# Table-top Soft X-ray Source for XAS Experiments with Photon Energies up to
350 eV

O. A. Naranjo-Montoya, M. Bridger, R. Bhar, L. Kalkhoff, M. Schleberger, H.
Wende, A. Tarasevitch*, and U. Bovensiepen  University of Duisburg-Essen,
Faculty of Physics and Center for Nanointegration (CENIDE), Lotharstrasse 1,
47057 Duisburg, Germany<EMAIL_ADDRESS>
###### Abstract

We present a table-top setup for femtosecond x-ray absorption spectroscopy
based on high harmonic generation (HHG) in noble gases. Using sub-millijoule
pump pulses at a central wavelength of 1550 nm broadband HHG in the range 70
to 350 eV was demonstrated. The HHG coherence lengths of several millimeters
were achieved by reaching the nonadiabatic regime of harmonic generation.
NEXAFS experiments on the boron K edge of a boron foil and a hexagonal BN
(hBN) 2D material demonstrate the capabilities of the setup.

††preprint: AIP/123-QED

##  I Introduction

Soft x-ray spectroscopy is a well established methodology which comprises
various photon-in photon-out techniques to probe core level excitations of
atoms, molecules, and condensed matter. X-ray absorption spectroscopy analyzes
the transition from a core level to unoccupied states and x-ray emission
detects the x-ray fluorescence induced by creation of a core hole. While both
techniques provide information on the excited core levels they complement each
other regarding the valence electronic states. X-ray absorption probes the
unoccupied and x-ray emission the occupied valence electronic structure de
Groot (2001).

In the spectral range near the resonant core level excitation element and
orbital selective insights on the unoccupied valence electronic structure are
obtained primarily in near x-ray absorption fine structure absorption
spectroscopy (NEXAFS) Stöhr (1992); de Groot (2001) In the extended spectral
range the locally emitted photoelectron wave function upon resonant core level
excitation is scattered back from the neighboring ion cores in molecules and
condensed matter, which leads to interference effects in the absorption cross
section detected in extended x-ray absorption fine structure absorption
spectroscopy (EXAFS). This technique analyzes the local ion core structure Lee
_et al._ (1981).

More recently, resonant inelastic x-ray scattering (RIXS) has become available
as a tool to measure low energy excitations and their dispersion relation in
momentum space Ament  _et al._ (2011); Gel’mukhanov  _et al._ (2021).

Clearly, x-ray spectroscopy is a very important tool in various fields of the
natural sciences, like, e.g., material science Schnohr and Ridgway (2014); van
der Laan and Figueroa (2014); Franco and Dodrill (2021), interface science xas
(2018), coordination chemistry Penner-Hahn (1999), energy conversion and
catalysis Cutsail III and DeBeer (2022), photosynthesis Yano and Yachandra
(2009), and biology Guilherme Buzanich (2022). Moreover, it is widely used in
conservation of cultural heritage and art Farges and Cotte (2016); Cotte  _et
al._ (2010).

A major effort in setting an x-ray spectrometer is dedicated to the x-ray
source. Early efforts exploited the emission of x-ray tubes Siegbahn (1919);
Sayers  _et al._ (1971). The required spectral resolution and signal to noise
ratio lead to very long times needed for data accumulation in such laboratory
based instruments. The high brilliance provided by synchrotron light sources
resulted in considerable improvement in this regard and nowadays most x-ray
spectroscopy experiments are conducted at synchrotron light sources Malzer
_et al._ (2021). Higher x-ray photon fluxes and shorter pulse durations became
possible after having shifted from storage rings used in synchrotron light
sources to linear accelerators in x-ray free electron lasers which provide
dedicated instruments for soft x-ray spectroscopy Öström  _et al._ (2015);
Baykusheva  _et al._ (2022); Le Guyader  _et al._ (2023); Lojewski  _et al._
(2023).

The limited access to the necessary beam times has always fueled the
development of table-top x-ray light sources and laser-based approaches have
led to considerable success. Essentially two mechanisms of light-matter
interaction are exploited. For table-top x-ray spectroscopy light sources
based on laser plasma generation Jonas  _et al._ (2019); Borchert  _et al._
(2023) and on higher harmonic generation (HHG) in gases Popmintchev  _et al._
(2018); Fan  _et al._ (2022) have been developed. Such laser based sources
allow generation of ultrashort x-ray pulses Chang  _et al._ (1997); Spielmann
_et al._ (1997); Joachain  _et al._ (2000); Brabec and Krausz (2000); Gibson
_et al._ (2003); Popmintchev  _et al._ (2009); Chen  _et al._ (2010), which
provide highly relevant opportunities for pump-probe experiments and time
domain x-ray spectroscopy Kraus  _et al._ (2018). The plasma based approach
provides sufficient photon flux also at hard x-ray photon energies. HHG allows
shorter pulse duration Sidiropoulos  _et al._ (2021) reaching the attosecond
limit; a development that was recognized by awarding the Nobel Prize in
Physics 2023 to P. Agostini, A. L’Huillier, and F. Krausz.

Using mid-infrared femtosecond pump pulses HHG with photon energies exceeding
1 keV became available Popmintchev  _et al._ (2018, 2012), and for competing
with the accelerator based sources in terms of the x-ray photon yield a phase
matched harmonic emission from a larger atomic ensemble becomes essential. The
phase matched HHG by adjusting the gas pressure in the interaction volume has
been discussed and demonstrated for HHG in gas jets Constant  _et al._ (1999);
Geissler  _et al._ (2000); Tempea  _et al._ (2000); Heyl  _et al._ (2012); Tao
_et al._ (2017), in hollow core waveguides (HCWs) DurfeeIII  _et al._ (1999);
Chen  _et al._ (2010); Popmintchev  _et al._ (2009, 2012); Chen  _et al._
(2014); Hernández-García  _et al._ (2016) or both Meyer  _et al._ (2000).
Using HCWs in longitudinal geometry for the HHG is more promising, because of
longer interaction lengths compared to transverse geometry (jets, etc.).
Important limitations in this case, are absorption Constant  _et al._ (1999)
and the necessity to keep the gas pressure in the HCW constant along the
capillary to provide a long coherence length of the HHG.

