Lev Ioffe

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    Dynamics of magnetization at infinite temperature in a Heisenberg spin chain
    Trond Andersen
    Rhine Samajdar
    Andre Petukhov
    Jesse Hoke
    Dmitry Abanin
    ILYA Drozdov
    Xiao Mi
    Alexis Morvan
    Charles Neill
    Rajeev Acharya
    Richard Ross Allen
    Kyle Anderson
    Markus Ansmann
    Frank Arute
    Kunal Arya
    Juan Atalaya
    Gina Bortoli
    Alexandre Bourassa
    Leon Brill
    Michael Broughton
    Bob Buckley
    Tim Burger
    Nicholas Bushnell
    Juan Campero
    Hung-Shen Chang
    Jimmy Chen
    Benjamin Chiaro
    Desmond Chik
    Josh Cogan
    Roberto Collins
    Paul Conner
    William Courtney
    Alex Crook
    Ben Curtin
    Agustin Di Paolo
    Andrew Dunsworth
    Clint Earle
    Lara Faoro
    Edward Farhi
    Reza Fatemi
    Vinicius Ferreira
    Ebrahim Forati
    Brooks Foxen
    Gonzalo Garcia
    Élie Genois
    William Giang
    Dar Gilboa
    Raja Gosula
    Alejo Grajales Dau
    Steve Habegger
    Michael Hamilton
    Monica Hansen
    Sean Harrington
    Paula Heu
    Gordon Hill
    Markus Hoffmann
    Trent Huang
    Ashley Huff
    Bill Huggins
    Sergei Isakov
    Justin Iveland
    Cody Jones
    Pavol Juhas
    Marika Kieferova
    Alexei Kitaev
    Andrey Klots
    Alexander Korotkov
    Fedor Kostritsa
    John Mark Kreikebaum
    Dave Landhuis
    Pavel Laptev
    Kim Ming Lau
    Lily Laws
    Joonho Lee
    Kenny Lee
    Yuri Lensky
    Alexander Lill
    Wayne Liu
    Salvatore Mandra
    Orion Martin
    Steven Martin
    Seneca Meeks
    Amanda Mieszala
    Shirin Montazeri
    Ramis Movassagh
    Wojtek Mruczkiewicz
    Ani Nersisyan
    Michael Newman
    JiunHow Ng
    Murray Ich Nguyen
    Tom O'Brien
    Seun Omonije
    Alex Opremcak
    Rebecca Potter
    Leonid Pryadko
    David Rhodes
    Charles Rocque
    Negar Saei
    Kannan Sankaragomathi
    Henry Schurkus
    Christopher Schuster
    Mike Shearn
    Aaron Shorter
    Noah Shutty
    Vladimir Shvarts
    Vlad Sivak
    Jindra Skruzny
    Clarke Smith
    Rolando Somma
    George Sterling
    Doug Strain
    Marco Szalay
    Doug Thor
    Alfredo Torres
    Guifre Vidal
    Cheng Xing
    Jamie Yao
    Ping Yeh
    Juhwan Yoo
    Grayson Young
    Yaxing Zhang
    Ningfeng Zhu
    Jeremy Hilton
    Anthony Megrant
    Yu Chen
    Vadim Smelyanskiy
    Vedika Khemani
    Sarang Gopalakrishnan
    Tomaž Prosen
    Science, 384 (2024), pp. 48-53
    Preview abstract Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain’s center, P(M). The first two moments of P(M) show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems. View details
    Stable quantum-correlated many-body states through engineered dissipation
    Xiao Mi
    Alexios Michailidis
    Sara Shabani
    Jerome Lloyd
    Rajeev Acharya
    Igor Aleiner
    Trond Andersen
    Markus Ansmann
    Frank Arute
    Kunal Arya
    Juan Atalaya
    Gina Bortoli
    Alexandre Bourassa
    Leon Brill
    Michael Broughton
    Bob Buckley
    Tim Burger
    Nicholas Bushnell
    Jimmy Chen
    Benjamin Chiaro
    Desmond Chik
    Charina Chou
    Josh Cogan
    Roberto Collins
    Paul Conner
    William Courtney
    Alex Crook
    Ben Curtin
    Alejo Grajales Dau
    Dripto Debroy
    Agustin Di Paolo
    ILYA Drozdov
    Andrew Dunsworth
    Lara Faoro
    Edward Farhi
    Reza Fatemi
    Vinicius Ferreira
    Ebrahim Forati
    Brooks Foxen
    Élie Genois
    William Giang
    Dar Gilboa
    Raja Gosula
    Steve Habegger
    Michael Hamilton
    Monica Hansen
    Sean Harrington
    Paula Heu
    Markus Hoffmann
    Trent Huang
    Ashley Huff
    Bill Huggins
    Sergei Isakov
    Justin Iveland
    Cody Jones
    Pavol Juhas
    Kostyantyn Kechedzhi
    Marika Kieferova
    Alexei Kitaev
    Andrey Klots
    Alexander Korotkov
    Fedor Kostritsa
    John Mark Kreikebaum
    Dave Landhuis
    Pavel Laptev
    Kim Ming Lau
    Lily Laws
    Joonho Lee
    Kenny Lee
    Yuri Lensky
    Alexander Lill
    Wayne Liu
    Orion Martin
    Amanda Mieszala
    Shirin Montazeri
    Alexis Morvan
    Ramis Movassagh
