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The dataset generation failed
Error code: DatasetGenerationError
Exception: BadZipFile
Message: zipfiles that span multiple disks are not supported
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1492, in compute_config_parquet_and_info_response
fill_builder_info(builder, hf_endpoint=hf_endpoint, hf_token=hf_token, validate=validate)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 683, in fill_builder_info
) = retry_validate_get_features_num_examples_size_and_compression_ratio(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 602, in retry_validate_get_features_num_examples_size_and_compression_ratio
validate(pf)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 640, in validate
raise TooBigRowGroupsError(
worker.job_runners.config.parquet_and_info.TooBigRowGroupsError: Parquet file has too big row groups. First row group has 389851202 which exceeds the limit of 300000000
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1995, in _prepare_split_single
for _, table in generator:
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 797, in wrapped
for item in generator(*args, **kwargs):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 84, in _generate_tables
for file_idx, file in enumerate(itertools.chain.from_iterable(files)):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 1577, in __iter__
for x in self.generator(*self.args, **self.kwargs):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 1658, in _iter_from_urlpaths
if xisfile(urlpath, download_config=download_config):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 1024, in xisfile
fs, *_ = url_to_fs(path, **storage_options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 395, in url_to_fs
fs = filesystem(protocol, **inkwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 293, in filesystem
return cls(**storage_options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 80, in __call__
obj = super().__call__(*args, **kwargs)
File "<string>", line 3, in __init__
File "/usr/local/lib/python3.9/unittest/mock.py", line 1092, in __call__
return self._mock_call(*args, **kwargs)
File "/usr/local/lib/python3.9/unittest/mock.py", line 1096, in _mock_call
return self._execute_mock_call(*args, **kwargs)
File "/usr/local/lib/python3.9/unittest/mock.py", line 1157, in _execute_mock_call
result = effect(*args, **kwargs)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 934, in track_metadata_read_once
out = func(instance, fo=urlpath, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 62, in __init__
self.zip = zipfile.ZipFile(
File "/usr/local/lib/python3.9/zipfile.py", line 1266, in __init__
self._RealGetContents()
File "/usr/local/lib/python3.9/zipfile.py", line 1329, in _RealGetContents
endrec = _EndRecData(fp)
File "/usr/local/lib/python3.9/zipfile.py", line 286, in _EndRecData
return _EndRecData64(fpin, -sizeEndCentDir, endrec)
File "/usr/local/lib/python3.9/zipfile.py", line 232, in _EndRecData64
raise BadZipFile("zipfiles that span multiple disks are not supported")
zipfile.BadZipFile: zipfiles that span multiple disks are not supported
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1505, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1099, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2038, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
image_filename
string | caption
string |
|---|---|
dataset/figures/0704_0008_pgascmp1.eps | Principal isentrope and shock Hugoniot for air (perfect gas):
numerical calculations for general material models,
compared with analytic solutions. |
dataset/figures/0704_0008_AlcmpT.eps | Shock Hugoniot for Al in pressure-temperature space,
for different representations of the equation of state. |
dataset/figures/0704_0008_Becmpvp.eps | Principal adiabat and shock Hugoniot
for Be in normal stress-compression space,
neglecting strength (dashed), for Steinberg-Guinan strength (solid),
and for elastic-perfectly plastic with Y=10\,GPa (dotted). |
dataset/figures/0704_0008_Becmppus.eps | Principal adiabat and shock Hugoniot
for Be in shock speed-normal stress space,
neglecting strength (dashed), for Steinberg-Guinan strength (solid),
and for elastic-perfectly plastic with Y=10\,GPa (dotted). |
dataset/figures/0704_0008_Becmptp.eps | Principal adiabat, shock Hugoniot, and release adiabat
for Be in normal stress-temperature space,
neglecting strength (dashed), for Steinberg-Guinan strength (solid),
and for elastic-perfectly plastic with Y=10\,GPa (dotted). |
dataset/figures/0704_0008_Almelt.eps | Demonstration of shock Hugoniot solution across a phase boundary:
shock-melting of Al, for different initial porosities. |
dataset/figures/0704_0008_impact.eps | Wave interactions for the impact of a flat projectile
moving from left to right with a stationary target.
Dashed arrows are a guide to the sequence of states.
