Zhang Jiang
Zhang is part of Google's quantum AI team. He worked at NASA Ames research center before joining Google. His main interests include quantum control, quantum simulation, and quantum optimization.
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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.
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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.
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Measurement-induced entanglement and teleportation on a noisy quantum processor
Jesse Hoke
Matteo Ippoliti
Dmitry Abanin
Rajeev Acharya
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
Josh Cogan
Roberto Collins
Paul Conner
William Courtney
Alex Crook
Ben Curtin
Alejo Grajales Dau
Agustin Di Paolo
ILYA Drozdov
Andrew Dunsworth
Daniel Eppens
Edward Farhi
Reza Fatemi
Vinicius Ferreira
Ebrahim Forati
Brooks Foxen
William Giang
Dar Gilboa
Raja Gosula
Steve Habegger
Michael Hamilton
Monica Hansen
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
Seun Omonije
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
Xiao Mi
Vedika Khemani
Nature, 622 (2023), 481–486
Preview abstract
Measurement has a special role in quantum theory: by collapsing the wavefunction, it can enable phenomena such as teleportation and thereby alter the ‘arrow of time’ that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space–time that go beyond the established paradigms for characterizing phases, either in or out of equilibrium. For present-day noisy intermediate-scale quantum (NISQ) processors, the experimental realization of such physics can be problematic because of hardware limitations and the stochastic nature of quantum measurement. Here we address these experimental challenges and study measurement-induced quantum information phases on up to 70 superconducting qubits. By leveraging the interchangeability of space and time, we use a duality mapping to avoid mid-circuit measurement and access different manifestations of the underlying phases, from entanglement scaling to measurement-induced teleportation. We obtain finite-sized signatures of a phase transition with a decoding protocol that correlates the experimental measurement with classical simulation data. The phases display remarkably different sensitivity to noise, and we use this disparity to turn an inherent hardware limitation into a useful diagnostic. Our work demonstrates an approach to realizing measurement-induced physics at scales that are at the limits of current NISQ processors.
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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.
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Efficient and Noise Resilient Measurements for Quantum Chemistry on Near-Term Quantum Computers
William Huggins
Nathan Wiebe
K. Birgitta Whaley
Nature Quantum Information, 7 (2021)
Preview abstract
Variational algorithms are a promising paradigm for utilizing near-term quantum devices for modeling electronic states of molecular systems. However, previous bounds on the measurement time required have suggested that the application of these techniques to larger molecules might be infeasible. We present a measurement strategy based on a low-rank factorization of the two-electron integral tensor. Our approach provides a cubic reduction in term groupings over prior state-of-the-art and enables measurement times three orders of magnitude smaller than those suggested by commonly referenced bounds for the largest systems we consider. Although our technique requires execution of a linear-depth circuit prior to measurement, this is compensated for by eliminating challenges associated with sampling nonlocal Jordan–Wigner transformed operators in the presence of measurement error, while enabling a powerful form of error mitigation based on efficient postselection. We numerically characterize these benefits with noisy quantum circuit simulations for ground-state energies of strongly correlated electronic systems.
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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.
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Low-Depth Mechanisms for Quantum Optimization
Masoud Mohseni
Vadim Smelyanskiy
PRX Quantum, 3 (2021), pp. 030312
Preview abstract
One of the major application areas of interest for both near-term and fault-tolerant quantum computers is the optimization of classical objective functions. In this work, we develop intuitive constructions for a large class of these algorithms based on connections to simple dynamics of quantum systems, quantum walks, and classical continuous relaxations. We focus on developing a language and tools connected with kinetic energy on a graph for understanding the physical mechanisms of success and failure to guide algorithmic improvement. This physical language, in combination with uniqueness results related to unitarity, allow us to identify some potential pitfalls from kinetic energy fundamentally opposing the goal of optimization. This is connected to effects from wavefunction confinement, phase randomization, and shadow defects lurking in the objective far away from the ideal solution. As an example, we explore the surprising deficiency of many quantum methods in solving uncoupled spin problems and how this is both predictive of performance on some more complex systems while immediately suggesting simple resolutions. Further examination of canonical problems like the Hamming ramp or bush of implications show that entanglement can be strictly detrimental to performance results from the underlying mechanism of solution in approaches like QAOA. Kinetic energy and graph Laplacian perspectives provide new insights to common initialization and optimal solutions in QAOA as well as new methods for more effective layerwise training. Connections to classical methods of continuous extensions, homotopy methods, and iterated rounding suggest new directions for research in quantum optimization. Throughout, we unveil many pitfalls and mechanisms in quantum optimization using a physical perspective, which aim to spur the development of novel quantum optimization algorithms and refinements.