    Wojtek Mruczkiewicz
    Charles Neill
    Ani Nersisyan
    Michael Newman
    JiunHow Ng
    Murray Ich Nguyen
    Tom O'Brien
    Alex Opremcak
    Andre Petukhov
    Rebecca Potter
    Leonid Pryadko
    Charles Rocque
    Negar Saei
    Kannan Sankaragomathi
    Henry Schurkus
    Christopher Schuster
    Mike Shearn
    Aaron Shorter
    Noah Shutty
    Vladimir Shvarts
    Jindra Skruzny
    Clarke Smith
    Rolando Somma
    George Sterling
    Doug Strain
    Marco Szalay
    Alfredo Torres
    Guifre Vidal
    Cheng Xing
    Jamie Yao
    Ping Yeh
    Juhwan Yoo
    Grayson Young
    Yaxing Zhang
    Ningfeng Zhu
    Jeremy Hilton
    Anthony Megrant
    Yu Chen
    Vadim Smelyanskiy
    Dmitry Abanin
    Science, 383 (2024), pp. 1332-1337
    Preview abstract Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qubits. In one dimension, we observed long-range quantum correlations and a ground-state fidelity of 0.86 for 18 qubits at the critical point. In two dimensions, we found mutual information that extends beyond nearest neighbors. Lastly, by coupling the system to auxiliaries emulating reservoirs with different chemical potentials, we explored transport in the quantum Heisenberg model. Our results establish engineered dissipation as a scalable alternative to unitary evolution for preparing entangled many-body states on noisy quantum processors. View details
    Purification-Based Quantum Error Mitigation of Pair-Correlated Electron Simulations
    Thomas E O'Brien
    Gian-Luca R. Anselmetti
    Fotios Gkritsis
    Vincent Elfving
    Stefano Polla
    William J. Huggins
    Oumarou Oumarou
    Kostyantyn Kechedzhi
    Dmitry Abanin
    Rajeev Acharya
    Igor Aleiner
    Richard Ross Allen
    Trond Ikdahl Andersen
    Kyle Anderson
    Markus Ansmann
    Frank Carlton Arute
    Kunal Arya
    Juan Atalaya
    Michael Blythe Broughton
    Bob Benjamin Buckley
    Alexandre Bourassa
    Leon Brill
    Tim Burger
    Nicholas Bushnell
    Jimmy Chen
    Yu Chen
    Benjamin Chiaro
    Desmond Chun Fung Chik
    Josh Godfrey Cogan
    Roberto Collins
    Paul Conner
    William Courtney
    Alex Crook
    Ben Curtin
    Ilya Drozdov
    Andrew Dunsworth
    Daniel Eppens
    Lara Faoro
    Edward Farhi
    Reza Fatemi
    Ebrahim Forati
    Brooks Riley Foxen
    William Giang
    Dar Gilboa
    Alejandro Grajales Dau
    Steve Habegger
    Michael C. Hamilton
    Sean Harrington
    Jeremy Patterson Hilton
    Markus Rudolf Hoffmann
    Trent Huang
    Ashley Anne Huff
    Sergei Isakov
    Justin Thomas Iveland
    Cody Jones
    Pavol Juhas
    Marika Kieferova
    Andrey Klots
    Alexander Korotkov
    Fedor Kostritsa
    John Mark Kreikebaum
    Dave Landhuis
    Pavel Laptev
    Kim Ming Lau
    Lily MeeKit Laws
    Joonho Lee
    Kenny Lee
    Alexander T. Lill
    Wayne Liu
    Orion Martin
    Trevor Johnathan Mccourt
    Anthony Megrant
    Xiao Mi
    Masoud Mohseni
    Shirin Montazeri
    Alexis Morvan
    Ramis Movassagh
    Wojtek Mruczkiewicz
    Charles Neill
    Ani Nersisyan
    Michael Newman
    Jiun How Ng
    Murray Nguyen
    Alex Opremcak
    Andre Gregory Petukhov
    Rebecca Potter
    Kannan Aryaperumal Sankaragomathi
    Christopher Schuster
    Mike Shearn
    Aaron Shorter
    Vladimir Shvarts
    Jindra Skruzny
    Vadim Smelyanskiy
    Clarke Smith
    Rolando Diego Somma
    Doug Strain
    Marco Szalay
    Alfredo Torres
    Guifre Vidal
    Jamie Yao
    Ping Yeh
    Juhwan Yoo
    Grayson Robert Young
    Yaxing Zhang
    Ningfeng Zhu
    Christian Gogolin
    Nature Physics (2023)
