Method for diagnosing quantum devices and related quantum devices

Abstract

The present invention relates to a method for diagnosing a quantum device, comprising the steps of: - configuring a quantum computing device; - characterizing a characteristic operation of the quantum computing device to obtain and store an output characteristic noise corresponding to an input white noise; - following the previous step, characterizing at least one diagnostic operation of the device to obtain an output diagnostic noise corresponding to the input white noise; - performing a probabilistic analysis comparing the output diagnostic noise with the stored output characteristic noise to generate at least one fault indicator if the deviation therebetween is greater than a predetermined value. The present invention also relates to an apparatus for implementing this method.

Description

[Technical Field]

[0001] The present invention relates to a method for diagnosing a quantum device and to a related quantum device. The present invention further relates to a diagnostic and correction method in which the type of diagnostic step described above is combined with a computation step including a procedure for correcting the results in order to reduce or eliminate decoherence errors in quantum mechanical states associated with quantum computation. [Background technology]

[0002] A quantum device is a device significantly affected or governed by the laws associated with quantum mechanics, which means any device adapted to perform at least one "quantum computation".

[0003] Quantum computing relates to "any process performed by quantum circuits," such as any of the following operations based on the laws of quantum mechanics: measuring, generating, and manipulating quantum states, sequences of symbols derived therefrom, etc., without further limitation.

[0004] A quantum device comprises at least one "quantum circuit", which is, for example, part of a quantum processor, and is configured to construct output data based on the quantum computation described above.

[0005] The output data can be quantum data (qubits), classical data (bits), or an extension thereof, qudits, or a combination thereof, and is typically in string form.

[0006] Quantum circuits also have input data, which preferably comprises classical data such as bits, objects, events, symbols, or even signals in the quantum regime, typically in the form of strings.

[0007] Quantum computing is used to construct output data based on input data.

[0008] Quantum devices can comprise quantum computers, networks thereof, quantum data transmission devices, sensors, classical ones and combinations thereof, or networks thereof.

[0009] The definition of quantum device also includes quantum cryptography systems, which, possibly combined with other "classical" devices, are adapted to generate cryptographic keys or sequences of objects, events, or symbols.

[0010] The concept of an "event" can be understood as a general physical manifestation that occurs within a universe, or within any multiverse, or in the more abstract metaverse.

[0011] In this way it can be seen for example how the device can become a quantum sensor, according to which in this case quantum computation is the measurement.

[0012] Each such quantum device is built on an associated piece of hardware and is referred to herein as a device supporting the hardware.

[0013] A quantum device can include a single quantum circuit or a set of them.

[0014] For completeness, it should be noted that quantum computing is based on quantum bits, also known as "qubits." A qubit is understood by the well-known definition in quantum mechanics, i.e., a quantum piece of information represented by a unit vector in Hilbert space. Quantum computing can also be based on an extension of qubits, currently known as "qudits" (extensions of qubits with a broad base). For simplicity, the term qubit will hereafter also include qudits. For example, a qubit is a state of a subatomic particle, such as a photon or an electron. Because each particle can be in several different states simultaneously and with different possibilities due to the principle of superposition, it is possible to "overcome" the duality of the classical binary 0 / 1 code and carry more information, thereby enabling several operations to be performed simultaneously.

[0015] Systems for quantum computing are widely recognized to be undergoing unprecedented development, offering new deployments of previously unimaginable computing power and services that will impact and involve an ever-increasing number of users and activities in the future.

[0016] It is also widely known that, despite the fact that current electronic technology allows the use of ever-faster computers, exceeding petabyte speeds, and capable of reaching very high degrees of computational efficiency (expressed in bits per second), the increasing demand for greater computational capacity has pushed classical computers, which are substantially based on standard bits, against their physical limitations in terms of materials and circuits.

[0017] In this case, it is particularly important to develop new methods together with new technological solutions that make it possible to make ever deeper use of knowledge of the laws of nature to solve increasingly complex computational problems, as is now required.

