def run(intensity, chroma=0, i_oct=0):
'''Arguments:
- intensity: integer number of charges in beam
- chroma: first-order chromaticity Q'_{x,y}, identical
for both transverse planes
- i_oct: octupole current in A (positive i_oct means
LOF = i_oct > 0 and LOD = -i_oct < 0)
'''
# BEAM AND MACHINE PARAMETERS
# ============================
from LHC import LHC
# energy set above will enter get_nonlinear_params p0
assert machine_configuration == 'LHC-injection'
machine = LHC(n_segments=1,
machine_configuration=machine_configuration,
**get_nonlinear_params(chroma=chroma,
i_oct=i_oct,
p0=0.45e12 * e / c))
# BEAM
# ====
epsn_x = 3.e-6 # normalised horizontal emittance
epsn_y = 3.e-6 # normalised vertical emittance
sigma_z = 1.2e-9 * machine.beta * c / 4. # RMS bunch length in meters
bunch = machine.generate_6D_Gaussian_bunch(n_macroparticles,
intensity,
epsn_x,
epsn_y,
sigma_z=sigma_z,
matched=True)
print("\n--> Bunch length and emittance: {:g} m, {:g} eVs.".format(
bunch.sigma_z(), bunch.epsn_z()))
# CREATE BEAM SLICERS
# ===================
slicer_for_slicemonitor = UniformBinSlicer(50,
z_cuts=(-3 * sigma_z,
3 * sigma_z))
slicer_for_wakefields = UniformBinSlicer(
50,
z_cuts=(-3 * sigma_z, 3 * sigma_z),
circumference=machine.circumference,
h_bunch=machine.h_bunch)
print("Slice")
# CREATE WAKES
# ============
wake_table1 = WakeTable(
wakefile,
[
'time',
'dipole_x',
'dipole_y',
# 'quadrupole_x', 'quadrupole_y',
'noquadrupole_x',
'noquadrupole_y',
# 'dipole_xy', 'dipole_yx',
'nodipole_xy',
'nodipole_yx',
])
wake_field = WakeField(slicer_for_wakefields, wake_table1, mpi=True)
# CREATE DAMPER
# =============
dampingtime = 50.
gain = 2. / dampingtime
damper = IdealBunchFeedback(gain)
# CREATE MONITORS
# ===============
try:
bucket = machine.longitudinal_map.get_bucket(bunch)
except AttributeError:
bucket = machine.rfbucket
simulation_parameters_dict = {
'gamma': machine.gamma,
'intensity': intensity,
'Qx': machine.Q_x,
'Qy': machine.Q_y,
'Qs': bucket.Q_s,
'beta_x': bunch.beta_Twiss_x(),
'beta_y': bunch.beta_Twiss_y(),
'beta_z': bucket.beta_z,
'epsn_x': bunch.epsn_x(),
'epsn_y': bunch.epsn_y(),
'sigma_z': bunch.sigma_z(),
}
bunchmonitor = BunchMonitor(
outputpath + '/bunchmonitor_{:04d}_chroma={:g}'.format(it, chroma),
n_turns,
simulation_parameters_dict,
write_buffer_to_file_every=512,
buffer_size=4096)
slicemonitor = SliceMonitor(
outputpath + '/slicemonitor_{:04d}_chroma={:g}'.format(it, chroma),
n_turns_slicemon,
slicer_for_slicemonitor,
simulation_parameters_dict,
write_buffer_to_file_every=1,
buffer_size=n_turns_slicemon)
# TRACKING LOOP
# =============
# machine.one_turn_map.append(damper)
machine.one_turn_map.append(wake_field)
# for slice statistics monitoring:
s_cnt = 0
monitorswitch = False
print('\n--> Begin tracking...\n')
