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1 - 15 of 129 publications
    Analyzing Prospects for Quantum Advantage in Topological Data Analysis
    Dominic W. Berry
    Yuan Su
    Casper Gyurik
    Robbie King
    Joao Basso
    Abhishek Rajput
    Nathan Wiebe
    Vedran Djunko
    PRX Quantum, vol. 5 (2024), pp. 010319
    Preview abstract Lloyd et al. were first to demonstrate the promise of quantum algorithms for computing Betti numbers in persistent homology (a way of characterizing topological features of data sets). Here, we propose, analyze, and optimize an improved quantum algorithm for topological data analysis (TDA) with reduced scaling, including a method for preparing Dicke states based on inequality testing, a more efficient amplitude estimation algorithm using Kaiser windows, and an optimal implementation of eigenvalue projectors based on Chebyshev polynomials. We compile our approach to a fault-tolerant gate set and estimate constant factors in the Toffoli complexity. Our analysis reveals that super-quadratic quantum speedups are only possible for this problem when targeting a multiplicative error approximation and the Betti number grows asymptotically. Further, we propose a dequantization of the quantum TDA algorithm that shows that having exponentially large dimension and Betti number are necessary, but insufficient conditions, for super-polynomial advantage. We then introduce and analyze specific problem examples for which super-polynomial advantages may be achieved, and argue that quantum circuits with tens of billions of Toffoli gates can solve some seemingly classically intractable instances. View details
    Drug Design on Quantum Computers
    Raffaele Santagati
    Alán Aspuru-Guzik
    Matthias Degroote
    Leticia Gonzalez
    Elica Kyoseva
    Nikolaj Moll
    Markus Oppel
    Robert Parrish
    Michael Streif
    Christofer Tautermann
    Horst Weiss
    Nathan Wiebe
    Clemens Utschig-Utschig
    Nature Physics (2024)
    Preview abstract The promised industrial applications of quantum computers often rest on their anticipated ability to perform accurate, efficient quantum chemical calculations. Computational drug discovery relies on accurate predictions of how candidate drugs interact with their targets in a cellular environment involving several thousands of atoms at finite temperatures. Although quantum computers are still far from being used as daily tools in the pharmaceutical industry, here we explore the challenges and opportunities of applying quantum computers to drug design. We discuss where these could transform industrial research and identify the substantial further developments needed to reach this goal. View details
    Preview abstract Measurement is one of the essential components of quantum algorithms, and for superconducting qubits it is often the most error prone. Here, we demonstrate a model-based readout optimization achieving low measurement errors while avoiding detrimental side-effects. For simultaneous and mid-circuit measurements across 17 qubits we observe 1.5% error per qubit with a duration of 500 ns end-to-end and minimal excess reset error from residual resonator photons. We also suppress measurement-induced state transitions and achieve a qubit leakage rate limited by natural heating.This technique can scale to hundreds of qubits, and be used to enhance performance of error-correcting codes as well as near-term applications View details
    Optimizing quantum gates towards the scale of logical qubits
    Alexandre Bourassa
    Andrew Dunsworth
    Will Livingston
    Vlad Sivak
    Trond Andersen
    Yaxing Zhang
    Desmond Chik
    Jimmy Chen
    Charles Neill
    Alejo Grajales Dau
    Anthony Megrant
    Alexander Korotkov
    Vadim Smelyanskiy
    Yu Chen
    Nature Communications, vol. 15 (2024), pp. 2442
    Preview abstract A foundational assumption of quantum error correction theory is that quantum gates can be scaled to large processors without exceeding the error-threshold for fault tolerance. Two major challenges that could become fundamental roadblocks are manufacturing high-performance quantum hardware and engineering a control system that can reach its performance limits. The control challenge of scaling quantum gates from small to large processors without degrading performance often maps to non-convex, high-constraint, and time-dynamic control optimization over an exponentially expanding configuration space. Here we report on a control optimization strategy that can scalably overcome the complexity of such problems. We demonstrate it by choreographing the frequency trajectories of 68 frequency-tunable superconducting qubits to execute single- and two-qubit gates while mitigating computational errors. When combined with a comprehensive model of physical errors across our processor, the strategy suppresses physical error rates by ~3.7× compared with the case of no optimization. Furthermore, it is projected to achieve a similar performance advantage on a distance-23 surface code logical qubit with 1057 physical qubits. Our control optimization strategy solves a generic scaling challenge in a way that can be adapted to a variety of quantum operations, algorithms, and computing architectures. View details