[0018] Further in this regard, the computational process implemented by quantum logic, known as quantum computing, is of particular importance. It has recently proven more powerful than classical computing for solving certain classical problems. This advantage stems from the quantum ability of qubits, which are analogous to bits, to maintain stable coherence between different classical states, manifested as coherent superpositions of 0 and 1, a property related to classical bits. This property allows quantum computers to simultaneously perform calculations on many classical input states, enabling quantum computers to exponentially increase computational speed, at least in theory.

[0019] Widely known examples are devices for detecting quantum effects to quantum computing, from astronomy to other experimental sciences, communications, quantum and classical cryptography, and combinations thereof.

[0020] However, in practice, quantum computing faces a well-known problem of quantum mechanical state decoherence: each quantum mechanical state, be it a particle, ion, or photon, is in fact highly sensitive to its surrounding environment, and therefore loses its quantum mechanical identity (i.e., suffers from decoherence), which is the property we want to use for quantum computing, and the results are therefore invalidated.

[0021] Error correction procedures exist in the literature, which consist in using a large number of these qubits in a control procedure that sacrifices a certain number of qubits available for the calculation during the calculation, thus reducing the computational capacity of the device, or sometimes each calculation is repeated, which sacrifices most of the qubits, meaning values ​​up to about 80%, thus compromising the overall computational capacity and leaving the remaining qubits to be used.

[0022] Instead of using the full number of qubits N available for computation, k qubits are used for error correction, leaving Nk qubits available for computation or quantum registers. Thus, the N-dimensional Hilbert space associated with computation is reduced to an Nk-dimensional subspace for computation and another subspace of k dimensions for error correction.

[0023] In addition to this, there are other problems that may arise when the device is no longer in optimal condition, i.e. when some components are malfunctioning.

[0024] It should be noted that Professor Tamburini, the inventor and applicant of this patent, has previously authored the following scientific publication: Fabrizio Tamburini et al: “Testing the equivalence principle and discreteness of spacetime through the t 3 gravitational phase with quantum information technology” ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN CORNELL UNIVERSITY LIBRARY ITHACA, NY 14853, 19 August 2021, XP091034684.

[0025] The literature describes the possibility of detecting perturbations of space-time froth fluctuations at the Planck scale. The Planck scale is hypothetically characterized by random fluctuations in space and time, which can be explained by white noise if gravity is due to Einstein, and these fluctuations were hypothesized by Wheeler in the 1960s. Each space-time fluctuation is independent of the next. There are so-called t 3If other variations, as described by factors, exist, these are expected to produce different variations in the gravitational field, with the consequence that they alter the stochastic process they describe, and so in modern terminology this process in space-time variations is called "colored." These are well-known mathematical techniques used in various fields of physics and statistics.

[0026] Therefore, the literature considers the Planck scale standard gravity white noise as t 3 Compare with what is expected by factor t 3 The factors modify gravity itself and have time correlations and characteristic scales that can be statistically described as stochastic non-white noise processes, commonly referred to as colored noise.

[0027] However, to date, there has been little progress in translating this purely theoretical teaching into practical diagnostic detection procedures. Reaching the Planck scale would require energies currently unavailable to our technology and could result in the creation of mini-black holes or wormholes.

[0028] First, the work in question does not teach any practical application of the principle to a machine. Even if one were to apply it, he or she would gain nothing more than knowledge of the perturbations that color white input, and would not understand how to determine whether this is a malfunction. In fact, the literature does not describe any machines or tools adapted to correct errors, but it does consider experiments that make it possible to characterize spacetime fluctuations in the "bubbles" of spacetime, to confirm whether they are Wheeler's or not. Perhaps future measurements involving distant quasars or other extremely high-energy phenomena in the universe could provide some indication. However, such things have absolutely no bearing on error correction in machines or any device.

[0029] Furthermore, the comparative conditions in the literature are theoretically derived and have well-defined properties. 3It describes fluctuations that are not connected to each other at all, since it is between so-called "colored" noise (i.e., not general "colored" noise, but a well-defined stochastic process) of fluctuations with factors and white noise. If only because, as a condition of comparison, one needs to have a way to measure very high energy gravitational field fluctuations in order to compare them with white noise, the teachings are only theoretically defined and cannot be applied to actual machines that can be made with current technology. Currently, no device capable of detection is known. Therefore, the comparison can only be made theoretically.

