Hi Jochen, There are currently two main approaches to quantum computing. The first is called adiabatic quantum computing (AQC). Complexity enthusiasts that have followed the spin glass literature will be familiar with Ising spin systems. AQC exploits the tendency of physical systems to go to low energy. It turns out that many kinds of operations can be implemented even with two body interactions. For example logic programs map to Ising systems. In fact a former colleague of mine, Scott Pakin has implemented a Prolog interpreter for a quantum annealer. The reason to use a quantum annealer over a classical thermal annealer is essentially speed. An anneal can be repeated every tens of microseconds. For sampling applications, like finding all the ways to solve an NP-hard constrained optimization problem with discrete variables, this is potentially a big win. Classical mixed-integer programming approaches can be fast to find local/global optima, but may give a fragile picture of the fitness landscape. It is possible to use annealers to mimic materials, and study phenomenon like quantum phase transitions. Quantum tunneling and entanglement have been demonstrated using commercially-available quantum annealers.
The other approach to quantum computing is the gate model. Here the idea is to compose together unitary operators. This model is less surprising from a from a (functional) programming perspective: There are gates that feed into other gates kind of like classical circuits. This is a what IBM (and others) are trying to do, and the difficulty of the task is reflected by the fact they only have a handful of qubits. Estimates vary, but to implement the error correction that would give reliability on-par with classical digital computers could take 1000-fold or even more redundancy. That’s to get _one_ good qubit at > 99.9% reliability. AQC doesn’t require the long coherence times (especially resistance to dephasing) that the gate model requires. Recently there’s been a middle ground declared called NISQ which is trying to find algorithms (like annealing) that work on imperfect gate-model qubits. There are two popular foundational technologies for qubits, superconductors and ion traps. The tradeoff is essentially between latency and stability. Ion traps can maintain coherence a long time, but are relatively expensive to configure. The system you mention from IBM is a the former. Superconductors typically operate near absolute zero (tens of mK) with many layers of protection from electromagnetic radiation and the Ion traps use elaborate laser control systems. Quantum computing is not BS, but it is very hard to engineer these systems and there is a long road ahead to bring this technology to practitioners. The CMOS-based computing systems we all use are a miraculous accomplishments of humans, and are easy to take for granted. One of the national labs here in New Mexico actually owns an AQC system. Marcus From: Friam <[email protected]> on behalf of Jochen Fromm <[email protected]> Reply-To: The Friday Morning Applied Complexity Coffee Group <[email protected]> Date: Saturday, January 26, 2019 at 3:23 PM To: The Friday Morning Applied Complexity Coffee Group <[email protected]> Subject: [FRIAM] Quantum Computing What do you think of Quantum Computing, will it be successful? IBM just built the IBM Q System One... https://youtu.be/LAA0-vjTaNY ...while others make a strong case against it.. https://spectrum.ieee.org/computing/hardware/the-case-against-quantum-computing ..or even call it bullshit https://scottlocklin.wordpress.com/2019/01/15/quantum-computing-as-a-field-is-obvious-bullshit/ What's your opinion? -Jochen
============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com archives back to 2003: http://friam.471366.n2.nabble.com/ FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
