摩根士丹利-再探量子计算 Quantum Computing Revisited 29 SEPTEMBER 2026

Quantum

ComputingRevisited

ErrorCorrectionChangestheProblem

EDGE|COUNTERPOINTGLOBALTEAM|September2026

QuantumComputing:ThenandNow

Sixyearsago,wearguedthatquantumcomputingwas

approachingthetransitionfromscientifictheorytoward

commercialreality.Sincethen,thefieldhasmademeaningful

progress,althoughsignificantchallengesremain.Most

importantly,researchershavedemonstratedacriticalprincipleofquantumerrorcorrection:undertherightconditions,addingmorephysicalqubitscanmakequantuminformationmore

reliableratherthanless.1,2Thatdevelopmentchangesthenatureoftheproblem.Thecentralquestionisincreasinglyshifting

fromwhetherfault-tolerantquantumcomputingisscientificallypossibletohowquicklyitcanbeengineeredandscaled—andwhenitmightbeginsolvingeconomicallyvaluableproblems.

FromPhysicaltoLogicalQubits

Aclassicalcomputerstoresinformationinbitsthattakeavalueofeither0or1.Quantumcomputersusequbits,whichexploitthepropertiesofquantummechanicstorepresentandmanipulateinformationdifferently.Addingqubitsrapidlyexpandsthemathematicalstatespaceaquantumcomputercan

represent,butusefulcomputingpowerdependsonmorethanqubitcount.It

alsorequiresaccuracy,speed,connectivity,and,critically,errorcorrection.1Thatiswhytheindustryisshiftingitsattentionfromphysicalqubitsto

logicalqubits.Physicalqubitsaretheindividualhardwarecomponentsandareinherentlynoisy.Alogicalqubitspreadsquantuminformationacross

multiplephysicalqubitssothesystemcandetectandcorrecterrorswithoutdestroyingtheinformationbeingprotected.2

1CounterpointGlobal,“QuantumComputing,”CounterpointGlobalInsights,October2020.Theoriginalpaperdescribedquantumcomputingasapproachingcommercialrealityandidentifiederrorcorrectionandscalingascentralchallenges.

2GoogleQuantumAIandCollaborators,“QuantumErrorCorrectionBelowtheSurfaceCodeThreshold,”Nature638,920–926(2025),DOI:10.1038/s41586-024-08449-y.

COUNTERPONTGOBAl

WELCOMETOTHEEDGE.

MorganStanleyInvestment

Management’sCounterpoint

Globalsharestheirproprietary

viewsonabigideathathasthe

potentialtotriggerfar-reaching

consequences—ideassuchas

blockchain,autonomousvehicles,machinelearningandgeneediting.CounterpointGlobal’slong-termownershipmindsetemphasizes

perspective,insightandthinkingacrosscategories,whileour

investmentprocessfocusesonidentifyinguniquecompanies

withsustainablecompetitive

advantages.ThroughTheEDGE,weshareourframeworkfor

thinkingaboutchangeandourprocessforrecognizingpatternsthatmaydrasticallyalterthe

investmentlandscapeoverthelongerterm.

Thisworkcomplements

ourteam’smoretraditional,

fundamentalresearchtocreateaframeworkforlong-term

investingthatisgroundedinintellectualcuriosityandflexibility,perspective,self-awarenessandpartnership.

Asimpleanalogyisstoringan

importantrecordinseverallocationsandcontinuallycheckingthecopies.Onecomponentmayfail,butthe

groupcanpreservetheunderlyinginformation.Physical-qubitcountsdescribethesizeofamachine.

Logicalqubitsbegintodescribehowmuchreliableworkitmayeventuallyperform.

ErrorCorrectionChangestheProblem

Quantumerrorcorrectionisnot

new.Whatremainedunprovenonaquantumprocessorwasthescalingbehaviorrequiredforapractical

computer:whetheraddingmore

physicalqubitstoanerror-correctingcodecouldproducealowerlogicalerrorrate.

