# Constraining the scalar-tensor gravity theories with and without screening mechanisms by combined observations

## TL;DR

This paper combines multiple observational tests to place new, stringent constraints on scalar-tensor gravity theories, including screened modified gravity and Brans-Dicke models, showing their deviations from general relativity are tightly limited.

## Contribution

It provides the first comprehensive analysis of observational constraints on scalar-tensor theories with screening mechanisms, improving bounds by over seven orders of magnitude in some cases.

## Key findings

- LLR measurements set the strongest constraints on SMG.
- Cassini experiment provides the tightest bounds on Brans-Dicke theories.
- All tests are consistent with general relativity, tightening limits on deviations.

## Abstract

Screened modified gravity (SMG) and Brans-Dicke (BD) gravity are typical examples of scalar-tensor theories with and without screening mechanisms, which can suppress the scalar field in dense regions. In this paper, we investigate the tests of time-varying gravitational constant $G$, gravitational dipole radiation, and Nordtvedt effect in BD and SMG theories, respectively. We place new constraints on these theories by combining Cassini experiment, lunar laser ranging (LLR) measurements, and pulsar observations from PSRs J1738$+$0333 and J0348$+$0432. We find that screening mechanism has important influence on theoretical constraints. The strongest, second, and weakest constraints on BD are from Cassini, pulsar, and LLR tests, respectively. The most stringent constraint on SMG comes from LLR measurements and improves the previous best constraint by more than seven orders of magnitude. We derive the bounds on the cosmological evolution of the scalar background in these theories using the time variation of $G$. The results of all tests agree well with general relativity (GR) and give more stringent constraints on the deviations from GR. Finally, as an example, we consider the chameleon model and derive the constraints on the model parameters.