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Quantum computers: How do they work and what will we use them for?

Quantum computers are set to revolutionize technology far beyond the capabilities of today's digital systems. While conventional computers work with bits, quantum computers use qubits to solve highly complex problems in record time. Despite ongoing development challenges, they offer enormous opportunities in sectors such as finance, chemistry, logistics, and cybersecurity. Thanks to its world-class research and strong industrial base, Switzerland is well-positioned to benefit from these groundbreaking innovations. Discover how quantum computing could transform your industry.

Quantum computers are set to revolutionize technology far beyond the capabilities of today's digital systems. While conventional computers work with bits, quantum computers use qubits to solve highly complex problems in record time. Despite ongoing development challenges, they offer enormous opportunities in sectors such as finance, chemistry, logistics, and cybersecurity.
Thanks to its world-class research and strong industrial base, Switzerland is well-positioned to benefit from these groundbreaking innovations. Discover how quantum computing could transform your industry.

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Quantum computers

How do they work and what will we use them for?

Our lives have been characterised by digital technology since the invention of the semiconductor microchip.

The world relies on billions of smartphones and PCs, electric cars and satellites. Quantum computers represent

a further step and are being worked on feverishly around the world. Given the major expectations and unanswered

questions involved, it is worth getting to know quantum computers and their amazing functionality

and astonishing advantages, but also their disadvantages.

Spectacular 2nd quantum revolution

Firstly, what do widely used microchips have to do with the still little

known quantum computers? Microchips utilise a number of quantummechanical

phenomena from the so-called 1st quantum revolution

(also known as “Quantum 1.0”, see glossary). However, what we call

a quantum computer only became possible with the 2nd quantum

revolution (or “Quantum 2.0”). New insights into quantum physics

and ongoing technical progress made its realisation possible.

The expected characteristics mean the new quantum computer

generation will be able to solve extremely complex problems in the

future. There is no shortage of positive prophecies, especially for

industries such as chemistry, materials science, finance, logistics and

meteorology. The area of cybersecurity may also be strongly affected

by this development and will most probably experience massive

further development. Traditional network components are already

being upgraded to make them “quantum-safe”, meaning they are

protected against the decryption of certain security codes by quantum

computers.

High hopes and (even) greater hurdles

Are these new types of computers a disruptive innovation, and will

all computers soon be calculating with quanta? What can be said

now is that quantum computers will not replace our everyday digital

devices in the foreseeable future, but will complement them for

certain tasks. They will certainly be superior to today’s computers

when it comes to solving special problems of enormous computational

intensity.

An example is the area of encryption technology. RSA encryption,

which is considered the global standard and is based on the factorisation

of prime numbers, can be cracked within hours, if not minutes,

using a quantum computer, but conventional computers

would take years or decades. That is why work is already underway

on “post-quantum cryptography”. It comes as no surprise that the

quantum computer is seen as “the next really big thing” in tech and

investment communities. It is sometimes claimed it could change

“everything”– a typical indication of hype.

Demystification and orientation

Quantum computers could indeed fundamentally change our world.

As soon as stable, available and economically viable systems are developed,

they are likely to become pioneering instruments in various

branches of industry, research areas and economic sectors. The question

is only when and how the quantum computer disruption or, at

the very least, transformation will occur. And what the technology

will really be capable of once the fog of speculation has lifted.

No universally applicable quantum computer currently exists that

would be superior to conventional high-performance computers.

Conversely, we know of tested and proven “simpler” quantum 2.0

applications such as quantum measurement technology. It impresses

with its accuracy, as this surpasses previous methods by several

orders of magnitude. However, it will take some years before the

quantum computer becomes part of everyday life.

Contents

High-tech revolution with new physics 2

Quantum phenomena 3

What are quantum computers capable of? 5

Quantum computer technologies “in competition” 6

Advantages and disadvantages 7

Switzerland, a quantum computing hub 10

Most promising applications 11

Amazing (quantum) computer history 14


High-tech revolution with new physics

Of all the new quantum technologies of the 2nd quantum revolution,

quantum computing is regarded as a cutting-edge discipline.

One needs to solve so many physical, technological and programming

problems that, despite enormous international efforts, it will

take some years before practical and efficient quantum computer

products can be expected. On the other hand, quantum computing

also embodies enormous potential which could profoundly

change certain areas of the economy and society.

Weighting and forecasting of different quantum technologies.

Quantum

computing

Difficulty / Complexity / Business potential

Quantum

sensing

Quantum

key

exchange

Quantum

communication

Quantum

imaging

Quantum

widgets/apps

Quantum

networks

Quantum

games

2020 2025 2030 2035 2040 2045

Source: QIDIS (Quantum Industry Day in Switzerland) 2021 / P. Seitz

Quantum technologies of the 2nd quantum

revolution

Products that make practical use of the insights of the 2nd quantum

revolution are already being manufactured, both worldwide and in

Switzerland:

– Quantum key exchange, quantum sensing technology and

quantum imaging: Findings from these first “fruits” of quantum

technology can already be exploited for practical applications and

further research.

– Quantum networks and communication: In just a few years,

functional, reliable quantum communication networks should be

possible. For physical reasons, the latter will be absolutely tapproof,

thanks to quantum technology (secure by physics). Experts

estimate that commercial communication channels with quantum

cryptography could appear in around five years. A secure quantum

internet, on the other hand, could still take until 2050.

– Quantum widgets and games: Humans have always been extremely

inventive in their use of new technologies, and unexpected

applications have sometimes found widespread use and

been greatly beneficial. We are, as yet, unfamiliar with “quantum

widgets” and “quantum games”, but it is possible that

some clever mind will soon surprise us with them.

– Quantum computers: These are, in a sense, the ultimate application

of quantum technology, as they will one day solve

problems that cannot be solved with conventional computer

hardware in a reasonable amount of time.

Global quantum computer race

Despite many unanswered questions and enormously expensive

technology, the race to utilise the advantages of quantum computers

efficiently is well underway. There is, after all, a lot at stake, as

the great potential of quantum computing ranges from scientific

and technological applications to economic progress.

