Coherent imaging spectroscopy of a quantum many-body spin system

Characterization of a quantum simulator Ultracold gases can be used to simulate the behavior of more complicated systems, such as solid materials. Senko et al. developed a method similar to nuclear magnetic resonance that can be used to validate the properties of such simulators. They demonstrated the method on an array of interacting trapped ions that simulate magnetism. A modulated magnetic field resonantly enhanced the transfer of the population between the different configurations of the system. The authors varied the modulation frequency to measure the energy of each configuration and mapped the effective interactions. Science, this issue p. 430 A method for validating quantum simulations is based on interrogating the system with a modulated magnetic field. Quantum simulators, in which well-controlled quantum systems are used to reproduce the dynamics of less understood ones, have the potential to explore physics inaccessible to modeling with classical computers. However, checking the results of such simulations also becomes classically intractable as system sizes increase. Here, we introduce and implement a coherent imaging spectroscopic technique, akin to magnetic resonance imaging, to validate a quantum simulation. We use this method to determine the energy levels and interaction strengths of a fully connected quantum many-body system. Additionally, we directly measure the critical energy gap near a quantum phase transition. We expect this general technique to become a verification tool for quantum simulators once experiments advance beyond proof-of-principle demonstrations and exceed the resources of conventional computers.

[1]  J. K. Freericks,et al.  Quantum simulation and phase diagram of the transverse-field Ising model with three atomic spins , 2010, 1005.4160.

[2]  M. Kastner,et al.  Relaxation timescales and decay of correlations in a long-range interacting quantum simulator , 2012, 1209.3697.

[3]  M. Chang,et al.  Entanglement and tunable spin-spin couplings between trapped ions using multiple transverse modes. , 2009, Physical review letters.

[4]  Alán Aspuru-Guzik,et al.  Photonic quantum simulators , 2012, Nature Physics.

[5]  L. Duan,et al.  Prethermalization and dynamic phase transition in an isolated trapped ion spin chain , 2013, 1305.0985.

[6]  P. Hauke,et al.  Spread of correlations in long-range interacting quantum systems. , 2013, Physical review letters.

[7]  G. Goldhaber On communication. , 1979, Hospital supervisor's bulletin.

[8]  H. Diep Frustrated Spin Systems , 2020 .

[9]  M. Johanning,et al.  Designer spin pseudomolecule implemented with trapped ions in a magnetic gradient. , 2011, Physical review letters.

[10]  Lu-Ming Duan,et al.  Quantum simulation of frustrated Ising spins with trapped ions , 2010, Nature.

[11]  F. Fressin,et al.  Emergence and Frustration of Magnetism with Variable-Range Interactions in a Quantum Simulator , 2012, Science.

[12]  Michael J. Berry,et al.  Weak pairwise correlations imply strongly correlated network states in a neural population , 2005, Nature.

[13]  B. Cipra The Ising Model Is NP-Complete , 2000 .

[14]  R. Blatt,et al.  Quantum simulations with trapped ions , 2011, Nature Physics.

[15]  M. Lukin,et al.  Probing real-space and time-resolved correlation functions with many-body Ramsey interferometry. , 2013, Physical review letters.

[16]  D. James Quantum dynamics of cold trapped ions with application to quantum computation , 1997, quant-ph/9702053.

[17]  Klaus Molmer,et al.  Entanglement and quantum computation with ions in thermal motion , 2000 .

[18]  L.-M. Duan,et al.  Correcting detection errors in quantum state engineering through data processing , 2012, 1201.4379.

[19]  M. Lewenstein,et al.  Can one trust quantum simulators? , 2011, Reports on progress in physics. Physical Society.

[20]  C. F. Roos,et al.  Entanglement growth in quench dynamics with variable range interactions , 2013, 1305.6880.

[21]  Géza Tóth,et al.  Optimal spin squeezing inequalities detect bound entanglement in spin models. , 2007, Physical review letters.

[22]  B. Lanyon,et al.  Quasiparticle engineering and entanglement propagation in a quantum many-body system , 2014, Nature.

[23]  S. Olmschenk,et al.  Manipulation and detection of a trapped Yb+ hyperfine qubit , 2007, 0708.0657.

[24]  F. Nori,et al.  Quantum Simulation , 2013, Quantum Atom Optics.

[25]  Aaron C. E. Lee,et al.  Experimental Performance of a Quantum Simulator: Optimizing Adiabatic Evolution and Identifying Many-Body Ground States , 2013, 1305.2253.

[26]  J. Cirac,et al.  Goals and opportunities in quantum simulation , 2012, Nature Physics.

[27]  C. Monroe,et al.  Onset of a quantum phase transition with a trapped ion quantum simulator. , 2011, Nature communications.

[28]  J. Freericks,et al.  Diabatic ramping spectroscopy of many-body excited states for trapped-ion quantum simulators , 2014, 1402.7357.

[29]  Michael J. Biercuk,et al.  Engineered two-dimensional Ising interactions in a trapped-ion quantum simulator with hundreds of spins , 2012, Nature.

[30]  R. Feynman Simulating physics with computers , 1999 .

[31]  S. Sachdev Quantum Phase Transitions , 1999 .

[32]  J. Cirac,et al.  Effective quantum spin systems with trapped ions. , 2004, Physical Review Letters.

[33]  L.-M. Duan,et al.  Correcting detection error in quantum computation and state engineering through data processing , 2012 .

[34]  J. Dalibard,et al.  Quantum simulations with ultracold quantum gases , 2012, Nature Physics.

[35]  Seth Lloyd,et al.  Universal Quantum Simulators , 1996, Science.

[36]  G. Bodenhausen,et al.  Principles of nuclear magnetic resonance in one and two dimensions , 1987 .