For a projectile moving from right to left, the construction is the
mirror image reflected in the normal stress axis. |
dataset/figures/0704_0008_shockrel.eps | Wave interactions for the release of a shocked state
(shock moving from left to right)
into a stationary `window' material to its right.
The release state depends whether the window has a higher or lower
shock impedance than the shocked material.
Dashed arrows are a guide to the sequence of states.
For a shock moving from right to left, the construction is the
mirror image reflected in the normal stress axis. |
dataset/figures/0704_0008_doublerel.eps | Wave interactions for the release of a shocked state
by tension induced as materials try to separate in opposite directions
when joined by a bonded interface.
Material damage, spall, and separation are neglected: the construction
shows the maximum tensile stress possible.
For general material properties, e.g. if plastic flow is included,
the state of maximum tensile stress is not just the negative of the
initial shock state.
Dashed arrows are a guide to the sequence of states.
The graph shows the initial state after an impact by a projectile moving
from right to left;
for a shock moving from right to left, the construction is the
mirror image reflected in the normal stress axis. |
dataset/figures/0704_0008_composite.eps | Schematic of uniaxial wave interactions induced by the impact
of a flat projectile with a composite target. |
dataset/figures/0704_0008_impactsim_notes.eps | Hydrocode simulation of Al projectile at 3.6\,km/s
impacting a Mo target with a LiF release window,
1.1\,s after impact.
Structures on the waves are elastic precursors. |
dataset/figures/0704_0009_f12.ps | sedI0Spectral Energy Distributions of the Class I sources in
the sample.
The open dots signal the observed fluxes from J-band to MIPS-70 when
available. The label gives the index in Table yso-table. |
dataset/figures/0704_0009_f14.ps | sedF0Spectral Energy Distributions of the Flat sources in the sample. Symbols as in Figure sedI0. |
dataset/figures/0704_0009_f15.ps | sedII0Spectral Energy Distributions (SED) of the Class II sources in the
sample. The open and solid dots are the observed and dereddened fluxes
respectively. The grey line is the stellar model of a K7 star and the
dashed line is the median SED of the TTauri stars in Taurus by Hartmann
et al. (2005) normalized to the dereddened J-band flux for comparison.
See text for more information. |
dataset/figures/0704_0009_f16.ps | sedII1Spectral Energy Distributions of the Class II sources in the
sample (continued). |
dataset/figures/0704_0009_f17.ps | sedII2Spectral Energy Distributions of the Class II sources in the
sample (continued). |
dataset/figures/0704_0009_f18.ps | sedII3Spectral Energy Distributions of the Class II sources in the
sample (continued). |
dataset/figures/0704_0009_f19.ps | sedIII0Spectral Energy Distributions of the Class III sources in the
sample. |
dataset/figures/0704_0009_f21.eps | diskLDistribution of disk to star luminosity ratios. The solid
and dashed lines are the total sample and T Tauri-like sample of SEDs,
respectively. Also marked are the typical ranges of L_
disk/L_ star ratios for debris disks, passive irradiated
disks and accretion disks. The figure indicates that objects of all
three evolutionary stages are found in Serpens, with a predominance
of young accreting T Tauri-type stars. |
dataset/figures/0704_0017_hbgpspx4win_24591rvel1.ps | Radial-velocity Fourier amplitude spectra from the 1991 combined data are shown for =3000 km s^-1 and 900 km s^-1 for the ^-1 and 1200 km s^-1 for the denotes the orbital frequency of the system, 2 its first harmonic and + the upper orbital side band where is the spin frequency. The data were prewhitened by the orbital frequency and are displayed in the third panels from the top. Window spectra are plotted below the amplitude spectra (bottom panels). |
dataset/figures/0704_0017_hapspx4win_01rvelspin1.ps | Radial velocity amplitude spectra shown for the =3500 km s^-1 and 1200 km s^-1. The vertical dashed line shows the expected position of the orbital and spin period peaks. The data were prewhitened by and are shown in the third panel from the top. A window spectrum is shown at the bottom. |
dataset/figures/0704_0017_habgidltrl01-5xv.ps | 2001 , , q=0.21, i=78^ and M_1=0.50 M_. The bottom panels are the reconstruction of the average-subtracted data. The fourth and bottom panels are also plotted on the same scale except for |
dataset/figures/0704_0017_habg_24591-1t2wunbpr.eps | The (top panel), (middle panel) and (bottom panel) spin radial velocities of the narrow component from the 1991 combined data () and 2001 data (). The |
dataset/figures/0704_0017_ha_01spinrvel3t51t2wf.ps | The spin radial velocity curves of the |
dataset/figures/0704_0017_trailer_spin_01avinvar4pxv.ps | The , , 4471 trailed spectra from 2001 folded on the spin period are shown at the top panels and the average-subtracted spectra are shown at the second panels. Doppler maps constructed from the phase-invariant subtracted spectra are shown in the bottom panels. The Doppler maps were constructed using the BPM and are shown on the same velocity scale with the trailed spectra. The lookup table is as in Figure~q:habegatrl. |
dataset/figures/0704_0017_habgidltrl01sp-4ixv.ps | , . The lookup table is as in Figure~q:habegaidltrl. |
dataset/figures/0704_0017_qexillus2e.eps | A depiction of the regions where |
dataset/figures/0704_0022_time3.eps | Rigid body:
We show the log-distance of the approximate solution
to the unit sphere as a function of time for each of the methods.
