IBM has made the largest quantum chemistry simulation to date. It is a success for quantum computers

The prototypes of quantum computers currently available are gradually breaking down some barriers. These machines have a weak point: they make mistakes. This is the reason why Ignacio Cirac, the Spanish physicist who, together with Peter Zoller, developed the theoretical basis of quantum computing, holds that the correct thing is to identify them as prototypes to differentiate them from the fully functional quantum computers that will hopefully arrive in the future. During the conversation we had with Ignacio Cirac in June 2021, the director of the Theoretical Division of the Max Planck Institute for Quantum Optics he explained to us who believed that quantum computers will be very valuable tools in the field of quantum chemistry to, for example, design drugs. Just five years after that conversation, a very important milestone has occurred that invites us to scan the horizon of this discipline with a very healthy optimism. And a group of researchers from IBM; the RIKEN Center for Quantum Computing, in Japan; and Cleveland Clinic, in the USA, have carried out the largest quantum-classical chemistry simulation carried out to date. It’s a very important achievement for a reason: it represents a huge leap in the way quantum computers can be used alongside classical supercomputers to study real-world chemistry problems. “This result is a dream” Dr. Kenneth Merz, the leader of this research, assures that the result obtained by the team he leads is a dream. Until now, the most ambitious simulation that had been possible in this area using a quantum computer recreated a protein with only 303 atoms. However, Merz’s team has managed to simulate two biologically relevant proteins (T4-Lysozyme and Trypsin), as well as the molecules to which they bind, in a completely realistic aqueous environment and reaching 12,635 atoms. To make this possible, they have used two quantum processors that add up to 94 qubits, executing 9,200 circuits over more than 100 hours and collecting 1.3 billion measurement results. The quantum data were subsequently processed with the Japanese supercomputer Fugaku. In this area, the calculation capacity of quantum computers makes a difference, although the merit does not belong exclusively to these machines. The strategy that these scientists have developed consists of dividing large molecules into smaller, more manageable groups. The strategy these scientists have developed is to divide large molecules into smaller, more manageable groups. Classical supercomputers solve the simpler regions, while quantum systems address the more complex and computationally demanding parts. The results are then recombined to obtain a global image of the molecule. To carry out this simulation, the researchers introduced improvements in both classical and quantum techniques. However, one of the most important innovations they have developed is the improvement of the way in which the system identifies which parts of a molecule require detailed quantum treatment, which reduces the overall computational cost. As we have just seen, we are facing a very important milestone, although we need to put it in context. And, despite its value, the strategy that these researchers have developed still does not surpass the best classical approaches. However, it demonstrates that quantum systems can already contribute to the resolution of significant scientific problems, especially when integrated with existing computing infrastructure. Image | IBM More information | Interesting Engineering In Xataka | Beyond AI, US semiconductor manufacturers face the real battle of the future: quantum chips

Science has been measuring whether size matters for years. A study with 3D simulation has the most complete answer

It is probably one of the most recurring questions in the history of humanity and, yet, one of the ones that accumulates the most myths per square meter. Leaving aside popular culture and internet forums, scientific literature has been trying for years to quantify what is true about the importance penis size. Science to the rescue. A published study This year, PLOS Biology wanted to resolve a question that has undoubtedly generated many jokes and also some complexes in the male sex. And the truth is that the short answer to this question is that size does matterbut perhaps not for the reasons most men believe. The signal theory. Until now, many studies were based on simple surveys to answer this question. However, this study has gone one step further by using 343 3D figures to evaluate the response of more than 800 participants. The goal was to understand penis size not only as a reproductive tool, but as an evolutionary signaling trait. The results. In the investigationfemale participants rated men as more attractive, which combined three factors: greater height, a “V” shaped torso (wide shoulders and narrow hips) and a larger penis. But there is a very important nuance. Attraction doesn’t follow a line of “the more the merrier” ad infinitum. The study in this case detected diminishing returns, since after a certain size, attractiveness does not increase proportionally, but rather there is a ceiling. Competence. But men also went through this study to evaluate the size of other men. In this case, it was highlighted that they perceived those with larger genitals as more competitive rivals and with greater fighting capacity. This suggests that, evolutionarily, the size could have served as both sexual ornament and a signal of status or threat towards other males, similar to the antlers of a deer. What they prefer. If we move away from evolutionary theory and go to stated preference, the baseline study remains the one published by N. Prause in PLOS One in 2015. This work is key because it differentiated, for the first time with rigor, between the type of relationship sought. In this case, using 3D models on heterosexual women, a preference was specifically shown for a slightly larger size, averaging about 16.3 cm in length in an erect state and 12.7 cm in circumference. But in the case of stable couples, the preference dropped slightly to 16 cm and 12.2 cm in circumference. The key reading. The first point to note is that circumference matters more than length in visual choice. The second is that these measures are only “slightly” above the population average. A mechanical reality. This is where science busts most porn myths. A narrative review published in the Journal of Sexual Medicine in 2023 analyzed the existing literature To answer the million-dollar question: does a larger penis give more pleasure? The answer is a very nuanced ‘it depends’. Science points out in this case that there are few high-quality studies that manage to directly link size with the organism, and the results are heterogeneous. But if we draw a clear conclusion, the truth is that the quality of the relationship such as trust or communication correlates more strongly with sexual satisfaction than the size of the penis. Male anxiety. If female preferences are moderate and satisfaction depends more on technique than size, why is there still so much anxiety among society? The studies in this case They point out that there is a great disconnection between reality and male perception, since approximately 38% of men report some degree of dissatisfaction with their penis. However, the vast majority of couples have a positive view of their partners’ genitals. Images | Deon Black In Xataka | Desire in times of stress and screens: this is how the era of programmed sex was born