[0030] Thus, there is a potential need in industry for diagnostic procedures for quantum computing devices. [Prior art documents] [Non-patent literature]

[0031] [Non-Patent Document 1] Fabrizio Tamburini et al: “Testing the equivalence principle and discreteness of spacetime through the t3 gravitational phase with quantum information technology” ARXIV.ORG,CORNELL UNIVERSITY LIBRARY,201 OLIN CORNELL UNIVERSITY LIBRARY ITHACA,NY 14853,19 August 2021,XP091034684 Summary of the Invention [Problem to be solved by the invention]

[0032] The object of the present invention is to detect anomalies in quantum devices while maintaining high computational power.

[0033] Another object of the present invention is to eliminate or at least reduce errors in quantum computing while maintaining high computing power.

[0034] Another preferred object of the present invention is to provide a diagnostic procedure and a procedure for correcting computational errors from decoherence errors, which work together to increase available computational power over known techniques.

[0035] Another preferred object is to provide a diagnostic procedure that is compatible with a variety of procedures for correcting computational errors due to decoherence of quantum mechanical states involved in quantum computation.

[0036] Another preferred object is to provide diagnostic, and possibly corrective, methods for quantum devices and related quantum devices that are simple and inexpensive to implement. [Means for solving the problem]

[0037] According to a first general aspect, the present invention relates to a method for diagnosing a quantum device, comprising the steps of: -Deploying a quantum computing device; characterizing the quantum computing device to obtain and store a characteristic output noise corresponding to an input white noise; - characterizing at least one operation of the device following the previous step to obtain an output diagnostic noise corresponding to the input white noise; - performing a probabilistic analysis to compare the output diagnostic noise with the stored output characteristic noise and generate at least one fault indicator if the deviation therebetween is greater than a predetermined value;

[0038] Advantageously, it is not necessary to repeat this diagnostic with each calculation, so that once successful operation of the device is established, quantum computations can be performed at full power, with associated simple procedures for correcting decoherence errors.

[0039] The step of obtaining the output diagnostic noise is preferably an iteration of obtaining the output characteristic noise, so that the comparison therebetween essentially verifies that such noise is stable over the various iterations and rules out certain errors, which can be done, for example, by verifying the stability of the fractal exponents.

[0040] Contrary to previous theoretical teachings in the literature on space-time fluctuations at the Planck scale by Professor Tamburini, cited in the preamble, the present invention advantageously solves the remaining problem of providing an applicable diagnostic procedure for machines. This problem is solved by comparing two colored outputs, i.e., two different stochastic processes, one a characteristic and one a diagnostic derived from the "behavior" of the device.

[0041] The teachings of the above literature regarding the present invention represent a misdirection, since admitting its application to a machine suggests nothing more than comparing input white noise with corresponding colored noise generated by other types of space-time fluctuations, thereby detecting perturbations (gravitational or otherwise) that color the input as expected from Einstein's gravity using Wheeler's foam model of space-time or gravitational waves. However, this is far removed from the experimental capabilities required for quantum computing machines or other similar devices. In fact, comparisons between two colored outputs, one characteristic used for comparison conditions and one for diagnostics, would not be obtained.

[0042] Preferably, said output noise comprises each of at least one characteristic probabilistic distribution and at least one diagnostic probabilistic distribution.

[0043] Preferably, said output is obtained by quantum computation starting from said input.

[0044] According to some preferred embodiments, the above probabilistic analysis is performed using a probabilistic test for diagnostic purposes and utilizes fractal geometry.

[0045] In this case, preferably, the above probabilistic analysis is: - associate at least one value of at least one fractal comparison parameter, each with two output noises; - repeat the calculation to obtain both the output characteristics and the diagnostic noise until the deviation from the average value in each of the respective comparison parameters reaches a zero limit, using a value of at least 2, preferably 3, more preferably 5 sigma; This comparison between the output diagnostic noise and the stored output characteristic noise is expected to generate at least one fault indicator if the average values with a reduced deviation to zero of the above parameters in the two outputs are different from each other by less than a predetermined value, using a value of at least 2, preferably 3, more preferably 5 sigma. For example, the predetermined value is proportional to the number of sigmas chosen for the test.