Below we show the approximate solutions as a function of time
for the stochastic Taylor (blue) and Munthe-Kaas methods (magenta).
The trajectory starts at the top right and eventually drifts over
the left horizon. |
dataset/figures/0704_0022_casimirs040607.eps | Autonomous underwater vehicle:
We show the log-distance of the approximate solution
to the two Casimirs C_1= p(dotted line)
and C_2=|p|^2(solid line) as a function of time
for each of the methods. Below, we also show the
global error as a function of stepsize. |
dataset/figures/0704_0027_LLphononRes2.eps | (a) Optical phonons are lattice
vibrations with an out-off-phase oscillation of the two sublattices. %(b) Interband electron-hole excitations coupling to phonon modes with
different circular polarization. |
dataset/figures/0704_0027_PhononPlasmonB30.eps | (a) Coupled phonon and
magneto-excitons as a function of the magnetic field. Energies are in units
of the bare phonon energy . Dashed lines indicate the
uncoupled valley-symmetric modes, with g_A=0. (b)
Mode splitting as a function of the filling factor, as may be seen in Raman
spectroscopy, with the resonance condition _n=0%_0, for =0 in (I), 0<||<2(in II), and = 2(in III). The absolute
intensity of the modes is in arbitrary units, but the height and the width
reflect the expected relative intensities. (c) Mode splitting for %
n=0, as a function of the filling factor . (d) Same
as in (c) for n 1. |
dataset/figures/0704_0030_fig1.eps | Second order contributions to the
self-energy. Straight lines represent electron Green's functions of
the host and wavy lines phonon Green's functions. |
dataset/figures/0704_0030_fig2A.ps | fig:cmpmillis The spectral function in the static
limit of the half-filled Holstein model computed at temperature
T=0.08(a) using the exact solution and (b) using 2nd order IPT at a
low frequency, _0=0.004. The IPT
solution at this small non-zero frequency is quite close to the exact
solution in the static limit. In particular, the band splitting and
the positions of the maxima agree. To contrast, panel (c) shows the
results of the approximation using the full Green's function (Diagram
2c from figure fig:phon2o is not included to avoid
overcounting) |
dataset/figures/0704_0030_fig3A.ps | fig:ipt Spectral functions of the half-filled
Holstein model for various electron-phonon couplings
U, approximated using 2nd order perturbation theory at
T=0.02 and _0=0.056(top), _0=0.5(center) and
_0=2(bottom). In the low frequency
limit (_0=0.125), the spectral
functions are similar to those in the static limit shown in
Fig. fig:cmpmillis, with only a small effect from the non-zero
phonon frequency. As the temperature is lower than the phonon
frequency, the central quasiparticle peak is clearly resolved for
U 2. For the intermediate frequencies
(central panel) the peak around =0 is
again clear and has a width _0 at
low coupling. In the gapped phase at large couplings two
band-splittings are visible. For _0 the band splits just as in the static limit, while for
U there is a peak at a renormalized
phonon frequency (which is less than the bare phonon frequency). In
the ungapped phases for _0=0.5 and
2, the low energy behavior is similar to that
found in the Hubbard model with a narrow quasiparticle band forming
near the Fermi energy with the value at the Fermi energy pinned to its
value in the non-interacting case. |
dataset/figures/0704_0030_fig4.ps | fig:seImaginary part of the self-energy of the half-filled Holstein
model when U=2 and _0=2
computed using IPT and analytically continued using MAXENT. At low
temperatures the low frequency behavior is Fermi-liquid like (quadratic
dependence on ) down to quite low frequencies
(at very low frequencies and low temperatures there are some inaccuracies
associated with the truncation in Matsubara frequencies). There are
peaks at the frequencies associated with the phonon energy and with
U. As the temperature increases the minimum
at the Fermi energy ( =0) increases as
incoherent on-site scattering in the corresponding local impurity
increases (see text). At temperatures above the characteristic
(Kondo-like) energy scale the central peak subsides and disappears. |
dataset/figures/0704_0030_fig5.ps | fig:ocThe real part of the optical
conductivity for a system with U=2.0 and _0=2.0 for a range
of temperatures. The structure of the spectrum reflects that in the
