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      "body": "<html> <p>https://cdn.steemitimages.com/DQmTwB7QeE8banonoQiPaTBSTf6EazKkbVKxbvG8yFfBhsH/image.png<br> </p> <p><br></p> <p>Inverse problem solving isn't a new technique in classical physics, but this algorithm represents one of the first successful examples of an inverse problem solving method with quantum materials. And it could make searching for interesting physics a more streamlined and deliberate process for many scientists. More physicists are working in condensed matter than any other subfield of physics -- the rich diversity of condensed matter systems and phenomena provide ample unsolved problems to explore, from superconductivity and superfluidity to magnetism and topology. Experimentalists probe the macro-and microscopic properties of materials to observe the behavior and interactions of particles in materials under a strict set of controls. Theoretical condensed matter physicists, on the other hand, work to develop mathematical models that predict or explain the fundamental laws that govern these behaviors and interactions.</p> <p>The field of theoretical condensed matter physics has the well-earned reputation for being esoteric and difficult for the lay person to decipher, with its focus on understanding the quantum mechanics of materials. The process of writing and solving condensed matter equations is extremely intricate and meticulous. That process generally starts with a Hamiltonian -- a mathematical model that sums up the energies of all the particles in the system.</p> <p>Clark explains, 'For a typical condensed matter problem, you start with a model, which comes out as a Hamiltonian, then you solve it, and you end up with a wave function -- and you can see the properties of that wave function and see whether there is anything interesting. This algorithm inverts that process. Now, if you know the desired type of physics you would like to study, you can represent that in a wave function, and the algorithm will generate all of the Hamiltonians -- or the specific models -- for which we would get that set of properties. To be more exact, the algorithm gives us Hamiltonians with that wave function as an energy eigenstate.'</p> <p><br></p> <p><em>Clark says the algorithm gives a new way to study physical phenomena such as superconductivity.</em></p> <p>'Typically, you would guess Hamiltonians that are likely to be superconducting and then try to solve them. What this algorithm -- in theory -- will allow us to do is to write down a wave function that we know superconducts and then automatically generate all of the Hamiltonians or the specific models that give that wave function as their solution. Once you have the Hamiltonians, in some sense, that gives you all the other properties of the system -- the excitation spectrum, all the finite temperature properties.</p> <p>That requires some more steps once you have the Hamiltonian, so we didn't improve that part of the research process. But what we did, we found a way to find interesting models, interesting Hamiltonians.'</p> <p>Chertkov adds, 'There are lots of wave functions people have written down for which there are no known Hamiltonians -- maybe 50 years worth. Now we can take any of these wave functions and ask if any Hamiltonians give those as eigenstates and you may end up with one model, no models, or many. For example, we are interested in spin-liquid wave functions, highly entangled quantum states with interesting topological properties.</p> <p><br></p> <p><em>Theorists have constructed many spin-liquid wave functions, but don't know which Hamiltonians give them.</em></p> <p><br></p> <p><code>In the future, our algorithm should let us find these Hamiltonians.'</code></p> <p><br></p> <p>Clark and Chertkov tested the algorithm on wave functions related to frustrated magnetism, a topic that presents interesting physics with many open questions. Frustrated magnetism occurs in a class of materials that is insulating, so the electrons don't move around, but their spins interact. Clark explains one such wave function they tested, 'The electron spins in a frustrated magnet want to be anti-aligned, like the north and south on a magnet, but can't because they live on triangles. So we make a wave function out of a linear-superposition of all of these frustrated states and we turn the crank of this algorithm, and ask, given this wavefunction, which is an interesting quantum state on a frustrated magnet, are there</p> <p><br></p> <p><code>Hamiltonians that would give it. And we found some.'</code></p> <p><br></p> <p>Chertkov says the results of the algorithm could point experimentalists in the right direction to find interesting new physics: 'That would hopefully be one way it would be used. You pick a wave function that has some kind of physics that you care about and you see what sort of interactions can give you that sort of physics, and hopefully then the models you find through this method can be looked for in experiments. And it turns out you find many models with our method.'</p> <p>Clark sums up, 'This has inverted the part of the process where we were sort of hunting in the dark. 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      "body": "<html> <p><br></p>https://cdn.steemitimages.com/DQmS3qo4RZWEEEu5bXoy8iQHTzxN6zLTv9jo8Mk17VmsN9a/image.png <p><br></p> <p>According to Nouriel Roubini, the professor of economics at New York University who is said to have predicted the 2008 global financial crisis, Bitcoin represents “the mother of all bubbles”. He’s the latest in a long list of economics and financial luminaries to have dismissed cryptocurrencies, from Alan Greenspan, the former chairman of the US Federal Reserve, to Jamie Dimon, the chief executive of JP Morgan.</p> <p><br></p> <p>It’s harder to find experts of equal weight who argue that cryptocurrency is not a bubble. That doesn’t mean it is one, of course, but the rocketing values of the last year or so point that way.</p> <p><br></p> <p>A ‘bubble’, in economic terms, is when the price of an asset far exceeds its intrinsic value. For example, the dotcom bubble of the early 2000’s was marked by companies that saw their share prices rise simply because they were in the dotcom industry, and without reference to their likely profits or chances of succeeding.</p> <p><br></p> <h2>Bubbles are hard to spot in advance</h2> <p>Very often, in a bubble, prices are driven up because people are overly optimistic about an asset; sometimes, it appears that it’s simply a case of people rushing to avoid missing out as valuations keep climbing. Eventually, however, the bubble bursts and those who haven’t already sold up are left with nothing.</p> <p>Cryptocurrency, according to the likes of Roubini, fits this pattern. Bitcoin rose by 900 per cent last year for example, and it’s not obvious what that value is based on, beyond the expectation of further increases.</p> <p>Part of the difficulty of the definition is that bubbles are mostly identified after they have popped. Until that point, they are hard to identify. For example, in 2012 plenty of analysts were arguing that Apple shares were in a bubble as they hit $100 per share. At the time of writing, they are at $187. Six years and the bubble still hasn’t burst.</p> <p><br></p> <h3>Cryptocurrency’s value is hard to determine</h3> <p>However, although lots of people seem to be holding (or “hodling” is the preferred phrase), their cryptocurrency as if it were a stock, it actually isn’t. That makes underlying its value harder to determine. Of course, it doesn’t really act like a currency either, which makes it hard to compare to currency valuations. That, say cryptocurrency enthusiasts, is because it is an entirely new thing. Like any new technology, it has been greeted with skepticism, especially from the sector it might potentially disrupt and, like any new technology, it has the potential to disrupt far more significantly than it has so far.</p> <p>Complicating the picture is the growing number of cryptocurrencies. One might argue that the valuations of Bitcoin and Ethereum are not bubbles but that the bubble is represented by the flurry of new cryptocurrencies, each trying to attract a wave of buyers that hope to get in on the next big thing. In that sense, it bears some relation to the dotcom bubble. While Amazon was not a sign of a bubble, Pets.com, which went from IPO to liquidation in 268 days, most certainly was.</p> <p>So is cryptocurrency a bubble? Ask us in 10 years’ time. Meanwhile, the dotcom bubble offers some sense of how to behave here. Don’t jump on a bandwagon because you fear missing out. Instead, evaluate your own attitude to risk and the value you are likely to get from your investment, and proceed accordingly.</p> </html>",
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