For the phase matching two types of the phase contributions have to be taken
into account: the time independent (neutral gas dispersion and geometrical
contribution) and time dependent (plasma dispersion and nonlinear refraction).
The time dependent one comes into play at higher pump intensities and the HHG
switches correspondingly from adiabatic to nonadiabatic Rae  _et al._ (1994);
Geissler  _et al._ (2000); Brabec and Krausz (2000) (or time gated Hernández-
García  _et al._ (2016)) regime.

In this paper we demonstrate a table-top x-ray source based on HHG in noble
gases using low energy (compared to Popmintchev  _et al._ (2018, 2012)) pump
pulses at the wavelength of 1550 nm. The generated x-ray pulses were applied
to the measurements of the x-ray absorption spectra (XAS) on the boron K-edge.
We show that switching to the nonadiabatic regime is essential for the phase
matched harmonic emission.

Figure 1: Experimental schematic. A broadband Ti:Sa oscillator is used as a
seed source for both the OPCPA itself and for the pump channel. The 6 fs
pulses at the wavelength of 800 nm are stretched and used as seed for the four
stage OPCPA, consisting of two BBO crystals followed by KTA and LiIO3 stages.
The pump channel is seeded with 1030 nm pulses and consists of a stretcher,
two-stage amplifier and compressor. Part of the pump radiation is converted to
the second harmonic (SH) in an LBO crystal for pumping of BBO stages. BB
stands for beam blocks. After the amplification the pulses are compressed
using CM and MD in ZnSe, BK7, and CaF2. The pulses at the wavelength of 1550
nm are used for pumping of the harmonic source.

##  II Experimental set-up

The pump laser for the HHG was an upgraded version of the optical parametric
chirped pulse amplification (OPCPA) set-up reported in Bridger  _et al._
(2019). Its schematic is depicted in Fig. 1. The system was seeded by a
Ti:sapphire (Ti:Sa) oscillator producing 6 fs pulses at the central wavelength
of 800 nm with an energy of 2.5 nJ per pulse and the repetition rate of 80
MHz. A fraction at the wavelength of 1030$\pm$2 nm of the broad-band
oscillator emission was used to seed the OPCPA pump channel. The 1030 nm seed
pulses were stretched to a 2 ns duration and amplified in a two-stage
amplifier to the energy of 27 mJ. After the amplification, the pulses were
compressed to a duration of 1.2 ps. A 1 mJ fraction of the compressed pulse
energy was frequency doubled and used to pump the first two OPCPA stages.

The 6 fs seed pulses at the central wavelength of 800 nm provided by the Ti:Sa
oscillator were first stretched with the help of a 10 cm BK7 slab to the
duration of 3 ps full width at half maximum (FWHM), which is longer than the
pump pulse duration. By changing the delay between the pump and the strongly
stretched seed pulses, one could choose the central wavelength at which the
amplification takes place.

The set-up was running at the repetition rate of 100 Hz. In the first OPCPA
stage the pump (wavelength 515 nm) and the seed were interacting
noncollinearly in a 3.9 mm thick type I BBO crystal ($\theta$ = 24.3∘). The
noncollinear interaction with the angle of 2.4∘($\theta$ = 24.3∘) allowed
reaching high amplification while keeping a broad amplification spectrum. The
next OPCPA stage was used for the difference frequency generation. The pump at
the wavelength of 515 nm and the signal beam with the central wavelength
shifted to 770 nm were interacting collinearly in order to avoid the angular
chirp of the idler wave. In order to maintain the broad spectral width, a much
shorter (0.6 mm) type I BBO crystal was used. The idler pulses of the second
stage at the central wavelength of 1550 nm were amplified in the third OPCPA
stage. A 3 mm thick type II KTA crystal ($\theta$ = 48.6∘) was pumped by the
pulses at the wavelength of 1030 nm in the noncollinear geometry (noncollinear
angle of $4.2^{\circ}$), providing high amplification in a wide spectrum. In
the fourth and last OPCPA stage, pumped by the 1030 nm pulses, the radiation
at the wavelength of 1550 nm (signal wave) was further amplified up to the
energy of 1.8 mJ per pulse. For this purpose a 4.5 mm thick type I LiIO3
crystal was chosen because of its wide amplification bandwidth for a collinear
interaction. The energy of the idler pulses at the wavelength of 3050 nm
reached 0.8 mJ.

Figure 2: Measured (a) and retrieved (b) SH FROG traces of the pulses at the
central wavelengths of 1550 nm. The retrieved pulse shape (37 fs FWHM) and
spectrum are shown with red solid lines in the panels (c) and (d),
respectively. The blue dashed lines in (c) and (d) represent correspondingly
the bandwidth limited pulse (35 fs FWHM) and the independently measured
spectrum. The black dash-dotted line in (d) shows the retrieved spectral
phase.

For the compression of both signal and idler pulses, combinations of material
dispersion (MD) and chirped mirror (CM) dispersion were employed (Fig. 1).
Such a combination allows better compensation of the second and third order
dispersion and the possibility of dispersion fine-tuning. The pulse durations
were determined using FROG Trebino (2000). An example of the measured and
retrieved second harmonic FROG traces for the signal pulse is shown in Fig. 2a
and b. The retrieved pulse (Fig. 2c) had the duration of 37 fs. The retrieved
spectrum was in qualitative agreement with the independently measured one
(Fig. 2d). The pulse energy after the compression was 1.6 mJ. The duration of
the compressed idler pulses was found to be 43 fs using a third harmonic FROG.
The energy of the compressed pulses was 0.6 mJ.

Figure 3: The beam at the wavelength of 1550 nm is focused at the entrance of
the HCW using a CaF2 lens. The noble gas (Ar, Ne or He) is injected through a
small hole in the center of the HCW. The emission at the output of the HCW is
filtered with a Ti foil and can be used for the XAS of a sample. The
transmitted radiation is spectrally resolved with the help of a concave
grating and recorded using a back-side illuminated CCD camera. Inset: energy
distribution in the focal plane of the CaF2 lens.

