# Relationship between science and technology with physics formulas

### BBC Bitesize - Higher Physics - Spectra - Revision 1

Mathematical equations, from the formulas of special and general relativity, to the Pythagorean theorem, are both powerful and pleasing in their. The equation used to calculate the power is: power = \frac {work \ done}{time \ taken}. P = \frac {E}{t}. This is when: power (P) is measured in watts (W); work done. Understand the structure of the atom based on atomic line spectra. Calculate electron This relationship is represented by the following equation: I = \frac{P}{ A}.

All of this complex phenomena that you see around us, whether we're looking at a galaxy or we're looking at ocean waves, or we're looking at even biological systems, we'll see that a shocking amount of them can start to be described using some fairly elegant mathematics that we can build on and continue to build on.

Simple or elegant mathematics like force is equal to mass times acceleration. And we're gonna talk about force and acceleration as vector quantities. We're gonna think about things like displacement, and I'll put it as a vector quantity, and we'll soon learn more about vector and scalar quantities are.

Displacement is equal to velocity times time. We'll learn things like accelaration is equal to change in velocity over change in time. What we'll see with even a handful of very simple ideas like this. We'll go into much more depth in future videos.

You can explain all sorts of complex phenomena. And the one thing that I always loved about physics, and I don't think it's always fully appreciated, sometimes as you start to learn physics, you'll see all these complicated formula, all of these kind of complicated problems, but it's super valuable to realize it's all coming from some of these basic ideas.

Some of the things that I just mentioned, these ideas, we're gonna explore ideas of energy. We're going to explore Newton's laws.

We're going to explain, we're gonna think about what are the the different types of forces out there, and why they might, why they might actually exist.

At its essence, it's all about trying to explain the complexity of the universe, predict what is going to happen based on simple ideas. And that's what physics is all about. Now when we think of physics, it's been studied by humanity for a very, very long time. In fact, I'm sure we don't know who the first physicists were.

But some of the, I guess you could say foundational thinkers in physics are these gentlemen that I have here. And this is just a You could kind of say this is some of the most prominent thinkers in physics, but this is by no means a complete list.

First and foremost, we'd wanna include Isaac Newton. Especially when you start to study physics, you're starting to understand the world as Newton understood it. In addition to the steps identified in Recommendations andannual collection of the following information would allow the community to better understand and improve itself: Perhaps the mathematical science professional societies, in concert with some funding agencies, could work to build up such an information base, which would help the enterprise move forward.

However, the committee is well aware of the challenges in gathering such data, which would very likely be imprecise and incomplete.

### Quotes about Science, Physics and Life

Needless to say, these are deeply intertwined, and it is becoming increasingly standard for major research efforts to require expertise in both simulation and large-scale data analysis. Before discussing these two major drivers, it is critical to point out that a great deal of mathematical sciences research continues to be driven by the internal logic of the subject—that is, initiated by individual researchers in response to their best understanding of promising directions.

While over the years there have been important shifts in the level of activity in certain subjects—for example, the growing significance of probabilistic methods, the rise of discrete mathematics, and the growing use of Bayesian statistics—the committee did not attempt to exhaustively survey such changes or prognosticate about the subjects that are most likely to produce relevant breakthroughs. The principal lesson is that it continues to be important for funding sources to support excellence wherever it is found and to continue to support the full range of mathematical sciences research.

Indeed, all areas of the mathematical and statistical sciences have the potential to be important to innovation, but the time scale may be very long, and the nature of the link is likely to be surprising. Many areas of the mathematical and statistical sciences that strike us now as abstract and removed from obvious application will be useful in ways that we cannot currently imagine. On the one hand, we need a research landscape that is flexible and non-prescriptive in terms of areas to be supported.

We must have a research funding landscape capable of nurturing a broad range of basic and applied research and that can take into account the changing characteristics of the research enterprise itself. And on the other hand, we need to build and maintain infrastructure that will connect the mathematical and statistical sciences to strategic growth areas.

Quoted text is from p. Page 73 Share Cite Suggested Citation: That is because computational modeling is inherently mathematical. Accordingly, those fields depend on—and profit from—advances in the mathematical sciences and the maintainance of a healthy mathematical science enterprise.

