Quantum data processing system

Abstract

Methods, systems, and apparatus for quantum data processing. In one aspect, the method includes storing multiple copies of the quantum state in a quantum memory, including, for each copy of the quantum state, i) probing a target system with an initialized quantum sensor to obtain an evolved quantum state of the quantum sensor, ii) converting the evolved quantum state of the quantum sensor into a quantum state of a quantum buffer, iii) logically encoding the quantum state of the quantum buffer into a quantum error correction code, and iv) moving the logically encoded quantum state of the quantum buffer to a quantum memory, loading the multiple copies of the quantum state in the quantum memory into a quantum computer, processing the multiple copies of the quantum state by the quantum computer to obtain a refined quantum state, and measuring the refined quantum state to determine a characteristic of the target system.

Description

Technical Field

[0001] This specification relates to quantum sensing and quantum computing.

Background Art

[0002] A quantum sensor is a quantum device that uses the sensitivity of a quantum system to disturbances to measure physical quantities or parameters including magnetic or electric fields, time, frequency, rotation, temperature, or pressure. Quantum devices are characterized by quantized energy levels and can include superconducting or spin qubits, neutral atoms, or the electronic, magnetic, or vibrational states of trapped ions. In conventional quantum sensing protocols, the quantum sensor is initialized and interacts with the signal of interest. The quantum state of the quantum sensor is then transformed and / or read out. Phase estimation or parameter estimation techniques are applied to the readout data obtained from a series of such readouts to reconstruct the physical quantity of interest.

Summary of the Invention

Means for Solving the Problems

[0003] This specification describes a quantum data processing system.

[0004] In general, one innovative aspect of the subject matter described in this specification is, for each copy of a quantum state, i) a step of probing a target system with an initialized quantum sensor to obtain an evolved quantum state of the quantum sensor; ii) a step of converting the evolved quantum state of the quantum sensor into a quantum state of a quantum buffer; iii) a step of logically encoding the quantum state of the quantum buffer into a quantum error correction code; iv) a step of moving the logically encoded quantum state of the quantum buffer into a quantum memory; a step of storing multiple copies of the quantum state in the quantum memory; a step of loading the multiple copies of the quantum state in the quantum memory into a quantum computer; a step of processing the multiple copies of the quantum state by the quantum computer to obtain a purified quantum state; and a step of measuring the purified quantum state to determine a characteristic of the target system.

[0005] Other implementations of these aspects include corresponding computer systems, devices, and computer programs recorded on one or more computer storage devices configured to perform the actions of the methods. A system of one or more classical computers and / or quantum computers can be configured to perform particular operations or actions by installing in the system software, firmware, hardware, or combinations thereof that cause the system to perform the actions during operation. One or more computer programs can be configured to perform particular operations or actions by including instructions that, when executed by a data processing apparatus, cause the apparatus to perform the actions.

[0006] The above and other implementations can each optionally include one or more of the following features, alone or in combination. In some implementations, the quantum sensor is configured to maintain quantum coherence.

[0007] In some implementations, the evolved quantum state of the quantum sensor encodes the characteristics of the target system when probing.

[0008] In some implementations, the evolved quantum state of the quantum sensor includes the state of multiple qubits, or the state of bosonic or photonic modes.

[0009] In some implementations, probing the target system to obtain the evolved quantum state of the quantum sensor is performed with a finite signal-to-noise ratio.

[0010] In some implementations, the quantum sensor is configured to perform full or partial quantum error correction on the evolved quantum state of the quantum sensor.

[0011] In some implementations, the quantum sensor includes a first computing medium, the quantum buffer includes a second computing medium, and the second computing medium is different from the first computing medium.

[0012] In some implementations, logically encoding the quantum state of the quantum buffer into a quantum error correction code includes applying a unitary encoding quantum circuit to the quantum state of the quantum buffer or performing a state injection technique.

[0013] In some implementations, the quantum error correction code includes an operation performed by a quantum computer to obtain a purified quantum state or a code distance that depends on at least one of the expected durations required to store multiple copies of the quantum state.

[0014] In some implementations, the quantum error correction code is a quantum buffer.

[0015] In some implementations, processing multiple copies of the quantum state to obtain a purified quantum state includes performing a linear distillation technique to purify multiple copies of the quantum state.

[0016] In some implementations, the linear distillation technique includes quantum state distillation, virtual state distillation, or a quantum principal component analysis algorithm.

[0017] In some implementations, determining the characteristics of the target system by measuring the purified quantum state includes providing the measurement results to a quantum machine learning system to learn the characteristics of the target system.

[0018] In some implementations, the target system includes a temporary target system.

[0019] The subject matter described herein can be implemented in a particular manner so as to realize one or more of the following advantages.

[0020] In conventional quantum data processing, a quantum sensor interfaces with a classical system. This forces early use of the measurement and destroys the quantum information. Thus, subsequent data purification / extraction or processing steps are exponentially costly depending on the copy number.

[0021] To reduce these costs, the presently described quantum data processing system includes a quantum sensor that interfaces with a quantum device. The quantum device implements quantum conversion and quantum storage techniques via repeated multiple data collections and exceeds the capabilities of quantum sensors that are only coupled to classical computers. In particular, the presently described quantum data processing system achieves an exponential advantage in the number of times measurements have to be made based on the size of the quantum sensor. This exponential advantage can be realized even when both the quantum memory and the quantum processor are noisy. Thus, the presently described techniques are particularly suitable for implementations that use near-term quantum computing devices, such as noisy intermediate-scale quantum (NISQ) devices.

[0022] In addition, compared to conventional quantum data processing systems, the presently described quantum data processing systems can improve sensitivity and the ability to remove noise from signals from quantum sensors.

[0023] In addition, unlike conventional quantum data processing systems, the presently described quantum data processing systems can collect and process quantum data in applications of temporary sensing where only limited data collection time may be available.

[0024] In addition, the presently described quantum data processing systems are modular and can have different components changed or upgraded as needed to suit the needs of a particular application.

[0025] In addition, the presently described quantum data processing systems can be used in a variety of applications, such as improving the identification of chemical substances, improving the properties of quantum materials, and enabling more accurate sensing in imaging applications, including medical imaging applications such as MRI.

[0026] Details of one or more implementations of the subject matter of this specification are set forth in the accompanying drawings and the description below. Other features, aspects, and advantages of the subject matter will become apparent from the description, the drawings, and the claims.

Brief Description of the Drawings

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[0028] Like reference numerals and names in the various drawings indicate like elements.

[0029] Overview In this specification, quantum data processing methods and systems for collecting and processing quantum data that are exponentially faster than classical processing for quantum data are described. The data collection step is performed a fixed number of times or continuously. During the data collection step, a quantum sensor probes a target system and collects data from the target system. The data is transferred to a quantum buffer compatible with logical encoding and encoded with a quantum error correction code. The encoded data is then shuttled to a quantum memory. When a sufficient number of copies of data are collected in the quantum memory, the quantum memory is loaded into a quantum computer. The quantum computer performs quantum data processing to purify or further refine the data. The purified data can then be used to measure and extract information about the target system and supplied to a classical computer or an experimenter for further analysis.