For the HHG generation a specially adapted "XUUS" source from KM Labs (USA)
was used xuu . The signal beam at the wavelength of 1550 nm was coupled into
HCW using a 300 mm focal length CaF2 lens (Fig. 3). The HCW with an inner
diameter of 100 $\mu$m and the length of 10 mm was filled with argon, neon or
helium. For the optimum matching of the beam and the EH11 mode of the HCW the
beam waist diameter at 1/e2 was set to 64 $\mu$m. The inset in Fig. 3 shows
the beam energy distribution in the focal plane of the lens. The gas at the
pressure up to 30 bar was injected through a hole in the middle of the HCW
(Fig. 3) and evacuated at its both sides with four roughing pumps.

The emitted radiation from the HCW was filtered with the help of a 200 nm Ti
foil and recorded using a McPherson model 251MX flat field spectrometer with a
Greateyes (GE 2048 515 B1 UV1) charge-coupled device (CCD) camera (Fig. 3).
The spectrometer chamber was pumped out with an additional vacuum pump down to
the pressure of 10-5–10-3 mbar depending on the experimental conditions. The
spectrometer was equipped with a pair of grazing incidence gratings on concave
spherical substrates. The lower photon energy grating (LEG) with 1200
groves/mm and the higher photon energy grating (HEG) with 2400 groves/mm had
nominal wavelength ranges of about 5 to 20 nm (250 to 60 eV) and about 1 to 6
nm (1240 to 200 eV).

Figure 4: Top panel: calculated gas density distribution along the axis of the
HCW ($X$-axis). The distribution is symmetric with respect to the middle of
the waveguide (X =0). Bottom panel: measured (solid lines) and calculated
(dashed and dash-dotted lines) third harmonic spectra at the output of a He-
filled HCW. The pump intensity was about $5\times 10^{14}$ W/cm2. Red solid
and black dash-dotted lines correspond to a low He pressure. Blue solid and
black dashed lines represent the spectra for a high He pressure. Figure 5:
Normalized high harmonic emission in Ar (left panel), Ne, and He (right panel)
using the 1550 nm fundamental wavelength. In case of Ar the spectrum was
recorded using the LEG, while for Ne and He the HEG was used. The pump
radiation and lower harmonics were cut using a 200 nm thick Ti-foil. The
dashed blue line corresponds to transmission of a 3 mm path in He at 5 bar and
the Ti-foil.

##  III Switching to the nonadiabatic regime

Due to a constant gas flow through the HCW, a gas density drop is expected
along the waveguide axis. Figure 4, top panel shows the density distribution
along the axis calculated using an Autodesk CFD (Computational Fluid Dynamics)
software. Below we estimate the influence of this gradient on reaching the
phase matched harmonic emission.

The wave vector mismatch $\Delta k$ between the q-th harmonic and the
corresponding polarization wave induced by the pump can be expressed as (see
e.g. Popmintchev  _et al._ (2009))

$\Delta
k=-q\frac{2\pi}{\lambda_{L}}(n_{L}-1)(1-\eta)p+qN_{a}r_{e}\lambda_{L}\eta
p+q\frac{u_{nm}^{2}\lambda_{L}}{4\pi a^{2}},$ (1)

where $n_{L}$ is the refractive index of the gas at the pump wavelength
$\lambda_{L}$, $\eta$ is the ionisation fraction of the gas, $N_{a}$ is the
number density of atoms, $r_{e}$ is the classical electron radius, $u_{mn}$ is
the capillary mode factor, and $a$ is the capillary radius. Both $n_{L}$ and
$N_{a}$ are taken at the pressure of 1 bar and $p$ is the gas pressure in bar.
The factor $1-\eta$ takes into account the reduction of neutral atoms due to
ionization. In (1) we have neglected the nonlinear refractive index of the
gas.

The phase matching pressure tolerance is given by $\Delta p=\Delta
k_{FWHM}(d\Delta k/dp)^{-1}$. Above $\Delta k_{FWHM}$ corresponds to the full
width at half maximum of harmonic intensity as a function of $\Delta k$ and
satisfies the condition $\Delta k_{FWHM}=5.56/L$ dK , where $L$ is the
interaction (HCW) length. In the adiabatic regime with $\eta\approx 0$ one
gets:

$\Delta p(\eta=0)=\frac{5.56}{2\pi}\frac{1}{n_{L}-1}\frac{\lambda_{q}}{L},$
(2)

above $\Delta p(\eta=0)$ is the pressure tolerance in the adiabatic regime and
$\lambda_{q}$ is the wavelength of the q-th harmonic. Simple estimations show
that for harmonics with about $1\>keV$ photon energy using $\lambda_{L}=$1550
nm and $L=$ 1 cm $\Delta p(\eta=0)$ lies in the mbar range and no phase
matching along the HCW is possible.

At higher intensities with the developing ionisation the phase matching can be
achieved for the fraction of a pump pulse because of the time dependent $\eta$
(nonadiabatic or time gated regime Rae  _et al._ (1994); Geissler  _et al._
(2000); Brabec and Krausz (2000); Hernández-García  _et al._ (2016)). However,
the pressure tolerance can be sufficiently increased. Indeed, it follows from
(1) that

$\Delta p(\eta)=\frac{\Delta p(\eta=0)}{1-\eta/\eta_{cr}},$ (3)

where $\Delta p(\eta)$ is the pressure tolerance in the nonadiabatic regime
and $\eta_{cr}$ is the critical ionization fraction, starting from which the
phase matching is no more possible
($\eta_{cr}=[\lambda_{L}^{2}N_{a}r_{e}/(2\pi(n_{L}-1))+1]^{-1}$ Popmintchev
_et al._ (2009); DurfeeIII  _et al._ (1999)).