    Preview abstract An important measure of the development of quantum computing platforms has been the simulation of increasingly complex physical systems. Prior to fault-tolerant quantum computing, robust error mitigation strategies are necessary to continue this growth. Here, we study physical simulation within the seniority-zero electron pairing subspace, which affords both a computational stepping stone to a fully correlated model, and an opportunity to validate recently introduced ``purification-based'' error-mitigation strategies. We compare the performance of error mitigation based on doubling quantum resources in time (echo verification) or in space (virtual distillation), on up to 20 qubits of a superconducting qubit quantum processor. We observe a reduction of error by one to two orders of magnitude below less sophisticated techniques (e.g. post-selection); the gain from error mitigation is seen to increase with the system size. Employing these error mitigation strategies enables the implementation of the largest variational algorithm for a correlated chemistry system to-date. Extrapolating performance from these results allows us to estimate minimum requirements for a beyond-classical simulation of electronic structure. We find that, despite the impressive gains from purification-based error mitigation, significant hardware improvements will be required for classically intractable variational chemistry simulations. View details
    Noise-resilient Majorana Edge Modes on a Chain of Superconducting Qubits
    Alejandro Grajales Dau
    Alex Crook
    Alex Opremcak
    Alexa Rubinov
    Alexander Korotkov
    Alexandre Bourassa
    Alexei Kitaev
    Alexis Morvan
    Andre Gregory Petukhov
    Andrew Dunsworth
    Andrey Klots
    Anthony Megrant
    Ashley Anne Huff
    Benjamin Chiaro
    Bernardo Meurer Costa
    Bob Benjamin Buckley
    Brooks Foxen
    Charles Neill
    Christopher Schuster
    Cody Jones
    Daniel Eppens
    Dar Gilboa
    Dave Landhuis
    Dmitry Abanin
    Doug Strain
    Ebrahim Forati
    Edward Farhi
    Emily Mount
    Fedor Kostritsa
    Frank Carlton Arute
    Guifre Vidal
    Igor Aleiner
    Jamie Yao
    Jeremy Patterson Hilton
    Joao Basso
    John Mark Kreikebaum
    Joonho Lee
    Juan Atalaya
    Juhwan Yoo
    Justin Thomas Iveland
    Kannan Aryaperumal Sankaragomathi
    Kenny Lee
    Kim Ming Lau
    Kostyantyn Kechedzhi
    Kunal Arya
    Lara Faoro
    Leon Brill
    Marco Szalay
    Markus Rudolf Hoffmann
    Masoud Mohseni
    Michael Blythe Broughton
    Michael Newman
    Michel Henri Devoret
    Mike Shearn
    Nicholas Bushnell
    Orion Martin
    Paul Conner
    Pavel Laptev
    Ping Yeh
    Rajeev Acharya
    Rebecca Potter
    Reza Fatemi
    Roberto Collins
    Sergei Isakov
    Shirin Montazeri
    Steve Habegger
    Thomas E O'Brien
    Trent Huang
    Trond Ikdahl Andersen
    Vadim Smelyanskiy
    Vladimir Shvarts
    Wayne Liu
    William Courtney
    William Giang
    William J. Huggins
    Wojtek Mruczkiewicz
    Xiao Mi
    Yaxing Zhang
    Yu Chen
    Yuan Su
    Zijun Chen
    Science (2022) (to appear)
    Preview abstract Inherent symmetry of a quantum system may protect its otherwise fragile states. Leveraging such protection requires testing its robustness against uncontrolled environmental interactions. Using 47 superconducting qubits, we implement the kicked Ising model which exhibits Majorana edge modes (MEMs) protected by a $\mathbb{Z}_2$-symmetry. Remarkably, we find that any multi-qubit Pauli operator overlapping with the MEMs exhibits a uniform decay rate comparable to single-qubit relaxation rates, irrespective of its size or composition. This finding allows us to accurately reconstruct the exponentially localized spatial profiles of the MEMs. Spectroscopic measurements further indicate exponentially suppressed hybridization between the MEMs over larger system sizes, which manifests as a strong resilience against low-frequency noise. Our work elucidates the noise sensitivity of symmetry-protected edge modes in a solid-state environment. View details
    Preview abstract We propose a quantum algorithm for inferring the molecular nuclear spin Hamiltonian from time-resolved measurements of spin-spin correlators, which can be obtained via nuclear magnetic resonance (NMR). We focus on learning the anisotropic dipolar term of the Hamiltonian, which generates dynamics that are challenging to classically simulate in some contexts. We demonstrate the ability to directly estimate the Jacobian and Hessian of the corresponding learning problem on a quantum computer, allowing us to learn the Hamiltonian parameters. We develop algorithms for performing this computation on both