We are used to the idea that in medicine, simple fixes often come with side effects. Taking pain relief for a headache, for example, can leave you drowsy. Now it turns out that a similar principle applies to quantum error correction (QEC). Although QEC protocols are designed to keep quantum devices accurate by eliminating the headache of environmental noise, researchers at ETH Zurich in Switzerland and the Massachusetts Institute of Technology (MIT) in the US have shown that QEC can also introduce bias into the output of quantum sensors. In their analysis, the researchers recommend remedies for this side effect that could prove important in developing commercial quantum sensors for navigation and environmental surveys, among other applications.
Quantum sensors are often better than their classical counterparts at detecting electric or magnetic fields or measuring quantities such as temperature and pressure. However, there is a trade-off: the same quantum effects that give these devices their sensitivity are also very easily destroyed by the equivalent of a crackle in your headphones or glitches on the edges of your computer screen. Because environmental noise can render a quantum sensor’s output inaccurate, QEC protocols are formulated to cancel it out at every step of the sensing process. Each time the sensor performs some action to detect the quantity of interest, the protocol corrects the resulting signal before the next detection occurs – a bit like a sailor correcting a ship’s course as it moves through choppy waters that push it in random directions.
Delayed correction
Crucially, for any realistic quantum sensor, this “steering” cannot happen immediately after the ship starts to veer off. Instead, there is a small delay between the error and the correction, explains Florentin Reiter, a physicist at ETH and the co-author of a study in Physical Review Letters describing the research.
“In the early days of quantum error correction, you simply assumed to have perfect error correction, but that’s just not realistically going to happen. That’s not what we have now,” Reiter says. With sensors based on extremely cold atoms that are controlled by laser light, for instance, Reiter explains that perfect error correction would require those lasers to be infinitely powerful. “QEC is actually being experimentally realized now so we have to be more realistic about it,” he observes.
Quntao Zhuang, a physicist at the University of Arizona, US who was not involved in the study, agrees that we need more realistic and nuanced theoretical models of error correction to fully understand how to make quantum sensors most accurate. “This work explores a problem that was overlooked in the past,” he says. “When you do error correction with operations that have a finite speed, there will be some side effects on how well you can estimate parameters in the system [where sensing is being done].”
Biased measurements
The side effect Reiter and collaborators identified was a consistent bias of the sensor’s output, analogous to a ship tending to drift in the direction of the current. This bias means that all the sensor’s readings will be somewhat inaccurate, and perhaps even unrealistic. What is more, the bias could lead to overly optimistic estimates for the minimum signal the sensor can detect in the first place.
The specific case that Reiter and colleagues considered in their study involved implementing QEC into a procedure for detecting an electromagnetic signal using a system of many identical quantum bits (qubits). However, in the study they demonstrated that their conclusions are true for quantum sensors very generally. Put simply, “when you use error correction, you have to take care of the bias that comes from finite corrections,” says Ivan Rojkov, a PhD student at ETH and the study’s lead author.
The team’s work also contains suggestions for how this side effect of realistic QEC could be remedied. Namely, researchers could anticipate the QEC-induced bias and account for it from the get-go. “If you have full information about how fast you correct and how strong the noise in your system is, you can determine the strength of your error and sort of have a re-calibration of the sensor,” Rojkov explains.
While Zhuang points out that implementing error correction in quantum sensors is technically challenging in the near term, and comparable to the task of developing small-scale quantum computing, the ETH-MIT team is optimistic about the impact the work may have in the future. Reiter says that the combination of QEC and bias correction could help physicists push their already extremely precise devices (atomic clocks, for instance, can measure time with an accuracy of 10-15 s) even further. And with several start-ups working to commercialize this technology for applications in navigation, the need for a detailed understanding of quantum effects and quantum information protocols transcends academic research – though Reiter underlines that the new work is relevant for fundamental physics, too. “You could measure tiny relativistic effects and potentially gain better insight into the nature of the universe as given by the most precise values of fundamental constants,” he suggests.
Under a microscope, bacteria appear to wriggle and wobble to get to where they need to go. These bizarre motions are nevertheless effective: every second, a bacterium can swim tens of times the length of its body, the equivalent of a human swimming faster than 20 metres per second. Incredibly, in fluids such as those lining the lungs and stomach, bacteria can swim even faster. In fact, the “messier” the fluid, the straighter and faster bacteria travel. After decades of research, the physics of this phenomenon is still under debate.
