Dear New Mind Creator's, I would suggest you to always attach the Source and References of the topic that you are displaying. This would ensure that whatever content you have created can be reviewed critically by your viewers. Thank you!!🤗🤗
You did an amazing job. I'm a software developer who double majored in Computer Science and Physics. Representing the qubit states as positions on the surface of a sphere did wonders for my ability to actually grasp the transformations being done upon them. This paired with working through and explaining the fundamental gates was an absolute banger of an educational service. Thank you. I can't imagine having to learn this in a classroom as opposed to a video. I probably spent twice the video's length rewinding and repeating pieces of dialog until I could parse them out fully.
@@dynodyno6970 I don't know why that feels like such a big question. I don't feel like I can get back into the head of an intro-course computer scientist anymore, but I do have some things to say? - My understanding is that intro comp sci is a filter class. It gives you a taste, and it turns people away who get too frustrated at the kinds of problems computers throw at you. After this course, *it's all design philosophy*, until much later when you take Algorithms & Data Structures and Computer Architecture. The design philosophy classes will seem like obvious vague uselessness, UNLESS you've actually experienced the pain of trying to make a respectably sized program without good design first. Scraping together a program at 3am that barely does the thing you want it to do IS NOT SO DIFFICULT. What is extremely difficult is trying to make sense of the code and modify it in the morning, so that you can improve it and add new features. Until you've experienced the pain of trying to work with badly designed code, you won't understand design philosophy. However, the design philosophy you're taught may be woefully out of date. You'll probably be recommended a book like "Clean Code", which if I understand correctly, is very out of date, and you should not read it. I'm currently reading one called "A Philosophy of Software Design", published in 2018. I've only been employed for a year and a half as a full stack web developer, and I'm only now appreciating what it has to tell me. - You'll probably have an easier time learning from videos than from text books. - You likely won't really understand something until you've tried to build with it. - Patience. Frustration is the mind killer. - Those error messages are indeed telling you what's wrong, but they can be hard to understand given your lack of knowledge in your first course. - Googling problems and best practices is MUCH OF YOUR JOB. Get really really good at writing search queries. The answer to your problem is out there 95% of the time, you just need the right query to find it. - I'm tired now bye Why are you taking intro comp sci? I feel like I could think of more things if I knew why you were interested, and maybe which subdomain of comp sci you were drawn towards.
Hello. Do you think I can do my master's degree in astrophysics if I choose computer engineering for my undergrad ? I love physics but there is practically no jobs for it in my country so I'm doing that just to be safe if I don't travel
@@kepler-452b7 First of all, I'm in my early twenties, so I'm not the bastion of knowledge you may think I am. Secondly, lol, I kinda did something like that. When finishing my Physics major, I realized that I would need to go to grad school for physics if I wanted to have marketable skills in it. I did not want to do this, so I quickly pivoted and was able to BARELY complete a second major as Computer Science. I didn't know what I wanted to do, but I knew that being good with computers could kinda make me useful anywhere I choose to go. *If you can*, I personally think it's a great idea to also do Computer Science. Worst case scenario, you'll be employable. But also you'll be able to create more astronomy tools for yourself. As a junior in high school, I did a project with the local university where we combed through Kepler data and used Python to turn some of the raw data into a huge folder of images of photometric curve graphs. I was a dunce when it came to Python at the time, but now I could have been so much more helpful.
6:15 - this measurement is supposed to be in core years, not years per core. Core years means that your productivity is the product of the number of cores you have and the number of years you work. So 20 core years could mean 1 core working for 20 years, 2 cores working together for 10 years, or 20 cores working together for 1 year. if more difficult problems were said to take more "years per core", that would mean that adding more cores would make the problem take longer to solve, which doesn't make sense for this problem, unless large clusters of CPUs unionize and go on strike.
This has been by far the best explanation of quantum computing I've seen on youtube. Both very accessible language but also deep information. Thank you! Can't wait for part 2!
the 'quantum mechanics' part of this video starts at around 6:34. Prior to that, the video talks about computer architecture and algorithmic complexity. That in itself is the best explanation I've ever come across.
This is the first in depth quantum computer video I’ve found in years! I was so interested in the subject, but couldn’t find a video explaining what those « quantum gates » were in detail. Really looking forward to watching part 2, keep it up!
Proton proton collusion and wave theory fo light can help you understand together with peridodontitis and ostheomielitis in the heart and endocarditis. Then you go to synapsis and neural transmission which is 1-120 m per second, and then you can understand the computer ;). First learn the human neuronal system then you move to computer and then only being a psychopath you can make logic of all this, as for me what tryed to do still is unknown for me.
In fact, New Mind's approach is what I hope to be the new wave of edu YT, embracing the technical details with clarity and focus (and amazing visual support). I watched a lot vids about quantum computing and all I got was a little more than knowing it exists. But with NM I am left both enlightened and fascinated. So I encourage you: don't shy away from fairly mundane but poorly understood science.
As a Mechatronics engineer I understood pretty much nothing and loved it at the same time. It would be interesting to see how a computer like this would work step by step in a simple program.
If you mean conceptually solving an example math problem using the gates, I think that's exactly what he's going to be the 2nd video. Looking forward to it, too.
During this summer I participated in a quantum computing camp where we learned all of these concepts, and even got to code them on really quantum computers. Thank u for the video, it's really good for reviewing those concepts!
Is part 2 going to include how these quantum gates are created? I liked the visual representations of them in the video, but I struggle to understand how one goes about actually making one of these gates. Is similar to conventional logic where transistors are combined to create gates so the quantum equivalent would be using qubits to create quantum gates?
I don't think he's going to go into how gates are made. Probably the limitations of use as a quantum computer needs to run somewhere near absolute zero.
I'll be focusing more on the how the concept can be utilized for practical computing and the algorithms that are designed around it. Though I will touch a bit on the physical aspects and it's shortcomings. It's still a highly theoretical field.
The construction of the gate highly depends on how the qubits are physically represented. For example, if the qubit is polarization of photon, than a mirror is a single-input logic gate (it reflects the polarization along certain an axis). So is a delay line (shifts the phase). For electron spin, such logic gate could be a magnetic field applied in specific direction for certain amount of time. Where it gets complicated are multi-input logic gates. You need some way to make the qubits interact in way that puts them in superposition. With photons, this is nearly impossible. With superconductor-based circuits logic gates are somewhat easier to construct, but moving the qubits is harder. In general, the quantum gate is not a device. It is a process you apply to the qubits that are stored somewhere.
Like KohuGaly said, there is more than one way to skin Schrödinger's cat. With classical computing for example, you could implement logic gates using whatever you want really, as long the inputs and outputs behave as expected: You could use voltages on wires Or water in containers: ua-cam.com/video/IxXaizglscw/v-deo.html Or mechanical force in legos: ua-cam.com/video/5X_Ft4YR_wU/v-deo.html Or redstone in Minecraft: ua-cam.com/video/ggHEpL87i-I/v-deo.html We just got really good at making them really small and fast using transistors so that's what we do. Boolean logic existed long before computers did, it took a lot of effort to get our physical representations to be as fast and efficient as they are. Likewise, with quantum computing, the math is there, the race is now to design and build the best platform for it to run on. And that could mean fastest / cheapest / easiest / warmest / etc. Unlike with classical computers, even in 50 years, there will likely still be multiple designs which use different types of qubits that are best suited for their specific applications.
Thanks for your clear and concise intro. I'm struck by both your grasp of what's essential and by your ability to cover a lot of territory without feeling hurried.
I've never needed a "part 2" this badly, that was an AMAZING explainer in the second half. I feel like I finally understand quantum computing enough to start poking at it, and I'm so hyped to see where this technology goes. One note - entanglement doesn't allow for faster-than-light communication. If I recall correctly, it still requires 1 bit of classical information to make the entanglement happen, and using the qubit destroys it, meaning you need to do more entanglement. Or something to that effect. Googling "quantum entanglement faster than light" should give you what you need. That's still _really_ fast, because it essentially means computation and information is all at the speed of light. You're not running on metal and silicon -- you're running on reality itself.