density of states (see fig fig:ipt. At low frequencies,
electrons may be excited within the quasiparticle resonance. The
second peak at 2.0 represents excitations from the Kondo
resonance to the large satellite (Hubbard band), and the peak at
5.0 represents excitations between the satellites. |
dataset/figures/0704_0030_fig6.ps | fig:resThe resistivity as a function of temperature
for the Holstein model for _0=2 for
varying electron-phonon coupling strengths. The resistivity is in
units of e^2V/ h a^2 with V the unit cell
volume and a the lattice cell spacing. The behavior reflects what
is seen in the self-energy. At low temperatures the behavior is
similar to that in a Kondo lattice. The resistivity rises sharply
with temperature for temperatures smaller than the quasiparticle
bandwidth. The resistivity then drops for temperatures larger than
this lattice coherence temperature. A simple logarithmic decay with
temperature is not visible because, in addition to the Kondo-like
scattering processes, the electrons are scattered from thermally
excited phonons whose spectral weight broadens and shifts towards
lower frequencies as the temperature rises. This leads to a second
peak. In contrast, the second peak is not visible for the Hubbard
model, and indicates the presence of two energy scales in the Holstein
model. |
dataset/figures/0704_0045_fig1a.eps | Isolated solitary wave (a) and undular bore (b) entering
the variable topography/bottom friction region. |
dataset/figures/0704_0045_fig2.eps | Dependence of the modulus m on the physical space
coordinate x in the cases without and with bottom friction in the
X-independent modulation solution. |
dataset/figures/0704_0045_fig3a.eps | Left: Dependence of the mean value
A in the X-independent modulation solution on the
physical space coordinate x without (dashed line) and with (solid
line) bottom friction; Right: Same but multiplied by the Green's law
factor, h^1/4 |
dataset/figures/0704_0045_fig4.eps | Dependence of the surface elevation amplitude a on the space
coordinate x. Dashed line corresponds to the frictionless case and
solid line to the case with bottom friction. |
dataset/figures/0704_0045_fig5a.eps | Left: Riemann invariants behaviour in the similarity
modulation solution for the flat-bottom zero-friction case ; (). |
dataset/figures/0704_0045_fig6a.eps | Characteristics behaviour for the similarity modulation
solution near the leading edge ^+(): (a) families
_1: d/d = v_1 and _2 : =C_2 ,
(b) family _3: d/d = v_3. |
dataset/figures/0704_0045_fig7a.eps | a) Leading edge ^+() of non-self-similar
undular bore as an envelope of pairwise merging characteristics from
the families d/d=v_1 and d/d=v_2; r_3 0. |
dataset/figures/0704_0045_fig8a.eps | Riemann variables behaviour in the vicinity of the
leading edge of the undular bore propagating over gradual slope with
bottom friction (a) Adiabatic variations of the similarity GP
regime, , C_D ; (b) General
case, C_D . |
dataset/figures/0704_0060_fig1.eps | Comparison between experimental Coulomb excitation cross sections (solid
stars with error bars) and theoretical ones, calculated either with eq. cross_2(open
circles), or with eq. approx(open triangles). |
dataset/figures/0704_0060_fig2.eps | Coulomb excitation cross section of ^11Be, ^11B and ^54Ni and of the 13.05 MeV sate in ^16O
projectiles incident on Pb targets as a function of the laboratory energy. |
dataset/figures/0704_0069_postproductionCurrent.jpg | A current comprised of parallel submanifolds smeared and cropped. |
dataset/figures/0704_0082_1sol_comp.eps | Snapshots of one-soliton density profiles. The upper row is plotted for =0 at the moment t=0, with k=0, _0=1, _1=1+, _1=1.27+0.79((x,t)=-(1.57-2.54)x-(8.23-1.94)t) and =hspace*-1mmcc
4/5 -1mm&-1mm2/5\\
2/5-1mm&-1mm1/5
-1mm. The lower row is plotted for 0 at the moment t=0, with the same parameters except for =hspace*-1mmcc
1/2-1mm&-1mm2/5\\
2/5-1mm&-1mm3/(52)
-1mm. The left panel (a) depicts the local density for each component, |_1|^2(solid line), |_0|^2(chain line) and |_-1|^2(dotted line). The center panel (b) depicts the local number density n, where the contribution of the background is included. The right panel (c) depicts the local spin densities, f_x(solid line) and f_z(dotted line). f_y vanishes identically due to a choice of a real matrix .