“Quantum information science is a

completely new way of harnessing

nature. It will be the first technology

that allows useful tasks

to be performed in collaboration

between parallel universes.”

David Deutsch,

Dirac and Isaac Newton Medal Laureate

2


Quantum computer | 2024

Worldwide public sector investment in quantum technologies in USD million

Denmark

406

European Quantum Flagship

1100

Sweden

160

Russia

1450

The Netherlands

1000

Finland

27

China

15,000

Canada

1100

US National

Quantum Initiative

3750

Brazil

12

United Kingdom

4300

France

2200

Spain

67

Switzerland

900

Germany

3300

Austria

127

Hungary

11

Israel

390

Qatar

10

South Africa

3

India

735

Thailand

6

Singapore

138

South Korea

2350

Japan

700

Taiwan

282

Philippines

17

Australia

599

New Zealand

37

Source: “Overview of Quantum Initiatives Worldwide 2023”, QURECA, 19 July 2023. Department of Industry, Science and Resources, Austria; ETH Domain (ETH Zurich, EPFL, PSI).

The diagram illustrates global investment in

quantum technology in 2023, whereby quantum

computing is considered the main application

of quantum technologies (reliable figures solely

relating to the area of quantum computing are,

unfortunately, not available). By comparison,

China spends around USD 15 billion annually

on this, and Switzerland USD 900 million.

While most nations and companies focus on

one or a few types of implementations (see

Chapter 4), partly for reasons relating to

resources, those that make large investments

usually pursue several approaches at the same

time to achieve progress and results as quickly

as possible.

Quantum phenomena

With their semiconductor structures of only a few nanometres, the

best of conventional microprocessors today soon reach their physical

limitations. The well-known Moore’s law (which is, strictly speaking,

not a law, but a self-fulfilling prophecy that has so far proved

accurate) by Intel co-founder Gordon Moore states that the number

of transistors on an integrated circuit doubles on average every two

years because of the efforts of research and industry.

This constant miniaturisation will eventually end on the atomic level.

In the smallest dimensions of our universe, the laws of classical mechanics,

as formulated by Isaac Newton, tend to fail. In systems consisting

of nanoscale particles such as photons and electrons, the laws

of quantummechanics prevail, which often contradicts our perception

of every day laws.

Plenty of room at the bottom

Paradoxically, where it becomes smaller and smaller by our usual

standards, a huge world opens up – the world of quanta. “There’s

Plenty of Room at the Bottom” is the title of a visionary lecture

given by physicist and Nobel Prize winner Richard Feynman in 1959.

In this lecture, he presented his ideas on how technology could

work at a sub-microscopic level – or even further “down” in the no

longer visible, nanoscale world. Only gradually do we discover how

the world is structured at the smallest dimensional level of atoms

(see glossary).

How can you imagine these incredibly small particles? Depending

on the element, atoms are only about 1–5 tenths of a nanometre

in size. A nanometre is one billionth of a metre. A grain of dust

contains around 100 million billion atoms – more than there are

stars in the universe. Today’s microelectronics, semiconductor

technology and optoelectronics with their LEDs, laser diodes and

displays are based on the “Quantum 1.0” class, where the simpler

phenomena of quantum physics, such as the quantisation of energy

states, the existence of pure energy packets (photons) and the interaction

of electrons with these photons – also known as QED

(quantum electrodynamics) – are used.

The new quantum technologies of the “Quantum 2.0” class utilise

the physical phenomena and processes of quantum mechanics at

the atomic and subatomic level. They utilise three additional quantum

phenomena: superposition (superposition of base states, whereby

measurement results can only be predicted by probabilities), entanglement

(whereby all components of entangled systems “know

about each other”) and interference (the possibility of manipulating

quantum systems in such a way that “disturbing” states are subtracted).

3


Three prerequisites for quantum computing

Superposition

The bit, the smallest unit of a conventional digital

computer, can only assume two states – either 0 or 1

– and arithmetic operations are usually performed

sequentially. Unless the computer has cores that

work in parallel. A quantum bit (qubit) in a quantum

computer, on the other hand, is in a state of superposition

of – usually two – base states during the calculation. The “calculation”

in a quantum computer is performed by systematically manipulating the

probabilities that the qubits are in certain base states. The result of a quantum

calculation is obtained by reading out the qubits, whereby these are

found with a certain probability in one of the base states. This is also the

reason why a quantum computer cannot deliver “perfect” results, but only

“probabilities”. The more often you repeat a quantum calculation, the more

accurate the result will be.

The physical properties of a quantum unit therefore remain undefined until

they are measured. Nobody knows what value a qubit “really” has, not even

the universe. Albert Einstein felt very uncomfortable with the idea that physics

is determined by chance when he said: “God does not play dice.” And yet

today we know that this is the case. In a quantum physical system, there is

no certainty (before the measurement) as to where a quantum particle is or

what state it is in – there are only probabilities. You cannot know more

about a particle than these probabilities.

Our everyday experience is based on the assumption that all objects have a

well-defined state, always and everywhere. But this is precisely not the case

for quantum objects. This behaviour is sometimes explained by the fact that

quantum objects are in different base states at the same time, a condition

known as the superposition principle. But this description is only a “visualisation

aid” for the identity of quantum objects, which can only be described

correctly with mathematical probabilities. That’s why it is so difficult, indeed

almost impossible, to visualise this behaviour.

Entanglement

The physicists’ second insight,

which explains the enormous potential

of quantum computers, lies

in understanding another strange

quantum physical phenomenon,

namely that quantum objects can

be connected/entangled in such a way that they influence

each other, even over long distances. As soon as

the value of one quantum object is identified through

measurement, the value of its entangled twin is also

clear, and that means immediately, even before it is

measured. If you change the quantum state of one

qubit, all the other entangled qubits also “feel” this

change and their quantum state changes accordingly.

In a classical computer, the bits are stored and processed

independently of each other. This is not the case with a

quantum computer. Each calculation step always affects

all entangled qubits and, therefore, the entire quantum

computer. The number of variables that can be used for

calculations in a classical computer thus increases linearly

with the number of bits. In a quantum computer, on the

other hand, the number of information units that can be

stored and processed increases exponentially with the

number of qubits.