Yes, I have yet to see anything show that quantum entanglement is effectively different from if I wrote A and B on pieces of paper, sealed them in separate envelopes, gave you one, traveled ten million light years in the opposite direction of you, opened my envelope and seeing that it has A written on it, learn that your paper says B, and therefore claim I have moved information faster than the speed of light. It is very tempting to think it may be possible to transmit data faster than light, and people try to concoct ways to do it with entanglement, but it seems that even when it appears possible on paper there's some physical reason it doesn't actually work. Similar to other areas of science, like perpetual motion machines. There are meaningful differences versus my A/B example, I can't remember what they are but they are interesting and people are trying to find applications... But none of them break "information conservation", or you'd see money pouring into the first video feed of the future. Sadly, no ansible for us anytime in the near future, it seems.
@@craigslist6988 I don't think the A/B example is accurate. It's mathematically guaranteed that the two will be the same, you just don't know which one until you open it. I don't think the actual, provable math ever showed faster than light information travel was possible - that's just something people keep saying.
Incredible video, love the practical emphasis but I'd also love to understand how these gates actually work, highly doubt there's a better explanation than what you could provide out there. Either way, looking forward to part 2 :)
This gets a bit into it ua-cam.com/video/-UlxHPIEVqA/v-deo.html and this presentation has some detail as well quantum.phys.cmu.edu/QCQI/QC_CMU2 ...but it is a lot harder to find (right now) than the theory. (I haven't listed to it, by ua-cam.com/video/A750loExcbM/v-deo.html might have promise as well.)
Can’t wait for quantum computing to be used for its real purpose. Programming actual AI responses and keeping track of complex relationship matrices in Visual Novels.
Bro you're crazy :D How can you so casually make a video on such a complicated topic. Like it's as easy as 2+2 for you. The animations/explanations are so beautiful at the same time!
I've been watching videos about quantum computing since 2017. I still feel like I don't really get it, but I hope to see the technology advance! Who knows? In 20 years, a gaming PC might be powered by a GPU with quantum acceleration built in!
> I don't really get it it means you know something about physics, and yor mind has a strong grip of reality. all this Q. computing stuff is a YYYUGE HOAX
Part 2 will probably shed some light on why they probably won't ever be found in general purpose computers- If quantum computing even becomes practical.
@@NewMind I feel like, it can be useful for specific tasks such as GPUs used for visual computing. We might see QPU as an additional component in maybe the next 3-4 decades.
@@NewMind That's a bold statement to make saying quantum computers won't be around for normal people. I'll be back to prove you wrong in the future. For now I'm waiting for part two.
Qubits that are entangled, when measured, their outcomes aren’t dependent on each other therefore there is no “communication” happening faster than the speed of light. Their states were set when they were entangled
I never understood this quantum bit hype as seeing that it's purely based on probability, I thought that it could fatally produce inaccurate results. And now that you've explained how these probability could be manipulated using gates and advanced math stuffs. As a math lover, I certainly feel proud knowing that these thousands of years of math discovery can be finally given a justification to how these math stuffs can be applied. What a time to be alive
The most unfortunate thing about quantum computing is that its not really computing in a sense that would be general. This means that the programs are only for a single purpose, which means that quantum computers are really quantum devices. General programmability is something that is likely not going to happen any time soon as there are quite many challenges in making our deterministic models of computation relate to the inherently stocastic model of quantum computing. So its doubtful that any generalized augmentation of current computer capabilities would be likely yet. The entire concept of quantum computing is still really interesting.
Wouldnt it be a good idea to combine traditional hardware with quantum hardware? You could build all kinds of unprogrammable small quantum circuits that are used all the time and connect these via classic electrical components that are able to be programmed. So by programming the connections between the inputs and outputs of every quantun circuit you might be able to create adjustable software.
All programs, even classical ones, are single purpose. Quantum computers, as envisioned currently, have a finite register of qubits, a set of quantum logic gates that can be applied to arbitrary qubits in the register, and a classical control unit, that schedules which gate is to be applied. The quantum register of N qubits represents a unit vector in 2^N dimensional complex-valued space. The quantum computer can perform any length-preserving reversible linear transformation of that unit vector, in polynomial number of steps. A classical computer would need exponential memory and time to perform such operation. The quantum computer is practical to use only if the problem at hand can be expressed as aforementioned transformation and no polynomial-time/memory classical algorithm is known. I don't think that a quantum computer with quantum control unit is possible.
There's a very interesting paper by Ben Barlett from Stanford last year that proposes a design of quantum computer that could be truly reprogrammable, as it is essentially a classical computer with access to a bunch of qubits circulating in a loop that can be reused whenever. You're right that figuring out how to program these things is difficult, but there were some very interesting talks about programming languages for hybrid classical-quantum programs this year at the QPL conference that you might want to check out. In particular I thought Finn Voichick's talk on Qunity was super cool, as it models measurements through exception handling! I would avoid the talks on Quipper unless you're a category theory wizard.
Totally loved the video, I don't know if enough people on UA-cam will be interested on this topic, but i'm making sure i like and comment to show my appreciation! Thank you for this video😊😊😊😊❤❤
One way to think of this is that the wave particle duality of light and matter in the form of electrons is forming a blank canvas for us (atoms) to interact with; we have waves over a period of time and particles as an uncertain future unfolds. The mathematics of quantum mechanics represents the physics of time with classical physics represents processes over a ‘period of time’ as in Newton's differential equations. In this theory the mathematics of quantum mechanics represents geometry, the Planck Constant ħ=h/2π is linked to 2π circular geometry representing a two dimensional aspect of 4π spherical three-dimensional geometry. We have to square the wave function Ψ² representing the radius being squared r² because the process is relative to the two-dimensional spherical 4π surface. We then see 4π in Heisenberg’s Uncertainty Principle ∆×∆pᵪ≥h/4π representing our probabilistic temporal three dimensions life. The charge of the electron e² and the speed of light c² are both squared for the same geometrical reason. We have this concept because the electromagnetic force forms a continuous exchange of energy forming what we experience as time. The spontaneous absorption and emission of light photon ∆E=hf energy is forming potential photon energy into the kinetic energy of electrons. Kinetic Eₖ=½mv² energy is the energy of what is actually happening. An uncertain probabilistic future is continuously coming into existence with the exchange of photon energy.
One thing I always loved about figuring out Even/Odd numbers is that you don't need to use a loop or even use the modulus operator. The beauty of X & 1 is hard to beat, just check if the last bit is set. And since 1 and 0 are considered true or false, you don't even need to check if it's equal to anything. The modulus operator is quite expensive at much larger numbers (depending how its implemented in the language), which tbh I'm sure most programmers here woulda just immediately assumed that was what was going on at 2:30
It is not even remotely related to how the programming language implements it. It's implemented via the CPU and is very quick. It's still much slower than simply bit and, but still quick. And also, you do have to negate the result. If the last bit is not set, it's even. So, for checking if the number's odd, no negating would be required, but with checking whether it's even, it would.
@@shambhav9534 I'm sorry, but you're correct and incorrect. Yes, the CPUs ALU literally does some things on it's own, I'm just saying that modulus and divison isn't always implemented the way you think it is. And btw, CPU can do the basic commands you commonly know, XOR, OR, AND, add, subtract, etc, but it can't do modulus or division, there's algorithms implemented to simulate that function (To quickly estimate division on AMD cpus they use the Goldschmidt method). And for example, modulus in python is actually implemented with a .c algorithm and the modulus operator just calls to that function. Why do you think theres operator overloading in Python? You can change what the operator does, it isn't prebuilt inside the CPU, the call to a basic command is. The reason why + is addition in almost all languages is because its what we expect it to do. But however, if we implement that weirdly it cause issues, take the language BrainFu*k for example.