    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
    Austin Fowler
    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
    Trent Huang
    Ashley Huff
    Bill Huggins
    Sergei Isakov
    Justin Iveland
    Zhang Jiang
    Cody Jones
    Pavol Juhas
    Mostafa Khezri
    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
    Benjamin Villalonga
    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, vol. 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
    Austin Fowler
    Brooks Foxen
    Élie Genois
    William Giang
    Dar Gilboa
    Raja Gosula
    Steve Habegger
    Michael Hamilton
    Monica Hansen
    Sean Harrington
    Paula Heu
    Trent Huang
    Ashley Huff
    Bill Huggins
    Sergei Isakov
    Justin Iveland
    Zhang Jiang
    Cody Jones
    Pavol Juhas
    Kostyantyn Kechedzhi
    Mostafa Khezri
    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
    Benjamin Villalonga
    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, vol. 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
    Triply efficient shadow tomography
    Robbie King
    David Gosset
    arXiv:2404.19211 (2024)
    Preview abstract Given copies of a quantum state $\rho$, a shadow tomography protocol aims to learn all expectation values from a fixed set of observables, to within a given precision $\epsilon$. We say that a shadow tomography protocol is \textit{triply efficient} if it is sample- and time-efficient, and only employs measurements that entangle a constant number of copies of $\rho$ at a time. The classical shadows protocol based on random single-copy measurements is triply efficient for the set of local Pauli observables. This and other protocols based on random single-copy Clifford measurements can be understood as arising from fractional colorings of a graph $G$ that encodes the commutation structure of the set of observables. Here we describe a framework for two-copy shadow tomography that uses an initial round of Bell measurements to reduce to a fractional coloring problem in an induced subgraph of $G$ with bounded clique number. This coloring problem can be addressed using techniques from graph theory known as \textit{chi-boundedness}. Using this framework we give the first triply efficient shadow tomography scheme for the set of local fermionic observables, which arise in a broad class of interacting fermionic systems in physics and chemistry. We also give a triply efficient scheme for the set of all $n$-qubit Pauli observables. Our protocols for these tasks use two-copy measurements, which is necessary: sample-efficient schemes are provably impossible using only single-copy measurements. Finally, we give a shadow tomography protocol that compresses an $n$-qubit quantum state into a $\poly(n)$-sized classical representation, from which one can extract the expected value of any of the $4^n$ Pauli observables in $\poly(n)$ time, up to a small constant error. View details
    Quantum Error Mitigation
    Zhenyu Cai
    Simon Benjamin
    Suguru Endo
    William J. Huggins
    Ying Li
    Thomas E O'Brien
    Reviews of Modern Physics, vol. 95 (2023), pp. 045005
    Preview abstract For quantum computers to successfully solve real-world problems, it is necessary to tackle the challenge of noise: the errors that occur in elementary physical components due to unwanted or imperfect interactions. The theory of quantum fault tolerance can provide an answer in the long term, but in the coming era of noisy intermediate-scale quantum machines one must seek to mitigate errors rather than completely eliminate them. This review surveys the diverse methods that have been proposed for quantum error mitigation, assesses their in-principle efficacy, and describes the hardware demonstrations achieved to date. Commonalities and limitations among the methods are identified, while mention is made of how mitigation methods can be chosen according to the primary type of noise present, including algorithmic errors. Open problems in the field are identified, and the prospects for realizing mitigation-based devices that can deliver a quantum advantage with an impact on science and business are discussed. View details
    Matchgate Shadows for Fermionic Quantum Simulation
    Kianna Wan
    Bill Huggins
    Joonho Lee
    Communications in Mathematical Physics (2023)