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Tuning Quantum Information Scrambling on a 53-Qubit Processor
Alan Derk
Alan Ho
Alex Opremcak
Alexander Korotkov
Alexandre Bourassa
Andre Gregory Petukhov
Andrew Dunsworth
Anthony Megrant
Bálint Pató
Benjamin Chiaro
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
Jeffrey Marshall
Jeremy Patterson Hilton
Jimmy Chen
Josh Mutus
Juan Atalaya
Kostyantyn Kechedzhi
Kunal Arya
Marco Szalay
Masoud Mohseni
Matt Trevithick
Michael Blythe Broughton
Michael Newman
Nicholas Bushnell
Nicholas Redd
Orion Martin
Pavel Laptev
Ping Yeh
Rami Barends
Roberto Collins
Salvatore Mandra
Sean Harrington
Sergei Isakov
Thomas E O'Brien
Trent Huang
Trevor Mccourt
Vadim Smelyanskiy
Vladimir Shvarts
William Courtney
Wojtek Mruczkiewicz
Xiao Mi
Yu Chen
arXiv (2021)
Preview abstract
As entanglement in a quantum system grows, initially localized quantum information is spread into the exponentially many degrees of freedom of the entire system. This process, known as quantum scrambling, is computationally intensive to study classically and lies at the heart of several modern physics conundrums. Here, we characterize scrambling of different quantum circuits on a 53-qubit programmable quantum processor by measuring their out-of-time-order correlators (OTOCs). We observe that the spatiotemporal spread of OTOCs, as well as their circuit-to-circuit fluctuation, unravel in detail the time-scale and extent of quantum scrambling. Comparison with numerical results indicates a high OTOC measurement accuracy despite the large size of the quantum system. Our work establishes OTOC as an experimental tool to diagnose quantum scrambling at the threshold of being classically inaccessible.
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Exponential suppression of bit or phase flip errors with repetitive quantum error correction
Alan Derk
Alan Ho
Alex Opremcak
Alexander Korotkov
Alexandre Bourassa
Andre Gregory Petukhov
Andrew Dunsworth
Anthony Megrant
Bálint Pató
Benjamin Chiaro
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
Kostyantyn Kechedzhi
Kunal Arya
Marco Szalay
Masoud Mohseni
Matt Trevithick
Michael 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
Wojtek Mruczkiewicz
Xiao Mi
Yu Chen
Nature (2021)
Preview abstract
Realizing the potential of quantum computing will require achieving sufficiently low logical error rates. Many applications call for error rates below 10^-15, but state-of-the-art quantum platforms typically have physical error rates near 10^-3. Quantum error correction (QEC) promises to bridge this divide by distributing quantum logical information across many physical qubits so that errors can be corrected. Logical errors are then exponentially suppressed as the number of physical qubits grows, provided that the physical error rates are below a certain threshold. QEC also requires that the errors are local, and that performance is maintained over many rounds of error correction, a major outstanding experimental challenge. Here, we implement 1D repetition codes embedded in a 2D grid of superconducting qubits which demonstrate exponential suppression of bit or phase-flip errors, reducing logical error per round by more than 100x when increasing the number of qubits from 5 to 21. Crucially, this error suppression is stable over 50 rounds of error correction. We also introduce a method for analyzing error correlations with high precision, and characterize the locality of errors in a device performing QEC for the first time. Finally, we perform error detection using a small 2D surface code logical qubit on the same device, and show that the results from both 1D and 2D codes agree with numerical simulations using a simple depolarizing error model. These findings demonstrate that superconducting qubits are on a viable path towards fault tolerant quantum computing.
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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.
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