@@XenXenOfficial Do you know of the "div" instruction? It does integer division and also provides with the remainder right there in the dx register. Every language will call that instruction. It does not depend on what the language implements. Well, Python does not. I have literally no idea why. And most C compilers will also do some weird dark magic for performance, which I doubt the effectiveness off. But anyway, the fact remains, your CPU can tell you the remainder of a division and no algorithms are required. I can already tell you're not that knowledgeable in this subject (neither am I). You're retelling basic facts as if they are revelations and used the phrase ".c algorithm". I'm not saying this is bad or anything, it's just that I know you're not so experienced. I'm no psychologist; I may be wrong (don't complain if I'm wrong). This doesn't imply that I'm an expert though, or that I know more than you. I just made a prediction and am waiting for you to reply to see if I'm right.
@@shambhav9534 You're correct the DIV instruction exists, but that's on other architectures like POWER FAMILY. I personally feel like we're both correct and both have inaccuracies in our comments, but I also know personally that programming languages are a human created contruct with their own definitions on what is & is not, and I know that unless you truly know what's going on under the hood of a language, you can't truly say or know what it's doing. That's also why some languages are more efficient in some use cases, like you wouldn't use Python for genuine software cause of their type juggling, but that can also go for JavaScript or even C for their type casting. That's all under-the-hood things you wouldn't know unless you just... Know. And I bring that up cause it applies the same to modulus
Addition is actually faster than O(n) (linear) time. Addition can be done in O(log(n)) time (which is **a lot** more efficient than just linear time) by using "carry look ahead" addition. A better example of a linear time algorithm would have been to find the maximum or minimum value in any list - there is absolutely no way to do it faster than linear time as you need to check each element for whether they are the largest or smallest element encountered.
Don't you still have to check each of the bits you "skip" (making it an O(n) algorithm)? I'm talking pure algorithm here, not specialized, parallel hardware that can look at all of the bits at the same time and "cheat" the time complexity by moving the carry past several bits at a time. (Is it called "parallel time complexity"?)
For anyone looking to dig deeper, "Quantum Computation and Quantum Information" by Michael Nielsen and Isaac Chuang is a great text on this topic. I recently started reading it, and I'm already struggling with the math in it, so I try to pick it up needed as I go cuz this stuff is so damn interesting.
Thank you, this was soooo good. Admittedly I did not understand it as much as I would have liked but it is the very first time I’ve ever watched a video or read an article where I honestly believed the author knew how quantum computers actually worked. It has been repeatedly disappointing to read the title of an article/video and to find out quite quickly that the author has no idea what they are talking about. I very much look forward to the rest of the series. 😊👍
Wow that was awesome thanks so much I learnt a lot particularly about the logic quantum gates. Also I never knew about the speed of entanglement I assumed it was instantaneous. Really looking forward to future videos from your channel. Keep up the quality content.
I have listened to many explanations of quantum computing, and your video was the first that got me to actually understand. Thank you. I intend to pursue this field.
QUESTION: Entanglement: One particle can be both positive or negative unless measured, and consequentially the 'twin' antiparticle will be the opposite unless we measure the first one... Well, is it not that the first particle 'is already' positive or negative, but we simply cannot know before measuring, and consequentially the twin 'is already' the opposite? I am totally ignorant of physics, except for youtube videos... But i never see these question explained... Do you have an answer? Thank you so much! 😊
congrats friend... Linear algebra and general geometry helped me to fully grasp the content without ever directly studying quantum computing, although i suspect, one day, as a software engineer i will have to study it. The idea that ortogonality implies dimensionality, with weak or semantics codependency, helped me a lot to intuitionally visualize the importance of phase and the z axis rotations. also nlp models helped me on understading how we can encode oposition and the degree of this oposition into 180 vectors of variable length from 0 to 1 with origin from the center of the semantic space. Thanks man.
Finally... I never understood how we could leverage a non-deterministic phenom to generate must be deterministic results, and your explanation that we would collect statistical data from many iterations and probably empirically test the outcome made it clear to me. Probably one feature of this kind of computation will be precision treshold sufficiency, when the result is good enough to not demand further narrowing of the probability distribution for the empirical phase.
*Quantum circuit is a great model of quantum computing* A quantum register is simply a sequence of entangled qu-bits. A quantum circuit is simply a network of quantum logic gates. Together they make up a Quantum computer. Physically a qu-bit could be implemented using Electron spin (up vs. down) or photon polarization (horizontal vs. vertical).
Thanks for this, I finally start to understand quantum computing. The stuff you usually hear does not help "q-bits are in a superposition" - well and how does this help exactly? Phases! As an electrical engineer an "of course!" moment.
Awesome Video, this is a really cool introduction to quantum computing. However I think you made a small mistake, whenever talking about the timecomplexity of the addition algorithm at 3:15. Everytime you multiply the input-number by 10, you add 1 computation step. This algorithm is therby logarithmic, not linear. This is obviously not very important to the main takeaways from the video though
It's a little unintuitive but the video isn't actually wrong here. Because in the video n, or the size of the input, refers to the size of the number (either in bits or digits). A list of 1000 elements has 10x the number of elements as a list of 100, but the number 1000 compared to the number 100 only has 1 more digit, and adding a digit always only adds 3 or 4 bits, not 10x the number of bits. This is why brute forcing a range of numbers with a constant time test, which would normally be thought of as linear time, is exponential time in the video.
Your animations are just MINDBLOWING DUDE!! Couldnt take my eyes off em! And gr8 work explaining this. I've been delving into this domain for some time now and this is simply ONE OF THE BEST introductions I've found.
The use of Hadamard and CNOT gates to manipulate entanglement is related to the concept of "entanglement swapping." While this can create correlations between distant particles, it still doesn't allow for faster-than-light communication. The outcome of the entanglement is random and cannot be controlled to transmit specific information.
Wow, really powerful. Only using state superposition and entanglement. That's fantastic. Anyway I have a degree in physics engineer and another in mechatronics engineering. I would love to work with this kind of things😍. Basically we could bypass P vs NP problem using quantum computer. Nice! If I understand well, since measuring will collapse the state, if we want to have "control"we should have a model in order to estimate the probability of a state in any point in the quantum circuit architecture and obviously know apriori the overall architecture that we are using for solve a specific problem. So we collapse the measure only in some strategical point ("end states") millons of time and make a probability profile in order to get the final answer. I think that I will study more about the quantum logic gate and all this stuff. Totally loved the control gate part. 🔝🔝🔝
I was a subscriber from your first video and I knew that channel was going to grow big. You are the only channel that I actively visit to rewatch some of your videos. They're so packed with information and it's worth to watch them multiple times. Wish I had the time to watch all your videos multiple times.... :)
Wow...I liked the video because I couldn't understand any of these😉. Some of it sounded like 'Infinite probability drive ' to me. I am fascinated. ...Thank you for posting this...I think I am going to try better to understand this.
Thank you so much! I've tryed to understand the gates so many times, but this sums it up for me to understand it enough with the basic knowledge I've been accumulating about quantum physics!
Quantum computing is like asking me to build something then make an electrical diagram instead of a blueprint. I can think of some genius solution, put it in a mechanical drawing and build it, but ask me how the electrics work, I'll just wave my angle grinder at you and use my Jedi mind tricks. "This is not the right engineer you're looking for. Go two doors down, make a left and ask for Jeff. Move along."
Want your video to get tons of engagement? Simple! Just slap on some suspenseful tech-vibe music in the background and keep repeating, "A qubit can be both 1 and 0. This is called superposition."
I finally feel like I really understand what's going on with these things. That was great! It does sadden me, however. Since I very likely will never have the power of such a computer at my fingertips.
Off! Thank God you are alive. I subscribed you after watching that Switzerland flywheel bus video. I believe you upload video once in a month. It's my eager request to increase the frequency a little bit. Not much, just one in 15 days. Anyway thanks for this video. 👍🏼
@@NewMind oh I am sorry. I didn't know that. It's perfectly fine. Once in a month is also a good frequency 😄. Why don't you upload your content on nebula. That platform is made for quality content and made by quality people like you. Actually I am a curiosity stream and nebula subscriber for almost a year. I have been following their engineering and physics, math contents as these two are my favourite subjects. I don't know about their monetisation strategy. But if that helps you and if you wish to join, tell it to your next video. I will pay my subscription fee by using your promo code for sure in November 2022 for one year subscription.