|
dataset/figures/0704_0082_2sol+pp.eps | Density plots of |_1|^2(a), |_0|^2(b) and |_-1|^2(c) for a mutual collision between two PS-types. The parameters used here are k=1, _0=1, _1=1.03, _3=1.05+, _1=hspace*-1mmcc
1/2-1mm&-1mm/2\\/2-1mm&-1mm0
-1mm, _3=hspace*-1mmcc
0 -1mm&-1mm/2\\/2-1mm&-1mm1/2-1mm. The velocity of the right (left) moving soliton is 2.00(-3.41). The collision takes place at t=0.
|
dataset/figures/0704_0082_2sol+fp.eps | Density plots of |_1|^2(a), |_0|^2(b) and |_-1|^2(c) for a mutual collision between DW-type and PS-type. The parameters used here are the same as those of Fig. fig:ppcollision, except for _1=hspace*-1mmcc
2/3 -1mm&-1mm2/3\\2/3-1mm&-1mm-1/3
-1mm, _3=hspace*-1mmcc
1/2-1mm&-1mm0\\
0-1mm&-1mm-1/2-1mm. The right (left) moving soliton is DW-type (PS-type).
|
dataset/figures/0704_0082_2sol+ff.eps | Density plots of |_1|^2(a), |_0|^2(b) and |_-1|^2(c) for a mutual collision between two DW-types. The parameters used here are the same as those of Fig. fig:ppcollision, except for _1=hspace*-1mmcc
1/2 -1mm&-1mm/2\\/2-1mm&-1mm-1/2
-1mm, _3=hspace*-1mmcc
1 -1mm&-1mm0\\
0-1mm&-1mm0
-1mm. The values more than 2 are colored white.
|
dataset/figures/0704_0094_ana.ps | Analytical timing-predicted dynamical mass vs.
the relative speed of two objects separated by 700 kpc after 10 4 Gyrs
(three lines in increasing order for increasing time)
assuming Keplerian potential of point masses. Three vertical lines indicate typical
Local Group Halo mass, Baryonic mass in galaxy clusters, and most massive CDM halo masses.
Three horizontal lines indicate the error bar of the speed of the X-ray "bullet" gas.
|
dataset/figures/0704_0094_kap.ps | Predicted bullet cluster convergence (rescaled for sources at infinity)
along the line Y=0.3X+cst connecting our two potential centroids.
The model predicts a lensing signal in between that of
observed weak lensing data from sources at z_s=1(Clowe et al, lower end of error bars)
and the united weak lensing and strong lensing (z_s=3) data (Bradc et al.
upper part of error bars); the mismatch of these two datasets are presently unresolved. |
dataset/figures/0704_0094_orb-.ps | The orbit of the bullet subcluster X-ray gas (red, with present V_gas=5400
for the 10 Gyrs in the past, and pink: for the future 4 Gyrs), and the orbits of the colliding main cluster halo
(blue dashes) and subhalo (black dashes) in the potential (eqs. 8-10)
determined by lensing data; dashes indicate length traveled in 0.5 Gyrs steps.
No explicit assumption of gravity is needed for these calculations.
Orbits with different present halo relative velocity V_DM
and halo growth rate C are shown after a vertical shift for clarity.
