Chapter 432: Supeputing Application


    Trantor: Henyee Trantions Editor: Henyee Trantions


    After receiving Lu Zhou’s reply, Carlson basically didn’t have any hope. The Millennium Prize Problem ceremony was put to a hold.


    However, someone might have leaked the news of the y Institute’s original award ceremony ns.


    Then the rumors ended up being that Lu Zhou had rejected the award.


    Ever since the Navier–Stokes equation was solved, the media had been paying attention to the million-dor Millennium Prize Problem award. After all, for people that didn’t study mathematics, a million-dor award was much more shocking than the solution to the Navier–Stokes equation...


    The New York Times reporter’sments.


    [... After Perelman, a Russian mathematician, refused the million-dor award, Chinese mathematician Lu Zhou also refused the award. There seems to be a magical curse attached to the Millennium Prize Problems as everyone that solves the problems seems to lose interest in money?]


    Hardy handed the newspaper article to Lu Zhou, and after Lu Zhou finished reading it, he threw it in the garbage bin and shook his head.


    “It’s absolute nonsense! When did I refuse the award? I only told y Institute to wait for a bit as I’ve been very busy recently. I don’t have time to fly to Paris.”


    Hardy: “Professor, did you dismiss the y Institute’s prize money because you don’t have time to go there?”


    Lu Zhou corrected him. “I postponed it, not dismissed.”


    Hardy shrugged and said, “Okay, postponed... Professor, actually I have a suggestion, I don’t know if I should say it.”


    Lu Zhou looked at Hardy and asked, “What suggestion?”


    Hardy scratched his head and smiled as he said, “What I’m saying is, if you don’t have the time, I can go to Paris and ept the prize for you. You’re busy with research, but I don’t mind traveling...”


    Lu Zhou: “...”


    This dude... has too much free time!


    ...


    The rumors about Lu Zhou was only a minor disturbance.


    Lu Zhou was busy with sma turbulence research, and he didn’t have time to go do some press conference and clear this boring matter.


    Solving the Navier–Stokes equation didn’t only cause Lu Zhou to receive excessive media and award ceremony attention, but it also gave him other troubles.


    For example, ever since he returned to America with the Fields Medal, his email had been filled with invitations from various ces.


    Some of which were from domestic and foreign research institutes, some were from the top 100 mathematics universities, and some weren’t even from the academic field; there were invitations for a TV show and a talk show...


    Once Lu Zhou left Xiao Ai to sort through these emails, he felt a lot more rxed.


    In addition to rejecting people and dealing with the spams, Xiao Ai was basically his personal assistant. As demonstrated, Xiao Ai had be more and more intelligent.


    After solving these trivial matters, Lu Zhou returned to his research on the sma turbulence problem.


    It was worth mentioning that the difficulty of the turbulence problem was divided into two parts.


    The first part mainly came from theplexity of the system itself and the environment around the system as well as the difficulty that arose from the diversity of the turbulent motion system as a whole.


    Take a spacecraft as an example. As the altitude, speed, or even location and material surface temperature changed, the gas and macromechanical environment around the spacecraft was also constantly changing.


    The second part came from the methodology of ssical physics.


    Traditional reductionism started from the most basicponents of the material dynamics and established the equations of motion from the basic interactionws. This sounded simple. After all, most ssical physics forms didn’t even require advanced physics.


    However, in the world of physics, “more isplex”.


    Take an aircraft as an example, the flow field around the aircraft contains 10^15~10^24 microfluids, and each microfluid had to be individually mechanically analyzed. The interaction forces between the microfluids also had to be considered, and this problem couldn’t be solved even with the entire world’sputing resources.


    Due to itsplexity, most models made byputational fluid dynamics researchers were phenomenon-based. Therefore, different schrs using the sameputational fluid dynamics modeling method could get different results.


    Because of this, turbulenceputational fluid dynamics modeling based on a closed model was often considered an art rather than hard science.


    The reason why people were so obsessed with a smooth solution to the Navier–Stokes equation was not only because they wanted to find out if such a solution existed, but they also wanted to know what mathematicians would find out while researching this problem.


    The mathematicians might find out a structural quantity between the subsonic zone and sonic zone, or an approximate weak form in a limited range. Or in the case of L Manifold, the L Manifold differential geometry method that could be used on partial differential equations.


