• 72321440 OP Big Curt : You’re an investor in quantum companies. I have a lot of respect for IonQ’s academic achievements. Their technique is to use trapped ions, which is literally what it sounds like, to store quantum information, instead of the superconducting transmon circuits that are popular in industry. These ions are held at room temperature, which is a strong advantage over superconducting. However, they have to be put in extremely low-pressure vacuums and controlled with lasers to have almost zero energy. The general view of industry players is that ion traps are too sensitive to be useful. The company has talked about putting out a 100-qubit computer called Tempo by the end of this year. Unfortunately, IBM is already far ahead of this scale. Yhe movement and timing of government contracts may be misrepresenting IonQ’s position as a leader in the field. Right now, the publicly traded quantum computing stocks are the only pure-plays in this area accessible to investors. There is no reason to buy Google or IBM for their quantum efforts. Quantinuum and other exciting companies are private. So, the impression for retail investors is to buy these 3rd-tier stocks because they’re the only ones which can move substantially. Despite its marginally higher revenue, mostly from their Air Force contract, IonQ is still behind all of the serious quantum players: IBM, Google, Quantinuum (private) and PsiQuantum (private). The most advanced IonQ machine on AWS Braket is the Forte 1, a mere 36-qubit machine. As I write, the Forte 1, which is $7,000 per hour,  went on an unscheduled maintenance recently; my experiments with IBM’s machine lead me to believe that even their stable, less error-prone, 128-qubit machines are useless. IonQ is not even close to 128 qubits! So, the premium of IonQ over Rigetti seems very unwarranted, and it is probably an even better short.

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• 72321440 OP StockPeep : I don’t have a position in any of these companies. I have better positions to play off. I’m just stating the facts. It’s free money, as it’s essentially a scam.

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• 72321440 OP Strain : Since the dawn of man, we’ve sought to exploit nature to calculate. Silicon-based, transistor-based computers have reigned supreme for 50 years. There have been architectural shifts and debates over time, but the fundamental unit has been unchanged. But man has also sought, and failed, to exploit other technologies to improve on the current state of computing. DNA, optical, analog and the new thermodynamic, come to mind.
  Quantum computing was proposed by Feynman and Deutsch in 1980s. He prophetically intuited that if we wanted to simulate reality, a computer that was capable of emulating nature’s quantum effects made sense. While this point is debatable, scientists raced ahead to prove that a theoretical quantum computer could do certain operations faster than a non-quantum computer. But this “faster” is complexity’s definition of faster, which while still quite important, requires someone to make said computer at a scale where the quantum computer’s speed outpaces the non-quantum computer’s. Why scale? With just a few bits of information, no algorithm will be meaningfully faster than another. With further bits, the practical payoff of quantum still won’t be realized since our current computing technologies are robust. Only at much larger sizes would quantum realize its “supremacy” potential, on some algorithms. This is important to know: no one thinks (or wants) quantum computers to run Windows or video games. These machines are expected to be, eventually, specialized tools equipped to help in a very narrow field of problems. We’ll talk about which algorithms are faster with a quantum computer later.
  After the discovery of these critical algorithms made quantum computing tantalizing, several developers began efforts to create such machines. If you remember anything about high school physics, classical mechanics described everything in the Universe we needed to describe, until the 1920s. In the 1920s, relativity and quantum mechanics changed the way we thought about the universe—specifically for quantum mechanics, with very, very small particles. The way a billiard ball hits another or how a ball falls from a height did not change. But we had to change the way we looked at these tiny particles, which seemed to disobey classic mechanics at these infinitesimally small scales.
  These quantum effects mostly involve probability and quantum-specific effects called superposition and entanglement. The idea of probability is crucial in quantum mechanics. The idea is that a particle could be characterized as a combination of states instead of the classical idea of a point—with a location and velocity. This is the idea of superposition. Entanglement is the idea where multiple quantum particles can share a joint state which cannot be separated. We will get into how we can exploit these states to run some algorithms faster than classical computers can, at least theoretically.Two of the major algorithms that get most of the discussion are Shor’s and Grover’s. These brilliant men proved that, in theory, a quantum computer could be exploited to run a factoring algorithm faster than a traditional computer could, in what is called algorithmic time. The field of complexity is a fascinating intersection between math and computer science, and it deals with the theoretical running time of algorithms. Reality tends to mirror theory, but only after implementation of hardware capable of running said algorithms.
  What do these algorithms do? Shor’s algorithm is the fastest factoring algorithm theoretically known. Factoring integers is largely the domain of cryptography. This, in my view, is the main use case for quantum computers. We’ll talk later about the commercial implications of integer factorization later. For now, I think it is reasonable to believe that eventually quantum computers will be able to factor integers of possibly arbitrary length, but certainly numbers larger than what we rely on (1024, 2048-bit RSA, 256-bit ECDSA). This means that any communications encrypted with these algorithms are possibly decodable.
  Grover’s algorithm is the next major algorithm we need to discuss. This algorithm is a lot harder to understand than Shor’s. But, if you studied computing, you can probably just think of it as a better sorting algorithm. There are some problems where Grover’s may be useful. In some ways, we can try and recharacterize any problem as a ‘search’ problem—but to implement Grover’s to do something useful will take time. Incidentally, Grover’s can also help with cryptography.There will be more algorithms discovered that use quantum mechanics effectively. One part of the bull thesis for quantum computing is that we can’t predict exactly what these machines will be useful for, but we may need them. Indeed, Intel and Nvidia could not foresee what was ahead of them by more than a few years at a time.