How bacteria swim in fluids…maybe
Bacteria are single-celled organisms a few thousandths of a millimetre in size. To swim in fluids, they rely on flagella, flexible helical filaments that are connected to “motors” anchored to the cell surface. The thrust generated when the motors turn propels the bacteria forward. When all the motors are synchronized, the flagella appear as a single bundle that rotates uniformly. To balance this rotation, the bacteria’s cell body rotates, too. Imprecise alignments between the motion of the cell body and the flagellar bundle result in the helical, corkscrew-like trajectory seen as “wobbling” under a microscope.
This bacterial swimming looks different depending upon the fluid in which the bacteria are immersed. In complex fluids, such as those lining some organs, bacteria swim much faster than in simple fluids such as water – an observation that has intrigued scientists for over sixty years.
“Previous studies have shown that bacteria swim faster in polymer solutions of low concentrations than in pure water. But exactly why they show such an unusual behaviour was not known,” says Xiang Cheng, from the University of Minnesota.
Theories put forth to date about how bacteria swim in complex fluids focused on the dynamics introduced by the presence of polymers (molecules made by linking many small units together to form larger molecules). Yet, a new study finds similar enhanced bacterial swimming behaviours in the presence of colloids, polymers that are distributed evenly throughout a fluid.
A new model for bacteria swimming
The study, published in Nature, is the result of a collaboration between Cheng’s team and scientists at Beijing Computational Science Research Centre and Beijing Normal University. The researchers analysed how individual bacteria swim by studying low concentrations of fluorescently tagged E. coli injected in a colloid solution (at high concentrations, bacteria such as E. coli show collective swimming, like bird flocking or fish schooling, that changes swimming behaviours). The team noted seven features, such as swimming speed and tumbling rates, that agreed with bacterial swimming behaviours observed in polymer solutions and concluded that dynamics induced by the presence of polymers alone cannot explain why bacteria travel faster in complex liquids.
The researchers realized that each particle, whether a colloid or a polymer, appears as a solid surface to a travelling bacterium. Bumping into the surface of an object induces a torque, bending the flagella and decreasing the misalignment between the flagellar bundle and the cell body, resulting in straighter, faster swimming overall. To combine their experimental results mathematically, the researchers then developed a mathematical model of bacterial swimming. Their parameter-free model introduces a new way to think about bacterial swimming by combining the rigid-body rotation of the bacteria with the angular velocity of the cell body.
Cheng says that while micro-organism movements are relevant to many microbiological processes, such as disease infection, fertility and reproduction, and ecosystem health, his motivation for engaging in this field of research is a passion for how small swimmers such as bacteria live in their natural environments.
“I am simply interested in how such a small creature swims and moves around in their normal life,” he says.
Fortunately – for Cheng at least – this study is not the last word on bacterial swimming. His team is now investigating how bacteria behave in the presence of high concentrations of colloids and how bacteria interact with large solid boundaries.
The German philosopher Friedrich Nietzsche once proposed a terrifying thought experiment. Suppose, some lonesome night, a demon whispers in your ear and says you’ll have to live your life over and over again – each time in precisely the same way as before. “Every pain and every joy and every thought and sigh and everything unutterably small or great in your life will have to return to you,” Nietzsche warned, “all in the same succession and sequence.”
Given that you’ll be continually re-living your life, you need to be extremely careful about how you react. That’s because the demon imagined by Nietzsche, which appeared in his 1882 book The Gay Science, is effectively forcing you to take full responsibility for your life. So do you run away from this little beast or cry out, “Bring it on!”
Demons like Nietzsche’s have played a long and important role in literature, philosophy and science. Another famous example can be found in Meditations on First Philosophy, a book by the 17th-century French scientist and philosopher René Descartes. He invited the reader to imagine a demon who sought to cloak you in such a perfect simulation that you’d be deceived into mistaking it for reality. Could the demon, Descartes wondered, fool you completely and forever?
It was a question that worried Descartes: if we’re all being fooled, how can we prove that science is really telling us truths about the world? Could it be that science is telling us only about the illusions created by the demon? The good news, according to Descartes, is that we can thwart that demon, for even a demon can’t force a conscientious thinker to say “I do not exist” and really believe it. And once that truth is established, more and more truths unfold from it until – eventually – your confidence in the validity of science is restored.
But Nietzsche’s demon still haunts us with the horrifying thought – which surfaces now and then in science fiction – that time might repeat over and over again in a loop. Descartes’ demon, meanwhile, has spawned generations of descendants from the Matrix movies to “brain-in-a-vat” thought experiments, in which a person’s mind is removed from their body and hooked up to a computer that perfectly simulates the outside world. In The Matrix, one escapes the simulation by swallowing a red pill; for Descartes it requires philosophical reasoning.