[0030] FIG. 1 is a diagram 100 comparing a conventional process 102 for collecting and processing quantum data and a presently described quantum-enhanced process 104 for collecting and processing quantum data. In the conventional process 102, a quantum sensor interfaces with a classical machine that executes classical algorithms. The classical machine can store and process classical information. In the quantum-enhanced process 104, a quantum sensor interfaces with a quantum machine that executes quantum algorithms. The quantum machine can store and process quantum information.

[0031] In step (a), experiments are performed. Each experiment involves probing a target physical system using a quantum sensor, as detailed below with reference to FIG. 2. The target physical system can be a real-world system of interest, such as a molecule, virus, DNA, planet, or black hole.

[0032] In some implementations, each experiment generates a physical quantum state ρ. In these implementations, the purpose of data processing is to learn some property of ρ, as shown in step (b). In the conventional process 102, multiple copies of ρ are measured separately to obtain classical measurement data. The classical measurement data is stored in classical memory. The classical computer processes the classical measurement data to output a prediction of the property of ρ. In the quantum enhanced process 104, the quantum state ρ can coherently modify the quantum information stored in the memory of the quantum machine. A copy of ρ is stored in quantum memory as quantum data. Quantum memory is generally a memory that stores quantum states that may be in a superposition state. In contrast, classical memory stores states only as binary states. The quantum machine processes the quantum data, performs measurements on the quantum memory, and outputs a prediction of the property of ρ. In some tasks, it can be shown that the number of experiments required to learn the target property of ρ is exponential in n when using the conventional process 102, but only polynomial in n when using the quantum enhanced process 104. In appropriately defined tasks, exponential quantum advantage can be achieved using a simple protocol of storing two copies of ρ in quantum memory and performing an entangling measurement.

[0033] In other implementations, each experiment is the evolution of a quantum state under a physical process ε. In these implementations, the purpose of data processing is to learn some property of the physical process ε, as shown in step (c). In the conventional process 102, the classical machine specifies the input state to ε using a classical bit string and obtains classical measurement data. In the quantum enhanced process 104, the evolution ε coherently modifies the memory of the quantum machine, the input state to ε is entangled with the quantum memory of the quantum machine, and the output state is coherently retrieved by the quantum machine. In these implementations, the quantum enhanced process 104 achieves a similar exponential advantage.

[0034] Exemplary Operating Environment FIG. 2 is a block diagram of an exemplary quantum data processing system 200 for performing the presently described quantum enhanced data processing techniques. The exemplary quantum data processing system 200 is an example of a system implemented as classical and quantum computer programs on one or more classical computers and quantum computing devices located in one or more locations that can implement the systems, components, and techniques described herein.

[0035] The exemplary quantum data processing system 200 includes one or more quantum sensors, such as quantum sensor 204, a quantum buffer 208, a quantum memory 214, a quantum computer 216, and a classical or quantum computer 218. A quantum sensor is a quantum device configured to probe a respective target system, such as target system 202, and collect data 206 from the target system. The target system 202 is a system of interest, such as a system in which a physical quantity or parameter is to be estimated, and can vary based on the quantum data processing task performed by the system 200. The target system 202 and the physical quantity or parameter can be either quantum or classical. For example, the data collected by the quantum sensor 204 can be generated by a classical process. In such a case, by implementing the techniques described herein, the characteristics of such a classical process can be determined exponentially faster even though the source data is classical. The exemplary target system will be described in more detail below with reference to FIG. 4.

[0036] To probe the target system 202, the quantum sensor 204 interacts with the target system 202, and the quantum state of the quantum system included in the quantum sensor 204 (hereinafter referred to as the quantum state of the quantum sensor 204) evolves for a predetermined sensing time. During the evolution, the state of the quantum sensor 204 becomes dependent on the physical quantity or parameter of interest and reflects the state of the target system 202. In this way, the quantum sensor 204 collects data 206 from the target system 202, and the data 206 is the evolved quantum state of the quantum sensor 204. In some implementations, the data 206 can be collected with a finite signal-to-noise ratio. In some implementations, the quantum sensor 204 can implement full or partial quantum error correction to improve its sensing ability or data retention ability. In some implementations, the quantum sensor 204 can maintain quantum coherence.

[0037] The type of the quantum sensor 204 included in the quantum data processing system 200 depends on the target system 202 and the physical quantity or parameter of interest. For example, for magnetic measurement, electrical measurement, temperature measurement, and chemical sensing applications, the quantum sensor 204 can be a solid-state quantum sensor including nitrogen vacancies in diamond (either isolated or distributed in a network). Other exemplary quantum sensors include superpolarized spins in gases, nuclear spins of chemical species in solution, or cavity modes used for sensing photonic states or detecting exotic particles.

[0038] As a specific example, in some implementations, the target system 202 can be an unknown metabolite, and the physical quantity / property can be the structure of the unknown metabolite. In this example, the structure of the unknown metabolite can be determined through signatures related to spin magnetization, electronic or vibrational excitation, or charge transport, and the quantum sensor can include a hyperpolarized gas suitable for spin transport, nitrogen vacancies in diamond with sufficient spatial resolution, or a nanomechanical sensor for vibrational measurement.

[0039] As another example, in some implementations, the target system can be any system in which the density profile inside an unknown system is determined, such as imaging inside a cave, a container, or a building. In this example, the physical quantities to be determined can include the amount, distribution, and type of matter, as well as material properties such as density or rigidity. The quantum sensors can include quantum sensors sensitive to gravitational effects, such as advanced atomic interferometers or atomic fountains that use quantum effects to sense the gravity between different spatial positions of atoms. The quantum data processing system can improve the sensitivity and capabilities of these sensors.

[0040] In some implementations, the system can include a plurality of quantum sensors that probe the target system 202 in parallel. By using a plurality of quantum sensors to probe the target system 202 in parallel, especially when performing sensing on multiple copies of the same target system, such as many copies of a molecule, the time the state is held in memory can be shortened and the sampling rate can be improved. Alternatively, or in addition, the plurality of quantum sensors can include different types of quantum sensors. For example, by collecting complementary data in parallel from different types of sensors, the capabilities of the quantum data processing system can be improved. For example, the system can become capable of extracting more accurate and insightful information, and thus capable of calculating improved estimates of physical properties and parameters, enabled by the structure and workflow of the quantum data processing system.

[0041] In a conventional quantum data processing system, i.e., a system different from the quantum data processing system described herein, the quantum state of the quantum sensor 204 evolves during a predetermined sensing time, and after collecting data 206 from the target system, the evolved quantum state of the quantum sensor 204 is measured. The target system 202 is repeatedly probed by the quantum sensor 204 during the total available measurement time, and an estimated value of the physical quantity or parameter of interest is inferred from the accumulated measurement data through classical calculations. Therefore, quantum information is destroyed early in the process, and subsequent data purification / extraction or data processing is exponentially costly depending on the number of probes.

[0042] To avoid these costs, the quantum data processing system 200 transfers the data 206 collected by the quantum sensor 204 to the quantum buffer 208. The quantum buffer 208 is a quantum computing device configured to logically encode quantum information. For example, the quantum buffer 208 can be a superconducting computer including superconducting qubits, an ion trap quantum computer, or a quantum computer including cluster state photonic qubits.

[0043] Since the quantum sensor 204 and the quantum buffer 208 can be different quantum devices including different quantum media, the devices can operate at different energy scales. For example, in some implementations, the quantum sensor 204 can provide data as the state of a boson cavity mode, while the quantum buffer 208 can include superconducting qubits. Therefore, to transfer the data 206, the quantum data processing system 200 is configured to perform a quantum transformation on the data 206 collected by the quantum sensor 204 and convert the data 206 into converted data 210 in an appropriate format.