The surprising effect of the “entanglement” of quantum

systems, even across astronomical distances, was another

source of suspicion for Albert Einstein throughout his

life. He called it “spooky action at a distance”. The definitive

proof of quantum entanglement, which is now recognised

as the central property of quantum computers,

was only demonstrated experimentally in 2015, resulting

in the Nobel Prize being awarded in 2022 to Alain Aspect,

John Clauser and Anton Zeilinger.

Interference

Quantum mechanical interference is the

consequence of the fact that the behaviour

of a quantum system is described by combining

all possible processes of the development

of the quantum system. However, this

“combination” is not achieved by simply

adding the final states. Instead, it must be taken into account that

quantum states are represented by wave functions. For this reason,

the amplitudes of all the wave functions involved must be added

together for the correct combination – in the same manner as with

water waves, for example. This makes it possible for different wave

contributions to cancel each other out for a final result. This means

that quantum particles are not found at certain locations or in final

states where they would be expected in classical physics. This mutual

cancellation of wave functions is a central tool in the programming

of quantum computers, because the aim of every efficient

quantum computer algorithm is to make the probability distribution

of final results as narrow as possible, thus obtaining as high a statistical

significance of the results obtained as practically feasible.

4


Quantum computer | 2024

What are quantum computers capable of?

Surprisingly, a definitive answer does not yet seem to exist to this

simple and obvious question. Mathematical complexity theory

deals with precisely such central questions. What is the “complexity”

of a problem, meaning how does the effort required to solve

a problem increase when the number of parameters (the problem

size) is increased? Good-natured problems show an increase in

effort that rises with a potency (e.g. quadratic) with the size of the

problem. Such problems can be solved with classical computers in

a reasonable amount of time.

Unfortunately, many important problems exhibit exponential complexity

behaviour. The computational effort increases exponentially

with the size of the problem, and soon a limit is reached where even

the fastest classical computer needs far too much time to solve a

problem. Such practical problems include the factorisation of numbers

(which is used for conventional encryption), the packing problem

(how can one pack the maximum number of objects of different

dimensions into a prescribed volume), the travelling salesman

problem (how can one traverse a route which must pass through a

given number of locations in a minimum amount of time – compare

with use case 2) or the simulation of quantum systems (especially of

molecules and their interactions with other molecules).

Computing capacity still undefined

Although complexity mathematicians are aware of their responsibility

to finally bring order to the world of complexity, they have

not yet succeeded in precisely defining the limits of the computing

power of quantum computers. All we know today is that both the

factorisation problem and the quantum system simulation with

quantum computers do not increase exponentially with the size of

the problem, but only to the power of one. However, for the most

important optimisation problems, it is still unclear whether the

computing effort of quantum computers increases exponentially

with the size of the problem, as is the case for classical computers.

The adjacent graphic illustrates the complexity map of computational

problems assumed by most complexity theorists today. The

PSPACE (polynomial space) shown consists of the set of calculation

problems for which the memory requirement with conventional

computers does not increase exponentially (i.e. with a polynomial).

The NP area (non-deterministic polynomial time)

comprises the calculation problems whose solution can be checked

with conventional computers with polynomial effort. P describes

the subclass of NP problems that can also be solved with polynomial

effort using conventional computers. A particularly important

class are the problems that are labelled NP-complete. It was mathematically

proven that finding a single polynomial solution for one

of the NP-complete problems would also work for all others. However,

it is assumed that conventional computers would have to

expend exponential effort to solve this class of problem.

PSPACE

NPcomplete

P

BQP

NP

Illustration of the

probable complexity

map of computational

problems. By Scott

Aaronson, The Limits

of Quantum, Scientific

American, 2008

And what about the capabilities of quantum computers? This capability

is described by the BQP class (bounded-error quantum

polynomial time), which includes all problems that can be solved

by a quantum computer in polynomial time. If the BQP class were

also to include the eminently important NP-complete problems,

this could expand the possible applications of quantum computers

enormously and endow the technology with significant practical

importance. But complexity theory has still not been able to prove

this. Rather, it is assumed that the NP-complete problems are outside

the BQP class and that the practical significance of quantum

computers therefore remains limited. This uncertain situation is illustrated

by the cloudy boundary in the chart.

“In AI, practice is wildly ahead of theory, and there’s a race for

scientific understanding to catch up to where we’ve gotten via

the pure scaling of neural nets and the compute and data used to

train them. In quantum computing, it’s just the opposite: there’s

right now a race for practice to catch up to where theory has

been since the mid-1990s.”

Scott Aaronson, Quantum Computing: Between Hope and Hype, 2024

5


Quantum computer technologies “in competition”

There are currently around 15 approaches worldwide, some of which are completely different, to help quantum computing achieve a

breakthrough. All these systems are based on the phenomena of superposition and entanglement of qubits, and each of them has advantages

and shortcomings.

Superconducting circuits

One of the most widespread types are superconducting qubits. These consist of

superconducting microwave oscillating circuits with a frequency in the range between 4

and 8 GHz. They are cooled as low as possible down to a few millikelvin above the

(unattainable) absolute zero temperature. These qubits can be easily manipulated by

microwave pulses and lose practically no energy, as the current flows without resistance

(superconductivity).

The extreme cold stabilises the sensitive quantum states

in the qubits by greatly reducing thermal noise.

This method is characterised by the “chandelier” refrigerator (mixed cryostat), cooled

and electrically connected with countless fine cables (see cover image). The computing

unit with the qubits is located at the bottom and therefore in the coldest part, and is

encased in multiple insulating layers. IBM, Google, IQM and Rigetti, among others, rely

on this type of quantum computer.

Ion traps

In this type of quantum computer, atoms or molecules are captured and

manipulated, often in a vacuum, by electromagnetic fields and lasers in

order to process and store information. They are suitable for precision

measurements and applications that require great stability and control.

Players in this field include IonQ, AQT, Infineon, Oxford Ionics, Universal

Quantum, Quantinuum and eleQtron.

6

Neutral (cold) atoms

In quantum computers with neutral atoms, these are often

“captured” contact-free in an ultra-high vacuum with the help

of many focussed laser beams, the so-called optical tweezers.

