Artificial Intelligence - Quantum AI.

 

Artificial intelligence and quantum computing, according to Johannes Otterbach, a physicist at Rigetti Computing in Berkeley, California, are natural friends since both technologies are essentially statistical.

Airbus, Atos, Baidu, b|eit, Cambridge Quantum Computing, Elyah, Hewlett-Packard (HP), IBM, Microsoft Research QuArC, QC Ware, Quantum Benchmark Inc., R QUANTECH, Rahko, and Zapata Computing are among the organizations that have relocated to the region.

Bits are used to encode and modify data in traditional general-purpose computer systems.

Bits may only be in one of two states: 0 or 1.

Quantum computers use the actions of subatomic particles like electrons and photons to process data.

Superposition—particles residing in all conceivable states at the same time—and entanglement—the pairing and connection of particles such that they cannot be characterized independently of the state of others, even at long distances—are two of the most essential phenomena used by quantum computers.

Such entanglement was dubbed "spooky activity at a distance" by Albert Einstein.

Quantum computers use quantum registers, which are made up of a number of quantum bits or qubits, to store data.

While a clear explanation is elusive, qubits might be understood to reside in a weighted combination of two states at the same time to yield many states.

Each qubit that is added to the system doubles the processing capability of the system.

More than one quadrillion classical bits might be processed by a quantum computer with just fifty entangled qubits.

In a single year, sixty qubits could carry all of humanity's data.

Three hundred qubits might compactly encapsulate a quantity of data comparable to the observable universe's classical information content.

Quantum computers can operate in parallel on large quantities of distinct computations, collections of data, or operations.

True autonomous transportation would be possible if a working artificially intelligent quantum computer could monitor and manage all of a city's traffic in real time.

By comparing all of the photographs to the reference photo at the same time, quantum artificial intelligence may rapidly match a single face to a library of billions of photos.

Our understanding of processing, programming, and complexity has radically changed with the development of quantum computing.

A series of quantum state transformations is followed by a measurement in most quantum algorithms.

The notion of quantum computing goes back to the 1980s, when physicists such as Yuri Manin, Richard Feynman, and David Deutsch realized that by using so-called quantum gates, a concept taken from linear algebra, researchers would be able to manipulate information.

They hypothesized qubits might be controlled by different superpositions and entanglements into quantum algorithms, the outcomes of which could be observed, by mixing many kinds of quantum gates into circuits.

Some quantum mechanical processes could not be efficiently replicated on conventional computers, which presented a problem to these early researchers.

They thought that quantum technology (perhaps included in a universal quantum Turing computer) would enable quantum simulations.

In 1993, Umesh Vazirani and Ethan Bernstein of the University of California, Berkeley, hypothesized that quantum computing will one day be able to effectively solve certain problems quicker than traditional digital computers, in violation of the extended Church-Turing thesis.

In computational complexity theory, Vazirani and Bernstein argue for a special class of bounded-error quantum polynomial time choice problems.

These are issues that a quantum computer can solve in polynomial time with a one-third error probability in most cases.

The frequently proposed threshold for Quantum Supremacy is fifty qubits, the point at which quantum computers would be able to tackle problems that would be impossible to solve on conventional machines.

Although no one believes quantum computing would be capable of solving all NP-hard issues, quantum AI researchers think the machines will be capable of solving specific types of NP intermediate problems.

Creating quantum machine algorithms that do valuable work has proved to be a tough task.

In 1994, AT&T Laboratories' Peter Shor devised a polynomial time quantum algorithm that beat conventional methods in factoring big numbers, possibly allowing for the speedy breakage of current kinds of public key encryption.

Since then, intelligence services have been stockpiling encrypted material passed across networks in the hopes that quantum computers would be able to decipher it.

Another technique devised by Shor's AT&T Labs colleague Lov Grover allows for quick searches of unsorted datasets.

Quantum neural networks are similar to conventional neural networks in that they label input, identify patterns, and learn from experience using layers of millions or billions of linked neurons.