# GO!!!
for i in range(n_turns):
t0 = time.clock()
# track the beam around the machine for one turn:
machine.track(bunch)
ex, ey, ez = bunch.epsn_x(), bunch.epsn_y(), bunch.epsn_z()
mx, my, mz = bunch.mean_x(), bunch.mean_y(), bunch.mean_z()
# monitor the bunch statistics (once per turn):
bunchmonitor.dump(bunch)
# if the centroid becomes unstable (>1cm motion)
# then monitor the slice statistics:
if not monitorswitch:
if mx > 1e-2 or my > 1e-2 or i > n_turns - n_turns_slicemon:
print("--> Activate slice monitor")
monitorswitch = True
else:
if s_cnt < n_turns_slicemon:
slicemonitor.dump(bunch)
s_cnt += 1
# stop the tracking as soon as we have not-a-number values:
if not all(np.isfinite(c) for c in [ex, ey, ez, mx, my, mz]):
print('*** STOPPING SIMULATION: non-finite bunch stats!')
break
# print status all 1000 turns:
if i % 100 == 0:
t1 = time.clock()
print('Emittances: ({:.3g}, {:.3g}, {:.3g}) '
'& Centroids: ({:.3g}, {:.3g}, {:.3g})'
'@ turn {:d}, {:g} ms, {:s}'.format(
ex, ey, ez, mx, my, mz, i, (t1 - t0) * 1e3,
time.strftime("%d/%m/%Y %H:%M:%S", time.localtime())))
print('\n*** Successfully completed!')
def run(intensity, chroma=0, i_oct=0):
'''Arguments:
- intensity: integer number of charges in beam
- chroma: first-order chromaticity Q'_{x,y}, identical
for both transverse planes
- i_oct: octupole current in A (positive i_oct means
LOF = i_oct > 0 and LOD = -i_oct < 0)
'''
# BEAM AND MACHINE PARAMETERS
# ============================
from LHC import LHC
# energy set above will enter get_nonlinear_params p0
assert machine_configuration == 'LHC-injection'
machine = LHC(n_segments=1,
machine_configuration=machine_configuration,
**get_nonlinear_params(chroma=chroma,
i_oct=i_oct,
p0=0.45e12 * e / c))
# BEAM
# ====
#print(filling_scheme)
epsn_x = 3.e-6 # normalised horizontal emittance
epsn_y = 3.e-6 # normalised vertical emittance
sigma_z = 1.2e-9 * machine.beta * c / 4. # RMS bunch length in meters
beam = machine.generate_6D_Gaussian_bunch(n_macroparticles,
intensity,
epsn_x,
epsn_y,
sigma_z=sigma_z,
matched=True,
filling_scheme=filling_scheme)
bunch_list = beam.split_to_views()
for b in bunch_list:
if b.bucket_id[0] < batch_length:
b.x += 1e-3
b.y += 1e-3
bunch = bunch_list[0]
print("\n--> Bunch length and emittance: {:g} m, {:g} eVs.".format(
bunch.sigma_z(), bunch.epsn_z()))
# CREATE BEAM SLICERS
# ===================
slicer_for_slicemonitor = UniformBinSlicer(50,
z_cuts=(-3 * sigma_z,
3 * sigma_z))
slicer_for_wakefields = UniformBinSlicer(
50,
z_cuts=(-3 * sigma_z, 3 * sigma_z),
circumference=machine.circumference,
h_bunch=machine.h_bunch)
# CREATE WAKES
# ============
wake_table1 = WakeTable(
wakefile,
[
'time',
'dipole_x',
'dipole_y',
# 'quadrupole_x', 'quadrupole_y',
'noquadrupole_x',
'noquadrupole_y',
# 'dipole_xy', 'dipole_yx',
'nodipole_xy',
'nodipole_yx',
])
wake_field = WakeField(slicer_for_wakefields,
wake_table1,
mpi='linear_mpi_full_ring_fft')
# CREATE DAMPER
# =============
from PyHEADTAIL_feedback.feedback import OneboxFeedback
from PyHEADTAIL_feedback.processors.multiplication import ChargeWeighter
from PyHEADTAIL_feedback.processors.register import TurnFIRFilter
from PyHEADTAIL_feedback.processors.convolution import Lowpass, FIRFilter
from PyHEADTAIL_feedback.processors.resampling import DAC, HarmonicADC, BackToOriginalBins, Upsampler
from MD4063_filter_functions import calculate_coefficients_3_tap, calculate_hilbert_notch_coefficients
# from PyHEADTAIL_feedback.processors.addition import NoiseGenerator
dampingtime = 20.
