Atomic shapes are so simple that they can’t be broken down any further. Mathematicians are trying to turn to artificial intelligence (AI) for help to build a periodic table of these shapes, hoping it will assist in finding yet-unknown atomic shapes.
Tom Coates at Imperial College London and his colleagues are working to classify atomic shapes known as Fano varieties, which are so simple that they can’t be broken down into smaller components. Just as chemists arranged element s in the periodic table by their atomic weight and group to reveal new insights, the researchers hope that organizing these atomic shapes by their various properties will help in understanding them.
The team has given each atomic shape a sequence of numbers based on its features such as the number of holes it has or the extent to which it bends around itself. This acts as a bar code (条形码) to identify it. Coates and his colleagues have now created an AI that can predict certain properties of these shapes from their bar code numbers alone, with an accuracy of 98 percent.
The team member Alexander Kasprzyk at the University of Nottingham, UK, says that the AI has let the team organize atomic shapes in a way that begins to follow the periodic table, so that when you read from left to right, or up and down, there seem to be general patterns in the geometry (几何) of the shapes.
Graham Nib lo at the University of Southampton, UK, stresses that humans will still need to understand the results provided by AI and create proofs of these ideas. “AI has definitely got unbelievable abilities. But in the same way that telescopes (望远镜) don’t put astronomers out of work, AI doesn’t put mathematicians out of work,” he says. “It just gives us new backing that allows us to explore parts of the mathematical landscape that are out of reach.”
The team hopes to improve the model to the point where missing spaces in its periodic table could point to the existence of unknown shapes.
1. What is the purpose of building a periodic table of shapes?| A．To gain deeper insights into the atomic shapes. |
| B．To create an AI to predict the unknown shapes. |
| C．To break down atomic shapes into smaller parts. |
| D．To arrange chemical elements in the periodic table. |
| A．Its holes. | B．Its bends. |
| C．Its atomic weight. | D．Its properties. |
| A．Design. | B．Help. | C．Duty. | D．Threat. |
| A．Thanks to AI, new atomic shapes have been discovered. |
| B．Mathematicians turn to AI to create more atomic shapes. |
| C．AI helps build a relationship between chemistry and maths. |
| D．A periodic table of shapes can be built with the help of AI. |
相似题推荐
【推荐1】Chilean astronomer Maritza Soto has discovered a planet three times as large as Jupiter orbiting a red giant star larger than the Sun and the planet is located some 290 million light years from the Earth.
Soto, a 25-year-old Ph. D. student in sciences at the University of Chile, worked for eight months using two telescopes at the La Silla Observatory, about 370 miles north of Santiago. Last November, she discovered the planet now hearing the designation HD 110014c and her work has now been published in a journal of the London Royal Astronomical Society. The discovery of planets orbiting red giant stars is “rare”, with only five such planets located around stars of that magnitude to date, she told EFE.
HD 110014c orbits its star at a distance about six- tenths the distance from the Sun to the Earth or about the distance between Venus and the Sun. “It’s like imagining a planet three times bigger than Jupiter with the orbit of Venus and the Sun,” she said, adding that the red giant star is about twice the size of the Earth’s Sun.
Another planet had already been discovered orbiting the star, and now Soto’s work has added a second planet to that solar system. To find the planet, she used the so-called radial velocity (径向速度) method, which consists of measuring the slight jiggling (晃动) movement of a star as a planet orbits around it, given that the planets themselves send only a very weak signal and are quite difficult to detect on their own.
“The planets are very weak compared to the stars and you have to use indirect methods to detect them. I analyzed the data that had been gathered over years to confirm the first planet and I discovered the second one orbiting the star,” she said.
