the chemical ‘map’ to the desired destination. The results are reported in two studies in the journals ACS Central Science and Chemical Communications.                                            

    A central challenge in drug discovery and materials science is finding ways to make complicated organic molecules by chemically joining together simpler building blocks. The problem is that those building blocks often react in unexpected ways.

    “Making molecules is often described as an art realised with trial-and-error experimentation because our understanding of chemical reactivity is far from complete,” said Dr Alpha Lee from Cambridge’s Cavendish Laboratory, who led the studies. “Machine learning algorithms can have a better understanding of chemistry because they distil patterns of reactivity from millions of published chemical reactions, something that a chemist cannot do.”                                                                                                                                             

    The algorithm developed by Lee and his group uses tools in pattern recognition to recognise how chemical groups in molecules react, by training the model on millions of reactions published in patents.

    The researchers looked at chemical reaction prediction as a machine translation problem. The reacting molecules are considered as one ‘language,’ while the product is considered as a different language. The model then uses the patterns in the text to learn how to ‘translate’ between the two languages.

    Using this approach, the model achieves 90% accuracy in predicting the correct product of unseen chemical reactions, whereas the accuracy of trained human chemists is around 80%. The researchers say that the model is accurate enough to detect errors in the data and correctly predict a plethora of difficult reactions.

    The model also knows what it doesn’t know. It produces an uncertainty score, which eliminates incorrect predictions with 89% accuracy. As experiments are time-consuming, accurate prediction is crucial to avoid pursuing expensive experimental pathways that eventually end in failure.

    In the second study, Lee and his group, collaborating with the biopharmaceutical company Pfizer, demonstrated the practical potential of the method in drug discovery.

    The researchers showed that when trained on published chemistry research, the model can make accurate predictions of reactions based on lab notebooks, showing that the model has learned the rules of chemistry and can apply it to drug discovery settings.

    The team also showed that the model can predict sequences of reactions that would lead to a desired product. They applied this methodology to diverse drug-like molecules, showing that the steps that it predicts are chemically reasonable. This technology can significantly reduce the time of preclinical drug discovery because it provides medicinal chemists with a blueprint of where to begin.

    “Our platform is like a GPS for chemistry,” said Lee, who is also a Research Fellow at St Catharine’s College. “It informs chemists whether a reaction is a go or a no-go, and how to navigate reaction routes to make a new molecule.”

    The Cambridge researchers are currently using this reaction prediction technology to develop a complete platform that bridges the design-make-test cycle in drug discovery and materials discovery: predicting promising bioactive molecules, ways to make those complex organic molecules, and selecting the experiments that are the most informative. The researchers are now working on extracting chemical insights from the model, attempting to understand what it has learned that humans have not.

    “We can potentially make a lot of progress in chemistry if we learn what kinds of patterns the model is looking at to make a prediction,” said Peter Bolgar, a PhD student in synthetic organic chemistry involved in both studies. “The model and human chemists together would become extremely powerful in designing experiments, more than each would be without the other.”

    The research was supported by the Winton Programme for the Physics of Sustainability and the Herchel Smith Fund.

    References:
    Philippe Schwaller et al. ‘Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction.’ ACS Central Science (2019). DOI: 10.1021/acscentsci.9b00576

    Alpha Lee et al. ‘Molecular Transformer unifies reaction prediction and retrosynthesis across pharma chemical space.’ Chemical Communications (2019). DOI: 10.1039/C9CC05122H

     

    Researchers have designed a machine learning algorithm that predicts the outcome of chemical reactions with much higher accuracy than trained chemists and suggests ways to make complex molecules, removing a significant hurdle in drug discovery.

    Our platform is like a GPS for chemistry
    Alpha Lee
    Background abstract line

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    They will explore how emerging technologies like those underpinning genomics, AI, clean energy, and smart cities can be used and regulated to create a more equitable and sustainable global community as well as how to encourage sustainable leadership across disciplines and move beyond traditional diplomacy to address global challenges like climate change and social inequalities.

    Shaping Horizons 2019 is a Summit and Action Programme rooted in science, policy, and innovation and will strengthen ties and build relationships between young Future Leaders and Senior Leaders from the UK and Latin America. The delegates have been selected from across academia, industry, and government.

    Prof. David Cardwell, FREng, Pro-Vice-Chancellor for Strategy and Planning at the University of Cambridge, welcomed delegates at the start of the Summit on behalf of the University.

    “On every front, the University has been and continues to be engaged with Latin America, including the pleasure of hosting this fantastic summit, Shaping Horizons, where the mission is to empower and promote youth, create networks and to drive change,” Cardwell said.

    The week will culminate with the Future Leaders pitching for prize money to support their own innovative social impact projects they have developed through mentorship and learning during the Summit.