These quantum computers are less sensitive to stray electric

fields, making them suitable for quantum processors. Pasqal,

Atom Computing, ColdQuanta, Planqc and QuEra are exponents

of this approach. Photo: An arrangement of many neutral

caesium atoms confined in a grid of optical traps formed by

laser light.

Photonic quantum computers

Photons (light particles) are used to store, transmit and process quantum

information in this design. For large-scale quantum computers, photonic

qubits are a promising alternative to quantum computers based on

trapped ions or neutral atoms which require cryogenic or laser-generated

cooling. However, these quantum computers have to use photons “in

flight”, and their programmability is therefore limited compared to other

architectures.

Companies such as PsiQuantum, Quantum Computing Inc, ORCA

Computing and Xanadu are active in this area, although their technical

approaches differ greatly.

Alternatives for the construction of a functional quantum

computer are electrons on helium, diamonds with

integrated nitrogen atom defects (NV diamond) and

the topological approach from Microsoft.

Quantum dots (QD)

Quantum dots are artificial atoms made of

semiconductor material where the potential for the

charge carriers is not defined by the atomic nucleus,

but by voltages on the metal electrodes on the

semiconductor surface. In most cases, the QD qubit

is then defined by two magnetic spin states which

are manipulated by different applications of spin

resonance.

The companies involved here include Diraq,

Siquance and Quantum Motion.

Illustrations: Adobe Stock Photo | Infineon Technologies | Preston Huft, Saffman Lab | Adobe Stock Photo | Adobe Stock Photo


Quantum computer | 2024

Utilisation of various physical effects for the implementation of qubits

Natural Qubits

Synthetic/Artificial Qubits

Trapped Ions Neutral Atoms Photonics Superconducting

Qubits

Silicon

Quantum Dots

Topological

Qubits

Nitrogen

Imperfections

in Artificial

Diamonds

Qubit

coherence

time (sec.)

>1,000 1 ––––––––––––––––––– 0.00005 0.03 N/A N/A

Fidelity 99.9% 97% ––––––––––––––––––– 99.4% ~99% N/A 99.2%

No.

connected

qubits

High

Very high, low

individual control

––––––––––––––––––– High Very Low N/A Low

Companies

IonQ, Quantinuum

(formerly

Honeywell)

Infleqtion

(formerly

ColdQuanta),

QuEra Computing,

Atom Computing,

Q-Block

Computing Inc.

PsiQuantum,

Xanadu, QC82,

Quantum

Computing Inc.

(QCI)

Google, IBM,

Quantum Circuits

(QCI), Rigetti and

many more

HRL, Intel, SQC

Microsoft,

Bell Labs

Quantum

Brilliance, Xeedq,

SaXonQ

Advantages

– Very stable

– Highest achieved

gate fidelities

Many qubits 2D,

possibly 3D

– Linear optical

gates

– Integrated on

chip

Can represent

physical circuits on

chip

Borrows from

existing

semiconductor

industry

Greatly reduced

errors

Can operate at

room temperature

Disadvantages

– Slow sequence

– Many lasers are

needed

– Hard to program

and control

individual qubits

– Prone to failure

– Each program

requires its own

chip with unique

optical channels.

– No memory

– Must be cooled

to near absolute

zero.

– High variability in

fabrication

– Very sensitive to

disruptive factors

– Only a few

connected.

– Must be cooled

to near absolute

zero.

– High variability in

fabrication

Existence not yet

confirmed

– Difficult to create

high number of

qubits – Limited

computing

capacity

Source: Science / Chris Monroe. With permission from Klea Dhimitri, Hamamatsu Photonics USA

Advantages and disadvantages

There is no doubt that quantum computers are capable of performing

important computational and optimisation tasks in a reasonable

amount of time. However, enormous efforts must still be made for

the development of hardware and software solutions if quantum

computers are actually to become suitable for everyday use and

can be applied by numerous programmers to solve their problems

efficiently.

A number of quantum computer applications already exist; some

are exploratory, others are demonstrative in character. In most cases,

these are problems that conventional computers can only solve

with a great deal of computing capacity or by using approximation

methods. Thanks to the further development of classic algorithms,

conventional computers still lead the way.

This is because the usefulness of today’s quantum systems is limited

by the occurrence of errors. In order to maintain the fragile state of a

completely entangled quantum system with hundreds or thousands

of qubits, a quantum computer must in practice always be errorcorrected

again after a few dozen calculation steps, or the executed

programs are limited to a few hundred sequential operations.

Intensive research is also being currently conducted into eliminating

the errors that occur during operation for a commercially viable

quantum computer through integrated continuous error correction.

Alternative approaches attempt to achieve the necessary quality of

results through post-processing. If the quantum processors used for

computing can be further improved and scaled up, quantum computers

will be more efficient than conventional supercomputers in

just a few years’ time when it comes to solving significant problems.

7


Finding the needle in the haystack

Quantum computers are particularly suitable for solving complex problems in a defined area. They will probably be

able to crack the encryption protocols most commonly used today (based on the time needed for the factorisation

of prime numbers) within a few hours or minutes. This is because complexity mathematics has proved that the factorisation

of large numbers with quantum computers does not increase exponentially with the size of the number.

Cracking encryption protocols will probably not be a task that every home computer will have to master. However,

there is a growing market for IT security companies, governments, secret services and other circles. The problem

of insufficiently secure encryption protocols has been recognised, and quantum-safe encryption is being successfully

developed on a global level.

Simulate nature!

The physicist Richard Feynman expressed it memorably in 1981:

Nature does not behave according to “classical” physics. Anybody

wishing to simulate (the smallest particles in) nature

should adopt a quantum mechanical approach. This was the

starting signal for quantum computing.

“Nature isn’t classical, dammit,

and if you want to make a

simulation of nature, you’d better

make it quantum mechanical.”

Richard Feynman (1918–1988), Nobel Laureate, was referring

to classical, Newtonian physics, which is unable to describe

quantum mechanical processes in nature.

The simulation of the quantum systems of nature

through another, more controllable quantum system

– the quantum computer – has proved to be extremely

difficult. However, enormous progress in

the isolation, manipulation and recognition of individual

quantum objects, especially in the last decade,

indicates that these physical implementations of

“quantum simulators” have become a reality – albeit

not yet a marketable reality.