1. What can we know about HD 110014c from the passage?| A．It’s about three times the size of Jupiter. |
| B．It is the first planet discovered in that solar system. |
| C．Its star is about 290 million light years from the Earth. |
| D．It orbits its star at the distance between the Sun and the Earth. |
| A．It takes years to gather data. |
| B．They’re far away from the Earth. |
| C．Their signal is too weak to catch. |
| D．The existing technology is not mature. |
| A．To describe how to discover a planet. |
| B．To tell an inspiring story of Maritza Soto. |
| C．To inform readers of a new discovery of a planet. |
| D．To stress the importance of discovering a planet. |
| A．Geography. | B．Science. |
| C．Business. | D．Environment. |
【推荐2】Revealing the source of Jupiter’s x-ray auroral flares
Abstract
Jupiter’s rapidly rotating, strong magnetic field provides a natural laboratory that is key to understanding the dynamics (动力学) of high-energy plasmas (等离子体). Spectacular auroral (极光的) X-ray flares (耀斑) are diagnostic of the most energetic processes governing magnetospheres but seemingly unique to Jupiter. Since their discovery 40 years ago, the processes that produce Jupiter’s X-ray flares have remained unknown. Here, we report simultaneous (同时的) in situ satellite and space-based telescope observations that reveal the processes that produce Jupiter’s X-ray flares, showing surprising similarities to terrestrial ion aurora. Planetary-scale electromagnetic waves are observed to modulate (调节) electromagnetic ion cyclotron waves, periodically causing heavy ions to precipitate and produce Jupiter’s X-ray pulses. Our findings show that ion aurorae share common mechanisms across planetary systems, despite temporal, spatial, and energetic scales varying by orders of magnitude.
INTRODUCTION
Aurorae, observed from planetary polar regions across the solar system, are displays of light that are produced when energetic particles precipitate along magnetic field lines and transfer their energy to the atmosphere. Jupiter’s soft x-ray aurorae are produced by energetic [~ (MeV) (电子伏)] heavy ions (S and O), originally from the moon Io’s (木卫一的) volcanic activities. The dynamic X-ray emissions often pulse with a regular beat of a few tens of minutes. The spectacular quasi-periodic (准周期性的) auroral pulsations at Jupiter have also been observed in ultraviolet (UV), infrared, and radio emissions. The X-ray aurorae are predominately confined (主要局限于) to the region poleward of Jupiter’s main aurora, connecting to Jupiter’s outer magnetosphere via magnetic field lines. The mapping of the emissions leads to the suggestion that the particle precipitations were driven by magnetic reconnection. However, observations show that the x-ray pulsations last for several Jupiter days or longer, evidencing that the driver may not be a transient process like magnetic reconnection.
To date, 40 years after their discovery, the mechanisms that cause these X-ray aurorae remain unknown. Simultaneous measurements of the magnetospheric environment and the auroral emissions are critical to revealing their driving mechanisms. Here, we present observations of Jupiter’s unique x-ray aurorae with simultaneous in situ measurements from the magnetosphere. In this study, we reveal the physical driver for Jupiter’s pulsating x-ray emissions by analyzing simultaneous in situ measurements from Juno and remote spectroscopic imaging by XMM-Newton telescope (XMM，牛顿卫星) during 16 and 17 July 2017. XMM’s European Photon Imaging Camera (EPIC-pn and MOS) instruments provided spatial, spectral, and timing data of Jupiter for a continuous 26-hour (~2.6 Jupiter rotations) observation from 18:26 UT on 16 July to 22:13 UT on 17 July, which was shifted to account for the ~46-min light travel time between Jupiter and Earth. This XMM observation was planned to coincide with the time when NASA’s Juno spacecraft was moving from 62 to 68 RJ (1 RJ = 71 492 km) radially away from the planet in the Southern Hemisphere in the predawn sector between ~0400 and 0430 magnetospheric local time (MLT).
Ionosphere-magnetosphere (电离层) mapping from previous observations suggested that the origins of Jupiter’s X-ray auroral pulsations occurred at these distances from the planet. Juno provided contemporaneous (同时发生的) in situ measurements from the plasma sheet only when Jupiter’s north magnetic pole tilted to Earth. Therefore, we focus on the northern aurora, for which Juno’s in situ measurements detail what was happening in the plasma sheet during the X-ray pulses. At Jupiter, the analysis of these comparisons between in situ and remote sensing observations is more complex than at Earth. At Earth, during the time scale of an auroral event, typically tens of minutes, a spacecraft in the terrestrial magnetosphere usually travels little (e.g., hundreds of kilometers) in comparison to the spatial scale of a magnetospheric event (e.g., several Earth radii) that would cause a large auroral brightening so that this in situ spacecraft could be magnetically connected to the aurora region over the full auroral lifetime. This is not true for Jupiter, because the footprint of the aurora (which is rotating with Jupiter) with respect to Juno’s location changes substantially during an observation. There are also substantial travel times (a few tens of minutes) along the magnetic field expected from the outer magnetosphere to the Jovian aurora. Therefore, the correlation between a single outer magnetosphere event in Jupiter’s in situ measurements and a single auroral pulse cannot be expected on a one-to-one level basis. Instead, a series of successive events are required to draw reliable careful correlations, with the regular periodicity of the x-ray flares, providing an invaluable diagnostic signature of the source process.
