128 results about "Error mitigation" patented technology

Some embodiments perform fully unsupervised string error detection and repair, for strings containing both syntactic errors and semantic errors. In some embodiments, string error mitigation includes learning a regular-expression-based pattern that characterizes at least a predefined fraction of a set of string data values, identifying and masking a semantic substring, deriving edits to repair a string which contains the semantic substring, and replacing a mask value with a replacement substring that conforms to the pattern. Some embodiments utilize a language model. Some embodiments include or utilize a pattern learner, one or more learned significant patterns, and a repair engine. Some embodiments exploit program execution information to generate patterns when significant patterns are not initially found.

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.

Techniques are provided for mitigating group delay errors across half duplex and full duplex operations. An example method of performing a round trip time message exchange includes performing the round trip time message exchange with a wireless node including receiving a downlink positioning reference signal and transmitting an uplink positioning reference signal, wherein the round trip time message exchange is associated with at least one duplex mode, and reporting a receive-transmit time difference measurement value based on the round trip time message exchange, wherein the reporting includes an indication of the at least one duplex mode.

A computer implemented method, for mitigating errors in a quantum circuit comprising at least one occurrence of a quantum logic operation G. The method includes computing a set of coefficients {cp}, associated with a set of basis operations B = {Bp}, to obtain a quasi-probability decomposition G0 ≈ ΣpcpBp on the set of basis operations B. The quasi-probability decomposition is of a target version of the quantum logic operation G, denoted G0. The set of basis operations {Bp} forms a multi-type basis, constructed from the quantum logic operation G and elements of a set of mitigation operations . The decomposition is computed so as to reach a decomposition target, being based on at least one of a decomposition accuracy target, and a decomposition sampling overhead target. The method includes implementing the quasi-probability decomposition on the quantum processor.

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.

In one embodiment, a method includes: receiving, in a receiver of a gateway, from a wireless device a radio frequency (RF) signal including a packet and processing the RF signal to obtain a digital stream; detecting and synchronizing, in the gateway, the packet based at least in part on a preamble of the packet; decoding, in the gateway, a header of the packet to obtain information associated with the packet; demodulating, in the gateway, a data portion of the packet into soft information; and sending at least a portion of the decoded header and the soft information from the gateway to a server coupled to the gateway, to enable the packet to be decoded using the soft information.

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.

A method, system and computer program product for generating optimal samples in quantum optimization algorithms. A quantum error mitigation technique is used to generate samples of a resulting probability distribution from random quantum circuits. Examples of such quantum error mitigation techniques include probabilistic error cancellation (PEC) and zero noise extrapolation (ZNE). An objective (ƒ(x)) for every generated sample (|x) is then computed. A conditional value at risk (CVaR) at a particular level of the computed objective functions corresponding to an optimal sample in a quantum optimization algorithm, such as a variational quantum optimization algorithm, is then computed. In this manner, optimal samples in quantum optimization algorithms are generated using quantum error mitigation techniques, such as probabilistic error cancellation and zero noise extrapolation.

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.

A method, system and computer program product for calibrating a quantum error mitigation technique with appropriate settings. Calibrations of the quantum error mitigation technique corresponding to combinations of noise factors and extrapolation functions that when applied to quantum circuits that represent the target quantum circuit achieve an expectation value that is close to a zero-noise value within a threshold degree of accuracy are saved. A calibration (combination of noise factors and an extrapolation function) is then selected from the saved calibrations based on the depth of the target quantum circuit. The quantum error mitigation technique is then calibrated based on the selected calibration. The calibrated quantum error mitigation technique is then performed on the target quantum circuit. In this manner, a quantum error mitigation technique is automatically calibrated with the appropriate settings to achieve a zero-noise value by the target quantum circuit without requiring multiple iterations.

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.

A method, system and computer program product for calibrating a quantum error mitigation technique with appropriate settings. Calibrations of the quantum error mitigation technique corresponding to combinations of noise factors and extrapolation functions that when applied to quantum circuits that represent the target quantum circuit achieve an expectation value that is close to a zero-noise value within a threshold degree of accuracy are saved. A calibration (combination of noise factors and an extrapolation function) is then selected from the saved calibrations based on the depth of the target quantum circuit. The quantum error mitigation technique is then calibrated based on the selected calibration. The calibrated quantum error mitigation technique is then performed on the target quantum circuit. In this manner, a quantum error mitigation technique is automatically calibrated with the appropriate settings to achieve a zero-noise value by the target quantum circuit without requiring multiple iterations.

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.