Many experts expect that these applications of quantum

computing technology in particular will have a

lasting impact on life sciences. If the properties of

large molecules and their interaction with their chemical

environment can be calculated efficiently, then

“computational chemistry” will soon become part of

everyday life, even for molecules of great complexity.

Promising candidates for new drugs or new materials

can be determined on the computer and require

much less experimental effort. Interactions of new

drugs in the human body no longer need to be investigated

in countless clinical trials, as the “digital patient”

could be simulated with increasing reliability

using quantum computers.

8

An enormous effort

In order to restrict the freedom of particles, or solely their movement, they need to

be immobilised in as far as possible through extreme cooling. Liquid helium is

required for this purpose, and unfortunately helium cannot be extracted from air,

as it is so light that gravity cannot retain it in the Earth’s atmosphere. Helium is

the only noble gas separated as a component of natural gas, meaning helium is

primarily of fossil origin. It is therefore essential to work with closed-loop cooling

systems that enclose the helium used so well that it cannot escape from the

cooling circuit for years.

For even simpler quantum computers, it could also be desirable in the long term to

dispense which can be further miniaturised, extreme cooling with helium and for

systems to function at higher temperatures, perhaps even at room temperature.

Illustrations: Adobe Stock Photo | GL Archive / Alamy Stock Photo


Quantum computer | 2024

Fault tolerance and decoherence

However, a quantum computer has an unpleasant trait on account of its physical, probabilistic

properties. The calculation result is not a precise number, but a statistically distributed

answer. Therefore, the same calculation must be repeated many times and the final result

determined by statistical analysis, in the simplest case by averaging. For this reason, it is

clear from the outset that a quantum computer cannot be used for all computing problems.

For example, what use is the extremely rapid calculation of a large, complex spreadsheet

if the calculation results achieved are not precise?

The results produced by a quantum computer are therefore not precise numbers; rather, they

need to be complexly aggregated from the statistical results of many quantum calculations.

Furthermore, quantum entanglement can quickly become unbalanced if all qubits are no

longer perfectly entangled with each other. As a result, calculation errors can accumulate,

and the calculation result could be completely wrong. In addition, environmental disturbances

of various kinds can lead to the decoherence of the crucial phenomena of superpositioning

and entanglement. This is why quantum computer architectures must be implemented

in a fault-tolerant manner whenever possible. A logical qubit is represented by a

small armada of 10 to 20 physical qubits. These physical qubits can then be used to identify

and eliminate possible errors and inconsistencies in regular “consolidation operations”.

“Anyone who is not

confused by quantum

mechanics has not

really understood it.”

Niels Bohr (1885–1962),

Nobel Laureate

The input/output problem

Compared to classical computers, quantum

computers can be faster when it comes to

problems of great complexity concerning

relatively small amounts of data. Theoretically,

quantum computers far outperform

classical computers in terms of computing

speed, provided the computing effort in a

quantum computer for a particular problem

does not increase exponentially with the

size of the problem. However, the error corrections

required at short intervals, including

when saving a data record for a problem,

mean the quantum computer can only

input and output a limited data record (I/O).

In addition, the results depend heavily on

the suitability of the algorithms used. To

date, only a few basic quantum computer

algorithms exist that can solve important

problems efficiently. Accordingly, the initially

higher time expenditure required for the

quantum computer only pays off after a

certain period of time.

Experts therefore assume that quantum computers will primarily be suitable for “computationally

intensive, low-data” problems in the foreseeable future. When processing enormous

data sets, such as when training artificial intelligence, conventional supercomputer solutions

with huge numbers of specialised, parallel computing chips with a conventional architecture

are superior to quantum computing.

Comparison of classical computers and quantum computers:

Calculation time with increasing problem size

Time

Equilibrium time

Classical

computer

Problem size (N)

Parity size

Quantum

computer

For small-scale problems, a classical computer is unbeatable, because it calculates the

result precisely in a series of steps. However, if the problem grows substantially, it

suddenly needs exponentially more time for these many steps (see blue line). A quantum

computer, on the other hand, has a linear, flatly increasing performance curve. It

calculates parallel, but inaccurately, and needs to repeatedly correct errors. For a task

which we consider to be very easy, such as 2 + 2, it needs time, but the solution to a

major task does not take much longer. The quantum computer therefore has an advantage

when it comes to major problems. The two computers are equal where they have

the same time to solve a problem of size N (intersection point).

(Source: ETH Zurich, Microsoft, ACM / P. Seitz)

9


Switzerland, a quantum computing hub

The race to be at the forefront of quantum computing is getting

increasingly tougher. Switzerland has been an international pioneer

in this field for decades and has established a major network of

quantum research expertise. In May 2021, Switzerland withdrew

from the negotiations on bilateral agreements with the EU. As a

result, the European Commission decided to downgrade Switzerland

to a non-associated third country in Horizon Europe. Because

of the strategic importance of the EU’s major quantum programmes,

Swiss researchers are now excluded from participating in these programmes.

This weakens Switzerland as a centre of research in the

quantum field, because if we are no longer allowed to work directly

with the best in this field, we will only learn at a later stage about

the most promising new research approaches and disruptive breakthroughs.