    Preview abstract "Classical shadows" are estimators of an unknown quantum state, constructed from suitably distributed random measurements on copies of that state [Nature Physics 16, 1050-1057]. Here, we analyze classical shadows obtained using random matchgate circuits, which correspond to fermionic Gaussian unitaries. We prove that the first three moments of the Haar distribution over the continuous group of matchgate circuits are equal to those of the discrete uniform distribution over only the matchgate circuits that are also Clifford unitaries; thus, the latter forms a "matchgate 3-design." This implies that the classical shadows resulting from the two ensembles are functionally equivalent. We show how one can use these matchgate shadows to efficiently estimate inner products between an arbitrary quantum state and fermionic Gaussian states, as well as the expectation values of local fermionic operators and various other quantities, thus surpassing the capabilities of prior work. As a concrete application, this enables us to apply wavefunction constraints that control the fermion sign problem in the quantum-classical auxiliary-field quantum Monte Carlo algorithm (QC-AFQMC) [Nature 603, 416-420], without the exponential post-processing cost incurred by the original approach. View details
    Preview abstract Quadratic programming over the (special) orthogonal group encompasses a broad class of optimization problems such as group synchronization, point-set registration, and simultaneous localization and mapping. Such problems are instances of the little noncommutative Grothendieck problem (LNCG), a natural generalization of quadratic combinatorial optimization where, instead of binary decision variables, one optimizes over orthogonal matrices. In this work, we establish an embedding of this class of LNCG problems over the orthogonal group onto a quantum Hamiltonian. This embedding is accomplished by identifying orthogonal matrices with their double cover (Pin and Spin group) elements, which we represent as quantum states. We connect this construction to the theory of free fermions, which provides a physical interpretation of the derived LNCG Hamiltonian as a two-body interacting-fermion model due to the quadratic nature of the problem. Determining extremal states of this Hamiltonian provides an outer approximation to the original problem, analogous to classical relaxations of the problem via semidefinite programming. Furthermore, we show that when considering optimization over the special orthogonal group, our quantum relaxation naturally obeys additional, powerful constraints based on the convex hull of rotation matrices. The classical size of this convex-hull representation is exponential in matrix dimension, whereas the quantum representation requires only a linear number of qubits. Finally, to project the relaxed solution into the feasible space, we employ rounding procedures which return orthogonal matrices from appropriate measurements of the quantum state. Through numerical experiments we provide evidence that this quantum relaxation can produce high-quality approximations. View details
    Josephson parametric amplifier with Chebyshev gain profile and high saturation
    Ryan Kaufman
    Mark Dykman
    Andrea Iorio
    George Sterling
    Alex Opremcak
    Lara Faoro
    Tim Burger
    Robert Gasca
    Physical Review Applied, vol. 20 (2023), pp. 054058
    Preview abstract We demonstrate a Josephson parametric amplifier design with a band-pass impedance matching network based on a third-order Chebyshev prototype. We measured eight amplifiers operating at 4.6~GHz that exhibit gains of 20~dB with less than 1~dB gain ripple and up to 500~MHz bandwidth. The amplifiers further achieve high input saturation powers around $-93$~dBm based on the use of rf-SQUID arrays as their nonlinear element. We characterize the amplifiers' readout efficiency and their signal-to-noise ratio near saturation using a Sycamore processor. In addition, we measure the amplifiers intermodulation distortion in two-tone experiments as a function of input power and inter-tone detuning, and observe excess distortion at small detuning with a pronounced dip as a function of signal power, which we interpret in terms of power-dependent dielectric losses. View details
    Preview abstract We demonstrate a 3-port Josephson parametric circulator, matched to 50 Ohm using second order Chebyshev networks. The device notably operates with two of its signal ports at the same frequency and uses only two out-of-phase pumps at a single frequency. As a consequence, When operated as an isolator it does not require phase coherence between the pumps and the signal, simplifying the requirements for its integration into standard dispersive qubit readout setups. The device utilizes parametric couplers based on a balanced bridge of rf-SQUID arrays, which offer purely parametric coupling and high dynamic range. We characterize the device by measuring its full 3x3 S-matrix as a function of frequency the relative phase between the two pumps. We find up to 15 dB nonreciprocity over a 200 MHz signal band, port match better than 10 dB, low insertion loss of 0.6 dB, and saturation power exceeding -80 dBm. View details
    Exponential Quantum Speedup in Simulating Coupled Classical Oscillators
    Dominic Berry
    Rolando Somma
    Nathan Wiebe
    Physical Review X, vol. 13 (2023), pp. 041041
