science
The Biography of Jim Simons
The Biography of Jim Simons; Capitalist who solved the puzzle of the market with math
When it comes to investing, no one comes close to Jim Simons ; Not Warren Buffett , not Steve Cohen and not even George Soros , who are probably more familiar names to you. “Renaissance Technology” company, Siemens, has a famous hedge fund called Medallion, which has average annual return of 66% for 30 years. In simpler terms, if you had invested $100 in the Medallion fund in 1988, 30 years later this figure would have reached $398.7 million!
Stranger than that, Simons hired people who knew nothing about investing; Instead, Medallion’s employees were mathematicians and scientists like himself. While ordinary investors relied on economic intuition and instinct, consulting with executives and analyzing earnings reports to make trades, Simons took a different path to investing.
As a veteran mathematician, Simons believed that the market behaves rationally; So he decided to enter the field of capital with a scientific approach. He made decisions based on large sets of data, computer models, and algorithms, and inspired the revolution that swept Wall Street.
Jim Simons was never calm; It was not enough for him to be a mathematician, to be a professor at MIT and Harvard, nor to crack codes for the US National Security Agency during the Cold War. According to his first wife, Barbara Blustein, in The Man Who Solved the Market Riddle, “Jim learned from an early age that money equals power.”
Jim Simons, the pioneer of investing with computer models and known as the “Quant King”, died at the age of 86 on May 10, 2024 (May 21, 1403) in Manhattan, New York. This is the story of a mathematician who, with the help of mathematical magic and algorithms, produced the world’s biggest money-making machine in his mysterious company and became the biggest investor in history.
First days
James Harris Simons, the only child of Matthew Simons and Marcia Kantor, was born on April 25, 1938, in Brookline, a suburb of Boston. His mother worked as a volunteer at Jamie’s school and saw the fulfillment of her own dreams in her son. Jimmy’s father was a sales representative for 20th Century Fox but later worked in his father-in-law’s shoe factory. Matthew later told his son that he wished he hadn’t given up his promising career in the film industry for what was expected of him. The lesson Jimmy learned from his father was: “Do what you love, not what you feel you have to do.”
What Jimmy loved to do more than anything else was think about math. His mind was always occupied with numbers and shapes. At the age of three, he could multiply and divide numbers by two and knew all the powers of two up to the number 1024. At the age of four, when his father stopped for gas, Jimmy was pondering one of Xenon’s paradoxes , known as the two-part paradox.
At the age of eight, when the family doctor told Jamie that his ideal career would be in medicine, Jamie replied, “I want to be a mathematician or a scientist.” The doctor insisted that there was no money in mathematics, but Jimmy said he didn’t care about money.
As he had hoped, Simons majored in mathematics at MIT, skipping his freshman year because of the advanced mathematics course he had taken in high school. With too much self-confidence, he decided to graduate with abstract algebra in the second semester; But he could not keep up with his classmates. So he bought a book on abstract algebra and studied it all summer until he finally “bloomed,” as he put it.
The next year, when he came up with Stokes’ Theorem, a surprising combination of calculus, algebra, and geometry, he did so well in class that students sought his help. Simons was delighted to see that powerful theorems and formulas could reveal the secrets of truth and connect the disparate fields of mathematics and geometry. He said: “Mathematical concepts were beautiful and elegant to me.”
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Simons earned a bachelor’s degree in mathematics after three years at MIT, and got his first taste of investing while studying for a doctorate at the University of California, Berkeley. He went to a brokerage in San Francisco to trade soy futures.
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Simons was lucky in his professional life but unlucky in his personal life
During these days, Simons married his first wife, Barbara Bluestein, and had three children, one of whom died in a bicycle accident. Simons and Barbara’s marriage ended in divorce 15 years later. Simons had two children with his second wife Marilyn Howris, a Stony Brook economics student, one of whom died due to drowning; The death of her two children was shocking to her and she couldn’t understand how she could be so lucky in her professional life but so unlucky in her personal life.
Simons returned to MIT in 1961 to teach, feeling that his future path was clear. In a 2020 interview with the American Institute of Physics, he said: “I remember one day I was sitting in the library and I said to myself, well, first I will become an assistant professor, then an assistant professor, and then a professor, and I will continue to live like this until I die. But at that moment I thought that maybe there are other things in the world.”