Red pill blue pill The Matrix films are descended from Descartes’ demon, a thought experiment about living in a simulation so perfect it cannot be distinguished from reality. In the movies, swallowing a red pill offers an escape back to the supposed real world. (Courtesy: Shutterstock/diy13)
Descartes’ demon has also inspired the philosopher David Chalmers’ recent and provocative book Reality+: Virtual Worlds and the Problems of Philosophy (Allen Lane, 2022). Based at New York University in the US, Chalmers argues that we already pretty much live in virtual reality and that there is no significant difference between it and everyday reality.
In these and other thought experiments, demons are just imaginary beings. Still, they are powerful, insightful and can manipulate anything (or almost anything); you engage with them or ignore them at your peril.
Why demons matter
In some ways, the history of demons offers a particular insight into the history of Western culture. That’s why I have been working with Elyse Graham – a colleague of mine in the English department at Stony Brook University in the US – to create a course for our undergraduates both in the humanities and in the sciences, in which we let demons do the teaching. Graham and I were inspired to develop the course, which we’re calling “Demons to think with”, after reading Jimena Canales’ superb book Bedeviled: a Shadow History of Demons in Science (Princeton University Press, 2020).
Canales, who is a science historian at the University of Illinois, was aware that demons feature in numerous books by novelists, priests and anthropologists about things like black magic, the supernatural and primitive cultures. She also knew that demons threaten us with eternal recurrence, saturate us with fake facts, and can even physically make our computers crash. But what really surprised Canales was how often demons turn up in respected academic journals working alongside scientists like James Clerk Maxwell, Charles Darwin, Albert Einstein, Richard Feynman and others.
Demons are found throughout physics – whether trying to overthrow the fundamentals of thermodynamics, expose the incompleteness of quantum mechanics, or mess with a variety of other natural laws
Demons, in fact, are found throughout physics – whether trying to overthrow the fundamentals of thermodynamics, expose the incompleteness of quantum mechanics, or mess with a variety of other natural laws. Some demons fiddle with atoms. Others un-conserve energy. There are demons travelling at the speed of light, or establishing the exact position and momentum of elementary particles, or seeking to carry out other feats that theorists have declared impossible. Sometimes these demons are successful at it, sometimes not.
After reading Canales’s book, Graham and I realized that demons would make terrific undergraduate instructors. Witty, rebellious and charismatic, they would captivate students and be able to instruct them in a variety of topics while delivering important ethical lessons. In our course at Stony Brook, I will deal with the demons that physically inhabit the real world, while Graham, who has a PhD in digital humanities and a background in computer security, will discuss the demons that dwell virtually in computers (see box below).
Demons to think with – a new kind of university course
(Courtesy: iStock/bymuratdeniz)
The course on demons that Elyse Graham and I are developing at Stony Brook University promises to be unique in appealing to science and humanities students alike. While I will be managing the metaphysical demons, Graham will be corralling the physical ones that lurk in software and computer systems. Often known to computer geeks as “daimons”, this race of super-demons has been created through the growth of artificial intelligence (AI). Smarter than humans, these demons can learn and even assign themselves tasks.
Created by hackers and software designers, scientists and spies, these demons lurk in the background, waiting for the right moment to pop up and do something beneficial or harmful, before dropping out of sight again. So whereas literary demons are fictions, and philosophical or scientific demons are thought experiments, these computer demons actually do things using software and IT. These demons won’t go away: better computing will simply yield yet more powerful versions of them.
Graham’s part of the course is project-based. Students will write code to create demons of different kinds and understand how they work. She will not try to teach students to create Cartesian deceivers, Nietzschean provocateurs, Maxwellian midget manipulators or the like. Rather, she will teach students enough coding – in Python – to create and cope with elementary versions of things like Trojan horses, sniffers, spoofers and other dangerous demon-like programs lurking in cyberspace.
Graham will also teach what’s known as “address resolution protocol” (ARP) spoofing. ARP spoofing demons can manipulate these protocols to convince one computer that it is talking to another computer. The demon can therefore set itself up between the two devices to make each one “think” they are exchanging messages with the other. But in the middle, the ARP is intercepting these messages and passing them back and forth – and sometimes adding a little bit more. “It’s terrifyingly simple,” says Graham of the program, which is just a few lines long.
