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arXiv:2512.18509

Comment on: "The future of the correlated electron problem", arXiv:2010.00584

Vasily R. Shaginyan, ALFRED Z. MSEZANE

Published Dec 20, 2025• 0 citations
arXivHTMLPDF

Abstract

In our comment we show that some of the very difficult problems have been successfully solved. We have to focus on the resolved problems, since the authors claims: Our hope, however, is that the topics we have presented will provide inspiration for others working in this field and motivation for the idea that significant progress can be made on very hard problems if we focus our collective energies. Thus, there is no need to mislead potential researchers.

DOI
10.48550/arxiv.2512.18509

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In our comment we show that some of the very difficult problems have been successfully solved. We have to focus on the resolved problems, since the authors claims: Our hope, however, is that the topics we have presented will provide inspiration for others working in this field and motivation for the idea that significant progress can be made on very hard problems if we focus our collective energies. Thus, there is no need to mislead potential researchers.
A central problem in modern condensed matter physics is the understanding of materials with strong electron correlations. Despite extensive work, the essential physics of many of these systems is not understood and there is very little ability to make predictions in this class of materials. In this manuscript we share our personal views on the major open problems in the field of correlated electron systems. We discuss some possible routes to make progress in this rich and fascinating field. This manuscript is the result of the vigorous discussions and deliberations that took place at Johns Hopkins University during a three-day workshop January 27, 28, and 29, 2020 that brought together six senior scientists and 46 more junior scientists. Our hope, is that the topics we have presented will provide inspiration for others working in this field and motivation for the idea that significant progress can be made on very hard problems if we focus our collective energies.
Machine learning, especially deep learning, has achieved remarkable success in a wide range of applications.It is one of today' s most rapidly growing fields in science and technology.In recent years, the interplay between machine learning and physics has attracted tremendous attention, giving rise to a new interdisciplinary research frontier.On the one hand, we may utilize machine learning methods to tackle certain intricate physical problems that are beyond the capability of traditional approaches.On the other hand, certain concepts, ideas, and methods originated in physics can also be exploited to enhance the study of machine learning.Without a doubt, the fusion of machine learning and physics will bring us new opportunities and challenges, and significantly advance the studies in both fields.This special topic contains several review papers written by experts working actively in this emergent interdisciplinary field.These papers review a number of hot topics and some latest progresses, covering adversarial learning in quantum artificial intelligence, quantum generative models, machine learning based on waves and diffusions, automatic differentiation, machine learning assisted quantum adiabatic algorithm design, state preparation in quantum machine learning, experimental progress of quantum machine learning based on spin systems, etc.We hope this special topic can help readers gain a primary picture of the research content, basic ideas and methods, the latest developments, and the challenges and opportunities faced in the intersection of machine learning and physics.Meanwhile, we also hope this special topic can provide some inspiration to readers, and attract more researchers to join this exciting interdisciplinary field.
Much has been talked about quantum computers. Today they are working on difficult simulations, so we can already congratulate the college of researchers at the Oak Ridge National Laboratory as the world's first to successfully simulate an atomic nucleus using a quantum computer. The results that were published in the physical examination letters demonstrate the huge capacity of quantum systems to calculate the problems of nuclear physics and to be able to be successfully used in the future for special and complex simulations. It is already known that quantum calculus, which is based on the quantum principles of matter and which was proposed by American physicist Richard Feynman in the early 1980s, unlike the ordinary bits of normal computers today, uses the qubit units used by quantum computers to store information in two-state systems, such as electrons or photons, considered simultaneously in all possible quantum states (essentially a phenomenon known as overlapping). In October 2017, a multidisciplinary ORNL team began working on codes to perform various simulations on quantum computers such as IBM QX5 and Righetti 19Q within a DOE Quantum Testbed Pathfinder project in an effort to verify and validate various scientific applications on different types of quantum hardware. Today, quantum computers have potential applications in cryptography, artificial intelligence and weather forecasting, as each additional qubit clings in some way inextricably from the others, thus exponentially increasing the number of possible results for the final measured state. Obviously, this huge benefit also has negative effects on the system, because errors can in turn exponentially increase the size of the problem and the final results even. However, it is hoped that in the future on the basis of much-improved hardware, researchers will be able to solve problems that cannot be solved today using current calculation methods. In the present paper the authors propose an original method of rapid theoretical determination with great precision of the dimensions of all elementary particles, the method which, although predicting results similar to those obtained by other theoreticians, still has the advantage of its simplicity, of its general applicability, that is of its universality and especially this new method is a precious tool in the work of scientists worldwide to understand matter at its elementary level. Even though we would have expected that the size of a deuteron would be larger (double) than that of one component particle (of a proton or neutron), at the same velocity, the theory (20-21) demonstrates the opposite. By fusing two free nucleons, a proton and a neutron, a deuterium nucleus is obtained with smaller dimensions than its two components, which makes the energy of rejection between two Deuteron cores much larger than we would have waited. That's why the fusion reaction between two Deuterons is even more difficult than was suspected, even when they are accelerating.