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• 72321440 OP Strain : D-Wave Systems (NYSE: QBTS) was the first company to focus on quantum computing systems. The company went public via SPAC in 2022 after struggling as a private company. With a tiny valuation and more than twenty years of trying to sell quantum “annealers” (not quite quantum computers), D-Wave was on death’s door before the SPAC and, like most SPACs, was about to knock again. With just $9 million in annual revenue and $100 million in annual losses and only $25 million in cash left as of Q324, D-Wave was as good as done. After the willow announcement, D-Wave promptly refilled its balance sheet with a $175 million ATM at $5 per share. D-Wave now trades at $9, giving it around a $2.5 billion valuation. D-Wave was trading for around $1 before the Google Willow announcement, which does not affect D-Wave. Keep in mind that D-Wave’s quantum annealers are not considered “real” quantum computing and can only perform a very specific function that has not been commercially viable in the company’s 25-year history. At 288x sales which are not growing (2022: 7.2m, 2023: 8.9m, 2024E: 8.4m) and Google’s announcement does not serve as a catalyst for, D-Wave will go back to its old stock price.
  Rigetti Computing (RGTI) is the first ‘real’ quantum computing company we will consider. Chad Rigetti founded Rigetti Computing in 2013 and the company has spent $402 million since its inception. Revenue has been declining (2022: 13m, 2023: 12m, 2024: 12m) and the outlook for Rigetti prior to Google’s Willow announcement was bleak. After down rounds in the private market, a SPAC public transaction and continued lack of commercial progress, Chad left Rigetti. Worth only $300 million with ballooning losses, Rigetti also looked to be on the brink. Rigetti then sold stock at $1.53 via an ATM and $2.00 in a registered direct. The stock is $18.66 as I write this.
  What does Rigetti actually do? Unlike D-Wave, Rigetti does make actual quantum computers. The problem is, they don’t work. Rigetti is seen in the quantum industry as a third-tier competitor. Rigetti uses the superconducting approach to quantum computing, favored by Google and IBM. Rigetti announced their 84-qubit “Ankaa-3” system. What is a qubit? Why do we care about them?
  Qubits are quantum computing’s version of the classical bit in traditional computing. Bits are binary—it’s in their name, binary digit—and are the fundamental unit with which we create processors, store data, et cetera. While we will examine how qubits work, I do not think it is useful to try to compare and analogize them to traditional bits. Many try to do this and fail spectacularly—do not believe what you have read elsewhere. Think of qubits as fundamental processing units that can run the special algorithms I mentioned earlier.
  First, let’s remember that quantum computing requires particles so small that they show quantum effects. From physics, we remember Schrodinger’s concept of wave-particle duality. When we deal with the macroscopic world, particles are 100% reliably described as such: a point location and a velocity is all you need to know. As we get smaller (at the size of atomic and subatomic particles), particles (like electrons) start to be able to be described as waves. Why does this matter?
  If we want to leverage quantum behavior, we need to use particles that exhibit these effects. Transistors are too big. What could work? Superconductors appear to be the favored answer. Superconductors are materials which allow the flow of electrons with zero resistance. Most superconductors require temperatures very close to absolute zero. Incidentally, one of the only exciting investment opportunities in quantum computing is the dilution refrigerators required to achieve these temperatures.Once the temperature has been achieved, a superconducting circuit will act as a qubit and store quantum information. Before we talk about how they do that, keep in mind that these quantum states are exquisitely fragile. Any “noise”, including any interference from the natural world, can destroy the qubit’s state.Qubits themselves store probabilities in complex numbers. As you may remember from high school, complex numbers have an imaginary “i” component. The qubit itself is a combination of states we’ll call alpha and beta. Each state holds the magnitude (real) and phase (imaginary) values of those states. The probability of finding the qubit in its alpha state post-observation is given by the square of the magnitude. The probabilities of the two states must equal to 1. The ability to store this non-binary data reminds me of analog computing, an idea which failed previously and is being reconstructed. Regardless, the details of how exactly these qubits form the basis for faster computing is not worth discussing in too much detail. Immediately you can see that storing four non-decimal values in one qubit can be worthwhile. When combined with other quantum dynamics, qubits become very powerful.