In a nutshell, if you enter a problem into a quantum computer as a string of 1's and 0's, it will re-arrange them in such a way as to optimize its quantum state. If these 1's and 0's represent an initial non-optimized state of a physical system, the result will be the optimized state of that system. Therefore quantum computers can solve optimization problems in a fraction of the time compared to traditional computers.
To me, the hardest part of understanding quantum computers, is my brain trying to equate (translate) quantum to binary computing concepts, which makes it difficult to process. I would compare it to learning languages, if you try to force one language into another, it will be a struggle, however once your brain manages (with practice) to isolate and unlink the different languages you know, it becomes seamless.
what ive found is that quantum computers are just barely different enough that it's not really worth going about it in that way if you can help it; note how in the video he calls it an offshoot of quantum mechanics exploited by computer scientists, rather than an offshoot of CS suited to the quantum physicist trying to recover those same computing concepts without needing "binary" or implying a necessarily digital information-theoretic framework as a starting point is a thought experiment that i feel can illustrate this pretty well
Really looking forward to the second part because this first part was really REALLY well done. Sound Desing, Graphics and over all Information was perfectly compromised into a really informativ and nice to watch video. Great Job
▶ Visit brilliant.org/NewMind to get started learning STEM for free, and the first 200 people will get 20% off their annual premium subscription
Dear New Mind Creator's, I would suggest you to always attach the Source and References of the topic that you are displaying. This would ensure that whatever content you have created can be reviewed critically by your viewers. Thank you!!🤗🤗
15:54 bro forgot his voice was gonna get uploaded to youtube for a second
Wow that Hademar gate , lets me think " ..beam me up Scotty"..lol
Grtz from the netherlands
Johny geerts
en.m.wikipedia.org/wiki/Injection_locking#Entrainment
PLEASEEEEEEEEEEEE WHERE IS PART 2 PLEASEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE
We desperately need more quantum computing videos that aren't just repeating "a q-bit can be both 1 and 0 at the same time".
exactly.
Lol
Please start making some.😁
dont forget that quantum entanglement is also repeated many times either
Yeah for real. Leaves us who understand this better than the average person just hanging around
I can't wait to watch this and not understand anything
Just take it in and let your brain sort it out while you sleep. That's how I learned to do a backflip 😆
İm almost through. Didnt understand Jack.
@@NewMind wait are you Max Deutsch? The guy who defeated magnus Carlson with a mental algorithm?
@@NewMind proof video when?
Feels pointless to watch if you’re not heavily involved in computer science already
00:10 The Algorithm
00:53 Binary data- logic gate types
01:10 CPU
01:30 Digital computing- processors
02:13 Algorithms complexity
02:22 Constant time algorithms - most efficient
02:55 Linear time alorithms
03:38 Brute Force Method
04:55 Exponential time algorithm
05:12 Intractable property
05:35 RSA algorithm
06:00 Why exponential problems require Quantum Computers
06:24 History of quantum mechanics-physics
06:46 Paul Benioff
06:54 Richard Feynman
07:28 Quantum Computers
07:35 Bits
08:23 Quantum Comp- probabalistic
08:32 Coherent Superposition
09:06 Quantum phenomena
09:24 Phase component (wave) interference
10:12 Quantum circuit
10:50 Statistical probabality
11:20 Bloch Sphere
12:04 Quantum logic gates
12:15 Quantum gate vs classical gate
12:29 Pauli gates X, Y, Z (180)
13:18 Hadamard Gate H
14:24 S (45), T(90) Phase gates
14:43 Composite Gates Rx, Ry, Rz, R¥
15:28 Entanglement
15:53 Control Gate- conditional
16:13 Control Not Gate ( C-not)
16:45 Bell State
17:25 Toffoli Gate
17:32 Swap Gate
17:36 CZ Gate
You are welcome 🌹
I think chapters should be added to these sort of videos... thanks
Hero!
Wow, beauty and smart!. 😏👍
Ty, so he never gets to any programming samples/demos at all.
Thanks!
You did an amazing job. I'm a software developer who double majored in Computer Science and Physics. Representing the qubit states as positions on the surface of a sphere did wonders for my ability to actually grasp the transformations being done upon them. This paired with working through and explaining the fundamental gates was an absolute banger of an educational service. Thank you.
I can't imagine having to learn this in a classroom as opposed to a video. I probably spent twice the video's length rewinding and repeating pieces of dialog until I could parse them out fully.
Any advice for first year comp sci?
@@dynodyno6970 I don't know why that feels like such a big question. I don't feel like I can get back into the head of an intro-course computer scientist anymore, but I do have some things to say?
- My understanding is that intro comp sci is a filter class. It gives you a taste, and it turns people away who get too frustrated at the kinds of problems computers throw at you. After this course, *it's all design philosophy*, until much later when you take Algorithms & Data Structures and Computer Architecture. The design philosophy classes will seem like obvious vague uselessness, UNLESS you've actually experienced the pain of trying to make a respectably sized program without good design first. Scraping together a program at 3am that barely does the thing you want it to do IS NOT SO DIFFICULT. What is extremely difficult is trying to make sense of the code and modify it in the morning, so that you can improve it and add new features. Until you've experienced the pain of trying to work with badly designed code, you won't understand design philosophy. However, the design philosophy you're taught may be woefully out of date. You'll probably be recommended a book like "Clean Code", which if I understand correctly, is very out of date, and you should not read it. I'm currently reading one called "A Philosophy of Software Design", published in 2018. I've only been employed for a year and a half as a full stack web developer, and I'm only now appreciating what it has to tell me.
- You'll probably have an easier time learning from videos than from text books.
- You likely won't really understand something until you've tried to build with it.
- Patience. Frustration is the mind killer.
- Those error messages are indeed telling you what's wrong, but they can be hard to understand given your lack of knowledge in your first course.
- Googling problems and best practices is MUCH OF YOUR JOB. Get really really good at writing search queries. The answer to your problem is out there 95% of the time, you just need the right query to find it.
- I'm tired now bye
Why are you taking intro comp sci? I feel like I could think of more things if I knew why you were interested, and maybe which subdomain of comp sci you were drawn towards.
Avery Lemons
So that would be a no then?
Hello. Do you think I can do my master's degree in astrophysics if I choose computer engineering for my undergrad ? I love physics but there is practically no jobs for it in my country so I'm doing that just to be safe if I don't travel
@@kepler-452b7 First of all, I'm in my early twenties, so I'm not the bastion of knowledge you may think I am.
Secondly, lol, I kinda did something like that. When finishing my Physics major, I realized that I would need to go to grad school for physics if I wanted to have marketable skills in it. I did not want to do this, so I quickly pivoted and was able to BARELY complete a second major as Computer Science. I didn't know what I wanted to do, but I knew that being good with computers could kinda make me useful anywhere I choose to go.
*If you can*, I personally think it's a great idea to also do Computer Science. Worst case scenario, you'll be employable. But also you'll be able to create more astronomy tools for yourself.
As a junior in high school, I did a project with the local university where we combed through Kepler data and used Python to turn some of the raw data into a huge folder of images of photometric curve graphs. I was a dunce when it came to Python at the time, but now I could have been so much more helpful.
6:15 - this measurement is supposed to be in core years, not years per core.
Core years means that your productivity is the product of the number of cores you have and the number of years you work. So 20 core years could mean 1 core working for 20 years, 2 cores working together for 10 years, or 20 cores working together for 1 year.
if more difficult problems were said to take more "years per core", that would mean that adding more cores would make the problem take longer to solve, which doesn't make sense for this problem, unless large clusters of CPUs unionize and go on strike.
Thank you for the clarification, was pretty confused since those measurements didn't really seem to add up.
Thanks for clarifying
This has been by far the best explanation of quantum computing I've seen on youtube. Both very accessible language but also deep information. Thank you! Can't wait for part 2!
the 'quantum mechanics' part of this video starts at around 6:34. Prior to that, the video talks about computer architecture and algorithmic complexity. That in itself is the best explanation I've ever come across.
This is the first in depth quantum computer video I’ve found in years! I was so interested in the subject, but couldn’t find a video explaining what those « quantum gates » were in detail. Really looking forward to watching part 2, keep it up!
