QUANTUM FRONTIERSREPORT ON COMMUNITY INPUT TO THE NATION'SSTRATEGY FOR QUANTUM INFORMATION SCIENCE

Product of

THE WHITE HOUSE
NATIONAL QUANTUM COORDINATION OFFICE

October 2020
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QUANTUM FRONTIERSINTRODUCTION
Under the Trump Administration, the United States has made American leadership in quantum
information science (QIS) a critical priority for ensuring our Nation’s long-term economic prosperity andnational security. Harnessing the novel properties of quantum physics has the potential to yieldtransformative new technologies, such as quantum computers, quantum sensors, and quantum
networks.
The United States has taken significant action to strengthen Federal investments in QIS research anddevelopment (R&D) and prepare a quantum-ready workforce. In 2018, the White House Office of Scienceand Technology Policy (OSTP) released the National Strategic Overview for Quantum Information
Science, the U.S. national strategy for leadership in QIS. Following the strategy, President Trump signed
the bipartisan National Quantum Initiative Act into law, which bolstered R&D spending and establishedthe National Quantum Coordination Office (NQCO) to increase the coordination of quantum policy andinvestments across the Federal Government.
Building upon these efforts, the Quantum Frontiers Report on Community Input to the Nation’s Strategy
for Quantum Information Science outlines eight frontiers that contain core problems with fundamental
questions confronting QIS today:•

Expanding Opportunities for Quantum Technologies to Benefit Society•

Building the Discipline of Quantum Engineering•

Targeting Materials Science for Quantum Technologies•

Exploring Quantum Mechanics through Quantum Simulations•

Harnessing Quantum Information Technology for Precision Measurements•

Generating and Distributing Quantum Entanglement for New Applications•

Characterizing and Mitigating Quantum Errors•

Understanding the Universe through Quantum Information

These frontier areas, identified by the QIS research community, are priorities for the government,
private sector, and academia to explore in order to drive breakthrough R&D.
As background for this report, Federal agencies on the National Science and Technology Council
Subcommittee on QIS have engaged with the QIS research community through public requests for
information (RFI) [1] and through a series of QIS workshops, roundtables, and technical studies led byexperts and stakeholders in the QIS R&D community. The NQCO analyzed the RFI responses andworkshop readouts and found several recurring themes. This report summarizes and organizes thecommunity input in order to focus the Nation’s QIS research, academic, private sector, and Federal
Government leaders on frontiers where key questions must be answered to enable the full potential of
QIS. The Trump Administration remains committed to maintaining and strengthening America’s QIS
leadership and unleashing the promise of this emerging field to improve the prosperity, security, andwell-being of the American people.

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QUANTUM FRONTIERSQUANTUM FRONTIERS IN BRIEF
1. Expanding Opportunities for Quantum Technologies to Benefit Society
a. Elucidating Fundamental Capabilities of Quantum Technologies
b. Engaging QIS Researchers with Domain Specialists and End-Users
2. Building the Discipline of Quantum Engineeringa. Integrating Quantum Hardware, Software, and Support Technology
b. Exploring System-level Architectures, Abstractions, and Testingc. Enabling Modular Systems
3. Targeting Materials Science for Quantum Technologies
a. Using Materials Science to Improve Device Performanceb. Pursuing New Approaches to Materials Design, Fabrication, and Characterization
4. Exploring Quantum Mechanics through Quantum Simulations
a. Developing Quantum Simulation Applications
b. Implementing Algorithms on Available Devices and Exploring Their Performance
5. Harnessing Quantum Information Technology for Precision Measurements
a. Deploying Quantum Technology for Improved Accuracy and Precisionb. Creating New Modalities and Applications for Quantum Sensing In Situ and In Vivoc. Using Entanglement and Quantum Computers to Improve Measurements
6. Generating and Distributing Quantum Entanglement for New Applications
a. Developing Foundational Components for Quantum Networks
b. Enabling Quantum State Transduction
c. Integrating Quantum Networking Systems
d. Exploring Quantum Networking Algorithms, Applications, Protocols, and Approaches
7. Characterizing and Mitigating Quantum Errors
a. Characterizing and Controlling Multi-qubit Systems
b. Approaching the Fault-tolerant Domainc. Using Current Devices to Expand the Limits of Performance for Qubit Performance
8. Understanding the Universe through Quantum Information
a. Exploring Mathematical Foundations of Computation and Information
b. Expanding the Limits of Physical Theory
c. Testing the Standard Model of Particle Physics–2–

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1. Expanding Opportunities for Quantum Technologies to Benefit Society“[W]hile the Strategic Overview takes a basic research-driven approach, appliedresearch should not be neglected…it is important to accelerate the development of
quantum technology toward usable results. This means balancing pure basic
research with use-inspired research which is more likely to yield usable
technology.” – RFI response

The nature of information technology is governed by the rules of the universe itself, known as quantum
mechanics. This realization helped establish the field of QIS. Presently, new technologies that harness
unique quantum properties of coherence, entanglement, and measurement are emerging fromfundamental advances in QIS. Developing practical, real-world applications for these technologies that
benefit other scientists and end-users in a wide range of disciplines is now an important frontier for
quantum information scientists and technologists. Two major areas of inquiry are key for making
progress along this frontier: discovering what is fundamentally possible with quantum technology,
including practical quantum advantages and a deeper understanding of the classical-quantum tradespace; and engaging interdisciplinary QIS researchers with domain scientists and end-users early on, towork together and identify potential applications for QIS technologies and concepts in government,
industry and other branches of science.

a. Elucidating Fundamental Capabilities of Quantum Technologies
Improving our fundamental understanding of how quantum technologies can provide meaningfuladvantages over conventional classical methods was a recurring theme in RFI responses. This includes:
elucidating where improvements can be gained over existing technologies by utilizing quantum
phenomena to accomplish specific tasks; characterizing entirely new capabilities enabled by quantum
phenomena that have no classical counterparts; and understanding fundamental advantages forquantum metrology and quantum computing that can be derived from quantum networking.
For quantum computing, RFI respondents noted that advances in computational complexity theory
could clarify the classes of problems for which quantum computational advantage is possible inprinciple, paving the way for building more useful quantum algorithms in the long term. In the nearterm, consideration of non-asymptotic regimes (corresponding to problem sizes that could be
addressed by near-term digital quantum computers or simulators) and specific device parameters (e.g.,
actual time requirements for quantum gate operations and auxiliary tasks such as stabilization or errorcorrection protocols) will also be important for such analyses. The development of approaches formathematically evaluating the potential for quantum advantage in analog quantum computation(quantum annealing, adiabatic quantum computation, and quantum emulation) is also an area for
exploration.
“Quantum complexity theory research should be encouraged to understand where
quantum computing has the most value and why. Quantum algorithm researchshould focus on demonstrating incontrovertible quantum advantage on realquantum hardware for classically-intractable practical problems.” – RFI response–3–

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RFI respondents also highlighted the potential value of heuristic approaches for finding applications ofnear-term quantum devices. Direct experimentation with quantum devices could establish what they
are capable of in practice; applications for established quantum capabilities may then be sought.
“The space to be explored in the next 10 years is vast and the first useful
applications of these new technologies may come from actually just trying new
ideas without requiring a long and slow period of developing the appropriate
theoretical foundations.” – RFI response

Members of the research community have also recognized the potential for demonstrating quantum
advantage on noisy, intermediate-scale quantum (NISQ) devices. Near-term quantum computers andquantum emulators could be explored to realize transformative approaches with advantages forworking on problems that can be mapped to a quantum algorithm or to a quantum system forcomputation or simulation. Developing new quantum algorithms suited to NISQ devices, and formal
methods of resource estimation for evaluating their potential for quantum advantage, could facilitate
near-term progress in this frontier.
“Applications for NISQ computing are critical for the future of QIS because, in
addition to the scientific insights they generate, they form the path to the longer
term goal of fault tolerant quantum computation.” – RFI response“What are the NISQ-era algorithms that offer quantum advantage for meaningfulproblems?” – RFI response

b. Engaging QIS Researchers with Domain Specialists and End-Users
The need to identify important real-world tasks for which quantum technologies may offer a promisingsolution was a common theme in the RFI responses. Prospective areas for exploration include
biocompatible quantum sensors for in vivo characterization of biomolecules for diagnostic or research
purposes; QIS-based metrology for environmental or industrial systems monitoring; quantum
computing approaches to classically-hard problems such as modeling of chemical systems relevant todrug discovery or nitrogen fixation, and certain optimization and machine learning tasks; quantum
networks to enable secure communications and blind quantum computation in support of data privacy
and confidentiality; deployment of quantum networking for satellite communications; and further
development and deployment of robust quantum-enabled navigation systems.