[0046] According to some preferred embodiments, the fractal parameter is the Hurst exponent, and this method is: - a value of 1 / 2 of the Hurst exponent for the input white noise, - a value of 0 < Hdf < 1 of the Hurst exponent for the output characteristic noise (which is 1 / 2 in the case of output white noise or ≠ 1 / 2 in the case of output colored noise), - a value of 0 < Hdd < 1 of the Hurst exponent for the output diagnostic noise (which is 1 / 2 in the case of output white noise or ≠ 1 / 2 in the case of output colored noise), are associated, If the average values with a reduced deviation to zero of Hdd and Hdf are different, a fault is reported unless a predetermined error is indicated.

[0047] If at least Hdf is equal to 1 / 2 or the average values with a reduced deviation to zero are equal, they are not excluded.

[0048] For example, the predetermined error takes into account the number of sigmas chosen for the test: the more sigmas, the higher the accuracy.

[0049] Preferably, the method is characterized by: - the step of obtaining and storing the output characteristic noise includes obtaining a probabilistic distribution of a set of characteristics identified by relative fractal indices (Hdf1, ...Hdfn), each indices of the set corresponding to an internal configuration of the quantum device; Similarly, the step of obtaining the output diagnostic noise includes obtaining a corresponding set of continuous probabilistic diagnostic distributions and relative fractal indices (Hdd1, ...Hddn); - If a comparison of the two sets of corresponding fractal indices reveals at least one difference, a disturbance of the corresponding internal structure is indicated.

[0050] Preferably, the diagnostic method described is associated with a calculation and a correction method to generate a diagnostic and correction method: A calculation step 10 is carried out after the diagnosis step, where the calculation step includes a correction procedure of the results to reduce or eliminate decoherence errors of the quantum mechanical states involved in the quantum calculation.

[0051] According to some preferred embodiments, this calculation step comprises: - repeating the desired quantum calculation until the deviation of the output or a parameter thereof from the mean value is reduced to zero, using a value of at least 2, preferably 3, more preferably 5 sigma, Includes.

[0052] This is the definition of zero limit, meaning that the deviation from the mean value tends to the zero limit with a value of at least 2, preferably 3, more preferably 5 sigma.

[0053] Preferably, the desired quantum computation is a computation with a probabilistic output, and the method comprises: - characterizing the output using a fractal index, e.g., the Hurst exponent (Hc); repeating the calculation and accepting the result when the mean value of the fractal index in this iteration has stabilized; Includes:

[0054] For example, the values ​​are considered stable when, upon repeated calculations, the deviation of the fractal index from the mean value is reduced to zero by a value of at least 2, preferably 3, and more preferably 5 sigma.

[0055] The desired quantum computation is rather a deterministic computation, where the method comprises: - repeating the calculation and accepting the result when the average value of the results has stabilized; Includes:

[0056] For example, the above values ​​are considered stable when the calculation is repeated and the resulting deviation from the mean value is reduced to zero by a value of at least 2, preferably 3, and more preferably 5 sigma.

[0057] According to a second general aspect, the present invention relates to a quantum device comprising at least one quantum circuit 60, means for probabilistic analysis of outputs 75, and means for generating at least one input white noise 80, wherein the means for probabilistic analysis of outputs comprises at least one memory 80 in which at least one software is stored, which is configured to implement a diagnostic method of the type described above.

[0058] Preferably, the means for probabilistic analysis of the output comprises at least one memory in which a piece of software is stored, which is adapted to implement a diagnostic and corrective method of the type described above.

[0059] Further characteristics and advantages of the present invention will become more apparent from the following detailed description of some preferred embodiments, given by way of indication and non-limiting example, with reference to the accompanying drawings, in which: [Brief explanation of the drawings]

[0060] [Figure 1] 1 shows a schematic flow diagram of a diagnostic and correction method according to the present invention; [Figure 2] 1 shows a schematic diagram of a quantum device according to the present invention; DETAILED DESCRIPTION OF THE INVENTION

[0061] Referring to FIG. 1, the diagnostic and correction method is generally designated by the reference numeral 1 and includes a diagnostic method 5 and a calculation and correction method 10 .