In 1963, Simons accepted a research position at Harvard University, teaching an advanced graduate course on partial differential equations. Simons didn’t know much about the subject, but he found teaching a good way to learn. He used to tell his students that he learned the subject a week or two before the class; A confession that was funny to the students.
Decoding the Cold War
A year later, Simons also left Harvard to join the IDA intelligence group to decipher coded messages from the Soviet Union during the Cold War. The Institute for Defense Analyzes was affiliated with the National Security Agency, which is the largest and most secret intelligence agency in the United States.
Starting at IDA, Simons’ salary doubled and he was able to clear his debts. In addition, he could pursue his own mathematical projects while collaborating with the government. The only problem with working at IDA was that he couldn’t tell anyone about his achievements, because everyone in the group was sworn to secrecy.
Jim Simons (left) with two other colleagues at IDA
Simons joined the IDA during a turbulent period, as complex Soviet codes had not been systematically deciphered for more than a decade. However, working in an intelligence agency taught Simons how to build mathematical models to recognize and interpret patterns in seemingly meaningless data.
Siemens was terrible at developing computer programs
In order to decode the codes, Simons first defined an attack plan; Then he designed an algorithm to test and implement his strategy. Siemens was terrible at developing computer programs and had to go to the organization’s programmers for coding; But during this time, he strengthened other skills that were used later in his professional life. “I realized that I liked designing algorithms and testing them on the computer,” he said.
Jim Simons worked for the National Security Agency for more than three years before being fired for protesting the Vietnam War. In an article for the New York Times, Maxwell Taylor, the head of the IDA, asserted that the United States was about to win a war that was worth it. In a letter to the editor, Simons wrote that “any political gains from military victory cannot possibly offset its enormous economic, intellectual, and moral costs.”
Three days later, the US president announced the end of the bombing of Vietnam, which marked the end of the war. Simons assumed the news meant he could go back to work, but he was told not to bother going back.
Inventing a method of investing in overtime
While working at IDA, Jim Simons devoted his free time to studying the stock market. With the help of three other colleagues, he designed a new system for stock trading and claimed that their method can have at least 50% annual profit.
The unique feature of the Simons system was that it did not try to identify or predict different states of the stock market with economic theory or other conventional methods, and it did not seek to investigate why the market entered certain states.
Simon’s model was the forerunner of revolutions in the financial field
For Simons and his colleagues, it was not the “why” that mattered, but the strategies with which market conditions could be used to their advantage. For most investors, this approach was completely unfamiliar, but not for people who were gamblers. For example, poker players guess the mood of their opponents by judging their behavior and choosing their strategy based on this guess.
Jim Simons and his colleagues also proposed a similar approach to forecast stock prices, relying on a complex mathematical tool called the “Hidden Markov Model”. Just as a gambler may infer the state of mind of an opponent based on his decisions, an investor may infer the state of the market from its price changes.
Simons’ argument was that it is not important to understand all the underlying levers of the stock market but rather to find a mathematical system that matches these levers with the ability to make consistent returns. The Simons model was the forerunner of revolutions in the financial field; Including factor investing, the use of models based on unobservable states, and other quantitative investment methods that swept the investment world decades later.
The golden age of mathematics
After being fired from IDA at the age of 30, Simons managed to become the head of the mathematics department of Stony Brook University in New York with the suggestion of his mathematician friend. Simons made a discovery in Stony Brook about the reduction of shapes in curved and three-dimensional spaces. When he showed his discovery to the brilliant physicist Shiying-Shen Chern, Chern realized that the theory could apply to all dimensions, not just three-dimensional space. Chern and Simons introduced the Chern-Simons invariant constant in their 1974 paper “Characteristic Forms and Geometric Variables”, which was used in various mathematical fields.
Jim Simons teaching mathematics at the university
In 1976, at the age of 37, Simons received the American Mathematical Society’s Oswald Veblen Prize in Geometry, the highest honor in the field, for his paper with Chern, as well as his earlier research on minimal manifolds. A decade later, theoretical physicist Edward Witten and others discovered that Chern-Simons theory has applications in a wide range of areas of physics, including dense matter, string theory, and supergravity. This theory was even critical to the methods used by companies like Microsoft to develop quantum computers capable of solving extremely complex problems, including drug development and artificial intelligence.
