of 31
Development of Quantum InterConnects (QuICs)
for Next-Generation Information Technologies
David Awschalom
1
, Karl K. Berggren
2
, Hannes Bernien
1
, Sunil Bhave
3
, Lincoln D. Carr
4
, Paul Davids
5
,
Sophia E. Economou
6
, Dirk Englund
2
, Andrei Faraon
7, 8
, Marty Fejer
9
, Saikat Guha
10, 11, 12
, Martin V.
Gustafsson
13
, Evelyn Hu
14, 15
, Liang Jiang
1
, Jungsang Kim
16, 17
, Boris Korzh
18
, Prem Kumar
19, 20
, Paul G.
Kwiat
21, 22
, Marko Lončar
14, 15
*, Mikhail D. Lukin
15, 23
, David A. B. Miller
9
, Christopher Monroe
24, 25, 26
,
Sae Woo Nam
27
, Prineha Narang
14, 15
, Jason S. Orcutt
28
, Michael G. Raymer
29, 30
*, Amir H.
Safavi-Naeini
9
, Maria Spiropulu
31
, Kartik Srinivasan
25, 32
, Shuo Sun
9, 33
, Jelena Vučković
9
, Edo Waks
25, 34
,
Ronald Walsworth
24, 34, 35, 36
, Andrew M. Weiner
3, 37
, Zheshen Zhang
10, 38
1
Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL 60637
2
Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA 02139
3
School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907
4
Department of Physics, 1500 Illinois St., Colorado School of Mines, Golden, Colorado, 80401
5
Photonic & Phononic Microsystems, Sandia National Laboratory, Albuquerque, NM 87185
6
Department of Physics, Virginia Tech, Blacksburg, VA 24061
7
T .J. Watson Laboratory of Applied Physics, California Institute of Technology, Pasadena, CA 91125
8
Kavli Nanoscience Institute, California Institute of Technology, Pasadena, CA 91125
9
E.L. Ginzton Laboratory, Stanford University, Stanford, CA 94305
10
College of Optical Sciences, The University of Arizona, Tucson, AZ 85721
11
Department of Electrical and Computer Engineering, The University of Arizona, Tucson, AZ 85721
12
Department of Applied Mathematics, The University of Arizona, Tucson, AZ 85721
13
Raytheon BBN Technologies, Cambridge, MA 02138
14
John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138
15
Harvard Quantum Initiative (HQI), Harvard University, Cambridge, MA 02138
16
Department Of Electrical and Computer Engineering, Duke University, Durham, NC 27708
17
IonQ Inc., College Park, MD 20740
18
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109
19
Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL 60208
20
Department of Physics and Astronomy, Northwestern University, Evanston, IL 60208
21
Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801
22
IQUIST, University of Illinois at Urbana-Champaign, Urbana, IL 61801
23
Department of Physics, Harvard University, Cambridge, MA 02138
24
Department of Physics, University of Maryland, College Park, MD 20742
25
Joint Quantum Institute, University of Maryland, College Park, MD 20742
26
Joint Center for Quantum Information and Computer Science, University of Maryland, College Park, MD 20742
27
National Institute of Standards and Technology, Boulder, CO 80305
28
IBM T. J. Watson Research Center, Yorktown Heights, NY 10598
29
Oregon Center for Optical, Molecular, and Quantum Science, University of Oregon, Eugene, OR 97403
30
Department of Physics, University of Oregon, Eugene, OR 97403
31
Division of Physics Mathematics and Astronomy, California Institute of Technology, Pasadena, CA 91125
32
National Institute of Standards and Technology, Gaithersburg, MD 20899
33
JILA and Department of Physics, University of Colorado, Boulder, CO 80309
34
Department of Electrical and Computer Engineering, University of Maryland, College Park, MD 20742
35
Quantum Technology Center University of Maryland, College Park, MD 20742
36
Harvard - Smithsonian Center for Astrophysics, Cambridge, MA 02138
37
Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, IN 47907
38
Department of Materials Science and Engineering,The University of Arizona, Tucson, AZ 85721
*To whom correspondence should be addressed: Marko
Lončar:
loncar@seas.harvard.edu
; Michael G. Raymer:
raymer@uoregon.edu
1
Abstract
Just as ‘classical’ information technology rests on a foundation built of interconnected
information-processing systems, quantum information technology (QIT) must do the same. A
critical component of such systems is the ‘interconnect,’ a device or process that allows transfer
of information between disparate physical media, for example, semiconductor electronics,
individual atoms, light pulses in optical fiber, or microwave fields. While interconnects have
been well engineered for decades in the realm of classical information technology, quantum
interconnects (QuICs) present special challenges, as they must allow the transfer of fragile
quantum states
between different physical parts or degrees of freedom of the system. The
diversity of QIT 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. For these reasons, it is the position of the community represented by participants of the
NSF workshop on “Quantum Interconnects” that accelerating QuIC research is crucial for
sustained development of a national quantum science and technology program. Given the
diversity of QIT platforms, materials used, applications, and infrastructure required, a convergent
research program including partnership between academia, industry and national laboratories is
required.
This document is a summary from a U.S. National Science Foundation supported workshop held on 31
October - 1 November 2019 in Alexandria, VA. Attendees were charged to identify the scientific and
community needs, opportunities, and significant challenges for quantum interconnects over the
next 2-5 years.
