A quantum noise process analysis method, applicable to a computer device, the method comprises: performing quantum process tomography, QPT, on a quantum noise process of a target quantum system, to obtain dynamical maps of the quantum noise process; extracting transfer tensor maps, TTMs, of the quantum noise process from the dynamical maps, the TTMs being maps recursively extracted from dynamical maps of the quantum noise process, the maps encoding a memory kernel of the target quantum system, and being used for predicting a dynamical evolution of the quantum noise process and determining properties of noise; and analyzing the quantum noise process according to the TTMs, wherein the dynamical maps comprise dynamical maps of the quantum noise process at K time points, K being a positive integer, wherein the extracting the TTMs of the quantum noise process from the dynamical maps comprises calculating the TTMs of the quantum noise process at the K time points according to the dynamical maps of the quantum noise process at the K time points, characterized in that analyzing the quantum noise process according to the TTMs comprises: determining that the quantum noise process is a Markov process in a case that each of moduli of TTMs of the quantum noise process at first time points is less than a preset threshold, the first time points being time points other than the foremost time point of the K time points; and determining that the quantum noise process is a non-Markov process in a case that a modulus of a TTM of the quantum noise process at a second time point is greater than the preset threshold, the second time point being at least one time point other than the foremost time point of the K time points, and wherein the method further comprises: determining a respective noise suppression solution according to the determination of the quantum noise process being a Markov process or a non-Markov process. performing quantum process tomography, QPT, on a quantum noise process of a target quantum system, to obtain dynamical maps of the quantum noise process; extracting transfer tensor maps, TTMs, of the quantum noise process from the dynamical maps, the TTMs being maps recursively extracted from dynamical maps of the quantum noise process, the maps encoding a memory kernel of the target quantum system, and being used for predicting a dynamical evolution of the quantum noise process and determining properties of noise; and analyzing the quantum noise process according to the TTMs, wherein the dynamical maps comprise dynamical maps of the quantum noise process at K time points, K being a positive integer, wherein the extracting the TTMs of the quantum noise process from the dynamical maps comprises calculating the TTMs of the quantum noise process at the K time points according to the dynamical maps of the quantum noise process at the K time points, characterized in that analyzing the quantum noise process according to the TTMs comprises: determining that the quantum noise process is a Markov process in a case that each of moduli of TTMs of the quantum noise process at first time points is less than a preset threshold, the first time points being time points other than the foremost time point of the K time points; and determining that the quantum noise process is a non-Markov process in a case that a modulus of a TTM of the quantum noise process at a second time point is greater than the preset threshold, the second time point being at least one time point other than the foremost time point of the K time points, and wherein the method further comprises: determining a respective noise suppression solution according to the determination of the quantum noise process being a Markov process or a non-Markov process. determining that the quantum noise process is a Markov process in a case that each of moduli of TTMs of the quantum noise process at first time points is less than a preset threshold, the first time points being time points other than the foremost time point of the K time points; and determining that the quantum noise process is a non-Markov process in a case that a modulus of a TTM of the quantum noise process at a second time point is greater than the preset threshold, the second time point being at least one time point other than the foremost time point of the K time points, and wherein the method further comprises: determining a respective noise suppression solution according to the determination of the quantum noise process being a Markov process or a non-Markov process.