Analyzing each option:
(A) $\frac{\sqrt{2}X_1}{\sqrt{X_2^2 + X_3^2}} \sim t_2$
The numerator: $\sqrt{2}X_1 \sim N(0,2)$, so $\frac{\sqrt{2}X_1}{\sqrt{2}} = X_1 \sim N(0,1)$
The denominator: $X_2^2 + X_3^2 \sim \chi^2_2$
The t-distribution with $n$ degrees of freedom has the form: $$T = \frac{Z}{\sqrt{V/n}}$$ where $Z \sim N(0,1)$ and $V \sim \chi^2_n$ are independent.
Rewrite: $$\frac{\sqrt{2}X_1}{\sqrt{X_2^2 + X_3^2}} = \frac{X_1}{\sqrt{(X_2^2 + X_3^2)/2}}$$
Since $X_1 \sim N(0,1)$ and $(X_2^2 + X_3^2) \sim \chi^2_2$:
This matches the form of $t_2$ distribution.
(A) is TRUE
(B) $\frac{\sqrt{2}X_1}{|X_2 + X_3|} \sim t_1$
Note that $X_2 + X_3 \sim N(0,2)$, so $\frac{X_2 + X_3}{\sqrt{2}} \sim N(0,1)$
Therefore: $(X_2 + X_3)^2 \sim 2\chi^2_1$
Rewrite: $$\frac{\sqrt{2}X_1}{|X_2 + X_3|} = \frac{\sqrt{2}X_1}{\sqrt{(X_2 + X_3)^2}} = \frac{X_1}{\sqrt{(X_2 + X_3)^2/2}}$$
Since $(X_2 + X_3)^2/2 \sim \chi^2_1$ and $X_1 \sim N(0,1)$:
This matches the form of $t_1$ distribution.
(B) is TRUE
(C) $\frac{(X_1 - X_2)^2}{(X_1 + X_2)^2} \sim F_{1,1}$
Note that:
Therefore: $$\frac{(X_1 - X_2)^2}{(X_1 + X_2)^2} = \frac{2\chi^2_1/1}{2\chi^2_1/1} = \frac{\chi^2_1/1}{\chi^2_1/1}$$
This has the form of $F_{1,1}$ distribution.
(C) is TRUE
(D) $\sum_{i=1}^3 X_i^2 \sim \chi^2_2$
Since each $X_i \sim N(0,1)$, we have $X_i^2 \sim \chi^2_1$
The sum of independent chi-squared variables: $$\sum_{i=1}^3 X_i^2 \sim \chi^2_3$$
NOT $\chi^2_2$
(D) is FALSE
Answer: (A), (B), and (C) are true