(Adapted from an essay on Science.)
1. What does the essay focus on?| A．The X-ray pulses happening on Jupiter. |
| B．The formation of the aurora in the pole of Jupiter. |
| C．The ways to teach people how to appreciate auroras. |
| D．The process of detecting the X-ray pulses on Jupiter. |
| A．Their conclusions. | B．Their measure to do the research. |
| C．Discussion of some problems of preciseness. | D．Their acknowledgements. |
| A．辐射 | B．红外线技术的 | C．太阳风 | D．红外线 |
| A．The strong magnetic is a good breakthrough point to research the auroral flares. |
| B．The X-ray pulses will last for several days on Jupiter. |
| C．The soft X-rays are caused by high-energy ions. |
| D．The X-ray pulses beat regular on Jupiter. |
【推荐3】AlphaZero--an Updated Model of AI
Soon after Garry Kasparov, the former world chess champion, lost his rematch against IBM’s Deep Blue in 1997, the short window of human-machine chess competition slammed shut forever. Unlike humans, machines keep getting faster, and today a smartphone chess app can be stronger than Deep Blue. However, as people see with the new AlphaZero system, machine dominance has not ended the historical role of chess as a laboratory of cognition.
Much as airplanes don’t flap their wings like birds, machines don’t produce chess moves like humans do. Based on a generic algorithm (算法), AlphaZero incorporates deep learning and other AI techniques like Monte Carlo tree search to play against itself to develop its own chess knowledge. Unlike the traditional program Stockfish, which employs many preset evaluation functions as well as opening and endgame moves, AlphaZero starts out knowing only the rules of chess, with no preset human strategies. In a few hours, it plays more games against itself than have been recorded in human chess history. It teaches itself the best way to play, reevaluating the relative values of the pieces. It quickly becomes strong enough to win 28, draw 72, and lose none in a victory over Stockfish. Since AlphaZero can program itself, this superior understanding allows it to outclass the world’s top traditional program despite calculating far fewer positions per second. It’s the typical example of the cliché, “work smarter, not harder”.
AlphaZero shows that machines can be the experts, not merely expert tools. Explainability is still an issue—it’s not going to put chess coaches out of business just yet. But the knowledge it produces is information humans can learn from. AlphaZero is surpassing humans in a profound and useful way, and researchers are working on transferring the knowledge acquired from AlphaZero to other fields.
Machine learning systems aren’t perfect. Even though great progresses have been achieved, AI algorithms are still struggling on open problems such as computer vision, natural language understanding... There will be cases where an AI will fail to detect exceptions to its rules. Therefore, as Kasparov writes, “We must work together to combine our strengths. I know better than most people what it’s like to compete against a machine. Instead of raging against them, it’s better if we’re all on the same side.”
Questions 1-5: Judge if the following statements agree with the information given in the passage.
Choose A for TRUE if the statements agree with it; choose B for FALSE if the statements don’t agree with it; choose C for NOT GIVEN if the information the statements carry is not mentioned anywhere in the passage.根据文章内容判断下列表述。如果表述与文章内容一致，选 A 项；表述与文章内容不一致，选 B 项；文章中未提及的信息，则选 C 项。
Questions 6-9: Choose the correct headings for Paragraphs 1-4 from the box. Note that there are two choices more than you need.请为文章的四段匹配小标题，从A—F中选择。（提示：6个选项中有2项是多余的）
A. The proper attitude to AI
B. The history of AlphaZero
C. The limitations of machines
D. The influences of AlphaZero
E. The working theory of AlphaZero
F. The fast development of machines
1. Machine dominance plays an important role in cognition study.
2. AlphaZero knows opening and endgame moves before playing.
3. AlphaZero develops chess strategies by playing against itself.
4. Chess coaches have already been laid off throughout the world.
5. Sometimes artificial intelligence may not discover exceptions to its rules.
6. Paragraph 1
7. Paragraph 2
8. Paragraph 3
9. Paragraph 4
10. The author uses the underlined sentence in the last paragraph to ______.
| A．argue for the advantages of AI over humans |
| B．inform readers of machine dominance in chess |
| C．advise people to work together to fight against AI |
| D．call on people to combine strengths with the machines |
【推荐1】Black taxis have been a common sight in London for many years. Now these taxis and their drivers have become the focus of a new study into Alzheimer’s (阿尔兹海默症). For those on the outside, it may seem that behind the wheel of these black taxis are just common people who help move us to our places. But hidden within their brains is a map of London’s streets that has put GPS technology to shame for many years.