Computer demons are also relevant to “chatbots” and voice assistants such as Alexa, which message or speak as if they’re human. They can turn into demons when they engage us in dialogue, make us feel able to confide in them, and pretty soon steal our souls. But chatbots and voice assistants can also help us cope with our own “Freudian demons” – obsessions created by our psychic activity, perhaps in response to some traumatic experience. These demons continue to return and consume us – “the return of the repressed” as Freud put it – unless we pay attention. If properly programmed, chatbots and voice assistants can draw these obsessions out in the open for us to contemplate, analyse and find better ways to cope with them.
A new generation of demons
Practically as old as religion, demons have come a long way since they first appeared in ancient texts. Those “old-school” demons were scientifically illiterate but morally astute in the sense that they knew how to corrupt you. Each possessing their own wills and objectives, they cannily sought opportunities to steal, betray, sabotage and cause other physical and moral harm. To evade such demons, humans had to mature, and improve their ethical demeanour and cognitive skills. Shakespeare’s Hamlet, for instance, must decide whether what confronts him on the parapet is a deadly demon or a genial ghost, and prepare himself for either eventuality.
What I call “New Gen” demons first began to appear at the start of the 17th century with the birth of modern science. The turning point, in my judgement, was a parable by the philosopher Francis Bacon about a sphinx who haunted the wilds around Thebes. With the wings of a bird and the claws of a griffin, the sphinx would lie in wait for travellers, “whom she would suddenly attack and lay hold of; and when she had mastered them, she propounded to them certain dark and perplexed riddles”.
But Oedipus, whom Bacon described as “a man of wisdom and penetration”, solved the riddle, rendered the sphinx powerless, and slew it. Bacon saw the parable as a metaphor: the demon represented nature and Oedipus represented the scientist. Nature could be deadly, Bacon implied, but it was knowable. So by investigating the demon and thinking through its issues rationally you can render nature harmless.
As modern science progressed, scientists began to realize that demons have skills and abilities that they themselves lack, setting demons to work tackling apparently insoluble problems.
Indeed, as modern science progressed, scientists began to realize that demons have skills and abilities that they themselves lack, setting demons to work tackling apparently insoluble problems. If the demons could solve a particular question, then maybe eventually the scientists could as well. And if the wise and (nearly) all-powerful demons couldn’t solve those problems, at least scientists knew they were on the right track. Demons, in other words, can tell us “What are the things we can’t – or eventually can – do?”.
Particularly interesting is the “imperialist” demon invented by the French mathematician Pierre-Simon Laplace in 1814. Laplace was a proponent of Newton, who had famously pictured the celestial sphere as a clockwork universe. If you know where every piece is and how each moves, Newton’s reasoning implied, you’ll know everything about how the cosmos had worked and how it will in future. Laplace’s demon cleverly carried those Newtonian laws down to the tiniest atomic level.
Although Laplace did not know what makes up matter at such small scales, the implications were massive. That’s because if you know the positions and motions of everything in the cosmos, then she (Laplace, as Canales points out, referred to his demon as “une intelligence”) will know everything that ever was and ever would be. She could solve crimes, answer historical questions, predict the weather, and even strip human beings of their free will.
Her calculational prowess inspired the British mathematician Charles Babbage’s early computers and other mechanical devices, provoked Charles Darwin to contemplate the purely mechanical development of life, and led Erwin Schrödinger to wonder whether something with analogous powers didn’t maintain cellular order. Laplace’s demon ruled for about a century and was only overthrown at the start of the 20th century when physicists developed quantum mechanics, which rendered them powerless to pin down the positions and motions of tiny stuff.
Maxwell’s demon
Perhaps the most famous demon in physics is that devised by Maxwell in 1867. His demon had a completely different job from Laplace’s, being stationed at a door between two chambers of gas. The demon quickly opens and closes the door to let fast-moving molecules go through in one direction and slow-moving molecules go in via the other. One chamber therefore warms and the other cools, reducing the overall entropy and violating the second law of thermodynamics (figure 1).
In her book, Canales calls Maxwell’s demon “more dangerous than Descartes’ demon” because he acts directly on the natural world without having to deceive anyone. He is also more powerful than Laplace’s demon because he does not just know history backwards and forwards but can change it too. What’s more, the ability of Maxwell’s demon to sense the difference between approaching fast and slow atoms in time to grant or refuse them entry to the other side seemed to give him special powers.
The demon could seemingly power perpetual motion machines, make or break molecules, reverse time, reduce entropy, and carry out a host of physics law-breaking activities. If the demon could indeed pull these things off, it meant that the obstacles standing in the way to achieving them were not theoretical but practical. Physicists have long been studying how much entropy the little demon “sweats” and heats up in his efforts, and if it’s enough to ruin his goals.