    Preview abstract We present a quantum algorithm for simulating the classical dynamics of 2^n coupled oscillators (e.g., 2^n masses coupled by springs). Our approach leverages a mapping between the Schrodinger equation and Newton's equations for harmonic potentials such that the amplitudes of the evolved quantum state encode the momenta and displacements of the classical oscillators. When individual masses and spring constants can be efficiently queried, and when the initial state can be efficiently prepared, the complexity of our quantum algorithm is polynomial in n, almost linear in the evolution time, and sublinear in the sparsity. As an example application, we apply our quantum algorithm to efficiently estimate the kinetic energy of an oscillator at any time, for a specification of the problem that we prove is \BQP-complete. Thus, our approach solves a potentially practical application with an exponential speedup over classical computers. Finally, we show that under similar conditions our approach can efficiently simulate more general classical harmonic systems with 2^n modes. View details
    Evaluating the Evidence for Exponential Quantum Advantage in Ground-State Quantum Chemistry
    Seunghoon Lee
    Joonho Lee
    Huanchen Zhai
    Yu Tong
    Alexander Dalzell
    Ashutosh Kumar
    Phillip Helms
    Johnnie Gray
    Zhi-Hao Cui
    Michael Kastoryano
    John Preskill
    David Reichman
    Earl Campbell
    Edward Valeev
    Lin Lin
    Garnet Chan
    Nature Communications, vol. 14 (2023)
    Preview abstract Due to intense interest in the potential applications of quantum computing, it is critical to understand the basis for potential exponential quantum advantage in quantum chemistry. Here we gather the evidence for this case in the most common task in quantum chemistry, namely, ground-state energy estimation, for generic chemical problems where heuristic quantum state preparation might be assumed to be efficient. The availability of exponential quantum advantage then centers on whether features of the physical problem that enable efficient heuristic quantum state preparation also enable efficient solution by classical heuristics. Through numerical studies of quantum state preparation and empirical complexity analysis (including the error scaling) of classical heuristics, in both ab initio and model Hamiltonian settings, we conclude that evidence for such an exponential advantage across chemical space has yet to be found. While quantum computers may still prove useful for ground-state quantum chemistry through polynomial speedups, it may be prudent to assume exponential speedups are not generically available for this problem. View details
    Readout of a quantum processor with high dynamic range Josephson parametric amplifiers
    Aaron Shorter
    Alejandro Grajales Dau
    Alex Crook
    Alex Opremcak
    Alexander Korotkov
    Alexander Lill
    Alexandre Bourassa
    Alexis Morvan
    Alfredo Torres
    Andrew Dunsworth
    Ani Nersisyan
    Anthony Megrant
    Ashley Anne Huff
    Ben Curtin
    Benjamin Chiaro
    Bob Benjamin Buckley
    Brooks Riley Foxen
    Charles Neill
    Christopher Schuster
    Dave Landhuis
    Ebrahim Forati
    Fedor Kostritsa
    Frank Carlton Arute
    Grayson Robert Young
    Jamie Yao
    Jeremy Patterson Hilton
    Jimmy Chen
    JiunHow Ng
    John Mark Kreikebaum
    Josh Godfrey Cogan
    Juhwan Yoo
    Justin Thomas Iveland
    Kannan Aryaperumal Sankaragomathi
    Kenny Lee
    Kunal Arya
    Leon Brill
    Lily MeeKit Laws
    Marco Szalay
    Marika Kieferova
    Markus Ansmann
    Michael C. Hamilton
    Mike Shearn
    Murray Nguyen
    Nicholas Bushnell
    Ningfeng Zhu
    Pavel Laptev
    Ping Yeh
    Rajeev Acharya
    Rebecca Potter
    Reza Fatemi
    Roberto Collins
    Sean Harrington
    Shirin Montazeri
    Tim Burger
    Trent Huang
    Trevor Johnathan Mccourt
    Vladimir Shvarts
    Wayne Liu
    William Giang
    Xiao Mi
    Yu Chen
    Applied Physics Letters, vol. 122 (2023), pp. 014001
    Preview abstract We demonstrate a high dynamic range Josephson parametric amplifier (JPA) in which the active nonlinear element is implemented using an array of rf-SQUIDs. The device is matched to the 50 $\Omega$ environment with a Klopfenstein-taper impedance transformer and achieves a bandwidth of 250-300 MHz, with input saturation powers up to $-95$~dBm at 20 dB gain. A 54-qubit Sycamore processor was used to benchmark these devices, providing a calibration for readout power, an estimate of amplifier added noise, and a platform for comparison against standard impedance matched parametric amplifiers with a single dc-SQUID. We find that the high power rf-SQUID array design has no adverse effect on system noise, readout fidelity, and qubit dephasing, and we estimate an upper bound on amplifier added noise at 1.6 times the quantum limit. Lastly, amplifiers with this design show no degradation in readout fidelity due to gain compression, which can occur in multi-tone multiplexed readout with traditional JPAs. View details