Large matrices and vectors produced by neural networks can be processed exponentially quicker by quantum computers than by classical computers.

Aram Harrow of MIT and Avinatan Hassidum gave the critical algorithmic insight for rapid classification and quantum inversion of the matrix in 2008.

Michael Hartmann, a visiting researcher at Google AI Quantum and Associate Professor of Photonics and Quantum Sciences at Heriot-Watt University, is working on a quantum neural network computer.

Hartmann's Neuromorphic Quantum Computing (Quromorphic) Project employs superconducting electrical circuits as hardware.

Hartmann's artificial neural network computers are inspired by the brain's neuronal organization.

They are usually stored in software, with each artificial neuron being programmed and connected to a larger network of neurons.

Hardware that incorporates artificial neural networks is also possible.

Hartmann estimates that a workable quantum computing artificial intelligence might take 10 years to develop.

D-Wave, situated in Vancouver, British Columbia, was the first business to mass-produce quantum computers in commercial numbers.

In 2011, D-Wave started producing annealing quantum computers.

Annealing processors are special-purpose products used for a restricted set of problems with multiple local minima in a discrete search space, such as combinatorial optimization issues.

The D-Wave computer isn't polynomially equal to a universal quantum computer, hence it can't run Shor's algorithm.

Lockheed Martin, the University of Southern California, Google, NASA, and the Los Alamos National Laboratory are among the company's clients.

Universal quantum computers are being pursued by Google, Intel, Rigetti, and IBM.

Each one has a quantum processor with fifty qubits.

In 2018, the Google AI Quantum lab, led by Hartmut Neven, announced the introduction of their newest 72-qubit Bristlecone processor.

Intel also debuted its 49-qubit Tangle Lake CPU last year.

The Aspen-1 processor from Rigetti Computing has sixteen qubits.

The IBM Q Experience quantum computing facility is situated in Yorktown Heights, New York, inside the Thomas J.

Watson Research Center.

To create quantum commercial applications, IBM is collaborating with a number of corporations, including Honda, JPMorgan Chase, and Samsung.

The public is also welcome to submit experiments to be processed on the company's quantum computers.

Quantum AI research is also highly funded by government organizations and universities.

The NASA Quantum Artificial Intelligence Laboratory (QuAIL) has a D-Wave 2000Q quantum computer with 2,048 qubits that it wants to use to tackle NP-hard problems in data processing, anomaly detection and decision-making, air traffic management, and mission planning and coordination.

The NASA team has chosen to concentrate on the most difficult machine learning challenges, such as generative models in unsupervised learning, in order to illustrate the technology's full potential.

In order to maximize the value of D-Wave resources and skills, NASA researchers have opted to focus on hybrid quantum-classical techniques.

Many laboratories across the globe are investigating completely quantum machine learning.

Quantum Learning Theory proposes that quantum algorithms might be utilized to address machine learning problems, hence improving traditional machine learning techniques.

Classical binary data sets are supplied into a quantum computer for processing in quantum learning theory.

The NIST Joint Quantum Institute and the University of Maryland's Joint Center for Quantum Information and Computer Science are also bridging the gap between machine learning and quantum computing.

Workshops bringing together professionals in mathematics, computer science, and physics to use artificial intelligence algorithms in quantum system control are hosted by the NIST-UMD.

Engineers are also encouraged to employ quantum computing to boost the performance of machine learning algorithms as part of the alliance.

The Quantum Algorithm Zoo, a collection of all known quantum algorithms, is likewise housed at NIST.

Scott Aaronson is the director of the University of Texas at Austin's Quantum Information Center.

The department of computer science, the department of electrical and computer engineering, the department of physics, and the Advanced Research Laboratories have collaborated to create the center.

The University of Toronto has a quantum machine learning start-up incubator.

Peter Wittek is the head of the Quantum Machine Learning Program of the Creative Destruction Lab, which houses the QML incubator.

