Lev Ioffe
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Dynamics of magnetization at infinite temperature in a Heisenberg spin chain
Tomaž Prosen
Vedika Khemani
Rhine Samajdar
Jesse Hoke
Sarang Gopalakrishnan
Andrew Dunsworth
Bill Huggins
Markus Hoffmann
Alexis Morvan
Josh Cogan
Ben Curtin
Guifre Vidal
Bob Buckley
Tom O'Brien
John Mark Kreikebaum
Rajeev Acharya
Joonho Lee
Ningfeng Zhu
Shirin Montazeri
Sergei Isakov
Jamie Yao
Clarke Smith
Rebecca Potter
Sean Harrington
Jeremy Hilton
Paula Heu
Alexei Kitaev
Alex Crook
Fedor Kostritsa
Kim Ming Lau
Dmitry Abanin
Trent Huang
Aaron Shorter
Steve Habegger
Steven Martin
Gina Bortoli
Seun Omonije
Richard Ross Allen
Charles Rocque
Vladimir Shvarts
Alfredo Torres
Anthony Megrant
Charles Neill
Michael Hamilton
Dar Gilboa
Lily Laws
Nicholas Bushnell
Kyle Anderson
Ramis Movassagh
David Rhodes
Mike Shearn
Wojtek Mruczkiewicz
Desmond Chik
Leonid Pryadko
Xiao Mi
Brooks Foxen
Frank Arute
Alejo Grajales Dau
Yaxing Zhang
Lara Faoro
Alexander Lill
Gordon Hill
JiunHow Ng
Justin Iveland
Marco Szalay
Orion Martin
Juan Campero
Juhwan Yoo
Michael Newman
William Giang
Gonzalo Garcia
Alex Opremcak
Amanda Mieszala
William Courtney
Andrey Klots
Wayne Liu
Pavel Laptev
Paul Conner
Rolando Somma
Vadim Smelyanskiy
Benjamin Chiaro
Grayson Young
Tim Burger
ILYA Drozdov
Agustin Di Paolo
Jimmy Chen
Marika Kieferova
Hung-Shen Chang
Michael Broughton
Negar Saei
Juan Atalaya
Markus Ansmann
Pavol Juhas
Murray Ich Nguyen
Yuri Lensky
Roberto Collins
Élie Genois
Jindra Skruzny
Yu Chen
Reza Fatemi
Leon Brill
Seneca Meeks
Ashley Huff
Doug Strain
Monica Hansen
Noah Shutty
Ebrahim Forati
Doug Thor
Dave Landhuis
Kenny Lee
Ping Yeh
Kunal Arya
Henry Schurkus
Cheng Xing
Cody Jones
Edward Farhi
Vlad Sivak
Raja Gosula
Andre Petukhov
Clint Earle
Alexander Korotkov
Ani Nersisyan
Christopher Schuster
George Sterling
Trond Andersen
Alexandre Bourassa
Salvatore Mandra
Kannan Sankaragomathi
Vinicius Ferreira
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.
