105 results about "Error mitigation" patented technology

Methods, systems, and computer-readable storage media for a software debugging system that leverages a LLM in combination with an entity matching model to propose solutions for mitigating errors. In some examples, the LLM is used to generate embeddings that are used to identify two or more matched historical errors. The matched historical errors are potential matches to a current error that needs to be resolved. The entity matching model is used to determine a matched historical error from the two or more matched historical errors. The LLM is also used to generate a proposed solution to the current error based on a historical solution to the matched historical error. The proposed solution can be executed to resolve the current error.

A method, system, and computer program product for learning noise models to perform quantum error mitigation. Each target layer of a quantum circuit is divided into a set of sub-layers. Each of the sub-layers for each target layer of the quantum circuit is grouped into a reduced set of learning layers, which enables each sub-layer's noise model to be learned from fewer layers (learning layers). A learning layer refers to a layer that is used in combination with other learning layers to form the minimally complete layer set for learning all the layer components used in the quantum circuit. The noise models for each of the sub-layers are then learned on the reduced set of learning layers. Such learned noise models are combined to form a complete set of noise models for the target layers of the quantum circuit and used to perform quantum error mitigation on the quantum circuit.

The invention provides a quantum error mitigation method and device, and the method comprises the steps: obtaining a sample quantum state through linear superposition of the results of a plurality of first unitary transformations which have a first probability and act on an accurate quantum state, constructing a quantum channel model, carrying out the inverse solution of the quantum channel model, obtaining a quasi-probability model, and carrying out the calculation of the quasi-probability model. The second initial state passes through a quantum circuit with noise to obtain an output quantum state, error correction is performed on the output quantum state by using a quantum error correction code method to obtain a quantum state to be subjected to error mitigation, and error mitigation is performed on the quantum state to be subjected to error mitigation by executing an operation process in a quasi-probability model on the quantum state to be subjected to error mitigation. According to the quantum error correction method, the number of physical bits required for realizing quantum error correction is reduced, the requirement on physical resources can be remarkably reduced on the premise of not sacrificing performance, so that the construction and maintenance of a quantum computing system are more economical and efficient, and higher computing accuracy can be kept under the conditions of higher noise and limited operation precision.

Systems and methods for error mitigation in a software pipeline. In some aspects, the system receives a request for evaluating a pipeline at a recurrent interval of time. The request comprises a first version of software, a second version of software, evaluation tests to execute on the second version of the software at intermittent intervals, and the recurrent interval of time. The system, in response to determining the recurrent interval of time elapsed, executes the evaluation tests on the second version of the software. The system determines that the output of the evaluation tests does not match one or more target values. The system terminates deployment of the second version of the software. The system generates instructions to replace the second version of the software with the first version of the software and transmits a notification to a remote device.

The invention discloses a quantum error mitigation acceleration method and accelerator using sparsity in a tensor product, and belongs to the technical field of quantum computation.The method comprises the steps that a quantum error mitigation conversion equation is established; the quantum error mitigation conversion equation is divided into three steps of operation of matrix-vector multiplication, tensor product and multiplication accumulation; sparsity acceleration is realized based on the output sparsity and the input sparsity; executing probability-level and state-level parallel computing on the tensor product operation to realize parallelism acceleration based on sparsity; and alternately executing row main sequence and column main sequence generation operation on the tensor product operation in an iteration round to realize operation fusion acceleration based on sparsity and parallelism. According to the method, the calculation efficiency and fidelity of the quantum read-out error mitigation method can be improved, so that the development and application of the quantum calculation technology are further promoted.

Methods, systems and apparatus for determining an error-mitigated expectation value of a target observable with respect to a noisy quantum state. In one aspect a method includes obtaining multiple copies of the noisy quantum state; performing measurements on tensor products of M copies of the noisy quantum state to compute an expectation value of the target observable with respect to an entangled quantum state, wherein M?1 and eigenvalues corresponding to non-dominant eigenvectors of the noisy quantum state in the spectral decomposition of the entangled quantum state are suppressed exponentially in M; and using the computed expectation value of the target observable with respect to an entangled quantum state to determine the error-mitigated expectation value of the target observable with respect to the noisy quantum state.

Techniques facilitating error mitigation for quantum computing devices. In one example, a system can comprise a process that executes computer executable components stored in memory. The computer executable components comprise: an approximation component; a budget component; and an optimization component. The approximation component can generate an approximate decomposition of a quantum gate. The budget component can set a budget value (Cbudget) for a C-factor that is a metric for increase in variance of quasi-probability sampling. The optimization component can determine an optimal decomposition for the quantum gate as a function of Cbudget.

