Quantum Computing 2019

Quantum Computing 2019

What Is Quantum Computing All About? Michael I. Shamos, Ph.D., J.D. School of Computer Science Carnegie Mellon University THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS 22 FEB 2019 THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Background • A.B., Princeton University (physics, 1968) • M.A., Vassar College (physics, 1970) • Ph.D., Yale University (computer science, 1978) • J.D., Duquesne University (law, 1981) • Carnegie Mellon Computer Science faculty (1975 -) – Institute for Software Research – Language Technologies Institute • Director, eBusiness Technology Master’s Program (2002-2018) (roughly equivalent to ECOM-ICOM) • Director, MS in Artificial Intelligence and Innovation • Visiting Professor, University of Hong Kong (2001-) THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Limits on Computing • By 2040, there will not be enough power generated on Earth to run all the computers (of present type) we will need. • What can we do about that? – Generate more power? – Compute less? – Compute BETTER! THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Computer Size and Speed • Ultimately, computing is performed by physical systems • We always want smaller, faster and more capable computers • We are packaging more and more physical objects into less and less space • How far can this go? THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Classical vs. Quantum Physics • Classical physics deals with objects on a macroscopic scale • Compute with large objects, like gears or transistors: classical physics works • Quantum mechanics deals with objects on an atomic/subatomic scale • Compute with tiny objects, like individual photons or electrons, quantum mechanics is needed to explain their behavior. THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Problem “Nobody understands quantum mechanics” Richard Feynman (1918-1988) Nobel Prize 1965 THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Abacus • Has physical beads THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Adding Machine • Has gears THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS First Transistor (1947) Bardeen, Brattain, Shockley Nobel Prize 1956 THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Mainframe Computer • Has transistors, circuits, boards, cables IBM Z14 8 TB RAM 850 MILLION ENCRYPTED TRANSACTIONS PER DAY 14 nanometer technology (Gordon) Moore’s Law • Transistor density doubles every two years Personal Computer • Apple A12X (for 2018 iPad Pro) has 10 BILLION transistors End of Moore’s Law? • The features on the Apple A12X are only 7 nanometers wide, allowing 80 million transistors per square mm 7 nm Problem: A silicon atom is 0.2 nm wide. If transistors are made much smaller, quantum effects will dominate. Here are 7 nm worth (35) of silicon atoms: ................................... Possible Future of Moore’s Law atom-sized transistors molecular-sized transistors 2025 2040 SOURCE: CHRIS MONROE Quantum Mechanics • Quantum mechanics seems weird, but so are magnetism and gravity – it’s just less familiar • We experience magnetism and gravity in everyday life – we don’t experience quantum mechanics, so it seems very odd THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Classical Physics • Why do masses attract each other? • Newton did not answer that question • His “Law of Gravitation” allowed computation of the attractive force (proportional to the product of the masses, inverse to the square of the distance) • It did not explain WHY masses attract THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Einstein’s Gravity • Masses (and energy) cause spacetime to curve • Gravity is a consequence of this curvature • General relativity does not explain WHY spacetime is curved • It’s not supposed to. It allows calculation of paths of motion that correspond to experiment THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS The Double Slit Experiment Thomas Young (1801) EXPECTED PATTERN The Double Slit Experiment Thomas Young (1801) ACTUAL PATTERN Photoelectric Effect • If you shine light on a metal, electrons are ejected • Light energy is given to the electrons, which escape from atoms in the metal • Expectation: more intense light, more energy, more electrons • Reality: ejection depends on the frequency of the light, not its intensity Einstein’s Explanation (1905) • Light comes in discrete quantized packets (photons) • Whether an electron is ejected depends on the energy of the photons (frequency of light), not the number of photons (intensity of light) Yellow light, no electrons Purple light – electrons! • So light behaves like both a wave and a particle SOURCE: GERMAIN SALVATO-VALLVERDU Explanation by Bohr & Heisenberg (1925) • Particles are spread throughout space, like waves • A particle can be observed anywhere, with a non- zero probability The Mach-Zehnder