papers

Publications (99)

quant-ph2017

Optimizing Variational Quantum Algorithms using Pontryagin's Minimum Principle

Zhi-Cheng Yang, Armin Rahmani, Alireza Shabani +2

We use Pontryagin's minimum principle to optimize variational quantum algorithms. We show that for a fixed computation time, the optimal evolution has a bang-bang (square pulse) fo…

quant-ph2021

Quantum advantage in learning from experiments

Hsin-Yuan Huang, Michael Broughton, Jordan Cotler +8

Quantum technology has the potential to revolutionize how we acquire and process experimental data to learn about the physical world. An experimental setup that transduces data fro…

quant-ph2024

Sampling diverse near-optimal solutions via algorithmic quantum annealing

Masoud Mohseni, Marek M. Rams, Sergei V. Isakov +5

Sampling a diverse set of high-quality solutions for hard optimization problems is of great practical relevance in many scientific disciplines and applications, such as artificial…

quant-ph2019

Supplementary information for "Quantum supremacy using a programmable superconducting processor"

Frank Arute, Kunal Arya, Ryan Babbush +74

This is an updated version of supplementary information to accompany "Quantum supremacy using a programmable superconducting processor", an article published in the October 24, 201…

quant-ph2018

Universal Quantum Control through Deep Reinforcement Learning

Murphy Yuezhen Niu, Sergio Boixo, Vadim Smelyanskiy +1

Emerging reinforcement learning techniques using deep neural networks have shown great promise in control optimization. They harness non-local regularities of noisy control traject…

quant-ph2008

Image recognition with an adiabatic quantum computer I. Mapping to quadratic unconstrained binary optimization

Hartmut Neven, Geordie Rose, William G. Macready

Many artificial intelligence (AI) problems naturally map to NP-hard optimization problems. This has the interesting consequence that enabling human-level capability in machines oft…

quant-ph2021

Power of data in quantum machine learning

Hsin-Yuan Huang, Michael Broughton, Masoud Mohseni +4

The use of quantum computing for machine learning is among the most exciting prospective applications of quantum technologies. However, machine learning tasks where data is provide…

quant-ph2023

Learning to Decode the Surface Code with a Recurrent, Transformer-Based Neural Network

Johannes Bausch, Andrew W Senior, Francisco J H Heras +15

Quantum error-correction is a prerequisite for reliable quantum computation. Towards this goal, we present a recurrent, transformer-based neural network which learns to decode the…

quant-ph2022

Noise-resilient Edge Modes on a Chain of Superconducting Qubits

Xiao Mi, Michael Sonner, Murphy Yuezhen Niu +125

Inherent symmetry of a quantum system may protect its otherwise fragile states. Leveraging such protection requires testing its robustness against uncontrolled environmental intera…

quant-ph2021

Quantum Approximate Optimization of Non-Planar Graph Problems on a Planar Superconducting Processor

Matthew P. Harrigan, Kevin J. Sung, Matthew Neeley +83

We demonstrate the application of the Google Sycamore superconducting qubit quantum processor to combinatorial optimization problems with the quantum approximate optimization algor…

quant-ph2017

Tunable inductive coupling of superconducting qubits in the strongly nonlinear regime

Dvir Kafri, Chris Quintana, Yu Chen +3

For a variety of superconducting qubits, tunable interactions are achieved through mutual inductive coupling to a coupler circuit containing a nonlinear Josephson element. In this…

quant-ph2019

Decoding quantum errors with subspace expansions

Jarrod R. McClean, Zhang Jiang, Nicholas C. Rubin +2

With the rapid developments in quantum hardware comes a push towards the first practical applications on these devices. While fully fault-tolerant quantum computers may still be ye…

physics.bio-ph2015

Neuroreceptor Activation by Vibration-Assisted Tunneling

Ross D. Hoehn, David Nichols, Hartmut Neven +1

G protein-coupled receptors (GPCRs) constitute a large family of receptor proteins that sense molecular signals on the exterior of a cell and activate signal transduction pathways…

quant-ph2024

Quantum error correction below the surface code threshold

Rajeev Acharya, Laleh Aghababaie-Beni, Igor Aleiner +246

Quantum error correction provides a path to reach practical quantum computing by combining multiple physical qubits into a logical qubit, where the logical error rate is suppressed…