A new mathematical proof settles the debate over whether the universe is a simulation

What if everything we see, feel and experience is not real? It is one of the most fascinating ideas in science fiction and modern philosophy, in which it is proposed that everything around us it’s a real simulation of computer of some higher civilizationas if we were literally sims. And such is its magnitude, that science has had to come out to deny this idea. The problem. The ‘simulation hypothesis’ has gone beyond being a simple movie premise to a serious debate in technology circles and physical. The argument is usually statistical: if a civilization can create one simulation of reality, it will probably create many. These simulations could in turn generate their own and in this infinite ‘stack’ of realities, the odds that our universe be original, they are almost non-existent. And although this has been a very restrained topic among philosophers, science has also wanted to fully enter into research to respond to a problem within fundamental physics and pure mathematics. And the answer is quite clear: we are not in a simulation. The study. An international team of physicists, including Dr. Mir Faizal of the University of British Columbia (UBC) and renowned physicist Dr. Lawrence M. Krauss, has mathematically proven that the universe cannot be a computer simulation. His findings, published in it Journal of Holography Applications in Physicsnot only disprove the idea, but reveal something much deeper about the nature of reality: the universe is based on a type of “understanding” that exists beyond the reach of any algorithm. The reality. To understand this test, we must first understand what ‘reality’ is. Modern physics no longer sees the universe as tangible ‘matter’ moving in empty space, but thanks to Einstein space and time merged to now demonstrate that the microscopic world is probabilistic. The most widely accepted theory today focuses on quantum gravity, which suggests that space and time are fundamental. They are “emergent”: they spring from something deeper, something more like pure information. In this way, physicists assume that a “Theory of Everything“(ToE) that unifies gravity and quantum physics would, in essence, be a large axiomatic system: a set of meaningful rules and algorithmic calculations from which the entire universe, including spacetime itself, could be “computed” and generated. Incompleteness Theorems. In 1931, logician Kurt Gödel demonstrated something that blew up the foundations of mathematics: any formal system (such as a computer program or a set of physical laws) that is complex enough to include basic arithmetic will be incomplete or inconsistent. By ‘incomplete’ we mean that there will be true statements within the systems themselves that will never be able to be demonstrated following their own rules. It’s like the famous paradox that says “this statement is true, but it cannot be proven.” Faizal’s team argues that any purely algorithmic ToE would suffer from this limitation. There would always be “Gödelian truths” about the physics of the universe (perhaps about specific microstates of black holes or the nature of the singularity) that such a computational system could not test. Two layers. If the algorithmic universe is “incomplete”, how does our reality seem to work? Researchers propose that reality is not only the algorithm. This is what allows the universe to “know” that these Gödel truths are true, even though the algorithm alone cannot prove them. It is a fundamental layer of reality that transcends simple computing. The final test. With all the pieces on the table, the refutation of the simulation hypothesis becomes clear and elegant. The first of all is that every simulation is logarithmic, that is, a computer executes a problem following very specific rules that leave no room for doubt. In this way, we come face to face with our theories that are not ‘perfect’ in their demonstrations. But they don’t stop there, since scientists have pointed out that an algorithm can only simulate the algorithmic part, meaning that a computer could only, in the best of cases, emulate the computational and incomplete part of our universe. And the most important thing without a doubt is that our universe is more than an algorithm, since as Gödel’s theorems demonstrate, complete physical reality must include a non-algorithmic layer to be consistent and complete. Images | Compare Fiber In Xataka | Exactly 100 years ago we began to understand how the world works. Quantum physics has radically changed our lives

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