Wikipedia

Quantum simulator

(Redirected from Trapped-ion simulator)

Quantum simulators permit the study of a quantum system in a programmable fashion. In this instance, simulators are special purpose devices designed to provide insight about specific physics problems.[1][2][3] Quantum simulators may be contrasted with generally programmable "digital" quantum computers, which would be capable of solving a wider class of quantum problems.

In this photograph of a quantum simulator crystal the ions are fluorescing, indicating the qubits are all in the same state (either "1" or "0"). Under the right experimental conditions, the ion crystal spontaneously forms this nearly perfect triangular lattice structure. Credit: Britton/NIST
Trapped ion quantum simulator illustration: The heart of the simulator is a two-dimensional crystal of beryllium ions (blue spheres in the graphic); the outermost electron of each ion is a quantum bit (qubit, red arrows). The ions are confined by a large magnetic field in a device called a Penning trap (not shown). Inside the trap the crystal rotates clockwise. Credit: Britton/NIST

A universal quantum simulator is a quantum computer proposed by Yuri Manin in 1980[4] and Richard Feynman in 1982.[5]

A quantum system may be simulated by either a Turing machine or a quantum Turing machine, as a classical Turing machine is able to simulate a universal quantum computer (and therefore any simpler quantum simulator), meaning they are equivalent from the point of view of computability theory. The simulation of quantum physics by a classical computer has been shown to be inefficient.[6] In other words, quantum computers provide no additional power over classical computers in terms of computability, but it is suspected that they can solve certain problems faster than classical computers, meaning they may be in different complexity classes, which is why quantum Turing machines are useful for simulating quantum systems. This is known as quantum supremacy, the idea that there are problems only quantum Turing machines can solve in any feasible amount of time.

A quantum system of many particles could be simulated by a quantum computer using a number of quantum bits similar to the number of particles in the original system.[5] This has been extended to much larger classes of quantum systems.[7][8][9][10]

Quantum simulators have been realized on a number of experimental platforms, including systems of ultracold quantum gases, polar molecules, trapped ions, photonic systems, quantum dots, and superconducting circuits.[11]

Solving physics problems

edit

Many important problems in physics, especially low-temperature physics and many-body physics, remain poorly understood because the underlying quantum mechanics is vastly complex. Conventional computers, including supercomputers, are inadequate for simulating quantum systems with as few as 30 particles because the dimension of the Hilbert space grows exponentially with particle number.[12] Better computational tools are needed to understand and rationally design materials whose properties are believed to depend on the collective quantum behavior of hundreds of particles.[2][3] Quantum simulators provide an alternative route to understanding the properties of these systems. These simulators create clean realizations of specific systems of interest, which allows precise realizations of their properties. Precise control over and broad tunability of parameters of the system allows the influence of various parameters to be cleanly disentangled.

Quantum simulators can solve problems which are difficult to simulate on classical computers because they directly exploit quantum properties of real particles. In particular, they exploit a property of quantum mechanics called superposition, wherein a quantum particle is made to be in two distinct states at the same time, for example, aligned and anti-aligned with an external magnetic field. Crucially, simulators also take advantage of a second quantum property called entanglement, allowing the behavior of even physically well separated particles to be correlated.[2][3][13]

Recently quantum simulators have been used to obtain time crystals[14][15] and quantum spin liquids.[16][17]

Trapped-ion simulators

edit

Ion trap based system forms an ideal setting for simulating interactions in quantum spin models.[18] A trapped-ion simulator, built by a team that included the NIST can engineer and control interactions among hundreds of quantum bits (qubits).[19] Previous endeavors were unable to go beyond 30 quantum bits. The capability of this simulator is 10 times more than previous devices. It has passed a series of important benchmarking tests that indicate a capability to solve problems in material science that are impossible to model on conventional computers.

The trapped-ion simulator consists of a tiny, single-plane crystal of hundreds of beryllium ions, less than 1 millimeter in diameter, hovering inside a device called a Penning trap. The outermost electron of each ion acts as a tiny quantum magnet and is used as a qubit, the quantum equivalent of a “1” or a “0” in a conventional computer. In the benchmarking experiment, physicists used laser beams to cool the ions to near absolute zero. Carefully timed microwave and laser pulses then caused the qubits to interact, mimicking the quantum behavior of materials otherwise very difficult to study in the laboratory. Although the two systems may outwardly appear dissimilar, their behavior is engineered to be mathematically identical. In this way, simulators allow researchers to vary parameters that could not be changed in natural solids, such as atomic lattice spacing and geometry.