[0044] Certain conversions performed by the quantum data processing system 200 may depend on and vary with the types of the quantum sensors 204 and quantum buffers 208 included in the quantum data processing system 200. For example, the quantum data processing system 200 may perform a conversion from microwave to optical to convert data from the optical photon state of the quantum sensor 204 to the superconducting quantum state of the quantum buffer 208. As another example, the quantum data processing system 200 may perform an optical-ion conversion for an ion trap quantum buffer, a cavity mode-superconducting qubit conversion for a superconducting quantum buffer, or a cavity mode-photonic qubit conversion for a quantum buffer including cluster state photonic qubits. In some implementations, the conversion may be performed with limited fidelity.

[0045] In some implementations, the quantum data processing system 200 logically encodes the conversion data 210 in the quantum buffer 208 into a quantum error correction code, generating logical encoded data 212. Encoding the conversion data 210 accommodates the storage of multiple copies of the probed data and subsequent calculations on the probed data. In some implementations, the quantum data processing system 200 can logically encode the conversion data 210 by applying a unitary encoding circuit or a state injection technique. In these implementations, the logical encoding can have a fidelity limited by the computational operations performed to apply the unitary encoding circuit or the state injection technique.

[0046] The quantum memory 214 is configured to store the logically encoded data 212 obtained from the quantum buffer 208. In some implementations, for example, when computational resources are limited, the quantum error correction code may be the quantum buffer itself. Exemplary logical encoding and quantum memory systems implementable by the quantum data processing system 200 include unitary encoding into a surface code, state injection into a surface code, direct encoding or injection into a quantum LDPC code, injection into an LDPC or higher rate code following injection into a surface code, or direct transfer from a logical sensor to a logical code state. The quantum memory can be, for example, an optical quantum memory such as a cavity-based quantum memory or a medium-based quantum memory (e.g., an atom, ion, or molecule-based memory). It should be understood that many examples of quantum memories may be used alternatively.

[0047] In some implementations, the code distance of the code used by the quantum data processing system can be determined, for example, by subsequent calculations performed on the data by the quantum computer 216 as described hereinafter, and / or the expected waiting time required to store a sufficient number of state copies in the quantum memory 214. For example, the code distance can be determined by, in addition to the required computation time, the waiting time until a copy of the quantum state is received in a given protocol. For example, if 10 copies of the quantum state are required and the calculation is expected to take a certain amount of time, using the physical error rate of the device and the threshold of the code, the required code distance can be calculated from these elements to safely ensure that the information does not decay within the computer at that timescale and for that operation. In some implementations, the code distance d can scale as d ~ log(expected waiting time + computation time).

[0048] The quantum memory 214 is configured to store the logically encoded data 212 obtained from the quantum buffer 208. For example, as described in more detail below with reference to FIG. 3, the quantum data processing system 200 can repeatedly probe the target system 202 to collect multiple copies of the evolved quantum state of the quantum sensor 204 (as used herein, a copy of the evolved quantum state is understood to mean the quantum state obtained after the quantum sensor 104 is reset and / or initialized and interacts with the target system 102 for a predetermined sensing time to obtain the evolved quantum state of the quantum sensor). Each copy can be transformed and logically encoded before being stored in the quantum memory 214.

[0049] Once a predetermined number of copies of the evolved quantum state of the quantum sensor 204 are stored in the quantum memory 214, the stored data 220 can be loaded into the quantum computer 216 for processing. The predetermined number of copies depends on and can vary according to the operations to be performed on the data by the quantum computer 216.

[0050] The quantum computer 216 is configured to process the data received from the quantum memory 214, for example, by applying a quantum algorithm. In some implementations, the quantum computer 216 can purify the data received from the quantum memory 214. For example, the quantum computer can perform quantum data extraction on the data using linear distillation techniques such as, for example, quantum state distillation, virtual state distillation, or quantum principal component analysis (qPCA). The data extraction step achieves an exponential advantage over conventional methods in terms of the number of copies that need to be recorded to perform this extraction. An exemplary quantum computer 314 for processing the data received from the quantum memory 214 will be described later with reference to FIG. 3.

[0051] The quantum data processing system 200 can perform measurements on the extracted quantum data, obtain measurement data 222, and extract relevant information. The measurement data 222 can be provided to a classical or quantum computer 216 for further analysis, for example, to estimate a physical quantity or parameter of interest. In some implementations, the extracted information can be provided as an input to a quantum machine learning system included in a classical or quantum computer 218 to learn characteristics about the data. In FIG. 2, the classical or quantum computer 216 is shown as a separate device from the quantum computer 216, but in some implementations, the system 200 can include one computing device configured to perform the operations described above with reference to the quantum computer 216 and the classical or quantum computer 218.

[0052] In some implementations, the quantum data processing system 100 can be included in or applied to a communication or quantum internet setting. For example, the quantum data processing system 200 can operate on data received from a quantum internet, a quantum network, or a quantum repeater along a quantum network. In these implementations, quantum communication protocols can also be included. In such a setting, the quantum data processing system 200 can be used to recover from errors with additional effects beyond the code distance of the original message.

[0053] FIG. 3 shows an exemplary classical / quantum computer 300 for performing some or all of the classical and quantum operations described herein, such as quantum computer 216, and the operations described above with reference to classical or quantum computer 218. The exemplary classical / quantum computer 300 includes an exemplary quantum computing device 302. The quantum computing device 302 is intended to represent various forms of quantum computing devices. The components, their connections and relationships, and their functions shown herein are merely exemplary and are not intended to limit the implementations of the invention described and / or claimed herein.

[0054] The exemplary quantum computing device 302 includes a qubit assembly 352 and a control and measurement system 304. The qubit assembly includes a plurality of qubits, such as qubit 306, used to perform algorithmic operations or quantum computations. The qubits shown in FIG. 3 are arranged in a rectangular array, which is a schematic depiction and not intended to be limiting. The qubit assembly 352 also includes adjustable coupling elements, such as coupler 308, that enable interaction between coupled qubits. In the schematic of FIG. 3, each qubit is adjustably coupled by its respective coupling element to each of four adjacent qubits. However, this is an exemplary arrangement of qubits and couplers, and other arrangements are possible, including non-rectangular arrangements that enable coupling between non-adjacent qubits and arrangements that include adjustable coupling between more than two qubits.

[0055] Each qubit can be a physical two-level quantum system or device having levels representing the logical values 0 and 1. The specific physical realizations of multiple qubits and how they interact with each other depend on various factors, including the type of quantum computing device 302 included in the exemplary computer 300, or the type of quantum computing being performed by the quantum computing device. For example, in an atomic quantum computer, qubits can be realized through atoms, molecules, or solid quantum systems, such as ultrafine atomic states. As another example, in a superconducting quantum computer, qubits can be realized through superconducting qubits or semiconductor qubits, such as superconducting transmon states. As another example, in an NMR quantum computer, qubits can be realized through nuclear spin states.