Google’sWillowprocessorprovidedanimportantdemonstration.Googlebuiltprogressivelylargererror-correcting

logicalqubitsandfoundthatreliabilityimprovedastheamountoferror

correctionincreased.Initslargest

test,thelogicalmemorypreserved

informationlongerthanitsbest

constituentphysicalqubit,andGoogledemonstratedreal-timedecoding

acrossasmanyasonemillionerror-correctioncycles.

2

Thisisknownasoperatingbelow

threshold.Abovethethreshold,

additionalhardwareintroducesmoreerrorsthantheredundancycan

correct.Belowit,makingtheerror-

correctingcodelargercanmakethelogicalqubitincreasinglyreliable.Thatisthescalingpropertyfault-tolerantquantumcomputingrequires.

Thepatternisnotlimitedtoone

architecture.Infleqtionhasdemonstratedfault-tolerantoperationsonlogical

qubitsusingneutralatoms,whilea

MicrosoftandQuantinuumexperimentontrapped-ionhardwarereported

largeimprovementsinlogicalerror

ratesusingcombinationsofcorrectionanddetection.

3

,4Theseexperiments

usedifferenthardware,codes,and

metrics,sotheirresultsarenotdirectlycomparable.Thebroaderpointismoreimportant:logicalperformancehas

beguntoexceedphysicalperformanceacrossmultiplesystems.

Logicalqubitcounthelpsdeterminehowmuchinformationamachinecanprocess;logicalerrorratehelpsdeterminehowlongitcankeepcalculatingbeforean

uncorrectederrorspoilstheresult.Ausefulquantumcomputerneedsboth

3WooChangChungetal.,“Fault-TolerantOperationandMaterialsSciencewithNeutralAtomLogicalQubits,”npjQuantumInformation11,193(2025),DOI:10.1038/s41534-025-01095-w.

4AdamPaetznicketal.,“ImprovedQuantumProcessorLogicalErrorRatesviaCorrectionandDetection,”Nature654,349–355(2026),DOI:10.1038/s41586-026-10628-y.

2MORGANSTANLEYINVESTMENTMANAGEMENT|COUNTERPOINTGLOBAL

enoughlogicalqubitstorepresentanimportantproblemandsufficientlylowerrorratestofinishsolvingit.Companyroadmapsincreasinglyframeprogressinthosetermsratherthanphysical-qubitcountsalone.5

Q-DayMovesintothePlanningHorizon

Oneofthebest-understoodapplicationsofquantumcomputingisbreakingpublic-keycryptography.PeterShorshowed

thatasufficientlycapablequantum

computercouldfactorlargeintegersfarmoreefficientlythanknownclassical

methods,potentiallyunderminingRSAandrelatedcryptographicsystems.6

In2020,wewrotethataperfectly

functioningquantumcomputerwith

roughly4,100qubitscouldtheoreticallybreakRSA-2048.Thosewere

effectivelyperfectlogicalqubits,not

today’snoisyphysicalqubits.1A2021

studyestimatedthatthecalculation

couldrequire20millionnoisyphysicalqubitsunderspecifiedassumptions;

a2025GoogleQuantumAIpreprint

reducedtheestimatetofewerthanonemillion,largelythroughimprovementsinalgorithms,arithmetic,logical-qubitstorage,anderrorcorrection.7,8

Thedayonwhichaquantum

computercanbreakwidelyused

public-keycryptographyiscommonlycalledQ-Day.Itstimingremains

uncertain,butthethreathasmoved

intoinstitutionalplanninghorizons.Googlehasset2029asthedeadlineforcompletingitsmigrationto

post-quantumcryptography,while

NISTfinalizeditsfirstprincipalpost-quantumcryptographystandardsin2024andsaysorganizationsshouldbeginapplyingthemnow.9,10“Storenow,decryptlater”attacksmaketheissuerelevantbeforeQ-Daybecauseintercepteddatamayremainvaluablelongenoughtobedecryptedbya

futuremachine.9

WhyIt’sDisruptive

Cryptographyisthebest-understoodapplicationofquantumcomputing,

butpotentiallynotthemostvaluable.Thelargercaserestsonsimulation.Quantumsystemsnaturallyrepresentotherquantumsystems,creatingthepossibilityofmodelingmolecules

andmaterialsthatbecomeextremelydifficultforclassicalcomputers.