2
I. Executive Summary
A quantum science and technology revolution is currently in the making, which is widely
expected to bring a myriad of scientific and societal benefits. Commensurate with this promise,
large challenges exist in seeing the vision become a reality, one of which is the engineering of an
essential class of components of any quantum information system—the quantum interconnects.
Figure 1.
The broad role of QuICs in quantum information technology. QS = Quantum switch; QR =
Quantum repeater (a device that can relay an entangled state from one set of qubits to a distant set
without physically sending an entangled qubit the entire distance); QMod = Modular quantum
processor; QFC = Quantum frequency converter; RNG = Random number generator. The QuICs are
indicated by bold red arrows or by wave packets representing photons.
Quantum interconnects (QuICs) are devices or processes that allow the transfer of quantum
states between two specified physical degrees of freedom (material, electromagnetic, etc.), or,
more broadly, connect a quantum system with a classical one. As illustrated in
Figure 1
, QuICs
are an integral part of nearly all conceivable quantum information processing systems, including
quantum computing, quantum sensing, and quantum communication. For example,
it can be
argued that modular quantum computing schemes provide the only viable approach that will
enable scaling up to truly large numbers of error corrected qubits
. Since modular approaches are
crucially dependant on efficient QuICs,
substantial and focused investment in this vital next
stage of quantum computing is timely.
Similarly, the ability to transmit information securely by
leveraging the laws of quantum physics, in a way that it is “future proof” against even the most
powerful quantum computers, is of great national importance. However, the reach of secure
fiber-based quantum networks, and the communication rates that they currently allow, are
severely limited by the optical losses in the existing quantum interconnects (transmission drops
exponentially in conventional optical fibers). Enhancing these interconnects with quantum
repeaters will extend the reach and the rate of quantum communication systems. With recent
proof-of-principle demonstrations at hand, this effort is ready to be accelerated.
3
Large technical hurdles exist to implementing QuICs: they must transfer the quantum
information (quantum states) with high fidelity, fast rates and low loss, often across a wide range
of energies, and do so in a scalable fashion. In some cases a viable candidate QuIC approach is
well understood, but dedicated engineering effort is needed to implement it, while in others new
physical phenomena need to be explored to implement a given QuIC. An acceleration of research
toward the invention and implementation of QuICs will also greatly boost progress in
development of materials, devices, systems and supporting infrastructure in critical-path areas
that support the development of practical quantum technologies. Such research would enable
quantum information science and technology across a wide range of specialties, with ensuing
scientific and societal benefits as described in the inset box.
SOCIETAL BENEFITS OF QUANTUM-ENABLED TECHNOLOGY
In September 2018 the National Science and Technology Council released a report, “National
Strategic Overview for Quantum Information Science,” which stated, “Through developments in
[quantum information science], the United States can improve its industrial base, create jobs, and
provide economic and national security benefits.”
[1]
Among the intentions of the national effort
outlined by the OSTP report are to: “Focus on a science-first approach that aims to identify and solve
Grand Challenges: problems whose solutions enable transformative scientific and industrial progress;”
and to “Provide the key infrastructure and support needed to realize the scientific and technological
opportunities.”
A commentary paper in
Science
[2]
co-authored by two participants in the QuIC Workshop, along
with a co-author of the NSTC report cited above, summarizes several of the societal benefits that QIT
can bring: “A fully functioning quantum computer would radically enhance our capabilities in
simulating nuclear and high-energy physics; designing new chemicals, materials, and drugs; breaking
common cryptographic codes; and performing more speculative tasks such as modeling, machine
learning, pattern recognition, and optimizing hard logistical problems such as controlling the electric
energy grid or traffic control systems.
[3]
” And, “Using qubits instead of conventional bits makes it
possible to create shared randomness between parties while knowing whether the communication
channel has been compromised by an eavesdropper. This enables sending information securely.
Quantum communication can also allow secure communication between multiple parties, and for
interconnecting large-scale quantum computers via a quantum internet.
[4], [5]
” Finally, the
Science
paper also states that the next generation of quantum-based sensors is projected to outperform current
sensing technologies, for example in geo-exploration and GPS–free navigation, biological and medical
research, and diagnostic technology.
QuIC ACCELERATOR WORKSHOP
An NSF-sponsored two-day “QuICs Accelerator Workshop” brought together a representative group of
over thirty scientists and engineers from academia, industry and national laboratories to identify the
present roadblocks that need to be overcome to create functioning QuICs across the necessary range of
QIT platforms. The consensus of the participants is that there are concepts and technologies whose
development warrants a large, synergistic, and convergent effort involving a range of expertise on a
national scale.
4
II. Introduction
As quantum technology progresses to real-world applications, a major identified hurdle needs to
be overcome: the development of quantum interconnects (QuICs). Just as ‘classical’ information
technology rests on a foundation built of interconnected information-processing systems,
quantum information technology (QIT) must do the same. Quantum interconnects include a wide
range of systems and processes that allow the transfer of quantum states between two specified
physical degrees of freedom (material, electromagnetic, etc.). They may also include components
that connect a quantum system with a system that is well described by classical physics for
purposes of controlling or reading out information from the quantum system. Quantum
interconnects present specific challenges, as they must allow the transfer of fragile
quantum
states
between different physical parts or degrees of freedom of the system. With the recent
dramatic progress in individual QIT systems for quantum computation, communication, and
sensing, an urgent need is to push rapidly toward the integration of such sub-systems to create
core technologies that will revolutionize the economy and society in many ways. (See Societal
Benefits box).