[0056] In some implementations, for example, quantum computing can be advanced by loading qubits from a quantum memory and applying a series of unitary operators to the qubits. Applying a unitary operator to a qubit can include, for example, applying a sequence of quantum logic gates corresponding to the qubit to implement a quantum algorithm such as a quantum principal component algorithm. Exemplary quantum logic gates include single qubit gates, such as Pauli-X, Pauli-Y, Pauli-Z (also called X, Y, Z), Hadamard gate, S gate, rotation, two qubit gates, such as controlled-X, controlled-Y, controlled-Z (also called CX, CY, CZ), controlled-NOT gate (also called CNOT), controlled-swap gate (also called CSWAP), and gates involving three or more qubits, such as the Toffoli gate. Quantum logic gates can be implemented by applying control signals 310 generated by the control and measurement system 304 to the qubits and couplers.

[0057] For example, in some implementations, the qubits of the qubit assembly 352 may be frequency tunable. In these examples, each qubit can have an associated operating frequency that is adjustable by the application of voltage pulses via one or more drive lines coupled to the qubit. Exemplary operating frequencies include the qubit's idling frequency, the qubit's interaction frequency, and the qubit's readout frequency. Different frequencies correspond to different operations that the qubit can perform. For example, by setting the operating frequency to the corresponding idling frequency, the qubit can be put into a state where it does not strongly interact with other qubits and can be used to perform single qubit gates. As another example, when qubits interact via a coupler with fixed coupling, the qubits can be configured to interact with each other by setting their respective operating frequencies to some gate-dependent frequency detuned from a common interaction frequency. In other cases, for example, when qubits interact via a tunable coupler, the qubits can be configured to interact with each other by setting the parameters of each coupler to enable interaction between the qubits and then setting the respective operating frequencies of the qubits to some gate-dependent frequency detuned from a common interaction frequency. Such interactions can be performed to execute multi-qubit gates.

[0058] The type of control signal 310 used depends on the physical implementation of the qubit. For example, the control signal may include RF pulses or microwave pulses in an NMR or superconducting quantum computer system, or optical pulses in an atomic quantum computer system.

[0059] Quantum computing can be accomplished by measuring the state of qubits using quantum observables such as X or Z, respectively, using each control signal 310. Upon measurement, a readout signal 312 representing the measurement result is sent back to the measurement and control system 304. The readout signal 312 can include an RF signal, a microwave signal, or an optical signal, depending on the quantum computing device and / or the physical scheme of the qubits. For convenience, the control signal 310 and the readout signal 312 shown in FIG. 3 are shown to address only selected elements (i.e., the top and bottom rows) of the qubit assembly, but during operation, the control signal 310 and the readout signal 312 can address each element within the qubit assembly 352.

[0060] The control and measurement system 304 is an example of a classical computer system that can be used to perform various operations on the qubit assembly 352 as described above, as well as other classical subroutines or calculations. The control and measurement system 304 includes one or more classical processors, such as classical processor 314, one or more memories, such as memory 316, and one or more I / O units, such as I / O unit 318, connected by one or more data buses. The control and measurement system 304 can be programmed to send a sequence of control signals 310 to the qubit assembly to perform, for example, a selected series of quantum gate operations, and to receive a sequence of readout signals 312 from the qubit assembly as part of performing a measurement operation.

[0061] The processor 314 is configured to process instructions for execution within the control and measurement system 304. In some implementations, the processor 314 is a single-threaded processor. In another implementation, the processor 314 is a multi-threaded processor. The processor 314 can process instructions stored in the memory 316.

[0062] Memory 316 stores information within control and measurement system 304. In some implementations, memory 316 includes a computer-readable medium, a volatile memory unit, and / or a non-volatile memory unit. In some cases, memory 316 can include a storage device that provides mass storage for system 304, such as, for example, a hard disk device, an optical disk device, a storage device shared over a network by multiple computing devices (such as a cloud storage device), and / or some other mass storage device.

[0063] Input / output device 318 provides input / output operations for control and measurement system 304. Input / output device 318 can include a D / A converter, an A / D converter, an RF / microwave / optical signal generator, a transmitter, a receiver, thereby sending control signal 310 to the qubit assembly and receiving readout signal 312 from the qubit assembly according to the physical scheme of the quantum computer. In some implementations, input / output device 318 can also include one or more network interface devices, such as an Ethernet card, a serial communication device, such as an RS-232 port, and / or a wireless interface device, such as an 802.11 card. In some implementations, input / output device 318 can include a driver device configured to receive input data and send output data to other external devices, such as a keyboard, a printer, and a display device.

[0064] Although an exemplary control and measurement system 304 is shown in FIG. 3, the implementation of the subject matter and the functional operations described in this specification can be implemented in other types of digital electronic circuits, or in computer software, firmware, or hardware, or in one or more combinations thereof, including the structures disclosed in this specification and their structural equivalents.

[0065] Exemplary system 300 also includes an exemplary classical processor 350. The classical processor 350 can be used to execute the classical computing operations described herein according to some implementations, for example, according to the classical machine learning methods described herein.

[0066] Exemplary Process for Processing Quantum Data FIG. 4 is a flowchart of an exemplary process 400 for processing quantum data. For convenience, process 400 is described as being executed by a quantum data processing system. For example, the quantum data processing system 200 of FIG. 2 appropriately programmed according to this specification can execute process 400.

[0067] The system stores multiple copies of the quantum state in quantum memory (step 402). The quantum state can encode the characteristics of the corresponding target system or target process, as will be described in more detail below. In some implementations, copies of the quantum state can be generated using a quantum sensor, for example, a sensor that interacts coherently with the physical world, as will be described later with reference to FIG. 5. In other implementations, copies of the quantum state can be generated by an analog quantum simulator or a gate-based quantum computer. In other implementations, copies of the quantum state can be generated by evolving an initial quantum state under a target process, for example, an evolution operator.

[0068] The system loads multiple copies of the quantum state in the quantum memory into the quantum computer (step 404). In some implementations, the system processes multiple copies of the quantum state using the quantum computer to obtain a purified quantum state (step 406). A purified quantum state is a quantum state that represents multiple copies of the quantum state. To process multiple copies of the quantum state and obtain a purified quantum state, the system can execute a linear distillation technique for purifying multiple copies of the quantum state, for example, quantum state distillation, virtual state distillation, or a quantum principal component analysis algorithm.

[0069] The system measures a quantum state purified using a quantum computer. The measured purified quantum state is used to determine characteristics of the target system or the target process by classical or quantum computation (step 408). For example, in some implementations, the system can provide the measurement results to a quantum machine learning system to learn characteristics of the target system or the target process.

[0070] FIG. 5 is a flowchart of a first exemplary process 500 for storing multiple copies of a quantum state in a quantum memory. The exemplary process 500 can be used to execute step 402 of the above-described exemplary process 400, such as when the exemplary process 400 is used to learn the physical state or characteristics of a system. For convenience, process 500 is described as being executed by a quantum data processing system. For example, the quantum data processing system 200 of FIG. 2, appropriately programmed according to this specification, can execute process 500.

[0071] To store one copy of the quantum state in the quantum memory, the system probes the target system using a quantum sensor (initialized with an initial quantum state) to obtain the evolved quantum state of the quantum sensor (step 502). The evolved quantum state of the quantum sensor encodes the characteristics of the target system at the time of probing and can be the state of multiple qubits, or the state of a bosonic or photonic mode, as described above with reference to FIG. 2. In some implementations, the system can probe the target system with a finite signal-to-noise ratio.