Proton proton collusion and wave theory fo light can help you understand together with peridodontitis and ostheomielitis in the heart and endocarditis. Then you go to synapsis and neural transmission which is 1-120 m per second, and then you can understand the computer ;). First learn the human neuronal system then you move to computer and then only being a psychopath you can make logic of all this, as for me what tryed to do still is unknown for me.
I always love the voice of the speaker and the word choices too. It is like a silken blanket for my ears and mind
In fact, New Mind's approach is what I hope to be the new wave of edu YT, embracing the technical details with clarity and focus (and amazing visual support). I watched a lot vids about quantum computing and all I got was a little more than knowing it exists. But with NM I am left both enlightened and fascinated. So I encourage you: don't shy away from fairly mundane but poorly understood science.
This was the best single explanation of Quantum computing that I have ever encountered. Thanks.
As a Mechatronics engineer I understood pretty much nothing and loved it at the same time.
It would be interesting to see how a computer like this would work step by step in a simple program.
People already have a hard enough time with ladder logic. Lol
If you mean conceptually solving an example math problem using the gates, I think that's exactly what he's going to be the 2nd video. Looking forward to it, too.
During this summer I participated in a quantum computing camp where we learned all of these concepts, and even got to code them on really quantum computers. Thank u for the video, it's really good for reviewing those concepts!
Do you still use languages like python, java etc? And paradigms like procedural and oop?
What’s the name of the program?
Did you use windows os, Apple IOS or Linux? I bet the computer was already turn on. Did they run a video on the same machine?
Is part 2 going to include how these quantum gates are created? I liked the visual representations of them in the video, but I struggle to understand how one goes about actually making one of these gates. Is similar to conventional logic where transistors are combined to create gates so the quantum equivalent would be using qubits to create quantum gates?
no.
they dont exist.
and they inprinciple can not exist.
case closed.
I don't think he's going to go into how gates are made. Probably the limitations of use as a quantum computer needs to run somewhere near absolute zero.
I'll be focusing more on the how the concept can be utilized for practical computing and the algorithms that are designed around it. Though I will touch a bit on the physical aspects and it's shortcomings. It's still a highly theoretical field.
The construction of the gate highly depends on how the qubits are physically represented. For example, if the qubit is polarization of photon, than a mirror is a single-input logic gate (it reflects the polarization along certain an axis). So is a delay line (shifts the phase). For electron spin, such logic gate could be a magnetic field applied in specific direction for certain amount of time.
Where it gets complicated are multi-input logic gates. You need some way to make the qubits interact in way that puts them in superposition. With photons, this is nearly impossible. With superconductor-based circuits logic gates are somewhat easier to construct, but moving the qubits is harder.
In general, the quantum gate is not a device. It is a process you apply to the qubits that are stored somewhere.
Like KohuGaly said, there is more than one way to skin Schrödinger's cat.
With classical computing for example, you could implement logic gates using whatever you want really, as long the inputs and outputs behave as expected:
You could use voltages on wires
Or water in containers: ua-cam.com/video/IxXaizglscw/v-deo.html
Or mechanical force in legos: ua-cam.com/video/5X_Ft4YR_wU/v-deo.html
Or redstone in Minecraft: ua-cam.com/video/ggHEpL87i-I/v-deo.html
We just got really good at making them really small and fast using transistors so that's what we do.
Boolean logic existed long before computers did, it took a lot of effort to get our physical representations to be as fast and efficient as they are. Likewise, with quantum computing, the math is there, the race is now to design and build the best platform for it to run on.
And that could mean fastest / cheapest / easiest / warmest / etc. Unlike with classical computers, even in 50 years, there will likely still be multiple designs which use different types of qubits that are best suited for their specific applications.
Thanks for your clear and concise intro. I'm struck by both your grasp of what's essential and by your ability to cover a lot of territory without feeling hurried.
I really like the way you maintain standards of your videos. "Made for science not specifically for views". Being an undergrad I like your vids a lot.
This has been the best video I've seen on quantum computing. Respect. I love to learn.
Part 2, Part 2, Part 2…I can’t wait. Really struggling to understand how a problem is encoded and then the solution decoded with quantum computers.
I've never needed a "part 2" this badly, that was an AMAZING explainer in the second half. I feel like I finally understand quantum computing enough to start poking at it, and I'm so hyped to see where this technology goes.
One note - entanglement doesn't allow for faster-than-light communication. If I recall correctly, it still requires 1 bit of classical information to make the entanglement happen, and using the qubit destroys it, meaning you need to do more entanglement. Or something to that effect. Googling "quantum entanglement faster than light" should give you what you need.
That's still _really_ fast, because it essentially means computation and information is all at the speed of light. You're not running on metal and silicon -- you're running on reality itself.
Yes, I have yet to see anything show that quantum entanglement is effectively different from if I wrote A and B on pieces of paper, sealed them in separate envelopes, gave you one, traveled ten million light years in the opposite direction of you, opened my envelope and seeing that it has A written on it, learn that your paper says B, and therefore claim I have moved information faster than the speed of light.
It is very tempting to think it may be possible to transmit data faster than light, and people try to concoct ways to do it with entanglement, but it seems that even when it appears possible on paper there's some physical reason it doesn't actually work. Similar to other areas of science, like perpetual motion machines.
There are meaningful differences versus my A/B example, I can't remember what they are but they are interesting and people are trying to find applications...
But none of them break "information conservation", or you'd see money pouring into the first video feed of the future.
Sadly, no ansible for us anytime in the near future, it seems.
@@craigslist6988 I don't think the A/B example is accurate. It's mathematically guaranteed that the two will be the same, you just don't know which one until you open it.
I don't think the actual, provable math ever showed faster than light information travel was possible - that's just something people keep saying.
Incredible video, love the practical emphasis but I'd also love to understand how these gates actually work, highly doubt there's a better explanation than what you could provide out there. Either way, looking forward to part 2 :)
This gets a bit into it ua-cam.com/video/-UlxHPIEVqA/v-deo.html and this presentation has some detail as well quantum.phys.cmu.edu/QCQI/QC_CMU2 ...but it is a lot harder to find (right now) than the theory. (I haven't listed to it, by ua-cam.com/video/A750loExcbM/v-deo.html might have promise as well.)
Wow. You always manage to dive deep into these topics and not just stop at a basic level like others. Very nice!
exactlyyy
He goes so deep so that he talks bullshit, those who dont have creativity and have low IQ the internet is full of those kind of sharlatans.
@@urimtefiki226 now i'm curious, what was factually wrong here?
Can’t wait for quantum computing to be used for its real purpose. Programming actual AI responses and keeping track of complex relationship matrices in Visual Novels.
Bro you're crazy :D
How can you so casually make a video on such a complicated topic.
Like it's as easy as 2+2 for you.
The animations/explanations are so beautiful at the same time!
I've been watching videos about quantum computing since 2017. I still feel like I don't really get it, but I hope to see the technology advance!
Who knows? In 20 years, a gaming PC might be powered by a GPU with quantum acceleration built in!
> I don't really get it
it means you know something about physics, and yor mind has a strong grip of reality.
all this Q. computing stuff is a YYYUGE HOAX
Part 2 will probably shed some light on why they probably won't ever be found in general purpose computers- If quantum computing even becomes practical.
Noooo
@@NewMind I feel like, it can be useful for specific tasks such as GPUs used for visual computing. We might see QPU as an additional component in maybe the next 3-4 decades.
@@NewMind That's a bold statement to make saying quantum computers won't be around for normal people. I'll be back to prove you wrong in the future. For now I'm waiting for part two.
Qubits that are entangled, when measured, their outcomes aren’t dependent on each other therefore there is no “communication” happening faster than the speed of light. Their states were set when they were entangled
I never understood this quantum bit hype as seeing that it's purely based on probability, I thought that it could fatally produce inaccurate results.