    Winners will be supported in further developing and launching their projects through the Action Programme which will follow on from the Summit.

      

    Nigel Baker, OBE MVO, Head of the Latin America Department at the Foreign and Commonwealth Office told delegates that all their ideas would help shape the future.

    “Shaping Horizons is absolutely driven by the sense of entrepreneurship, innovation, and ideas of the young people involved. It is going to be fascinating to see the proposals that are coming out,” Baker said.

    “There are 24 different teams and there are going to be some spectacular proposals and ideas. Some will win prizes, some will not, but I suspect that all of those ideas are going to be applicable in the future.”

    Shaping Horizons is a non-profit initiative organised at the University of Cambridge with the support of the Office of Postdoctoral Affairs, and the Cambridge Hub of Global Shapers Community, which is an initiative of the World Economic Forum.

    Shaping Horizons was founded by Dr. Matias Acosta, a UK-Canada Fellow at the Centre for Science and Policy, and Theo Lundberg, a NanoDTC PhD Student in the Department of Physics.

    “Shaping Horizons was founded to promote sustainability using global, cross-disciplinary cooperation as our driving force,” Acosta said.

    “We are a team of 40 undergraduates and academics from across more than 20 departments from the University of Cambridge bringing this initiative forward. Our goal is to build a shared and sustainable future between Latin America and the UK.

    "We will be providing more than £30,000 in support for cooperative bilateral projects and also have designed a continuous mentorship programme to maximize the chance of success of each of the ideas.”

    More than 100 future leaders from the UK and Latin America have gathered at the University of Cambridge to discuss the future of work and education in an increasingly global digital era at this year’s Shaping Horizons summit.

    Shaping Horizons was founded to promote sustainability using global, cross-disciplinary cooperation as our driving force
    Shaping Horizons founder Dr. Matias Acosta

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    Weather board at Cambridge University Botanic Garden showing data for 25 July 2019

    In July this year, staff at the Cambridge University Botanic Garden registered the United Kingdom’s highest ever temperature: 38.7° C. Temperatures in the glasshouses rose to an unbearable 45° C. It is clear that far from being a unique occurrence, this is part of an evolving pattern. It is widely agreed that in the future we will have to contend with increasingly frequent extreme weather events. Climate change is real, and it is happening here and now.

    Today sees the beginning of a global week of action on climate change. Around the world, schoolchildren, parents, teachers, environmental campaigners and concerned citizens will be gathering to raise awareness of the dangers posed by climate change. Here in Cambridge, and with the University’s full support, students and members of staff will be among the demonstrators urging policy-makers to heed the advice of the scientific community.

    Part of our responsibility as a globally influential academic institution is to take a leading role in helping our society move towards a sustainable future. As young people take to the streets, it is worth reflecting on what the University of Cambridge is doing to mitigate the environmental threat.

    Cambridge chemists and physicists are developing next-generation batteries and solar cells – both of which are vital in the transition to a low-carbon economy. Our engineers are supporting the delivery of electric forms of transport that will be essential for the UK to meet its decarbonisation targets. The Cambridge Creative Circular Plastics Centre is developing methods to eliminate plastic waste.

    Flood defences

    From working with local communities to improve flood defences along the eastern coast, or alerting us to the increased pace of melting glaciers, to identifying populations who are most likely to shoulder the burden of climate change, our researchers are already deeply invested in helping us better understand the multifaceted nature of the challenge.

    Our researchers are not only developing greener fuels, better technologies and more sustainable materials, but addressing all aspects of a zero-carbon future: the impact it will have on what we eat, how we work, how we travel, the way we communicate, how we measure economic progress and the way our societies are organised. Crucially, they are producing the knowledge to ensure that policy decisions are based on the best available evidence.

    These academic efforts – arguably the greatest contribution we can make to tackling climate change – are backed up by action within the University itself, as we continue to implement the recommendations made by the Divestment Working Group in 2018.

    We are leading by example, and demonstrating what is achievable. Our Sustainable Food Policy, launched in 2016, has already reduced food-related carbon emissions from our catering service by a third, and has been widely held up as an example for large institutions.

     

    More recently, Cambridge became the first university in the world to announce that it has adopted a science-based target for decarbonisation, committing itself to a 75% decrease of its 2015 energy-related carbon emissions by 2030, and to reducing them to absolute zero by 2048. We are working with local authorities to plan a future that offers staff practical and affordable ways of travelling sustainably to and from work. Through our Green Impact programmewe will be seeking ideas from students and staff on how we can accelerate our decarbonisation.

    New initiative

    Later this term, we will be formally launching a major new initiative, led by Dr Emily Shuckburgh, harnessing the full breadth of the University’s research and teaching capabilities to respond to climate change and support the transition to a sustainable future, both in the UK and globally.  