[0072] Next, the system transfers the information encoded in the evolved quantum state of the quantum sensor to the quantum state of the quantum buffer. In some implementations, the quantum sensor and the quantum buffer can include different computational media. For example, the quantum sensor can include a first computational media, the quantum buffer can include a second computational media, and the second computational media is different from the first computational media. Thus, to transfer the information encoded in the evolved quantum state of the quantum sensor to the state of the quantum buffer, the system converts the evolved quantum state of the quantum sensor to the quantum state of the quantum buffer (step 504).

[0073] Next, the system logically encodes the quantum state of the quantum buffer into a quantum error correction code (step 506). For example, the system can apply a unitary encoding quantum circuit to the quantum state of the quantum buffer or perform a state injection technique. In some implementations, the distance of the quantum error correction code can depend on at least one of the operations performed by the quantum computer to obtain the extracted quantum state, as described later with reference to step 306, or the expected duration required to store multiple copies of the quantum state in the quantum memory.

[0074] In some implementations, the system moves the logically encoded quantum state of the quantum buffer to the quantum memory (step 508). The system can move the logically encoded quantum state of the quantum buffer to the quantum memory if the encoding of the quantum buffer is different from the encoding of the quantum memory. For example, a large number of copies of the quantum state may be required, the qubits are sparse, and a higher code rate of the quantum memory and rapid encoding in the buffer may be beneficial. In other implementations, the quantum buffer and the quantum memory can be the same device, and thus there is no need to move the logically encoded quantum state to the quantum memory.

[0075] Steps 502 - 508 are repeated until a predetermined number of copies of the quantum state are stored in the quantum memory or until a predetermined duration has elapsed, such as when the target system is a transient system and the time interval during which the target system can be probed is limited. Exemplary transient systems include chemical substances that decompose in a short time. For example, in some chemical systems, photo - bleaching (destruction of the dye via interaction with light), such as when imaging or inspecting a dye, can occur on a short time scale of less than 100 milliseconds, and when the process of making the dye is unknown, the opportunity for measurement is limited. Another exemplary transient system includes rare sensing events, such as detection of cosmic rays, that do not occur frequently, for example, once per second.

[0076] FIG. 6 is a flowchart of a second exemplary process 600 for storing multiple copies of a quantum state in a quantum memory. The exemplary process 600 can be used to perform step 402 of the above - described exemplary process 400, such as when the exemplary process 400 is used to learn the characteristics of the physical dynamics / process. For convenience, process 600 is described as being executed by a quantum data processing system. For example, the quantum data processing system 200 of FIG. 2, appropriately programmed in accordance with this specification, can execute process 600.

[0077] To store a copy of a quantum state in a quantum memory, the system prepares an initial quantum state in which n system qubits are entangled with n memory qubits contained in the quantum memory (step 602). The system evolves the system qubits under an evolution operator corresponding to the physical dynamics / process to be learned (step 604). The system exchanges the system qubits and the memory qubits (e.g., applies a quantum circuit including a plurality of swap gates, each swap gate being configured to exchange the states of two qubits on which the gate operates) (step 606). Then, the system evolves the system qubits again under the evolution operator (step 608).

[0078] By processes 602 to 608, the evolution operator coherently changes the states of the n memory qubits such that the quantum states of the n memory qubits correspond to the quantum states evolved under the evolution operator. Steps 602 to 608 are repeated until a predetermined number of copies of the quantum state are stored in the quantum memory.

[0079] The systems and processes described above with reference to FIGS. 1 to 6 can be applied to different learning tasks and quantum reinforcement experiments, as will be described in more detail below.

[0080] Exemplary learning tasks and related quantum reinforcement experiments: learning of quantum states One exemplary learning task that can be performed using the techniques described herein is to learn the properties of a physical system described by an n-qubit state ρ. In this example, each experiment (e.g., a sensor interaction or other state preparation method as described above with reference to FIGS. 1 and 2) generates one copy of ρ. In a conventional setting, each copy of ρ is measured to obtain classical data. In the quantum-enhanced setting described herein, a quantum computer stores each copy of ρ in quantum memory and operates jointly on multiple copies of ρ. In either scenario, all quantum data must be measured at the end of the learning phase of the procedure so that only classical data remains. After learning is complete, the learner is required to provide an accurate prediction of the expected value of an observable quantity (i.e., a physical quantity) drawn from a set {O1, O2,...}, where the number of observable quantities in the set grows exponentially with n. The observable quantities in the set may not be compatible; for example, each observable quantity may not commute with many other observable quantities in the set.

[0081] When applied to this example, the quantum advantage achieved by the techniques described herein can be summarized as follows. There exists a distribution over n-qubit states and a set of observables such that in a conventional scenario, at least 2 n experiments are required to predict the absolute value of one observable selected from the set, while in the quantum-enhanced scenario described herein, a fixed number of experiments suffices.

[0082] Exponential quantum advantage can occur even when the state ρ is not entangled. For example, in some experiments, ρ ∝ (I + αP), where P is a Pauli operator on n qubits and α ∈ (-1, 1). This state can be realized as a probabilistic ensemble of product states that are eigenstates of P with eigenvalue α each. Although it is known that the state is in such a form, even when P and α are unknown, an exponential separation persists between conventional experiments and quantum-enhanced experiments. Furthermore, quantum advantage can be achieved by performing a simple entanglement measurement on pairs of copies of ρ. The fact that quantum advantage applies even when the correlations between n qubits are classical indicates that quantum-enhanced strategies are useful in a wide class of sensing applications.

[0083] Figure 7 is a diagram 700 showing quantum advantage achieved using the techniques presently described for learning a physical state. In particular, this figure shows results corresponding to the task of estimating the magnitude of the expectation value of a Pauli observable with respect to the physical state. In this example, the physical state is an n-qubit state ρ = 2 -n (I + αP) without entanglement, where α = ±0.95, P is a Pauli operator, and both α's are unknown. After all measurements are complete and learning is finished, two different Pauli operators Q1 and Q2 are announced, one of which is P and the other is not equal to P. The machine is configured to determine which of |tr(Q1ρ)| and |tr(Q2ρ)| is larger.

[0084] Part (a) of FIG. 700 shows that N repetitions of a quantum-enhanced experiment are performed and the corresponding data are fed into a supervised machine learning model, such as a gated recurrent neural network (GRU), for prediction. In the conventional scenario of measuring one copy of ρ at a time, the best-known strategy is to use randomized Clifford measurements that require an exponential number of copies to achieve a reasonable probability of success. In the quantum-enhanced scenario currently being described, two copies of ρ can be stored in quantum memory at once, and Bell measurements can be performed over the two copies to extract a snapshot of the state.

[0085] The supervised ML model is trained to determine which of two n-qubit Pauli operators has a larger expected value magnitude in the unknown state ρ. Cross-entropy is used as the training loss in this example. In some implementations, the neural network can be trained using noise-free simulation data for small system sizes (n < 8). Then, when experimental data for large system sizes (8 ≤ n ≤ 20) are provided, the neural network can be used for prediction. The probability of correct prediction is used as the prediction accuracy. Random guessing results in a prediction accuracy of 0.5. The graph shown in part (b) of FIG. 600 shows the performance of the ML model when the neural network is trained.

