Dripto M. Debroy
Dripto is a research scientist with the Quantum Physics team of Google Quantum AI. He received his PhD in Physics from Duke University, and his BS in Physics from the University of California - Santa Barbara. His work is focused on improving the reliability of quantum computers through effective calibration, benchmarking, and quantum error correction, with a particular interest in taking advantage of the structure found in experimental systems.
Research Areas
Authored Publications
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Reinforcement Learning Control of Quantum Error Correction
Cameron Maxfield
Guifre Vidal
Bob Buckley
Jonathan Waltz
Christopher Wood
Reza Molavi
John Mark Kreikebaum
Rajeev Acharya
David Sobel
Abeer Vaishnav
Ali Hadjikhani
Ryuho Kudo
Wendy Leung
Brett Buchea
Ningfeng Zhu
Shirin Montazeri
Jamie Yao
Bicheng Ying
Eric Mascot
Lenny Fuste
Zhenjie Zou
Rodrigo Cortinas
Matt Lloyd
Clarke Smith
Kris Ottosson
Emma Ropes
Felix Borjans
Rebecca Potter
Sean Harrington
Jeremy Hilton
David Enriquez
Stephen Heslin
Paula Heu
Daniel Lundahl
Elliot Young
Alex Crook
Fedor Kostritsa
Roberto Rodriguez
Chia Ni
Kim Ming Lau
Priyanka Thiruraman
Martin Damyanov
Logan Oas
Dmitry Abanin
Oscar Higgott
Aaron Shorter
Steve Habegger
Aniket Maiti
Ryan Kaufman
Valerie Ehimhen
Sayra Alcaraz
Marcos Flores
Elizabeth Rossi
Aria Shahingohar
Dario Rosenstock
Travis Weidel
Steven Waltman
Kristi Wong
Murat Sarihan
Arun Kumar
Vladimir Shvarts
Matt Reagor
Alfredo Torres
Michael Qian
Anthony Megrant
Charles Neill
Christopher Hudspeth
Michael Hamilton
Bill Huggins
Laura De Lorenzo
Tan Ha
Ran Zhang
Dar Gilboa
Nicholas Bushnell
Sherman Peek
David Rhodes
Leigh Martin
Mike Shearn
Vlad Kurilovich
David Browne
Spencer Small
Brian Ballard
Will Oliver
Lior Ella
Orion Pritchard
Josh Cogan
Rachel Resnick
Dmitri Maslov
Jose Guerrero
Paul Masih Das
Theodore White
Helge Gehring
Nikita Astrakhantsev
Can Knaut
Maddy Woodson
Brooks Foxen
Frank Arute
Alejo Grajales Dau
Yaxing Zhang
Aaron Szasz
Alexander Lill
Justin Ledford
Xiaoxuan Jin
Andreas Kabel
Sid Madhuk
Orion Martin
Catherine Vollgraff Heidweiller
Gabrielle Roberts
Juan Campero
Juhwan Yoo
Robert Salazar
Michael Newman
Arpit Ranadive
James Goeders
William Giang
Gonzalo Garcia
Agnetta Cleland
Maddie Taylor
Dogan Timucin
Ross Alcaraz
Hui Kang
Johannes Bausch
William Courtney
Robert Gasca
Kevin Satzinger
Meghan Voorhees
Silas Chen
Laleh Beni
Andrew Dunsworth
Jamal Busnaina
Pavel Laptev
Kiseo Kang
Shannon Wang
Paul Donohoe
Paul Conner
Vadim Smelyanskiy
James Spencer
Benjamin Chiaro
Grayson Young
Tim Burger
ILYA Drozdov
Peter Brooks
Jordan Suchard
Austin Fowler
Jimmy Chen
Alec Eickbusch
Francisco Heras
Hung-Shen Chang
Michael Broughton
Jeanne Hartshorn
Aviv Elbag
Martin Bigdeli
Tanner Hadick
Juan Atalaya
Mahmoud Elzouka
Melvin Mathews
Alex Sztein
Markus Ansmann
Pavol Juhas
Bryan Cochrane
Murray Ich Nguyen
Ashley Maloney
Will Livingston
Roberto Collins
Ming Li
Élie Genois
Jeremiah Ford
Christopher Garrick
Sayan Das
David Peterson
Eifu Tomita
Suhas Ganjam
Reno Hiltermann
Dylan Bowers
Bryce Kobrin
Yu Chen
Dan Riley
Leon Brill
Barrett Spells
Ben Curtin
Mike Hucka
Seneca Meeks
Sebastian Molina
Tiano Lange-Dei
Georg Aigeldinger
Ashley Huff
Wing Li
ZLATKO MINEV
Monica Hansen
Sebastian Schroeder
Walt Askew
Dietrich Graumann
Elias Portoles
Stijn de Graaf
Matt Cockrell
Harold Cook
Masaya Fukami
Ed Gonzales
Robert Geiger
Amir Karamlou
Loick Le Guevel
Ebrahim Forati
Justin Vargas
Doug Thor
Joel Grebel
Lucia De Rose
LILY LI
Dave Landhuis
Emma Rosenfeld
Hsin-Yuan (Robert) Huang
Kenny Lee
Shaun Jevons
Ping Yeh
Amira Abbas
Kunal Arya
Henry Schurkus
Hector Bates
Ganesh Ramachandran
Sergey Vdovichev
Brayden Ware
Max Schaefer
Cheng Xing
Brandon Langley
Anthony Cabrera
Michel Devoret
Cody Jones
Vlad Sivak
Mert Torunbalci
Ben Kueffler
Chaitali Joshi
Raja Gosula
Joy Lee
Alexander Korotkov
Thomas Edlich
Aditya Locharla
Nathan Lacroix
George Sterling
Hao Tran
Kostyantyn Kechedzhi
Trond Andersen
Alexandre Bourassa
Aaron Lunt
Alan Fung
Alex Pizzuto