Entering the field of transactions
By 1977, Jim Simons was convinced that the currency markets were extremely profitable. World currencies were moving up and down regardless of the price of gold, and the British pound had fallen. According to Simons, a new era of instability had begun. In 1978, Simons finally left academia to start a small firm focused on currency trading; A decision that neither his father liked nor the mathematicians who knew him.
Mathematicians usually have a complicated relationship with money
Mathematicians usually have a complicated relationship with money. They understand the value of wealth, but for many of them, wealth accumulation is a low-value distraction from their much more valuable mission. Academics didn’t say anything to Simons directly, but some believed that his rare talents were being wasted.
But Simons saw the story differently. By the age of forty, he had experienced a career in deciphering, had climbed the heights of mathematics, and had set up his own successful mathematics department. Now he was sure that he could conquer the trading world as well.
For centuries, investors have been trying to solve the mystery of the market and dominate it; But they rarely achieve great success. Some investors and analysts considered market fluctuations completely random and believed that all possible information was already included in the prices; So only events that are impossible to predict can make prices go up or down. But Simons came from the world of mathematics and was used to scrutinizing large sets of data and finding order and patterns where others saw only random occurrences.
Jim Simons concluded that the stock market does not always react logically and explainably to news or events and that relying on traditional research makes it difficult to predict prices. However, prices seemed to show at least a few distinct patterns even in chaotic arithmetic markets.
Simons decided to treat the financial markets like a chaotic system. Just as physicists create beautiful models by analyzing large amounts of data to identify laws in nature, Simons wanted to create mathematical models to identify order in financial markets. His approach was very similar to the strategy he had devised years ago at IDA. At that time, Simons said that the markets are in various hidden states that can be revealed by mathematical models.
Renaissance’s original Long Island office was located near clothing boutiques, pizzerias, and the Stony Brook Railroad.
To test this strategy in the real world, Simons launched Monemetrics, an investment firm in Long Island, New York, later renamed Renaissance Technologies. Manometrics was derived from two words “Money” and “Econometrics”. Simons wanted to show that he could generate a lot of wealth by using math and analyzing financial data. So, instead of hiring an investor, he hired a team of mathematicians like himself to analyze market data for months, identify trends, and write mathematical formulas to make money from the stock market.
One of these mathematicians who was willing to give up his lucrative job at IDA to make Simons’ dream come true was Leonard Baum, who had helped Simons write the IDA research paper. It didn’t take long for Baum to develop an algorithm for the Renaissance. If the value of the currency went below a certain level of the trend line, the algorithm said to buy it; And if it went above this line, it was time to sell. Baum, who until one or two years ago did not think about anything else except mathematics, now only thought about currency transactions.
The birth of the medallion fund
Renaissance started its business with foreign exchange, commodity, and bond trading and chose not to enter the stock market for the time being because their diversity is high and the value of each stock is highly dependent on the unique circumstances of the companies.
Jim Simons dreams of a trading system that is completely driven by algorithms without the intervention of human judgment; But the computers of the eighties did not have the ability to run fully automatic programs. For this reason, the Renaissance initially used both mathematical models and human judgment, which became troublesome for him; For example, Baum bought tens of millions of dollars in bonds in 1984, but held them until they fell in value and put the company under heavy pressure; Until Simons went as far as giving up on the renaissance.
Simons dreamed of a fully automated trading system without the intervention of human judgment
Realizing the limits of human judgment, Simons added James Ax, a friend from his doctoral days at Berkeley to the Renaissance team. The group James led collected data from the 1800s and fed it into computers to discover new hidden patterns. Simons believed that if he had enough data, he could make more accurate predictions.
Simons and Ax launched a new hedge fund called Medallion, named after the prestigious math awards they won. The medallion fund initially had many problems, but eventually became the most successful hedge fund in history. After ten years of improving algorithms and progressing the processing power of computers, the turning point of the Renaissance came in 1990.