And now that you've explained how these probability could be manipulated using gates and advanced math stuffs. As a math lover, I certainly feel proud knowing that these thousands of years of math discovery can be finally given a justification to how these math stuffs can be applied. What a time to be alive
Maths has been essential to several fields lol why
This is probably the best video on this topic
Thanks for the quantum knowledge, now I have learned something I still don't know
The most unfortunate thing about quantum computing is that its not really computing in a sense that would be general. This means that the programs are only for a single purpose, which means that quantum computers are really quantum devices. General programmability is something that is likely not going to happen any time soon as there are quite many challenges in making our deterministic models of computation relate to the inherently stocastic model of quantum computing.
So its doubtful that any generalized augmentation of current computer capabilities would be likely yet. The entire concept of quantum computing is still really interesting.
Wouldnt it be a good idea to combine traditional hardware with quantum hardware? You could build all kinds of unprogrammable small quantum circuits that are used all the time and connect these via classic electrical components that are able to be programmed. So by programming the connections between the inputs and outputs of every quantun circuit you might be able to create adjustable software.
All programs, even classical ones, are single purpose. Quantum computers, as envisioned currently, have a finite register of qubits, a set of quantum logic gates that can be applied to arbitrary qubits in the register, and a classical control unit, that schedules which gate is to be applied.
The quantum register of N qubits represents a unit vector in 2^N dimensional complex-valued space. The quantum computer can perform any length-preserving reversible linear transformation of that unit vector, in polynomial number of steps. A classical computer would need exponential memory and time to perform such operation.
The quantum computer is practical to use only if the problem at hand can be expressed as aforementioned transformation and no polynomial-time/memory classical algorithm is known.
I don't think that a quantum computer with quantum control unit is possible.
There's a very interesting paper by Ben Barlett from Stanford last year that proposes a design of quantum computer that could be truly reprogrammable, as it is essentially a classical computer with access to a bunch of qubits circulating in a loop that can be reused whenever. You're right that figuring out how to program these things is difficult, but there were some very interesting talks about programming languages for hybrid classical-quantum programs this year at the QPL conference that you might want to check out. In particular I thought Finn Voichick's talk on Qunity was super cool, as it models measurements through exception handling! I would avoid the talks on Quipper unless you're a category theory wizard.
Part 2 please! This was so good. Also viewership generally drops as a series goes on so fingers crossed for a little bit of maths as well :)
Totally loved the video, I don't know if enough people on UA-cam will be interested on this topic, but i'm making sure i like and comment to show my appreciation!
Thank you for this video😊😊😊😊❤❤
One way to think of this is that the wave particle duality of light and matter in the form of electrons is forming a blank canvas for us (atoms) to interact with; we have waves over a period of time and particles as an uncertain future unfolds. The mathematics of quantum mechanics represents the physics of time with classical physics represents processes over a ‘period of time’ as in Newton's differential equations. In this theory the mathematics of quantum mechanics represents geometry, the Planck Constant ħ=h/2π is linked to 2π circular geometry representing a two dimensional aspect of 4π spherical three-dimensional geometry. We have to square the wave function Ψ² representing the radius being squared r² because the process is relative to the two-dimensional spherical 4π surface. We then see 4π in Heisenberg’s Uncertainty Principle ∆×∆pᵪ≥h/4π representing our probabilistic temporal three dimensions life. The charge of the electron e² and the speed of light c² are both squared for the same geometrical reason. We have this concept because the electromagnetic force forms a continuous exchange of energy forming what we experience as time. The spontaneous absorption and emission of light photon ∆E=hf energy is forming potential photon energy into the kinetic energy of electrons. Kinetic Eₖ=½mv² energy is the energy of what is actually happening. An uncertain probabilistic future is continuously coming into existence with the exchange of photon energy.
One thing I always loved about figuring out Even/Odd numbers is that you don't need to use a loop or even use the modulus operator. The beauty of X & 1 is hard to beat, just check if the last bit is set. And since 1 and 0 are considered true or false, you don't even need to check if it's equal to anything. The modulus operator is quite expensive at much larger numbers (depending how its implemented in the language), which tbh I'm sure most programmers here woulda just immediately assumed that was what was going on at 2:30
yeah, modulus cost the same as division if I am correct.
It is not even remotely related to how the programming language implements it. It's implemented via the CPU and is very quick. It's still much slower than simply bit and, but still quick. And also, you do have to negate the result. If the last bit is not set, it's even. So, for checking if the number's odd, no negating would be required, but with checking whether it's even, it would.
@@shambhav9534 I'm sorry, but you're correct and incorrect. Yes, the CPUs ALU literally does some things on it's own, I'm just saying that modulus and divison isn't always implemented the way you think it is. And btw, CPU can do the basic commands you commonly know, XOR, OR, AND, add, subtract, etc, but it can't do modulus or division, there's algorithms implemented to simulate that function (To quickly estimate division on AMD cpus they use the Goldschmidt method). And for example, modulus in python is actually implemented with a .c algorithm and the modulus operator just calls to that function. Why do you think theres operator overloading in Python? You can change what the operator does, it isn't prebuilt inside the CPU, the call to a basic command is. The reason why + is addition in almost all languages is because its what we expect it to do. But however, if we implement that weirdly it cause issues, take the language BrainFu*k for example.
@@XenXenOfficial Do you know of the "div" instruction? It does integer division and also provides with the remainder right there in the dx register. Every language will call that instruction. It does not depend on what the language implements. Well, Python does not. I have literally no idea why. And most C compilers will also do some weird dark magic for performance, which I doubt the effectiveness off. But anyway, the fact remains, your CPU can tell you the remainder of a division and no algorithms are required.
I can already tell you're not that knowledgeable in this subject (neither am I). You're retelling basic facts as if they are revelations and used the phrase ".c algorithm". I'm not saying this is bad or anything, it's just that I know you're not so experienced. I'm no psychologist; I may be wrong (don't complain if I'm wrong). This doesn't imply that I'm an expert though, or that I know more than you. I just made a prediction and am waiting for you to reply to see if I'm right.
@@shambhav9534 You're correct the DIV instruction exists, but that's on other architectures like POWER FAMILY. I personally feel like we're both correct and both have inaccuracies in our comments, but I also know personally that programming languages are a human created contruct with their own definitions on what is & is not, and I know that unless you truly know what's going on under the hood of a language, you can't truly say or know what it's doing. That's also why some languages are more efficient in some use cases, like you wouldn't use Python for genuine software cause of their type juggling, but that can also go for JavaScript or even C for their type casting. That's all under-the-hood things you wouldn't know unless you just... Know. And I bring that up cause it applies the same to modulus
Quantum mechanics, programming computing or whatever it is literally magic , we've come so far , that we can create literal magic
Fantastic to have logic circuits explained at the quantum level
What an intrigue you left in the end... It's been 5 moths already, where is the 2nd part?? Can't wait to watch it!!
Addition is actually faster than O(n) (linear) time. Addition can be done in O(log(n)) time (which is **a lot** more efficient than just linear time) by using "carry look ahead" addition.
A better example of a linear time algorithm would have been to find the maximum or minimum value in any list - there is absolutely no way to do it faster than linear time as you need to check each element for whether they are the largest or smallest element encountered.
Don't you still have to check each of the bits you "skip" (making it an O(n) algorithm)? I'm talking pure algorithm here, not specialized, parallel hardware that can look at all of the bits at the same time and "cheat" the time complexity by moving the carry past several bits at a time. (Is it called "parallel time complexity"?)
For anyone looking to dig deeper, "Quantum Computation and Quantum Information" by Michael Nielsen and Isaac Chuang is a great text on this topic. I recently started reading it, and I'm already struggling with the math in it, so I try to pick it up needed as I go cuz this stuff is so damn interesting.