Materials discovery, optimization, and logistics, reinforcement and unsupervised machine learning, chemical engineering, genomics and drug discovery, systems design, finance, and security are all areas where the University of Toronto incubator is fostering innovation.

In December 2018, President Donald Trump signed the National Quantum Initiative Act into law.

The legislation establishes a partnership of the National Institute of Standards and Technology (NIST), the National Science Foundation (NSF), and the Department of Energy (DOE) for quantum information science research, commercial development, and education.

The statute anticipates the NSF and DOE establishing many competitively awarded research centers as a result of the endeavor.

Due to the difficulties of running quantum processing units (QPUs), which must be maintained in a vacuum at temperatures near to absolute zero, no quantum computer has yet outperformed a state-of-the-art classical computer on a challenging job.

Because quantum computing is susceptible to external environmental impacts, such isolation is required.

Qubits are delicate; a typical quantum bit can only exhibit coherence for ninety microseconds before degrading and becoming unreliable.

In an isolated quantum processor with high thermal noise, communicating inputs and outputs and collecting measurements is a severe technical difficulty that has yet to be fully handled.

The findings are not totally dependable in a classical sense since the measurement is quantum and hence probabilistic.

Only one of the quantum parallel threads may be randomly accessed for results.

During the measuring procedure, all other threads are deleted.

It is believed that by connecting quantum processors to error-correcting artificial intelligence algorithms, the defect rate of these computers would be lowered.

Many machine intelligence applications, such as deep learning and probabilistic programming, rely on sampling from high-dimensional probability distributions.

Quantum sampling methods have the potential to make calculations on otherwise intractable issues quicker and more efficient.

Shor's method employs an artificial intelligence approach that alters the quantum state in such a manner that common properties of output values, such as symmetry of period of functions, can be quantified.

Grover's search method manipulates the quantum state using an amplification technique to increase the possibility that the desired output will be read off.

Quantum computers would also be able to execute many AI algorithms at the same time.

Quantum computing simulations have recently been used by scientists to examine the beginnings of biological life.

Unai Alvarez-Rodriguez of the University of the Basque Country in Spain built so-called artificial quantum living forms using IBM's QX superconducting quantum computer.

~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram

You may also want to read more about Artificial Intelligence here.

See also: 

General and Narrow AI.

References & Further Reading:

Aaronson, Scott. 2013. Quantum Computing Since Democritus. Cambridge, UK: Cambridge University Press.

Biamonte, Jacob, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd. 2018. “Quantum Machine Learning.” https://arxiv.org/pdf/1611.09347.pdf.

Perdomo-Ortiz, Alejandro, Marcello Benedetti, John Realpe-Gómez, and Rupak Biswas. 2018. “Opportunities and Challenges for Quantum-Assisted Machine Learning in Near-Term Quantum Computers.” Quantum Science and Technology 3: 1–13.

Schuld, Maria, Ilya Sinayskiy, and Francesco Petruccione. 2015. “An Introduction to Quantum Machine Learning.” Contemporary Physics 56, no. 2: 172–85.

Wittek, Peter. 2014. Quantum Machine Learning: What Quantum Computing Means to Data Mining. Cambridge, MA: Academic Press

Quantum Computing Keywords

We can start to focus in on qubit modalities by composing a working quantum computing vocabulary:

Table Of Contents
What Are Qubits?
What Is A Universal Quantum Computer?
What Is Quantum Annealing?
What Is Quantum Speedup?
What Is Quantum Edge?
What Is Quantum Supremacy?
What Is A Bloch Sphere?
What Is Coherence in Quantum Computing?
What Is DiVincenzo Criteria?
What Is Quantum Entanglement?
What Is Measurement In Quantum Computing?
What Are Quantum Dots?
What Is Quantum Error Correction?
What Is Quantum Indeterminacy?
What Is Quantum Tunneling?
What Is Superposition?
What Is Teleportation In Quantum Computing?
What Is A Topological Quantum Computer?

What Are Qubits?

The quantum equivalent of conventional digital bits are qubits (quantum bits). 