With the arrival of James X in the renaissance, Simons’ dream became closer to reality
Edward Trapp, the first modern mathematician who made a huge investment fortune using the Cammy Simons strategy, wrote in the Wall Street Journal article, “Computer Formulas Are the Secret to Market Success”:
A computer model is a simplified version of reality, like a street map that shows how to travel from one point of a city to another. If you design them right, you can use its rules to predict what will happen in new situations.
Renaissance models were so successful in trading that Siemens continued to trust its computers even in decisions that didn’t seem logical. The only problem was that Renaissance was very small, and after ten years its assets were only a quarter of those of rival DE Shaw; David Shaw not only used computer models for trading, but unlike the Renaissance, he also went to the stock market.
Simons knew that in order to leave a legacy, he had to enter the stock market; That’s why he hired Robert Mercer and Peter Brown, who had become famous for the great speech-to-text achievement at IBM. The two looked at language as a game of possibilities in which some words followed other words. Siemens wanted a similar system that could predict financial market trends. Brown and Mercer designed an automated stock trading system in 1995 that was written in half a million lines of code, compared to the tens of thousands of lines of code in the old system.
Robert Mercer (left) and Peter Brown played key roles in many of the Renaissance’s successes
With Renaissance entering the stock market, the medallion fund soared. In 2000, Medallion returned an astonishing 98.5% including losses, during the dot-com bubble, during which many telecommunications companies went bankrupt and larger companies such as Amazon and Cisco lost much of their market value. They gave.
The Medallion fund made more than $100 billion in profits between 1988 and 2018, and as of summer 2019, its annual return before deficits was about 66%, and after deficits was about 39%. In 1993, the fund was closed to new investors, and since 2005, only Renaissance employees are allowed to invest in it. With their windfall, these employees bought so many mansions in the Old Field neighborhood of Long Island that the neighborhood was nicknamed the “Renaissance Riviera.”
Medallion earned more than 100 billion dollars in profit in 30 years
Renaissance’s assets are now around $50 billion, and with a 44% fee, which is higher than any other large hedge fund, the Medallion fund has an annualized return of more than 30%, which is totally worth it. By comparison, Warren Buffett’s Berkshire Hathaway fund has a compound annual return of just 20%.
Medallion’s astonishing performance made Simons the 50th richest person in the world at the time of his death, with a fortune of $31.4 billion. Simmons first appeared on Forbes magazine’s list of the richest Americans in 2004 with a net worth of $2.5 billion.
Currently, Renaissance is led by Peter Brown and has about 300 employees consisting of 90 scientists with PhDs in mathematics, physics, computer science, and related fields. The research database of this company hosts more than 40 terabytes of data daily and uses 50,000 computer cores with a global connection of 150 gigabytes per second.
The secret of Renaissance success
Quantitative strategies, based on more conservative models, have become popular on Wall Street since Simons revolutionized the trading world in the 1980s, and the funds now account for little more than 20 percent of all equity holdings.
But how Renaissance was able to achieve such startling results remains among the company’s top secrets, and employees are not allowed to talk about Renaissance’s algorithms. Simmons also had a very secretive personality and rarely appeared in public. Although he never talked about the Renaissance Algorithm, he did share the secret of his success; “he never turned his back on the model.” Once Simons had decided what to do, he stood his ground until what the model predicted happened.
The success of the Renaissance is also a reminder of the predictability of human behavior. Renaissance studies the past because it is certain that investors will make similar decisions in the future. At the same time, company employees avoid emotional and emotional biases by relying on the scientific method. They hypothesize, then test and measure, and rely on data instead of instinct when making decisions.
Humanitarian actions
In 2009, Simons decided to step down from the management of Renaissance and hand over the leadership of the company to Robert Mercer and Peter Bevan. Having amassed an impressive fortune over two decades, Simons decided to spend a large portion of it on philanthropic causes.
Siemens has spent more than $6 billion on philanthropic causes
He and his wife, Marilyn, established the Simons Foundation in 1994 to provide scholarships for the fields of biology, mathematics, physics, computer science, and neuroscience. In 2012, the idea of ”Siemens Collaborations” was conceived to support research into the inner workings of the brain, and in 2016, the Flatiron Institute became a center for computational science and projects related to astrophysics, biology, mathematics, neuroscience, and quantum physics. .