Interferometer Invented in 1892! Before photons No were known! Photons! Photons Photons! Beamsplitter Photons 2 Photons Photons Photons 1 The Mach-Zehnder Interferometer 25% 25% Barrier Quantization • Many physical quantities come in discrete packages and do not vary continuously • Example: light energy (intensity) exists as individual photons • Electrical charge comes in discrete units. No elementary particle has smaller charge than an electron • Problem: discrete packages, like photons and electrons, don’t always behave like particles confined to a given space THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Quantization Example: A Coin • A coin can be in one of two “states” Observing • HEADS (1) (measuring) the state Is easy. Just look. • TAILS (0) But what is looking? THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Coins As Bits • A sequence of coins can represent a bit string: T H T T H H T H = 0 1 0 0 1 1 0 1 = 7710 THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS What is the “State” of this Coin? In quantum mechanics, the coin is in a “superposition” of states 1 and 0. It’s BOTH heads and tails until it falls over and is observed in one state or the other. THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS A Qubit (Quantum Bit) Is A Quantum-Mechanical “Coin” • An electron can have spin up or spin down • Let spin up represent 1, spin down 0 • The electron is in a superposition of both states until measured Another Qubit • A photon can have one of two polarizations • Let vertical polarization represent 1, horizontal polarization 0 • The photon is in a superposition of both states until measured Yet Another Qubit • An atom can be in two different states, depending on electron energy levels • Let the excited state represent 1, the ground state 0 • The atom is in a superposition of both states until measured Three Actual Qubits • Three beryllium atoms held in place by an “atom trap’ using electrical and magnetic fields • Holds 23 = 8 different values simultaneously • Three classical bits would hold 1 of 8 values Measuring a Single Atom ground state ↓ excited state ↑ laser laser atom emits 108 photons/sec atom remains dark 0.2 1 Probability 0 0 0 10 20 30 0 10 20 30 # photons collected in 200µs # photons collected in 200µs THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Bits vs. Qubits • n classical bits can represent ONE out of 2 n values – 8 bits (1 byte): one of 256 values (0 to 255) – 32 bits (4 bytes): one of 4,294,967,296 values – 8192 bits (1 KB): one of 2 8192 ≈ 10 2466 values • n qubits can represent ALL 2 n values SIMULTANEOUSLY • Operating on n qubits can (in principle) perform 2 n calculations at the same time • 300 qubits can represent more values than there are atoms in the universe THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS “Moore’s Law” of Qubits • The size (in qubits) of quantum computers doubles every year • Large numbers of qubits are needed because of errors in quantum computation THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Entanglement • Sometimes it is impossible to describe the states of two particles separately • We can only describe the state of the combined set of particles – they act as a single quantum system • The particles are “entangled” with each other THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Entangled Coins • Create two coins simultaneously that are of opposite spin but in linked superposition: THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Entangled Coins • Separate the coins THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Entangled Coins • Measure (observe) one coin (heads) THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Entangled Coins • The other coin immediately falls tails, no matter how far apart they are • Measure (observe) one coin (heads) THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Entangled Qubits • To represent all 2N values in a single register that can be operated on as a unit, the qubits must all be entangled • Without entanglement, a quantum computer would be a “very expensive classical computer” • Each qubit would be operated on separately, instead of all together THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I. SHAMOS Gates • Analogous to logic gates in classical computers, such as an AND gate: x xy∧ y • Classical gates operate on bits and are implemented as circuits: x y xy∧ Quantum “Gates” • Quantum “gates” operate on qubits, i.e., they operate on all the states of entangled qubits at the same time • Quantum “gates” are NOT CIRCUITS. They are physical processes (protocols) for operating on qubits, e.g., by shining lasers on them • Example: a Hadamard gate is equivalent to spinning a coin – it creates a mixture of two states with equal probability THE UNIVERSITY OF HONG KONG FEBRUARY 27, 2019 © 2019 MICHAEL I.

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