[0062] Preferably, at least part of the diagnostic method is performed at the start-up of the device, such as bootstrapping in the case of a quantum computer.

[0063] Diagnostic method 5 includes the following steps: -Deploying a quantum computing device; characterizing the quantum computing device and obtaining and storing in a diagnostic register a probabilistic distribution characteristic of the initial outputs of the device, hereafter referred to as the probabilistic distribution of characteristics; characterizing at least one operation of the device after obtaining the probabilistic distribution of the characteristics and obtaining a probabilistic distribution of an output diagnosis of the device, hereinafter referred to as the probabilistic distribution of the diagnosis; -Comparing the probabilistic distribution of the characteristic with the diagnostic distribution to establish the deviation between the two; - generating at least one fault indicator if the deviation is greater than a predetermined value;

[0064] The characteristic output stochastic distribution is generated using as input a stochastic process known in stochastic analysis as "white noise" (also known as classical Brownian motion), with a Hurst exponent H=1 / 2. An ideal device, free of decoherence or impairments, would also generate white noise (H=1 / 2) at the output. However, such a device is not (currently) realizable, and the output stochastic distribution will always be "colored noise" (also known as fractional Brownian motion). Nevertheless, the output colored noise is a characteristic of the device and can generally be used as a condition of comparison to detect impairments. However, we do not exclude the ideal case, where the output is still white noise and is used as a condition of comparison.

[0065] The calculations used to generate the characteristic probabilistic distribution and the diagnostic probabilistic distribution are the same and are predetermined calculations chosen from any probabilistic test calculation, such as the well-known Boson Sampling.

[0066] Fractional Brownian motion is a stochastic process with a distribution characterized by precise indices related to the fractal dimensions of the process itself, which are described by fractal exponents or indices (fractional is a synonym).

[0067] In general, therefore, each "real" device will be characterized by an output with a stochastic distribution of properties, i.e., by its own stochastic "noise", or rather by a type of stochastic process that can be explained by non-integer Brownian motion, and therefore a fractal exponent or index.

[0068] Therefore, the deviation between the two stochastic processes, indicated by the corresponding fractal indices, the characteristics of the device with "fault-free operation" and the characteristics of the device with "faulty operation", is an indication of the presence of a fault.

[0069] The deviation between probabilistic distributions can be established in various ways. A very reliable and practical procedure for accessing this is Hurst R / S analysis, or Hurst exponent analysis. Such analysis associates the value of a variable, the Hurst exponent H, generally to a stochastic process or to any set of historical data. Hurst analysis is applied here to both the output of the device, i.e., the probabilistic distribution of the characteristic and the diagnostic distribution, to generate a value of the H index for each. The Hurst exponent is known to take values ​​between 0 and 1, where H=½ represents the ideal case of classical Brownian motion and is therefore the value of the input "white noise."

[0070] As mentioned, the output "colored noise" is rather a fractional Brownian motion, which is characterized by a Hurst exponent H≠½.

[0071] However, this does not exclude the ideal case where the output is also white noise with H=1 / 2.

[0072] The device is characterized by a precise factory characteristic value for the Hurst exponent of the output, hereafter referred to as Hdf. If the diagnostic method finds a probabilistic distribution of diagnoses with values ​​other than Hdf (within given limits), the device is faulty.

[0073] The diagnostic method 5 of the present invention identifies at least one probabilistic distribution characteristic of a new device in its early stages of use, such as immediately after construction or typically upon leaving the factory. Such distribution, or at least one associated datum, such as the associated Hurst exponent Hdf, is stored in a characteristic register of the device, called a "diagnostic register," which is typically a kind of "factory marking," and which will accompany the device throughout its lifetime.

