IELTS Academic Reading Practice Test 114

In 1917 Albert Einstein published a paper on how atoms interact with radiation, and in it he described a process he called stimulated emission. An atom that had absorbed energy, he suggested, could be nudged into releasing that energy as a photon, a particle of light. More remarkably, one photon could trigger the same process in a neighbouring excited atom. One photon became two, two became four, all of the same wavelength and travelling in the same direction. Einstein treated the effect as a theoretical curiosity; nothing in his paper suggested a practical use.

For decades the idea stayed in the textbooks. The route to applying it began with microwaves, the long-wavelength radiation used in radar. In the early 1950s several physicists, including Charles Townes at Columbia University, worked out how to amplify microwaves in the way Einstein had described. They passed them through a gas in which most molecules had been raised to an excited state. Townes's apparatus produced an extremely pure and steady signal, and its name was an acronym: maser, for microwave amplification by stimulated emission of radiation. Masers were operating years before any laser existed. Townes shared the Nobel Prize in Physics in 1964 with Nikolay Basov and Alexander Prokhorov, who had developed similar ideas independently.

Microwaves have wavelengths measured in centimetres, whereas visible light has wavelengths tens of thousands of times shorter. Whether the trick could be performed at optical frequencies was uncertain, and in 1958 Townes and Arthur Schawlow, of the Bell Telephone Laboratories, set out the conditions in a celebrated paper. The word laser had already been coined in 1957 by Gordon Gould, a graduate student at Columbia who filled a notebook with designs and had it officially dated. Gould spent much of the next thirty years arguing with the patent office, and was eventually granted a series of patents.

The first person to make a laser work was Theodore Maiman, a physicist at the Hughes Research Laboratories in California. On 16 May 1960 he fired a powerful flashlamp at a cylinder of synthetic ruby no bigger than a fingertip. Its ends had been coated with silver so that light would bounce back and forth inside. The device produced short pulses of deep red light at a wavelength of 694 nanometres. Maiman sent an account to Physical Review Letters, which declined it; a shorter version appeared in Nature in August 1960.

At the end of 1960 a team at Bell Laboratories led by Ali Javan produced the first gas laser, using a mixture of helium and neon and delivering a continuous beam rather than a series of flashes. In 1962 semiconductor lasers made from layers of gallium arsenide showed how small a laser could be. One could be smaller than a grain of salt and driven by a modest electric current. This was the device that would make laser light cheap enough for everyday equipment, from supermarket tills to the machines that read discs.

The earliest applications were in places where no other tool would do. Surgeons used the intense heat of a focused beam to seal tissue and reattach a detached retina without cutting into the eye. Surveyors and the military measured distance with an accuracy that had previously been impossible. In July 1969 astronauts on Apollo 11 left panels of reflectors on the Moon. Observatories on Earth have bounced laser pulses off them ever since, timing the return to within a fraction of a nanosecond and recording how slowly the Moon is receding.

Telecommunications proved to be the largest market. Light travelling through a thin strand of glass, an optical fibre, can carry far more information than an electric current through copper wire, and is immune to electrical interference. Because light weakens as it travels, signals must be boosted at intervals, and in the late 1980s amplifiers powered by lasers made it possible to send enormous quantities of data across oceans without converting it back into electricity. Every internet connection that crosses an ocean still depends on that arrangement.

Meanwhile the laser became a consumer product. In June 1974 a supermarket in Ohio installed the first barcode scanner, which swept a low-power beam across a packet of chewing gum. Compact disc players, which read a plastic disc with a finely focused spot of light, went on sale in 1982. Laser printers replaced impact printers, and by the late 1990s laser surgery was reshaping the cornea to correct short sight. None of these devices looks like Maiman's apparatus, yet all depend on the same principle.

The most powerful lasers are built for research. In the 1980s a method called chirped pulse amplification made it possible to stretch a pulse, amplify it and compress it again. Huge energies could then be concentrated into pulses lasting a tiny fraction of a second without destroying the optical components. For this work Gerard Mourou and Donna Strickland shared the Nobel Prize in Physics in 2018 with Arthur Ashkin, who had used focused beams to hold and move individual cells and tiny particles. Giant lasers are also used in attempts to reproduce nuclear fusion on Earth, where the aim is to merge atomic nuclei and release energy.