“[Identify] key problems that need QIS as a tool for solutions, from modeling andunderstanding complex physical phenomena to optimization problems tocryptography and security; characterizing problems and their quantum
requirements.” – RFI response–4–

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RFI responses also noted that efforts to find meaningful applications for quantum technologies would
be accelerated by connecting QIS scientists and engineers with experts from other domains to explore
potential use cases. This could expedite the timeline for finding new solutions to critical societal
challenges and enable informed technology design strategies from an early stage. Reciprocally, as an
added benefit, this work would provide a new lens through which to advance fundamental QIS bymotivating new experiments, stimulating new hypotheses, and inspiring theoretical advances.
Collaboration and continued discussion across QIS, computing, mathematics, engineering, and otherapplication domains will be needed to reveal what can—and cannot—be accomplished uniquely withquantum technologies, and to achieve this potential in actual devices.
“In a co-design approach, the problems can help drive the design and the engineeringand scientific research while at the same time the scientific and engineering
advances can drive designs to motivate new approaches to solving problems.”– RFI response

An overarching goal for R&D in this frontier is to demonstrate quantum technologies that offer
advantages for practical tasks. How might quantum technologies bring better, cheaper, or neverbefore-possible solutions to other scientists and end-users, and to society at large? Discoveries in thisarea would help to further establish the value proposition of QIS, beyond its role in expanding theboundaries of human knowledge.

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2. Building the Discipline of Quantum Engineering“Quantum engineering should be established as a new discipline or a sub-disciplinein engineering schools which requires developing curricula and textbooks both atundergraduate and graduate levels.” – RFI response“As new quantum information science-based technology (‘quantum technology’ forshort) develops, the U.S. will need a new type of profession that has not previously
existed: the quantum engineer. Quantum engineers will not be—and will not need
to be—specialists in the detailed physics of QIS but will instead be expert in the use
and extended application of the new systems, tools and possibilities enabled by QIS.”– RFI response“One element to U.S. Government engagement with academia on workforce
development should be promoting the development of the field of quantum
engineering, not as classical engineering to support quantum technologies (i.e.
classical control electronics or thermal control systems), but as its own disciplinewhere there are models of abstraction permitting useful engineering of quantum
systems…quantum-engineering-focused research efforts will be required fordeveloping the engineering models that appropriately abstract away the details of
the complex underlying effects, while still allowing academic courses that teachthese models to provide engineers with the appropriate intuition and depth ofunderstanding.” – RFI response

Advances in QIS and technology have led to compelling proof-of-principle experiments with gate-based
and analog quantum computing, and demonstrations of quantum sensing with unprecedented
capabilities and precision. However, many technical and systems-level challenges still remain to be
overcome before today’s quantum control capabilities are considered as standard ingredients forplanning and constructing complex devices. This is especially true for products defined by a broad
range of specifications and practical constraints for real-world applications. The emerging discipline ofquantum engineering may bridge this gap by creating new perspectives on topics ranging fromdesigning and integrating components, to optimizing and verifying functionality, and providing useful
abstractions and heuristics. As illustrated by some RFI responses, these are among the variety ofconcepts currently referred to as quantum engineering. Pathways for progress in this frontier include:
understanding what makes designs scalable and useful; integrating the development of quantum
hardware, software, and support technologies; developing and using system-level architectures; andcreating the new discipline of quantum engineering.

a. Integrating Quantum Hardware, Software, and Support Technology
Physical elements that were identified in several RFI responses and workshop reports as needing to be
characterized, integrated, and optimized by quantum engineers include qubit arrays, refrigeration
devices, electronics, optics such as silicon nitride waveguides and delay lines, single-photon detectors,–6–

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vacuum systems, wiring and feedthroughs, lasers and stabilization components, radiofrequency andmicrowave technologies, and device packaging. Other hardware research areas that RFI responses
suggested may be improved and integrated with an engineering approach are: the development of
quantum memory technologies; efficient methods of quantum state preparation—especially forloading classical data into quantum information storage, processing, or communication devices; andthe transduction of quantum states between heterogeneous components of quantum systems.
On the software and systems side, important research areas identified in RFI responses include
development of modular software designs, methods for mapping computational problems to thespecific hardware configurations of early devices, and exploration of programming languages built
upon hardware-informed semantic models. Major research opportunities include further developmentof system architectures and abstractions and community-acceptable metrics and standards (oncetechnologies have reached the appropriate level of maturity) for use in system validation, verification,and performance benchmarking and to inform technology selection and system optimization for
specific use cases.
“Whether it be in quantum computing, quantum software, or other QIS disciplines,
a hybrid approach that integrates various quantum systems will be important tomake breakthroughs. This means facilitating the combination of the best of various
quantum systems to build new devices, capabilities, and platforms based on multiple
different physical realizations.” – RFI response“Longer term, the use of abstractions to enhance productivity will be needed, once
quantum resources are more plentiful….We must establish the sorts of modularityand layering commonly needed for scalable systems.”– Next Steps in Quantum Computing: Computer Science’s Role (Computing Community
Consortium 2018)b. Exploring System-level Architectures, Abstractions, and Testing
Establishing essential principles of quantum engineering that enable researchers to build and use
quantum systems at various levels of abstraction without having to start from first principles is
considered groundbreaking for QIS R&D. Research community members also suggested that quantum
engineers should work closely with domain experts to pioneer new applications that drive the designand experimental testing of tools, techniques, and architectures, and which could lead to near-term
use cases for quantum technologies, as noted for frontier A.
“[W]e have found the most fruitful work results from programs that enable close
collaborations between quantum engineers and application domain experts.”– RFI response–7–

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c. Enabling Modular Systems
At the hardware level, systems of tens of entangled qubits have been demonstrated experimentally forseveral different qubit types, including superconducting, trapped ion, and photonic as examples
provided in the RFI responses. These experiments illustrate that it is possible to access unique regimes
for quantum information processing. However, as they grow in number, qubit systems generally
become increasingly difficult to prepare, couple, and control, and their inherent complexity makes
them concomitantly more difficult to understand, model, and validate—posing significant challenges
for realizing systems of a larger scale. RFI responses highlighted the need to develop techniques,
protocols, models, and validation approaches to enable heterogeneous, modular, and scalable
designs, fabrication methods, characterization techniques, and packaging of qubit technologies.
“Developing common terminology and metrics will allow researchers in different
groups to communicate more clearly and encourage better exchange of ideas andenable faster progress.” – RFI response“Several QIS areas remain in an early phase of research, where the engineering of acore technology is relatively immature.” – RFI response

Members of the R&D community identified a range of technical challenges that would benefit from theapplication of engineering principles, including: optimizing quantum materials, fabrication, andmanufacturing methods to meet hardware requirements; establishing specifications, parameters, anda common terminology for quantum system design that can be shared across qubit technologies anddisciplines; developing new models of system behavior and efficient emulation techniques forcomparison with actual performance; inter-qubit communication and connectivity; and methods fordebugging systems that do not perform as intended. These methods could enable design anddevelopment of stable, self-contained collections of physical quantum hardware and control systems
that would serve as the basis for a modular approach to system design.
“Focus on how to build quantum computers with a modular architecture. This will
require bringing together [experts] from engineering, as well as system architects
and computer scientists, to think about how to make interfaces and how to scale
those interfaces.” – RFI response

A vision of progress in this frontier is to build a broadly applicable set of quantum engineering
principles, tools, and specifications for designing quantum systems that are stable, sophisticated,compact, and cost-effective enough to be useful and usable in a range of different environments andcontexts. They would also lay the groundwork for designing and deploying large-scale, quantum
computing and communication technologies and infrastructures.