As quantum systems scale to larger size, a quantum interconnect bottleneck becomes imminent,
and surmounting it is emerging as a central goal for QIT. In the context of quantum
communication networks, a challenging but extremely important purpose of an interconnect will
be to enable the transfer of quantum information (that is, quantum states) across a distance—long
or short, depending on the application needs. A prime example of a long-sought-after but elusive
subsystem of long-range communication networks (over distances exceeding hundreds of
kilometers) is the
quantum repeater
, which would relay an entangled quantum state across a
distance that is not accessible using optical fibers only, due to unavoidable signal losses in the
communication channels. At shorter length scales, modular quantum computing schemes, which
are likely the
only
viable many-qubit near-term approaches, depend crucially on quantum
transducers—
devices that convert variations in a physical quantity, such as spin state or
superconducting flux, into a transmittable signal.
Finally, at the chip-scale level, large numbers
of quantum memories—devices or systems that can maintain a quantum state over long periods
of time—implemented, e.g., using trapped atoms or spin systems in solid state, need to be
interfaced using integrated, low-loss and fast on-chip optical networks in order to realize
integrated quantum repeaters.
QUANTUM ENTANGLEMENT
An entangled quantum state describes the joint state (condition) of two or more quantum objects or
fields that are statistically correlated in their measured properties, with correlations that are stronger
than possible according to classical physics. Entanglement is the essential resource that enables nearly
all quantum technology, but is very fragile, making it hard to create and maintain over long times and
across large distances.
A consensus in the scientific community is that the technologies needed for quantum computing
and quantum networking are closely intertwined, indicating that convergent approaches to these
challenges will be the most productive. For these reasons, it is the position of the community
represented by participants of the NSF workshop on “Quantum Interconnects” that accelerating
5
QuIC research is crucial for sustained development of a national quantum science and
technology program.
An important affiliated technology is quantum-enhanced sensing of a wide range of physical
factors: gravitation, electromagnetism and environmental factors as well as biomedical structure
and function. For quantum sensors to reach full capability, in many cases, interfacing them with
quantum memories and processors and distributing them across space for collective sensing will
be required. Quantum interconnects will play a crucial role in such distributed sensing
applications.
EXAMPLES of QuICs COMPONENTS:
communication channel
(optical, acoustic, microwave, etc.) between two quantum systems that
can be on the same chip or separated by large distance. Examples include an optical cavity,
waveguide or fiber connecting two quantum emitters, or cold microwave waveguide
connecting two superconducting-qubit processors;
quantum memory
(e.g., color center, trapped ion, all-photonic cluster state based) and the
associated interface to the communication channel;
quantum transducer
used to connect qubits of different kinds (acousto-optical, spin-photon,
spin-phonon, etc.), or of the same kind but at different energy (microwave-optical photon,
visible-telecom photon);
converter
between different qubit encoding schemes or degrees of freedom (e.g., polarization,
temporal, spectral encodings of photons);
small scale & application specific quantum computer,
e.g., quantum repeater, to extend the
reach of quantum communication channels;
entanglement sources
physical processes that create quantum-entangled states of two or more
matter-based or photonic qubits.
Combination of different elements of QuIC would enable, for example, links between different
processing regions in a quantum computing system in which data qubits are stored in memories
(based on, e.g., trapped ions), and transferred into an alternate form (e.g., superconducting
qubits) for fast quantum processing. Such hybrid systems will benefit from integrated approaches
to connecting classical systems with quantum systems, e.g., for delivery of optical signals to
trapped ion- and atom-based quantum computers/clocks/sensors/etc., and to enable efficient data
read out.
Finally, it is important to recognize that many information channels, such as an optical fiber or a
metallic stripline, largely act as a conduit that can carry both classical signals and quantum states
of the signaling medium under appropriate conditions. Thus, classical technologies and
quantum-enabled technologies live in a common technological ecosystem with large positive
feedback in both directions. For example, classical telecom technology has already provided
enormous acceleration of quantum optical communication research; at the same time, the
stringent needs of all-optical quantum processors have driven advances in building on-chip
reconfigurable multi-mode optical networks, which may benefit classical approaches to
information technology. Thus, the
dual-use
paradigm of technology innovation applies to
quantum-inspired developments.
6
III.A Modular Quantum Processors & Computers
Constructing a large-scale quantum processor is challenging because of the errors and noise that
are inherent in real-world quantum systems, as well as the practical engineering challenges that
emerge. One promising approach to addressing this challenge is to utilize modularity—a strategy
used frequently in nature and engineering to build complex systems robustly. Such an approach
manages complexity and uncertainty by assembling relatively small, specialized modules into a
larger architecture. Modern high-performance classical computers and data centers are
constructed by connecting thousands of computers, memories and storage units into an
interconnected network, over which complex computational tasks are distributed. These
considerations have motivated the vision of a quantum modular architecture, in which separate
quantum systems are incorporated into a quantum network via quantum interconnects
[4], [6]
.
