HHL algorithm Qiskit version

      from qiskit import QuantumRegister, QuantumCircuit
import numpy as np

t = 2  # This is not optimal; As an exercise, set this to the

nqubits = 4  # Total number of qubits
nb = 1  # Number of qubits representing the solution
nl = 2  # Number of qubits representing the eigenvalues

theta = 0  # Angle defining |b>

a = 1  # Matrix diagonal
b = -1/3  # Matrix off-diagonal

# Initialise the quantum and classical registers
qr = QuantumRegister(nqubits)

# Create a Quantum Circuit
qc = QuantumCircuit(qr)

qrb = qr[0:nb]
qrl = qr[nb:nb+nl]
qra = qr[nb+nl:nb+nl+1]

# State preparation.
qc.ry(2*theta, qrb[0])

# QPE with e^{iAt}
for qu in qrl:
qc.h(qu)

qc.u1(a*t, qrl[0])
qc.u1(a*t*2, qrl[1])

qc.u3(b*t, -np.pi/2, np.pi/2, qrb[0])

# Controlled e^{iAt} on \lambda_{1}:
params=b*t

qc.u1(np.pi/2,qrb[0])
qc.cx(qrl[0],qrb[0])
qc.ry(params,qrb[0])
qc.cx(qrl[0],qrb[0])
qc.ry(-params,qrb[0])
qc.u1(3*np.pi/2,qrb[0])


My question regarding this part of the code is

What is $$e^{iAt}$$ and controlled-$$e^{iAt}$$, and why is controlled U gates based on different angles $$at,2at$$. There are many questions regarding this.

Can somebody explain this code to me, on this site or can somebody share his/her mail. I really am have trouble regarding this HHL algorithm and its implementation.