• The qubits are in a state of superposition and operate on quantum mechanics principles. 

• To alter the state of the qubits, we must use quantum mechanics concepts. 

• We can measure the state of the qubits at the conclusion of the computation by projecting them into conventional digital bits. 

What Is A Universal Quantum Computer?

A Quantum Turing Machine, also known as a Universal Quantum Computer, is an abstract machine that is used to simulate the effects of a quantum computer. 

• Any quantum algorithm may be described formally as a particular quantum Turing Machine, similar to the conventional Turing Machine. 

Quantum states defined in Hilbert space are used to represent internal states. 

• In Hilbert space, the transition function is a collection of unitary matrices. 

What Is Quantum Annealing?

Quantum Fluctuations are used to discover a heuristic method that finds a global minimum from a limited collection of candidate solutions. 

• Quantum Annealing may be used to tackle combinatorial optimization problems having a discrete search space with multiple local minima, such as the traveling salesman problem. 

• The system begins with the quantum parallelism superposition of all possible states and evolves using the time-dependent Schrodinger equation. 

• The amplitudes of all states may be altered by changing the transverse field (a magnetic field perpendicular to the axis of the qubit), resulting in Quantum Tunneling between them. 

The aim is to maintain the system as near to the Hamiltonian's ground state as possible. 

• The system achieves its ground state when the transverse field is eventually switched off, which corresponds to the solution of the optimization issue. 

• D-Wave Systems exhibited the first Quantum Annealer in 2011. 

What Is Quantum Speedup?

This is the best-case situation, in which no classical algorithm can outperform a quantum algorithm. 

• There are a few quantum algorithms that have a polynomial speedup in addition to factorization and discrete logarithms. 

• Grover's algorithm is one such algorithm. 

There have been reports on simulation methods for physical processes in quantum chemistry and solid-state physics. 

• The main ideal problem in polynomial time and an approximation method for Jones polynomial with a polynomial speedup and a solution to Pells' equation have been presented. 

• This area is changing. 

What Is Quantum Edge?

Quantum computers have a computational advantage. 

• The idea that quantum computers can execute certain calculations more quickly than traditional computers. 

What Is Quantum Supremacy? 

Quantum computers' prospective capacity to tackle issues that conventional computers can't. 

• Decoherence is the process by which the quantum information in a qubit is lost over time as a result of interactions with the environment. 

• Quantum Volume is a practical method to track and compare progress toward lower system-wide gate error rates for quantum computing and error correction operations in the near future. 

• It's a single-number metric that a concrete protocol can measure with a quantum computer of modest size n <=50 in the near future.

What Is A Bloch Sphere?

The Bloch sphere, named after scientist Felix Bloch, is a geometrical representation of the pure state space of a two-level quantum mechanical system (qubit) in quantum mechanics. 

• Antipodal points correspond to a pair of mutually orthogonal state vectors on the Bloch sphere, which is a unit sphere. 

The Bloch Sphere's interpretation is as follows: 

• The poles represent classical bits, and the notation |0 and |1 is used to denote them. 

• Unlike conventional bit representation, where these are the only conceivable states, quantum bits span the whole sphere. 

• As a result, quantum bits contain a lot more information, as shown by the Bloch sphere. 

• When a qubit is measured, one of the two poles collapses. 

Which of the two poles collapses depends on which direction the arrow in the Bloch representation points: 

• if the arrow is closer to the north pole, there is a greater chance of collapsing to that pole; similarly, 
• if the arrow is closer to the south pole, there is a greater chance of collapsing to that pole. 

This adds the concept of probability to the Bloch sphere: 

• the angle of the arrow with the vertical axes correlates to that probability. 

• If the arrow points to the equator, each pole has a 50/50 probability of collapsing.

What Is Coherence in Quantum Computing?

A qubit's coherence is defined as its capacity to sustain superposition across time. 

• It is therefore the lack of "decoherence," which is defined as any process that collapses a quantum state into a classical one, such as contact with the environment.