Ouroriginalpaperhighlighted

catalysts,batteries,pharmaceuticals,solarmaterials,fertilizers,and

superconductorsascandidates.1

Earlyevidencepointsinthatdirectionwithoutyetestablishingcommercialusefulness.Infleqtionusedtwologicalqubitsinaprototypematerials-

sciencecalculation.3Google’s

“QuantumEchoes”experimentranasetofcircuitsroughly13,000timesfasterthanitsestimateforthebest

classicalalgorithmontheFrontier

supercomputer,andacompanion

experimentappliedthemethodto

molecular-structureanalysis.11Neitherresultrepresentsacommercial

application,andneitherisyeta

demonstrationofeconomicvalue.

Optimization,finance,andmachinelearningaremorecontingent

becauseanyadvantagemust

survivedatapreparation,repeated

sampling,verification,andcontinuingimprovementinclassicalmethods.

Arealisticpathtocommercialvaluemaythereforebenarrow:aquantumprocessorneednotreplaceanentireworkflowifitcanaccelerateone

economicallyconsequentialstepthatclassicalsystemshandlepoorly.

TheQuantum-ClassicalModel

Quantumcomputersareunlikelyto

replaceclassicalcomputers.Theyaremorelikelytofunctionasspecializedacceleratorsinsideclassicalcomputingenvironments.Aquantumprocessingunit,orQPU,mayperformtheportionofacalculationforwhichquantum

mechanicsprovidesanadvantage,

whileCPUsandGPUspreparedata,controlthehardware,decodeerror

signals,andcompletetheworkbeforeandafterthequantumcalculation.

Large-scaleerrorcorrectionmay

itselfrequiresubstantiallow-latencyclassicalcomputing.12

5IonQ,“Industry-LeadingRoadmap,”companytechnologyroadmap,accessedAugust27,2026.

6PeterW.Shor,“Polynomial-TimeAlgorithmsforPrimeFactorizationandDiscreteLogarithmsonaQuantumComputer,”SIAMJournalonComputing26,no.5(1997):1484–1509,DOI:10.1137/S0097539795293172.OriginallypresentedatFOCS1994.

7CraigGidneyandMartinEkerå,“HowtoFactor2048-BitRSAIntegersin8HoursUsing20MillionNoisyQubits,”Quantum5,433(2021),DOI:10.22331/q-2021-04-15-433.

8CraigGidney,“HowtoFactor2048-BitRSAIntegerswithLessThanaMillionNoisyQubits,”arXiv:2505.15917(2025).Preprint;notpeerreviewed.

9HeatherAdkinsandSophieSchmieg,“Google’sTimelineforPQCMigration,”Google,March25,2026;KentWalkerandHartmutNeven,“TheQuantumEraIsComing.AreWeReadytoSecureIt?”Google,February6,2026;bothaccessedAugust29,2026.

10NationalInstituteofStandardsandTechnology,“Post-QuantumCryptography,”includingthe2024publicationofFIPS203,FIPS204,andFIPS205andthetransitionframeworkdescribedinNISTIR8547,accessedAugust29,2026.

11GoogleQuantumAIandCollaborators,“ObservationofConstructiveInterferenceattheEdgeofQuantumErgodicity,”Nature646,825–830(2025),DOI:10.1038/s41586-025-09526-6;“QuantumComputationofMolecularGeometryviaMany-BodyNuclearSpinEchoes,”arXiv:2510.19550(2025),

preprint;GoogleQuantumAI,“AVerifiableQuantumAdvantage,”October22,2025,accessedAugust29,2026.The13,000-timesfigureisGoogle’sestimateoftheclassicalcost.