The bombshells of relativity and quantum mechanics at the start of the 20th century inaugurated a new generation of demons with still more miraculous abilities.
The bombshells of relativity and quantum mechanics at the start of the 20th century inaugurated a new generation of demons with still more miraculous abilities. Canales recounts how Einstein tried to exorcise ones who travelled faster than light and who used a force called “gravitation” (rather than space–time) to push and pull things. There are also quantum Maxwell’s demons (QMD), nanoscale demons and even nuclear magnetic resonance (NMR) demons.
Feynman once contemplated a computer, modelled on DNA-replication processes, that could get work out of nearly random fluctuations. The US mathematician Norbert Wiener mixed features of Laplace’s and Maxwell’s demons to create a cybernetic, or “self-governing”, demon that can learn from feedback. The cosmologist John Wheeler introduced demons who live in black holes, devouring information and energy, seemingly making entropy disappear. The philosopher John Searle, meanwhile, had a demon who lives in the brain and consumes neural synapses.
In her book, Canales tracks down demons in game theory, neuroscience, economics, management and beyond. Demons are found in art, such as the Spanish painter Francisco Goya’s haunting drawing The Sleep of Reason Produces Demons [Monstruos]. Demons appear in literature. You can find them in philosophy, poetry, psychology, religion and even in popular culture – a demon is mentioned, for example, in an entirely different context and to make an entirely different point, in a video for “Montero” by the rapper Lil Nas X. Demons are the seamy underside of the science and technologically permeated modern world.
A demonic future
But back to our course on demons at Stony Brook. Graham and I are not mixing cyber and cultural demons to turn our students into cybercops or cybercriminals. Instead, we hope to teach them important lessons that cross the sciences and the humanities. Demons make tangible our intentions, placing them materially in the real world, able to act independently of the intentions that led us to construct them. This makes them easier to observe and evaluate than when we simply try to reflect on them. Our course will help students not only to code but also to evaluate their intentions before they build demons (rather than afterwards when it’s too late).
If “Demons to think with” succeeds, Graham and I will have achieved the holy grail sought by Stony Brook and most universities we know of. For we will have developed a course that appeals equally to humanities and science students, inspiring and instructing them, and forcing them to work together (though Graham quips that teaching coding to arts students will be easier than getting scientists to read humanities texts). Students, Graham and I believe, need to cope with demons and understand their principles – and would be poorly educated if they couldn’t.
We’ll soon be trying out the course – unless some sphinx is lurking in wait.
An international research team has configured the deep-learning-based Z-net algorithm to generate MRI-guided near-infrared spectral tomography (NIRST) images directly from measured optical signals and MRI data. According to its developers, from Dartmouth College, Beijing University of Technology and the University of Birmingham, the new algorithm shows potential to improve the detection and diagnosis of breast cancer. Reporting their findings in Optica, they note that the algorithm’s ability to learn from data in near-real time overcomes a major hurdle in multimodality imaging. Z-Net also can distinguish between malignant and benign tumours using data from non-contrast MRI-guided NIRST breast exams.
NIRST is a diagnostic imaging technique that characterizes soft tissue optical properties in the spectral range of 600–1000 nm for early detection of cancer. The complexity and time required to reconstruct diagnostic quality NIRST images, however, has made the technology impractical for day-to-day clinical use.
Incorporating structural information from simultaneous MR imaging can significantly improve the obtained tissue function images. The researchers explain that the process of MRI guidance in NIRST has been time consuming, however, due to the need for tissue-type segmentation and forward diffuse modelling of light propagation in tissue. As such, they propose using an artificial intelligence algorithm to perform near-real-time image reconstruction of MRI-guided NIRST, without the need for complex light propagation modelling.
To create the Z-Net-based algorithm, the researchers used diffuse optical signals and MR images as inputs to the neural network, and simultaneously recovered the concentrations of oxy-haemoglobin, deoxy-haemoglobin and water from 20,000 sets of computer-generated simulations. After training the algorithm, they confirmed that eliminating diffuse light propagation modelling and MRI segmentation did not degrade the quality of the resulting images.
Principal investigator: Keith Paulsen and colleagues developed the new deep-learning algorithm.