What Is  DiVincenzo Criteria?

The DiVincenzo criteria are a set of requirements for building a quantum computer that were originally suggested by theoretical physicist David P. DiVincenzo in his article "The Physical Implementation of Quantum Computation" in 2000. 

The DiVincenzo criteria are a collection of 5+2 requirements that must be met by an experimental setup in order to effectively execute quantum algorithms like Grover's search algorithm or Shor factorization. 

To perform quantum communication, such as that utilized in quantum key distribution, the two additional requirements are required.

1 – A physically scalable system with well-defined qubits.

2 – The ability to set the qubits' states to a simple fiducial state.

3 – Long decoherence periods that are relevant.

4 – A set of quantum gates that is “universal.”

5 – A measuring capability unique to qubits.

6 — Interconversion of stationary and flying qubits.

7 – The capacity to reliably transfer flying qubits between two points.

What Is Quantum Entanglement?

Quantum entanglement is a unique relationship that exists between two qubits. 

• Entanglement may be created in a variety of ways. 

• One method is to entangle two qubits by bringing them close together, performing an operation on them, and then moving them apart again. 

• You may move them arbitrarily far away from each other after they're entangled, and they'll stay intertwined. 

The results of measurements on these qubits will reflect this entanglement. 

• When measured, these qubits will always provide a random result of zero or one, regardless of how far apart they are. 

The first characteristic of entanglement is that it cannot be shared, which allows all of the applications that are derived from it to be created. 

• If two qubits are maximally entangled, no other person in the universe may share their entanglement. 

• The monogamy of entanglement is the name given to this feature.

Maximum coordination is the second characteristic of entanglement that gives it its strength. 

• When the qubits are measured, this characteristic is shown. 

• When two entangled qubits are measured in the same basis, no matter how far apart they are, the result is always the same. 

• This result is not predetermined; rather, it is entirely random and determined at the time of measurement.

What Is Measurement In Quantum Computing?

The act of seeing a quantum state is known as measurement. 

• This observation will provide traditional data, such as a bit. 

• It's essential to remember that the quantum state will change as a result of this measurement procedure. 

If the state is in superposition, for example, this measurement will cause it to ‘collapse' into a classical state: zero or one. 

• This process of collapsing occurs at random. 

• There is no way of knowing what the result will be until the measurement is completed. 

• However, the chance of each result may be calculated. 

This probability is a prediction about the quantum state that we can test by preparing it many times, measuring it, and calculating the percentage of each result.

What Are Quantum Dots?

Quantum dots may be thought of as "manufactured atoms." 

• They are semiconductor nanocrystals in which an electron-hole pair may be trapped. 

• Because the nanoscale size is equivalent to the wavelength of light, the electron may occupy distinct energy levels, exactly as in an atom. 

• The dots may be encased in a photonic crystal cavity and probed with laser light.

What Is Quantum Error Correction?

Quantum computers are always in touch with the outside world. This environment has the potential to disrupt the system's computational state, resulting in data loss. 

• Quantum error correction compensates for this loss by distributing the system's computational state over multiple qubits in an entangled state. 

• Outside classical observers may detect and correct perturbations using this entanglement without having to see the computational state directly, which would collapse it.

What Is Quantum Indeterminacy?

The basic condition of existence, backed up by all empirical evidence, in which an isolated quantum system, like as a free electron, does not have fixed characteristics until those attributes are seen in experiments intended to quantify them. 

• That is, unless those characteristics are measured, a particle does not have a particular mass, location, velocity, or spin. 

• Indeed, the particle does not exist until it is seen in a strict sense.

What Is Quantum Tunneling?

Due to the wave-like nature of particles, quantum tunneling is a quantum mechanical phenomenon in which particles have a limited chance of overcoming an energy barrier or transiting through an energy state usually prohibited by classical physics. 

• A particle's probability wave reflects the likelihood of locating the particle in a certain place, and there is a limited chance that the particle is on the opposite side of the barrier.

What Is Superposition?