In a modular architecture, the essential building block is the teleportation-based quantum gate,
which uses quantum entanglement to connect different modules and thereby implement
non-local quantum operations
[7]–[10]
. In order to connect the modules with each other to
perform distributed quantum computation, one has to be able to generate quantum entanglement
between pairs of modules to teleport quantum states or quantum gates. Critical figures of merit of
such inter-module entanglement generation are (1) the rate of entanglement generation, (2) the
fidelity of the generated entanglement, and (3) the reconfiguration of the pairs of modules
between which the entanglement is generated.
Protocols and Progress
Several protocols have been proposed and demonstrated for transporting quantum information
between two nodes. The first is the so-called pitch-and-catch protocol, where a flying qubit, such
as a photon, emitted by a stationary qubit (or reflected off a cavity holding a qubit) on the
transmitting end would carry the quantum state over the communication channel and transfer it
to another qubit on the receiving end
[11]
. Heroic experiments have been performed using
atomic qubits in high finesse optical cavities demonstrating this process
[12]
. However, the loss
in the photonic channel rapidly degrades the performance of this scheme, which makes it
impractical at optical frequencies. In superconducting circuits, it is possible to create very strong
coupling between the transmitting and receiving qubits with a microwave photon in a
transmission line connecting the two modules and featuring negligible loss over the short
communication distances involved
[13]–[16]
. Therefore, such a pitch-and-catch protocol is more
practical in these systems.
The second is a heralded entanglement generation protocol, where a pair of entangled qubits in
the two modules is first generated probabilistically using photon emission from the qubits and
the detection of emitted photons, then a deterministic teleportation of the qubit (or quantum gate)
is accomplished using the generated entanglement as a resource. In this protocol, first the
communication qubit on each module (such as a trapped ion, neutral atom, atom-like color center
in solid-state or quantum dot) emits a photon in such a way that a degree of freedom of the
photon (such as polarization, frequency, phase or time-bin, etc.) is entangled with the qubit. The
emitted photons are collected (with finite loss), interfere on a 50/50 beamsplitter, and are
detected at the outputs. The detection event signals a successful generation of entanglement
between the two qubits that emitted the photons. Although the successful execution of the
7
protocol occurs only probabilistically, success is heralded (i.e., confirmed) by detection of two
photons at the output of the beamsplitters, and reliable entanglement can be generated at
low-to-moderate rates
[9], [17]
.
There have been significant advances in generating entanglement between different modules
with improved efficiency and fidelity. In trapped-ion systems, the entanglement generation rate
has significantly improved from 10
-3
[18]
to ~200 events per seco
nd over the course of the past
12 years
[19], [20]
, which enables quantum teleportation between different quantum modules
[21], [22]
. The advances come from improving the efficiency of photon collection from atoms,
reducing photon loss in the channels, and using single-photon detectors with higher detection
efficiencies. Similar protocols have been demonstrated in neutral atoms
[12], [23]
, Nitrogen
Vacancy (NV) color centers in diamond
[24]
and quantum dots
[25]
. In order to ensure that a
modular quantum computer can be constructed, it is important to have fully functional quantum
computers as the modules, and the entanglement generation rate (quantum communication rate)
between the modules must be fast compared to the decoherence rate of the qubits in the modules.
Furthermore, efficient optical interconnects to the modules have to be compatible with quantum
computing within the modules. For instance, optical cavities can provide an optical interface to
atomic quantum computing modules
[26]
but it remains a challenge to integrate cavities with
neutral-atom quantum computing architectures based on Rydberg interactions
[27]
or trapped-ion
quantum computing architectures
[28]
. Recently efficient quantum optical interfaces have been
realized using integrated nanophotonic devices for both trapped neutral atoms
[29]
and diamond
color centers
[30]
.
In superconducting circuits, the pitch-and-catch protocol is indeed practical using a microwave
photon as an information carrier. The communication between two superconducting qubit
modules has been demonstrated by several research groups
[13]–[16]
. As long as the
communication channel has high quality, it should be possible to send quantum states, even
when the number of thermal photons in the channel is much larger than one
[31], [32]
.
Therefore, the current demonstrated approaches can be extended to connecting different dilution
fridges using high-quality thermal microwave links.
Challenges and Research Opportunities
Recently, proof-of-principle demonstrations of deterministic teleportation-based quantum gates
have been carried out in both superconducting-circuit and trapped-ion platforms
[33], [34]
. These
demonstrations show a promising path towards scalable modular quantum computing. However,
finding a technical development path to fully modular quantum computers interconnected via
quantum communication channels is an extremely challenging task, which requires substantial
advances in basic physical principles, device (qubit)-level advances, new protocols, integration
of modules and interfaces, and coherent operation across the modules. Here, we outline some of
the research directions towards the realization of scalable, modular quantum computers.