[0086] The graph shown in part (c) of FIG. 700 shows the quantum advantage in the number of experiments required to achieve a prediction accuracy of over 70% (depending on the system size n). Here, (Q) corresponds to the result of running a supervised ML model based on a quantum-enhanced experiment, and (C) corresponds to the result of running the best-known conventional strategy. The dotted line is the lower bound proven for any conventional strategy (C, LB). It can be seen that even when run on a noisy quantum processor, the currently described quantum-enhanced experiment significantly exceeds the theoretically achievable conventional results (C, LB).

[0087] Exemplary learning tasks and related quantum-enhanced experiments: Quantum principal component analysis When implementing the techniques presently described, another exemplary learning task that can achieve quantum supremacy is quantum principal component analysis (PCA). In this task, one copy of ρ is generated in each experiment, with the goal of predicting the properties of the (first) principal component of ρ, i.e., the eigenstate |ψ> of ρ with the largest eigenvalue. For example, it may be necessary to predict the expected values of some observables in the state |ψ>. This task can be valuable in future applications of quantum sensing. When an imperfect quantum sensor converts the detected quantum state into a quantum memory, the state can be destroyed by noise. However, the properties of the principal component are relatively robust to noise, and thus it is reasonable to expect that it is very beneficial for the non-destroyed state.

[0088] When applied to this example, the quantum supremacy achieved by the presently described techniques can be summarized as follows. In a conventional scenario, at least 2 n / 2 experiments are required to learn the fixed properties of the principal component of an unknown n-qubit quantum state, but in a quantum-enhanced scenario, a fixed number of experiments is sufficient.

[0089] Exemplary learning tasks and related quantum-enhanced experiments: Learning of quantum dynamics Another exemplary learning task that can be performed using the presently described techniques is to learn the properties of a physical process rather than a physical state. In these examples, each experiment executes a physical process ε. The physical process ε is interfaced via a quantum machine in a quantum-enhanced setting and via a classical machine in a conventional setting (as described above with reference to FIG. 1).

[0090] In these examples, a quantum machine can learn an approximate model of any polynomial-time quantum process ε from only a polynomial number of experiments. Given a distribution over input states, the approximate model can accurately predict the output state averaged from ε. In contrast, an exponential number of experiments is required to achieve the same task in a classical setting. That is, when applied to this example, the quantum supremacy achieved by the techniques currently being described can be summarized as follows. Consider a polynomial-time physical process ε acting on n qubits, and a probability distribution over n-qubit input states. In a classical scenario, at least 2 n experiments are required to learn an approximate model of ε that accurately predicts the output state averaged over, while in a quantum enhanced scenario, a polynomial number of experiments is sufficient.

[0091] FIG. 8 is a diagram 800 showing the quantum supremacy achieved using the techniques currently being described to learn a physical process. In particular, the figure shows the results corresponding to the task of learning to recognize a symmetric class of unknown evolution operators using teacherless ML (where the unknown evolution operator is drawn from either the class of all unitary transformations or the class of time-reversal symmetric unitary transformations (i.e., real orthogonal transformations)).

[0092] In a classical scenario, the unknown evolution operator is in the initial state

[0093]

Number

[0094] Repeatedly applied, each qubit in the output state is measured in the Y basis. In T-symmetric evolution, the output state has purely real amplitudes, and thus the expectation value of a purely imaginary observable such as the Pauli-Y operator is always zero. In contrast, the expectation value of Y after general unitary evolution is generally non-zero but can be exponentially small and thus difficult to distinguish from zero. In the quantum enhanced scenario, n additional memory qubits are used. An initial state is prepared where n system qubits are entangled with n memory qubits. The system qubits evolve under an unknown evolution operator. The system qubits and memory qubits are swapped, and the system qubits evolve again. Then n Bell measurements are performed, each acting on one system qubit and one memory qubit.

[0095] As shown in part (a) of FIG. 800, the physical process ε k For each, multiple, e.g., 500, repetitions of the quantum enhanced experiment (accessing each ε k twice) can be performed. The data is fed into an ML model without a teacher to learn a one-dimensional representation for describing different physical dynamics ε1, ε2,.... Alternatively, the ML without a teacher can be applied to data obtained from 1000 repetitions of the best-known conventional experiments (accessing each ε k once). k

[0096] Each evolution operator is a one-dimensional or two-dimensional n-qubit quantum circuit as shown in part (d) of FIG. 800. After sampling many different evolution operators from both symmetry classes (and after obtaining data multiple times from each sampled evolution), an ML model without a teacher is used to find a one-dimensional representation of the evolution operator. The representation learned by the ML model without a teacher is shown in parts (b) and (c) of FIG. 800.

[0097] ​Sub - figure (b) of the figure shows the representation learned by unsupervised ML for 1D dynamics. Each point corresponds to a different physical process ε k The vertical line at the bottom shows the exact 1D representation for each ε k Half of the processes satisfy time - reversal symmetry (diamonds), while the other half do not (circles). Sub - figure (c) of the figure shows a similar representation learned by unsupervised ML for 2D dynamics. Sub - figures (b) and (c) of Fig. 800 show that using quantum - enhanced data, the ML model discovers a clear separation between two symmetry classes (in the case of quantum enhancement, the results of the general symmetry class are shown on the left side of the graph, while the results of the T - symmetry class are shown only on the right side). When using data from conventional experiments, there is no distinguishable separation into classes (the results of the general class and the T - symmetry class are mixed, and there is no visible separation). The signal from the quantum - enhanced experiment is strong enough that the two classes can be easily recognized without accessing any labeled training data. Sub - figure (d) of the figure shows two exemplary classes of connectivity geometries for implementing 1D (top) and 2D (bottom) dynamics.

[0098] Implementations of the subject matter and the operations described in this specification can be realized in digital electronic circuitry, analog electronic circuitry, appropriate quantum circuitry, or more generally, a quantum computing system, tangibly embodied software or firmware, computer hardware including the structures disclosed in this specification and their structural equivalents, or one or more combinations thereof. The term "quantum computing system" can include, without limitation, a quantum computer, a quantum information processing system, a quantum cryptographic system, or a quantum simulator.

[0099] Implementations of the subject matter described in this specification can be implemented as one or more computer programs, i.e., as one or more modules of computer program instructions encoded on a tangible non-transitory storage medium for execution by, or to control the operation of, a data processing apparatus. The computer storage medium can be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, one or more qubits, or a combination of one or more of them. Alternatively, or in addition, the program instructions can be encoded on an artificially generated propagated signal that is generated to encode digital and / or qubit information for transmission to a suitable receiver device for execution by the data processing apparatus, e.g., a machine-generated electrical, optical, or electromagnetic signal that can encode digital and / or quantum information.

[0100] The terms quantum information and quantum data refer to information or data that is carried, held, or stored in a quantum system, and the smallest non-trivial system defines a qubit, i.e., the unit of quantum information. It is understood that the term "qubit" encompasses all quantum systems that can be suitably approximated as two-level systems in the corresponding context. Such quantum systems can include, for example, multi-level systems having two or more levels. By way of example, such systems can include atoms, electrons, photons, ions, or superconducting qubits. In many implementations, the computational basis states are identified with the ground and first excited states, but it is understood that other settings are possible where the computational states are identified with higher levels of excitation.