“The knowledge”, the test for London’s taxi drivers, stands among the hardest tests one could ever experience. It includes remembering information repeatedly from the memory of minute details about between 25,000 and 56,000 streets in London, depending on who’s taking the test, from the Trafalgar Square to the tiniest residential lanes (居民巷).
Usually, the hippocampus (海马体) feels the influences of Alzheimer’s most. The hippocampus controls the brain’s short-term memory and spatial memory (空间记忆) systems. University College London and Alzheimer’s Research UK are coming together to study these taxi drivers’ brains. And the taxi drivers’ hippocampi continue to grow as they go on doing the job for more years. This suggests that perhaps there’s something we can do to reproduce the influence on the general population.
Lead researcher Hugo Spiers was part of the team which 20 years ago found that, like birds’, the taxi drivers’ hippocampi slowly got bigger. In fact, research has found for years that any animal that requires detailed spatial knowledge of their land experiences growth in the hippocampus.
Spiers’ team hopes to deal with Alzheimer’s by studying the taxi drivers’ brains, since the hippocampus becomes smaller with the development of Alzheimer’s. To collect more information, Spiers has asked thirty London’s taxi drivers connected to an MRI machine to drive around. The machine will allow the researchers to keep a real-time watch on the workings of the hippocampus. “It’s been a joy to help scientists fight the disease,” said taxi driver Robert Lordan.
1. What can we learn about “The knowledge”?| A．It lasts for a few minutes only. | B．It invites some residents to be testers. |
| C．It is a great challenge to people’s memory. | D．It is usually held in London’s busy streets. |
| A．They are improved thanks to daily talks. | B．They grow together with taxi drivers’ job. |
| C．They fail to control short-term memory. | D．They are more likely to be influenced. |
| A．Animals’ hippocampi are quite different from humans’. |
| B．The new study can do good to animals as well. |
| C．More detailed studies on animals’ brains are needed. |
| D．Animals’ hippocampi are similar to humans’. |
| A．To decide who has the largest hippocampus. |
| B．To find out what their hippocampi are doing at work. |
| C．To know how Alzheimer’s develops in their brains. |
| D．To test whether the machine influences the hippocampus. |
【推荐2】I read somewhere that we spend a full third of our lives waiting. But where are we doing all of this waiting, and what does it mean to an impatient society like ours? To understand the issue, let’s take a look at three types of “waits”.
The very purest form of waiting is the Watched-Pot Wait. It is without doubt the most annoying of all. Take filling up the kitchen sink(洗碗池) as an example. There is absolutely nothing you can do while this is going on but keep both eyes fixed on the sink until it’s full. During these waits, the brain slips away from the body and wanders about until the water runs over the edge of the counter and onto your socks. This kind of wait makes the waiter helpless and mindless.
A cousin to the Watched-Pot Wait is the Forced Wait. This one requires a bit of discipline. Properly preparing packaged noodle soup required a Forced Wait. Directions are very specific. “Bring three cups of water to boil, add mix, simmer three minutes, remove from heat, let stand five minutes.”I have my doubts that anyone has actually followed the procedures strictly. After all, Forced Waiting requires patience.
Perhaps the most powerful type of waiting is the Lucky-Break Wait. This type of wait is unusual in that it is for the most part voluntary. Unlike the Forced Wait, which is also voluntary, waiting for your lucky break does not necessarily mean that it will happen.
Turning one’s life into a waiting game requires faith and hope, and is strictly for the optimists among us. On the surface it seems as ridiculous as following the directions on soup mixes, but the Lucky-Break Wait well serves those who are willing to do it. As long as one doesn’t come to rely on it, wishing for a few good things to happen never hurts anybody.
We certainly do spend a good deal of our time waiting. The next time you’re standing at the sink waiting for it to fill while cooking noodle soup that you’ll have to eat until a large bag of cash falls out of the sky, don’t be desperate. You’re probably just as busy as the next guy.