To test the algorithm’s clinical relevance, the researchers applied Z-Net to patient data obtained by their MRI-guided NIRST system. Principal investigator Keith Paulsen, of Dartmouth’s Thayer School of Engineering, explains that the MRI exam and NIRST data acquisition were carried out simultaneously for two women with suspicious undiagnosed abnormalities at the time of their imaging exams. One patient was later diagnosed with invasive ductal carcinoma and the other with a benign fibroadenoma. Z-Net was able to characterize and distinguish malignant from benign tissue, using only tissue haemoglobin concentration and water images.
“Since Z-Net can be expanded by adding other parameters, such as oxygen saturation, lipids and scattering properties into the network, the diagnostic power for breast cancer detection may be increased even further as multispectral systems for tissue spectroscopy are advanced,” the team writes.
Lead author Jinchao Feng, of the Beijing Key Laboratory of Computational Intelligence and Intelligent System, points out that the Z-Net algorithm reduces the time needed to generate a new image to several seconds. “Another advantage is that the algorithm can be trained with data generated by computer simulations rather than from actual patient exams, which can expedite training when in vivo data is insufficient or unavailable,” Feng explains. “These capabilities will allow Z-Net’s adaptation for use with other cancers and diseases for which multimodality imaging data are available.”
“Although Z-Net training sets were based on 3D simulations, data from a single MRI slice was input to the network, and thus, the network output was a 2D image of chromophore concentrations,” Paulsen tells Physics World.
The researchers are developing a new NIR/NIRST imaging system with a breast interface that has many more sources and detectors that cover the entire breast volume. They are also working on an improved Z-Net algorithm that receives the 3D MR image volume (many slices of the MR image) and returns the 3D NIRST images.
“We hope that 3D NIRST images of chromophore concentrations can be learned by Z-Net and recovered from patient data to improve MRI diagnostic accuracy and performance,” Paulsen adds. The team is now planning a clinical study, which will involve about 40 women who have breast abnormalities, in the near future.
Martin Knudsen at work in a laboratory. (Courtesy: University of Copenhagen, Denmark)
The Danish physicist Martin Knudsen (1871–1949) has just passed his 150th anniversary. Growing up, he worked as a shepherd during the summer and finished his career as a professor in physics and president at the University of Copenhagen.
In the period from about 1910 to 1920 he was investigating the behaviour of the gas flow in vacuum systems, in particular, low-pressure systems, in which the mean-free distance and dimensions of the vacuum system were comparable.
He introduced several concepts, the Knudsen Number, Knudsen gas, (Hertz-)Knudsen equation and Knudsen cells, which are still used today. The influence that Knudsen had on recent work will also be outlined.
Jørgen Schou graduated in 1980 at the University of Copenhagen, Denmark, with a study on electron- and ion-induced secondary electrons. In the following years, until 2007, he worked as a staff member of the physics department at Risø National Laboratory with the main emphasis on sputtering of volatile targets by ion and electron beams. The latest 10 years he worked as group leader at the Technical University of Denmark (DTU) mostly on photovoltaic films and retired in 2021 after having obtained the world record efficiency for CZTS-silicon tandem cells of about 7% as a coordinator for a major innovation project.
Harassing behaviour is pervasive in astronomy, with about a third experiencing discrimination at college or at work. That is according to a new report by American Institute of Physics (AIP) and the American Astronomical Society (AAS) that outlines ways forward for the community to rid itself of discriminatory conduct that has caused many researchers to leave the field.
The report is based on a longitudinal survey about harassment and discrimination experienced by early-career astronomers that began in 2003. It initially polled male and female students in astronomy graduate courses during the 2006/07 college year and then followed up with the same individuals in 2012/13 and 2015/16, by which time the students had entered the workplace. About 800 of the original 1300 candidates responded to the follow-up survey, where about a third reported having experienced harassment and discrimination at college or at work.
The latest report, released in late March, identifies four of the most common types of harassment. They are biased assumptions about young astronomers’ status, careers and personal life; verbal putdowns, such as jokes, criticisms and undermining comments; inequitable treatment based on demography that limited the young astronomers’ social support and professional development; and unwanted sexual attention that ranged from inappropriate comments to threats, stalking and assault.
The survey also reveals that harassing and discriminatory behaviour is not restricted to senior supervisors who are generally white and male. “It’s not just the bad actors,” says Rachel Ivie, director of the AIP’s statistical research centre, who co-authored the report.
“Harassment and discrimination can appear peer-to-peer, and even by subordinates to superiors – putting a female professor ‘in her place’, for example, or PhD candidates harassing postdocs.” Women are not the only victims either. “Men from under-represented groups were more likely to experience discrimination,” Ivie adds. “Women of colour were the most likely.”