Friedenauer et al., adiabatically manipulated 2 spins, showing their separation into ferromagnetic and antiferromagnetic states.[20] Kim et al., extended the trapped ion quantum simulator to 3 spins, with global antiferromagnetic Ising interactions featuring frustration and showing the link between frustration and entanglement[21] and Islam et al., used adiabatic quantum simulation to demonstrate the sharpening of a phase transition between paramagnetic and ferromagnetic ordering as the number of spins increased from 2 to 9.[22] Barreiro et al. created a digital quantum simulator of interacting spins with up to 5 trapped ions by coupling to an open reservoir[23] and Lanyon et al. demonstrated digital quantum simulation with up to 6 ions.[24] Islam, et al., demonstrated adiabatic quantum simulation of the transverse Ising model with variable (long) range interactions with up to 18 trapped ion spins, showing control of the level of spin frustration by adjusting the antiferromagnetic interaction range.[25] Britton, et al. from NIST has experimentally benchmarked Ising interactions in a system of hundreds of qubits for studies of quantum magnetism.[19] Pagano, et al., reported a new cryogenic ion trapping system designed for long time storage of large ion chains demonstrating coherent one and two-qubit operations for chains of up to 44 ions.[26] Joshi, et al., probed the quantum dynamics of 51 individually controlled ions, realizing a long-range interacting spin chain.[27]

Ultracold atom simulators

edit

Many ultracold atom experiments are examples of quantum simulators. These include experiments studying bosons or fermions in optical lattices, the unitary Fermi gas, Rydberg atom arrays in optical tweezers. A common thread for these experiments is the capability of realizing generic Hamiltonians, such as the Hubbard or transverse-field Ising Hamiltonian. Major aims of these experiments include identifying low-temperature phases or tracking out-of-equilibrium dynamics for various models, problems which are theoretically and numerically intractable.[28][29] Other experiments have realized condensed matter models in regimes which are difficult or impossible to realize with conventional materials, such as the Haldane model and the Harper-Hofstadter model.[30][31][32][33][34]

Superconducting qubits

edit

Quantum simulators using superconducting qubits fall into two main categories. First, so called quantum annealers determine ground states of certain Hamiltonians after an adiabatic ramp. This approach is sometimes called adiabatic quantum computing. Second, many systems emulate specific Hamiltonians and study their ground state properties, quantum phase transitions, or time dynamics.[35] Several important recent results include the realization of a Mott insulator in a driven-dissipative Bose-Hubbard system and studies of phase transitions in lattices of superconducting resonators coupled to qubits.[36][37]