Timing requires the present cluster relative velocity in between 2800<V_DM<3000
for potentials of normal truncation (lowest panels where the cluster truncation grows from zero to
C 10Gyr =1000), and 4200<V_DM<4750 for potentials with large truncation
(two upper panels where the cluster truncation grows from zero to
C 10 Gyr =10000). |
dataset/figures/0704_0100_accumulation.eps | An example in which no smoothing procedure makes
t|_H a Morse function on H.
Here, the intersection of the crease set S of the event horizon and t=t_0
hypersurface has an accumulation point. |
dataset/figures/0704_0100_isolation.eps | The smoothing procedure of the event horizon H.
The gradient-like vector field on H can be constructed through a slight
deformation of the null geodesic generators of H.
Here, the effect of the crease set S has been replaced by
that of the critical points p_1, p_2 and p_3. |
dataset/figures/0704_0100_critical.eps | The local structure around the critical point p of index .
It can be seen that H_t(p)+ is homeomorphic to
H_t(p)- with a -handle attached.
|
dataset/figures/0704_0100_pot.eps |
The attachment of a 1-handle and a 2-handle to a 3-manifold N
creates a new 3-manifold
N h^1 h^2.
|
dataset/figures/0704_0100_b0-handle.eps | The emergence of a black hole through a 0-handle attachment. |
dataset/figures/0704_0100_w0-handle.eps | The emergence of a bubble in the black hole region by 0-handle attachment,
which does not occur in the real black hole space-times. |
dataset/figures/0704_0100_b1-handle.eps | The collision of a pair of black holes, creating a single black hole,
is realized through
1-handle attachment. |
dataset/figures/0704_0100_wn-1-handle.eps | The bifurcation of one black hole into two is represeted
by an (n-1)-handle attachment.
This, however, never occurs in real black hole space-times. |
dataset/figures/0704_0100_handlebody.eps | The structure of -handle. The core D^\{0\} corresponds
to the stable submanifold with respect to the flow
generated by the gradient-like vector field,
and the co-core \{0\} D^n- corresponds
to the unstable submanifold. |
dataset/figures/0704_0100_U.eps | The neighborhood U of p is separated by h^ into
the future region, U^+, and the past region, U^-. |
dataset/figures/0704_0100_bifurcate.eps | The figure on the left is a conformal diagram of the maximally extended
Schwarzschild space-time. The structure of the event horizon defined with respect to the
two asymptotic ends is depicted on the right, with one dimension omitted. The shaded region
represents the black hole region at the critical time t=t(p).
This corresponds to the 2-handle attachment, where the exterior region
is separated into a pair of connected components. |
dataset/figures/0704_0100_ring_formation.eps | Black ring formation from a spherical black hole must be non-axisymmetric in
real black hole space-times. |
dataset/figures/0704_0106_4q-0.eps | Lowest order and leading-twist contribution to
semi-inclusive DIS. |
dataset/figures/0704_0106_4q-qg.eps | A typical diagram for quark-gluon double scattering with
three possible cuts [central(C), left(L) and right(R)]. |
dataset/figures/0704_0106_4q-d-0.eps | Diagram for leading order
quark-antiquark annihilation with three possible cuts [central(C),
left(L) and right(R)]. |
dataset/figures/0704_0106_4q-d-8.eps | The complex conjugate of Fig.~fig7. |
dataset/figures/0704_0106_4q-Ex-1.eps | A typical diagram for next-to-leading order correction to
quark-antiquark annihilation with three possible cuts [central(C),
left(L) and right(R)]. |
dataset/figures/0704_0106_4q-d-1.eps | The t-channel of q q gg annihilation
diagram with three possible cuts, central(C), left(L) and right(R). |
dataset/figures/0704_0106_4q-d-5.eps | The interference between t and u-channel of
q q gg annihilation. |