1. While doing a Watched-Pot Wait, we tend to ___________.| A．keep ourselves busy |
| B．get absent-minded |
| C．grow anxious |
| D．stay focused |
| A．The Forced Wait requires some self-control. |
| B．The Forced Wait makes people passive. |
| C．The Watched-Pot Wait needs directions. |
| D．The Watched-Pot Wait engages body and brain. |
| A．It is less voluntary than the Forced Wait. |
| B．It doesn’t always bring the desired result. |
| C．It is more fruitful than the Forced Wait. |
| D．It doesn’t give people faith and hope. |
| A．Take it seriously. |
| B．Don’t rely on others. |
| C．Do something else. |
| D．Don’t lose heart. |
| A．exploring various causes of “waits”. |
| B．describing detailed processes of “waits”. |
| C．analyzing different categories of “waits” |
| D．revealing frustrating consequences of “waits” |
【推荐3】In creating A.J. Fikry’s ordinary-yet-extraordinary life, the author Gabielle Zevin has thrown every clichés(老生常谈) into the mix. The hero, A.J. Fikry, lost his beloved wife Nic in a road accident. The sales of his bookstore have been decreasing. The enthusiastic new sales representative Amelia won’t stop annoying him with new books. His rare and very valuable first edition has gone missing. But the unexpected arrival of Maya left in his care brings about a series of events with love and hope to his life.
There are few real surprises in the plot and attentive readers will be able to tell where the story is headed. But that is not the point; the clichés and the predictable plot take nothing away from Zevin’s work The Storied Life of A.J. Fikry because it’s how she tells the story that first charms the readers, then holds their attention, making them read the whole book in a single sitting and finally give the book a long hug when they are finished. This book is a love letter to the joys of reading.
Each chapter begins with the title of a short story or a book and a note from A.J. Fikry describing what he likes about it, essentially introducing each character by what they read. The characters are so realistic that it’s hard not to fall in love with all of them: Maya, “the fantastic book-worm,” Amelia, “the giantess” with questionable taste in fashion, Lambiase, the adorable police chief, and A.J. Fikry, the reluctant hero who hates electronic reading devices that will “send centuries of a lively culture into what will surely be a rapid decline.”
The passage of time, race issues, and the bureaucratic argument of children’s services are all put aside in the telling of this story, not because there’s anything to hide or because reality is not allowed to interfere, but because the author chooses to focus on the important stuff. For example, it focuses on Lambiase who organizes a reading club for policemen at the book store. His original intention is to help promote business, but over the years he becomes a genuine book-lover, one who tends to always have simple advice for his cynical(愤世嫉俗的) friend, A.J. Fikry. “Bad timing,” Lambiase claims, “I’ve been a police officer for twenty years now and I’ll tell you pretty much every bad thing in life is a result of bad timing, and every good thing is the result of good timing.”
More than anything else, this novel is not only about the selling of them or the reading of them, but how books and stories become part of our lives, how we find ourselves within what we read and how we carry books with us. It is also about the power of unexpected happiness and always believing that something wonderful is just around the corner. The Late Bloomer is the book within a book which brings together A.J. Fikry and Amelia. It reminds them that life doesn’t follow a set script, things happen when they are meant to happen, and there is no such thing as “too late” for anything. Life is the big picture. Always look at the big picture. Enjoy it. Don’t get too concentrated on the details, because it will all be over before you know it. In the long run nobody, not even you, will remember the ordinary details because they are, in the end, quite irrelevant.
A.J. Fikry’s final words of wisdom to teen-aged Maya convey the same feelings in literary terms: “We are not quite novels. We are not quite short stories. In the end, we are collected works. We have read enough to know there are no collections where each story is perfect. Some of us hit. Some miss.”
1. The author’s attitude towards Zevin’s book is _________.| A．supportive | B．critical |
| C．objective | D．indifferent |
| A．Four. | B．Five. |
| C．Six. | D．Seven. |
| A．there is really nothing to hide | B．reality is not allowed to interfere |
| C．important stuff has been focused on | D．everything is a result of timing |
| A．The novel underlines happiness will always be around. |
| B．The novel mainly talks about the marketing of the book. |
| C．It is The Late Bloomer that brings A.J and Amelia together. |
| D．It is important to do things on the basis of overall situation. |
| A．our life is full of ups and downs | B．we should collect works all our life |
| C．our life is closely connected with books | D．we should read books all our life |
| A．the extraordinary life of A.J. Fikry | B．the moral lesson of no “too late” in life |
| C．a comment on The Later Bloomer | D．a review of The Storied Life of A.J. Fikry |