Thank you, this was soooo good. Admittedly I did not understand it as much as I would have liked but it is the very first time I’ve ever watched a video or read an article where I honestly believed the author knew how quantum computers actually worked. It has been repeatedly disappointing to read the title of an article/video and to find out quite quickly that the author has no idea what they are talking about. I very much look forward to the rest of the series. 😊👍
⥊ 360: 20
0: Good (if not good, then not zero)
0001: Uniqueness
001: Identity
002: Individuality
003: Variability
004: Diversity
005: Tolerance / Inclusion
006: Acceptance
007: Consonance / Harmony
008:
009: Transcendence
01: Awareness
02: Diversion
03: Sensing
04: Love
05: Grace
06: Reasoning
07: Ingenuity
08: Purity
09: Truth Seeking
1: Ethical
2: Problem-Solution
3: Situation
4: Abstraction
5: Expression Concrete
6: Why/Who/When/How/Where/What
7: Information/Code
8: Stability
9: Sanity
10: Network (Good Network, because zero)
11: Justice
12: Time/Spread/Dissipation/Easter
13: Death / Fact
14: Cognition
15: Agent
16: Reason
17: Discourse
18: State
19: Discipline / Control
20: Judgement
21: To Solve Problems with Ethics
22: Resistance/Endure Introspection
23: Consideration
24: Humor / Mental State
25: Behavior
26: Motivation
27: Cohesion
28: Dependability
29: Diagnostic
30: Liberty Subject Wellness
31: Consent
32: Discernment
33: Response
34: Ideas
35: Showing
36: Option
37: Opinion
38: Decision
39: Prognostic
40: Wellness
41: Attention / Idea
42: Critical Thinking
43: Acknowledgment
44: Free Love
45: Plan / Task Force
46: Purpose
47: Perspective
48: Character
49: Ambition
50: Good Expression
51: Manifestation
52: Support
53: Respect
54: Care
55: Peace / War
56: Pointing / Profiling
57: Tell / Counter-Terrorism
58: Invoking / Building
59: Proficiency / To Excel
60: Certainty
61: Identification
62: Qualification / Characterization
63: Inquiring
64: Conjecturing
65: Function / Role
66: Investigation
67: Arguing
68: Indicator
69: Scrutinity
70: Validation
71: Illustration / Knowledge
72: Construct
73: Explanation / Informing
74: Data
75: Materialization
76: Delineation / Instruction
77: Flow / Cadency
78: Share
79: Accountability
80: Personal Soverenity
81: Independency Constancy
82: Resilience
83: Established
84: Autonomy
85: Executing
86: Authority
87: Stream
88: Consistency
89: Boldness
90: Wisdom
91: Assertiveness
92: Optimism
93: Scrupulousness
94: Integrality
95: Composure
96: Blockchain: ⥊ (TRACE MARKER)
97: Anarchy
98: Veganism
99: Revolution
100: Liberation
101: Partnership / Peer-2-Peer
102: Decentralized Network
103: Financial Revolution
104: Production Revolution
105: Labour Reorganization
106: Needs Evaluation
107: Instruction
108: Personal Sovereignty
109: Resources Availability
110: Frankness
111: Honor
112: Distributed Ledger
113: Privacy
114: Abolitionism
115: Pride
116: Justifiable
119: Mission
120: Harvest
121: Deliverance
122: To Sort Out
125: Differentiate
126: Distinguish
130: Realization
131: Fulfillment
132: Regard
133: Responsable
134: Address
135: Execute
136: Obtain
138: To Mark
140: Serenity
141: Idea
144: To Notice
148: Mindfulness
150: Good Character
151: Virtue
153: Declaring
155: Perform
158: Rising
160: Technology
161: Communication Systems
166: Causality
167: To Label
170: Knowledge
185: System Accessibility
181: Structure
199: The Mission
200: Sanctuary
209: Enlist
210: Resolution
211: To Engage
212: Secure
215: Mobilize
219: Annihilation
220: Contemplation / Meditation
221: Either Way / Alignment
222: Cooperation
230: Resilience
250: To Thrive
255: To Emerge
266: Correlation
300: Crusade / Jihad
301: Confront
309: Consensus
310: Cell Net
311: Agreement
320: Deliberation
322: Oportunity
330: Win-Win
331: Bodily Autonomy
333: Abundance
340: Conceive
353: Energy Management
360: Technology
373: Remote Killing
370: Efficiency
390: Economicity
400: Earth Population
410: Permaculture
430: Ecosystem
440: Fellowship
444: Direct Digital Democracy
500: Assumption
501: Leadership
510: Admiration
511: Honorable
512: Altruism
520: Proficiency
530: Acceptance
535: Denoucing
540: Appreciation
550: Diplomacy
555: Gathering
556: To Pick Up Someone/Something
590: Excellency
600: Organizator
620: Diagnose
660: Operation
661: Operator
665: Role
666: Method
676: Deduce
700: Constitution
710: Intelligence
717: Desing
720: Quantum Mechanics
733: Argorithm Explaining
747: Artificial Intelligence
750: Consolidation
751: Enlightment
757: Prompt
766: Plan
770: The Gear
771: File
773: Algorithm Recoginzing
775: Output
777: Pattern / Rhetoric
778: Development
780: Systematization
799: Revolution Algorithm
800: Providence / Heroism
801: Production
802: Necessities
803: Resorces
804: Energy
808: Renewable Cycle
810: Permaculture
820: Management
830: Logistics
831: Scheme
832: Reach
833: Demand
834: Stock
835: Distribution
840: Consumption
850: Labor
860: Human Resources
863: Assignments
870: Structure
880: Peace
888: Globalization
890: Needs
899: Conception
900: Transparency
910: Institutions
911: Emergency Call
930: Energy Distribution
931: Only One Global Currency
960: Blockchain
962: Traceability
970: Optimination
990: Inspection
995: Accountancy
998: Regulation
999: Implementation
1000: Militancy
1001: Nova Era
1042: Drug Liberation
1100: Liberation Army
1160: Pacifism
1312: Boycott
1400: Unity
1500: Benevolence
1550: Charity
1807: Black & Yellow
2222: Paradox
3000: Freedom
3100: Triumph
3311: To Revolt
3330: We All Can Live In Abundance
4000: Coexist
4411: Riders of Justice
5000: Glory
5500: Greatness
6999: Mystery
7220: Unified Field Theory
8000: Sustainability
8999: Finitude
9997: Discovery
9998: Unknown
9999: Universe
10000: Existence
. This is a numeric Matrix for communications purposes.
. This can be used to convey meaning.
Ex.: 6022: Good Reason to Resist.
. Mathematical operators can be used to calculate meaning.
Ex.: To liberate with a good force: 340. 300 + 40 = 340.
. Logical operators to create statements.
Ex.: ¬11: 13. If not Justice then Death.
. Colors can also be used as information.
- You can help build it.
380: 38
How did u get these information? It's scary to see that everyone called 13 as death number even u that talking about quantum theory number @@gschitz
This channel should be called New Mind Blown
Wow that was awesome thanks so much I learnt a lot particularly about the logic quantum gates. Also I never knew about the speed of entanglement I assumed it was instantaneous. Really looking forward to future videos from your channel. Keep up the quality content.
Thank you for explaining the gates and the sphere representation of the quantum qubits. This was a great video.
This One was solid. The music on point. Thank you.
I have listened to many explanations of quantum computing, and your video was the first that got me to actually understand. Thank you. I intend to pursue this field.
Dude, this is so well presented!
Bravo. Best explaination of Quantum Computing on youtube.
I watch this video to humble myself when I feel smart.
Keep this series going for a long time please.
This video has get explanation. I love it. Where can I find part 2?
QUESTION: Entanglement: One particle can be both positive or negative unless measured, and consequentially the 'twin' antiparticle will be the opposite unless we measure the first one... Well, is it not that the first particle 'is already' positive or negative, but we simply cannot know before measuring, and consequentially the twin 'is already' the opposite?
I am totally ignorant of physics, except for youtube videos... But i never see these question explained... Do you have an answer? Thank you so much! 😊
Thank you for the explanation and visualization! Now i understand and don't understand quantum computing at the same time
I never knew about the quantum computing gates. Interesting. Complex numbers make our lives easier as physicists once you learn them. Good stuff.
My mind is in a superposition of thinking I understood a thing or two and completely blown to pieces.
Time to embark on a journey of learning. I am all here for it
brilliant is my favorite plateform❤❤
Always a joy to experience a video from your mind, New Mind!
Welcome1
Good video! Where's Pt 2?
An explanation that actually made sense, and not just "qBiTs CaN bE 1 Or 0 At ThE sAmE tImE" 👏
congrats friend... Linear algebra and general geometry helped me to fully grasp the content without ever directly studying quantum computing, although i suspect, one day, as a software engineer i will have to study it.