    The new initiative will develop a bold programme of education, research, demonstration projects and knowledge exchange focused on supporting a zero carbon world. Its ambition is to generate and disseminate the ideas and innovations that will shape our future – and to equip a future generation of leaders with the skills to navigate the global challenges of the coming decades.

    It is being launched only a few months after the UK became the first major world economy to legislate for net zero emissions. Eliminating greenhouse gas emissions by 2050 will mean a fundamental change over the coming decades in all aspects of our economy, including how we generate energy, and how we build decarbonisation into policy and investment.

    Through the initiative we will engage in active collaboration with other universities and research institutes in the UK and beyond, including the newly established Global Universities Alliance on Climate.

    Unite behind the science

    As the world’s leaders gather in Chile later this year for the latest round of climate change talks, the University will be decisively setting out its stall to demonstrate how it contributes to tackling this most pressing of global challenges.

    I am encouraged by the younger generations’ determination to make their voices heard on the key issue of climate change. I am especially struck by the rallying cry from that remarkable activist, Greta Thunberg, to “unite behind the science”, and to put “the best available science [at] the heart of politics”.

    That is exactly what Cambridge is determined to do – not only on this day of climate action, or even this week, but for the long term.

    The Vice-Chancellor, Professor Stephen J Toope kicks off a global day of action with a discussion on the University’s efforts to tackle climate change.

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    The international team, including researchers from the University of Cambridge, sent high-frequency sound waves across a modified semiconductor device to direct the behaviour of a single electron, with efficiencies in excess of 99%. The results are reported in the journal Nature Communications.

    A quantum computer would be able to solve previously unsolvable computational problems by taking advantage of the strange behaviour of particles at the subatomic scale, and quantum phenomena such as entanglement and superposition. However, precisely controlling the behaviour of quantum particles is a mammoth task.

    “What would make a quantum computer so powerful is its ability to scale exponentially,” said co-author Hugo Lepage, a PhD candidate in Cambridge’s Cavendish Laboratory, who performed the theoretical work for the current study. “In a classical computer, to double the amount of information you have to double the number of bits. But in a quantum computer, you’d only need to add one more quantum bit, or qubit, to double the information.”

    Last month, researchers from Google claimed to have reached ‘quantum supremacy’, the point at which a quantum computer can perform calculations beyond the capacity of the most powerful supercomputers. However, the quantum computers which Google, IBM and others are developing are based on superconducting loops, which are complex circuits and, like all quantum systems, are highly fragile.

    “The smallest fluctuation or deviation will corrupt the quantum information contained in the phases and currents of the loops,” said Lepage. “This is still very new technology and expansion beyond the intermediate scale may require us to go down to the single particle level.”

    Instead of superconducting loops, the quantum information in the quantum computer Lepage and his colleagues are devising use the ‘spin’ of an electron – its inherent angular momentum, which can be up or down – to store quantum information.

    “Harnessing spin to power a functioning quantum computer is a more scalable approach than using superconductivity, and we believe that using spin could lead to a quantum computer which is far more robust, since spin interactions are set by the laws of nature,” said Lepage.

    Using spin allows the quantum information to be more easily integrated with existing systems. The device developed in the current work is based on widely-used semiconductors with some minor modifications.

    The device, which was tested experimentally by Lepage’s co-authors from the Institut Néel, measures just a few millionths of a metre long. The researchers laid metallic gates over a semiconductor and applied a voltage, which generated a complex electric field. The researchers then directed high-frequency sound waves over the device, causing it to vibrate and distort, like a tiny earthquake. As the sound waves propagate, they trap the electrons, pushing them through the device in a very precise way, as if the electrons are ‘surfing’ on the sound waves.

    The researchers were able to control the behaviour of a single electron with 99.5% efficiency. “To control a single electron in this way is already difficult, but to get to a point where we can have a working quantum computer, we need to be able to control multiple electrons, which get exponentially more difficult as the qubits start to interact with each other,” said Lepage.

    In the coming months, the researchers will begin testing the device with multiple electrons, which would bring a working quantum computer another step closer.

    The research was funded in part by the European Union’s Horizon 2020 programme.

    Reference:
    Shintaro Takada et al. ‘Sound-driven single-electron transfer in a circuit of coupled quantum rails.’ Nature Communications (2019). DOI:10.1038/s41467-019-12514-w

     

    Researchers have successfully used sound waves to control quantum information in a single electron, a significant step towards efficient, robust quantum computers made from semiconductors.

    We believe that using spin could lead to a quantum computer which is far more robust, since spin interactions are set by the laws of nature
    Hugo Lepage
    3D render of the semiconductor nanostructure

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