Quantum physics' basic premise is superposition. 

• It asserts that quantum states, like waves in classical physics, may be joined together – superposed – to produce a new valid quantum state, and that every quantum state can be seen as a linear combination, a sum of other unique quantum states.

What Is Teleportation In Quantum Computing?

Quantum teleportation is a technique that uses entanglement to transmit qubits. 

• The following is how teleportation works: 

• Initially, Alice and Bob must create an entangled pair of qubits between them. 

• Alice next conducts a measurement on the qubit she wishes to transmit as well as the qubit that is entangled with Bob's qubit. 

• This measurement compresses the qubits and breaks the entanglement, but it also provides her with two classical outcomes in the form of two classical bits. 

• Alice transmits these two traditional bits to Bob over the traditional Internet. 

• Bob next applies to his qubit a rectification operation that is based on these two classical bits. 

• As a result, he is able to reclaim the qubit that was previously in Alice's control. 

It's worth noting that we've now sent a qubit without really utilizing a physical carrier capable of doing so. 

To accomplish this, you'll need entanglement, of course. 

It's also worth noting that quantum teleportation doesn't allow for communication faster than the speed of light. 

• This is because Bob will not be able to make sense of the qubit she has in her hands until he receives the classical measurement results from Alice. 

• The transmission of these traditional measurement results must take a certain length of time. 

• This time is also constrained by the speed of light.

What Is A Topological Quantum Computer?

A topological quantum computer is a theoretical quantum computer that uses anyons, which are two-dimensional quasiparticles whose world lines intersect to create braided in a three-dimensional spacetime (i.e., one temporal plus two spatial dimensions). 

• The logic gates that make up the computer are formed by these strands. 

• The benefit of utilizing quantum braiding over trapped quantum particles in a quantum computer is that the former is considerably more stable. 

• Small, cumulative perturbations may cause quantum states to decohere and create mistakes in computations, but they have no effect on the topological characteristics of the braiding. 

• This is comparable to the work needed to cut a string and reconnect the ends to create a new braid, rather than a ball (representing an ordinary quantum particle in four-dimensional spacetime) colliding with a wall. 

In 1997, Alexei Kitaev suggested topological quantum computing.

~ Jai Krishna Ponnappan

You may also want to read more about Quantum Computing here.

Quantum Computing - A New Way to Compute

 

Google formally debuted their newly created Sycamore quantum processor in 2019 and claimed to have completed the first computation that was simple for a quantum computer but extremely challenging for even the most powerful supercomputers. 

Previously, continuous breakthroughs in transistor fabrication technology had propelled the world's ever-increasing computer capability. Computing power has increased dramatically during the last 50 years. 

Despite these significant technical advancements, the underlying mathematical laws that govern computers have remained basically constant. 

Google's demonstration of so-called "quantum supremacy," also known as "quantum advantage," was based on 30 years of advancements in mathematics, computer science, physics, and engineering, and it heralded the start of a new era that might cause considerable upheaval in the technology landscape. 

Traditional (‘classical') computers work with data encoded in bits, which are often represented by the presence (or absence) of a little electrical current. 

According to computational complexity theory, this option leads to issues that will always be too expensive for traditional computers to solve. Simply put, the traditional cost of modelling complicated physical or chemical systems doubles with each extra particle added. 

In the early 1980s, American Nobel Laureate Richard Feynman proposed quantum computers as a solution to avoid this exponential expense. 

Information is encoded in quantum mechanical components called qubits, and quantum computers manage this information. 

Qubits are encoded by superconducting electrical currents that may be modified by precisely engineered electrical componentry in Google's Sycamore processor, for example. 

The ‘factoring problem,' in which a computer is entrusted with identifying the prime factors of a big number, remained an academic curiosity until quantum computers were shown to be capable of solving it effectively. 

The RSA public-key cryptosystem, which is a cornerstone of internet security, is based on this key issue. 

With that finding, a flurry of research activity erupted throughout the world to see if quantum computers could be developed and if so, how powerful they could be.