Salvatore Mandra
Alex Greene
Vitali Kutsko
Kannan Sankaragomathi
Sofia Springer
Vinicius Ferreira
Raymond Orosco
Nature (2026)
Preview abstract
The promise of fault-tolerant quantum computing is challenged by environmental drift that relentlessly degrades the quality of quantum operations. The contemporary solution, halting the entire quantum computation for recalibration, is unsustainable for the long runtimes of the future algorithms \cite{reiher2017elucidating,gidney2025factor}. We address this challenge by unifying calibration with computation, granting the quantum error correction process \cite{ryan2021realization,krinner2022realizing,sivak2023real,acharya2024quantum, bluvstein2024logical,bluvstein2025architectural,lacroix2025scaling} a dual role: its error detection events are not only used to correct the logical quantum state, but are also repurposed as a learning signal, teaching a reinforcement learning (RL) agent \cite{silver2017mastering,mnih2015human,levine2016end, shalev2016safe,ouyang2022training} to continuously steer the physical control parameters and stabilize the quantum system during the computation. We experimentally demonstrate this framework on a Willow superconducting processor, improving the logical stability of the surface code 3.5-fold against injected drift. By synthesizing our full suite of technological advances, including RL fine-tuning of the entire system and near-optimal decoding \cite{senior2025scalable, beni2025tesseract}, we achieve record performance of the surface and color codes, with average logical error per cycle of $\varepsilon_L=7.7\times10^{-4}$ and $\varepsilon_L=8.2\times10^{-3}$ respectively. Simulations of surface codes up to distance-15 with tens of thousands control parameters confirm the scalability of our RL framework, revealing an optimization speed that is independent of the system size. This work thus enables a new paradigm: a quantum computer that learns to self-improve directly from its errors and never stops computing.
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Diamond Circuits for Surface Codes
arXiv (2025)
Preview abstract
This short paper describes a new circuit to measure surface codes, which allows them to be implemented on the heavy-square lattice. The circuits perform far worse than the usual surface code, but are more efficient in terms of the distance they can achieve for a given number of qubits and couplers.
Paper Abstract:
We present and benchmark an interesting subfamily of circuits within the LUCI framework, which we refer to as diamond circuits, that implement a surface code on a Lieb or “Heavy-Square” lattice. This makes them more qubit- and measurement-efficient than previous constructions. These circuits are built around a mid-cycle state that resembles a Bravyi-Bacon-Shor surface code on the data and measurement qubits. These circuits preserve the spacelike distance of the code, but suffer a penalty in timelike distance. This could be useful in regimes where quantum computers are limited by the number of control lines or frequency collisions.
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Characterizing coherent errors using matrix-element amplification
Élie Genois
Yaxing Zhang
Wojtek Mruczkiewicz
Ze-Pei Cian
npj Quantum Inf (2024)
Preview abstract
Precision quantum estimation in the presence of noise remains a serious practical challenge for calibrating state-of-the-art quantum processors. Noise processes, such as flux noise in superconducting qubits, introduce fluctuations that obscure the true values of system parameters and hinder coherent amplification. We demonstrate a novel characterization technique that enables precise estimation of select unitary parameters for two-qubit gates by applying dynamical decoupling to suppress low-frequency noise. Our method exhibits order-of-magnitude improvements in parameter precision, is efficient in the number of experiments required, adapts to a variety of target two-qubit gates, and is robust to implementation imperfections.