[0074] After storing this characteristic probabilistic distribution, a diagnostic step, e.g., bootstrapping, is performed at each startup of the device. In this step, at least one diagnostic probabilistic output distribution is obtained corresponding to the same quantum information pathway for which the characteristic probabilistic distribution is generated. The diagnostic probabilistic distribution is also generated using stochastic white noise as input. Such an output will have a Hurst exponent Hdd. At this point, the diagnostic probabilistic distribution is compared with the characteristic probabilistic distribution; if they do not match (within a predetermined error), it indicates that a fault exists.

[0075] The comparison via the Hurst exponent is very practical: indeed, unless there is a certain error, if Hdd differs from Hdf, a fault exists, which the device can signal, for example, by emitting a corresponding signal.

[0076] To ensure that the comparison reveals only faults, i.e., that the comparison is not distorted by computational errors due to decoherence, the calculations can be repeated until the deviations of Hdf and Hdd from their mean values ​​are reduced to zero using at least 2, preferably 3, and more preferably 5 sigma to obtain both the characteristic probabilistic distribution and the diagnostic probabilistic distribution.

[0077] It is recognized that when the quantum device comprises multiple internal configurations, e.g., at least one quantum processor, the method comprises the step of obtaining a probabilistic distribution of each characteristic and diagnosis, i.e., one for each path along which quantum information actually flows, e.g., one for each quantum circuit of the processor. Thus, in such a case, obtaining a probabilistic distribution of at least one characteristic comprises obtaining a set of characteristic probabilistic distributions identified by relative fractal indices (Hdf1, ...Hdfn), each index of the set corresponding to a different internal configuration of the quantum device. Such a set is stored in a diagnostic register.

[0078] Similarly, obtaining a probabilistic distribution of at least one diagnosis includes obtaining a corresponding set of probabilistic distributions of subsequent diagnoses and their relative fractal exponents, e.g., Hurst exponents Hdd1, ...Hddn.

[0079] By comparing the corresponding probabilistic distributions, it is possible to determine which "information path" (part of the processor) has a fault.

[0080] In practical use, a sequence of suitably generated symbols can be used as input white noise, with H=½. The device will then be able to return a string of symbols that is no longer white noise, but in fault-free operation, the noise, characterized by the exponents Hdf and Hdd as mentioned, must remain stable, i.e., match within a given error.

[0081] In general, it can be shown that comparing probabilistic distributions involves the following steps: - generating at least one value of an index parameter for comparing two corresponding output stochastic distributions (output noise), one characteristic and one diagnostic, for example a value of a fractal index such as the characteristic Hurst fractal index H;

[0082] Other types of probabilistic tests can also be used for diagnostic purposes, among which preferred are those that use fractal geometry, such as that used by Nelson and Nottale to explain quantum phenomena.

[0083] If the diagnostic procedure 5 does not reveal any faults, it is possible to proceed to a correction procedure 10, which includes a quantum computation and an error correction procedure according to the quantum mechanical state involved in the quantum computation, which steps: - repeating the desired quantum calculation until the deviation of the output or a parameter thereof from the mean value is reduced to zero, using a value of at least 2, preferably 3, more preferably 5 sigma, Includes.

[0084] In particular, for computations with stochastic outputs, i.e., involving stochastic processes or generated from quantum processes, a fractal index, such as the fractal index Hc, can be used to characterize the output. By checking the fractal index, e.g., Hc, two or more times, it is then possible to control the well-being of the computation and ensure stability within a given error. For example, it is possible to accept a computation as correct if the deviation from the mean value is 2, preferably 3, more preferably 4, or even more preferably 5 sigma over a number of iterations.

[0085] In the case of deterministic computations, i.e., where the result is not a probabilistic output or does not directly use a probabilistic process (e.g., when computing prime numbers or breaking cryptographic keys), the computation is repeated and the result is accepted when it is stable (within a given error), i.e., the deviation from the mean is 2, preferably 3, more preferably 4, and even more preferably 5 sigma.

[0086] The advantage is that quantum computation is exponential, while the procedure is obtained by repeating the computation several times (thus using a linear procedure).

[0087] In theory, any computational error correction procedure could be used, and therefore procedures with steps other than those described; as non-exhaustive examples we cite entanglement, "herald photons", or squeezed state techniques.