dataset/figures/0704_0106_4q-d-14.eps | The s-channel of q q gg annihilation
diagram with only a central-cut. |
dataset/figures/0704_0106_4q-d-9.eps | The interference between t and s-channel of
q q gg annihilation. |
dataset/figures/0704_0106_4q-d-10.eps | The complex conjugate of Fig.~fig9. |
dataset/figures/0704_0106_4q-d-13.eps | s-channel q q q_i q_i
annihilation. |
dataset/figures/0704_0106_4q-d-2.eps | t-channel qq_i( q_i) qq_i( q_i)
scattering. |
dataset/figures/0704_0106_4q-d-3.eps | Interference between s and t-channel of
q q q q scattering |
dataset/figures/0704_0106_4q-d-4.eps | The complex conjugate of Fig.~fig3. |
dataset/figures/0704_0106_4q-d-21.eps | The interference between t and u-channel of
identical quark-quark scattering qq qq. |
dataset/figures/0704_0106_4q-d-7.eps | Interference between final-state gluon radiation
from single and triple-quark scattering. |
dataset/figures/0704_0109_figure1.eps | (Color online) Upper curve in each panel with numerals
indicate the distribution of first, second, third, fourth etc
nearest neighbor distances of SiNW(N) as cut from the ideal Si
crystal, same for structure-optimized bare SiNW(N)(middle curve)
and structure optimized H-SiNW(N) (bottom curve) for N=21, 57 and
81. Vertical dashed line corresponds to the distance of Si-H
bond. |
dataset/figures/0704_0109_figure2.eps | (Color online) Top and side views of optimized atomic
structures of various SiNW(N)'s. (a) Bare SiNWs; (b) H-SiNWs;
(c) single TM atom doped per primitive cell of H-SiNW (n=1); (d)
H-SiNWs covered by n TM atom corresponding to
n>1. E_c, E^_c, E_b,
E^_b, E_G, and , respectively denote the
average cohesive energy relative to free Si atom, same relative to the
bulk Si, binding energy of hydrogen atom relative to free H atom,
same relative to H_2 molecule, energy band gap and the net
magnetic moment per primitive unit cell. Binding energies in
regard to the adsorption of TM atoms, i.e. E_B,
E^_B for n=1 and average values
E_B, E^_B for n >1
are defined in the text and in Ref[binding]. The [001]
direction is along the axis of SiNWs. Small, large-light and
large-dark balls represent H, Si and TM atoms, respectively. Side
views of atomic structure comprise two primitive unit cells of the
SiNWs. Binding and cohesive energies are given in eV/atom. |
dataset/figures/0704_0109_figure3.eps | (Color online) Band structure and spin-dependent total
density of states (TDOS) for N=21, 25 and 57. Left panels:
Semiconducting H-SiNW(N). Middle panels: Half-metallic
H-SiNW(N)+TM. Right panels: Density of majority and minority spin
states of H-SiNW(N)+TM. Bands described by continuous and dotted
lines are majority and minority bands. Zero of energy is set to
E_F. |
dataset/figures/0704_0109_figure4.eps | (Color online) D(E,), density of minority (light) and
D(E,), majority (dark) spin states. (a) H-SiNW(25)+Cr, n=8; (b)
H-SiNW(25)+Cr, n=16. P and indicate
spin-polarization and net magnetic moment (in Bohr
magnetons per primitive unit cell), respectively. |
dataset/figures/0704_0112_PHSS3_arxiv_1.eps | ETs for S=15, N=5,6,7 (nested skyboxes in blue) and
``fractal limit.'' |
dataset/figures/0704_0114_Fig1.eps | (Color online) Dimer pattern in the quantum disordered (VBS) phase,
K/J > (K/J)_c. |
dataset/figures/0704_0114_Fig2.eps | (Color online) Triplon excitation gap = ( k_AF) in various approximations.
The point 0 corresponds to transition to the N\'eel phase. |
dataset/figures/0704_0114_Fig3.eps | Renormalization of quantum fluctuations by resummation of
a ladder series, with (interactionsy) at the vertices. |
dataset/figures/0704_0114_Fig4.eps | (Color online) (a.) Singlet bound state energy E_s(black),
binding energy = 2 - E_s(blue), and the triplon gap (red). (b.) Triplon density n_t. (c.) Dimer order parameters.