Source: SWISSNEX, 2023

National Initiatives (Headquarters)

1 Swiss Quantum Initiative

2 NCCR SPIN

3 NCCR SwissMAP

University Centres and Research Hubs

1 The Quantum Center at ETH Zurich

2 The Basel Quantum Center and Swiss Nanoscience

Institute at the University of Basel

3 The Center for Quantum Science and

Engineering (QSE) at EPFL

4 The ETHZ-PSI Quantum Computing Hub

5 The Quantum Center at the University of Geneva

6 Swiss Federal Laboratories for Materials Science

and Technology (EMPA)

7 Università della Svizzera italiana (USI)

8 University of Applied Sciences and Arts Northwestern

Switzerland (FHNW)

9 Lucerne University of Applied Sciences and Arts

(HSLU)

Ecosystem Builders and Accelerators

1 Switzerland Innovation Park Basel

2 Switzerland Innovation Park Innovaare

3 Switzerland Innovation Park West EPFL

4 QuantumBasel

5 QAI Ventures

6 CERN

7 The Geneva Science and Diplomacy Anticipator

(GESDA)

8 Verve Ventures

Private Companies and Centres

1 IBM Research

2 ID Quantique

3 Basel Precision Instruments

4 Zurich Instruments

5 Qnami

6 Swiss Centre for Electronics and Microtechnology

(CSEM)

7 Swissphotonics

8 Miraex

9 QZabre

10 Ligentec

11 Enlightra

12 Terra Quantum

13 IonQ

Government

1 Swissnex HQ

Other

1 World Economic Forum (WEF)

It is almost impossible to portray the many dozens of players in the dynamic landscape of Swiss quantum technology. The map shows the most

important research and innovation centres for quantum technology, both public and private.

Nevertheless, Switzerland is well positioned to develop further as

one of the leading ecosystems for quantum technologies. Its

strengths lie in cooperation in a spirit of partnership, a long-term

commitment to research, world-class universities and cutting-edge

technology that has already produced top industrial products of

Swiss provenance. Last but not least, as the home of CERN, the

European Organisation for Nuclear Research, Switzerland has direct

access to basic research, enabling it to gain a deep understanding

of the structure of matter. New insights in the field of quantum

physics can also be expected.

Quantum computers are likely to be of great significance in Switzerland,

simply because added value created in this country largely

occurs in sectors that are predestined for the new quantum com-

puter calculations. Over 55% of Swiss exports are in the pharmaceutical

and chemical categories. Banks and insurance companies

are also very important, as tasks relating to optimisation, risk management

and the prevention of fraud are addressed here that can

be solved efficiently with quantum computers.

Take chemistry. If, for example, one wanted to calculate the chemical

properties of the caffeine molecule precisely, one would need 10 to

the power of 48 bits (1048 = an octillion, i.e. a 1 with 48 zeros), and

this is currently impossible with a conventional computer. Ideally, just

160 qubits are needed for this purpose with a quantum computer.

The fact that IBM, one of the leading manufacturers, has located part

of its basic quantum computer research in Switzerland speaks in favour

of the many positive factors that come together in Switzerland.

10


Quantum computer | 2024

Most promising applications

Quantum computing: A growing ecosystem and industrial applications

Pharmaceuticals, medicine:

– Discovery of new drugs

– Digital twins

– Precision medicine

Chemistry:

– New catalytic converters

– Energy optimisation

– Precision agriculture

Automation, logistics:

– Route planning

– Traffic optimisation

– Supply chain management

Financial industry:

– Portfolio/risk management

– Credit assessment

– Fraud prognosis

Source: McKinsey, Dec. 2021

Where can quantum computers really show their strengths? The assumption is quantum system simulation, optimisation tasks (e.g. resource/transport

planning) and risk assessments (e.g. banking and finance). Quantum computers will probably have the greatest significance

in the calculation of quantum processes themselves. Pharmaceutical and chemical products can probably be simulated precisely in

the foreseeable future and their therapeutic efficacy and probable side effects will reliably predicted.

How important is quantum technology in Switzerland?

Dr Andreas Fuhrer

Manager Superconducting Quantum Hardware

IBM Research Europe – Zurich

Illustrations: IBM Research Europe – Zurich | Adobe Stock Photo

“Quantum technology has been expedited by huge advances in

materials and (nano)-technology. Today, this enables us to control

the quantum properties of materials and components with

unprecedented accuracy. The high level of technological innovation,

which requires extremely clean, precise and reliable manufacturing

of components, and the likely revolutionary applications in the fields

of communications, finance, chemistry and process optimisation

make quantum technology a very attractive emerging market for

Swiss companies looking to strengthen their core competencies –

from start-ups to established SMEs and large global enterprises.”

11


Use case 1: Chemistry, biology, pharmacy

The development of drugs or vaccines usually takes years –

at present. Quantum computers together with AI could massively

shorten the key processes of synthesis and efficacy testing

by allowing the behaviour of molecules and chemical

reaction sequences to be simulated precisely and reducing

the time and effort required for chemical-biological

tests. This should make the development

of treatments and drugs speedier, more sustainable

and more precise. The development of novel

biological products from simulations of protein

folding could lead to a breakthrough, thanks to

quantum computing. The same applies in personalised

and precision medicine, where huge data sets of

genomes and therapy results could be combed through in a

short time to find the right approach.

In computer-aided drug design and molecular

modelling, even supercomputers can only deliver

relatively imprecise results. The quantum

computer could make years of laboratory testing

superfluous and greatly accelerate discoveries.

Developers also pin their hopes on the quantum computer for

the development of new medications from low-molecular

compounds. These have the advantage of being able to slip

through cell membranes and reach intercellular targets. The development

of more resilient crops, aggregate food or the

recycling of plastic waste by bacteria could also experience

a development boost with the aid of quantum computing. One

example is the extremely complex three-dimensional folding of

a protein to determine how and whether it can carry out its

functions in the body correctly. Predicting the spatial structure

(folding) of a protein on the basis of the amino acid sequence

is therefore akin to the holy grail of biochemistry today. Since

the quantum computer is effective in mapping other quantum

systems, it should be able to play to its strengths here.

12

“If you change the way

you look at things, the

things you look at change.”

Nobel Laureate Max Planck (1858–1947)

Illustrations: Wikipedia | Adobe Stock Photo


Quantum computer | 2024

Use case 2: Logistics, trade, production

A conventional computer searches for a route for a lorry from a starting point

to the destination (red needle). To achieve this, it drives along all possible

roads successively until it either finds a connection (image on right) or realises

that it has ended up in the wrong place (image on left).

Logistics today are globally intertwined and more

complex than ever. Quantum computers could make

an important contribution to enhancing efficiency

and, simultaneously, achieving energy-saving and climate

targets. Examples include the sustainable optimisation

of container ship and truck routes, the reduction

of return transports of empties, the

distribution, storage and preservation of fresh food or

bridging of the last delivery mile through the clever

use of transporters, bicycle messengers or drones. In a

similar way, goods and energy flows for production

processes (raw material extraction, agriculture, etc.)

could be optimised.