The possibility of switching to the nonadiabatic regime in our experiments was
checked for helium, because it has the highest ionization potential. The
ionisation onset was monitored by measuring the blue shift of the spectrum of
the third harmonic at the HCW output using a compact Ocean Optics USB
spectrometer (Fig. 4, bottom panel). The pump intensity was about $5\times
10^{14}$ W/cm2. At low He input pressures (<100 mbar) the generated electron
density is too low and no shift is observed (red solid curve). At 4 bar the
blue shift $\Delta\lambda_{3\omega}$ of about 25 nm was measured. Assuming the
ratio of the fundamental shift $\Delta\lambda_{\omega}$ to that of the third
harmonic to be about 2, as our simulations show, one gets
$\Delta\lambda_{\omega}\approx 50~{}nm$. This shift corresponds to the
electron production rate of $d\langle n_{e}\rangle/dt\approx 10^{15}$ cm-3
fs-1, where the angle brackets indicate averaging along the HCW. Dividing this
rate over $N_{a}\langle p\rangle$ one gets $d\eta/dt\approx 2\times
10^{-5}\>fs^{-1}$. At this rate the ionization fraction $\eta$ can approach
$\eta_{cr}$ (which is about 10-3) within the pulse duration, and according to
(3) a larger pressure tolerance can be achieved.

##  IV High Harmonic Generation

Figure 5 shows the harmonic spectra generated in the nonadiabatic regime using
Ar, Ne, and He. Altogether the spectra cover the range from about 70 to about
350 eV. For maximum harmonic emission the pressures and pump energies were 1.5
bar and 0.3 mJ for Ar, 3.7 bar and 0.7 mJ for Ne, and 9.3 bar and 0.8 mJ for
He. Furthermore the pulse duration was increased to 54 fs. The photon fluxes
at the maxima of the spectra were 107, 104, and 105 ph/s in a fractional
bandwidth of 1% for Ar, Ne, and He, respectively. The high energy cut-offs of
the spectra follow the well-known low $\hbar\omega=I_{p}+3.17U_{p}$ Corkum
(1993) with the ponderomotive potential $U_{p}=9.33\times
10^{14}I_{L}\lambda^{2}_{L}$, where $I_{p}$ and $I_{L}$ are the gas ionization
potential and laser intensity, respectively. The gap at about 284 eV in the
case of He corresponds to the carbon K-edge and is due to the carbon
contamination of the spectrometer.

Figure 6: Pressure dependence of the HHG intensity in He. Inset: Spatial
distribution of the harmonic emission at the position of the entrance slit of
the spectrometer

The decay on the low energy side of the spectra is due to the absorption in
the gas and in the Ti foil abs ; Nagasaka (2020). The dashed blue line in Fig.
5 shows the calculated transmission of He together with the foil. The He
pressure was assumed to be 5 bar, which is the average pressure at the end of
the capillary according to Fig. 4. The path length in He was taken to be 3 mm
corresponding to the best match to the measured spectrum. The good agreement
indicates, that in spite of a considerable pressure gradient in the HCW (Fig.
4, left panel) switching to the nonadiabatic regime allows the effective HHG
length of several millimeters.

The pressure dependence of the intensity of the harmonic emission for the He-
filled HCW is shown in Fig. 6. The quadratic growth of the intensity and
saturation at a certain "optimum" pressure indicates the onset of the phase
matched HHG. The shape of the harmonic beam at the entrance slit of the
spectrometer can be evaluated from its image (see inset to Fig. 6) recorded
with the CCD-camera using HCW filled with He. The image is taken in the 0th
diffraction order of the spectrometer grating with the slit widely open (2.5
mm width). The beam is slightly elliptic with vertical and horizontal sizes of
about 2 mm FWHM.

##  V Near Edge X-ray Absorption Fine Structure (NEXAFS)

The generated harmonic spectra allow XAS measurements on carbon and boron
K-edges. In our experiments we have focused on the boron edge, which has been
shown to be very informative in several boron compounds Jiménez  _et al._
(1999). A set of two samples with different boron configurations was placed in
the harmonic beam and the transmitted spectrum was measured with our
spectrometer described above (see Fig. 3). A vacuum filter wheel was used as a
sample holder and allowed a rapid exchange of the samples without breaking the
vacuum. The first studied sample was a 100 nm thick boron foil, supported by a
nickel mesh (Lebow Co). The second one was a 5 mm$\times$5 mm stack of hBN
monolayers with a total thickness of 96 nm. The sample was supported by a
Si3N4 substrate with a thickness of 200 nm.

Figure 7: Comparison of the transmission spectra (green-filled areas) and
reference harmonic spectra (violet-filled area) The samples were a boron foil
(top) and an hBN sample (bottom). In the top panel the dashed blue line
corresponds to absorption in 200 nm Ti-filter and a path of 3 mm in He at the
pressure of 5 bar (top). In the bottom panel additionally a 200 mm Si3N4
substrate is taken into account and the best fit is achieved with a 2.5 mm
path.

Figure 7, shows the corresponding transmission spectra of the samples (in
green) together with the reference HHG spectra (in violet), which were
captured without the samples in the beam path. The spectra are normalized to
the maxima of the corresponding reference. Each spectrum was obtained in a
total time of 20 to 30 min. A clear difference in the transmitted spectra can
be observed.

Figure 8 represents the retrieved XAS for the boron foil and the hBN sample.
The retrieved spectrum of the boron foil (Fig. 8, top panel) is in good
agreement with the one recorded by Jiménez et al. Jiménez  _et al._ (1999)
using polycrystalline boron at the Stanford Synchrotron Radiation Lightsource.
Both spectra show a step starting with the edge jump around 190 eV and going
up to around 195 eV, followed by a broad feature of higher amplitude up to 210
eV.

Figure 8: XAS for a boron foil (top panel) and a hBN (bottom panel). Red solid
lines represent the absorption spectra calculated from those shown in Fig. 7.
The blue dashed lines correspond to the measurements by Jiménez et al. Jiménez
_et al._ (1999) (top panel) and Wang et al. Wang  _et al._ (2015) (bottom
panel). Vertical black dashed lines indicate the positions of the $\pi^{*}$\-
and most intense $\sigma^{*}$ resonance of hBN. Inset in the bottom panel
illustrates schematically the orientation of the electric field of the pulse
with respect to the $\pi^{*}$ and $\sigma^{*}$ orbitals in the 2D hBN layers.