1. Improving quantum interfaces:
While the existing quantum interfaces between modules
have seen dramatic improvements, most systems still have not reached the regime where
connection between the modules can be utilized for reliable transfer of qubits within the
timescale required for distributed quantum computation. For the heralded scheme, we have to
continue to improve the entanglement generation rate so that it is comparable to the local
8
entangling gate operation rate within a module. While this is not a strict requirement for efficient
quantum computation, it means that the cost of distributing a quantum task across the modules
would not substantially constrain the execution of the computational task. Another topic worth
noting is that all quantum interconnects are not perfect in terms of the fidelity of the distributed
entanglement, or the success probability of the pitch-and-catch scheme. The errors in the
quantum interconnects must be minimized or corrected, so that the distributed quantum
computation can succeed with viable probabilities, i.e., so that distributing the computation
actually improves performance rather than degrading it. New protocols and implementation
strategies to overcome the errors in the communication channel need to be developed.
2. Integration of modules and interfaces:
Seamless integration of the communication
interfaces with the computational functions of the modules can introduce some challenges. For
example, in heralded entanglement generation protocols, the qubit-photon entanglement
generation protocols can lead to decoherence of nearby qubits storing information. For these
systems, novel integration approaches must be developed so that the communication and local
data processing can co-exist. For solid-state qubits (such as superconducting qubits) that use
photons in the microwave range of the electromagnetic spectrum, communication over
room-temperature channels becomes impractical. In order to take advantage of modules realized
outside the cryogenic environment, frequency up-conversion of the photonic qubit to the optical
spectrum is necessary. Quantum transduction techniques to reliably convert microwave photons
to optical photons is an important area of research for these applications.
3. Hybrid modular architectures and interconnects:
The need for modularity can also be
driven by the computational functions, where various qubit technologies provide opportunities
for executing tasks with different performance requirements. For instance, memory modules that
contain qubits with very long coherence times could be implemented on a different platform than
processing modules where fast gate times are essential. This potential tremendous advantage
comes with additional challenges. In order to take full advantage of such a hybrid modular
architecture it is important to develop interconnects capable of distributing entanglement
between different qubit implementations, for example, superconducting currents or charges,
color centers, neutral atoms, ions, or photons. The spectral characteristics of the photons that
couple to each of these systems – including the wavelength and bandwidth – can be very
different, by several orders of magnitude, leading to extremely inefficient inter-species
conversion in the absence of suitable quantum transducers.
4. Coherent operation of modular quantum computer and distributed algorithms
: Even if
local quantum computer modules and the needed quantum interconnects are adequately
integrated, distributed quantum computation will require operating every module in the system
with full quantum coherence among them. This poses challenges in designing and operating
phase-coherent control systems across the modules, as well as tracking the quantum phase of
every module in the system. Algorithm-level strategies for efficiently distributing the
computational task over the modular quantum computer based on the performance specifications
of various functional components that constitute the system is therefore an important area of
research.
9
Table 1 - Timeline and Milestones for Modular Processors
3-year
5-year
10-year
Homogeneous
Qubit-Qubit
Interconnects
Connection of two fully-functional
quantum computer modules with a
quantum interconnect. Inter-module
entanglement distribution rate better
than 10x decoherence rate and 1%
of the local gate rate.
Connection of four
fully-functional quantum computer
modules with a reconfigurable
quantum interconnect.
Intermodule entanglement
distribution rate better than 100x
decoherence rate and 10% of the
local gate rate.
Manufacturable quantum
computer modules with quantum
interfaces that can scale to over
100 modules. Intermodule
entanglement distribution rate
better than 1000x decoherence rate
and 100% of the local gate rate.
Transduction
with non-native photonic
channels
Demonstration of tunable quantum
interconversion between disparate
photons (e.g., tunable
visible-to-telecom or
optical-to-microwave, including
bandwidth conversion).
Demonstration of interconversion
between microwave and optical
photons with high fidelity, SNR,
and bandwidth.
Connection to quantum internet.
Heterogenous
Qubit-Qubit
Interconnects
Interface between atom- and
solid-state-based memory to
non-native flexible/tunable
photonic channel.
Entanglement between two
different types of quantum
processor (various atomic and
solid-state memory qubits).
QC performance in a multi-node
cluster that goes beyond the
capability of any individual node,
and also beyond those individual
nodes connected by a classical
network.
III.B Quantum Internet
The quantum internet describes a collection of distributed quantum nodes, separated by a range
of distances over which one desires to perform some quantum communication protocol that can
support, for example, distributed quantum computation (Sect. III.A) or distributed sensing (Sect.
III.C). For an accessible overview, see
[35]
. There are now numerous quantum communication
and cryptographic protocols identified, including security distribution for encryption
[36]–[43]
,
quantum-certified random number generation in the form of random number beacons and
personal devices, secret-sharing
[44], [45]
, quantum fingerprinting
[46]–[48]
and other
multi-party computation protocols, such as secure quantum voting, byzantine agreements, and
multi-party private auctions
[49]
. Of particular relevance is the possibility of “blind” quantum
computation
[50], [51]
, whereby a remote user can program a quantum computer without
revealing to its owner the algorithm that is run or the computational result, and distributed
quantum processing, whereby two or more quantum computers share entanglement to enable
them to act as a single larger processor. Because of the distances involved (0.1- 1,000 km),
optical photons must be used.