Systems and methods for dynamic error resolution in hybrid quantum-classical computing environments are disclosed. A system can obtain telemetry data corresponding to a processing job. The system can determine that an error resolution technique is to be applied to the quantum portion of the processing job. The system can select, for a quantum portion of the processing job, the error resolution technique from a plurality of error correction techniques and a plurality of error mitigation techniques. The system can update a hierarchical data structure representing the processing job as at least a set of nodes. The hierarchical data structure can be updated to include the error resolution technique in association with a respective node of the hierarchical data structure representing the quantum portion of the processing job.

A system an analog to digital converter (ADC) operatively connected to receive an analog input signal from an input line and to output a digital input signal. A processor is operatively connected to receive the digital input signal from the ADC and to output a digital control signal for controlling a physical system based on the digital input signal. A digital to analog converter (DAC) is operatively connected to receive a copy of the digital input signal put out from the processor, and to output an analog output signal indicative of the copy of the digital input signal put out from the processor. Comparison logic is operatively connected to receive the analog input signal from the input line, to receive the analog output signal from the DAC, and to output an error signal in response to a mismatch between the analog input signal and the analog output signal.

The invention provides a base station self-calibration method in combination with direct non-line-of-sight error mitigation, which directly mitigates non-line-of-sight errors through a parallel deep regression network, and iteratively updates the position of a base station in combination with global optimization and local optimization strategies. The problems that an existing base station self-calibration method is limited by non-line-of-sight shielding and a multipath effect, the convergence speed is low and the self-calibration precision is low are effectively solved, and a more efficient and accurate solution is provided for ultra-wideband base station position self-calibration in a complex environment.

In various examples, systems and methods are disclosed relating to bandwidth preservation through selective application of error mitigation techniques for video frame regions. A subset of network packets for a video stream are identified as corresponding to an encoded region of a video frame of the video stream. At least one error correction packet is transmitted for the subset that encodes the region of the video frame. The network packets and the at least one error correction packet can be transmitted to a receiver device.

One or more systems, devices, computer program products and / or computer-implemented methods of use provided herein relate to an intelligent and automated system to solve quantum computing related problems. The computer-implemented system can comprise a memory that can store computer-executable components. The computer-implemented system can further comprise a processor that can execute the computer-executable components stored in the memory, wherein the computer-executable components can comprise a recommendation component that can employ a machine learning model to generate, based on an input, a recommendation comprising a combination of entities comprising, one or more quantum circuits, one or more algorithms, one or more quantum hardware units, one or more error mitigation or error correction techniques, and one or more quantum procedures, to solve a defined problem comprised in the input.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a network node may obtain an erroneous packet from a first communication device. The network node may output an indication of bit error rate information, based on the erroneous packet, to a second communication device to facilitate error mitigation at the second communication device. Numerous other aspects are described.

Using a quasi-probabilistic decomposition approach, a technique combining quantum error correction and quantum error mitigation is used to simulate fault-tolerant T-gates with low sampling overhead. In some embodiments, the T-gate can be simulated using two logic bits and magic state preparation that reduces the need for magic state extraction and thus has low sampling overhead. Alternatively, the T-gate can be simulated based on code deformation performed on the surface code. Quasi-probabilistic decomposition is used to remove noise from the T-gate based on learned logical error rates.

The present invention discloses a quantum error mitigation acceleration method and an accelerator utilizing sparsity in the tensor product, belonging to the technical field of quantum computing. The method includes: establishing a quantum error mitigation transformation equation; dividing the quantum error mitigation transformation equation into three-step operations of matrix-vector multiplication, tensor product, and multiply-accumulate; achieving sparsity acceleration based on output sparsity and input sparsity; performing probabilistic-level and state-level parallel computations on the tensor product operation to achieve sparsity-based parallel acceleration; and alternately performing row-major and column-major generation operations on the tensor product operation in iterative rounds to achieve operation fusion acceleration based on sparsity and parallelism. The present invention can improve the computational efficiency and fidelity of the quantum readout error mitigation method, thereby further promoting the development and application of quantum computing technology.

One or more systems, devices, computer program products and / or computer-implemented methods for determining error mitigated probability distributions are provided. A system can comprise a memory that can store computer-executable components. The system can further comprise a processor that executes at least one of the computer executable components that can execute a plurality of shots of a quantum circuit to obtain noise probabilities of observables; obtain a probability distribution of the noise probabilities; determine, using the probability distribution, expectation values of the observables; perform error mitigation on the expectation values to obtain an error mitigated probability distribution; and transform the error mitigated expectation values into an error mitigated probability distribution.