The same is true to the extent that those sectors increasingly rely on the analysis of large-scale quantities of data. This is not to say that a mathematical scientist is needed whenever someone builds or exercises a computer simulation or analyzes data although the involvement of a mathematical scientist is often beneficial when the work is novel or complex. But it is true that more and more scientists, engineers, and business people require or benefit from higher-level course work in the mathematical sciences, which strengthens connections between disciplines.

And it is also true that the complexity of phenomena that can now be simulated in silico, and the complexity of analyses made possible by terascale data, are pushing research frontiers in the mathematical sciences and challenging those who could have previously learned the necessary skills as they carry out their primary tasks.

As this complexity increases, we are finding more and more occasions where specialized mathematical and statistical experience is required or would be beneficial. Some readers may assume that many of the topics mentioned in this chapter fall in the domain of computer science rather than the mathematical sciences.

In fact, many of these areas of inquiry straddle both fields or could be labeled either way. For example, the process of searching data, whether in a database or on the Internet, requires both the products of computer science research and modeling and analysis tools from the mathematical sciences.

The challenges of theoretical computer science itself are in fact quite mathematical, and the fields of scientific computing and machine learning sit squarely at the interface of the mathematical sciences and computer science with insight from the domain of application, in many cases. Indeed, most modeling, simulation, and analysis is built on the output of both disciplines, and researchers with very similar backgrounds can be found in academic departments of mathematics, statistics, or computer science.

There is, of course, a great deal of mathematical sciences research that has not that much in common with computer sciences research—and, likewise, a great deal of computer science research that is not particularly close to the mathematical sciences. The reason is that mathematical science researchers not only create the tools that are translated into applications elsewhere, but they are also the creative partners who can adapt mathematical sciences results appropriately for different problems.

This latter sort of collaboration can result in breakthrough capabilities well worth the investment of time that is sometimes associated with establishing a cross-disciplinary team. Nothing can compare with that experience The reward of the old scientist is the sense of having seen a vague sketch grow into a masterly landscape. Nothing can compare with that experience.

Cecilia Payne-Gaposchkin In physics, you don't have to go around making trouble for yourself - nature does it for you. Frank Wilczek - Science is the only self-correcting human institution, but it also is a process that progresses only by showing itself to be wrong.

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Allan Sandage Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less. Maire Curie - Gravitation cannot be held responsible for people falling in love. How on earth can you explain in terms of chemistry and physics so important a biological phenomenon as first love?

Put your hand on a stove for a minute and it seems like an hour. Sit with that special girl for an hour and it seems like a minute. Albert Einstein In many cases, people who win a Nobel prize, their work slows down after that because of the distractions. Yes, fame is rewarding, but it's a pity if it keeps you from doing the work you are good at. Townes - Astronomy compels the soul to look upwards and leads us from this world to another.

Carl Sagan - Measure what can be measured, and make measureable what cannot be measured. Today's scientists have substituted mathematics for experiments, and they wander off through equation after equation, and eventually build a structure which has no relation to reality. Nikola Tesla - Equations are just the boring part of mathematics. I attempt to see things in terms of geometry.

Stephen Hawking - Mathematics is the language in which God has written the universe. Galileo Galilei - A ship in port is safe, but that is not what ships are for. Sail out to sea and do new things. Bahcall - There was a blithe certainty that came from first comprehending the full Einstein field equations, arabesques of Greek letters clinging tenuously to the page, a gossamer web. They seemed insubstantial when you first saw them, a string of squiggles.

Yet to follow the delicate tensors as they contracted, as the superscripts paired with subscripts, collapsing mathematically into concrete classical entities-- potential; mass; forces vectoring in a curved geometry-- that was a sublime experience.

The iron fist of the real, inside the velvet glove of airy mathematics.

**Equations of motion (Higher Physics)**

Gregory Benford - from "Timescape" A scientist is happy, not in resting on his attainments, but in the steady acquisition of fresh knowledge. Science is built up of facts, as a house is built of stones; but an accumulation of facts is no more science than a heap of stones a house. Jules-Henri Poincare - Somewhere, something incredible is waiting to be known.

Carl Sagan - An experiment is a question which science poses to Nature and a measurement is the recording of Nature's answer. Max Planck - Equipped with his five senses, man explores the universe around him and calls the adventure Science. Hubble In theory, there is no difference between theory and practice.