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• 72321440 OP Strain : Back to Rigetti. Like Google and IBM, Rigetti is going down the ‘traditional’ superconducting “transmon” qubit route. The Ankaa-2 Rigetti machine on AWS Braket (Amazon’s dedicated quantum computing service) has been ‘offline’ for the last few months I’ve been watching it. Ankaa-2 is their 84-qubit predecessor model to the Ankaa-3. So, what’s the issue? Won’t the industry scale the number of qubits and achieve its goals in the fields where quantum computing is applicable? Not so fast. The description of qubits earlier was an idealized version called a “logical” qubit. The “physical” qubits being described are not enough to do meaningful calculations. It’s estimated it could take as many as 1,000 physical qubits before a single error-free logical qubit is achieved. Only then, with thousands of logical qubits, could interesting calculations be made. I have used the commercial quantum computing services to factor the number 15. It is very hard to get these computers to do much more than that.
  What are the commercial prospects for a company like Rigetti, assuming they achieve their goals? The answer is, not much. The entire budget for the NSA is reportedly $10 to $15 billion. This makes sense, since the FBI budget is publicly disclosed at $11 billion, and a leak suggested the CIA budget is $14 to $15 billion. We think the NSA computing budget is roughly $2 billion annually. We think storage and data center operations consume at least half of that, and more likely quite a bit more. If quantum were to take over half of this budget, or the budget were to grow by $1 billion, this is the spend that is up for grabs.We can imagine a number of scenarios where Rigetti (or another company) receives 50% of this spending. The problem is Google, IBM, Quantinuum, IonQ and others would like this spend as well. But let’s assume Rigetti somehow wins it, and this budget appears in just 5 years. We discount 50% net margin cash flows (no tax assumed) at a 12-25% discount rate. The NPV is between $1 to $4/share versus the $18 stock price today. Even if we assume that this budget grows enormously to accommodate other uses (industrial, academic), which we do not see, and Rigetti gets to $2 billion in revenue by 2035, still at a 50% net margin, the stock is worth between $3 and $14/share depending on the discount rate. Rigetti has no chance of any of this happening, unfortunately.
  IonQ (IONQ) is a more substantial company than Rigetti at first glance. I have a lot of respect for IonQ’s academic achievements. Their technique is to use trapped ions, which is literally what it sounds like, to store quantum information, instead of the superconducting transmon circuits that are popular in industry. These ions are held at room temperature, which is a strong advantage over superconducting. However, they have to be put in extremely low-pressure vacuums and controlled with lasers to have almost zero energy. The general view of industry players is that ion traps are too sensitive to be useful. The company has talked about putting out a 100-qubit computer called Tempo by the end of this year. Unfortunately, IBM is already far ahead of this scale.

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• 72321440 : dont rely off people’s comments to invest in a company. do research.

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• 72321440 Zz catalyst :

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• 72321440 OP obliging Crane_9694 : Yeah. If it breaks under $1.9, no. She’s cooled off, needs some volume.

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• 72321440 OP obliging Crane_9694 : new p.t is 2.7

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