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3. Targeting Materials Science for Quantum Technologies“In applications of quantum computing, qubit quality is inextricably tied to materials
quality, particularly in solid-state platforms. The longer coherence times and lower
error rates needed to advance the aims of error-corrected quantum computing will
come fastest through a full predictive capacity for materials performance, one that isable to guide fabrication well enough to deliver desired QIS characteristics withconsistency and without trial-and-error processes. An improved understanding ofmaterials might also uncover new or better ways to fabricate error-protected qubits,
which if found and made reliably could represent a transformative leap toward
logical-qubit creation.” – RFI response

Quantum information can be coded into different physical systems: ions, atoms molecules, or solidstate materials and superconducting circuits, and photons or phonons—each with its own advantages
and challenges. Coherence in each system generally depends on how the qubits and interconnections
are fabricated and controlled. Fundamental knowledge of the quantum properties of matter can informthe design of high-fidelity qubit systems to minimize the potential for noise and error. Developing andapplying new and precise methods for characterizing and fabricating these physical components
according to engineering specifications will accelerate advances in system development. Key areas ripe
for progress include: using materials science to improve device performance, and pursuing new
approaches to materials design, fabrication, and characterization.
“Research opportunities encompass (1) development of new in situ and in operando
characterization and feedback techniques to discover materials with improved
properties and functionalities; (2) characterization and control of quantum material
properties on all length and time scales relevant to function, including tools to reveal
the often subtle forms of emergent and topological order; and (3) prediction of thefundamental properties of quantum materials, including emergent order, behavior
far from equilibrium, and functionality in the presence of disorder.”– Basic Research Needs Workshop on Quantum Materials for Energy RelevantTechnology (DOE 2016)

a. Using Materials Science to Improve Device Performance
RFI respondents identified key opportunities for communication and collaboration between QIS
researchers and those in fields such as materials science, chemistry, and condensed matter physics toleverage current knowledge and tools for improving the quality and resilience of the materials currently
in demand for building quantum devices. Established theory and experimental techniques from thesefields will aid in the design, characterization, fabrication, and evaluation of improved near-term
devices. Building a robust approach for mapping materials characterization knowledge to estimatedquantum bit and quantum device performance will advance this frontier.

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QUANTUM FRONTIERS“[D]evelop and optimize new advanced materials, including solid-state hosts foratom-like qubits (e.g., diamond and other semiconductors), materials with emergent
properties (analogous to graphene and topological insulators), and materials
developed by learning lessons from evolved (natural) biological and chemicalmaterials.”– Quantum Sensors at the Intersection of Fundamental Science, Quantum Information
Science, & Computing

b. Pursuing New Approaches to Materials Design, Fabrication, and Characterization
Members of the research community noted the opportunity to build on existing knowledge to advancethe theories, tools, and techniques that will enable researchers to explore the fundamental quantum
nature of materials, predict material properties, devise new synthesis and integration processes, andtarget new kinds of materials to outperform those currently in use. Key research pathways include
exploration of artificial intelligence-driven materials science; improved chemical simulation
techniques; 3-D atomic-scale imaging; scanning probe techniques for quantum materials
characterization and quantum device readout; higher-sensitivity magnetic resonance tools; and othernew measurement and modeling capabilities suited to extreme conditions.
“Quantum device coherence times, gate fidelity, and other metrics must be
improved using new materials, processes, designs, and approaches. Goals for device
improvement should be tied to actual system performance needs based on the bestsystem estimates possible.” – RFI response

Researchers noted that progress in realizing topological materials could yield entirely new, inherently
error-protected qubits that are expected to be much more resilient to noise than approaches currently
deployed. This area of exploration will involve substantial challenges in realizing quantum information
primitives in such systems, beyond the initial difficulties of showcasing topological behavior in suchmaterials in the first place. Demonstration of topological protection of quantum information inmaterials remains a wide-open question, with many potential pathways for success.
Opportunities were also highlighted for coupling a deeper understanding of materials properties withhigher-resolution, more precise, and more easily scalable fabrication and manufacturing processes toenhance the ease with which materials can be customized, including fabrication techniques to enable
the bottom-up construction of qubits from the atomic or molecular components. Collaboration
between quantum engineers and those studying materials science would enable the development ofmodels for optimizing materials selection for desired function and performance based upon
controllable properties, such as density of states, tunneling energies, and resonance frequencies, andthe qubit-relevant characterization of materials-related decoherence mechanisms.

– 10 –QUANTUM FRONTIERS“How can we develop a fast, iterative synthesis technology that integrates in situ
fabrication and characterization and is informed and/or directed by first principles
theory and machine learning, thereby enabling rapid convergence toward a desiredquantum-coherent property[?]”– Opportunities for Basic Research for Next-Generation Quantum Systems (Basic
Energy Sciences Roundtable, DOE 2017)

Progress in this frontier has the potential to enhance researchers’ abilities to fabricate high-quality
qubits and other specialized materials for quantum device components reliably and according todesired specifications, by design. It could also spur progress towards next-generation quantum
materials with increased resilience to noise, supporting efforts to build stable, compact, and low-costquantum devices with the potential for practical deployment.

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4. Exploring Quantum Mechanics through Quantum Simulations“The intellectual roots of [quantum computing] go back decades to pioneers such as
Richard Feynman who considered the fundamental difficulty of simulating quantum
systems and ‘turned the problem around’ by proposing to use quantum mechanics
itself as a basis for implementing a new kind of computer capable of solving suchproblems. Although the basic theoretical underpinning of [quantum computing] hasbeen around for some time, it took until the past 5 years to bring the field to an
inflection point: now small and intermediate-scale machines are being built invarious labs, in academia and industry.”– Next Steps in Quantum Computing: Computer Science’s Role (Computing Community
Consortium 2018)

Engineered quantum technologies can be used to efficiently simulate and emulate intrinsicallyquantum systems to elucidate their properties. Such efforts have already improved our understandingof previously mysterious phenomena and have the potential to lead to stunning progress infoundational and applied science. Quantum information technologies, such as NISQ computers andanalog quantum simulators available over the next 5 years, will offer the chance to improve ourunderstanding of quantum systems through computation, simulation, experimentation, and otherstudies. Key areas for progress include: leveraging quantum devices to improve approaches for theclassical, quantum, and hybrid simulation of quantum behavior from many-body physics to chemistry
to materials science; demonstrating quantum advantages based on quantum simulation; anddeveloping new algorithms for NISQ-era devices, and exploring their performance in the presence ofnoise.
“A quantum, rather than classical, simulation is naturally better equipped to explore
the state space spanned by quantum systems.”– Quantum Computing: Progress and Prospects (National Academies of Sciences,
Engineering, and Medicine 2019)a. Developing Quantum Simulation Applications
Many researchers noted the potential for quantum devices to improve our understanding of the scienceand engineering of a range of quantum systems. Key areas of opportunity include: chemical electronic
structure calculations; nuclear vibration and rotation calculations for molecular spectroscopy; manybody chemical dynamics and chemical reactions; equilibrium properties, phase diagrams, and othermaterials properties; and other many-body dynamics and complex physical phenomena such asprotein folding, high-temperature superconductivity, or nuclear fission. Simulation of these systems
could be conducted via analog or gate-based quantum computers, quantum emulation, or simulations
run on classical computers.