Quantum computers always have an advantage

when it comes to finding new ways and means to

deal with sudden interruptions or supply bottlenecks.

Compared to conventional computers,

the “turbo management” of such disruptions

is an easy task for the quantum computer,

working as it does with a lot of information

at the same time.

In contrast, the quantum computer calculates all routes simultaneously and finds the

right path at lightning speed.

“For a specific, but very important and practically relevant class of

combinatorial optimisation problems, quantum computers have

a fundamental advantage over classical computers.”

Jens Eisert and his team investigated the “travelling salesman’s problem” in 2024, namely visiting N reference points (cities etc.)

by the shortest route. As the number N increases, the computing time on a classical computer explodes (e.g. 10 cities: over 3.6 million

possible paths) – but this is not the case on a quantum computer.

13


Astonishing (quantum) computer history

The entanglement of

qubits is definitively

proven for the first time.

Alain Aspect, John F.

Clauser and Anton

Zeilinger receive the

Nobel Prize in Physics for

their work.

©TT News Agency /

Alamy Stock Photo

2022

D-Wave presents

the first commercial

quantum

computer with

128 qubits.

©Adobe Stock Photo

2011

The first

quantum

annealer

computer is

demonstrated.

2007

Establishment

of the Swiss

Quantum

Initiative SQI.

2023

Google claims to have

achieved the first “quantum

superiority” with its

Sycamore chip. However, the

fact that its quantum

computer is faster than any

conventional computer is

only true for a very specific

problem.

©Adobe Stock Photo

2019

IBM launches

“Quantum

Computing

as a Service”

(cloud access).

2016

The first 12-qubit

quantum computer

is developed

by researchers

from Canada and

the United States.

2006

William Shockley, John

Bardeen and Walter Brattain

invent the transistor. It is the basis

of modern microelectronics and

the digitalisation of our world.

©Wikipedia | Benedikt Seidl

1947

1964

©CERN

John Stewart Bell’s inequality states that

it is never violated in classical physics – but

it is in systems with quantum entanglement.

This theoretically refuted Einstein’s

conviction that “God does not play dice!”

(i.e. physics knows no coincidences or

probabilities). The Nobel Prize winners of

2022 provided the evidence.

©Wikipedia

Hertha Sponer makes extensive

contributions to the

application of quantum

theoretical methods in atomic

and molecular physics.

Together with Hedwig Kohn,

she confirms a number of

quantum mechanical

predictions in experiments.

1960

©Wikipedia

Erich Hückl formulates the fundamentals

of quantum chemistry.

Alexander Holevo proves

that n qubits can store

more information than n

classical bits.

1973

1940

©UtCon Collection /

Alamy Stock Photo

Erwin Schrödinger

formulates a quantum

mechanical wave equation

to calculate the probability

distribution for the

transport of quantum particles

and their possible

energetic states.

Werner Heisenberg, Max

Born and Pascual Jordan

publish the first conceptually

autonomous and logically

consistent formulation of

quantum mechanics based

on matrix calculations.

©Pictorial Press Ltd /

Alamy Stock Foto

1925

Albert Einstein, Boris Podolsky and Nathan

Rosen solve the EPR paradox named after

them. In theory, it should be possible to

perform a “measurement” on a particle without

disturbing it directly by performing this

measurement on a distant, entangled particle.

This fact could only be proven around 90 years

later.

©Adobe Stock Photo

1935

Albert Einstein describes

the photon and the photo

effect. His revolutionary light

quantum hypothesis states

that light consists of portions

(quanta) of energy. He is

awarded the Nobel Prize in

Physics in 1921 for this.

14


Quantum computer | 2024

The first five-photon

entanglement is

demonstrated by

Jian-Wei Pan.

©Uuongkinghe

2004

The race for

functional

quantum computers

First ion trap quantum

computer, first idea of

the adiabatic quantum

computer.

2000

© Infineon Technologies

1996

Lov Grover reveals the

first quantum search

algorithm. David

DiVincenzo defines the

criteria for a quantum

computer. Seth Lloyd

presents an algorithm that

can simulate quantum

mechanical systems.

Emanuel Knill,

Raymond Laflamme

and Gerard Milburn

establish linear

optical quantum

computing.

©BBC Bitesize

1

15

3

5

Lieven Vandersypen

and Matthias Steffen

publish the first

quantum computing

implementation of

Shor’s algorithm by

splitting the number

15 into its prime

numbers 3 and 5.

2001

Development of

quantum algorithms

©International Centre

for Theoretical Physics

1994/95

1981

Quantum computing in the lab

Richard Feynman proposes that

quantum phenomena be calculated

with a computer that uses/manipulates

individual quantum states and suggests

how a quantum computer could work.

David Deutsch formulates

the idea of the universal

quantum computer and the

principles of quantum

computing algorithms. He is

therefore regarded by many

as the founder of quantum

computing.

1985

Peter Shor publishes an algorithm

with which a future quantum

computer should be able to factorise

large integers exponentially faster

and, consequently, be able to crack

common encryption techniques. He

also proposes the first schemes for

quantum error correction.

Together with Paul Benioff and

David Deutsch, Richard Feynman

attempts to combine quantum

mechanics and computer science.

This means using quantum

simulators to simulate certain

problems that cannot be

modelled with a classical

supercomputer.

©Justinhsb

1982

1992

Ben Schumacher develops the first qubits and

the first Q-dots at the turn of the millennium.

Theoretical principles of quantum computing

Max Planck formulates the

hypothesis that energy states are

quantised. In 1919, he is awarded the

Nobel Prize in Physics for establishing

the quantum theory.

©André de Saint-Paul

1900

Invention of binary data processing

In 1725, Basile Bouchon from Lyon works on a way to

make textile weaving easier. Using a perforated roll of

paper that scans his mechanism, he succeeds in programming

fabric patterns. This is further developed with the aid

of J.-M. Jacquard’s punched cards (still in use 300 years

later!) that make his mechanical loom successful.