12NVIDIA,“NVIDIAIntroducesNVQLink,ConnectingQuantumandGPUComputing,”October2025,accessedAugust29,2026;“PlatformArchitectureforTightCouplingofHigh-PerformanceComputingwithQuantumProcessors,”arXiv:2510.25213(2025),preprint.

COUNTERPOINTGLOBAL|MORGANSTANLEYINVESTMENTMANAGEMENT3

Thismodelbroadenstheecosystem.

Usefulsystemswillrequirenotonly

quantumprocessorsbutalsocontrol

electronics,cryogenicsorphotonics

dependingonthearchitecture,software,networking,real-timedecoding,

andconventionalhigh-performance

computing.TheQPUmaytherefore

enterthedatacenterasanadditionalprocessoroptimizedforadistinctclassofproblems,muchastheGPUdid.12

CompetingArchitectures

Thereisstillnostandardizedquantumequivalentofthetransistor.Several

architecturesareadvancinginparallel,eachwithdifferentstrengthsand

engineeringchallenges.Thecomparisonbelowisintentionallysimplified;

performancedependsonthespecificimplementationandcontinuesto

changequickly.1,13

WhatThisMeansforInvestors

Forinvestors,thekeyquestionis

shiftingfromwhetherquantum

mechanicscansupportscalable

computationtowhensufficiently

reliablesystemswillsolve

economicallyvaluableproblems,which

architectureswilldoso,andwhereintheecosystemtheresultingvaluewillaccrue.

Theeventualwinnersmaynotbe

limitedtothecompaniesbuilding

quantumprocessors.Thequantum-classicalmodelcreatespotential

opportunitiesacrosscontrol

electronics,photonics,cryogenics,

software,networking,real-time

decoding,andhigh-performance

computing—evenbeforebroadly

usefulfault-tolerantsystemsarrive.12

Webelievethreeindicatorsdeserve

particularattention:thenumber

ofreliablelogicalqubits,the

logicalerrorrate,andevidenceof

economicallyusefuladvantageoverclassicalalternatives.Thefirsttwo

measurewhetherthetechnologyis

becomingtechnicallycapable;thethirdwilldeterminewhetherthatcapabilitycreatescommercialvalue.

Architectureremainsanimportant

uncertainty.DARPAisexplicitly

evaluatingmultipleapproachesinits

QuantumBenchmarkingInitiativeratherthanassumingasinglewinner.14For

investors,thatarguesforfocusinglessonheadlinephysical-qubitcountsandmoreondemonstratedlogicalperformance,

scalability,systemeconomics,andevidenceofusefulapplications.

ReasonsforCaution

Thehistoryofquantumcomputing

rewardscaution.Google’s2019

Sycamoreexperimentwaspresentedasacalculationthatwouldtakeaclassicalsupercomputer10,000years;three

yearslater,researchersgeneratedonemillionuncorrelatedsamplesfrom

thesamecircuitinroughly15hours

on512GPUs.15Classicalmethodshaveimprovedinresponsetonearlyeveryquantum-advantageclaimsofar.

Theerror-correctionresultsare

alsonarrowerthantheheadlines

cansuggest.Willowdemonstrated

below-thresholdscalingforaquantummemoryratherthanalargesetof

logicalgates,whichistheharder

problem.2Thebestdemonstrationsremainfarbelowroadmapscallingforthousandsoflogicalqubitsandcryptographicestimatesontheorderofamillionphysicalqubits.4,5,8

