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Major setbacks / pain points (high level)
Huge energy & cooling demand (cost + carbon risk).
— The accelerator complex consumes ~1 TWh+ per year in operating periods; Run-4 and HL-LHC will push this higher unless mitigated. This creates large operational cost and carbon footprint exposure (and political sensitivity).
HSE Unit
+1Cryogenics and superconducting-magnet reliability (quenches, maintenance intensity).
— Large helium cryogenic systems are complex, failure modes (quenches) are costly in downtime and magnet repairs. Improving reliability and maintainability is essential.
ResearchGate
+1Detector/detector-electronics aging and radiation damage.
— Higher luminosity → faster detector aging, higher trigger rates and harsher radiation environment requiring major on-detector upgrades (ATLAS/CMS upgrades for HL-LHC).
ATLAS Experiment at CERN
+1Data deluge: storage, networking, and offline processing bottlenecks.
— Expected output scales toward O(10^2) GB/s and 1000s of PBs long term; WLCG and national grids are stressed and must scale. This affects physics turnaround time and analysis capability.
CERN Document Server
+1Civil / space constraints and access logistics.
— The existing 27-km tunnel and experimental caverns impose tight space for new hardware, making upgrades complex and outage-dependent.Workforce / knowledge pipeline and supply chain fragility.
— Advanced accelerator/detector skills are scarce; specialized suppliers (superconducting cables, cryo components, ASIC fabs) have long lead times and single suppliers in some cases.Sustainability & public acceptance risks.
— Energy/cooling water use and greenhouse targets are politically sensitive; CERN has set environmental objectives that must be met to retain public support.
CERNCost, schedule and governance complexity.
— Multi-national funding and complex project interfaces increase risk of delays and scope creep (HL-LHC shows how ambitious detector + machine work is tightly coupled).
CERNSupplied by AI.
It means that no matter how much we seem to understand; there is more to know, that infinity, the dividing one a 1 into many parts can indeed go on forever. There will always be something to abstract upon. It doesn’t matter how much we think we know about a field of knowledge, there is always an infinite amount more to know about it. It is awe-inspiring at the same time it is disheartening. But that is the beauty of it, it’s the yin and yang of it all.
It makes us realize that perhaps some questions that we don’t have solutions for just yet, such as NP-Complete problems may still be yet answerable. New possibilities will open up after these solutions become apparent that we didn’t know were possible until we discovered something else. The tech tree is unfathomable long it seems. I guess we just have to keep tossing the fishing pole of time and computation at it and seeing what we pull out of the depth of knowledge that we currently have available, every catch increasing the pool that much more. Fascinating.
I believe collaborative efforts far supersede competitive efforts, there is vast wastage of resources incurred while we are in a competitive environment, and I do not believe that this breeds excellence, more often than not mistakes are made while we are rushing to complete a task in order to achieve something before another set of individuals completes their tasks. It does, however, force innovation to complete tasks more efficiently. And so I believe both are important to the creation of a more efficient and effective world. But If I was to pick one it would collaboration. As once famously quoted by Patrick Henry and echoed by many more, “united we stand divided we fall.” However that being said, well we are focusing teams on missions many different methodological processes of competitive capitulation can be used to effect changes to the design process of the system of team environments. But in a collaborative way, after all, one team was able to verify the other team’s effort.
It is only a matter of time until we have amassed more technological prowess that we will surpass previous notations this will result in a more informed and subsequently more elaborate view of the mechanisms at play within the universe that we observe. Even as I write today, new telescopes, such as the James Web telescope are already upheaving preconceived notations about what the universe is and was. And so I can only imagine and look into the past to inform the future that it would be asinine of me to assume that future advances in technology wouldn’t affect the same effects that they previously did.
We would agree on the slope of the mountain to be relatively the same, but the faster that George’s train travels the more significant the distortion. Only when we approach the speed of light, and at a significant fraction of it, does distortion become more noticeable, then we would not agree on the slope. It is all relative and is entirely dependent on the speed of either observer against each other. If we were splitting hairs then there would be a difference. But at the current rates of velocity, neither of us would be able to visually tell the difference.
Working with the formula and going through problem sets is an excellent way to get acquainted with the function before we go into a derivation of it later on in the course. I think that understanding how it functions and then learning the inner workings of the formula is an excellent way to learn.
It would be interesting to find the reverse resonance of structures through this computational synthesis to match frequencies to destroy structures or rip apart materials at the atomic scale. Being able to listen to the resonance, and then restructure the opposite would bring about some very unique properties, think about creating anti mater or anti materials of all materials. Fascinating.
Music sounds good because of dopamine to the brain, if we figure out the rhythm of the melody the brain receives a reward for knowing what’s coming up before the music plays. This is the reward cycle of the adoption of music. This is why some music doesn’t sound good at first, but after you listen to it a few times it sounds better because your brain is reconstructing it and getting a reward. This is what makes music sound good I believe.
I believe that scientific research towards energy generators should be the current national priority, but gravitational wave detectors and generators could be implemented into these generators. Thus I do believe that this project is a national priority.
While going through the course I was trying to figure out how to use these wave detectors and the principles inherited within this course to generate energy or to capture the energy and convert it into other types of energy.
The very fact that that single collision generated more energy than all of the light emitted by every star in the universe gives credibility to the idea of capturing this energy form and using it for the advancement of human civilization.
This was an amazing course, and I appreciate you for sharing this knowledge and information with me. And everyone at world science U.
The areas of research you listed do get funding regularly. But physics projects normally lead to massive increases in economic capability through numerous subsequent findings during the projects, other research areas just do not grant these findings at the same rate.
Physics, after all, is the philosophy of all things, so perhaps unlocking this field first is an optimal strategy because of the implications within other fields an unlock in this would have. It’s a multiplicative strength factor that compounds other areas of science, much in the same way Einstein couldn’t prove his theories without computers, we may not be able to prove other theories without pursuing the physics projects first.
I do not believe that these experiments are only limited to physics, as large-scale research projects such as ITER, which is a fusion power generator are currently in the works. There are also numerous other types of studies, such as quantum computers, wait for a second, these are all physics. haha… Perhaps our search for answers starts with the philosophy of math, and physics, and when we are trying to prove our theories with tests, we are required to implement them, at times large-scale projects are required.
Large-scale, highly-coordinated efforts are the optimal strategy for almost every type of research project. But funding is limited. The reason we want to use large-scale projects and highly-coordinated research is that we have more data to work with, and with more eyes on the data, with more peoples minds working on the project we get the power of diversity in these projects. And diversity breeds diverse thoughts and theories.
As we advance into a world that requires less labour because of automation and Universal basic income becomes more commonplace, we will have more freedom to conduct these experiments with more scientists capable of understanding the world and the work that comes from these super-massive projects.
Aiming this research toward DARPA by writing a grant geared towards the detection of nuclear submarines would be one way to get mission-critical funding.
This makes me wonder if these detectors could be used to ascertain the precise location of objects on earth. Even a tiny blip 1/10,000 the size of an atom in gravity could be detected. It gives me pause for thought about the types of real estate that space could bring to these fields. As then we could point detection capable arrays at the planet to precisely locate differentials in the fields experienced nominally.