Jim Simons and his wife Marilyn Simons
According to estimates, Simons spent more than $6 billion of his fortune on philanthropic causes and was ranked the sixth most philanthropic person in America by Forbes magazine. Jim credited Marilyn as the driving force behind the Simons Foundation, joking, “I just make money and Marilyn gives it all to charity.”
Speaking at MIT in 2010, Simons outlined the five pillars that have shaped his life and career in mathematics, investing, and philanthropy: “Do something new; Don’t go with the crowd; Surround yourself with the smartest people you can find; Go for beauty; Don’t give up easily and wish for luck!”
In this report, we review some of the strangest science stories that we came across last year.
The strangest science stories of the past year
Some scientists are working on tackling climate change or curing cancer, but others are more focused on finding out if time travel is really possible.
The report explores where “love” is felt in the body, the scientific value of giant piles of bird poop, and talking to whales as an exercise in communicating with aliens and extraterrestrials.
Here, we review 10 of the weirdest science stories of the past year.
Brain computers
Brain computers is the first science stories of the past year. Nothing like experimenting on the human brain in a crazy glass jar. This is despite the fact that researchers approached this case strangely and worryingly last year.
An Australian company called Cortical Labs has grown human brain tissue from stem cells and attached them to computer chips, growing neurons in simulations and allowing them to perform computational tasks and even play the popular game of Pong. Teaches Pong.
Another group developed brain organoids called “Brainoware,” which are literally tiny three-dimensional brains and taught them to recognize sounds and perform mathematical calculations.
In another study that was published late last year, a group of researchers from the University of Wisconsin-Madison created the first functional tissue of the human brain with 3D printing technology to examine brain function and investigate various neurological disorders, which can be used to study various neurological problems and disorders, including Alzheimer’s and Parkinson’s disease is useful.
While these systems are still too crude to demonstrate anything close to realizing consciousness, we’d better be prepared to set some ethical guidelines.
The strangest science stories of the past year
Did James Webb detect stars made of dark matter?
The James Webb Space Telescope may have spotted the first signs of theoretical “dark stars,” which are invisible objects that generate heat from the decay of dark matter particles in their cores, astronomers say.
Because the James Webb Space Telescope can look deeper into the universe than any other instrument, we are always open to discovering truly new and surprising things with it.
James Webb observes giant, ancient galaxies that expand our understanding of how the universe formed. That’s why some astrophysicists say that instead of messing with the standard model of cosmology, maybe what we’re seeing right now are “dark stars,” hypothetical bodies that generate heat from decaying dark matter particles in their cores.
These monsters are 10,000 times larger than the Sun, 10 million times heavier, and 10 billion times brighter (albeit in the infrared spectrum), which makes them look like galaxies from this distance.
This idea is interesting and at the same time completely speculative, but luckily it is testable. So we may have an answer to that soon.
Eerie dreams of artificial intelligence
Among these strange science stories, AI is the next one. The world of artificial intelligence is moving so fast that it’s hard to believe that just a few months ago we were laughing at the unrealistic results of its video production efforts. But now, within a short period of time, it has reached a place where it often leaves us with our fingers in our mouths.
Visualizer systems like ModelScope and Runway’s Gen-2 are designed to produce short videos based on text messages, and the results are amazing.
Google also recently unveiled its newest artificial intelligence called Lumiere, which is specialized for video production and editing only by receiving text commands.
We now stand at a point in history that seems both interesting and scary, because the continuous development of artificial intelligence, while offering new possibilities to mankind, is also accompanied by dangers that the greats of this field, such as Elon Musk and Sam Altman, have warned of. They have warned of its unmanaged development.
The strangest science stories of the past year
Artificial intelligence fashions feet in shoes
Artificial intelligence has shown that it can also enter the world of fashion, but not in the way you might think.
An Italian company active in the field of fashion called “Capable” has unveiled a line of colorful clothing that not only attracts the human eye but also deceives artificial intelligence.
These flamboyant patterns are designed in such a way that they also confuse artificial intelligence object recognition algorithms so that the wearer sees these clothes as giraffes or zebras.
This technology is very expensive, but at least it tries to make future fashion more fun than redesigning an old coat.