gain = 2. / dampingtime
lowpass100kHz = [
1703, 1169, 1550, 1998, 2517, 3108, 3773, 4513, 5328, 6217, 7174, 8198,
9282, 10417, 11598, 12813, 14052, 15304, 16555, 17793, 19005, 20176,
21294, 22345, 23315, 24193, 24969, 25631, 26171, 26583, 26860, 27000,
27000, 26860, 26583, 26171, 25631, 24969, 24193, 23315, 22345, 21294,
20176, 19005, 17793, 16555, 15304, 14052, 12813, 11598, 10417, 9282,
8198, 7174, 6217, 5328, 4513, 3773, 3108, 2517, 1998, 1550, 1169, 1703
]
lowpassEnhanced = [
490, 177, -478, -820, -370, 573, 1065, 428, -909, -1632, -799, 1015,
2015, 901, -1592, -3053, -1675, 1642, 3670, 1841, -2828, -6010, -3929,
2459, 7233, 4322, -6384, -17305, -18296, -5077, 16097, 32000, 32000,
16097, -5077, -18296, -17305, -6384, 4322, 7233, 2459, -3929, -6010,
-2828, 1841, 3670, 1642, -1675, -3053, -1592, 901, 2015, 1015, -799,
-1632, -909, 428, 1065, 573, -370, -820, -478, 177, 490
]
lowpass20MHz = [
38, 118, 182, 112, -133, -389, -385, -45, 318, 257, -259, -665, -361,
473, 877, 180, -996, -1187, 162, 1670, 1329, -954, -2648, -1219, 2427,
4007, 419, -5623, -6590, 2893, 19575, 32700, 32700, 19575, 2893, -6590,
-5623, 419, 4007, 2427, -1219, -2648, -954, 1329, 1670, 162, -1187,
-996, 180, 877, 473, -361, -665, -259, 257, 318, -45, -385, -389, -133,
112, 182, 118, 38
]
phaseEqualizer = [
2, 4, 7, 10, 12, 16, 19, 22, 27, 31, 36, 42, 49, 57, 67, 77, 90, 104,
121, 141, 164, 191, 223, 261, 305, 358, 422, 498, 589, 700, 836, 1004,
1215, 1483, 1832, 2301, 2956, 3944, 5600, 9184, 25000, -16746, -4256,
-2056, -1195, -769, -523, -372, -271, -202, -153, -118, -91, -71, -56,
-44, -34, -27, -20, -15, -11, -7, -4, -1
]
FIR_phase_filter = np.loadtxt(
'./injection_error_input_data/FIR_Phase_40MSPS.csv')
FIR_phase_filter = np.array(phaseEqualizer)
FIR_phase_filter = FIR_phase_filter / float(np.sum(FIR_phase_filter))
FIR_gain_filter = np.array(lowpass20MHz)
FIR_gain_filter = FIR_gain_filter / float(np.sum(lowpass20MHz))
# Cut-off frequency of the kicker system
fc = 1.0e6
ADC_bits = 16
ADC_range = (-1e-3, 1e-3)