The retrieved NEXAFS of hBN agrees well with the measurements of the XAS fine
structures by Wang et al. Wang  _et al._ (2015). The well-resolved spectral
structure can be attributed to the known resonances of hBN. The spectral
resolution of 2 eV was estimated by comparing the measured and the reference
curves in the Fig. 8, bottom. The peak at 192 eV is the $\pi^{*}$ resonance,
while the features at 198, 199, 204, 206 and 213 eV are due to different
$\sigma^{*}$ resonances Wang  _et al._ (2015). The relatively weak
contribution due to the $\pi^{*}$ resonance in our measurements can be
attributed (as well as in Wang  _et al._ (2015)) to the fact that the HHG beam
was nearly orthogonal to the sample, which is a 2D material. In this case the
electric field, which lies predominantly in the plane of the hBN layers (see
inset in Fig. 8) cannot effectively excite the $\pi^{*}$ resonance, because
for the transition 1s - $\pi^{*}$ the scalar product of the field and the
corresponding matrix element of the dipole momentum is small.

##  VI Conclusions

In conclusion, we have presented a table-top soft x-ray source for XAS
experiments with a 100 Hz repetition rate. The source is based on HHG in a
noble-gas-filled HCW pumped with pulses at the wavelength of 1550 nm. It
produces broadband spectra with the photon energies from 70 to 350 eV. Bcause
of a small diameter HCW (100 $\mu$m) the x-ray emission is generated by pump
pulses with the energies below 1 mJ. In spite of a substantial pressure
gradient along the HCW, switching to the nonadiabatic regime allows reaching
coherence lengths of the HHG of several millimeters. A longer (1 cm) HCW
allows a moderate gas consumption and pump rates of the vacuum pumps. With the
He filled HCW photon fluxes of about 105 ph/s at an energy of 270 eV in a
fractional bandwidth of 1% are reached. The characteristics and the overall
performance of the setup have been demonstrated with NEXAFS measurements on
the B K-edge with a 2 eV energy resolution and 20–30 min averaging per
recorded spectrum for a boron foil and a hBN sample.

The source provides opportunities for femtosecond time-resolved pump-probe XAS
measurements.

The higher photon energy of the HHG source can be achieved by switching to the
idler pulses with the central wavelength of 3050 nm (see Fig. 1. Switching to
the nonadiabatic regime also with these pulses will be possible after a
planned upgrade of the set-up.

##  VII Acknowledgments

We thank Margaret Murnane and Henry Kapteyn for fruitful discussions.

We acknowledge financial support by the Deutsche Forschungsgemeinschaft
through SFB 1242 (project number 278162697, TP A05).

##  VIII Author declarations

###  VIII.1 Conflict of Interests

The authors have no conflicts to disclose.

###  VIII.2 Author Contributions

O. Naranjo-Montoya: Investigation(lead), Data Curation (equal), Resources
(equal); M. Bridger: Resources (equal); R. Bhar: Resources (equal); L.
Kalkhof: Resources (equal); M. Schleberger Resources (equal); H. Wende:
Conceptualization (equal), Funding Acquisition (equal), Writing/Review &
Editing (equal); A. Tarasevitch: Investigation(supporting), Resources (equal),
Software (lead), Data Curation (equal), Methodology (leading), Funding
Acquisition (equal), Writing/Original Draft Preparation (equal),
Writing/Review & Editing (equal); U. Bovensiepen: Supervision(lead),
Conceptualization (equal), Funding Acquisition (equal), Writing/Original Draft
Preparation (equal), Writing/Review & Editing (equal). All authors provided
critical feedback and helped shape the research, analysis and manuscript.

##  IX Availability of Data

The data that support the findings of this study are available from the
corresponding author upon reasonable request.

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# A Vision on Open Science for the Evolution of Software Engineering Research
and Practice

Edson OliveiraJr  State University of MaringáMaringáBrazil<EMAIL_ADDRESS>,
Fernanda Madeiral  Vrije Universiteit AmsterdamAmsterdamNetherlands
<EMAIL_ADDRESS>,  Alcemir Rodrigues Santos  State University of
PiauíPiripiriBrazil<EMAIL_ADDRESS>,  Christina von Flach  Federal
University of BahiaSalvadorBrazil<EMAIL_ADDRESS>and  Sergio Soares  Federal
University of PernambucoRecifeBrazil<EMAIL_ADDRESS>
(2024; 2024-01-29; 2024-04-09)

###### Abstract.

Open Science aims to foster openness and collaboration in research, leading to
more significant scientific and social impact. However, practicing Open
Science comes with several challenges and is currently not properly rewarded.
In this paper, we share our vision for addressing those challenges through a
conceptual framework that connects essential building blocks for a change in
the Software Engineering community, both culturally and technically. The idea
behind this framework is that Open Science is treated as a first-class
requirement for better Software Engineering research, practice, recognition,
and relevant social impact. There is a long road for us, as a community, to
truly embrace and gain from the benefits of Open Science. Nevertheless, we
shed light on the directions for promoting the necessary culture shift and
empowering the Software Engineering community.

Open Science, artifacts, research software, education, culture shift

††copyright: acmlicensed††doi: 10.1145/3663529.3663788††journalyear:
2024††submissionid: fsecomp24ivr-p93-p††isbn:
979-8-4007-0658-5/24/07††conference: Companion Proceedings of the 32nd ACM
International Conference on the Foundations of Software Engineering; July
15–19, 2024; Porto de Galinhas, Brazil††booktitle: Companion Proceedings of
the 32nd ACM International Conference on the Foundations of Software
Engineering (FSE Companion ’24), July 15–19, 2024, Porto de Galinhas,
Brazil††ccs: Software and its engineering

##  1\. Introduction

In the 21st century, the Open Science movement is a significant paradigmatic
transformation entailing a systemic change in science and research in all
disciplines. It designates the practice of science in a way that (i) others
can collaborate and contribute, and (ii) publications, data, software, and
other research artifacts are made available, reusable, and reproducible
(United Nations Educational and, UNESCO; Munafò et al., 2017). In addition,
Open Science practices combat fraud and improve research rigorousness
(Seibold, 2024).