– 12 –QUANTUM FRONTIERS“[T]he answer to the question whether quantum mechanical resources of a quantum
computer are required for accurate computation of molecular electronic properties
is then also highly relevant. If the answer is aﬃrmative, then this makes a perfectpractical case for quantum computing. Otherwise, if we can show that quantum
chemistry may be described classically in spite of its quantum nature, this can open
the door to eﬃcient exact solutions of these problems on a classicalcomputer….Regardless of which way the question is resolved, the chemistrycommunity stands to beneﬁt, gaining a tool for simulating the electronic structure ofmolecules.” – Quantum Information and Computation for Chemistry (NSF 2016)b. Implementing Algorithms on Available Devices and Exploring Their PerformanceThis frontier also reflects the opportunities to advance and implement quantum algorithms andprotocols for studying these and other quantum systems. Examples of quantum algorithms highlighted
by the research community include quantum phase estimation, adiabatic state preparation, quantum
imaginary time evolution, Hamiltonian simulation, real space simulation, and fermionic simulation.
Hybrid quantum-classical approaches, which leverage quantum hardware for specific computational
steps within a larger algorithm, include the variational quantum eigensolver (VQE) for ground-stateenergy optimization and the quantum approximate optimization algorithm (QAOA). A key element of
this work will be establishing performance benchmarks for comparing different algorithms—both
theoretically and empirically—and for comparing quantum algorithm outputs to the best-knownclassical results. Insights gleaned from this work could also inform new or improved classicalcomputational approaches, helping to establish their capabilities and limitations.
“It is clear that one will rely on hybrid quantum-classical algorithms for many years
to come, and there remain many open questions. One is how to best adapt quantum
algorithms within existing quantum-classical frameworks.”– Enabling the Quantum Leap: Quantum Algorithms for Chemistry and Materials (NSF
2019)

This specific use case of NISQ devices provides a promising context to study how noise affects algorithm
implementation, varies with different hardware configurations, and scales with system size. Researchwould benefit from empirically validated resource estimation strategies and the development of noisemodels in support of system validation—perhaps enabled by quantum and approximate circuit
simulators. Quantum and classical simulation methods could also be used to model and optimize otherquantum technology components, such as elements of quantum networks.

– 13 –QUANTUM FRONTIERS“Estimating resources for quantum algorithms using realistic quantum computing
architectures is an important near-term challenge. Here, the focus is generally on
reducing the gate count and quantum circuit depth to avoid errors from qubit
decoherence or slow drifts in the qubit control system. Diﬀerent types of quantum
hardware support diﬀerent gate sets and connectivity, and native operations areoften more ﬂexible than fault-tolerant gate sets for certain algorithms. This
optimizing of speciﬁc algorithms to speciﬁc hardware is the highest and mostimportant level of quantum computer co-design.”– Quantum Computer Systems for Scientific Discovery (NSF 2019)

A vision for this frontier is to demonstrate transformative quantum advantage for solving many-bodyquantum physics, quantum chemistry, or materials science problems, while improving researchers’
abilities to engineer quantum hardware and software. It could also lead to models for how best toleverage quantum and classical computing resources complementarily for different kinds of problems.
At a fundamental level, it will help to illuminate practical efficiency, accuracy, and precision limits ofvarious methods for the computational study of quantum systems.

– 14 –QUANTUM FRONTIERS

5. Harnessing Quantum Information Technology for Precision Measurements“State-of-the-art detectors and sensing are developed and employed to perform
precision measurements that probe the laws of nature, to discover new particles andstates of matter, and to develop capabilities for national security needs.”– Nuclear Physics and Quantum Information (Nuclear Science Advisory Committee,
DOE, NSF 2019)

Several cutting-edge metrology techniques already demonstrate key benefits from quantum control
and QIS-related approaches, including atomic clocks, atom interferometers, magnetometers, andnuclear magnetic resonance (NMR) imaging systems. In this frontier, there are opportunities to improve
precision and accuracy, develop new measurement modalities, improve methods for deploying thesetechnologies in the field, and pioneer new applications for precision measurements. Key areas for
exploration include: improving understanding of quantum-related limits to accuracy and precision forsystems that can be deployed in the field to enhance navigation capabilities and for realization ofstandards; new modalities and applications for quantum sensing in situ and in vivo; and using
entanglement and small-scale quantum computers to improve measurement technologies.
“Attaining strong quantum enhancements in detection (e.g., quantum illumination)and in sub-Rayleigh quantum imaging represent significant challenges. Equallyimportant is the construction of compact and robust quantum sensors, detectors,
and imagers that are suitable for deployment in extreme environments.”– Future Directions of Quantum Information Processing. A Workshop on the Emerging
Science and Technology of Quantum Computation, Communication, and Measurement(Virginia Tech Applied Research Consortium, DOD 2016)

a. Deploying Quantum Technology for Improved Accuracy and Precision
Precision position, navigation and timing (PNT) applications already use quantum technology, but
typically have practical constraints on size, weight, power and cost (SWAP-C). Bandwidth and reliability
also matter. Members of the R&D community highlighted the exploration of attaining superior
performance while satisfying overall package requirements as a critical direction that combines
measurement science with quantum engineering. Positioning with millimeter accuracy and timetransfer with sub-nanosecond accuracy are available in the laboratory. However, their transition topractical quantum technologies, including designing and manufacturing rugged components forpractical deployment, remains a challenge.
The entire set of System International (SI) units is now tied to constants that can be realized using
quantum phenomena. This was a key reason for the redefinition of the kilogram in 2019. Connecting
measurements in the field and on the factory floor directly to fundamental constants, by using QIS
technology is a capability that will affect many fields of science and technology. New procedures canreplace some time-consuming and elaborate calibration chains that were required for conventional
approaches to metrology. This frontier will also leverage QIS to enable better precision and accuracy.

– 15 –QUANTUM FRONTIERS“There are many laboratory demonstrations of quantum sensors with performance
eclipsing fielded instruments, presenting opportunities for significant return on
investmentforengineering/development….Clocks,
accelerometers,
andmagnetometers may be the best opportunities.”– Applications of Quantum Technologies (Defense Science Board, DOD 2019)b. Creating New Modalities and Applications for Quantum Sensing In Situ and In Vivo
While quantum advantages for sensing can be profound, part of this frontier entails identifying
compelling use-cases that justify such quantum control as opposed to simply increasing flux or systemsize in standard approaches. Community-identified opportunities for exploration of precision
measurements include high energy physics detectors; spectroscopy in chemistry labs; NMR techniquesthat combine cutting-edge spatial resolution with spectroscopic chemical shift sensitivities; geodesy
and mapping; hydrology and mineral exploration; astronomy with quantum-enhanced telescopes; anda variety of bio-science applications ranging from electroencephalography (EEG) andmagnetoencephalography (MEG) to studies of vision, photosynthesis, cellular dynamics, andmagnetotaxis.
“[H]ighly entangled systems of trapped ions can be used not only for quantum
simulation…squeezing can perform extraordinarily precise measurements of force,with implications for searches of ultralight dark matter. Measurement of forces andfields is a basic operation of precision measurement and tests of fundamental
symmetries, and some of the most exciting developments today take advantage of
QIS techniques.”– Opportunities for Nuclear Physics and Quantum Information Science (DOE 2019)

Researchers also recognized that new measurement modalities with quantum states of light, next
generation atomic clocks, ultracold molecules, matterwave interferometers, color centers in crystals,
and other systems, offer new capabilities and in some cases unprecedented precision and accuracy
based on quantum coherence and superposition. However, to push this frontier even further,demonstrating the clear advantages for metrology using entanglement and many-body quantum stateswith non-classical correlations is seen as an important next step. Using squeezed vacuum states for
Advanced LIGO is a major achievement in this direction. Exploring this frontier will enable improved
performance with increasing degrees of entanglement, for useful applications in other scientific fields.
“[S]cientists have created new opportunities for understanding and constructing
quantum matter where many-body physics is no longer feared as a hurdle for
precision measurement, but rather a new frontier to advance precision andaccuracy.”– 16 –QUANTUM FRONTIERS– Manipulating Quantum Systems: An Assessment of Atomic, Molecular, and Optical
Physics in the United States (National Academies of Sciences, Engineering, andMedicine 2020)c. Using Entanglement and Quantum Computers to Improve Measurements
Extending this concept to sensor arrays and other networked quantum systems (e.g., a network ofentangled clocks) was identified by the research community as a cutting-edge opportunity for quantum
metrology. In principle, optimal entanglement and measurement using quantum pre- and postprocessing enable new domains of metrology. One suggested direction to explore is to use many-bodyquantum states, prepared with quantum circuits or small-scale quantum processors, to enable
metrology. This would utilize cutting-edge QIS technologies to expand the precision measurement
frontier.
“[Q]uantum technology is already having an impact in metrology and fundamental
discovery (gravitational waves; LIGO). Five years is a very realistic timeframe fordemonstrating the usefulness of quantum sensing technology in particular.”– RFI response

Progress in this frontier could lead to deployment of quantum sensors in new contexts and scientificdomains. These devices are expected to push the limits of accuracy and precision, and to be realized
via new underlying sensing mechanisms. In PNT, quantum technologies are likely to enable new levelsof accuracy and time transfer capabilities in field campaigns. In metrology, quantum effects can be used
to disseminate standards tied to defined SI units. Deployment of novel quantum sensing technologies
is a major goal, as is identification of key use cases where entanglement and small quantum computers
can improve metrological outcomes in applied settings.