Another key aspect of a fully functioning quantum internet is the potential for unconditional
information security—a feature of using quantum information that is not possible with classical
information processing. A further benefit of using quantum secured information will be that the
lifetime of the security is “infinite”; it will be secure against any advances in computation
capability that may occur in the future. There have been many cryptographic tasks in which
quantum-secured versions have been conceived. For all of these tasks, quantum interconnects are
required because of the need to preserve entangled quantum states.
10
To realize fully the potential of a quantum internet, significant convergent work is still needed to
improve the physical hardware. Theoretical work is also required to develop efficient
information processing techniques to preserve the quantum information and determine the most
robust and secure network connectivity. The development of quantum-secured devices and
protocols could transform the cryptographic landscape.
There are two primary channels over which to transmit the photons: optical fiber and free space.
Each of these has challenges and opportunities. The former can leverage the enormous existing
network of telecommunication fibers, though then the photons need to be in the
telecommunications band to avoid excessive losses. Even still, the transmission through such a
fiber will drop exponentially with length, so that direct transmission of quantum states becomes
highly inefficient beyond about 100 km. Free-space optical communication is far less well
developed, but has the advantage that it can operate over a much larger range of wavelengths,
and the losses (due to diffraction) grow only quadratically. Typically, greater care is needed to
reduce background light in free-space quantum communication channels; also, there is typically
the added challenge of stabilizing the free-space coupling using pointing and tracking methods,
and possibly adaptive optics to reduce the effects of turbulence. Nevertheless, many of these
challenges have been overcome in a series of free-space quantum communication
demonstrations, between mountains
[52]
,
[53]
, over water
[54]
within cities
[55]–[57]
, from
airplanes
[58]
, balloons, and drones
[59]
and even using satellites in low-earth orbit
[60], [61]
.
While the achieved transmission rates in these experiments might have greatly exceeded what
would have been possible using fiber channels—in one case by nearly 20 orders of magnitude
[60], [61]
, they are still often very low, and methods such as multiplexing or employing
higher-dimensional states (see below) may be needed to achieve practical rates.
Challenges and Research Opportunities
To build a fiber-based global network capable of distributing quantum entanglement, there are
two main challenges that have to be overcome. First, optical attenuation during fiber
transmission leads to an exponential decrease in the entangled-pair distribution
rate
. Second,
operational errors such as channel errors, gate errors, measurement errors, and qubit memory
errors can severely degrade the
quality
of the distributed entanglement, which at best reduces the
quantum advantage and at worst completely eliminates it, e.g., a quantum cryptographic key may
be completely insecure!
1. Quantum repeaters:
To overcome these challenges and extend the range of fiber-based
entanglement distribution beyond a few hundred kilometers, quantum repeaters (QRs) are
required, but are not yet available. Depending on the tools used for suppressing these
imperfections, the quantum information community has identified the following three
generations of QRs: The first generation of QRs
[62], [63]
uses heralded entanglement
generation and heralded entanglement purification, which can tolerate more errors but requires
two-way classical signaling over the entire chain of QRs; such signaling then implies that the
requisite quantum memory lifetimes/coherence times must be substantially longer than the
round-trip communication times. The second generation of QRs introduces quantum encoding
and classical error correction to replace the entanglement purification with classical error
correction, handling all operational errors
[64], [65]
, which is more demanding in physical
11
resources but requires only two-way classical signaling between neighboring repeater stations,
and consequently further improves the quantum communication rate. The third generation of
QRs would use quantum encoding to deterministically correct both photon losses and operation
errors
[66], [67]
. By entirely eliminating two-way classical signaling, the third generation of QRs
would promise extremely high entanglement distribution rates that can be close to classical
communication rates, limited only by the speed of local operations, in turn limited by, e.g.,
photon source rates, detector saturation rates and timing jitter, etc.
One important benchmark for QRs is the repeater-less bound
[68], [69]
, which imposes the
fundamental limit of the direct quantum communication protocols. Recently, there have been
significant advances in experimentally demonstrating key elements of a QR in an integrated
system. An important recent highlight is the experimental demonstration of memory-enhanced
quantum communication surpassing repeterless-less bound in proof-of-concept laboratory
setting, using a solid-state spin memory associated with Silicon Vacancy (SiV) color center
integrated in a diamond nanophotonic resonator
[30], [70]
. This paves the way towards the
demonstration of a full quantum repeater, which in turn will enable scalable large-scale quantum
networks.
2. Quantum memories:
The major challenge for the first generation of quantum repeaters is the
development of long-lived quantum memories with efficient optical interfaces, such as
addressable color center nuclear spins with integrated nanophotonics
[71]
, trapped-atomic qubits
with Purcell-enhanced emission
[12], [19], [23]
, or superconducting circuits with
microwave-to-optical transduction. In addition, the availability of efficient photon detectors with
low dark counts is crucial, with significant advances needed in reducing the cost, integration, etc.
3. Spectral-temporal encoding:
It is now generally recognized that practical rates of
entanglement distribution can likely be achieved only by employing high levels of channel
multiplexing (e.g., spectral, temporal, spatial) to enhance success probabilities; for instance,
quantum signals are simultaneously sent at multiple nearby wavelengths or in multiple time bins.