However, as many significant transformations and innovations in the history of
science had to deal with multiple challenges and barriers (National Academies
of Sciences, Engineering, and Medicine, 2018), Open Science benefits also come
with their own. Bartling and Friesike (2014) defined the transition towards
Open Science as a complex cultural change, and Guzzo et al. (2022) stressed
some incompatibilities between Open Science principles and scientific progress
through applied research. This suggests no straightforward recipe for
embracing Open Science, but a series of actions should be taken.

In Software Engineering, there has been some discussion about Open Science.
For instance, Mendez et al. (2020) discuss Open Science practices, e.g., open
materials and registered reports, and how the Empirical Software Engineering
community can adopt them. With regard to education and training, researchers
and representatives for research laboratories and funding agencies have joined
meetings and workshops to discuss the need for Research Software Engineers and
possible actions (US-RSE.org, 2022; WOSSS, 2024; Katz and Hettrick, 2023).

Although preliminary discussion exists in the literature, it still lacks an
answer to the question: “How can our Software Engineering community adopt the
Open Science movement?” (Mendez et al., 2020). Researchers can no longer
ignore or treat Open Science issues as incidental but adopt them as a first-
class research requirement. For instance, several universities are currently
restructuring their research career assessment process, shifting careers from
a paper-based model to a social-contribution-based one (Chawla, 2021). Such a
change comes with Open Science principles and practices attached (National
Academies of Sciences, Engineering, and Medicine, 2018), and Software
Engineering researchers will increasingly need to work their way toward
putting those into practice. Accordingly, research artifacts are present in
any research project and should, therefore, be recognized, evaluated, and
published together with the associated papers for the sake of Open Science.

In this paper, we share our reflections and visions about Open Science, with a
focus on research artifacts, as an attempt to structure future research to
answer Mendez et al. (2020)’s question. Artifacts are the backbone of research
projects and, consequently, of research papers. Although creating and sharing
reusable research artifacts is challenging, they allow transparency,
replications, and reuse in new research projects, making it possible for a
research community to mature. We present our vision as a framework relating
actions that should be taken toward Open Science in Software Engineering.

##  2\. Our Vision

Figure 1 shows an overview of our vision for addressing the challenges in
adopting Open Science practices, where building blocks that support each other
are connected. First, the modern Software Engineering research career has to
rely on Open Science principles and practices in its recognition and reward
system (Howison and Herbsleb, 2011). Research artifacts should be considered
as a part of research publication, just like papers are. Moreover, research
software should be accompanied by infrastructure-as-code to improve the
Empirical Software Engineering practice, as well as to support artifact
evaluation during paper or artifact review. To realize those, we need to
address Open Science education and training so that the research community
follows Open Science principles by design (National Academies of Sciences,
Engineering, and Medicine, 2018) in their research. Finally, Open Science
tooling is required to support researchers with several tasks in several
contexts. We elaborate on each building block in the following sections.

Figure 1. Our vision on Open Science for Software Engineering research and
practice.

###  2.1. Recognition and Reward System

Published papers and citations are the coins to pay for the researchers’ work
(Howison and Herbsleb, 2011). However, source code, curated datasets, evidence
briefings, and research software all have value in the construction of
Software Engineering knowledge. Preparing and sharing them is challenging and
time-consuming, which might be seen as not worth it if such an effort is not
properly recognized and rewarded. Therefore, we need more space to produce,
cite, and get recognition from different types of research artifacts. We argue
that such recognition should go beyond paper badging through Artifact
Evaluation Tracks, which is how researchers get some reward for producing and
sharing good artifacts. In our vision, artifacts should be valued in the
science ecosystem, and researchers should be assessed by taking their Open
Science practices into account.

####  2.1.1. Valuing Artifacts in the Science Ecosystem

Research software exists in many kinds of research due to the need for
automated data analyses. In Software Engineering, it is also often the case of
prototypes that serve as proof for proposed approaches that would ideally be
used by developers in the industry. Sharing them is important for scientific
advancement because several research projects rely on research software from
previous work. However, they end up hidden in the results of a research
publication. This is because research papers are the ultimate concrete object
considered as the result of a research project. Research software and other
artifacts, on the other hand, are not. Because of their importance, beyond
software citation (Katz et al., 2021), there should exist additional
mechanisms for recognizing and valuing research software and other artifacts
in the science ecosystem, e.g., a Google Scholar for research software, other
artifacts, and open reviews with blockchain-based token rewards (Santos,
2021).

####  2.1.2. Researcher Assessment

Any assessment of researchers, e.g., Ph.D. evaluation for obtaining the
degree, hiring processes, and career assessment for promotions (Commission et
al., 2017), considers publications but rarely research artifacts. Preparing
and sharing research software is challenging and time-consuming, and
researchers might neglect it due to a lack of recognition and reward. While
researcher assessment is mainly done over publications, Open Science practices
have started to be required by funding agencies, e.g., in the Netherlands
(Chawla, 2021). This is due to initiatives for more research openness and
sustainable software, which should be expanded in all events assessing
researchers. The adoption of Open Science principles and practices in Software
Engineering research may change incentive and reward systems (Howison and
Herbsleb, 2011, 2013), promoting balanced recognition of papers and research
artifacts.

###  2.2. Research Publication

Research papers are the main, and sometimes only, concrete outcome of a
research project. This is how research has been published and disseminated.
However, research artifacts are part of any research project and, therefore,
should be published together with the associated papers for the sake of Open
Science.