Techniques for automatic error mitigation in a database system using a backup plan are provided. After receiving a database statement, an error is detected as a result of compiling the database statement. In response to detecting the error, one or more backup plans are identified that are used to process the database statement or another database statement similar to the database statement. A particular backup plan of the one or more backup plans is selected. A result of the database statement is generated based on processing the particular backup plan.

The embodiment of the invention discloses a quantum error mitigation method, a fitting parameter determination method and a related device, and relates to the technical field of quantum computing. A conjugate circuit corresponding to an original quantum circuit is determined, and the overlap ratio of the conjugate circuit and the original quantum circuit is greater than or equal to 1 / 2; the conjugate circuit is easier to simulate on a classic computer, so that the simulation result of conjugation on the classic computer can be efficiently determined, and the fitting parameters of the conjugate circuit can be determined based on the simulation result of the conjugate circuit on the classic computer and the operation result of the conjugate circuit on the quantum chip. As the overlap ratio of the conjugate circuit and the original quantum circuit is high, the fitting parameter can also be used for correcting the operation result of the original quantum circuit.

Techniques for mitigating readout error for quantum expectation are presented. Calibration component applies first random Pauli gates to qubits at first output of first circuit prior to first readout measurements of the qubits. Estimation component applies second random Pauli gates to qubits at second output of second circuit prior to second readout measurements of the qubits, and generates an error-mitigated readout determination based on first random Pauli gates applied to qubits at first circuit output and second random Pauli gates applied to qubits at second circuit output. Calibration component determines calibration data based on first readout measurements. Estimation component determines estimation data based on second readout measurements. Estimation component determines normalization scalar value based on the calibration data, determines estimation scalar value based on the estimation data, and determines the error-mitigated readout determination associated with a circuit of interest based on the normalization scalar value and estimation scalar value.

Aspects of the present disclosure relate generally to systems and methods for use in the implementation and / or operation of quantum information processing (QIP) systems, and more particularly, to the use of performing automated symmetry verification on a quantum circuit. An exemplary method includes obtaining a quantum circuit with a compiled quantum program corresponding to a defined quantum computation; determining types of gates implemented on the quantum circuit; tracking allowed output states of the quantum circuit from an initial state based on the determined type of gates implemented on the quantum circuit; and detecting an error in the quantum circuit by identifying a possible output state that does not correspond to the subset of allowed output states.

The invention provides an error mitigation device and method for a continuous variable optical system, and the device is used for removing an error in a quantum signal generated by the continuous variable optical system, so as to obtain a measurement result of the quantum signal in the absence of phase damping noise. The error mitigation device at least comprises a noise modulation unit, a detection unit and a data processing unit, the noise modulation unit generates a plurality of voltage signals with different phases based on a plurality of noise parameters configured by a user, and performs phase modulation on quantum signals based on the generated voltage signals to obtain a plurality of phase-modulated quantum signals; the detection unit is used for detecting each phase-modulated quantum signal to obtain measurement results of all phase-modulated quantum signals; and the data processing unit is used for determining a measurement result of the quantum signal without phase damping noise by adopting an extrapolation method based on the noise parameters configured by the user and all measurement results detected by the detection unit.

A workflow for visual analytics using explainable data slices is described, which does not require any metadata. The workflow enables a user to validate and improve a machine learning model that has been trained using a dataset. The workflow generally comprises three phases: an Explainable Data Slice-Finding phase, a Slice Summarization and Annotation phase, and a Slice Error Mitigation phase. In the Explainable Data Slice-Finding phase, the workflow employs pixel attributions to create interpretable features of the dataset. In the Slice Summarization and Annotation phase, the workflow transforms the generated features into visualizations including a ‘Data Slice Mosaic.’ Finally, in the Slice Error Mitigation phase, the workflow leverages the annotation and user-verified spuriousness to mitigate slice errors in the machine learning model.

Embodiments of the present disclosure provide systems and methods to prevent false triggering of the touchpad buttons associated with a touchpad. The false touchpad button mitigation system and method uses executable logic that upon detection of a button press event, determines whether touchpad data is currently being received from the touchpad, and when no touchpad data is currently being received, inhibit the button press event from being processed by an Information Handling System (HIS). Touchpad data refers to data generated by a touchpad when a user's finger is touching the touchpad. Thus, if the user is not actively touching the touchpad, the false button press event may be blocked by the executable logic.