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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
Charles Neill
Rajeev Acharya
Richard Ross Allen
Kyle Anderson
Markus Ansmann
Frank Arute
Kunal Arya
Abe Asfaw
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
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
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
Aditya Locharla
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
Kevin Satzinger
Henry Schurkus
Christopher Schuster
Mike Shearn
Aaron Shorter
Vladimir Shvarts
Vlad Sivak
Jindra Skruzny
Clarke Smith
Rolando Somma
George Sterling
Doug Strain
Marco Szalay
Doug Thor
Alfredo Torres
Guifre Vidal
Catherine Vollgraff Heidweiller
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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Characterizing quantum operations with Matrix-Element Amplification using Dynamical Decoupling
Wojtek Mruczkiewicz
Yaxing Zhang
Ze-Pei Cian
Élie Genois
npj Quantum Information (2024)
Preview abstract
Repeating a gate sequence multiple times amplifies systematic errors coherently, making it a useful tool for characterizing quantum gates. However, the precision of such an approach is limited by low-frequency noise, while its efficiency is hindered by time-consuming scans required to match up the phases of the off-diagonal matrix elements being amplified. Here, we overcome both challenges by interleaving the gate of interest with dynamical decoupling sequences in a protocol we call Matrix-Element Amplification using Dynamical Decoupling (MEADD). Using frequency-tunable superconducting qubits from a Google Sycamore quantum processor, we experimentally demonstrate that MEADD surpasses the accuracy and precision of existing characterization protocols for estimating systematic errors in single- and two-qubit gates. We use MEADD to estimate coherent parameters of CZ gates with 5 to 10 times the precision of existing methods and to characterize previously undetectable coherent crosstalk, reaching a precision below one milliradian.
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Purification-Based Quantum Error Mitigation of Pair-Correlated Electron Simulations
Thomas E O'Brien
Gian-Luca R. Anselmetti
Fotios Gkritsis
Vincent Elfving
Stefano Polla
William J. Huggins
Oumarou Oumarou
Kostyantyn Kechedzhi
Dmitry Abanin
Rajeev Acharya
Igor Aleiner
Richard Ross Allen
Trond Ikdahl Andersen
Kyle Anderson
Markus Ansmann
Frank Carlton Arute
Kunal Arya
Juan Atalaya
Michael Blythe Broughton
Bob Benjamin Buckley
Alexandre Bourassa
Leon Brill
Tim Burger
Nicholas Bushnell
Jimmy Chen
Yu Chen
Benjamin Chiaro
Desmond Chun Fung Chik
Josh Godfrey Cogan
Roberto Collins
Paul Conner
William Courtney
Alex Crook
Ben Curtin
Ilya Drozdov
Andrew Dunsworth
Daniel Eppens
Lara Faoro
Edward Farhi
Reza Fatemi
Ebrahim Forati
Austin Fowler
Brooks Riley Foxen
William Giang
Dar Gilboa
Alejandro Grajales Dau
Steve Habegger
Michael C. Hamilton
Sean Harrington
Catherine Vollgraff Heidweiller
Jeremy Patterson Hilton
Markus Rudolf Hoffmann
Trent Huang
Ashley Anne Huff
Sergei Isakov
Justin Thomas Iveland
Cody Jones
Pavol Juhas
Marika Kieferova
Andrey Klots
Alexander Korotkov
Fedor Kostritsa
John Mark Kreikebaum
Dave Landhuis
Pavel Laptev
Kim Ming Lau
Lily MeeKit Laws
Joonho Lee
Kenny Lee
Alexander T. Lill
Wayne Liu
Aditya Locharla
Orion Martin
Trevor Johnathan Mccourt
Anthony Megrant
Xiao Mi
Masoud Mohseni
Shirin Montazeri
Ramis Movassagh
Wojtek Mruczkiewicz
Charles Neill
Ani Nersisyan
Michael Newman
Jiun How Ng
Murray Nguyen
Alex Opremcak
Andre Gregory Petukhov
Rebecca Potter
Kannan Aryaperumal Sankaragomathi
Kevin Satzinger
Christopher Schuster
Mike Shearn
Aaron Shorter
Vladimir Shvarts
Jindra Skruzny
Vadim Smelyanskiy
Clarke Smith
Rolando Diego Somma
Doug Strain
Marco Szalay
Alfredo Torres
Guifre Vidal
Jamie Yao
Ping Yeh
Juhwan Yoo
Grayson Robert Young
Yaxing Zhang
Ningfeng Zhu
Christian Gogolin
Nature Physics (2023)
Preview abstract
