Variational quantum solver employing the PDS energy functional

Recently a new class of quantum algorithms that are based on the quantum computation of the connected moment expansion has been reported to find the ground and excited state energies. In particular, the Peeters-Devreese-Soldatov (PDS) formulation is found variational and bearing the potential for further combining with the existing variational quantum infrastructure. Here we find that the PDS formulation can be considered as a new energy functional of which the PDS energy gradient can be employed in a conventional variational quantum solver. In comparison with the usual variational quantum eigensolver (VQE) and the original static PDS approach, this new variational quantum solver offers an effective approach to navigate the dynamics to be free from getting trapped in the local minima that refer to different states, and achieve high accuracy at finding the ground state and its energy through the rotation of the trial wave function of modest quality, thus improves the accuracy and efficiency of the quantum simulation. We demonstrate the performance of the proposed variational quantum solver for toy models, H2 molecule, and strongly correlated planar H4 system in some challenging situations. In all the case studies, the proposed variational quantum approach outperforms the usual VQE and static PDS calculations even at the lowest order. We also discuss the limitations of the proposed approach and its preliminary execution for model Hamiltonian on the NISQ device.

Peeling off foregrounds with the constrained moment ILC method to unveil primordial CMB B modes

ABSTRACT Galactic foregrounds are the main obstacle to observations of the cosmic microwave background (CMB) B-mode polarization. In addition to obscuring the inflationary B-mode signal by several orders of magnitude, Galactic foregrounds have non-trivial spectral signatures that are partially unknown and distorted by averaging effects along the line of sight, within the pixel/beam window, and by various analysis choices (e.g. spherical harmonic transforms and filters). Statistical moment expansion methods provide a powerful tool for modelling the effective Galactic foreground emission resulting from these averaging effects in CMB observations, while blind component separation treatments can handle unknown foregrounds. In this work, we combine these two approaches to develop a new semiblind component separation method at the intersection of parametric and blind methods, called constrained moment ILC (cMILC). This method adds several constraints to the standard ILC method to deproject the main statistical moments of the Galactic foreground emission. Applications to maps are performed in needlet space and when compared to the NILC method, this helps in significantly reducing residual foreground contamination (bias, variance, and skewness) in the reconstructed CMB B-mode map, power spectrum, and tensor-to-scalar ratio. We consider sky simulations for experimental settings similar to those of LiteBIRD and PICO, illustrating which trade-offs between residual foreground biases and degradation of the constraint on r can be expected within the new cMILC framework. We also outline several directions that require more work in preparation for the coming analysis challenges.

Combining ILC and moment expansion techniques for extracting average-sky signals and CMB anisotropies

The method of weighted addition of multi-frequency maps, more commonly referred to as Internal Linear Combination (ILC), has been extensively employed in the measurement of cosmic microwave background (CMB) anisotropies and its secondaries along with similar application in 21cm data analysis. Here we argue and demonstrate that ILC methods can also be applied to data from absolutely-calibrated CMB experiments to extract average-sky signals in addition to the conventional CMB anisotropies. The performance of the simple ILC method is, however, limited, but can be significantly improved by adding constraints informed by physics and existing empirical information. In recent work, a moment description has been introduced as a technique of carrying out high precision modeling of foregrounds in the presence of inevitable averaging effects. We combine these two approaches to construct a heavily constrained form of the ILC, dubbed MILC, which can be used to recover tiny monopolar spectral distortion signals in the presence of realistic foregrounds and instrumental noise. This is a first demonstration for measurements of the monopolar and anisotropic spectral distortion signals using ILC and extended moment methods. We also show that CMB anisotropy measurements can be improved, reducing foreground biases and signal uncertainties when using the MILC. While here we focus on CMB spectral distortions, the scope extends to the 21cm monopole signal and B-mode analysis. We briefly discuss augmentations that need further study to reach the full potential of the method.