See also

edit

References

edit
  1. ^ Johnson, Tomi H.; Clark, Stephen R.; Jaksch, Dieter (2014). "What is a quantum simulator?". EPJ Quantum Technology. 1 (10). arXiv:1405.2831. doi:10.1140/epjqt10. S2CID 120250321.
  2. ^ a b c   This article incorporates public domain material from Michael E. Newman. NIST Physicists Benchmark Quantum Simulator with Hundreds of Qubits. National Institute of Standards and Technology. Retrieved 2013-02-22.
  3. ^ a b c Britton, Joseph W.; Sawyer, Brian C.; Keith, Adam C.; Wang, C.-C. Joseph; Freericks, James K.; Uys, Hermann; Biercuk, Michael J.; Bollinger, John J. (2012). "Engineered two-dimensional Ising interactions in a trapped-ion quantum simulator with hundreds of spins" (PDF). Nature. 484 (7395): 489–92. arXiv:1204.5789. Bibcode:2012Natur.484..489B. doi:10.1038/nature10981. PMID 22538611. S2CID 4370334. Note: This manuscript is a contribution of the US National Institute of Standards and Technology and is not subject to US copyright.
  4. ^ Manin, Yu. I. (1980). Vychislimoe i nevychislimoe [Computable and Noncomputable] (in Russian). Sov.Radio. pp. 13–15. Archived from the original on 2013-05-10. Retrieved 2013-03-04.
  5. ^ a b Feynman, Richard (1982). "Simulating Physics with Computers". International Journal of Theoretical Physics. 21 (6–7): 467–488. Bibcode:1982IJTP...21..467F. CiteSeerX 10.1.1.45.9310. doi:10.1007/BF02650179. S2CID 124545445.
  6. ^ Feynman, Richard P. (1982-06-01). "Simulating physics with computers". International Journal of Theoretical Physics. 21 (6): 467–488. Bibcode:1982IJTP...21..467F. doi:10.1007/BF02650179. ISSN 1572-9575. S2CID 124545445.
  7. ^ Dorit Aharonov; Amnon Ta-Shma (2003). "Adiabatic Quantum State Generation and Statistical Zero Knowledge". arXiv:quant-ph/0301023.
  8. ^ Berry, Dominic W.; Graeme Ahokas; Richard Cleve; Sanders, Barry C. (2007). "Efficient quantum algorithms for simulating sparse Hamiltonians". Communications in Mathematical Physics. 270 (2): 359–371. arXiv:quant-ph/0508139. Bibcode:2007CMaPh.270..359B. doi:10.1007/s00220-006-0150-x. S2CID 37923044.
  9. ^ Childs, Andrew M. (2010). "On the relationship between continuous- and discrete-time quantum walk". Communications in Mathematical Physics. 294 (2): 581–603. arXiv:0810.0312. Bibcode:2010CMaPh.294..581C. doi:10.1007/s00220-009-0930-1. S2CID 14801066.
  10. ^ Kliesch, M.; Barthel, T.; Gogolin, C.; Kastoryano, M.; Eisert, J. (12 September 2011). "Dissipative Quantum Church-Turing Theorem". Physical Review Letters. 107 (12): 120501. arXiv:1105.3986. Bibcode:2011PhRvL.107l0501K. doi:10.1103/PhysRevLett.107.120501. PMID 22026760. S2CID 11322270.
  11. ^ Nature Physics Insight – Quantum Simulation. Nature.com. April 2012.
  12. ^ Lloyd, S. (1996). "Universal quantum simulators". Science. 273 (5278): 1073–8. Bibcode:1996Sci...273.1073L. doi:10.1126/science.273.5278.1073. PMID 8688088. S2CID 43496899.
  13. ^ Cirac, J. Ignacio; Zoller, Peter (2012). "Goals and opportunities in quantum simulation" (PDF). Nature Physics. 8 (4): 264–266. Bibcode:2012NatPh...8..264C. doi:10.1038/nphys2275. S2CID 109930964.[permanent dead link‍]
  14. ^ Kyprianidis, A.; Machado, F.; Morong, W.; Becker, P.; Collins, K. S.; Else, D. V.; Feng, L.; Hess, P. W.; Nayak, C.; Pagano, G.; Yao, N. Y. (2021-06-11). "Observation of a prethermal discrete time crystal". Science. 372 (6547): 1192–1196. arXiv:2102.01695. Bibcode:2021Sci...372.1192K. doi:10.1126/science.abg8102. ISSN 0036-8075. PMID 34112691. S2CID 231786633.