quant-ph2025

Magic state cultivation on a superconducting quantum processor

Emma Rosenfeld, Craig Gidney, Gabrielle Roberts +292

Fault-tolerant quantum computing requires a universal gate set, but the necessary non-Clifford gates represent a significant resource cost for most quantum error correction archite…

quant-ph2018

Barren plateaus in quantum neural network training landscapes

Jarrod R. McClean, Sergio Boixo, Vadim N. Smelyanskiy +2

Many experimental proposals for noisy intermediate scale quantum devices involve training a parameterized quantum circuit with a classical optimization loop. Such hybrid quantum-cl…

quant-ph2018

Classification with Quantum Neural Networks on Near Term Processors

Edward Farhi, Hartmut Neven

We introduce a quantum neural network, QNN, that can represent labeled data, classical or quantum, and be trained by supervised learning. The quantum circuit consists of a sequence…

quant-ph2019

Scaling advantage in quantum simulation of geometrically frustrated magnets

Andrew D. King, Jack Raymond, Trevor Lanting +51

The promise of quantum computing lies in harnessing programmable quantum devices for practical applications such as efficient simulation of quantum materials and condensed matter s…

quant-ph2019

Learning Non-Markovian Quantum Noise from Moiré-Enhanced Swap Spectroscopy with Deep Evolutionary Algorithm

Murphy Yuezhen Niu, Vadim Smelyanskyi, Paul Klimov +30

Two-level-system (TLS) defects in amorphous dielectrics are a major source of noise and decoherence in solid-state qubits. Gate-dependent non-Markovian errors caused by TLS-qubit c…

quant-ph2024

Scaling and logic in the color code on a superconducting quantum processor

Nathan Lacroix, Alexandre Bourassa, Francisco J. H. Heras +212

Quantum error correction is essential for bridging the gap between the error rates of physical devices and the extremely low logical error rates required for quantum algorithms. Re…

quant-ph2026

Reinforcement Learning Control of Quantum Error Correction

Volodymyr Sivak, Alexis Morvan, Michael Broughton +296

Quantum error correction (QEC) is the primary strategy for protecting a quantum computer from the environment. Its prerequisite is that errors must remain sufficiently rare, which…

quant-ph2017

Characterizing Quantum Supremacy in Near-Term Devices

Sergio Boixo, Sergei V. Isakov, Vadim N. Smelyanskiy +6

A critical question for the field of quantum computing in the near future is whether quantum devices without error correction can perform a well-defined computational task beyond t…

cond-mat.dis-nn2019

Intermittency of dynamical phases in a quantum spin glass

Vadim N. Smelyanskiy, Kostyantyn Kechedzhi, Sergio Boixo +2

Answering the question of existence of efficient quantum algorithms for NP-hard problems require deep theoretical understanding of the properties of the low-energy eigenstates and…

quant-ph2012

Robust Classification with Adiabatic Quantum Optimization

Vasil S. Denchev, Nan Ding, S. V. N. Vishwanathan +1

We propose a non-convex training objective for robust binary classification of data sets in which label noise is present. The design is guided by the intention of solving the resul…

quant-ph2025

Generative quantum advantage for classical and quantum problems

Hsin-Yuan Huang, Michael Broughton, Norhan Eassa +3

Recent breakthroughs in generative machine learning, powered by massive computational resources, have demonstrated unprecedented human-like capabilities. While beyond-classical qua…

quant-ph2018

For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances

Fernando G. S. L. Brandao, Michael Broughton, Edward Farhi +2

The Quantum Approximate Optimization Algorithm, QAOA, uses a shallow depth quantum circuit to produce a parameter dependent state. For a given combinatorial optimization problem in…

quant-ph2025

Visualizing Dynamics of Charges and Strings in (2+1)D Lattice Gauge Theories

Tyler A. Cochran, Bernhard Jobst, Eliott Rosenberg +189

Lattice gauge theories (LGTs) can be employed to understand a wide range of phenomena, from elementary particle scattering in high-energy physics to effective descriptions of many-…

quant-ph2021

Entangling Quantum Generative Adversarial Networks

Murphy Yuezhen Niu, Alexander Zlokapa, Michael Broughton +4

Generative adversarial networks (GANs) are one of the most widely adopted semisupervised and unsupervised machine learning methods for high-definition image, video, and audio gener…

quant-ph2024

Thermalization and Criticality on an Analog-Digital Quantum Simulator

Trond I. Andersen, Nikita Astrakhantsev, Amir H. Karamlou +224

Understanding how interacting particles approach thermal equilibrium is a major challenge of quantum simulators. Unlocking the full potential of such systems toward this goal requi…

quant-ph2025

Observation of disorder-free localization using a (2+1)D lattice gauge theory on a quantum processor