noisy near-term and future fault-tolerant quantum computers. We argue that the former is promising as an early beyond-classical quantum application since it only requires evolution of a local spin Hamiltonian. We investigate the example of a protein (ubiquitin) confined on a membrane as a benchmark of our method. We isolate small spin clusters, demonstrate the convergence of our learning algorithm on one such example, and then investigate the learnability of these clusters as we cross the ergodic to nonergodic phase transition by suppressing the dipolar interaction. We see a clear correspondence between a drop in the multifractal dimension measured across many-body eigenstates of these clusters, and a transition in the structure of the Hessian of the learning cost function (from degenerate to learnable). Our hope is that such quantum computations might enable the interpretation and development of new NMR techniques for analyzing molecular structure. View details
    Quantum Approximate Optimization of Non-Planar Graph Problems on a Planar Superconducting Processor
    Kevin Jeffery Sung
    Frank Carlton Arute
    Kunal Arya
    Juan Atalaya
    Rami Barends
    Michael Blythe Broughton
    Bob Benjamin Buckley
    Nicholas Bushnell
    Jimmy Chen
    Yu Chen
    Ben Chiaro
    Roberto Collins
    William Courtney
    Andrew Dunsworth
    Brooks Riley Foxen
    Rob Graff
    Steve Habegger
    Sergei Isakov
    Cody Jones
    Kostyantyn Kechedzhi
    Alexander Korotkov
    Fedor Kostritsa
    Dave Landhuis
    Pavel Laptev
    Martin Leib
    Mike Lindmark
    Orion Martin
    John Martinis
    Anthony Megrant
    Xiao Mi
    Masoud Mohseni
    Wojtek Mruczkiewicz
    Josh Mutus
    Charles Neill
    Florian Neukart
    Thomas E O'Brien
    Bryan O'Gorman
    A.G. Petukhov
    Harry Putterman
    Andrea Skolik
    Vadim Smelyanskiy
    Doug Strain
    Michael Streif
    Marco Szalay
    Amit Vainsencher
    Jamie Yao
    Leo Zhou
    Edward Farhi
    Nature Physics (2021)
    Preview abstract Faster algorithms for combinatorial optimization could prove transformative for diverse areas such as logistics, finance and machine learning. Accordingly, the possibility of quantum enhanced optimization has driven much interest in quantum technologies. Here we demonstrate the application of the Google Sycamore superconducting qubit quantum processor to combinatorial optimization problems with the quantum approximate optimization algorithm (QAOA). Like past QAOA experiments, we study performance for problems defined on the planar connectivity graph native to our hardware; however, we also apply the QAOA to the Sherrington–Kirkpatrick model and MaxCut, non-native problems that require extensive compilation to implement. For hardware-native problems, which are classically efficient to solve on average, we obtain an approximation ratio that is independent of problem size and observe that performance increases with circuit depth. For problems requiring compilation, performance decreases with problem size. Circuits involving several thousand gates still present an advantage over random guessing but not over some efficient classical algorithms. Our results suggest that it will be challenging to scale near-term implementations of the QAOA for problems on non-native graphs. As these graphs are closer to real-world instances, we suggest more emphasis should be placed on such problems when using the QAOA to benchmark quantum processors. View details
    Realizing topologically ordered states on a quantum processor
    Y.-J. Liu
    A. Smith
    C. Knapp
    M. Newman
    N. C. Jones
    Z. Chen
    X. Mi
    A. Dunsworth
    I. Aleiner
    F. Arute
    K. Arya
    J. Atalaya
    R. Barends
    J. Basso
    M. Broughton
    B. B. Buckley
    N. Bushnell
    B. Chiaro
    R. Collins
    W. Courtney
    A. R Derk
    D. Eppens
    L. Faoro
    E. Farhi
    B. Foxen
    A. Greene
    S. D. Harrington
    J. Hilton
    T. Huang
    W. J. Huggins
    S. V. Isakov
    K. Kechedzhi
    A. N. Korotkov
    F. Kostritsa
    D. Landhuis
    P. Laptev
    O. Martin
    M. Mohseni
    S. Montazeri
    W. Mruczkiewicz