Although each spectral or temporal channel has some probability of failure or loss, the likelihood
that all would be unsuccessful decreases with the number of multiplexed channels. However, one
needs a mechanism to demultiplex into a single spectral-temporal mode; alternatively, they are
each coupled to their own quantum memory qubit, but then some mechanism for identifying and
coupling a particular pair of successfully “loaded” quantum registers is needed. The use of such
temporal multiplexing has recently enabled a 30x enhancement in the success rate of a
two-photon quantum communication protocol
[72]
; the advantages become exponentially larger
for protocols requiring higher numbers of qubits. The benefits of multiplexing arise only if the
quantum interconnects that implement the multiplexing and demultiplexing have high fidelity
and low loss.
Another emerging strategy is to use qudits, the higher-dimensional counterparts to qubits, e.g.,
using three time bins to encode numbers 0, 1, and 2, and arbitrary superpositions thereof. Just as
it does for classical communication, such encoding increases the information-carrying capacity
of a photon by log(
d
) where
d
is the dimensionality, at the expense of more complex
measurements and manipulations. Finally, encoding multiple qubits (or even their
higher-dimensional counterparts, qudits) onto a single photon can yield intrinsic robustness to
loss: because all of them are guaranteed to be lost or transmitted together, the net success
12
probability can be greatly enhanced. For instance, the probability that a channel with 99% loss
will successfully transmit a 3-photon three-qubit state is only
in comparison, a
;
1
0
6
single-photon three-qubit state experiences the loss only once, i.e., with a 1% success
probability. The concept of qubit entanglement also generalizes to hybrid entanglement
[73]
,
between different degrees of freedom of a single photon, e.g., polarization and spatial mode, and
hyper-entanglement
[74]
, between multiple corresponding degrees of freedom of two photons,
e.g., polarization and time bin [71], or time-bin and frequency-bin
[75], [76]
. One critical need is
a method to transduce such higher dimensional quantum states into qubit memories.
4. Efficient measurements:
Finally, all three generations of QRs can be greatly enhanced by
including efficient quantum non-demolition (QND) measurements
[77]
– a measurement that
records the successful passing of a photon without observing it or changing its quantum state. In
this way, any memory can be converted to a
heralded
quantum memory, which enables one to
know whether a photon has successfully been transmitted down the entire length of a
communication channel; such knowledge greatly reduces the required number of quantum
memories, since one is only needed in cases where the quantum signal was successfully
transmitted through the optical channel.
With the emerging demonstrations of quantum repeaters, it will be important to optimize them to
overcome realistic imperfections through use of robust architecture and encoding. It is also
urgently needed to develop novel quantum network applications and appropriate corresponding
performance metrics, such as entanglement fidelity, throughput, latency, resource overhead, etc.
These performance metrics should also guide the device design and fundamental investigation of
relevant physical platforms.
Table 2 - Timeline and Milestones for Quantum Internet
3-year
5-year
10-year
Major Achievements
Detected photonic entanglement
rate beyond 10
8
ebits/second
Quantum repeaters with error
correction against operation errors
Forward error-corrected photonic
quantum states for one-way
repeaters
Distance and Rates
Entangled quantum memory over
> 10 km distance
Verifiable quantum entanglement
distribution over >100 km at > 1
M-ebits/sec; distillable
entanglement rates >100k-ebits/sec
Quantum networks reaching
transcontinental scales of
thousands of km
Capability of Repeater
Nodes
Quantum repeater node via
entanglement swapping beyond
direct transmission
Active error correction against
operation errors; many-party
protocols demonstrated in fielded
quantum networks
Full error correction against loss
and operation errors; hybrid nodes
with different functions.
Number of Repeater
Nodes
Quantum networks with >3
memory nodes and >10 user nodes
Networks of >10 quantum
repeaters/quantum computers in
superposition
Networks with >100 of repeater
nodes
Free-Space Quantum
Network
Constellation of 3-5 mobile
platforms demonstrated
Entanglement swapping between
space-earth
Transcontinental entanglement
distribution via quantum
memory-enabled satellite
Quantum Network
Applications
Quantum-secured communication
rate exceeding 1 MB/sec over 100
km
Network-based quantum metrology
Blind Quantum Computing
13
III.C Quantum-Enhanced Sensors
Quantum-sensing technology has made significant progress over the last few decades and has
given rise to atomic clocks
[78]
, magnetometers
[79]
, and inertial sensors
[80]
that operate at the
standard quantum limit (SQL). With the tremendous advances in the theoretical and
experimental aspects of quantum information science over the last decade, new quantum
resources, such as quantum memories and entangled particles, can now be harnessed to enhance
further the performance of quantum sensors. Also known as quantum metrology,
quantum-enhanced sensing is aimed at taking advantage of these emerging quantum resources to
outperform the SQL and achieve unprecedented sensing performance. As a remarkable instance
of quantum-enhanced sensing, the Laser Interferometer Gravitational-wave Observatory (LIGO)
utilizes non-classical squeezed light to enable a measurement sensitivity below the SQL
[81]
.
Quantum-enhanced sensing has also been proven to be a powerful paradigm for a variety of
scenarios including magnetic sensing with quantum memories
[82]
, quantum-illumination target
detection
[83]
, sub-SQL atomic clocks
[84]
, and nano-mechanical sensors
[85]
.