  15. ^ S, Robert; ers; Berkeley, U. C. (2021-11-10). "Creating Time Crystals Using New Quantum Computing Architectures". SciTechDaily. Retrieved 2021-12-27.
  16. ^ Semeghini, G.; Levine, H.; Keesling, A.; Ebadi, S.; Wang, T. T.; Bluvstein, D.; Verresen, R.; Pichler, H.; Kalinowski, M.; Samajdar, R.; Omran, A. (2021-12-03). "Probing topological spin liquids on a programmable quantum simulator". Science. 374 (6572): 1242–1247. arXiv:2104.04119. Bibcode:2021Sci...374.1242S. doi:10.1126/science.abi8794. PMID 34855494. S2CID 233204440.
  17. ^ Wood, Charlie (2021-12-02). "Quantum Simulators Create a Totally New Phase of Matter". Quanta Magazine. Retrieved 2022-03-11.
  18. ^ Monroe, C; et, al (2021). "Programmable quantum simulations of spin systems with trapped ions". Rev. Mod. Phys. 93 (4): 025001. arXiv:1912.07845. Bibcode:2021RvMP...93b5001M. doi:10.1103/RevModPhys.93.025001. ISSN 0034-6861. S2CID 209386771.
  19. ^ a b Britton, Joseph W.; Sawyer, Brian C.; Keith, Adam C.; Wang, C.-C. Joseph; Freericks, James K.; Uys, Hermann; Biercuk, Michael J.; Bollinger, John J. (25 April 2012). "Engineered two-dimensional Ising interactions in a trapped-ion quantum simulator with hundreds of spins". Nature. 484 (7395): 489–492. arXiv:1204.5789. Bibcode:2012Natur.484..489B. doi:10.1038/nature10981. PMID 22538611. S2CID 4370334.
  20. ^ Friedenauer, A.; Schmitz, H.; Glueckert, J. T.; Porras, D.; Schaetz, T. (27 July 2008). "Simulating a quantum magnet with trapped ions". Nature Physics. 4 (10): 757–761. Bibcode:2008NatPh...4..757F. doi:10.1038/nphys1032.
  21. ^ Kim, K.; Chang, M.-S.; Korenblit, S.; Islam, R.; Edwards, E. E.; Freericks, J. K.; Lin, G.-D.; Duan, L.-M.; Monroe, C. (June 2010). "Quantum simulation of frustrated Ising spins with trapped ions". Nature. 465 (7298): 590–593. Bibcode:2010Natur.465..590K. doi:10.1038/nature09071. PMID 20520708. S2CID 2479652.
  22. ^ Islam, R.; Edwards, E.E.; Kim, K.; Korenblit, S.; Noh, C.; Carmichael, H.; Lin, G.-D.; Duan, L.-M.; Joseph Wang, C.-C.; Freericks, J.K.; Monroe, C. (5 July 2011). "Onset of a quantum phase transition with a trapped ion quantum simulator". Nature Communications. 2 (1): 377. arXiv:1103.2400. Bibcode:2011NatCo...2..377I. doi:10.1038/ncomms1374. PMID 21730958. S2CID 33407.
  23. ^ Barreiro, Julio T.; Müller, Markus; Schindler, Philipp; Nigg, Daniel; Monz, Thomas; Chwalla, Michael; Hennrich, Markus; Roos, Christian F.; Zoller, Peter; Blatt, Rainer (23 February 2011). "An open-system quantum simulator with trapped ions". Nature. 470 (7335): 486–491. arXiv:1104.1146. Bibcode:2011Natur.470..486B. doi:10.1038/nature09801. PMID 21350481. S2CID 4359894.
  24. ^ Lanyon, B. P.; Hempel, C.; Nigg, D.; Muller, M.; Gerritsma, R.; Zahringer, F.; Schindler, P.; Barreiro, J. T.; Rambach, M.; Kirchmair, G.; Hennrich, M.; Zoller, P.; Blatt, R.; Roos, C. F. (1 September 2011). "Universal Digital Quantum Simulation with Trapped Ions". Science. 334 (6052): 57–61. arXiv:1109.1512. Bibcode:2011Sci...334...57L. doi:10.1126/science.1208001. PMID 21885735. S2CID 206535076.
  25. ^ Islam, R.; Senko, C.; Campbell, W. C.; Korenblit, S.; Smith, J.; Lee, A.; Edwards, E. E.; Wang, C.- C. J.; Freericks, J. K.; Monroe, C. (2 May 2013). "Emergence and Frustration of Magnetism with Variable-Range Interactions in a Quantum Simulator". Science. 340 (6132): 583–587. arXiv:1210.0142. Bibcode:2013Sci...340..583I. doi:10.1126/science.1232296. PMID 23641112. S2CID 14692151.