# signal processing delay in turns before the first measurements is applied
delay = 1
extra_adc_bins = 10
# betatron phase advance between the pickup and the kicker. The value 0.25
# corresponds to the 90 deg phase change from from the pickup measurements
# in x-plane to correction kicks in xp-plane.
additional_phase = 0.25 # Kicker-to-pickup phase advance 0 deg
# additional_phase = 0. # Kicker-to-pickup phase advance 90 deg
f_RF = 1. / (machine.circumference / c / (float(machine.h_RF)))
# turn_phase_filter_x = calculate_hilbert_notch_coefficients(machine.Q_x, delay, additional_phase)
# turn_phase_filter_y = calculate_hilbert_notch_coefficients(machine.Q_y, delay, additional_phase)
turn_phase_filter_x = calculate_coefficients_3_tap(machine.Q_x, delay,
additional_phase)
turn_phase_filter_y = calculate_coefficients_3_tap(machine.Q_y, delay,
additional_phase)
print('f_RF: ' + str(f_RF))
processors_detailed_x = [
Bypass(),
ChargeWeighter(normalization='segment_average'),
# NoiseGenerator(RMS_noise_level, debug=False),
HarmonicADC(1 * f_RF / 10.,
ADC_bits,
ADC_range,
n_extras=extra_adc_bins),
TurnFIRFilter(turn_phase_filter_x, machine.Q_x, delay=delay),
FIRFilter(FIR_phase_filter, zero_tap=40),
Upsampler(3, [1.5, 1.5, 0]),
FIRFilter(FIR_gain_filter, zero_tap=34),
DAC(ADC_bits, ADC_range),
Lowpass(fc, f_cutoff_2nd=10 * fc),
BackToOriginalBins(),
]
processors_detailed_y = [
Bypass(),
ChargeWeighter(normalization='segment_average'),
# NoiseGenerator(RMS_noise_level, debug=False),
HarmonicADC(1 * f_RF / 10.,
ADC_bits,
ADC_range,
n_extras=extra_adc_bins),
TurnFIRFilter(turn_phase_filter_y, machine.Q_y, delay=delay),
FIRFilter(FIR_phase_filter, zero_tap=40),
Upsampler(3, [1.5, 1.5, 0]),
FIRFilter(FIR_gain_filter, zero_tap=34),
DAC(ADC_bits, ADC_range),
Lowpass(fc, f_cutoff_2nd=10 * fc),
BackToOriginalBins(),
]
# Kicker-to-pickup phase advance 0 deg
damper = OneboxFeedback(gain,
slicer_for_wakefields,
processors_detailed_x,
processors_detailed_y,
pickup_axis='displacement',
kicker_axis='divergence',
mpi=True,
beta_x=machine.beta_x,
beta_y=machine.beta_y)
# # Kicker-to-pickup phase advance 90 deg
# damper = OneboxFeedback(gain,slicer_for_wakefields,
# processors_detailed_x,processors_detailed_y, mpi=True,
# pickup_axis='displacement', kicker_axis='displacement')
# CREATE MONITORS
# ===============
try:
bucket = machine.longitudinal_map.get_bucket(bunch)
except AttributeError:
bucket = machine.rfbucket
simulation_parameters_dict = {
'gamma': machine.gamma,
'intensity': intensity,
'Qx': machine.Q_x,
'Qy': machine.Q_y,
'Qs': bucket.Q_s,
'beta_x': bunch.beta_Twiss_x(),
'beta_y': bunch.beta_Twiss_y(),
'beta_z': bucket.beta_z,
'epsn_x': bunch.epsn_x(),
'epsn_y': bunch.epsn_y(),
'sigma_z': bunch.sigma_z(),
}
bunchmonitor = BunchMonitor(
outputpath + '/bunchmonitor_{:04d}_chroma={:g}'.format(it, chroma),
n_turns,
simulation_parameters_dict,
write_buffer_to_file_every=512,
buffer_size=4096,
mpi=True,
filling_scheme=filling_scheme)
# slicemonitor = SliceMonitor(
# outputpath+'/slicemonitor_{:04d}_chroma={:g}_bunch_{:04d}'.format(it, chroma, bunch.bucket_id[0]),
# n_turns_slicemon,
# slicer_for_slicemonitor, simulation_parameters_dict,
# write_buffer_to_file_every=1, buffer_size=n_turns_slicemon)
# TRACKING LOOP
# =============
machine.one_turn_map.append(damper)
machine.one_turn_map.append(wake_field)
# for slice statistics monitoring:
s_cnt = 0
monitorswitch = False
print('\n--> Begin tracking...\n')