####  2.2.1. Paper Review

Researchers submit their papers to journals and conferences, which are
evaluated based on a series of criteria. These criteria usually include
relevance, novelty, soundness, and clarity. However, compliance with Open
Science policies is often neglected. Even though some conferences have defined
evaluation criteria for verifiability and transparency, artifact evaluation is
still optional. For instance, the call for papers for the ICSE 2024 research
track includes the following criteria: “Verifiability and Transparency: The
extent to which the paper includes sufficient information to understand how an
innovation works; to understand how data was obtained, analyzed, and
interpreted; and how the paper supports independent verification or
replication of the paper’s claimed contributions. Any artifacts attached to or
linked from the paper may be checked by one reviewer”. Moreover, although one
reviewer may check artifacts, acceptance is not conditional to artifact
sharing. In our vision, artifact sharing, or a compelling justification for
not doing so, should be a requirement for acceptance, independent of other
reviewing criteria. If not enforced, changing the current practice will be
difficult because researchers will naturally prefer to focus their time on
other activities than on an optional task.

####  2.2.2. Artifact Evaluation Tracks

Artifact Evaluation Tracks call for submissions of artifacts produced for
already accepted papers. The calls include a set of badges that are supposed
to stamp papers indicating the availability or quality of the artifacts
related to the papers. Researchers submit artifacts claiming for specific
badges, which are evaluated according to the reward criteria. Even though
paper badging is the current way researchers are rewarded for producing and
sharing good research artifacts, the existence of Artifact Evaluation Tracks
also means that creating and sharing reusable artifacts is not the default
expected outcome from researchers. This does not comply with the idea of the
Open Science movement. Therefore, artifact evaluation should be either
directly incorporated in the paper reviewing process (when the community has
the proper resources for that, see Section 2.4 and Section 2.6), or should
exist only for advanced recognition (e.g., for the ACM “Results Validated”
badges (ACM, 2020)).

###  2.3. Empirical Software Engineering

Empirical Software Engineering has played a central role in the last decades
as an effective way to provide reliable evidence for various research topics.
However, such studies have not practically evolved concerning reproducibility,
transparency, and openness (Gonzalez-Barahona and Robles, 2023). Open Science
practices and principles might contribute to effectively evolving Software
Engineering empirical studies in the following four perspectives.

####  2.3.1. Reproducibility

The reproducibility of empirical studies might be reached by defining open
data life cycles and providing a detailed description of artifact provenance,
preservation, and curation. Such Open Science characteristics make empirical
studies able to be audited and reproducible, thus allowing one to understand
the whole data and artifacts cycle, provenance, and prospective traceability
of evidence (Chirigati et al., 2016; Rampin et al., 2018; Pimentel et al.,
2017; Cordeiro, 2022; Cordeiro and OliveiraJr, 2021; OliveiraJr et al., 2021).
Open replication packages also contribute to reproducibility. They should
include all analyzed data (open data), research software (e.g., scripts),
workflows, and other research artifacts necessary to comprehend and run the
study. In addition, they should follow the FAIR (Wilkinson et al., 2016)
principles for findable, accessible, interoperable, and reusable data.
Provenance techniques must support such packages to guarantee their
traceability over time, derivation, and manipulation techniques that might
affect previous and prospective studies and curation procedures.

####  2.3.2. Sustainability

As the research evolves, new replication packages are made available, thus
demanding preservation techniques aimed at keeping data and other artifacts
conserved and maintained. In addition, such techniques must consider policies
for Green Computing (Paul et al., 2023) most related to energy consumption to
the long-term keeping of artifacts deposited in repositories.

####  2.3.3. Registered Reports

Registered reports are essential for rigorous empirical research. They
contribute to avoiding misconduct and planning to deviate by establishing a
peer-reviewed protocol before an empirical study is conducted (National
Academies of Sciences, Engineering, and Medicine, 2018). Although they are
little explored in the Software Engineering literature (Ernst and Baldassarre,
2023), they represent a way of putting Open Science into practice by, for
instance, demanding them for artifacts provenance and preservation,
encompassing a Data Management Plan (DMP) for peer reviewing of such report,
thus a fair operation.

####  2.3.4. Widely Evidence Dissemination

Most empirical studies in Software Engineering lack proper dissemination of
their findings, especially their artifacts. Finding documented study protocols
or even their data for reproducibility is not trivial. Therefore, open
empirical portals might effectively aid researchers and practitioners in
localizing such artifacts. Such portals must encompass formal descriptions of
empirical studies from ontologies, for instance, with proper metadata, as well
as implementing features to facilitate users to perform Open Science practices
such as provenance and curation (Cordeiro, 2022). These portals might
integrate with open repositories such as Zenodo or FigShare via APIs to
deposit large artifacts and receive a unique identification as a DOI (Santana
et al., 2023).

###  2.4. Infrastructure-as-Code for Research Software

Research software supports studies reported in scientific papers (Cohen et
al., 2021). Several kinds of studies that build upon previous research, e.g.,
replications and empirical comparisons, would require access to research
software produced in previous research, as well as clear and complete
documentation to properly execute it. However, sharing reusable research
software is challenging due to its dynamic nature (Wiese et al., 2020).
Sharing also involves knowledge about several steps to execute and operate
software, such as installation and configuration, a challenge also faced by
professionals who develop or operate software systems in the industry.

Even if authors can make research software available with proper
documentation, it might be challenging for researchers to follow all the
instructions to execute it and reproduce results. As with replications and
reuse of software in new research projects, artifact evaluation also requires
executing research software, depending on the artifact kind. This comes with
additional challenges, including the lack of knowledge from reviewers on the
research software, the potential need for familiarity with the research topic
it belongs to, and limited time to read a full paper and execute many steps to
verify if the software produces what it should.

In our vision, researchers should make research software available accompanied
by infrastructure-as-code. Infrastructure-as-code is the practice of preparing
an infrastructure for running a software system by means of executable code.
In such a format, whoever runs the software system would not need to read and
understand documentation and then manually create and prepare the
infrastructure. Instead, a script would do this task, allowing the successful
execution of research software in an easier way. In combination with automated
pipelines, if research software is made available with infrastructure-as-code,
one could execute one single command that would result in a table or figure
reported in a paper, for instance. Such a feature would make reproducing
results and evaluating artifacts so easy that paper-related tracks could
incorporate Artifact Evaluation as a criterion for accepting a paper.