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Stable quantum-correlated many-body states through engineered dissipation
Sara Shabani
Dripto Debroy
Jerome Lloyd
Alexios Michailidis
Andrew Dunsworth
Bill Huggins
Markus Hoffmann
Alexis Morvan
Josh Cogan
Ben Curtin
Guifre Vidal
Bob Buckley
Tom O'Brien
John Mark Kreikebaum
Rajeev Acharya
Joonho Lee
Ningfeng Zhu
Shirin Montazeri
Sergei Isakov
Jamie Yao
Clarke Smith
Rebecca Potter
Sean Harrington
Jeremy Hilton
Paula Heu
Alexei Kitaev
Alex Crook
Fedor Kostritsa
Kim Ming Lau
Dmitry Abanin
Trent Huang
Aaron Shorter
Steve Habegger
Gina Bortoli
Charles Rocque
Vladimir Shvarts
Alfredo Torres
Anthony Megrant
Charles Neill
Michael Hamilton
Dar Gilboa
Lily Laws
Nicholas Bushnell
Ramis Movassagh
Mike Shearn
Wojtek Mruczkiewicz
Desmond Chik
Leonid Pryadko
Xiao Mi
Brooks Foxen
Frank Arute
Alejo Grajales Dau
Yaxing Zhang
Lara Faoro
Alexander Lill
JiunHow Ng
Justin Iveland
Marco Szalay
Orion Martin
Juhwan Yoo
Michael Newman
William Giang
Alex Opremcak
Amanda Mieszala
William Courtney
Andrey Klots
Wayne Liu
Pavel Laptev
Charina Chou
Paul Conner
Rolando Somma
Vadim Smelyanskiy
Benjamin Chiaro
Grayson Young
Tim Burger
ILYA Drozdov
Agustin Di Paolo
Jimmy Chen
Marika Kieferova
Michael Broughton
Negar Saei
Juan Atalaya
Markus Ansmann
Pavol Juhas
Murray Ich Nguyen
Yuri Lensky
Roberto Collins
Élie Genois
Jindra Skruzny
Igor Aleiner
Yu Chen
Reza Fatemi
Leon Brill
Ashley Huff
Doug Strain
Monica Hansen
Noah Shutty
Ebrahim Forati
Dave Landhuis
Kenny Lee
Ping Yeh
Kunal Arya
Henry Schurkus
Cheng Xing
Cody Jones
Edward Farhi
Raja Gosula
Andre Petukhov
Alexander Korotkov
Ani Nersisyan
Christopher Schuster
George Sterling
Kostyantyn Kechedzhi
Trond Andersen
Alexandre Bourassa
Kannan Sankaragomathi
Vinicius Ferreira
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.
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Purification-Based Quantum Error Mitigation of Pair-Correlated Electron Simulations
Christian Gogolin
Vincent Elfving
Fotios Gkritsis
Oumarou Oumarou
Gian-Luca R. Anselmetti
Masoud Mohseni
Andrew Dunsworth
William J. Huggins
Markus Rudolf Hoffmann
Alexis Morvan
Josh Godfrey Cogan
Ben Curtin
Guifre Vidal
Bob Benjamin Buckley
Trevor Johnathan Mccourt
Thomas E O'Brien
John Mark Kreikebaum
Rajeev Acharya
Joonho Lee
Ningfeng Zhu
Shirin Montazeri
Sergei Isakov
Jamie Yao
Clarke Smith
Rebecca Potter
Sean Harrington
Jeremy Patterson Hilton
Alex Crook
Fedor Kostritsa
Kim Ming Lau
Dmitry Abanin
Trent Huang
Aaron Shorter
Steve Habegger
Richard Ross Allen
Vladimir Shvarts
Alfredo Torres
Stefano Polla
Anthony Megrant
Charles Neill
Michael C. Hamilton
Dar Gilboa
Lily MeeKit Laws
Nicholas Bushnell
Kyle Anderson
Ramis Movassagh
Mike Shearn
Wojtek Mruczkiewicz
Desmond Chun Fung Chik
Xiao Mi
Brooks Riley Foxen
Frank Carlton Arute
Alejandro Grajales Dau
Yaxing Zhang
Lara Faoro
Alexander T. Lill
Jiun How Ng
Justin Thomas Iveland
Marco Szalay
Orion Martin
Juhwan Yoo
Michael Newman
William Giang
Alex Opremcak
William Courtney
Andrey Klots
Wayne Liu
Pavel Laptev
Paul Conner
Rolando Diego Somma
Vadim Smelyanskiy
Benjamin Chiaro
Grayson Robert Young
Tim Burger
Ilya Drozdov
Jimmy Chen
Marika Kieferova
Michael Blythe Broughton
Juan Atalaya
Markus Ansmann
Pavol Juhas
Murray Nguyen
Daniel Eppens
Roberto Collins
Jindra Skruzny
Igor Aleiner
Yu Chen
Reza Fatemi
Leon Brill
Ashley Anne Huff
Doug Strain
Ebrahim Forati
Dave Landhuis
Kenny Lee
Ping Yeh
Kunal Arya
Cody Jones
Edward Farhi
Andre Gregory Petukhov
Alexander Korotkov
Ani Nersisyan
Christopher Schuster
Kostyantyn Kechedzhi
Trond Ikdahl Andersen
Alexandre Bourassa
Kannan Aryaperumal Sankaragomathi
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.