# GO!!!
for i in range(n_turns):
t0 = time.clock()
# track the beam around the machine for one turn:
machine.track(beam)
bunch_list = beam.split_to_views()
bunch = bunch_list[0]
ex, ey, ez = bunch.epsn_x(), bunch.epsn_y(), bunch.epsn_z()
mx, my, mz = bunch.mean_x(), bunch.mean_y(), bunch.mean_z()
# monitor the bunch statistics (once per turn):
bunchmonitor.dump(beam)
# if the centroid becomes unstable (>1cm motion)
# then monitor the slice statistics:
if not monitorswitch:
if mx > 1e-2 or my > 1e-2 or i > n_turns - n_turns_slicemon:
print("--> Activate slice monitor")
monitorswitch = True
else:
if s_cnt < n_turns_slicemon:
# slicemonitor.dump(bunch)
s_cnt += 1
# stop the tracking as soon as we have not-a-number values:
if not all(np.isfinite(c) for c in [ex, ey, ez, mx, my, mz]):
print('*** STOPPING SIMULATION: non-finite bunch stats!')
break
# print status all 1000 turns:
if i % 100 == 0:
t1 = time.clock()
print('Emittances: ({:.3g}, {:.3g}, {:.3g}) '
'& Centroids: ({:.3g}, {:.3g}, {:.3g})'
'@ turn {:d}, {:g} ms, {:s}'.format(
ex, ey, ez, mx, my, mz, i, (t1 - t0) * 1e3,
time.strftime("%d/%m/%Y %H:%M:%S", time.localtime())))
print('\n*** Successfully completed!')
machine.one_turn_map.insert(ix, machine.longitudinal_map)
bunch = machine.generate_6D_Gaussian_bunch_matched(macroparticlenumber_track,
intensity,
epsn_x,
epsn_y,
sigma_z=sigma_z)
beam_x = []
beam_y = []
beam_z = []
sx, sy, sz = [], [], []
epsx, epsy, epsz = [], [], []
for i_turn in range(n_turns):
print('Turn %d/%d' % (i_turn, n_turns))
machine.track(bunch)
beam_x.append(bunch.mean_x())
beam_y.append(bunch.mean_y())
beam_z.append(bunch.mean_z())
sx.append(bunch.sigma_x())
sy.append(bunch.sigma_y())
sz.append(bunch.sigma_z())
epsx.append(bunch.epsn_x() * 1e6)
epsy.append(bunch.epsn_y() * 1e6)
epsz.append(bunch.epsn_z())
plt.figure(2, figsize=(16, 8), tight_layout=True)
plt.subplot(2, 3, 1)
plt.plot(beam_x)
plt.ylabel('x [m]')
plt.show()
machine.one_turn_map.insert(ix, machine.longitudinal_map)
bunch = machine.generate_6D_Gaussian_bunch_matched(
macroparticlenumber_track, intensity, epsn_x, epsn_y, sigma_z=sigma_z)
beam_x = []
beam_y = []
beam_z = []
sx, sy, sz = [], [], []
epsx, epsy, epsz = [], [], []
for i_turn in xrange(n_turns):
print 'Turn %d/%d'%(i_turn, n_turns)
machine.track(bunch)
beam_x.append(bunch.mean_x())
beam_y.append(bunch.mean_y())
beam_z.append(bunch.mean_z())
sx.append(bunch.sigma_x())
sy.append(bunch.sigma_y())
sz.append(bunch.sigma_z())
epsx.append(bunch.epsn_x()*1e6)
epsy.append(bunch.epsn_y()*1e6)
epsz.append(bunch.epsn_z())
plt.figure(2, figsize=(16, 8), tight_layout=True)
plt.subplot(2,3,1)
plt.plot(beam_x)
plt.ylabel('x [m]');plt.xlabel('Turn')