– 17 –QUANTUM FRONTIERS

6. Generating and Distributing Quantum Entanglement for New Applications“[O]nly a small number of scientific techniques and technological applications
take advantage of the unique phenomena of quantum superposition andentanglement.”– Opportunities for Basic Research for Next-Generation Quantum Systems (Basic
Energy Sciences Roundtable, DOE 2017)

Progress in distributing entanglement has stimulated great interest in quantum networks as anenabling platform for quantum technologies. Interconnecting quantum devices by entangling qubits inseparate modules may be a key pathway for scaling up quantum computers. Furthermore, distributing
quantum information across spatially separated nodes is expanding the intellectual domain ofquantum communication into the larger field of quantum networking. Inventing the physical layercomponents to distribute entanglement, developing algorithms, applications, protocols, and use cases
for various quantum network systems, and understanding the integration of components and protocols
into systems-level architectures are areas to explore in this frontier.
“Quantum communication systems require repeaters and quantum
memory…early technology demonstrations exist but repeaters and memory are
far from levels of performance to be useful.” – RFI response

a. Developing Foundational Components for Quantum Networks
RFI respondents and workshop reports named several foundational technologies that need further
development before long-distance quantum networks can be realized. These range from quantum
repeaters to memories and interconnects. An outstanding challenge is the development of quantum
repeaters that are efficient and scalable, possess sufficient bandwidth, and are deployable. Likewise,plug and play modules for quantum memory remain an open R&D track, despite early progress on
protocols.
“Quantum interconnects (QuICs) present special challenges, as they must allow
the transfer of fragile quantum states between different physical parts ordegrees of freedom of the system. The diversity of QIT [quantum information
technology] platforms (superconducting, atomic, solid-state color center, optical,etc.) that will form a ‘quantum internet’ poses additional challenges. As quantum
systems scale to larger size, the quantum interconnect bottleneck is imminent,
and is emerging as a grand challenge for QIT.”– Development of Quantum InterConnects for Next-Generation Information
Technologies (NSF 2019)– 18 –QUANTUM FRONTIERS

b. Enabling Quantum State Transduction
Quantum interconnects are needed for coupling the often heterogeneous elements of quantum
systems. Researcher-identified avenues for exploration include: coherent transduction of quantum
states in atomic, optical, microwave, electronic, and solid state systems; quantum frequency
conversion; quantum control of spin states, charge states, polarization, spatial modes, orbital angularmomentum, and other degrees of freedom such as spectral-temporal encoding; higher dimensional
qubits; and manifestations of entanglement with continuous variables. Furthermore, practicalmethods to generate and distribute entanglement must mitigate loss, noise, and errors to meet
specifications (e.g., data processing rates and compounded efficiency or throughput) needed for
applications such as those discussed below.
“[L]arge-scale networks of superconducting quantum computers—quantum
networks—are impossible without new ways to distribute entanglement overlong distances, necessitating the development of efficient quantum statetransduction.” – RFI response

c. Integrating Quantum Networking Systems
Researchers have identified a need for infrastructure and engineering to facilitate entanglement
distribution over a range of distance scales. Entanglement distribution over short ranges, from cryostat
to cryostat, across integrated photonics devices, or between qubits in a single system are key
challenges. Aerial and satellite platforms equipped for free-space communication of quantum statesand for interconnecting local networks (e.g., terrestrial fiber-optics based quantum intranets) are also
pursued in this frontier. Infrastructure and protocols for entanglement distribution and research
testbeds or facilities (e.g., with switching, purification, interconnections, and hybrid classical-plusquantum methods) require substantial exploration.
“[O]ptical telescopes connected across the globe in a quantum network could
allow determination of apparent positions of stars with unprecedented
precision. Evolution of the above ideas will depend very much on theoreticalefforts to develop concepts of experiments and to evaluate their sensitivity.”– Quantum Networks for Open Science Workshop (DOE/ASCR 2019)

d. Exploring Quantum Networking Algorithms, Applications, Protocols, and Approaches
Members of the R&D community also pointed beyond the physical layer, towards opportunities to
explore applications of quantum networks such as distributed quantum computing, blind quantum
computing, end-to-end quantum encryption, secure software distribution, and entangled sensor
arrays. In addition to entirely new algorithms and applications, networking protocols may needrefinement or large-scale revision to work on nascent quantum network testbeds. A variety of networkarchitectures may be envisioned, or encountered in the real world, and algorithms for distributed
quantum computing will need to account for network topologies. Applications of sensor networks,– 19 –QUANTUM FRONTIERS

including long baseline telescopes, Heisenberg-limited interferometry, and improved clock
synchronization align both here and with frontiers 1, 2, and 5.
“Quantum networking resources such as entanglement and teleportation are still
not well understood among domain scientists who could exploit them to solve newclasses of scientific problems.”– Quantum Networks for Open Science Workshop (DOE/ASCR 2019)

A key opportunity on this frontier is for researchers to develop and validate a sufficiently complete setof foundational quantum networking components that work together so long-distance quantum
networks can then be designed, established and operated to distribute entanglement to multiple nodeson (and around) Earth. During the same period, novel algorithms could enable exploration of new
applications for quantum networks. Several concepts such as blind quantum computing and quantumenhanced telescopes could be tested and improved with empirical studies using quantum network
testbeds or prototypes. Feasibility studies for space-based missions to distribute entanglement will
combine concepts from quantum engineering (and technology readiness levels) with fundamental
studies of entanglement generation, distribution, and utilization. Furthermore, new concepts forsensor arrays and distributed quantum computers are likely to be discovered as proofs-of-principle
unfold.

– 20 –QUANTUM FRONTIERS

7. Characterizing and Mitigating Quantum Errors“The grand challenge…for the Nation is understanding and experimentally realizing
quantum error correction and, ultimately, fault tolerance at large scales.”– RFI response

Quantum systems are inherently sensitive to their environment, which inevitably leads to errors. Thisis a fundamental issue because controlled interactions make qubits useful, yet untamed interactions
cause decoherence. The frontier of preserving coherent superpositions and entangled states longenough to perform valid quantum computations therefore relies on understanding how to diagnose,
avoid, and mitigate quantum errors. Fighting such decoherence is essential for quantum metrology andnetworking, too. In addition to materials science and topological protection discussed in Section 3,
improved control will be needed with explorations ranging from quantum error correction todecoherence-free subspaces and new approaches for fault-tolerant quantum computing. Key themes
include: optimal characterization and control for multi-qubit systems, including use of measurement,
feedback, and novel encodings; development and exploration of novel universal computing
approaches in the fault-tolerant domain; and use of current devices to expand the limits of performancefor qubits.
“A variety of techniques have been used to characterize qubits and the operations(gates) performed on them. Currently, the two dominant techniques are randomized
benchmarking (RB), and gate set tomography (GST)….Future protocols that directlyprobe the effect of changing how we implement gates will be critical for improving
our devices and stabilizing them against drift.”– ASCR Report on a Quantum Computing Testbed for Science (DOE 2017)

a. Characterizing and Controlling Multi-qubit Systems
Exploring how, and to what extent, characterizations of 2-qubit gates enable predictions of system
performance may be key for designing and controlling quantum computers at scale. New techniques
may be needed to fully predict how errors propagate in complex quantum processors and networks.
Characterization and modeling can guide the development of optimal gate operations, help mitigate
coherent errors and crosstalk, and stabilize devices against drift. Quantum error mitigation
opportunities named by members of the R&D community include improved materials (Section 3), multiqubit measurements and feedback, improved control techniques and platform designs, and extensions
to the fundamental theory of quantum error correction with novel encodings and protocols that may
improve the threshold for fault-tolerance, and reduce overhead costs in terms of resources (qubits,
gates, and times) for implementing logical qubits.