    J. Mutus
    C. Neill
    T. E. O'Brien
    A. Opremcak
    B. Pato
    A. Petukhov
    V. Shvarts
    D. Strain
    M. Szalay
    Z. Yao
    P. Yeh
    J. Yoo
    A. Megrant
    Y. Chen
    V. Smelyanskiy
    A. Kitaev
    M. Knap
    F. Pollmann
    Science, 374 (2021), pp. 1237-1241
    Preview abstract The discovery of topological order has revolutionized the understanding of quantum matter in modern physics and provided the theoretical foundation for many quantum error correcting codes. Realizing topologically ordered states has proven to be extremely challenging in both condensed matter and synthetic quantum systems. Here, we prepare the ground state of the emblematic toric code Hamiltonian using an efficient quantum circuit on a superconducting quantum processor. We measure a topological entanglement entropy of Stopo ≈ −0.95 × ln 2 and simulate anyon interferometry to extract the braiding statistics of the emergent excitations. Furthermore, we investigate key aspects of the surface code, including logical state injection and the decay of the non-local order parameter. Our results illustrate the topological nature of these states and demonstrate their potential for implementing the surface code. View details
    Resolving catastrophic error bursts from cosmic rays in large arrays of superconducting qubits
    Lara Faoro
    Kunal Arya
    Andrew Dunsworth
    Trent Huang
    Frank Arute
    Bob B. Buckley
    Nicholas Bushnell
    Jimmy Chen
    Roberto Collins
    Alan R. Derk
    Sean Harrington
    Fedor Kostritsa
    Pavel Laptev
    Xiao Mi
    Shirin Montazeri
    Josh Mutus
    Charles Neill
    Alex Opremcak
    Nicholas Redd
    Vladimir Shvarts
    Jamie Yao
    Ping Yeh
    Juhwan Yoo
    Yu Chen
    Vadim Smelyanskiy
    John Martinis
    Anthony Megrant
    Rami Barends
    Nature Physics (2021)
    Preview abstract Scalable quantum computing can become a reality with error correction, provided that coherent qubits can be constructed in large arrays. The key premise is that physical errors can remain both small and sufficiently uncorrelated as devices scale, so that logical error rates can be exponentially suppressed. However, impacts from cosmic rays and latent radioactivity violate these assumptions. An impinging particle can ionize the substrate and induce a burst of quasiparticles that destroys qubit coherence throughout the device. High-energy radiation has been identified as a source of error in pilot superconducting quantum devices, but the effect on large-scale algorithms and error correction remains an open question. Elucidating the physics involved requires operating large numbers of qubits at the same rapid timescales necessary for error correction. Here, we use space- and time-resolved measurements of a large-scale quantum processor to identify bursts of quasiparticles produced by high-energy rays. We track the events from their initial localized impact as they spread, simultaneously and severely limiting the energy coherence of all qubits and causing chip-wide failure. Our results provide direct insights into the impact of these damaging error bursts and highlight the necessity of mitigation to enable quantum computing to scale. View details
    Hartree-Fock on a Superconducting Qubit Quantum Computer
    Frank Carlton Arute
    Kunal Arya
    Rami Barends
    Michael Blythe Broughton
    Bob Benjamin Buckley
    Nicholas Bushnell
    Yu Chen
    Jimmy Chen
    Benjamin Chiaro
    Roberto Collins
    William Courtney
    Andrew Dunsworth
    Edward Farhi
    Brooks Riley Foxen
    Rob Graff
    Steve Habegger
    Alan Ho
    Trent Huang
    William J. Huggins
    Sergei Isakov
    Cody Jones
    Kostyantyn Kechedzhi
    Alexander Korotkov
    Fedor Kostritsa
    Dave Landhuis
    Pavel Laptev
    Mike Lindmark
    Orion Martin
    John Martinis
    Anthony Megrant
    Xiao Mi
    Masoud Mohseni
    Wojtek Mruczkiewicz
    Josh Mutus
    Charles Neill
    Thomas E O'Brien
    Eric Ostby
    Andre Gregory Petukhov
    Harry Putterman
    Vadim Smelyanskiy
    Doug Strain
    Kevin Jeffery Sung
    Marco Szalay
    Tyler Y. Takeshita
    Amit Vainsencher