From a footnote in a physics paper to an instrument in hospitals, factories and living rooms, the laser is a rare case: a technology whose principle was understood decades before anyone could build it. What changed between 1917 and 1960 was not the physics but the engineering.

A digital twin is a computer model of a physical object that is kept up to date by data from the object itself. The idea is usually traced to Michael Grieves, who described a virtual mirror image of a manufactured product in a presentation on managing products through their life in 2002. The phrase digital twin was coined around 2010 by John Vickers of NASA, an agency that had long used paired physical and computer models of spacecraft. What distinguishes the modern version is not the model but the connection: the twin runs alongside the real thing, changing as the real thing changes.

A twin is built in layers. The first is a geometric model, often assembled from design drawings or from scans of the finished object. The second describes how the object behaves: how a turbine blade bends under load, how heat spreads through a battery, how a bridge vibrates in the wind. The third is the live layer, in which sensors measure temperature, pressure, vibration or current and send the readings, often many times a second, to a computer. That computer compares what is happening with what the model predicted. Any gap between the two can be used to adjust the model, so that the twin becomes more faithful over time and can then be asked questions about the future.

The distinction between a twin and an ordinary simulation matters. An engineer can build a simulation of a bridge that has never been constructed and learn a great deal from it, but that simulation is a hypothesis. A twin, by contrast, is tied to one particular object in one particular place and is fed with that object's measurements. It is therefore a statement about what this turbine, this engine or this patient is actually doing, rather than about what such things generally do.

The commercial case rests mainly on maintenance. A modern jet engine carries a large number of sensors, and the data they produce can reveal a subtle change in vibration long before it becomes a fault. Airlines that use twins can schedule a repair for the week in which a part is expected to fail, instead of replacing it at fixed intervals, and can avoid the far greater cost of an aircraft grounded unexpectedly. Wind-farm operators take the same approach, comparing each turbine with its twin and with the other machines on the site, so that one that is underperforming for no obvious reason can be inspected before it breaks down.

Designers use twins before anything is built. Formula One teams run thousands of virtual laps against a model of a car and a model of a circuit, testing a new wing without spending a day at a track. Factories build a twin of a production line and use it to try out a new layout, discovering where queues will form or where a robot will run out of space. Because the experiment costs nothing but computing time, ideas that would once have been rejected as too risky can be tested properly.

Whole cities now have twins. Virtual Singapore, a three-dimensional model of the city-state, combines data on buildings, roads, drains, trees and population. It is used to study questions such as where solar panels would generate most power, how a new tower would shade the streets around it, or which districts would flood in a storm. Planners argue that such models reveal interactions that no single department would notice on its own, from the effect of a new hospital on traffic to the way a row of buildings changes the wind. Such a model is expensive to assemble and to keep current.

Medicine is the most demanding field. A model of one patient's heart can be built from scans and made to beat inside a computer, so that a surgeon can try a repair or a replacement valve on the twin before operating on the person. Cardiologists in several countries now use such models to plan complicated procedures. The difficulty is that a heart is far more complex than a turbine, and a model accurate enough to guide a surgeon needs both detailed images and a great deal of computing power.

Not every digital twin lives up to the name. Some products sold as twins are little more than three-dimensional pictures, with no live data and no predictive power; the label has become a marketing term as much as a technical one. Even a serious twin is only as good as its inputs, and sensors in a hot engine or on a remote pipeline can drift or fail. There is also a subtler risk, that the model and the object gradually part company. A twin that has been quietly adjusted to match reality may forecast well while understanding less, and engineers need ways of noticing when its internal physics has stopped making sense.