– 21 –QUANTUM FRONTIERS“Uncovering new types of error correction and mitigation suitable for near-term
simulators is an open problem. Furthermore, there is a natural trade-oﬀ between thecoherence of a system and the degree of programmability and tunability.
Understanding and exploring this trade-oﬀ is important in developing quantum
simulators. There is also an opportunity in the development of algorithms with thistrade-oﬀ in mind, leading naturally to the concept of co-design, i.e., developing
applications for speciﬁc hardware and architectures. Such eﬀorts will beneﬁt fromthe convergence of various areas of expertise, including experimental physics,
quantum control theory, computer science and software, and engineering.”–Quantum Simulators: Architectures and Opportunities 2019b. Approaching the Fault-tolerant Domain
Quantum error mitigation will enable explorations of universal computing with systems approaching
the fault-tolerant regime. Experiments in this direction can stimulate co-design efforts, for example
with error-aware implementations of algorithms supported in ways that minimize use of particulargates, operations, or states that are prone to decoherence (as mentioned in Sections 2 and 4). Several
R&D community inputs pointed out that developing a full stack—from physical to logical qubits andcompilers with software to implement higher-level quantum circuits—opens a series of new directions
for research. Explorations include new performance benchmarks (e.g., quantum volume or test-piececalculations) where results depend on error mitigation. Verification and validation will take on new
urgency as fault-tolerant modules and co-processors become available. Error-correcting quantum
repeaters and fault-tolerant approaches for adiabatic quantum computing and analog quantum
simulation are related research challenges.
“Research on quantum error correction can benefit enormously from using thecurrent and near-term quantum computer hardware (often referred to as Noisy
Intermediate Scale Quantum [NISQ] computers), which will allow error correction
codes and protocols to be developed from in situ studies on real hardware rather
than using idealized theoretical models.” – RFI response

c. Using Current Devices to Expand the Limits of Qubit Performance
At the same time, even as error-corrected systems are in development, several voices have been clearthat there is much to be learned from exploring newly available, albeit imperfect, technologies.
Problems can be mapped to device-specific architectures to seek value in the near-term (as mentioned
in Section 4). Explorations identified in this direction include examining what amount of error
mitigation is required to realize useful computations, development of useful low-depth algorithms(e.g., approximate optimization), and finding practical strategies for tailoring quantum error mitigation
techniques to specific hardware for specific applications.

– 22 –QUANTUM FRONTIERS“Quantum states are fragile; a great challenge is developing devices and techniques
to reduce noise in quantum devices. All avenues should be explored, including
topological materials and/or device designs that promise to reduce quantum statefragility, new error mitigation techniques, and quantum error correction codes.”– RFI response

In pursuit of fault-tolerance, both evolutionary and revolutionary pathways are being explored.
Experiments with state-of-the-art qubits can push the envelope of performance, even with incremental
developments. Improvements in support technologies such as lasers, microwave electronics,
cryogenics, and foundries can provide valuable steps in this direction. Work at testbeds can honequantum control methods (e.g., dynamical decoupling, pulse sequencing, and error correction), byfacilitating learning through experimentation to develop and apply device-specific models of noise,control, and errors. Some of the more revolutionary approaches that were named include topologicalqubits (touched upon in Section 3), use of cluster states and symmetry-protected states as a resources
for measurement-assisted quantum computing, studies of higher dimensional qubits such as oscillator
encodings, and other novel qubit architectures.
“Quantum computers are intrinsically far more vulnerable to error than classicalcomputers. Thus our hopes that large-scale quantum computers will be built andoperated someday are founded on the theory of quantum fault tolerance, which
establishes that reliable quantum computation is possible when the noise afflicting
the computer has suitable properties. Recent insights are broadening the class ofnoise models for which fault-tolerant quantum computing is provably effective, andclarifying the overhead cost of overcoming noise.”– Report of the Workshop on Quantum Information Science (NSF 2009)

The vision for this frontier is to develop reliable logical qubits and other techniques for achieving fault
tolerance. Development of more sophisticated error-corrected systems will benefit from improved
methods for characterizing system performance and error propagation. Error corrected networks andprocessors would serve as a next generation of hardware to support testing and stimulate developmentof new algorithms and protocols for verification and validation. While both incremental andrevolutionary approaches to enable large-scale fault-tolerant systems will continue to be explored,near-term applications for smaller-scale fault tolerant machines could be tested with a variety ofarchitectures and contexts. Aside from its practical importance for quantum technologies, theoreticalwork on quantum error correction may stimulate further discoveries about fundamental mathematicaland physical foundations of the universe, as discussed more in Section 8.

– 23 –QUANTUM FRONTIERS

8. Understanding the Universe through Quantum Information“This ‘entanglement frontier’ is exciting because, knowing that highly entangled systems
of many particles are hard to simulate with digital computers, we may anticipate thatsurprising, illuminating, and useful new phenomena will occur in sufficiently complex
quantum systems.”– Grand Challenges at the Interface of Quantum Information Science, Particle Physics, andComputing (DOE Study Group Report 2014)

QIS is a marvelous source of new perspectives on the mathematical and physical foundations of theuniverse. It has begun to transform the way we think about computation by exploring the limits of what
can be computed with physical systems, and could provide new opportunities for testing quantum
mechanics and other fundamental scientific theories in new regimes. Quantum technologies also
provide new ways to search for physics beyond the standard model of particles and fields, often via
precision measurements. In this frontier, foundational QIS research opens new scientific vistas. Three
major themes underlie this frontier: exploring the mathematical foundations of computation andinformation through the lens of quantum computing and quantum information theory; using concepts
from QIS and new applications of quantum simulation to explore the limits of physical theory, from dark
matter to quantum gravity; and leveraging precision measurement and many-body quantum systems
to test the expectations of the standard model of particle physics, and search for phenomena beyond
the current model.

“Some important areas of research in entanglement theory aim to: deepen understandingof fundamental physical and mathematical aspect of quantum vs classical correlations(notably, ‘monogamy’ of entanglement, also in relation to the ‘quantum marginal
problem,’ or relevant to temporal as opposed to spatial correlations); further push aspectsof the characterization and quantification of entanglement within a resource-theory
framework (with possible ramifications ranging from quantum thermodynamics to highenergy physics); ultimately, explore generalizations of the very notion of entanglement,that may incorporate ‘locality constraints’ more general than currently envisioned andmay allow [researchers] to unveil the nature and role of entanglement in topologicalquantum matter or in the emergence of space-time geometry.”– Executive Summary of 2015 NSF Conference on Mathematical Sciences Challenges in
Quantum Information (NSF 2015)

a. Exploring Mathematical Foundations of Computation and Information
Fundamental questions about computation (e.g., Can quantum computers efficiently simulate any
process that occurs in nature? And, for what computations might exponential speedup be achieved overclassical approaches?) raised in QIS workshops touch on quantum complexity theory, quantum
resource theory, and quantum computing. Fundamental research on the cybersecurity implications of– 24 –QUANTUM FRONTIERS

quantum technologies, and mitigation strategies, is a common area of interest for mathematics,
computer science, and QIS experts. Open questions on the theoretical limits of error correction andtopological quantum computing, and the universality of adiabatic quantum computation are also
discussed in the RFI responses and workshop reports.
“Although several theoretical models of quantum computation exist and are well‐studied,such as quantum circuits, topological quantum computation, dissipative quantum
computing, quantum walks, and the adiabatic quantum computing model, each model
has its pros and cons in the context of an actual hardware implementation. The space ofpossible quantum computational models is far from fully charted, and developing models
in a co-design approach with quantum hardware development may benefit both.”– 2015 DOE ASCR Workshop

