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por Rudraksh ChauhanHey, there. Welcome to our deep dive into the history of quantum computing, a journey that blends physics, computer science, and a touch of sci-fi magic. From the early musings of quantum theory to the revolutionary breakthroughs of today, we're unraveling how this mind-bending technology came to be, and why it's reshaping the future of computation. Let us begin our journey. What if I told you that right now, scientists are building computers so powerful they could break every password on the internet in seconds or simulate the behavior of every atom in your body at the same time? This isn't science fiction anymore. Welcome to the world of quantum computing, where the rules of regular computers don't apply. Today, we're going to explore how this mind-bending technology went from a crazy idea in a physicist's notebook to machines that could change everything we know about computing. We'll trace the complete journey from the 1980s when scientists first dreamed of quantum computers to today's race between tech giants to build the first truly useful quantum machine. By the end of this video, you'll understand not just what quantum computing is but how we got here and why everyone from Google to IBM is betting billions on this technology. Let's start at the very beginning, back in 1981. A brilliant physicist named Richard Feynman is giving a talk at MIT. He's frustrated because even the most powerful computers of the time can't properly simulate quantum physics. The math is just too complicated, and regular computers handle information in a way that's completely different from how quantum particles behave. So Feynman asks a simple but revolutionary question: What if we built computers that work the same way quantum particles do? What if instead of fighting against quantum weirdness, we use it to our advantage? This was the spark that started everything. But before we go further, let me explain why regular computers struggle with quantum problems. Your laptop processes information using bits, which are like tiny switches that can be either on or off, representing one or zero. Everything your computer does, from playing videos to running apps, comes down to manipulating millions of these ones and zeros very quickly. Quantum particles don't work this way at all. They can exist in what scientists call superposition, which means they can be in multiple states at the same time. Imagine flipping a coin that stays spinning in the air forever, being both heads and tails until you catch it. That's kind of how quantum particles behave. They also have this property called entanglement, where particles become connected in such a way that measuring one instantly affects the other, even if they're on opposite sides of the universe. So Feynman's idea was to build computers using these quantum properties instead of regular bits. These quantum computers would use quantum bits, or qubits, that could be in superposition and entangled with each other. But having a good idea and actually building the thing are two completely different challenges. In the early 1980s, most scientists thought quantum computers were interesting in theory but impossible to build in practice. The main problem was decoherence. Quantum states are incredibly fragile. Any tiny disturbance from the environment, even a single photon of light or vibration, can destroy the quantum properties you need for computation. But some scientists weren't ready to give up. In 1985, David Deutsch at Oxford University wrote a paper that many consider the foundation of quantum computing theory. He described how a quantum computer could, in principle, solve certain problems exponentially faster than any classical computer. This caught the attention of mathematicians and computer scientists around the world. Throughout the late 1980s and early 1990s, researchers began developing the theoretical framework for quantum algorithms. Nobody had actually built a working quantum computer yet. Then in 1994, everything changed. Peter Shor, a mathematician at Bell Labs, discovered something that made everyone sit up and pay attention. Shor developed an algorithm that could use a quantum computer to break the encryption that protects most of our digital communications today. This wasn't just academic curiosity anymore. Shor's algorithm meant that quantum computers could potentially crack the codes that keep our credit card numbers, emails, and government secrets safe. Suddenly, governments and businesses around the world realized they needed to take quantum computing seriously. The race to build a practical quantum computer. But Shor's algorithm also revealed something important about quantum computers. They're not necessarily faster at everything. For many everyday computing tasks, classical computers work just fine. Quantum computers are more like specialized tools that can solve specific types of problems much faster than any classical computer ever could. In 1996, Lov Grover developed another important quantum algorithm. Grover's algorithm showed that quantum computers could search through bot and unsorted databases much faster than classical computers. While a classical computer might have to check every item in a database one by one, Grover's algorithm could find the answer by checking roughly the square root of the total number of items. The first real quantum computers were tiny, with just a few qubits, and they could only run for fractions of a second before decoherence destroyed their quantum properties. In 1998, researchers at MIT and IBM built some of the first working quantum computers using nuclear magnetic resonance. These early machines could only handle two or three qubits, but they proved that quantum computing could work in practice. Around the same time, scientists developed different approaches to building qubits. Some used trapped ions, others used superconducting circuits. Each