Calling all aliens
This science stories among other sience stories is about aliens. Scientists have recently made contact with a “non-human intelligence”, although not the aliens we are thinking of. At least not yet.
Scientists from the Search for Extraterrestrial Intelligence (SETI) were able to talk to a whale in its own whale language as an exercise in communicating with aliens. This exercise could come in handy the day we probably finally meet extraterrestrials.
Meeting with aliens is a subject that mankind always has in mind and seems to be waiting for such an event to happen. Scientists are also now looking to practice communicating with extraterrestrials in the future by trying to talk to whales in their own language.
Communication between humans who speak different languages is difficult enough. This is despite the fact that we all have the same biological characteristics. But aliens could not only have their own language but probably have completely different ways of communicating. For example, they may convey a complete emotional spectrum through sound, frequency, tone, smell, taste, and density of the passing gas.
The team called it the first human-whale communication exchange, and all they did in the study was play a recording of a whale saying “hello” over and over until the whale got bored and left. That area was distanced.
The idea is that scientists can make conversations with whales more interactive so that eventually it can help us create filters that can pick up the structures of any alien message.
Scientists say whales are a good place to start. They are highly intelligent and have complex social communication systems that can be deciphered. Also, if we attack them, the only casualties might be a few yachts, not strategic world locations.
Scientists say we hope to manage the first close encounters with aliens with the help of whales.
where is the love?
Even the most hard-hearted people feel and experience love in some way, even if it is the love of a pet.
Scientists say there are 27 different types of love and they sought to determine where in their body people feel these 27 different types of love and how strong each one is.
So participants in one study were asked to point to a drawing of the human body, color the spot they wanted, and describe how physically and mentally pleasurable it was.
Interestingly, each type of love was felt in the head, and not surprisingly, most of them were also felt in the chest.
Love for children or parents was strongly felt in the heart and chest.
The strength and intensity of the feeling of love also differed according to its type. Love for beauty, wisdom, God, strangers, or country was felt more in the head, while participants inscribed true love across the entire body.
Of course, according to the researchers, expectations and preconceptions probably influenced the participants’ answers here.
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Time has been slower in the past
Astrophysicists have discovered that time passed more slowly in the early universe than it does now.
So time seems to be speeding up. Physicists studied the ticking of quasars billions of years away in space-time and found that one ancient second had passed as much as five seconds today.
It should be said that according to scientists, time did not feel slower for anyone at that point, although we know that everything is relative. But if there were people back then who could see us in the future, they would wonder why we are all moving and living in such a hurry.
This phenomenon is the result of “time dilation” which is caused by the deviation of the relativistic effects of the fabric of space-time. Just like the planet that revolves around a black hole in the movie Interstellar.
Time dilation is one of the physical concepts related to Albert Einstein’s theory of special relativity, which is expressed on the basis of relativity in such a way that the passage of time is examined differently from the perspective of two observers with different speeds. In general, the faster we move, the slower time passes and these two have an inverse relationship.
History hidden in a pile of bird droppings
On a rock in Argentina is something that probably wouldn’t be on a tourist website’s list of attractions, unless it’s interesting to scientists. Talk about a pile of excrement.
This unusual pile of excrement was created by generations of Andean condors that returned to the same spot where their nest was every year.
The Andean vulture with the scientific name (Vultur gryphus) is the name of a species of the New World vulture family. The Andean vulture is the largest flying bird in the world with a maximum wingspan of 3.3 meters.
When the scientists split this hill, they realized that it actually preserved 2200 years of history. By studying the layer by layer of this unpleasant mound, they found that these birds initially feasted mostly on the carcasses of native species, but after the arrival of European immigrants, they showed an interest in sheep and cattle.
Scientists could even say that the vultures have left this place for several centuries and moved their place of residence due to a period of volcanic activity in this area.
The genetic mystery of a woman who feels no pain
A new genetic study has identified specific genetic mutations that appear to allow a Scottish woman to feel no pain.
Jo Cameron is the name of this Scottish woman who feels no pain, fear, or anxiety and her wounds heal faster than usual.
Interestingly, this superpower of his was discovered in his 60s.