The AAS says it will now begin to implement measures to reverse the trend by, for example, adopting a code of ethics and an anti-harassment policy. AAS president Paula Szkody of the University of Washington says that the organization will now conduct a poll of graduate students to test progress on the initiatives.
Ivie adds the importance of questioning and restructuring organizational settings that enable such behaviours. “Harassment and discrimination can reinforce or realign power differentials in academic work and educational settings,” she says. “We’re now looking at the effect of harassment and discrimination on individual careers – what can be done in the field of astronomy to reduce attrition.”
Cosmic dust grains are believed to play an essential role in the emergency of chemical complexity in the universe. In particular, it may catalyze new chemical reactions with the circumstellar and interstellar gasses and therefore, dust-grain surfaces may contribute to the synthesis of the large variety of molecular species found in the interstellar medium. Albeit its importance, much remains unknown on the cosmic-dust formation processes, and high- and ultra-high-vacuum technologies may provide an excellent workbench for these studies.
In this webinar, we present the STARDUST machine, an innovative experimental station devoted to the engineering, production, manipulation, processing and in situ analysis of a wide variety of clusters and nanoparticles, particularly designed to mimic the travel of cosmic-dust seeds from their formation towards the interstellar medium. Its original design offers unique possibilities for nanoparticle growth with high throughput and controlled size and elemental composition. These highly controlled nanoparticles can also be used in other fields, like catalysis or medicine.
Jose A Martín Gago, research professor at ICMM-CSIC from 2012, obtained a PhD in physics funded by ESRF, Grenoble. He held a post-doctoral fellowship at synchrotron LURE-CNRS. Orsay, France, with a Marie-Curie fellowship. For six months during 2020–2021, he was invited professor at FZU-mobility program at the Institute of Physics of the Czech Academy of Sciences.
Jose is a member of important international scientific committees, such as the program scientific board of the large installation facilities: ESRF (Grenoble), ELETTRA (Italy) and ALBA (Barcelona). From 2010, he has been the Spanish representative in the executive council of the International union of vacuum science and technique and applications (IUVSTA). Jose also leads the ESISNA group (Interdisciplinary studies based on nanoscopic systems).
VitreaLab is developing displays based on photonic integrated circuits; how are these created?
Essentially, we take a standard piece of display glass and we put it in our laser-writing system, which is composed of a femtosecond pulsed laser and a motion stage. Then we focus the laser on a specific 3D position inside the glass and locally melt the glass. This raises the index of refraction, and if you string along this modification, you create a light channel, or waveguide. As the index of refraction is higher in these waveguides, light undergoes total internal reflection and is guided in a similar way to inside an optical fibre. The waveguides have diameters of 2 or 3 µm and we use them to build very complex photonic networks. We can distribute the light from a single laser diode to tens of thousands, hundreds of thousands, or even millions of separate laser beams.
Is this the laser-lit chip?
The laser-lit chip is essentially the waveguide technology integrated with a nanoimprint layer on the glass surface, which reshapes the beams a little. But it is essentially a piece of glass that emits a very dense array of red, green and blue laser beams. The beams are so tightly spaced that you can actually slot this chip behind a standard liquid-crystal display (LCD) panel and deliver one laser beam per pixel. And since you can’t see the pixels in such a display, you can imagine how dense this beam array is. This technology can create a lot of new display types, in both 2D and 3D.
We can go from 5% transmission through the display stack to 90%: a huge jump in energy efficiency
What are benefits of using these laser-lit chips in displays?
Even after decades of development, the displays that we have today are fairly bad in many aspects. An LCD typically works by having a rectangular white light source such as an LED at the back of the screen and a filter array in front of it that subtracts light to create the image. But this is an incredibly wasteful process, you waste about 95% of the light being emitted. If you look at a laptop screen with a reasonable brightness, for example, you can imagine how incredibly bright the screen has to be at the back, and this drains the battery of your device tremendously.
What we are doing is essentially just making the light flow much more easily through the entire liquid-crystal stack. It doesn’t get scattered, it doesn’t get colour filtered and it doesn’t create polarization-based loss. In this way, we can go from 5% transmission through the display stack to 90%. This makes a huge jump possible in energy efficiency. We see this as the strongest draw, what we can do for standard 2D display panels, this tremendous increase in energy efficiency.
Light micro-channels VitreaLab uses a unique laser-writing technology to inscribe tiny wave-guides into glass. (Courtesy: VitreaLab)
VitreaLab is also planning to create the first full holographic display, how will this work?