Gaurav Gyawali, Shashwat Kumar, Yuri D. Lensky +219

Disorder-induced phenomena in quantum many-body systems pose significant challenges for analytical methods and numerical simulations at relevant time and system scales. To reduce t…

quant-ph2023

Non-Abelian braiding of graph vertices in a superconducting processor

Trond I. Andersen, Yuri D. Lensky, Kostyantyn Kechedzhi +166

Indistinguishability of particles is a fundamental principle of quantum mechanics. For all elementary and quasiparticles observed to date - including fermions, bosons, and Abelian…

quant-ph2009

Training a Large Scale Classifier with the Quantum Adiabatic Algorithm

Hartmut Neven, Vasil S. Denchev, Geordie Rose +1

In a previous publication we proposed discrete global optimization as a method to train a strong binary classifier constructed as a thresholded sum over weak classifiers. Our motiv…

quant-ph2026

A scalable and real-time neural decoder for topological quantum codes

Andrew W. Senior, Thomas Edlich, Francisco J. H. Heras +21

Fault-tolerant quantum computing will require error rates far below those achievable with physical qubits. Quantum error correction (QEC) bridges this gap, but depends on decoders…

quant-ph2017

Scaling analysis and instantons for thermally-assisted tunneling and Quantum Monte Carlo simulations

Zhang Jiang, Vadim N. Smelyanskiy, Sergei V. Isakov +4

We develop an instantonic calculus to derive an analytical expression for the thermally-assisted tunneling decay rate of a metastable state in a fully connected quantum spin model.…

quant-ph2016

What is the Computational Value of Finite Range Tunneling?

Vasil S. Denchev, Sergio Boixo, Sergei V. Isakov +5

Quantum annealing (QA) has been proposed as a quantum enhanced optimization heuristic exploiting tunneling. Here, we demonstrate how finite range tunneling can provide considerable…

quant-ph2015

Systematic Dimensionality Reduction for Quantum Walks: Optimal Spatial Search and Transport on Non-Regular Graphs

Leonardo Novo, Shantanav Chakraborty, Masoud Mohseni +2

Continuous time quantum walks provide an important framework for designing new algorithms and modelling quantum transport and state transfer problems. Often, the graph representing…

quant-ph2025

Quantum-Classical Separation in Bounded-Resource Tasks Arising from Measurement Contextuality

Shashwat Kumar, Eliott Rosenberg, Alejandro Grajales Dau +280

The prevailing view is that quantum phenomena can be harnessed to tackle certain problems beyond the reach of classical approaches. Quantifying this capability as a quantum-classic…

cond-mat.dis-nn2021

Nonequilibrium Monte Carlo for unfreezing variables in hard combinatorial optimization

Masoud Mohseni, Daniel Eppens, Johan Strumpfer +7

Optimizing highly complex cost/energy functions over discrete variables is at the heart of many open problems across different scientific disciplines and industries. A major obstac…

quant-ph2023

Quantum computation of stopping power for inertial fusion target design

Nicholas C. Rubin, Dominic W. Berry, Alina Kononov +7

Stopping power is the rate at which a material absorbs the kinetic energy of a charged particle passing through it -- one of many properties needed over a wide range of thermodynam…

quant-ph2021

Observation of Time-Crystalline Eigenstate Order on a Quantum Processor

Xiao Mi, Matteo Ippoliti, Chris Quintana +102

Quantum many-body systems display rich phase structure in their low-temperature equilibrium states. However, much of nature is not in thermal equilibrium. Remarkably, it was recent…

quant-ph2020

Learnability and Complexity of Quantum Samples

Murphy Yuezhen Niu, Andrew M. Dai, Li Li +5

Given a quantum circuit, a quantum computer can sample the output distribution exponentially faster in the number of bits than classical computers. A similar exponential separation…