When scientists researched him, they found that these features were mostly due to mutations in two genes called FAAH and FAAH-OUT. Of course, hundreds of other genes, including those associated with wound healing, mood regulation, and drug levels, were also suppressed or enhanced.
Charged with contradictions
It seems that this woman is a very interesting case for the world of science, and research on her can help scientists create new treatments to relieve pain or mental illnesses.
Causality (the relationship between cause and effect) is the key to our experience of reality. For example, dropping a glass will break it, so the glass cannot shatter before being dropped. But in the quantum world, these rules don’t necessarily hold, and scientists have now shown how these wonders can be harnessed to charge quantum batteries.
In a sense, quantum batteries are powered by contradictions. On paper, they work by storing energy in the quantum states of atoms and molecules. Of course, as soon as the word “quantum” enters the conversation, you know something weird is about to happen. In this case, a new study has shown that quantum batteries can work by violating cause and effect as we know it.
Now, scientists at the University of Tokyo have taken advantage of this strange phenomenon to create a battery that charges faster and more efficiently. They conducted a laboratory experiment using lasers, lenses, and mirrors that act as a large-scale quantum battery.
Basically, the causality in quantum batteries can exist in a time superposition, leading to another strange effect where a low-power charger can charge a battery more efficiently than a high-power charger. Thus, this battery is charged by disrupting our understanding of the flow of time.
“Prolonged Covid treatment” and “Artificial Intelligence regulation” are among the topics we expect to see important news in the new year. Here we will talk about the expected scientific news in the new year.
Expected scientific news in the new year
With the US elections approaching and European parties’ differences over green policies, political tensions and differences can create problems and uncertainties for scientists in the new year. While the effects of the SARS-CoV-2 pandemic are winding down, a long-running COVID treatment trial may be showing its first results.
The warming of the Pacific Ocean known as “El Niño” is also likely to lead to the strengthening of the global temperature to higher limits. “Science” reporters have reviewed the research and policy areas that could make news in 2024.
Read More: 6 historical secrets scientists discovered in 2023
El Niño may perpetuate record heat
The first scientific news in the new year is El Niño. An El Niño heat wave in the eastern Pacific is likely to intensify in the next few months, pushing global average temperatures 1.5 degrees above pre-industrial levels for the first time. Also, the El Nino weather phenomenon is also expected to worsen the drought in the Amazon and Australia.
This change started last year and it is suspected that 2023 will become the hottest year in the history of the modern era, with the average temperature in the first 11 months of the year being 1.4 degrees above the pre-industrial level, which is higher than It can be explained only by the emission of greenhouse gases.
On the other hand, El Nino has reduced the heat absorption capacity of the ocean and this pattern will continue in the new year.
Competing to regulate artificial intelligence
The second scientific news in the new year is artificial intelligence. Governments around the world announced ambitious plans to increase AI oversight last year, and the race to regulate AI is expected to intensify in the new year.
American organizations will face a serious task in this field; Especially since the US government announced policy guidelines in November last year with the aim of determining the criteria for the responsible development of artificial intelligence.
Members of the US Congress have also been active in this regard and have presented more than 150 plans to ensure that artificial intelligence will be beneficial – and not threatening.
This is while it seems that the European Union is closer to approving and adopting ethical guidelines. But specific regulations may soon fall out of favor as new artificial intelligence software, such as chatbots based on large language models, enter the field so quickly and seemingly endlessly.
The arrival of anti-malarial mosquitoes
The next scientific news in the new year is anti-malarial mosquitoes.The strategy of releasing laboratory-modified mosquitoes to prevent the spread of dengue fever is being intensified this year after a string of successes.
Aedes aegypti mosquitoes, developed and tested by the non-profit organization “World Malaria Mosquito Program” (WMP), carry the bacteria Wolbachia pipientis, which prevents them from transmitting certain viruses.
A pilot program in Indonesia has shown that this strategy reduces the number of dengue cases and hospitalizations.
In the fall of last year, researchers reported that dengue fever material has decreased by at least 95% in the release areas of this laboratory mosquito in Colombia.
The first results of the long COVID treatment trial
Four years after the beginning of the pandemic caused by “SARS-CoV-2”, millions of people in the world have suffered from the consequences of the “prolonged COVID-19” syndrome, which is accompanied by symptoms such as fatigue, constant headache, and shortness of breath.