An important measure of the development of quantum computing platforms has been the simulation of increasingly complex physical systems. Prior to fault-tolerant quantum computing, robust error mitigation strategies are necessary to continue this growth. Here, we study physical simulation within the seniority-zero electron pairing subspace, which affords both a computational stepping stone to a fully correlated model, and an opportunity to validate recently introduced ``purification-based'' error-mitigation strategies. We compare the performance of error mitigation based on doubling quantum resources in time (echo verification) or in space (virtual distillation), on up to 20 qubits of a superconducting qubit quantum processor. We observe a reduction of error by one to two orders of magnitude below less sophisticated techniques (e.g. post-selection); the gain from error mitigation is seen to increase with the system size. Employing these error mitigation strategies enables the implementation of the largest variational algorithm for a correlated chemistry system to-date. Extrapolating performance from these results allows us to estimate minimum requirements for a beyond-classical simulation of electronic structure. We find that, despite the impressive gains from purification-based error mitigation, significant hardware improvements will be required for classically intractable variational chemistry simulations.
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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
Abe Asfaw
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
ILYA Drozdov
Andrew Dunsworth
Daniel Eppens
Edward Farhi
Reza Fatemi
Vinicius Ferreira
Ebrahim Forati
Austin Fowler
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
Aditya Locharla
Orion Martin
Amanda Mieszala
Shirin Montazeri
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
Kevin Satzinger
Henry Schurkus
Christopher Schuster
Mike Shearn
Aaron Shorter
Vladimir Shvarts
Jindra Skruzny
Clarke Smith
Rolando Somma
George Sterling
Doug Strain
Marco Szalay
Alfredo Torres
Guifre Vidal
Catherine Vollgraff Heidweiller
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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Suppressing quantum errors by scaling a surface code logical qubit
Abe Asfaw
Anthony Megrant
Cody Jones
Jeremy Hilton
Jimmy Chen
Juan Atalaya
Kenny Lee
Kevin Satzinger
Michael Newman
Vadim Smelyanskiy
Yu Chen
Catherine Vollgraff Heidweiller
Nature (2023)
Preview abstract
Practical quantum computing will require error rates that are well below what is achievable with
physical qubits. Quantum error correction [1, 2] offers a path to algorithmically-relevant error rates
by encoding logical qubits within many physical qubits, where increasing the number of physical
qubits enhances protection against physical errors. However, introducing more qubits also increases
the number of error sources, so the density of errors must be sufficiently low in order for logical
performance to improve with increasing code size. Here, we report the measurement of logical qubit
performance scaling across multiple code sizes, and demonstrate that our system of superconducting
qubits has sufficient performance to overcome the additional errors from increasing qubit number.
We find our distance-5 surface code logical qubit modestly outperforms an ensemble of distance-3
logical qubits on average, both in terms of logical error probability over 25 cycles and logical error
per cycle (2.914%±0.016% compared to 3.028%±0.023%). To investigate damaging, low-probability
error sources, we run a distance-25 repetition code and observe a 1.7 × 10−6 logical error per round
floor set by a single high-energy event (1.6 × 10−7 when excluding this event). We are able to
accurately model our experiment, and from this model we can extract error budgets that highlight
the biggest challenges for future systems. These results mark the first experimental demonstration
where quantum error correction begins to improve performance with increasing qubit number, and
illuminate the path to reaching the logical error rates required for computation.
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Noise-resilient Majorana Edge Modes on a Chain of Superconducting Qubits
Abe Asfaw
Aditya Locharla
Alejandro Grajales Dau
Alex Crook
Alex Opremcak
Alexa Rubinov
Alexander Korotkov
Alexandre Bourassa
Alexei Kitaev
Andre Gregory Petukhov
Andrew Dunsworth
Andrey Klots
Anthony Megrant
Ashley Anne Huff
Austin Fowler
Benjamin Chiaro
Bernardo Meurer Costa
Bob Benjamin Buckley
Brooks Foxen
Catherine Vollgraff Heidweiller
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
Kevin Satzinger
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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