quant-ph2024

Long-range wormhole teleportation

Joseph D. Lykken, Daniel Jafferis, Alexander Zlokapa +4

We extend the protocol of Gao and Jafferis arXiv:1911.07416 to allow wormhole teleportation between two entangled copies of the Sachdev-Ye-Kitaev (SYK) model communicating only thr…

quant-ph2008

Training a Binary Classifier with the Quantum Adiabatic Algorithm

Hartmut Neven, Vasil S. Denchev, Geordie Rose +1

This paper describes how to make the problem of binary classification amenable to quantum computing. A formulation is employed in which the binary classifier is constructed as a th…

quant-ph2019

Readiness of Quantum Optimization Machines for Industrial Applications

Alejandro Perdomo-Ortiz, Alexander Feldman, Asier Ozaeta +9

There have been multiple attempts to demonstrate that quantum annealing and, in particular, quantum annealing on quantum annealing machines, has the potential to outperform current…

quant-ph2021

TensorFlow Quantum: A Software Framework for Quantum Machine Learning

Michael Broughton, Guillaume Verdon, Trevor McCourt +26

We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data. This framework offers high…

quant-ph2017

Path-Integral Quantum Monte Carlo simulation with Open-Boundary Conditions

Zhang Jiang, Vadim N. Smelyanskiy, Sergio Boixo +1

The tunneling decay event of a metastable state in a fully connected quantum spin model can be simulated efficiently by path integral quantum Monte Carlo (QMC) [Isakov , Ph…

quant-ph2017

Fourier analysis of sampling from noisy chaotic quantum circuits

Sergio Boixo, Vadim N. Smelyanskiy, Hartmut Neven

Sampling from the output distribution of chaotic quantum evolutions, and of pseudo-random universal quantum circuits in particular, has been proposed as a prominent milestone for n…

quant-ph2020

Hartree-Fock on a superconducting qubit quantum computer

Frank Arute, Kunal Arya, Ryan Babbush +79

As the search continues for useful applications of noisy intermediate scale quantum devices, variational simulations of fermionic systems remain one of the most promising direction…

quant-ph2020

Observation of separated dynamics of charge and spin in the Fermi-Hubbard model

Frank Arute, Kunal Arya, Ryan Babbush +96

Strongly correlated quantum systems give rise to many exotic physical phenomena, including high-temperature superconductivity. Simulating these systems on quantum computers may avo…

quant-ph2019

Quantum Simulation of the Sachdev-Ye-Kitaev Model by Asymmetric Qubitization

Ryan Babbush, Dominic Berry, Hartmut Neven

We show that one can quantum simulate the dynamics of a Sachdev-Ye-Kitaev model with Majorana modes for time to precision with gate complexity $O(N^{7/2} t + N^{5/2} t…

quant-ph2022

Formation of robust bound states of interacting microwave photons

Alexis Morvan, Trond I. Andersen, Xiao Mi +147

Systems of correlated particles appear in many fields of science and represent some of the most intractable puzzles in nature. The computational challenge in these systems arises w…

physics.hist-ph2021

Do Robots powered by a Quantum Processor have the Freedom to swerve?

Hartmut Neven, Peter Read, Tobias Rees

Any scientific attempt to explain consciousness is tasked with reconciling the third person objective perspective of science with our first person subjective experience of the worl…

quant-ph2018

Universal discriminative quantum neural networks

Hongxiang Chen, Leonard Wossnig, Simone Severini +2

Quantum mechanics fundamentally forbids deterministic discrimination of quantum states and processes. However, the ability to optimally distinguish various classes of quantum data…

quant-ph2015

Computational Role of Collective Tunneling in a Quantum Annealer

Sergio Boixo, Vadim N. Smelyanskiy, Alireza Shabani +7

Quantum tunneling is a phenomenon in which a quantum state traverses energy barriers above the energy of the state itself. Tunneling has been hypothesized as an advantageous physic…

quant-ph2024

Dynamics of magnetization at infinite temperature in a Heisenberg spin chain

Eliott Rosenberg, Trond Andersen, Rhine Samajdar +178

Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the 1D Heisenberg model were conjectured…

quant-ph2019

Quantum-Assisted Genetic Algorithm

James King, Masoud Mohseni, William Bernoudy +5

Genetic algorithms, which mimic evolutionary processes to solve optimization problems, can be enhanced by using powerful semi-local search algorithms as mutation operators. Here, w…

quant-ph2016

Artificial quantum thermal bath: Engineering temperature for a many-body quantum system