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Quantum Computation of Molecular Structure using Data from Challenging-to-Classically-Simulate Nuclear Magnetic Resonance Experiments
David Fushman
Yuan Su
Thomas E O'Brien
Vadim Smelyanskiy
PRX Quantum, 3 (2022)
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.
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Noise-resilient Majorana Edge Modes on a Chain of Superconducting Qubits
Zijun Chen
Brooks Foxen
Masoud Mohseni
Emily Mount
Joao Basso
Andrew Dunsworth
William J. Huggins
Yuan Su
Markus Rudolf Hoffmann
Alexis Morvan
Guifre Vidal
Bob Benjamin Buckley
Thomas E O'Brien
John Mark Kreikebaum
Rajeev Acharya
Joonho Lee
Shirin Montazeri
Sergei Isakov
Jamie Yao
Rebecca Potter
Jeremy Patterson Hilton
Alexei Kitaev
Alex Crook
Fedor Kostritsa
Kim Ming Lau
Dmitry Abanin
Trent Huang
Steve Habegger
Alexa Rubinov
Vladimir Shvarts
Anthony Megrant
Charles Neill
Dar Gilboa
Nicholas Bushnell
Mike Shearn
Wojtek Mruczkiewicz
Xiao Mi
Frank Carlton Arute
Alejandro Grajales Dau
Yaxing Zhang
Lara Faoro
Justin Thomas Iveland
Marco Szalay
Orion Martin
Juhwan Yoo
Michael Newman
William Giang
Alex Opremcak
William Courtney
Andrey Klots
Wayne Liu
Pavel Laptev
Paul Conner
Vadim Smelyanskiy
Benjamin Chiaro
Bernardo Meurer Costa
Michael Blythe Broughton
Juan Atalaya
Daniel Eppens
Roberto Collins
Igor Aleiner
Yu Chen
Reza Fatemi
Leon Brill
Ashley Anne Huff
Doug Strain
Ebrahim Forati
Dave Landhuis
Kenny Lee
Ping Yeh
Kunal Arya
Michel Henri Devoret
Cody Jones
Edward Farhi
Andre Gregory Petukhov
Alexander Korotkov
Christopher Schuster
Kostyantyn Kechedzhi
Trond Ikdahl Andersen
Alexandre Bourassa
Kannan Aryaperumal Sankaragomathi
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.
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Quantum Approximate Optimization of Non-Planar Graph Problems on a Planar Superconducting Processor
Michael Streif
Florian Neukart
Andrea Skolik
Martin Leib
Ben Chiaro
Bryan O'Gorman
A.G. Petukhov
Masoud Mohseni
Andrew Dunsworth
Rami Barends
Amit Vainsencher
John Martinis
Josh Mutus
Bob Benjamin Buckley
Thomas E O'Brien
Sergei Isakov
Jamie Yao
Fedor Kostritsa
Steve Habegger
Anthony Megrant
Charles Neill
Nicholas Bushnell
Harry Putterman
Wojtek Mruczkiewicz
Xiao Mi
Leo Zhou
Brooks Riley Foxen
Frank Carlton Arute
Marco Szalay
Orion Martin
William Courtney
Pavel Laptev
Vadim Smelyanskiy
Jimmy Chen
Mike Lindmark
Michael Blythe Broughton
Juan Atalaya
Roberto Collins
Yu Chen
Kevin Jeffery Sung
Doug Strain
Rob Graff
Dave Landhuis
Kunal Arya
Cody Jones
Edward Farhi
Alexander Korotkov
Kostyantyn Kechedzhi
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.