Investigating how complex quantum states can be prepared or efficiently approximated could informthe development of performance benchmarks, and also elucidate the origins of thermodynamics andnon-equilibrium dynamics (e.g., via studies of time crystals, chaos, pre-thermalization, and quantum
information scrambling). At the same time, advances in QIS are spurring improvements in classicalcomputation—for example, with simulated quantum annealing or new approaches to Boson samplingthat raise expectations for demonstrable quantum advantages. One workshop report suggested QIS
can help answer the question, “Are there other fundamentally different models of computing that have
not yet been developed?”b. Expanding the Limits of Physical Theory“[T]he field should think carefully about which key, longstanding questions in physics could
be solved using quantum technology.” – RFI response

Research in QIS has begun to shed light on other interwoven areas of physics and other scientific fields.
For example, research on entanglement can address fundamental questions about the emergence of
spacetime, entropy of black holes, correspondence with wormholes, and the foundations ofthermodynamics. Research areas described in workshop reports and RFI responses include: howquantum computational analysis of quantum walks can extend scattering theory; how quantum error
correction codes and multipartite entanglement can inform searches for new phases of matter andtopological states; and how the anti-de Sitter/conformal field theory (AdS/CFT) correspondence andassociated dictionary for translating results can be used to inform quantum gravity theory, and explore
properties of gauge theories at strong coupling where perturbative analysis is not possible.
Furthermore, quantum networks and computers can test quantum mechanics in new regimes by
exploring fundamental limits for coherence and entanglement. QIS can help explore the question,“What credible deviations from conventional quantum theory are experimentally testable?” (e.g.,gravitationally induced decoherence, spontaneous wavefunction collapse models, or nonlinear
corrections to the Schroedinger equation).

– 25 –QUANTUM FRONTIERS“Focus on simulating quantum systems that cannot be studied in a lab, such as black holes.”– RFI responsec. Testing the Standard Model of Particle Physics
For fundamental physics, in addition to improvements in gravitational wave detection and precision
measurements of fundamental constants, QIS can provide new approaches to testing expectations
from the standard model of particle physics, and conjectured extensions to that field. Examples include:
searches for dark matter and dark energy; tests of fundamental symmetries such as charge, parity, time(CPT) and Lorentz invariance; and searches for variation of fundamental constants in time or space. QIS
methods such as coherent spectroscopy, atom interferometry, or advanced magnetometry enablesearches for permanent electric dipole moments of fundamental particles (tests of CP-violating
physics), measurements of the fine structure constant (useful for tests of quantum electrodynamics),
searches for axion-like particles (dark matter candidates), and fifth-force searches. This frontier will
improve our understanding of the foundations of the physical universe.
“Ultra‑precise measurements of quantum phenomena can be used as extremely powerfulprobes of new physics at very high energy scales, e.g., by testing fundamental physicalsymmetries and laws, and by searching for new phenomena such as that associated withthe ‘dark sector.’ For example, one of the most exciting opportunities at the Quantum
Frontier is searches for an electric dipole moment (EDM) of the electron, as well as related
quantities in atomic nuclei, which arise at a measurable level only from charge‑parity (CP)violation beyond that in the Standard Model.” – DOE Quantum Sensors Report
This frontier recognizes the value of QIS R&D for deepening foundational knowledge, with the potential
to yield unexpected discoveries, new scientific concepts and tools that translate to other disciplines,
and yet unknown applications and technologies downstream. QIS research provides opportunities totest, refine and extend fundamental mathematical and physical theories that we use to describe thenature of the universe; develop a more complete understanding of what can and cannot be efficiently
computed; and elucidate the value of quantum resources for computing, engineering and science itself.

– 26 –QUANTUM FRONTIERSSUMMARY AND OUTLOOKWithin these frontiers, what are the most pressing grand challenges facing QIS? The answer to that
depends on one’s objectives. The breadth of responses and details of R&D pursuits encouraged in the
RFI responses and QIS workshop reports provide a broad range of opportunities for research agencies
to consider and pursue according to their missions. This community input, received in multiple venues
from U.S. and worldwide technical experts, has been organized into eight technical areas identified
here as quantum frontiers. The frontiers are broad areas at the forefront of QIS that contain numerous
quantum questions that should be explored early on, and hard technical challenges that must be
overcome before applications can be developed.
Ensuring sustained American leadership in QIS hinges on coordinating core research programs acrossthe pillars of QIS U.S. Government funding: the civilian, intelligence, and defense agencies. For eachmission, the grand challenges and priorities may be different, but there are common hurdles wherecoordinated efforts can accelerate progress. The synopsis of R&D community perspectives presented
here is intended to gently guide this coordination by pointing towards quantum frontiers to explore.

Bibliography of QIS Workshop and Study Reports
1. Request for Information on National Strategic Overview for Quantum Information Science,
National Science Foundation, 12/11/2018 (reissued on 05/30/2019). This RFI sought input from
America’s QIS R&D community to inform the Government as it developed the means toaddress specific QIS policy recommendations outlined in the National Strategic Overview for
QIS.
2. H. J. Kimble, C. Callan Jr., K. Case, A. Despain, N. Fortson, J. Goodman et al. 1996. Quantum
Computing. JASON Study JSR-95-115.
3. Bennett, C.H., D.P. DiVicenzo, N. Gershenfeld, H.M. Gibbs, H.J. Kimble, J. Preskill, U.V. Vazirani,
D.J. Wineland, and C. Yao. 1999. Quantum Information Science. An Emerging Field ofInterdisciplinary Research and Education in Science and Engineering. NSF Workshop Report.
NSF-00-101.
4. Quantum Information Science and Technology Experts Panel. 2004. A Quantum Information
Science and Technology Roadmap. ARDA Report LA-UR-04-1778.
5. National Research Council. 2007. Controlling the Quantum World: The Science of Atoms,
Molecules, and Photons. Washington, DC: The National Academies Press.
6. National Science Foundation. 2009. Report of the Workshop on Quantum Information Science.
Workshop Report.
7. Farhi, Edward, Stephen Jordan, Patrick Hayden, Mikhail Lukin, Juan Maldacena, John Preskill,
Peter Shor, Jacob Taylor, and Carl Williams. 2015. Grand Challenges at the Interface of Quantum
Information Science, Particle Physics, and Computing. DOE Study Group Report.
8. Viola, Lorenza and Aram Harrow. 2015. Mathematical Sciences Challenges in Quantum
Information. NSF Workshop Report.
9. Department of Energy Quantum Computing Working Group. 2015. ASCR Workshop on Quantum
Computing for Science. SAND2015-5022R.
10. Fradkin, Eduardo, Juan Maldacena, Lali Chatterjee, and James W. Davenport. 2015. "BES-HEP
Connections: Common Problems in Condensed Matter and High Energy Physics, Round Table
Discussion." United States.
11. Department of Energy Office of Science. 2016. Quantum Sensors at the Intersections ofFundamental Science, Quantum Information Science & Computing. Roundtable Report.
– 27 –QUANTUM FRONTIERS