Alireza Shabani, Hartmut Neven

Temperature determines the relative probability of observing a physical system in an energy state when that system is energetically in equilibrium with its environment. In this pap…

quant-ph2020

Optimal fermion-to-qubit mapping via ternary trees with applications to reduced quantum states learning

Zhang Jiang, Amir Kalev, Wojciech Mruczkiewicz +1

We introduce a fermion-to-qubit mapping defined on ternary trees, where any single Majorana operator on an -mode fermionic system is mapped to a multi-qubit Pauli operator actin…

quant-ph2022

Suppressing quantum errors by scaling a surface code logical qubit

Rajeev Acharya, Igor Aleiner, Richard Allen +154

Practical quantum computing will require error rates that are well below what is achievable with physical qubits. Quantum error correction offers a path to algorithmically-relevant…

quant-ph2020

Majorana loop stabilizer codes for error correction of fermionic quantum simulations

Zhang Jiang, Jarrod McClean, Ryan Babbush +1

Fermion-to-qubit mappings that preserve geometric locality are especially useful for simulating lattice fermion models (e.g., the Hubbard model) on a quantum computer. They avoid t…

quant-ph2018

Efficient population transfer via non-ergodic extended states in quantum spin glass

Kostyantyn Kechedzhi, Vadim Smelyanskiy, Jarrod R. McClean +6

We analyze a new computational role of coherent multi-qubit quantum tunneling that gives rise to bands of non-ergodic extended (NEE) quantum states each formed by a superposition o…

quant-ph2021

Resolving catastrophic error bursts from cosmic rays in large arrays of superconducting qubits

Matt McEwen, Lara Faoro, Kunal Arya +50

Scalable quantum computing can become a reality with error correction, provided coherent qubits can be constructed in large arrays. The key premise is that physical errors can rema…

quant-ph2020

The Snake Optimizer for Learning Quantum Processor Control Parameters

Paul V. Klimov, Julian Kelly, John M. Martinis +1

High performance quantum computing requires a calibration system that learns optimal control parameters much faster than system drift. In some cases, the learning procedure require…

quant-ph2024

Optimizing quantum gates towards the scale of logical qubits

Paul V. Klimov, Andreas Bengtsson, Chris Quintana +21

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…

quant-ph2021

Information Scrambling in Computationally Complex Quantum Circuits

Xiao Mi, Pedram Roushan, Chris Quintana +90

Interaction in quantum systems can spread initially localized quantum information into the many degrees of freedom of the entire system. Understanding this process, known as quantu…

quant-ph2020

Low depth mechanisms for quantum optimization

Jarrod R. McClean, Matthew P. Harrigan, Masoud Mohseni +6

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 develo…

quant-ph2020

Compilation of Fault-Tolerant Quantum Heuristics for Combinatorial Optimization

Yuval R. Sanders, Dominic W. Berry, Pedro C. S. Costa +5

Here we explore which heuristic quantum algorithms for combinatorial optimization might be most practical to try out on a small fault-tolerant quantum computer. We compile circuits…

quant-ph2018

Simulation of low-depth quantum circuits as complex undirected graphical models

Sergio Boixo, Sergei V. Isakov, Vadim N. Smelyanskiy +1

Near term quantum computers with a high quantity (around 50) and quality (around 0.995 fidelity for two-qubit gates) of qubits will approximately sample from certain probability di…

quant-ph2020

Establishing the Quantum Supremacy Frontier with a 281 Pflop/s Simulation

Benjamin Villalonga, Dmitry Lyakh, Sergio Boixo +6

Noisy Intermediate-Scale Quantum (NISQ) computers are entering an era in which they can perform computational tasks beyond the capabilities of the most powerful classical computers…

cs.LG2015

Probabilistic Label Relation Graphs with Ising Models

Nan Ding, Jia Deng, Kevin Murphy +1

We consider classification problems in which the label space has structure. A common example is hierarchical label spaces, corresponding to the case where one label subsumes anothe…

quant-ph2021

Machine learning of high dimensional data on a noisy quantum processor

Evan Peters, João Caldeira, Alan Ho +6

We present a quantum kernel method for high-dimensional data analysis using Google's universal quantum processor, Sycamore. This method is successfully applied to the cosmological…

