Alright, so then good morning and welcome to these lectures on quantum computing.

I hope you excuse the initial difficulties, it's always nice to see that classical computing

hardware isn't perfect either.

Alright, so I want to start the lecture with a small introduction and appetizer before

then I get to start with the things I want to discuss about.

And to make things shiny I put on my front slide actually a picture, so this is from

Eric Luzero who is working at Google and the picture into one of their fridges that contains

one of the latest Google quantum computing hardware chips and actually I think on that

one you see the wiring but the chip isn't in there at this stage.

So first I just wanted to share a few thoughts, of course also from my perspective, why learning

about quantum computing is a useful and interesting thing to do at this stage.

And this has two important aspects, so one is, and that's been around for some time,

there's really a big promise in it in the sense that one knows from theory concepts

that it has truly revolutionary potential if the whole thing works.

So one of the most famous aspects of this is that quantum algorithms, in particular

Schor's algorithm, may eventually make most of the encryptions that we use today insecure.

So the way information is encrypted when you use your credit card may at some point be

trackable by quantum computers.

Another thing that I think has potential to become available much earlier than that is

that the huge computational power of quantum computers may allow to simulate how atoms

would form a material if you put them together, which to this stage is mostly a trial and

error thing.

You let some chemical reaction work and of course there is some experience that we have

built up over centuries now, what the properties of the upcoming material should be, so with

the ability to really numerically simulate the working of atoms, how they form molecules

and all this, there is a total new area of possibilities that becomes available in the

sense that how it is done now in engineering that before actually a company would build

a prototype of a car or whatever they try to simulate as much as they can, how they

should do this thing.

And that you could do in materials design and pharmaceutical science as well.

And of course if, so one prominent application or that is very much sought after these days

is so people hope to find new ways of building batteries.

So making cars run electrically rather than with fuel engines is one of the very hot topics

in industry today.

So it's mostly lithium ion batteries at this stage and these require some certain

admixture of cobalt and this cobalt for example is limited.

So one can estimate it's about 90 million batteries that you are able to build in this

way but then the cobalt is up and one can imagine that 90 million electrical cars won't

be sufficient.

So finding new ways of building batteries, designing materials that can store more energy,

building batteries without cobalt is something where there is a huge market behind and therefore

it generates a significant interest into the question whether quantum computing can help

there.

Okay, so this stage it's all theory promise and there is a question of like okay, or there

was for a long time a question of will it ever work and although that question isn't

fully answered in a positive way yet there has been very significant progress in the

recent years and all that generated also an increasing amount of investment into quantum

computing research and for example one very current thing, an article in Nature a couple

of days ago, the title is the quantum gold rush.

And this basically summarizes, so the abstract here summarizes what I've just been saying