approach had its own advantages and challenges. The 2000s brought steady progress, but it was slow. The qubits were too unreliable, and the computers couldn't run long enough to solve real-world problems. But researchers kept improving the technology, learning how to isolate qubits better and reduce the effects of decoherence. Then in 2007, a Canadian company called D-Wave announced they had built the first commercial quantum computer. This created a lot of excitement and controversy in the quantum computing community. D-Wave's approach was different from what most researchers were hu- way- working on. Instead of building a universal quantum computer that could run any quantum algorithm, D-Wave focused on a specific type of problem called quantum annealing. Their computer was designed to find the Sump it all, wat greft in krath of blood, do sum to problem called quantum annealing.Their computer was designed to find the Fluggy Wave Store, 96% from V waves. One does while locking with chains or your walks. And was lowest energy state of a system, which could be used to solve certain optimization problems. Many scientists questioned whether D-Wave's machines were really quantum computers or just very sophisticated classical computers. Meanwhile, the big tech companies were starting to pay serious attention to quantum computing. IBM had been working on quantum computing research for years, but around 2010, companies like Google began investing heavily in the field. In 2013, Google partnered with NASA to buy a D-Wave quantum computer for their quantum artificial intelligence lab. IBM continued developing their own approach using super conducting qubits. Microsoft took a different path, working on a theoretical approach called topological quantum computing that promised to be more resistant to errors. The 2010s saw rapid progress in quantum computing. The number of qubits in experimental systems grew from just a few to dozens and then to hundreds. In 2016, IBM made a bold move that democratized quantum computing research. They launched the IBM Quantum Experience, which allowed anyone with an internet connection to run experiments on a real quantum computer through the cloud. This opened up quantum computing to students, researchers, and hobbyists around the world who couldn't afford to build their own quantum labs. Thousands of people began experimenting with quantum algorithms for the first time. But the real breakthrough came in 2019. Google announced that their quantum computer had achieved something called quantum supremacy. They had performed a specific calculation in 200 seconds that would have taken the world's most powerful classical supercomputer 10,000 years to complete. The calculation itself wasn't useful. It was designed specifically to be hard for classical computers but easy for quantum computers. But it proved that quantum computers could actually outperform classical computers at something real, not just in theory. IBM disputed Google's claim, saying that with better algorithms, a classical computer could solve the same problem much faster than Google claimed. This sparked a friendly but intense competition between the tech giants to demonstrate quantum advantage in more practical applications. But quantum computing still faced major challenges. The biggest problem was errors. Current quantum computers are what scientists call noisy intermediate scale quantum devices, or NISQ computers. The quantum states are still... IBM disputed Google's claim, saying that with better algorithms, a classical computer could solve the same problem much faster than Google claimed. This sparked a friendly but intense competition between the tech giants to demonstrate quantum advantage in more practical applications. But quantum computing still faced major challenges. The biggest problem was errors. Current quantum computers are what scientists call noisy intermediate scale quantum devices, or NISQ computers. The quantum states are still fragile and errors accumulate quickly as calculations get more complex. To build truly powerful quantum computers, we need quantum error correction. This means using many physical qubits to create one logical qubit that's protected from errors. Most estimates suggest we'll need hundreds or thousands of physical qubits for each logical qubit. That means a practical quantum computer might need millions of physical qubits to run complex algorithms reliably. In 2021, IBM announced a roadmap to build quantum computers with over 1,000 qubits by 2023. Google is working on building quantum computers with millions of qubits for error correction. Other companies are exploring different approaches that might need fewer qubits or be more resistant to errors. Meanwhile, researchers are finding ways to get useful results from today's noisy quantum computers. Some companies are already using quantum computers to help design new materials, optimize financial portfolios, and improve machine learning algorithm. The promise of quantum computing, the ability to solve problems that are completely impossible for classical computers may be decades away. So there you have it: the incredible journey of quantum computing from a weird observation about light behaving strangely to a technology that might reshape our world. We've gone from Feynman's wild idea in 1981 to Google's quantum supremacy demonstration in 2019. The story of quantum computing shows us how the strangest discoveries in science can eventually become the most powerful technologies. Who would have thought that particles existing in multiple states at once could lead to computers that might, comforting solve climate change, discover new medicines, or break all our current encryption? What do you think about the future of quantum computing? Are you excited about the possibilities? Thank you for watching. I truly appreciate you sticking with the video till the end. Your time and support mean a lot. Hope it was worth the watch.