Dashed parts of the lines represent points corresponding to rapid growth
of the quasiparticle density. |
dataset/figures/0704_0119_Fig1.eps | (a) The temperature dependence of electrical resistivity of CeAg_2Ge_2, inset shows the low temperature part, (b) Temperature dependence of the magnetic susceptibility together with inverse magnetic susceptibility plot, solid lines indicate the CEF fitting and (c) Magnetization of CeAg_2Ge_2 measured at T~=~2~K. |
dataset/figures/0704_0119_Fig2.eps | (a) Temperature dependence of the specific heat of CeAg_2Ge_2 and LaAg_2Ge_2. The inset shows the magnetic entropy. (b) The field dependence of the specific heat of CeAg_2Ge_2 for the field applied along the easy axis of magnetization, namely [100]. |
dataset/figures/0704_0122_fig1.eps |
Stereographic view of the spin current texture, displaying simultaneously the number and spin densities. The pancake (=0.2)
is distorted and at the center the number density is depleted to give a doughnut like shape. g_d=0.2g. All spins lie in the x-y plane, i.e. a coplanar spin structure, circulating around the origin O. The length of the arrow
is proportional to its number density.
Inset shows the schematic spin configuration on z=0 plane.
|
dataset/figures/0704_0122_fig2.eps |
The r-flare texture. Left (right) column shows the cross-sectional density plots of the particle number (the corresponding spin structure). The circular profile in the x-y plane is spontaneously broken. g_d=0.2g, =0.2. |
dataset/figures/0704_0122_fig3.eps |
Cross sections of the particle number in Fig. fig:rflare along the x and y-axis
compared with Thomas-Fermi (TF) profile for g_d=0.
The profile is elongated (compressed) along
the x(y)-axis. |
dataset/figures/0704_0122_fig4.eps | (a) The z-flare spin texture in the cigar trap along the z-axis.
The spins almost point to the z direction. In the outer regions
they bent. The bright region in background corresponds to high number density.
g_d=0.2g, =5.0.(b) Schematic figure to explain this spin configuration
due to d-d interaction. |
dataset/figures/0704_0122_fig5.eps | (a) The two-z-flare spin texture
under the same parameter set (g_d=0.2g, =5.0.)
as in Fig. fig:zflare with different initial spin configuration.
The bright region in background corresponds to high number density.
(b) Schematic figure to explain this spin structure. At the
z=0 plane two oppositely aligned spins meet and the number density
is depleted.
|
dataset/figures/0704_0128_7530fig1.eps | 2007), created using
the software described in this paper and obtained from the |
End of preview.
Scientific Figures and Captions Dataset from research papers
This repository contains the Scientific Figures and Captions dataset, which includes approximately 4.2 million entries of scientific figures and their corresponding captions extracted from academic papers on arXiv. This dataset is intended for research purposes in the fields of computer vision and natural language processing, particularly for tasks related to image captioning and automated figure analysis.
Dataset Description
The dataset is structured as a Parquet dataframe with two columns:
image_filename: This column contains the relative paths to image files.caption: This column contains the textual captions associated with each image.
Images are stored under dataset/figures/ and are compressed into multiple parts (.z01, .z02, ..., .z103) with a final .zip file that encompasses all parts. This format is used for efficiently handling large datasets.
Extraction Instructions
To access the images, you must first decompress the multi-part ZIP archive. Make sure you have all parts of the archive (.z01 to .z103 and the .zip file) in the same directory. Most decompression tools will recognize and handle multi-part ZIP files seamlessly.
Here is an example using the command line with unzip:
# Navigate to the directory containing the compressed parts
cd dataset/figures
# Use unzip to extract the first set of images
unzip compressedfigures.zip
# combine the second set of images
cat compressedfigures_part2* > compressedfigures_part2.tar.gz
# unzip second set of images
tar xf compressedfigures_part2.tar.gz
# You're good to go!
This will extract the contents into the dataset/figures/ directory. Ensure that you have enough storage space to accommodate the uncompressed images.
Usage Example
To use the dataset in your Python projects, you'll need to read the Parquet file into a DataFrame. Here is an example using pandas:
import pandas as pd
# Load the dataset into a DataFrame
df = pd.read_parquet('dataset.parquet')
# Display the first few entries
df.head()
Once the dataset is loaded, you can use it as follows:
from PIL import Image
import matplotlib.pyplot as plt
# Example function to display an image with its caption
def show_image_with_caption(image_path, caption):
img = Image.open(image_path)
plt.imshow(img)
plt.title(caption)
plt.axis('off') # Hide the axis
plt.show()
# Display the first image and its caption
first_image_path = df.loc[0, 'image_filename']
first_caption = df.loc[0, 'caption']
show_image_with_caption(first_image_path, first_caption)
Acknowledgment
Special thanks to arxiv for providing access to all of the research papers.
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