The idea that ortogonality implies dimensionality, with weak or semantics codependency, helped me a lot to intuitionally visualize the importance of phase and the z axis rotations. also nlp models helped me on understading how we can encode oposition and the degree of this oposition into 180 vectors of variable length from 0 to 1 with origin from the center of the semantic space. Thanks man.
weak or none*
i could feel the power of collapsing entangled qubits over comptutations.
Finally... I never understood how we could leverage a non-deterministic phenom to generate must be deterministic results, and your explanation that we would collect statistical data from many iterations and probably empirically test the outcome made it clear to me. Probably one feature of this kind of computation will be precision treshold sufficiency, when the result is good enough to not demand further narrowing of the probability distribution for the empirical phase.
*Quantum circuit is a great model of quantum computing*
A quantum register is simply a sequence of entangled qu-bits. A quantum circuit is simply a network of quantum logic gates. Together they make up a Quantum computer.
Physically a qu-bit could be implemented using Electron spin (up vs. down) or photon polarization (horizontal vs. vertical).
Thanks for this, I finally start to understand quantum computing. The stuff you usually hear does not help "q-bits are in a superposition" - well and how does this help exactly?
Phases! As an electrical engineer an "of course!" moment.
Awesome Video, this is a really cool introduction to quantum computing. However I think you made a small mistake, whenever talking about the timecomplexity of the addition algorithm at 3:15. Everytime you multiply the input-number by 10, you add 1 computation step. This algorithm is therby logarithmic, not linear. This is obviously not very important to the main takeaways from the video though
It's a little unintuitive but the video isn't actually wrong here. Because in the video n, or the size of the input, refers to the size of the number (either in bits or digits). A list of 1000 elements has 10x the number of elements as a list of 100, but the number 1000 compared to the number 100 only has 1 more digit, and adding a digit always only adds 3 or 4 bits, not 10x the number of bits. This is why brute forcing a range of numbers with a constant time test, which would normally be thought of as linear time, is exponential time in the video.
Your animations are just MINDBLOWING DUDE!!
Couldnt take my eyes off em!
And gr8 work explaining this. I've been delving into this domain for some time now and this is simply ONE OF THE BEST introductions I've found.
Was always curious on how Programming quantum computers work, nice video
Thanks for sharing this. It's really accessible to ordinary people like me.
Golden presentation of many things.
Great video! Could you post the bibliography to check the details and learn more about this topic?
Hey, thank you for the awesome video. Where's the second part?
I need to watch this again to understand what is going on. Consider me saying this every time I re-watch.
BRING ON PART II!!
The use of Hadamard and CNOT gates to manipulate entanglement is related to the concept of "entanglement swapping." While this can create correlations between distant particles, it still doesn't allow for faster-than-light communication. The outcome of the entanglement is random and cannot be controlled to transmit specific information.
this is the best video i ever seen
Now I understand that Quantum Programming is just a fancy way to perform Addition and Subtraction.
Wow, really powerful. Only using state superposition and entanglement. That's fantastic. Anyway I have a degree in physics engineer and another in mechatronics engineering. I would love to work with this kind of things😍. Basically we could bypass P vs NP problem using quantum computer. Nice! If I understand well, since measuring will collapse the state, if we want to have "control"we should have a model in order to estimate the probability of a state in any point in the quantum circuit architecture and obviously know apriori the overall architecture that we are using for solve a specific problem. So we collapse the measure only in some strategical point ("end states") millons of time and make a probability profile in order to get the final answer. I think that I will study more about the quantum logic gate and all this stuff. Totally loved the control gate part. 🔝🔝🔝
Amazing presentation as always, mind blown.
Mind blown.. So in other words, you need a new mind?
@@bovanshi6564 Exactly!
Well played my friend. 😆
I was a subscriber from your first video and I knew that channel was going to grow big. You are the only channel that I actively visit to rewatch some of your videos. They're so packed with information and it's worth to watch them multiple times. Wish I had the time to watch all your videos multiple times.... :)
Thanks for the kind words. I appreciate you being there early on.
Anologe is making a come back to assist in the digital possessing.
it could make running computationally intensive machine learning algorithms a bit cheap💀
Can't wait till he puts out an English language version of this video! ☺☺
Great tutorial I'm now a certified quantum programmer
Wow...I liked the video because I couldn't understand any of these😉. Some of it sounded like 'Infinite probability drive ' to me. I am fascinated. ...Thank you for posting this...I think I am going to try better to understand this.
when will you make a part-2 i would like to watch it and gather more information about it 😊😊😊😊😊😊
My brain hurts 😂
Great presentation, extremely professional. Thoroughly enjoyed it.
Beautiful animations and illustrations lad. Can’t wait for part 2
Above good editing bro which software do you use
Thank you so much! I've tryed to understand the gates so many times, but this sums it up for me to understand it enough with the basic knowledge I've been accumulating about quantum physics!
Quantum computing is like asking me to build something then make an electrical diagram instead of a blueprint. I can think of some genius solution, put it in a mechanical drawing and build it, but ask me how the electrics work, I'll just wave my angle grinder at you and use my Jedi mind tricks. "This is not the right engineer you're looking for. Go two doors down, make a left and ask for Jeff. Move along."
Please continue this series
I predict that quantum computing and nuclear fusion will be the two biggest breakthroughs of the 21st century
Oh man. Saw this and nicely done. Tips me off to a rabbit hole of Qgates, Qalgos and application methods. But it isn't there yet! Gah!
Wow, mind blown!! In much anticipation for Part 2
Want your video to get tons of engagement? Simple! Just slap on some suspenseful tech-vibe music in the background and keep repeating, "A qubit can be both 1 and 0. This is called superposition."
As a quantum physicist, I completely understood everything. Thank you.
I finally feel like I really understand what's going on with these things. That was great! It does sadden me, however. Since I very likely will never have the power of such a computer at my fingertips.
Now I'm interested with analog! Seems like we gonna use analog again
Off! Thank God you are alive. I subscribed you after watching that Switzerland flywheel bus video. I believe you upload video once in a month.
It's my eager request to increase the frequency a little bit. Not much, just one in 15 days.
Anyway thanks for this video. 👍🏼
Trust me there's plenty of financial incentive to step it up. Its a challenge I haven't been able to pull of quite yet. I am trying.
@@NewMind oh I am sorry. I didn't know that. It's perfectly fine. Once in a month is also a good frequency 😄.
Why don't you upload your content on nebula. That platform is made for quality content and made by quality people like you. Actually I am a curiosity stream and nebula subscriber for almost a year. I have been following their engineering and physics, math contents as these two are my favourite subjects.
I don't know about their monetisation strategy. But if that helps you and if you wish to join, tell it to your next video. I will pay my subscription fee by using your promo code for sure in November 2022 for one year subscription.
The research time and animation work behind each episode makes the waiting time quite understandable....
In a nutshell, if you enter a problem into a quantum computer as a string of 1's and 0's, it will re-arrange them in such a way as to optimize its quantum state. If these 1's and 0's represent an initial non-optimized state of a physical system, the result will be the optimized state of that system. Therefore quantum computers can solve optimization problems in a fraction of the time compared to traditional computers.
To me, the hardest part of understanding quantum computers, is my brain trying to equate (translate) quantum to binary computing concepts, which makes it difficult to process.
I would compare it to learning languages, if you try to force one language into another, it will be a struggle, however once your brain manages (with practice) to isolate and unlink the different languages you know, it becomes seamless.
what ive found is that quantum computers are just barely different enough that it's not really worth going about it in that way if you can help it; note how in the video he calls it an offshoot of quantum mechanics exploited by computer scientists, rather than an offshoot of CS suited to the quantum physicist
trying to recover those same computing concepts without needing "binary" or implying a necessarily digital information-theoretic framework as a starting point is a thought experiment that i feel can illustrate this pretty well
Really looking forward to the second part because this first part was really REALLY well done. Sound Desing, Graphics and over all Information was perfectly compromised into a really informativ and nice to watch video. Great Job