quant-ph2022

Efficient approximation of experimental Gaussian boson sampling

Benjamin Villalonga, Murphy Yuezhen Niu, Li Li +4

Two recent landmark experiments have performed Gaussian boson sampling (GBS) with a non-programmable linear interferometer and threshold detectors on up to 144 output modes (see Re…

quant-ph2021

Focus beyond quadratic speedups for error-corrected quantum advantage

Ryan Babbush, Jarrod McClean, Michael Newman +3

In this perspective, we discuss conditions under which it would be possible for a modest fault-tolerant quantum computer to realize a runtime advantage by executing a quantum algor…

quant-ph2015

Understanding Quantum Tunneling through Quantum Monte Carlo Simulations

Sergei V. Isakov, Guglielmo Mazzola, Vadim N. Smelyanskiy +4

The tunneling between the two ground states of an Ising ferromagnet is a typical example of many-body tunneling processes between two local minima, as they occur during quantum ann…

cs.LG2014

Construction of non-convex polynomial loss functions for training a binary classifier with quantum annealing

Ryan Babbush, Vasil Denchev, Nan Ding +2

Quantum annealing is a heuristic quantum algorithm which exploits quantum resources to minimize an objective function embedded as the energy levels of a programmable physical syste…

quant-ph2021

Quantum computation of molecular structure using data from challenging-to-classically-simulate nuclear magnetic resonance experiments

Thomas E. O'Brien, Lev B. Ioffe, Yuan Su +4

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 magn…

quant-ph2019

Quantum Simulation of Chemistry with Sublinear Scaling in Basis Size

Ryan Babbush, Dominic W. Berry, Jarrod R. McClean +1

We present a quantum algorithm for simulating quantum chemistry with gate complexity where is the number of electrons and is the number of pl…

quant-ph2021

A quantum algorithm for training wide and deep classical neural networks

Alexander Zlokapa, Hartmut Neven, Seth Lloyd

Given the success of deep learning in classical machine learning, quantum algorithms for traditional neural network architectures may provide one of the most promising settings for…

quant-ph2026

Precision quantum simulation of magnon spectra and interactions

Trond I. Andersen, Nikita Astrakhantsev, Jeronimo Martinez +329

Quantum simulation promises to advance materials discovery by accurately simulating complex states of matter, their microscopic excitations, and macroscopic response functions. The…

quant-ph2025

Constructive interference at the edge of quantum ergodic dynamics

Dmitry A. Abanin, Rajeev Acharya, Laleh Aghababaie-Beni +262

Quantum observables in the form of few-point correlators are the key to characterizing the dynamics of quantum many-body systems. In dynamics with fast entanglement generation, qua…

quant-ph2021

Exponential suppression of bit or phase flip errors with repetitive error correction

Zijun Chen, Kevin J. Satzinger, Juan Atalaya +88

Realizing the potential of quantum computing will require achieving sufficiently low logical error rates. Many applications call for error rates in the regime, but state…

quant-ph2019

Learning to learn with quantum neural networks via classical neural networks

Guillaume Verdon, Michael Broughton, Jarrod R. McClean +5

Quantum Neural Networks (QNNs) are a promising variational learning paradigm with applications to near-term quantum processors, however they still face some significant challenges.…

quant-ph2018

Low Depth Quantum Simulation of Electronic Structure

Ryan Babbush, Nathan Wiebe, Jarrod McClean +3

Quantum simulation of the electronic structure problem is one of the most researched applications of quantum computing. The majority of quantum algorithms for this problem encode t…

cs.LG2024

Need is All You Need: Homeostatic Neural Networks Adapt to Concept Shift

Kingson Man, Antonio Damasio, Hartmut Neven

In living organisms, homeostasis is the natural regulation of internal states aimed at maintaining conditions compatible with life. Typical artificial systems are not equipped with…

quant-ph2022

Overcoming leakage in scalable quantum error correction

Kevin C. Miao, Matt McEwen, Juan Atalaya +114

Leakage of quantum information out of computational states into higher energy states represents a major challenge in the pursuit of quantum error correction (QEC). In a QEC circuit…

quant-ph2020

Improved Fault-Tolerant Quantum Simulation of Condensed-Phase Correlated Electrons via Trotterization