Holography is an often misused physics term – not everything that is a 3D display is a hologram. Holographic displays, by definition, are something that are interference-based and laser-based. How a holographic display works is that you have to have a huge laser wavefront, something highly continuous, then you make tiny modulations, phase shifts, and from this you can create a complex wavefront that encapsulates your entire image. Typically, you would use a laboratory laser, widen the beam with a big lens and eventually let that impinge on your panel – but that’s not practical for consumer products.
That’s where we come in: we miniaturize all of that. Our unique capability is to provide this wavefront, the laser light that you need to create a holographic image, in a form factor that nobody else can produce. We are able to control the laser light very well and enable this holographic back-light component. This will make consumer holographic displays possible.
Has VitreaLab released a commercial device yet?
We are still in the early R&D stages, we have been developing this technology now for three years. We have shown, in our YouTube channel and also at the Photonics West conference, the first proof-of-concept chips, at 15 × 15 mm and 20 × 20 mm. We demonstrated colour images using our laser-lit chip and just an off-the-shelf LCD component. The cool thing we can already show is that you can produce colour images just using an LCD without colour filters, so essentially a monochrome display unit. But because we illuminate each sub-pixel with the correct colour with our separate beams, we can create colour images out of that.
What type of display are you targeting for your first products?
At the moment, we are targeting mobile- to laptop-size displays, maybe also up to monitor sizes for 3D displays, 25 or 28 inches, but definitely nothing larger than that for now. We did some testing, and it seems that when you use a laptop for web surfing, at least half of the energy is just going to the display. So if you can reduce this by 80 or 90%, of course it will make a tremendous difference to your run time. Something similar should also be true for smartphones.
Finally, why do you think VitreaLab won the SPIE Startup Challenge?
I hope that we were chosen because we delivered a good pitch and the jury members were happy with what we presented. We made a statement that we can fundamentally change what this displays space can do and bring it into a new era, into the laser era, and I think this really resonated with them. And, we have evidence that we can actually do this, with these proof-of-concept devices that we were showing during Photonics West. It’s a great boost for us because it’s a renowned award and it validates us with this display technology that’s very different to what everybody else does.
This webinar presents a novel methodology for dosimetry audits on intracranial stereotactic radiosurgery applications. The succeSRS dosimetry audit service offered by RTsafe combines the Prime anthropomorphic head phantom with advanced dosimetry implemented by RTsafe’s highly experienced scientific team.
During this webinar, the overall experience of a radiotherapy department that performs SRS treatments on succeSRS and the acquired results of this service are shared.
Presenter
Andriana Peraticou is director of medical physics at the Bank of Cyprus Oncology Centre.
Numerous commercial technologies for online treatment monitoring (OTM) in radiotherapy (RT) are currently available including electronic portal imaging device (EPID) in vivo dosimetry (IVD), transmission detectors and log file analysis. Despite this, in the UK, there exists limited guidance on how to implement and commission a system for clinical use or information about the resources required to set up and maintain a service. A Radiotherapy Special Interest Group working party, established by the Institute of Physics and Engineering in Medicine (IPEM) was formed with a view to reassess the current practice for OTM in the UK and an aim to develop consensus guidelines for the implementation of a system.
In this webinar we discuss options for OTM, results and insights from the survey and a discussion on the future guidance ahead.
Simon Stevens is deputy chief physicist at the London Clinic Hospital based on Harley Street, UK. Having undertaken his physics degree at Imperial College London in 2005, Simon completed his medical physics Master’s at the University of Surrey with distinction in 2007 and underwent practical training at St George’s University NHS Trust, The Royal Marsden Hospital, and Royal Surrey County Hospital. He completed his state registration as a clinical scientist at St Bartholomew’s hospital, London, in 2011 and has worked as a lecturer in oncology for the Institute of Cancer Research.
Simon’s research interests included flattening filter-free technology, in vivo dosimetry and intra-operative radiotherapy. His publications have featured in Physics in Medicine & Biology and Physica Medical: European Journal of Medical Physics. He has presented his work at both national and international level, including IPEM and ESTRO meetings.
Simon is a member of IPEM and a member of the Institute of Physics. He is currently chair of the IPEM working party for online treatment monitoring in radiotherapy and a member of an IPEM working party for vendor-supplied quality-control equipment.
![The Sleep of Reason Produces Demons [Monstruos]](https://vignette.wikia.nocookie.net/warehouse-13-artifact-database/images/6/60/Goya_etching.jpg/revision/latest?cb=20151101153755){kind=link}