Most existing quantum-enhanced sensing demonstrations leverage non-classical resources to
improve the measurement performance at a single sensor, but many real-world applications rest
upon a network of sensors that work collectively to undertake measurement tasks. Notable
examples for such a setting include wireless sensor networks
[86]
, phased arrays
[87]
, and
long-baseline telescopes
[88]
. In this regard, the quantum internet presents unique opportunities
for quantum sensors to utilize shared entanglement to boost the performance in networked
sensing tasks. The following section discusses the concept, promising research avenues, and
application space for interconnected quantum sensors.
Interconnected Quantum Sensors
Extensive studies have been dedicated to using bipartite (two-party) entanglement as a resource
to overcome the SQL at a single sensor. In one step forward, recent theoretical works on
quantum-enhanced sensing based on multipartite entanglement show that interconnecting
distributed quantum sensors to form an entangled sensor network can probe global parameters at
the Heisenberg limit, i.e., at an estimate uncertainty that scales favorably compared to the scaling
for a network of independent sensors. Specifically, Ref.
[89]
proposed a quantum network of
clocks that enjoys boosted precision and security over conventional classical clock networks.
More generally, two theoretical frameworks for distributed quantum sensing based on,
respectively, discrete-variable
[90], [91]
and continuous-variable multipartite entanglement have
been formulated
[92]
. On the experimental front, a proof-of-concept distributed quantum sensing
experiment demonstrated the utility of multipartite continuous-variable entanglement for
enhancing the measurement sensitivity for estimating global phase shifts. To demonstrate the
prospect for interconnected quantum sensors in real-world applications, Ref.
[93]
reported an
entangled radiofrequency (RF)-photonic sensor network in which distributed RF sensors harness
their shared multipartite entanglement to enhance the precision of estimating the properties, e.g.,
the angle of arrival, of an incident RF wave across all sensor nodes.
In the context of a quantum internet, quantum sensors distributed over a distance will be able to
establish high-fidelity entanglement to achieve measurement sensitivities beyond the SQL.
14
Potential application scenarios for large-scale entangled quantum sensor networks would
encompass high-precision astronomical observation
[94]
[88]
environmental and health
monitoring, positioning, navigation, and timing. Two possible means of building up
entanglement shared by quantum sensors are the following: 1) a matter-based quantum sensor
first entangles with a photonic mode, which is then transmitted through the quantum internet
equipped with quantum repeaters to ensure high-rate long-distance entanglement distribution.
Entangling photonic quantum measurements are performed at the destination quantum repeater
nodes to establish multipartite entanglement between matter-based quantum sensors. 2) As an
alternative method to form an entangled quantum sensor network, photonic multipartite
entanglement tailored for a specific networked sensing task is first produced by a photonic
quantum chip at a central node. Each arm of the photonic entangled state is then transmitted to a
quantum sensor located in the quantum internet. As in the matter-based quantum sensor network,
the quantum internet takes advantage of quantum repeaters to compensate for entanglement
distribution loss so that high-fidelity photonic multipartite entanglement is maintained. At each
quantum sensor node, a high-efficiency low-noise quantum transducer converts the information
carried by the object of interest into the photonic domain so that quantum measurements on the
photonic multipartite entanglement unveil the global property of the interrogated object.
Challenges and Research Opportunities
Apart from the need for a quantum internet as a backbone, a number of technical accelerations
will be critical for the construction of entangled quantum sensor networks.
1. Device concepts:
Matter-based quantum sensor networks are comprised of any of a diverse
range of useful sensors. Examples, not exhaustive, include sensors of massive particles, photons,
magnetic fields, electric fields, temperature, gravity, pressure, and chemical processes. Such
sensor networks require efficient light-matter interfaces or interconnects to create entanglement
between quantum sensors and photonic modes. In an ideal situation, establishing entanglement
between multiple matter-based quantum sensors at the quantum repeaters calls for deterministic
multipartite Bell measurements with near-unity efficiency. Such a measurement can be realized
by first transferring the quantum states of photons into those of solid-state qubits, followed by
fault-tolerant quantum computation on a special-purpose small-scale quantum computer. As a
necessary ingredient, the outcomes of the Bell measurements need to be communicated to
different quantum-sensor nodes in realtime, by fast electronic processing and a low-latency
classical communication network. Since most matter-based quantum sensors operate with
readout in the visible to the near-infrared spectral range, high-efficiency low-loss quantum
frequency converters are required to shift the wavelengths of photons into the telecommunication
window for long-haul communication via a quantum internet.
The device requirement for the photonic quantum sensor network encompasses envisaged
programmable photonic quantum chips (PQCs) to generate appropriate photonic multipartite
entangled states. Each PQC would entail low-loss waveguides and couplers, high Q-factor ring
resonators, and single quantum emitters that provide needed (‘non-Gaussian’) resources for
universal quantum information processing. The produced photonic multipartite entangled states
need to be inserted into optical fibers through couplers with near-unity transmissivity. The PQCs
should also provide classical controls to pre-compensate the dispersion and other imperfections
incurred in the transmission. At each quantum sensor node, high-efficiency quantum transducers
15