Ian D. Kivlichan, Craig Gidney, Dominic W. Berry +9

Recent work has deployed linear combinations of unitaries techniques to reduce the cost of fault-tolerant quantum simulations of correlated electron models. Here, we show that one…

quant-ph2018

Non-ergodic delocalized states for efficient population transfer within a narrow band of the energy landscape

Vadim N. Smelyanskiy, Konstyantyn Kechedzhi, Sergio Boixo +3

We analyze the role of coherent tunneling that gives rise to bands of delocalized quantum states providing a coherent pathway for population transfer (PT) between computational sta…

quant-ph2019

A 28nm Bulk-CMOS 4-to-8GHz <2mW Cryogenic Pulse Modulator for Scalable Quantum Computing

Joseph C Bardin, Evan Jeffrey, Erik Lucero +28

Future quantum computing systems will require cryogenic integrated circuits to control and measure millions of qubits. In this paper, we report the design and characterization of a…

quant-ph2025

Demonstrating dynamic surface codes

Alec Eickbusch, Matt McEwen, Volodymyr Sivak +204

A remarkable characteristic of quantum computing is the potential for reliable computation despite faulty qubits. This can be achieved through quantum error correction, which is ty…

quant-ph2026

Hilbert space signatures of non-ergodic glassy dynamics

Aleksey Lunkin, Nicole S. Ticea, Shashwat Kumar +292

Disorder in quantum many-body systems can drive transitions between ergodic and non-ergodic phases, yet the nature--and even the existence--of these transitions remains intensely d…

quant-ph2026

Exponential quantum advantage in processing massive classical data

Haimeng Zhao, Alexander Zlokapa, Hartmut Neven +4

Broadly applicable quantum advantage, particularly in classical data processing and machine learning, has been a fundamental open problem. In this work, we prove that a small quant…

quant-ph2026

Securing Elliptic Curve Cryptocurrencies against Quantum Vulnerabilities: Resource Estimates and Mitigations

Ryan Babbush, Adam Zalcman, Craig Gidney +6

This whitepaper seeks to elucidate implications that the capabilities of developing quantum architectures have on blockchain vulnerabilities and mitigation strategies. First, we pr…

cs.LG2015

Totally Corrective Boosting with Cardinality Penalization

Vasil S. Denchev, Nan Ding, Shin Matsushima +2

We propose a totally corrective boosting algorithm with explicit cardinality regularization. The resulting combinatorial optimization problems are not known to be efficiently solva…

quant-ph2023

Quantum simulation of exact electron dynamics can be more efficient than classical mean-field methods

Ryan Babbush, William J. Huggins, Dominic W. Berry +6

Quantum algorithms for simulating electronic ground states are slower than popular classical mean-field algorithms such as Hartree-Fock and density functional theory, but offer hig…

quant-ph2018

Encoding Electronic Spectra in Quantum Circuits with Linear T Complexity

Ryan Babbush, Craig Gidney, Dominic W. Berry +5

We construct quantum circuits which exactly encode the spectra of correlated electron models up to errors from rotation synthesis. By invoking these circuits as oracles within the…

quant-ph2026

Observation of disorder-induced superfluidity

Nicole Ticea, Elias Portoles, Eliott Rosenberg +298

The emergence of states with long-range correlations in a disordered landscape is rare, as disorder typically suppresses the particle mobility required for long-range coherence. Bu…

quant-ph2018

Physical qubit calibration on a directed acyclic graph

Julian Kelly, Peter O'Malley, Matthew Neeley +2

High-fidelity control of qubits requires precisely tuned control parameters. Typically, these parameters are found through a series of bootstrapped calibration experiments which su…

quant-ph2015

Computational Role of Multiqubit Tunneling in a Quantum Annealer

Sergio Boixo, Vadim N. Smelyanskiy, Alireza Shabani +7

Quantum tunneling, a phenomenon in which a quantum state traverses energy barriers above the energy of the state itself, has been hypothesized as an advantageous physical resource…

quant-ph2023

Comment on "Comment on "Traversable wormhole dynamics on a quantum processor" "

Daniel Jafferis, Alexander Zlokapa, Joseph D. Lykken +5

We observe that the comment of [1, arXiv:2302.07897] is consistent with [2] on key points: i) the microscopic mechanism of the experimentally observed teleportation is size winding…