18th century

©Wikipedia

1905

By 1890, Herman Hollerith’s

electromechanical tabulating

machines were already using

millions of punched cards as

processing memory for the

US census. This requires an

entire system of punching,

reading and sorting devices.

Around 1820, Charles Babbage

invented the Difference Engine

and, in 1837, the first universal

calculating machine, the

Analytical Engine, both purely

mechanically operated devices.

The noblewoman Ada

Lovelace is the first person to

write a computer program for

the Analytical Engine.

©Wikipedia

19th century

15


Abstract

Unlike conventional computers, quantum computers do not calculate with digitally coded bits (0 and 1), but with a

superposition of the quantum states of several quantum bits (qubits). These systems, which consist of interacting

(entangled) nanoscale particles such as photons and electrons, are governed by the laws of quantum mechanics.

Quantum computers therefore have the unprecedented potential to solve highly complex computing and optimisation

tasks at great speed, but still require considerable development work in hardware and software to make

them suitable for everyday use.

Current applications of quantum computers demonstrate that classical computers with optimised algorithms are

currently still more efficient, as the susceptibility to errors and instability of quantum computers limits their usefulness.

Major advances in materials and nanotechnology have significantly advanced quantum technology, enabling

ever more precise control of quantum properties.

The new technology promises novel, revolutionary application options. Excellent quantum research is being

conducted in Switzerland in universities, research institutions and start-ups. As some of the anticipated fields of

application for quantum computers – including communications, finance, chemistry, pharmaceuticals, logistics and

process optimisation – correlate with the established strengths of the Swiss industry and economy, our country

could benefit significantly from this development in the coming years.

The Swiss Academy of Engineering Sciences SATW is the most important network of experts for

engineering sciences in Switzerland and is in contact with the highest Swiss bodies for science, politics

and industry. The network is comprised of elected individual members, member organisations and

experts.

On behalf of the federation, SATW identifies industrially relevant technological developments and

informs politics and society about their importance and consequences. As a unique expert organisation

with high credibility, it conveys independent and objective information on technology – as the

basis for establishing well-founded opinions. SATW also promotes the interests and understanding of

technology in the population, including young people in particular. It is politically independent and

non-commercial.

Imprint

Authors: Prof. Peter Seitz, Caspar Türler

Editing: Translingua AG

Cover image: Adobe Stock Photo

Design: Andy Braun

Print: Egger Druck

December 2024

DOI: doi.org/10.5281/zenodo.14040194

Swiss Academy of Engineering Sciences (SATW)

St. Annagasse 18 | 8001 Zurich | 044 226 50 11 | info@satw.ch | www.satw.ch


Glossary

Absolute zero temperature

Absolute zero, meaning the physically lowest possible temperature, is around three degrees lower

than the temperature in space, namely minus 273.15 degrees Celsius or 0 degrees Kelvin. This lowest

temperature is achieved down to a few millionths of a degree in the laboratories of low-temperature

physicists. It is possible to generate temperatures of up to approximately 1 millikelvin with a helium

mixture (i.e. within approximately one thousandth of a degree Celsius of absolute zero) in the laboratory.

Atom

In the 5th century BC, the ancient philosopher Leucippus of Miletus and his pupil Democritus of

Abdera developed the concept that the world was made up of a number of tiny, indivisible particles

known as atoms (Greek: átomos, “the indivisible”). We recognise 118 atoms in the periodic system of

chemical elements today, along with the particles of which they consist: protons and neutrons that

form the core, and electrons that surround this core. Protons and neutrons are in turn composed of up

quarks and down quarks. With its cloud of electrons, the atom is around 100,000 times larger than its

nucleus. If the atomic nucleus were the size of an apple, the atom would have a diameter of around

10 kilometres. Although we perceive matter as solid, individual atoms are largely empty. Even a diamond

consists mainly of empty space!

Bit

A portmanteau of binary digit, the binary number has the value 1 or 0. It is the unit of measurement for

the amount of digitally represented data (stored, transmitted).

Quantum

Originating from the Latin quantus (how big? how much?), this is the smallest known unit of measurement.

A particle confined in a finite space can only assume a limited number of energy states, as the

energy of the particle is quantised. A quantum is therefore an object that is generated by a change of

state in a system with discrete (quantised) values of a physical quantity. Quantised quantities are described

within the framework of quantum mechanics and sub-areas of theoretical physics inspired by

this, such as quantum electrodynamics. For example, light of a fixed frequency delivers energy in the

form of quanta called “photons”. Each photon of this frequency has the same amount of energy, and

this energy cannot be broken down into smaller units. Every atom in the universe contains quanta.

The human body alone consists of around 7x10 to the power of 27 atoms, equivalent to 7 quadrillion

(or 7 billion billion billion) atoms.

Quantum revolution 1.0

Technologies based on the understanding of fundamental quantum mechanical effects, in particular

the quantisation of energy, the existence of pure energy packets (photons), the interaction of photons

and electrons, quantum tunnelling phenomena or spin. This allows valuable products such as transistors

and chips, semiconductor sensors, LEDs, laser diodes, photovoltaic cells and magnetic resonance

tomographs to be realised.

Quantum revolution 2.0

Technologies that utilise additional quantum phenomena, in particular

– superposition (the condition of a quantum object can only be described as probability distribution,

where different basic conditions are detected through measurement);

– interference (quantum states can be manipulated so that certain final states can be excluded, meaning

their probability is subtracted to a minimum);

– entanglement (where the components of an entangled quantum system are instantaneously

“aware” of each other, meaning the component measurement results are strictly correlated). Consequently,

products with enormously enhanced performance can be realised, including quantum computers,

absolutely tap-proof quantum communication networks, quantum sensors with a sensitivity

enhanced by several orders of magnitude or quantum microscopy.

Qubit: Quantum bit

A system of two states that can only be correctly described by quantum mechanics, and which has

only two states that can be reliably distinguished by measurement. The qubit plays a role analogous to

the classic bit in conventional computers. It serves as the smallest possible storage unit and, simultaneously,

defines a measure for quantum information. Today’s qubits have a size of between 10 to the

power of -3 metres (= 1 millimetre) and 10 to the power of -10 metres (= 0.1 nanometres or 1 ten

billionth of a metre).


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