APPROACH

BASICIDEA

POTENTIALADVANTAGE

KEYCHALLENGE

Superconducting

Artificialcircuitscoolednear

Fastoperations;leverageschip-fabrication

Shorter-livedquantumstates,error

absolutezero

techniques

correction,andcryogenicscaling

Trappedions

Chargedatomsheldin

High-fidelityoperationsandnaturally

Sloweroperationsandengineeringlarge

electromagnetictraps

uniformqubits

interconnectedsystems

Neutralatoms

Unchargedatomspositionedand

Large,reconfigurablearraysand

Controlfidelity,atomloss,andfault-

controlledwithlasers

longcoherence

tolerantscaling

Photonic

Quantuminformationencodedin

Networking,connectivity,andpotential

Photonlossandresourceoverheadfor

particlesoflight

modularity

errorcorrection

Siliconspins

Electronornuclearspinscontrolledin

Potentialcompatibilitywith

Uniformfabrication,control,andscaling

semiconductordevices

semiconductormanufacturing

beyondsmalldevices

Sources:NIST;NatureElectronics;NatureMaterials;DARPA.13

13NationalInstituteofStandardsandTechnology,“QuantumComputingExplained,”accessedSeptember3,2026;NatureElectronics,“Bettingon

Qubits,”2025;NatureMaterials,“ThePhotonicPathtoQuantumAdvantage,”November26,2025;NatureMaterials,“TweezerArraysAdvanceQuantumComputing,”November21,2025;DefenseAdvancedResearchProjectsAgency,QuantumBenchmarkingInitiativematerials.Thesesourcesdescribetheprincipalhardwareapproachesandtheirbroadengineeringtradeoffs.

14DefenseAdvancedResearchProjectsAgency,“QuantumBenchmarkingInitiative”;“QuantumBenchmarkingInitiativeExpandsQuesttoSeparateHypefromReality,”March10,2026;StageBselectionmaterials,accessedSeptember3,2026.

15FrankAruteetal.,“QuantumSupremacyUsingaProgrammableSuperconductingProcessor,”Nature574,505–510(2019),DOI:10.1038/s41586-

019-1666-5;FengPan,KeyangChen,andPanZhang,“SolvingtheSamplingProblemoftheSycamoreQuantumCircuits,”PhysicalReviewLetters129,090502(2022),DOI:10.1103/PhysRevLett.129.090502.

4MORGANSTANLEYINVESTMENTMANAGEMENT|COUNTERPOINTGLOBAL

COUNTERPOINTGLOBAL|MORGANSTANLEYINVESTMENTMANAGEMENT5

Severalquestionsstillneedtobeanswered:

nCanbelow-thresholderror

suppressioncontinueatmuchlargercodesizesandacrosslogicalgates?

nCanlogical-errormetricsbecomecomparableenoughtoevaluatevendorsonacommonbasis?

nWhichapplicationsjustifythefullcostofthequantumandclassical

infrastructurerequiredtorunthem?

nWillonearchitecturedominate,orwillthemarketsupportseveral

specializedapproaches?

Conclusion

Thecasethatquantumcomputingcouldbecomeafoundational

technologyisstrongerthanitwasin2020.Thebiggestchangeiserrorcorrection.Researchershavenowdemonstratedthescalingbehavioronwhichfault-tolerantquantum

computingdepends:undertherightconditions,aquantumsystemcanbecomemorereliableasitserror-correctingcodebecomeslarger.2

Thatresultdoesnotcompletethepathtoausefulquantumcomputer,butitchangesthenatureofthechallenge.

Acentralscientificpropositionis

increasinglybecominganengineeringandsystemsproblem.Logicalerror

rateswillhelpdeterminehow

quicklytheindustryprogressesfromshortexperimentstodeep,useful

calculations.Decliningestimatesfor

cryptographicworkloads,late-decadehardwareroadmaps,andtheglobal

transitiontopost-quantumsecurity

suggestthatquantumcomputing

isenteringamoreconsequential

phase—evenasthetiming,winning

architectures,andultimatecommercialapplicationsremainuncertain.

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