[0101] The term "data processing apparatus" refers to digital and / or quantum data processing hardware and includes, by way of example, programmable digital processors, programmable quantum processors, digital computers, quantum computers, multiple digital and quantum processors or computers, and any kind of device, apparatus, and machine for processing digital and / or quantum data, including combinations thereof. The apparatus may also be or further include dedicated logic circuits, such as field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), or quantum simulators, i.e., quantum data processing apparatuses designed to simulate or generate information about a particular quantum system. In particular, a quantum simulator is a dedicated quantum computer that does not have the ability to perform general-purpose quantum computing. Optionally, in addition to the hardware, the apparatus may include code that creates an execution environment for digital and / or quantum computer programs, such as code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or one or more combinations thereof.

[0102] A digital computer program, also called or sometimes described as a program, software, software application, module, software module, script, or code, can be described in any form of programming language, including compiled or interpreted languages, declarative languages, or procedural languages, and it can be deployed in any form, such as as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a digital computing environment. A quantum computer program, also called or sometimes described as a program, software, software application, module, software module, script, or code, can be described in any form of programming language, including compiled or interpreted languages, declarative languages, or procedural languages, can be converted into an appropriate quantum programming language, or can also be described in a quantum programming language such as, for example, QCL or Quipper.

[0103] A computer program, although not necessarily required, can correspond to files in a file system. The program can be stored in a single file dedicated to the program, or in multiple coordinated files, such as one or more modules, subprograms, or files storing parts of code, or in parts of files that hold other programs or data, such as one or more scripts stored in a markup language document. A computer program can be deployed to be executed on one computer, or located at one site, or distributed across multiple sites and executed on multiple computers interconnected by digital and / or quantum data communication networks. A quantum data communication network is understood to be a network that can transmit quantum data using a quantum system, such as qubits. Generally, a digital data communication network cannot transmit quantum data, but a quantum data communication network can transmit both quantum data and digital data.

[0104] The processes and logical flows described herein can be executed by one or more programmable computers that operate using one or more processors as necessary, operate on input data, and execute one or more computer programs to perform functions by generating output. The processes and logical flows can also be executed as dedicated logic circuits, such as FPGAs or ASICs, or as quantum simulators, or by a combination of dedicated logic circuits or quantum simulators and one or more programmed digital and / or quantum computers.

[0105] A system of one or more computers being "configured to" perform a particular operation or action means that the system has installed, during operation, software, firmware, hardware, or a combination thereof that causes the system to perform the operation or action. One or more computer programs being configured to perform a particular operation or action means that the one or more programs include instructions that, when executed by a data processing apparatus, cause the apparatus to perform the operation or action. For example, a quantum computer may receive instructions from a digital computer that cause the quantum computing apparatus to perform an operation or action when executed by the quantum computing apparatus.

[0106] A computer suitable for the execution of a computer program may be based on a general or special purpose processor, or any other kind of central processing unit. Generally, the central processing unit receives instructions and data from a read-only memory, a random access memory, or a quantum system suitable for transmitting quantum data, such as photons, or a combination thereof.

[0107] The elements of a computer include a central processing unit for executing or implementing instructions, and one or more memory devices for storing instructions and digital, analog, and / or quantum data. The central processing unit and the memory can be supplemented or incorporated into by a dedicated logic circuit or a quantum simulator. Generally, a computer also includes one or more mass storage devices for storing data, such as, for example, a magnetic, magneto-optical disk, an optical disk, or a quantum system suitable for storing quantum information, or is operatively coupled to receive data from, transfer data to, or both of one or more mass storage devices. However, a computer need not have such a device.

[0108] A quantum circuit element (also referred to as a quantum computing circuit element) includes a circuit element for performing a quantum processing operation. That is, a quantum circuit element is configured to perform operations on data in a non-deterministic manner by utilizing quantum mechanical phenomena such as superposition and entanglement. Some quantum circuit elements, such as qubits, can be configured to represent and manipulate information in two or more states simultaneously. Examples of superconducting quantum circuit elements include, among others, quantum LC oscillators, qubits (e.g., flux qubits, phase qubits, or charge qubits), and superconducting quantum interference devices (SQUIDs) (e.g., RF-SQUIDs or DC-SQUIDs).

[0109] In contrast, classical circuit elements generally process data in a deterministic manner. Classical circuit elements can be configured to collectively execute the instructions of a computer program by performing basic arithmetic operations, logical operations, and / or input / output operations on data, where the data is represented in analog or digital form. In some implementations, classical circuit elements can be used to transmit data to and / or receive data from a quantum circuit element via an electrical connection or an electromagnetic connection. Examples of classical circuit elements include circuit elements based on CMOS circuits, rapid single flux quantum (RSFQ) devices, reciprocal quantum logic (RQL) devices, and ERSFQ devices, which are energy-efficient versions of RSFQ that do not use bias resistors.

[0110] In some cases, some or all of the quantum circuit elements and / or classical circuit elements can also be implemented using, for example, superconducting quantum circuit elements and / or classical circuit elements. The fabrication of superconducting circuit elements can involve the deposition of one or more materials such as superconductors, dielectrics, and / or metals. Depending on the materials selected, these materials can be deposited using deposition processes such as chemical vapor deposition, physical vapor deposition (e.g., evaporation or sputtering), or epitaxial techniques, among other deposition processes. The process of manufacturing the circuit elements described herein can involve removing one or more materials from the device during manufacturing. Depending on the materials being removed, the removal process can include, for example, wet etching techniques, dry etching techniques, or lift-off processes. The materials forming the circuit elements described herein can be patterned using known lithography techniques (e.g., photolithography or electron beam lithography).

[0111] During operation of a quantum computing system that uses superconducting quantum circuit elements and / or superconducting classical circuit elements such as the circuit elements described herein, the superconducting circuit elements are cooled within a cryostat to a temperature that allows the superconducting material to exhibit superconducting properties. A superconductor (or superconducting) material can be understood as a material that exhibits superconducting properties below the superconducting critical temperature. Examples of superconducting materials include aluminum (superconducting critical temperature 1.2 Kelvin), and niobium (superconducting critical temperature 9.3 Kelvin). Thus, superconducting structures such as superconducting traces and superconducting ground planes are formed from materials that exhibit superconducting properties below the superconducting critical temperature.

[0112] In certain implementations, control signals for the quantum circuit elements (e.g., qubits and qubit couplers) can be provided using classical circuit elements that are electrically and / or electromagnetically coupled to the quantum circuit elements. The control signals can be provided in digital and / or analog form.

[0113] Computer-readable media suitable for storing computer program instructions and data include, by way of example, semiconductor memory devices such as EPROM, EEPROM, and flash memory devices, magnetic disks such as internal hard disks or removable disks, magneto-optical disks, CD-ROM and DVD-ROM disks, and all forms of nonvolatile digital and / or quantum memories, media, and memory devices including quantum systems such as trapped atoms and electrons. Quantum memory is a device that can store quantum data with high fidelity and efficiency for a long time. For example, it is understood that light is used for transmission and the substance is an optical-matter interface for storing and preserving quantum features of quantum data such as superposition or quantum coherence.

[0114] The control of various systems described herein, or portions thereof, can be implemented in a computer program product stored on one or more non-transitory machine-readable storage media and including instructions executable on one or more processing devices. Each of the systems or portions thereof described herein can be implemented as an apparatus, method, or system that can include one or more processing devices and a memory storing executable instructions for performing the operations described herein.