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Realizing topologically ordered states on a quantum processor
A. Greene
F. Pollmann
L. Faoro
C. Knapp
B. Pato
Y.-J. Liu
R. Barends
J. Mutus
M. Knap
A. Smith
M. Mohseni
J. Basso
A. Dunsworth
W. J. Huggins
A. R Derk
B. B. Buckley
T. E. O'Brien
S. Montazeri
S. V. Isakov
Z. Yao
S. D. Harrington
J. Hilton
A. Kitaev
F. Kostritsa
T. Huang
V. Shvarts
A. Megrant
C. Neill
N. Bushnell
W. Mruczkiewicz
X. Mi
B. Foxen
F. Arute
M. Szalay
O. Martin
J. Yoo
M. Newman
A. Opremcak
W. Courtney
P. Laptev
V. Smelyanskiy
B. Chiaro
Z. Chen
M. Broughton
J. Atalaya
D. Eppens
R. Collins
I. Aleiner
Y. Chen
D. Strain
D. Landhuis
P. Yeh
K. Arya
N. C. Jones
E. Farhi
A. Petukhov
A. N. Korotkov
K. Kechedzhi
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.
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Resolving catastrophic error bursts from cosmic rays in large arrays of superconducting qubits
Andrew Dunsworth
Alan R. Derk
Rami Barends
John Martinis
Josh Mutus
Bob B. Buckley
Shirin Montazeri
Jamie Yao
Sean Harrington
Fedor Kostritsa
Trent Huang
Vladimir Shvarts
Nicholas Redd
Anthony Megrant
Charles Neill
Nicholas Bushnell
Xiao Mi
Frank Arute
Lara Faoro
Juhwan Yoo
Alex Opremcak
Pavel Laptev
Vadim Smelyanskiy
Jimmy Chen
Roberto Collins
Yu Chen
Ping Yeh
Kunal Arya
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.
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Hartree-Fock on a Superconducting Qubit Quantum Computer
Nathan Wiebe
Tyler Y. Takeshita
Masoud Mohseni
Andrew Dunsworth
Alan Ho
William J. Huggins
Eric Ostby
Rami Barends
Amit Vainsencher
John Martinis
Josh Mutus
Bob Benjamin Buckley
Thomas E O'Brien
Sergei Isakov
Jamie Yao
Fedor Kostritsa
Trent Huang
Steve Habegger
Anthony Megrant
Charles Neill
Nicholas Bushnell
Harry Putterman
Wojtek Mruczkiewicz
Xiao Mi
Brooks Riley Foxen
Frank Carlton Arute
Marco Szalay
Orion Martin
William Courtney
Pavel Laptev
Vadim Smelyanskiy
Benjamin Chiaro
Jimmy Chen
Mike Lindmark
Michael Blythe Broughton
Roberto Collins
Yu Chen
Kevin Jeffery Sung
Doug Strain
Rob Graff
Dave Landhuis
Ping Yeh
Kunal Arya
Cody Jones
Edward Farhi
Andre Gregory Petukhov
Alexander Korotkov
Kostyantyn Kechedzhi
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.
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Accurately computing electronic properties of materials using eigenenergies
Masoud Mohseni
Andrew Dunsworth
Alan Ho
William J. Huggins
Matt Trevithick
Eric Ostby
Alan Derk
Rami Barends
Bálint Pató
Josh Mutus
Bob Benjamin Buckley
Trevor Mccourt
Thomas E O'Brien
Sergei Isakov
Jamie Yao
Sean Harrington
Jeremy Patterson Hilton
Fedor Kostritsa
Trent Huang
Vladimir Shvarts
Nicholas Redd
Anthony Megrant
Charles Neill
Nicholas Bushnell
Wojtek Mruczkiewicz
Xiao Mi
Brooks Riley Foxen
Frank Carlton Arute
Marco Szalay
Orion Martin
Juan Campero
Michael Newman
Alex Opremcak
William Courtney
Pavel Laptev
Vadim Smelyanskiy
Benjamin Chiaro
Jimmy Chen
Michael Blythe Broughton
Juan Atalaya
Daniel Eppens
Roberto Collins
Igor Aleiner
Yu Chen
Doug Strain
Dave Landhuis
Ping Yeh
Kunal Arya
Cody Jones
Edward Farhi
Matt Jacob-Mitos
Andre Gregory Petukhov
Alexander Korotkov
Kostyantyn Kechedzhi
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.
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