[0088] By analyzing deviations in the obtained values ​​of H, it is possible to monitor the corrective action of the various devices used in the calculation. Again, it should be understood that the term "calculation" is used in a broad sense.

[0089] In fact, the analysis proposed above is also applicable to the creation of cryptographic keys or to the generation of general sequences of events, various codes or symbols.

[0090] By analyzing the deviations, it is possible to identify any faults in the hardware, its simulation, software, and / or its management in order to correct and possibly reduce any future calculation errors.

[0091] One example is the computational errors associated with the decoherence of the quantum states used in the calculation, which constitute a fundamental challenge in quantum computing.

[0092] For example, in the construction of a general encryption key (classical or quantum), this avoids anomalies that could result in the existence of information that allows for compromise.

[0093] Another example is the non-Markovianity of symbol sequences used in classical or quantum cryptography, which may not be optimal for encrypting / decrypting general information.

[0094] Another example is a detection instrument that uses a single quantum or a set of quanta, which has a characteristic intrinsic noise, such as a photodetector or other related ones, for example in quantum boundary astronomy or other scientific applications.

[0095] Referring to FIG. 2, a quantum device according to the present invention is shown generally at 50 .

[0096] The quantum device comprises at least one quantum circuit 60, at least one input register 65, at least one output register 70, a probabilistic analysis means 75, and a means 80 for producing input white noise.

[0097] The means for probabilistic analysis of the output comprises at least one memory 85 (classical or quantum) in which at least one software is stored, configured to implement the diagnostic step 5 above.

[0098] The means for probabilistic analysis of the output further comprises at least one memory, in which a piece of software is stored, configured to perform the calculation step 10 above.

[0099] [General terminology] For purposes of understanding the present invention, the term "comprising" and its derivatives, as used herein, are intended to be open-ended terms specifying the presence of stated properties, elements, components, groups, wholes, and / or steps, but not excluding the presence of other undeclared properties, elements, components, groups, wholes, and / or steps. The same also applies to words of similar meaning, such as the terms "comprised," "have," and their derivatives. Furthermore, the terms "part," "section," "portion," "member," or "element," when used in the singular, may have the dual meaning of a single part or multiple parts. When used herein to describe the above-described operational embodiments, the following directional terms "forward," "rearward," "upward," "downward," "vertical," "horizontal," "below," and "transverse," as well as any other similar directional terms, refer to the described embodiment in an operational position. Finally, terms of degree, such as "substantially," "about," and "generally," as used herein, refer to modified terms deviating by a reasonable amount so as not to significantly change the end result.

[0100] While only selected embodiments have been chosen to illustrate the present invention, it will be apparent to those skilled in the art from this description that various modifications and variations can be made without departing from the scope of the present invention, as defined by the appended claims. For example, the size, shape, location, or orientation of various components can be changed as needed and / or desired. Components shown directly connected or in contact with each other may have intermediate structures disposed therebetween. The function of one element can be performed by two, and vice versa. The structure and function of one embodiment may be adopted by another embodiment. Not all advantages of a particular embodiment necessarily exist simultaneously. Any feature that is novel over the prior art should also be considered, by itself or in combination with other features, as a separate description of the applicant's other invention, including the structural and / or functional concepts embodied by such feature. Accordingly, the foregoing description of embodiments in accordance with the present invention is provided for illustrative purposes only and not for the purpose of limiting the present invention, as defined by the appended claims and their equivalents.

Claims

1. 1. A method for diagnosing a quantum device, comprising: Deploying a quantum computing device; characterizing a characteristic operation of the quantum computing device to obtain and store an output characteristic noise corresponding to an input white noise; subsequent to said step, characterizing at least one diagnostic operation of said device to obtain an output diagnostic noise corresponding to an input white noise; performing a probabilistic analysis to compare the output diagnostic noise with the stored output characteristic noise and generate at least one fault indicator if a deviation therebetween is greater than a predetermined value; A diagnostic method comprising:

2. the output noise comprises at least one probabilistic distribution and at least one diagnostic probabilistic distribution; comparing the probabilistic distribution of the diagnosis with the probabilistic distribution of the characteristic and generating at least one of the fault indicators if a deviation therebetween is greater than a predetermined value; The diagnostic method according to claim 1, characterized by:

3. 3. A diagnostic method according to claim 1 or 2, characterized in that the output is obtained by quantum computation starting from the input.