  26. ^ Pagano, G; Hess, P W; Kaplan, H B; Tan, W L; Richerme, P; Becker, P; Kyprianidis, A; Zhang, J; Birckelbaw, E; Hernandez, M R; Wu, Y; Monroe, C (9 October 2018). "Cryogenic trapped-ion system for large scale quantum simulation". Quantum Science and Technology. 4 (1): 014004. arXiv:1802.03118. doi:10.1088/2058-9565/aae0fe. S2CID 54518534.
  27. ^ Joshi, M.K.; Kranzl, F.; Schuckert, A.; Lovas, I.; Maier, C.; Blatt, R.; Knap, M.; Roos, C.F. (13 May 2022). "Observing emergent hydrodynamics in a long-range quantum magnet". Science. 6594 (376): 720–724. arXiv:2107.00033. Bibcode:2022Sci...376..720J. doi:10.1126/science.abk2400. PMID 35549407. S2CID 235694285. Retrieved 13 May 2022.
  28. ^ Bloch, Immanuel; Dalibard, Jean; Nascimbene, Sylvain (2012). "Quantum simulations with ultracold quantum gases". Nature Physics. 8 (4): 267–276. Bibcode:2012NatPh...8..267B. doi:10.1038/nphys2259. S2CID 17023076.
  29. ^ Gross, Christian; Bloch, Immanuel (September 8, 2017). "Quantum simulations with ultracold atoms in optical lattices". Nature. 357 (6355): 995–1001. Bibcode:2017Sci...357..995G. doi:10.1126/science.aal3837. PMID 28883070.
  30. ^ Jotzu, Gregor; Messer, Michael; Desbuquois, Rémi; Lebrat, Martin; Uehlinger, Thomas; Greif, Daniel; Esslinger, Tilman (13 November 2014). "Experimental realization of the topological Haldane model with ultracold fermions". Nature. 515 (7526): 237–240. arXiv:1406.7874. Bibcode:2014Natur.515..237J. doi:10.1038/nature13915. PMID 25391960. S2CID 204898338.
  31. ^ Simon, Jonathan (13 November 2014). "Magnetic fields without magnetic fields". Nature. 515 (7526): 202–203. doi:10.1038/515202a. PMID 25391956.
  32. ^ Zhang, Dan-Wei; Zhu, Yan-Qing; Zhao, Y. X.; Yan, Hui; Zhu, Shi-Liang (29 March 2019). "Topological quantum matter with cold atoms". Advances in Physics. 67 (4): 253–402. arXiv:1810.09228. doi:10.1080/00018732.2019.1594094. S2CID 91184189.
  33. ^ Alberti, Andrea; Robens, Carsten; Alt, Wolfgang; Brakhane, Stefan; Karski, Michał; Reimann, René; Widera, Artur; Meschede, Dieter (2016-05-06). "Super-resolution microscopy of single atoms in optical lattices". New Journal of Physics. 18 (5): 053010. arXiv:1512.07329. Bibcode:2016NJPh...18e3010A. doi:10.1088/1367-2630/18/5/053010. ISSN 1367-2630.
  34. ^ Robens, Carsten; Brakhane, Stefan; Meschede, Dieter; Alberti, A. (2016-09-18), "Quantum Walks with Neutral Atoms: Quantum Interference Effects of One and Two Particles", Laser Spectroscopy, WORLD SCIENTIFIC, pp. 1–15, arXiv:1511.03569, doi:10.1142/9789813200616_0001, ISBN 978-981-320-060-9, S2CID 118452312, retrieved 2020-05-25
  35. ^ Paraoanu, G. S. (4 April 2014). "Recent Progress in Quantum Simulation Using Superconducting Circuits". Journal of Low Temperature Physics. 175 (5–6): 633–654. arXiv:1402.1388. Bibcode:2014JLTP..175..633P. doi:10.1007/s10909-014-1175-8. S2CID 119276238.
  36. ^ Ma, Ruichao; Saxberg, Brendan; Owens, Clai; Leung, Nelson; Lu, Yao; Simon, Jonathan; Schuster, David I. (6 February 2019). "A dissipatively stabilized Mott insulator of photons". Nature. 566 (7742): 51–57. arXiv:1807.11342. Bibcode:2019Natur.566...51M. doi:10.1038/s41586-019-0897-9. PMID 30728523. S2CID 59606678.
  37. ^ Fitzpatrick, Mattias; Sundaresan, Neereja M.; Li, Andy C. Y.; Koch, Jens; Houck, Andrew A. (10 February 2017). "Observation of a Dissipative Phase Transition in a One-Dimensional Circuit QED Lattice". Physical Review X. 7 (1): 011016. arXiv:1607.06895. Bibcode:2017PhRvX...7a1016F. doi:10.1103/PhysRevX.7.011016. S2CID 3550701.
edit
Retrieved from "https://en.wikipedia.org/w/index.php?title=Quantum_simulator&oldid=1258951950#Trapped-ion_simulators"