###  2.5. Open Science Education and Training

A short-term concern for Software Engineering research and practice is the
need for education and training on Open Science and Research Software. This
involves the development, adaptation, or systematization of the openness
definition (Levin et al., 2016), open methodologies, courses, and workshops
mainly based on Open Educational Resources (e.g., syllabi, materials, web
portals, and MOOCs).

####  2.5.1. Open Science Education by Design

Open Science by Design refers to principles and practices to foster openness
throughout the entire research life cycle by making research artifacts
associated with their publications openly available under the FAIR principles
(National Academies of Sciences, Engineering, and Medicine, 2018). We envision
Open Science Education by Design as a set of strategies for introducing Open
Science principles and practices in formal education as early as possible. In
Software Engineering Education, potential strategies may address them in one
discipline or as topics that crosscut several disciplines. Students’
comprehension can be assessed by direct application in an authentic research
context, such as graduate and undergraduate theses.

####  2.5.2. Open Science 101

Open Science may be introduced in Software Engineering curricula as Open
Science 101, an introductory course addressing core Open Science concepts, the
fundamentals of methods, practices, and tools for reproducible research
(OpenSciency Contributors, 2023), and recommending them for undergraduate
research projects. An update to the Software Engineering curriculum guidelines
(Ardis et al., 2015), for instance, could include these topics in a new
knowledge unit called “Open Science Foundations for Software”.

####  2.5.3. Research Software Education and Training

Scientists often develop domain software (Hettrick et al., 2015) to support
their research, and reproducibility requires it to be open and sustainable.
Still, researchers need to be aware of Software Engineering best practices,
including licenses, version control, coding standards, code documentation,
testing, and release engineering (FOSTER, 2023; Carpentries, 2023). Basic
training on such practices is vital for fostering reproducible research.
Alternatively, research software engineers can provide professional support
concerning research software to domain scientists.

####  2.5.4. Research Software Engineers

A research software engineer combines professional Software Engineering
expertise with an understanding of research (RSE.org, 2024) to work as an
integral member of research groups or institutions, addressing the challenges
of developing high-quality complex and customized software systems under Open
Science principles for various scientific domains (Consortium, 2024; RSE.Shef,
2024).

We envision at least two practical approaches to supporting such knowledge and
skills: a 4-year Software Engineering undergraduate degree with specialized or
intensive research-focused courses at the 4th year level (honors degree) and
new graduate programs (e.g., Masters in Research Software) with fundamentals
from Open Science 101 and new knowledge units. These should include (1) Open
and FAIR Research Data; (2) Open, FAIR, and Sustainable Research Software; (3)
Software Engineering for Research Software (quality attributes, open licenses,
documentation, life cycle models, development and maintenance, testing and
analysis, and CI/CD); (4) Recognition, Curation, and Preservation of Research
Software; (5) Infrastructure-as-Code for Research Software; (6) HPC and AI
applications for large and complex tasks; and (7) Open Science tools.

###  2.6. Open Science Tooling

One challenge in practicing Open Science is the scarcity of tools to aid
researchers in producing, assessing, and making research artifacts available
and reusable in compliance with Open Science principles. For instance, FAIR
guiding principles for Data (Wilkinson et al., 2016) and Research Software
(Chue Hong et al., 2022) help researchers think about their research artifacts
and how to make them available and reusable. However, tool support is needed
for researchers and artifact reviewers to assess how compliant such artifacts
are with Open Science and FAIR principles. One well-known challenge is to deal
with sensitive data. Researchers may not share sensitive data because
preparing the data to avoid leaking confidential information is difficult and
time-consuming. Tools for aiding researchers in handling such cases would
foster data sharing.

Our vision is that more specific tooling is needed to help researchers with
several tasks, considering several conditions, for the openness and assessment
of research artifacts. One such example is Anonymous GitHub (Durieux, 2023),
proposed and extensively used for anonymizing GitHub repositories, allowing
researchers to share their artifacts during the double-anonymous review
process. Other useful tools include the set of tools of the OpenAire
initiative for promoting Open Science, such as EOSC and FAIRCORE4EOSC, the
European Open Science Cloud (OpenAire, 2024), Reprozip (Chirigati et al.,
2016), ReproServer (Rampin et al., 2018), and NoWorkflow (Pimentel et al.,
2017).

##  3\. Final Remarks

To situate the adoption of Open Science in Software Engineering research and
practice, we use an analogy to the adoption of Empirical Software Engineering
practices 20 years ago. Empirical Software Engineering has played a central
role in the last decades as an effective way to provide reliable evidence for
various research topics. However, its broad adoption began when Software
Engineering venues enforced its principles and evaluation methods in their
calls for papers and review processes, and graduate programs promoted
education in Empirical Software Engineering. In our vision, a similar culture
shift is underway in the context of Open Science adoption in Software
Engineering research and practice. This adoption requires efforts on Open
Science education and training, valuing openness in Empirical Software
Engineering, better infrastructures and tools to support Open Science
practices, Open Science-aware paper reviewing and artifact evaluation tracks,
and changes in the current recognition and reward systems.

The Software Engineering community should not treat Open Science as incidental
and start seamlessly adopting its principles and practices, for instance,
while writing papers, sharing research artifacts, rewarding artifacts and
papers that share them, or evaluating a CV for a research position.

###### Acknowledgements.

Edson OliveiraJr thanks CNPq grant #311503/2022-5. Fernanda Madeiral is
partially supported by the European Commission grant 101120393 (Sec4AI4Sec)
and the Dutch Research Council (NWO). Sergio Soares is partially supported by
CNPq grant 306000/2022-9. This work is partially supported by INES 2.0
(www.ines.org.br), CNPq grant 465614/2014-0, FACEPE grants APQ-0399-1.03/17
and APQ/0388-1.03/14, CAPES grant 88887.136410/2017-00.

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