[0115] This specification includes many details of specific implementations, which are not limitations on the scope of the claims but rather should be construed as descriptions of features that may be specific to particular implementations. Some features described herein in the context of separate implementations can also be implemented in combination in a single implementation. Conversely, various features described in the context of a single implementation can also be implemented separately or in any suitable sub-combination in multiple implementations. Furthermore, features are described above as acting in certain combinations and may initially be claimed as such, but in some cases, one or more features from the claimed combination can be deleted and the claimed combination can be directed to a sub-combination or a variation of a sub-combination.

[0116] Similarly, although operations are shown in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown, or in sequential order, or that all of the illustrated operations be performed to achieve a desirable result. In some situations, multitasking and parallel processing may be advantageous. Further, the separation of various system modules and components in the above-described implementations should not be understood as necessarily requiring such separation in all implementations, and it should be understood that the described program components and systems can generally be incorporated together into a single software product or packaged into multiple software products.

[0117] Particular implementations of the subject matter have been described. Other implementations are within the scope of the following claims. For example, the actions recited in the claims can be performed in a different order and still achieve desirable results. As one example, the processes illustrated in the accompanying drawings do not necessarily require the particular or sequential order shown to achieve desirable results. In some cases, multitasking and parallel processing may be advantageous.

Description of Reference Numerals

[0118] 100 Diagram 102 Conventional Process 104 Quantum-Enhanced Process 200 Quantum Data Processing System 202 Target System 204 Quantum Sensor 206 Data 208 Quantum Buffer 210 Transformed Data 212 Logically Encoded Data 214 Quantum Memory 216 Quantum Computer 218 Classical or Quantum Computer 220 Stored Data 222 Measurement data 300 Classical / Quantum Computer 302 Quantum Computing Device 304 Control and Measurement System 306 Quantum Bit 308 Coupler 310 Control Signal 312 Readout Signal 314 Quantum Computer 314 Classical Processor 316 Memory 318 I / O Unit 350 Classical Processor 352 Quantum Bit Assembly 400 Process 500 Process

Claims

Claim 1 A computer-implemented method comprising: for each copy of a quantum state, i) probing a target system with the initialized quantum sensor to obtain an evolved quantum state of the quantum sensor, ii) converting the evolved quantum state of the quantum sensor into a quantum state of a quantum buffer, iii) logically encoding the quantum state of the quantum buffer into a quantum error correction code, and iv) moving the logically encoded quantum state of the quantum buffer to a quantum memory, the steps of storing a plurality of copies of the quantum state in the quantum memory; loading the plurality of copies of the quantum state in the quantum memory into a quantum computer; processing the plurality of copies of the quantum state by the quantum computer to obtain a purified quantum state; measuring the purified quantum state to determine a characteristic of the target system A computer-implemented method comprising the above steps. Claim 2 The method of claim 1, wherein the quantum sensor is configured to maintain quantum coherence. Claim 3 The method of claim 1, wherein the evolved quantum state of the quantum sensor encodes a characteristic of the target system at the time of the probing. Claim 4 The method of claim 1, wherein the evolved quantum state of the quantum sensor includes states of a plurality of qubits, or states of bosonic modes or photonic modes. Claim 5 The method of claim 1, wherein the step of probing the target system to obtain the evolved quantum state of the quantum sensor is performed at a finite signal-to-noise ratio. Claim 6 The method of claim 1, wherein the quantum sensor is configured to perform partial quantum error correction on the evolved quantum state of the quantum sensor. Claim 7 The method of claim 1, wherein the quantum sensor includes a first data format, the quantum buffer includes a second data format, and the second data format is different from the first data format. Claim 8 The method of claim 1, wherein the step of logically encoding the quantum state of the quantum buffer into a quantum error correction code includes applying a unitary encoding quantum circuit to the quantum state of the quantum buffer, or performing a state injection technique. Claim 9 The method according to claim 1, wherein the quantum error correction code includes a code distance that depends on at least one of the operations executed by the quantum computer to obtain the purified quantum state or the expected duration required to store the plurality of copies of the quantum state.

10. The method according to claim 1, wherein the step of processing the plurality of copies of the quantum state to obtain a purified quantum state includes the step of performing a linear distillation technique to purify the plurality of copies of the quantum state.

11. The method according to claim 10, wherein the linear distillation technique includes quantum state distillation, virtual state distillation, or a quantum principal component analysis algorithm.

12. The method according to claim 1, wherein the step of measuring the purified quantum state to determine the characteristics of the target system includes the step of providing the measurement results to a quantum machine learning system to learn the characteristics of the target system.

13. The method according to any one of claims 1 to 12, wherein the target system includes a temporary target system.

14. A quantum data processing system including a quantum sensor, a quantum buffer, a quantum memory, and a quantum computing device, wherein the quantum data processing system for each copy of the quantum state, i) probing a target system by the quantum sensor to obtain an evolved quantum state of the quantum sensor; ii) converting the evolved quantum state of the quantum sensor into a quantum state of the quantum buffer; iii) logically encoding the quantum state of the quantum buffer into a quantum error correction code; and iv) moving the logically encoded quantum state of the quantum buffer to the quantum memory, storing a plurality of copies of the quantum state in the quantum memory; loading the plurality of copies of the quantum state in the quantum memory into a quantum computer; processing the plurality of copies of the quantum state by the quantum computer to obtain a purified quantum state; measuring the purified quantum state by the quantum computer to determine the characteristics of the target system A quantum data processing system configured to perform operations including.

15. The quantum data processing system according to claim 14, wherein the quantum sensor is configured to maintain quantum coherence.

16. The quantum data processing system according to claim 14, wherein the evolved quantum state of the quantum sensor encodes the characteristics of the target system when probing the target system.

17. The quantum data processing system according to claim 14, wherein the evolved quantum state of the quantum sensor includes the states of a plurality of qubits, or the states of bosonic modes or photonic modes.

18. The quantum data processing system according to claim 14, wherein the quantum sensor is configured to probe the target system to evolve the quantum state of the quantum sensor with a finite signal-to-noise ratio.

19. The quantum data processing system according to claim 14, wherein the quantum sensor is configured to perform partial quantum error correction on the evolved quantum state of the quantum sensor.

20. The quantum data processing system according to claim 14, wherein the quantum sensor includes a first data format, the quantum buffer includes a second data format, and the second data format is different from the first data format.

21. The quantum data processing system according to claim 14, wherein the quantum data processing system is configured to logically encode the quantum state of the quantum buffer into a quantum error correction code by applying a unitary encoded quantum circuit to the quantum state of the quantum buffer or by executing a state injection technique.

22. The quantum data processing system according to claim 14, wherein the quantum error correction code includes a code distance that depends on at least one of the operations executed by the quantum computer to obtain the purified quantum state or the expected duration required to store the plurality of copies of the quantum state.

23. The quantum data processing system according to claim 14, wherein the quantum computing device is configured to process the plurality of copies of the quantum state to obtain a purified quantum state by executing a linear distillation technique to purify the plurality of copies of the quantum state.

24. The quantum data processing system according to claim 23, wherein the linear distillation technique includes quantum state distillation, virtual state distillation, or a quantum principal component analysis algorithm.

25. The quantum data processing system according to claim 14, wherein the quantum computing device is configured to provide measurement results obtained by measuring the purified quantum state to a quantum machine learning system in order to learn the characteristics of the target system.

26. The quantum data processing system according to any one of claims 14 to 25, wherein the target system includes a temporary target system.

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