    Nathan Wiebe
    Jamie Yao
    Ping Yeh
    Science, 369 (2020), pp. 6507
    Preview abstract As the search continues for useful applications of noisy intermediate scale quantum devices, variational simulations of fermionic systems remain one of the most promising directions. Here, we perform a series of quantum simulations of chemistry which involve twice the number of qubits and more than ten times the number of gates as the largest prior experiments. We model the binding energy of ${\rm H}_6$, ${\rm H}_8$, ${\rm H}_{10}$ and ${\rm H}_{12}$ chains as well as the isomerization of diazene. We also demonstrate error-mitigation strategies based on $N$-representability which dramatically improve the effective fidelity of our experiments. Our parameterized ansatz circuits realize the Givens rotation approach to free fermion evolution, which we variationally optimize to prepare the Hartree-Fock wavefunction. This ubiquitous algorithmic primitive corresponds to a rotation of the orbital basis and is required by many proposals for correlated simulations of molecules and Hubbard models. Because free fermion evolutions are classically tractable to simulate, yet still generate highly entangled states over the computational basis, we use these experiments to benchmark the performance of our hardware while establishing a foundation for scaling up more complex correlated quantum simulations of chemistry. View details
    Accurately computing electronic properties of materials using eigenenergies
    Alan Derk
    Alan Ho
    Alex Opremcak
    Alexander Korotkov
    Andre Gregory Petukhov
    Andrew Dunsworth
    Anthony Megrant
    Bálint Pató
    Benjamin Chiaro
    Bob Benjamin Buckley
    Brooks Riley Foxen
    Charles Neill
    Cody Jones
    Daniel Eppens
    Dave Landhuis
    Doug Strain
    Edward Farhi
    Eric Ostby
    Fedor Kostritsa
    Frank Carlton Arute
    Igor Aleiner
    Jamie Yao
    Jeremy Patterson Hilton
    Jimmy Chen
    Josh Mutus
    Juan Atalaya
    Juan Campero
    Kostyantyn Kechedzhi
    Kunal Arya
    Marco Szalay
    Masoud Mohseni
    Matt Jacob-Mitos
    Matt Trevithick
    Michael Blythe Broughton
    Michael Newman
    Nicholas Bushnell
    Nicholas Redd
    Orion Martin
    Pavel Laptev
    Ping Yeh
    Rami Barends
    Roberto Collins
    Sean Harrington
    Sergei Isakov
    Thomas E O'Brien
    Trent Huang
    Trevor Mccourt
    Vadim Smelyanskiy
    Vladimir Shvarts
    William Courtney
    William J. Huggins
    Wojtek Mruczkiewicz
    Xiao Mi
    Yu Chen
    arXiv preprint arXiv:2012.00921 (2020)
    Preview abstract A promising approach to study quantum materials is to simulate them on an engineered quantum platform. However, achieving the accuracy needed to outperform classical methods has been an outstanding challenge. Here, using superconducting qubits, we provide an experimental blueprint for a programmable and accurate quantum matter simulator and demonstrate how to probe fundamental electronic properties. We illustrate the underlying method by reconstructing the single-particle band-structure of a one-dimensional wire. We demonstrate nearly complete mitigation of decoherence and readout errors and arrive at an accuracy in measuring energy eigenvalues of this wire with an error of ~0.01 radians, whereas typical energy scales are of order 1 radian. Insight into this unprecedented algorithm fidelity is gained by highlighting robust properties of a Fourier transform, including the ability to resolve eigenenergies with a statistical uncertainty of 1e-4 radians. Furthermore, we synthesize magnetic flux and disordered local potentials, two key tenets of a condensed-matter system. When sweeping the magnetic flux, we observe avoided level crossings in the spectrum, a detailed fingerprint of the spatial distribution of local disorder. Combining these methods, we reconstruct electronic properties of the eigenstates where we observe persistent currents and a strong suppression of conductance with added disorder. Our work describes an accurate method for quantum simulation and paves the way to study novel quantum materials with superconducting qubits. View details