    For the sma inside the sterator, the firstplexity part was rtively easy to deal with. Although sma wasn’t stable under high temperatures and pressures, at least the macro-sma cirction was rtively uniform.


    The second type ofplexity problem was much more cumbersome.


    However, this was only difficult for normal people.


    After Lu Zhou applied the L Manifold into the Navier–Stokes equation and built a mathematical model based on differential geometry experimental data, he found out that although the process was difficult, the end result wasn’t asplex as he had imagined.


    Time quickly flew by.


    Early September.


    Lu Zhou sat in his office at Princeton Institute for Advanced Study while he stared at hisputer screen. From time to time, he would write on a draft paper with the pen in his hand.


    After he entered the final line of calctions on theputer, he finally let out a sigh of relief and put down his ballpoint pen.


    “Done!”


    When Hardy heard his professor’s voice, he looked up with a confused expression. He made eye contact with Qin Yue before he looked back down again.


    Jerick and Vera also looked at Lu Zhou with worship. Especially Vera, her eyes were almost twinkling with stars.


    Although she didn’t know what her professor was doing, she felt like her professor was doing something amazing.


    As for Wei Wen, he was writing his master’s thesis whilepletely ignoring themotion around him. He wanted to finish his master’s this year and start his PhD next year, so he wasn’t concerned with Lu Zhou’s work.


    All he knew was that his professor was researching something nutty again...


    Lu Zhou didn’t notice his students’ reaction; he quickly double-checked his mathematical model and then copied the data onto a USB. He took the USB and quickly left the office.


    Equation derivation could be done by a human brain, but whenever a numerical solution was concerned, the calctions were beyond the capabilities of a human.


    In order to verify his mathematical model and to collect some firsthand simtion data, Lu Zhou needed a supeputer.


    The faster theputer, the better!


    ...


    As one of the richest universities in North America, Princeton’s wealth wasn’t only reflected in its willingness to poach talented people, but also its campus hardware facilities.


    Although Princeton was a small town, there was everything from smaboratories to supeputers centers.


    This showed how important having a financially strong alumni association was for a university.


    Princeton’s supeputer was at the John von Neumann Center; it was mainly used for simtions in condensed matter physics, sma physics, and cosmic mechanics.


    Lu Zhou was acquainted with a big name in the parallelputing field—David Shaw.


    However, Anton’s supeputing powers only excelled in theputational chemistry field; it wasn’t ideal for generalputing.


    Not to mention, David Shaw might not be interested in sma physics or fluid dynamics simtion. Therefore, Lu Zhou didn’t want to bother him.


    Lu Zhou didn’t have to wait long after he filled in the application form in Nassau Hall. He quickly received approval from the school.


    Any research project linked to the PPPL had the highest priority.


    Not to mention, the researcher was a Fields Medal winner.


    Lu Zhou took the relevant documents to the John von Neumann Center and the director of the center, Amer Green. He told Amer Green about his intentions.


    After hearing Lu Zhou’s request, Green was full of surprise.


    “Unbelievable... Are you sure you’re not kidding? You sessfully built a mathematical model for sma turbulence in a sterator?”


    Although Green wasn’t a physicist, he still knew how amazing this achievement was.


    Lu Zhou sighed and waved the application approval document in his hand as he said, “It’s still six months until April Fool’s, I’m not joking.”


    Professor Green didn’t waste a second. He switched on his workputer and said, “Did you bring the model?”


    Lu Zhou put the USB on the table and said, “Of course.”


    Green plugged the USB into theputer and opened the files inside. He looked at the data and images on theputer screen and rubbed his beard. He thought for a bit before he said, “To put it bluntly, this is difficult. I’m not sure John Neumann has the capabilities to withstandputing on this magnitude. You might need something like the Summit supeputer at the Oak Ridge National Laboratory... Are you sure you can’t simplify the model?”


    Lu Zhou shook his head and said, “That’s the most I can simplify it.”


    “Okay then, you have given us a difficult problem on behalf of PPPL.” Professor Green spun the pen in his hand and said, “I can solve the algorithm part, but don’t expect results anytime soon.”


    Lu Zhou nodded and said, “I know, I will also help you guys.”


    Professor Green smiled and said, “Of course! After all, we do massively parallelputing; we’re no sma physicists.”