4. 4. Diagnostic method according to any one of claims 1 to 3, characterized in that the probabilistic analysis is carried out using probabilistic tests for diagnostic purposes using fractal geometry.

5. The probabilistic analysis associating a value of at least one of at least one fractal comparison parameter with each of the two output noises; repeating the calculations to obtain both the output characteristic noise and the diagnostic noise until the deviation from the mean value in each of said respective comparison parameters tends towards the zero limit using a value of at least 2, preferably 3, more preferably 5 sigma; said comparison between said output diagnostic noise and said stored output characteristic noise results in at least one fault indicator being generated if said mean values ​​of said parameters at the two outputs differ from each other by less than a predetermined value, with deviations reduced to zero using a value of at least 2, preferably 3, more preferably 5 sigma; The diagnostic method according to claim 4, characterized by:

6. The fractal parameter is the Hurst exponent, and the method comprises: a value of 1 / 2 of the Hurst exponent for the input white noise; a Hurst exponent for the characteristic output noise of 0<Hdf<1; a Hurst exponent for the diagnostic output noise of 0<Hdd<1; Associating 6. A diagnostic method according to claim 5, characterized in that a fault is reported if the mean values ​​of Hdd and Hdf with the deviation reduced to zero differ, up to a predetermined error.

7. said step of obtaining and storing output characteristic noise includes obtaining a probabilistic distribution of a set of characteristics, identified by relative fractal indices (Hdf1, . . . Hdfn), each indices of said set corresponding to an internal configuration of said quantum device; Similarly, obtaining and outputting the output diagnostic noise includes obtaining a corresponding set of continuous probabilistic diagnostic distributions and relative fractal indices (Hdd1, . . . Hddn); If a comparison of the two sets of corresponding fractal indices reveals at least one difference, a fault in the corresponding internal structure is indicated; The diagnostic method according to claim 5 or 6, characterized by:

8. 1. A method for diagnosing and correcting a quantum device, comprising: a diagnostic step (5) comprising a method according to any one of claims 1 to 7, a calculation step (10) carried out after said diagnostic step, comprising a correction procedure of the results, reducing or eliminating decoherence of the quantum mechanical states involved in the quantum computation; diagnostic and corrective methods, including:

9. The calculation step repeating the desired quantum computation until the deviation of the output or a parameter thereof from the mean value is reduced to zero, using a value of at least 2, preferably 3, more preferably 5 sigma; 9. The diagnostic and corrective method of claim 8, comprising:

10. The desired quantum computation is a computation with a probabilistic output, and the method comprises: characterizing the output using a fractal exponent, e.g., the Hurst exponent (Hc); repeating said calculation and accepting the result when the average value of the fractal index of said iterations stabilizes; 10. The diagnostic and corrective method of claim 9, comprising:

11. 11. The diagnostic and correction method according to claim 10, wherein the value is considered stable when, upon repeating the calculation, the deviation of the fractal index from the mean value is reduced to zero, using a value of at least 2, preferably 3, more preferably 5 sigma.

12. the desired quantum computation is a deterministic computation, and the method comprises: repeating the calculation and accepting the result when the average value of the result stabilizes; 10. The diagnostic and corrective method of claim 9, comprising:

13. 13. The diagnostic and correction method according to claim 12, wherein the calculation is repeated and the value is considered stable when the deviation of the result from the mean value is reduced to zero using a value of at least 2, preferably 3, more preferably 5 sigma.

14. Quantum device comprising at least one quantum circuit (60), means for probabilistic analysis of outputs (75), and means for providing at least one input white noise (80), said means for probabilistic analysis of outputs comprising at least one memory (80) in which at least one software is stored, said software being adapted to implement the diagnostic method according to any one of claims 1 to 7.

15. Quantum device according to claim 14, characterized in that the means for probabilistic analysis of the output comprise at least one memory in which a piece of software is stored, the software being adapted to implement the method according to any one of claims 8 to 13.

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