While there is no approved treatment for this condition, patients and their doctors are experimenting with various medications and nutritional supplements to treat the condition.
Scientists hope to announce the results of some long-running Covid treatment clinical trials this year, although the results may be preliminary. Some drugs, such as Paxlovid and other antiviral drugs, target SARS-CoV-2, and other proposed drugs will target some of the other unusual cases identified in long-running Covid research.
Even if these experiments are not successful, the scientists hope that the results of the experiments will shed light on the biology behind the prolonged COVID-19 state so that they can determine what to test next.
Creating order in the neutrino mass
Two ongoing experiments can show how clumps of tiny, elusive particles called neutrinos aggregate. These particles appeared in three types of electron, muon, and tao, which transform into each other and this phenomenon can explain why the universe has produced more matter than antimatter.
First, scientists must define their theoretical model. They know that two of the neutrinos have roughly the same mass, but they don’t know if there are two light neutrinos and one heavier one, or vice versa. Physicists working on the T2K experiment in Japan and the NOvA experiment in the US are studying neutrinos by firing them hundreds of kilometers into large sensors.
They plan to publish a joint analysis in the new year that could determine which of the two alternatives is correct.
Opposition to the green ambitions of the European Union
While far-right nationalist parties are doing well in polls leading up to June’s European elections, observers predict opposition to the EU’s green agenda will intensify. The “European Green Deal” adopted in 2020 aims to make Europe the “first climate-neutral continent” and reduce greenhouse gas emissions to zero by 2050. In this context, environmentally friendly measures have been designed in various sectors, including energy and transportation.
This is even though far-right parties and the conservative party “People of Europe” have already adopted friendly positions towards farmers and industries and, for example, have opposed policies aimed at reducing the use of insecticides. European lawmakers may also act to limit funding for implementing green laws, such as those related to ecosystem restoration.
Delay in nuclear fusion super project
Project managers for the Large Experimental Nuclear Experimental Reactor (ITER), which has been in the works for decades, are expected to announce a new completion date this year, putting the “first plasma” test beyond 2025.
This facility under construction in France at a cost of tens of billions of dollars for the international partners of this project is supposed to prove the feasibility of nuclear fusion as a carbon-free energy source, but it has been facing problems.
The COVID-19 pandemic delayed the production of parts; Some parts of the reactor were wrongly designed and shaped and did not fit in the work. The cooling pipes were worn out and corroded, and the French Atomic Regulatory Organization was not sure of the project’s safety.
The new head of this project is trying to restore the construction and implementation work to its routine. He is expected to announce a new and revised plan this year, but told a fusion energy conference late last year that “it’s not going to be good news.”
Cooperation with local experts
After centuries of colonial wars and decades of exploitation by some scientists, many indigenous peoples have hesitated to interact with researchers, but hopes have been created for reconciliation between the two sides and more research projects under the guidance of indigenous peoples aim to bring indigenous knowledge from the world into Western science. do
In the new year, new contributions may be made based on the excellent examples of the past year, including the study of the North American horse breed. The American National Science Foundation supports the development of efforts with 30 million dollars in five years to create a new scientific center in this field, and some other American institutions have allocated funds in this field to cooperate with universities.
Although some areas of past tension still remain, new models of cooperation will likely be created in the new year.
The launch of the expensive “Europa” probe
The last scientific news in the new year is the launch of the expensive “Europa” probe. NASA’s five-billion-dollar Europa Clipper probe is scheduled to launch this October with a SpaceX Falcon Heavy rocket, and it will be NASA’s most expensive planetary exploration mission since the Viking Mars mission in the 1970s.
Europa, one of the large moons of Jupiter, has an icy crust several kilometers thick, under which there is a large salty ocean that could potentially be a place for life to grow.
When the Clipper probe arrives at its destination in 2030, it will not directly sample the ocean but will fly by the moon 50 times, scanning its surface and gathering clues about the moon’s interior.
Scientists had hoped that this probe would be able to follow up on clues related to telescopic investigations of an active eruption from the side of this moon into space, but recent efforts with NASA’s James Webb Space Telescope did not find any evidence of this issue.
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