Methods, systems and apparatus for determining an error-mitigated expectation value of a target observable with respect to a noisy quantum state. In one aspect a method includes obtaining multiple copies of the noisy quantum state; performing measurements on tensor products of M copies of the noisy quantum state to compute an expectation value of the target observable with respect to an entangled quantum state, wherein M≥1 and eigenvalues corresponding to non-dominant eigenvectors of the noisy quantum state in the spectral decomposition of the entangled quantum state are suppressed exponentially in M; and using the computed expectation value of the target observable with respect to an entangled quantum state to determine the error-mitigated expectation value of the target observable with respect to the noisy quantum state.

A method, system, and computer program product for improving accuracy and efficiency of quantum error mitigation / correction techniques. A model (e.g., noise model) of a quantum gate set (collection of quantum gates) that accounts for SPAM and gate errors is built by running learning circuits at different depths with different initial states and measurements to extract information about the quantum system. A gauge transformation is then applied to the quantum gate set to transform both the SPAM and gate errors together. A gauge transformation enables a different perspective of the quantum system while still preserving the underlying physics. A quantum error mitigation / correction technique is then tailored to avoid interpreting errors (e.g., SPAM, gate errors, etc.) inconsistently if treated individually using the transformed SPAM and gate errors thereby requiring fewer additional circuit runs for accurate estimations which significantly reduces the computational overhead associated with quantum error mitigation / correction.

Techniques for automatic error mitigation in database systems using alternate plans are provided. After receiving a database statement, an error is detected as a result of compiling the database statement. In response to detecting the error, one or more alternate plans that were used to process the database statement or another database statement that is similar to the database statement are identified. A particular alternate plan of the one or more alternate plans is selected. A result of the database statement is generated based on processing the particular alternate plan.

To relax a quantum error in a quantum circuit using a non-Clifford gate.SOLUTION: The information processor 10 generates second quantum-bit circuits 3a, 3c,. by replacing the first two quantum-bit gates 4a to 7a in the first quantum-bit circuit 3 with a first equivalent circuit 7 including a second two quantum-bit gate 4b that performs a gate operation of phase-rotation by a first rotation angle. The information processor 10 replaces the first 2-qubit gates 3a to 3c in the first circuit 3 with a second equivalent circuit 8 including a third 2-qubit gate 8a that performs a gate operation of phase rotation of a second rotation angle to generate third circuits 5a, 5b,. The information processor 10 makes the quantum computer 1 execute the second quantum circuits 4a, 4b,. and the third quantum circuits 5a, 5b,., and outputs the average of the executed results as the executed result of the first quantum circuit 3.SELECTED DRAWING: Figure 1

A method includes: accessing a set of errors occurring during playback of segments of a video in a first rendition within a device population during a first time period and, during a subsequent time period, in response to receiving a first request for a first segment of the video in the first rendition: deriving, from the set of errors, a first error rate associated with the first segment in the first rendition; and, in response to the first error rate falling below a threshold, serving the first segment. The method also includes, in response to receiving a second request for a second segment of the video in the first rendition: deriving, from the set of errors, a second error rate associated with the second segment in the first rendition; and in response to the second error rate exceeding the threshold, serving the second segment in a second rendition.

A method, apparatus and computer program product are configured to mitigate error in an inertial navigation system (INS) that relies upon a reference system to determine or update filter parameters. In a method, a determination is made of (i) deviation or divergence of a filter of the INS and / or (ii) invalidity of observation(s) by the reference system. The method also identifies the filter parameters from a history buffer associated with a prior point in time at which performance of the filter is stable. The filter parameters were updated at least once based upon observation(s) by the reference system after the prior point in time. The method forward processes sensor samples of the INS obtained subsequent to the prior point in time using the filter parameters from the history buffer at which performance of the filter was stable to mitigate the error.

A method to detect time errors in a global navigation satellite system (GNSS) receiver can include determining a carrier-to-noise (CNo) delta between a CNo ratio of a first type of GNSS signal and a CNo ratio of a second type of GNSS signal. A time error may be detected based on the first CNo delta and a first threshold CNo delta, the time error indicating a use of an erroneous time uncertainty (TUNC) by the GNSS receiver. An error mitigation operation may be performed based on detecting the time error. The first type of GNSS signal may be selected based on determining that a first level of susceptibility to errors associated with the first type of GNSS signal is lower than a second level of susceptibility to errors associated with the second type of GNSS signal.