Research is therefore focused on making twins cheaper, faster and more trustworthy. One promising line combines physics with machine learning: the equations that engineers already trust are used where they are reliable, and a trained algorithm fills the gaps where they are not. Another is the shared language needed for models to be exchanged between companies. The most ambitious project of all is a twin of the planet. European researchers are building a model of the Earth's atmosphere, oceans and ice that will be fed continuously with observations and used to test the consequences of decisions before they are taken.

At the gate of almost any secondary school in a country that has restricted mobile phones, a familiar ritual now takes place: students file past a locker and surrender the device that, for the rest of the day, they will not be allowed to touch. France banned phones in primary and lower secondary schools in 2018, the Netherlands asked secondary schools to become phone-free at the start of 2024, and England issued guidance in the same year recommending that phones be kept out of sight throughout the school day. I support such rules for younger pupils. I doubt, though, that a ban on its own achieves what its supporters believe.

The case for restriction rests first on attention. The OECD's 2022 survey of fifteen-year-olds found that roughly two-thirds reported being distracted by digital devices in at least some lessons. The same survey found that students who spent long hours on screens for leisure scored lower in mathematics, reading and science than those who did not. Such figures cannot prove that phones cause poor results; a bored and struggling pupil may reach for a phone precisely because the lesson has already lost them. But what teachers report, and a growing body of experimental work on the way notifications interrupt concentration, points in the same direction.

The most cited evidence on attainment comes from England. In a study published in 2015, the economists Louis-Philippe Beland and Richard Murphy examined schools in four English cities that had introduced bans and compared them with schools that had not. Test scores rose where phones were prohibited, by an amount the authors calculated as equivalent to an extra week of teaching in the school year. The largest improvements were among the least able and the poorest pupils. Yet the study was not a controlled trial: schools chose their own policies, and the kinds of school that ban phones may differ in other ways as well.

Teachers in phone-free schools describe a different atmosphere. Break times become noisier, in the sense that conversation returns; pupils play games that involve running about; and the queue at the office where lost phones are reported shrinks. Such reports are encouraging, but they are also anecdotal. Whether a ban reduces bullying, much of which now happens online and continues long after the school day ends, is far less clear, and schools should be honest about what a rule enforced between nine and four can achieve.

Three objections deserve an answer. The first is safety: parents want to reach a child whose bus is late, and children with medical conditions may need a phone. A ban at the gate can accommodate both, by allowing phones to be left in a locker and collected at the end of the day. The second is educational: phones can be used for polls, research or translation in lessons. Where a school has decided that a device genuinely helps, it can provide a tablet, which is harder to hide under a desk than a phone.

The third objection is enforcement. Rules that are not enforced are worse than no rules, and enforcement falls on teachers who already have enough to do. Schools that have succeeded describe the same ingredients: a clear policy explained to parents in advance, a consistent response at the gate, and somewhere to store confiscated phones that does not turn a teacher into a jailer. Fairness matters too. A ban is easiest for the child whose parents own a car and hardest for the child who depends on a phone to coordinate a journey across a city. In my experience, though, most parents are relieved rather than resentful when a school takes a firm line.

The deepest objection is that a ban solves the problem only while the pupil is inside the building. Children leave school at eighteen into a world saturated with screens, and they will have had almost no practice in managing one. An analogy with road safety is useful: we do not keep children away from roads until they are adults, we teach them how to cross. A school that confiscates phones for five years and never discusses attention has taught obedience, not judgement.

This is why I would grade the policy by age. For pupils in the early years of secondary school, a phone-free day is justified, in the same way that other limits are placed on children who are not yet able to weigh risk. For students in their final two years, a blanket prohibition seems to me both unnecessary and counter-productive. A better arrangement is a phone-free classroom and a phone-permitted common room, a privilege that has to be earned and can be withdrawn.

None of this is an argument for surrender. A school that allows phones to buzz through lessons has simply failed to make a decision, and the research on distraction is too consistent to ignore. But a ban is a floor, not a ceiling. What matters is what fills the hours it protects: laboratories and libraries, sport, unstructured time with friends, and explicit teaching about how attention works and how easily it is sold. The countries now legislating against phones have made a start. They will have succeeded only when pupils no longer need the rule.