12. National Science Foundation. 2018. Midscale Instrumentation to Accelerate Progress in Quantum
Materials. Workshop Report.
13. Department of Energy Basic Energy Sciences. 2016. Quantum Materials for Energy RelevantTechnology.
14. Klemic, Kate and Jeremy Zeigler. 2016. Future Directions of Quantum Information Processing. A
Workshop on the Emerging Science and Technology of Quantum Computation, Communication,and Measurement. VT-ARC Report.
15. Olson, Jonathon, Yudong Cao, Jonathan Romero, Perer Johnson, Pierre-Luc Dallaire-Demers,
Nicolas Sawaya, Prineha Narang et al. 2017. Quantum Information and Computation for
Chemistry. NSF Workshop Report.
16. National Science Foundation Division of Materials Research. 2017. “Workshop: Convergence
QL: Workshop on Quantum Elements of Secure Communication.”
17. Carter, Jonathan, David Dean, Greg Hebner, Jungsang Kim, Andrew Landahl, Peter Maunz,
Raphael Pooser, Irfan Siddiqi, and Jeffrey Vetter. 2017. ASCR Report on a Quantum Computing
Testbed for Science. United States.
18. Dean, D.J., E. Dumitrescu, S. Economou, P.G. Evans, T. Humble. S. Jesse et al. 2017. Quantum
Information Science: Factual Document for the Office of Basic Energy Sciences at the Departmentof Energy.
19. Department of Energy Basic Energy Sciences. 2017. Report of the Basic Energy Sciences
Roundtable: Opportunities for Quantum Computing in Chemical and Materials Sciences.
20. Department of Energy Basic Energy Sciences. 2017. Report of the Basic Energy Sciences
Roundtable on Opportunities for Basic Research for Next-Generation Quantum Systems.
21. Institute for Nuclear Theory. 2017. Quantum Computing for Theoretical Nuclear Physics. INS
Report 18-008.
22. Department of Energy Fusion Energy Sciences. 2018. Report of the Fusion Energy Sciences
Roundtable on Quantum Information Science.
23. National Science Foundation. 2018. “Workshop: Quantum Biology and Quantum Processes in
Biology.” Tysons, Corner, VA, US. November 26–27, 2018.
24. Martonosi, Margaret and Martin Roeteller. 2019. Next Steps in Quantum Computing: Computer
Science’s Role. Computing Community Consortium Workshop Report.
25. University Industry Demonstration Partnership. 2018. Catalyzing Industry-University
Collaboration in Quantum technologies. Workshop Report.
26. National Academies of Sciences, Engineering, and Medicine. 2019. Quantum Computing:
Progress and Prospects. Washington, DC: The National Academies Press.
27. Walter G. Copan, et al. 2019. Return on Investment Initiative for Unleashing American
Innovation. NIST Special Publication 1234.
28. Bauer, Bela, Sergey Bravyi, Mario Motta, and Garnet Kin-Lic Chan. 2019. Enabling the Quantum
Leap: Quantum algorithms for quantum chemistry and material. NSF Workshop Report.
29. Computing Community Consortium. 2019. Identifying Research Challenges in Post Quantum
Cryptography Migration and Cryptographic Agility. Workshop Report.
30. Cloët, Ian C., Matthew R. Dietrich, John Arrington, Alexel Bazavov, Michael Bishof, Adam
Freese, Alexey V. Gorshkov et al. 2019. “Opportunities for Nuclear Physics & Quantum
Information Science.” Edited by Ian C Cloët and Matthew R. Dietrich.
31. Department of Energy Office of Advanced Scientific Computing Research. 2019. Quantum
Networks for Open Science Workshop Report. Workshop Report.
32. Defense Science Board Task Force on Applications of Quantum Technologies. 2019. Executive
Summary of the Defense Science Board Report on Application of Quantum Technologies.

– 28 –QUANTUM FRONTIERS

33. Air Force Research Laboratory Information Directorate. 2019. 1st International Workshop on
Quantum Information Science, State University of New York, Utica, NY, USA, July 9-11 2019.
34. National Science and Advisory Committee Subcommittee on Quantum Information Science.
2019. Nuclear Physics and Quantum Information Science.
35. Awschalom, David, Karl K. Berggren, Hannes Bernien, Bhavel Sunil, Lincoln D. Carr, PaulDavids, Sophia E. Economou et al. 2019. "Development of Quantum InterConnects for NextGeneration Information Technologies."
36. Alexeev, Yuri, Dave Bacon, Kenneth R. Brown, Robert Calderbank, Lincoln D. Carr, Frederic T.
Chong, Brian DeMarco et al. 2019. "Quantum Computer Systems for Scientific Discovery."
37. Altman, Ehud, Kenneth R. Brown, Giuseppe Carleo, Lincoln D. Carr, Eugene Demler, Cheng
Chin, Brian DeMarco et al. 2019. “Quantum Simulators: Architectures and Opportunities.”
38. National Academies of Sciences, Engineering, and Medicine. 2019. Manipulating Quantum
Systems: An Assessment of Atomic, Molecular, and Optical Physics in the United States.
Washington, DC: The National Academies Press.

– 29 –QUANTUM FRONTIERSABOUT THE OFFICE OF SCIENCE AND TECHNOLOGY POLICYThe Office of Science and Technology Policy (OSTP) was established by the National Science andTechnology Council (NSTC), Organization, and Priorities Act of 1976 to provide the President and others
within the Executive Office of the President with advice on the scientific, engineering, and technologicalaspects of the economy, national security, homeland security, health, foreign relations, theenvironment, and the technological recovery and use of resources, among other topics. OSTP leadsinteragency science and technology policy coordination efforts, assists the Office of Management andBudget with an annual review and analysis of Federal research and development in budgets, and serves
as a source of scientific and technological analysis and judgment for the President with respect to major
policies, plans, and programs of the Federal Government. More information is available athttps://www.whitehouse.gov/ostp.

ABOUT THE NATIONAL SCIENCE AND TECHNOLOGY COUNCIL
The National Science and Technology Council (NSTC) is the principal means by which the Executive
Branch coordinates science and technology policy across the diverse entities that make up the Federal
research and development enterprise. A primary objective of the NSTC is to ensure that science andtechnology policy decisions and programs are consistent with the President's stated goals. The NSTC
prepares research and development strategies that are coordinated across Federal agencies aimed ataccomplishing multiple national goals. The work of the NSTC is organized under committees thatoversee subcommittees and working groups focused on different aspects of science and technology.
More information is available at https://www.whitehouse.gov/ostp/nstc.

ABOUT THE NATIONAL QUANTUM INITIATIVEThe National Quantum Initiative (NQI) provides an overarching framework to strengthen andcoordinate QIS R&D activities across U.S. Departments and Agencies, private sector industry, and theacademic community. The NQI entails a whole of government effort to accelerate quantum researchand development, as legislated by the NQI Act of 2018. The NQI Act authorizes the National Science
Foundation (NSF), the Department of Energy (DOE), and the National Institute of Standards andTechnology (NIST) to strengthen QIS Programs, fund Centers, and support Consortia. The NQI Act also
calls for a coordinated approach to QIS R&D efforts across the Federal Government, including thecivilian, defense, and intelligence sectors. NQI activities are coordinated through the NSTC
Subcommittee on Quantum Information Science (SCQIS), with support from the National Quantum
Coordination Office (NQCO).

ABOUT THE NATIONAL QUANTUM COORDINATION OFFICEThe National Quantum Coordination Office (NQCO) coordinates QIS activities across the U.S. federal
government, industry, and academia. Legislated by the NQI Act of 2018 and established within the
White House Office of Science and Technology Policy, the NQCO oversees interagency coordination of
the NQI Program and QIS activities; serves as the point of contact on Federal civilian QIS activities;
ensures coordination among the consortia and various quantum centers; conducts public outreach,
including the dissemination of findings and recommendations of the NSTC Subcommittee on Quantum
Information Science and the NQI Advisory Committee; promotes access to and early application of the– 30 –QUANTUM FRONTIERS

technologies, innovations, and expertise derived from U.S. QIS activities, as well as access to quantum
systems developed by industry, universities, and Federal laboratories to the general user community.

ACKNOWLEDGEMENTS
This report was compiled by the NQCO with support from the Science and Technology Policy Institute(STPI). The NQCO gratefully acknowledges those who provided feedback to the Request for Information
on National Strategic Overview for QIS, as well as the numerous workshops participants and input frommembers of the NSTC SCQIS.

COPYRIGHT INFORMATIONThis document is a work of the United States Government and is in the public domain (see 17 U.S.C.
§105). Subject to the stipulations below, it may be distributed and copied with acknowledgment to the
NQCO. Copyrights to graphics included in this document are reserved by the original copyright holders
or their assignees and are used here under the Government’s license and by permission. Requests to
use any images must be made to the provider identified in the image credits or to NQCO if no provider
is identified. Published in the United States of America, 2020.

– 31 –