# Phase diagram of the ionic Hubbard model with density-dependent hopping

P. Roura-Bas  Centro Atómico Bariloche, GAIDI, CONICET, 8400 Bariloche,
Argentina  A. A. Aligia  Instituto de Nanociencia y Nanotecnología CNEA-
CONICET, GAIDI, Centro Atómico Bariloche and Instituto Balseiro, 8400
Bariloche, Argentina

###### Abstract

We obtain the quantum phase diagram of the ionic Hubbard model including
electron-hole symmetric density-dependent hopping. The boundaries of the
phases are determined by crossing of excited levels with particular discrete
symmetries, which coincide with jumps of charge and spin Berry phases with a
topological meaning. Reducing the magnitude of the hopping terms that do not
change the total number of singly occupied sites with respect to the other
one, the region of the phase diagram occupied by the fully gapped
spontaneously dimerized insulator (which separates the band insulating and
Mott insulating phases) is enlarged, particularly for small values of the
alternating on-site energy. This result might be relevant for experiments in
cold atoms in which topological charge pumping is observed when alternation in
the hopping is included.

##  I Introduction

Ultracold quantum gases provide a versatile platform as universal quantum
simulators of many-body problems gross . Cold atoms as well as other platforms
have been used to study quantized topological charge pumping in driven systems
citro . A time dependent adiabatic evolution in a closed cycle in a certain
space of parameters constitute a Thouless pump, in which a quantized amount of
charge or spin is transported, which is topologically protected thou ; niu .
Simulating the non-interacting Rice-Mele model (RMM) rice  with ultracold
atoms, quantized charge pumping has been achieved for bosons nakaji  and
fermions loh . More recently, charge pumping in the fermionic interacting RMM
(IRMM) has been studied experimentally konrad  and theoretically nakag ; eric
, including spin pumping eric .

The IRMM is a one-dimensional Hubbard model which includes alternating on-site
energies $\pm\Delta$ and hopping $t\pm\delta$ [Eq. (1) with
$t_{\alpha\beta}=t$]. Ideally, in a Thouless pump, a critical point of
degeneracy is surrounded in the adiabatic time cycle without closing a gap.
For the IRMM, and fixed on-site interaction $U$, the cycles which lead to non-
trivial charge pumping enclose critical points lying at $\delta=0$ and
$\Delta=\pm\Delta_{c}$. For $\delta=0$, the IRMM is equivalent to the ionic
Hubbard model (IHM) sdi ; phihm ; manih ; rihm ; abn ; stenzel  and it is
known that at $\Delta=\pm\Delta_{c}$ there is a charge transition in which the
topologically protected charge Berry phase jumps between the values $0$ and
$\pi$ phihm , implying a transport of one charge when a time cycle is
performed in the plane ($\delta,\Delta$) enclosing the point
($0,\pm\Delta_{c}$) eric ; zup .

Similarly at $\Delta=\pm\Delta_{s}$ there is a spin transition in the IHM
($\delta=0$) with a jump in the spin Berry phase and a closing of the spin gap
for $|\Delta|\leq\Delta_{s}<\Delta_{c}$. The IHM has three phases. The system
is a Mott insulator (MI) for $0\leq\Delta<\Delta_{s}$, a band insulator (BI)
for $\Delta>\Delta_{c}$ and a spontaneously dimerized insulator (SDI) in a
narrow region between the other two. The phase diagram (which is symmetric by
a change of sign in $\Delta$) has been constructed in Ref. phihm,  using the
method of crossing of excited energy levels (MCEL) based on conformal field
theory naka2 ; nomu ; naka ; naka1 ; som . The spin gap opens as
$|\delta|^{2/3}$ leading to a dimerized phase for finite $\delta$ eric .

The fact that the spin gap vanishes in the MI phase (that corresponds to
$\delta=0$, $-\Delta_{s}<\Delta<\Delta_{s}$) brings problems for the charge
pumping. A cycle in the plane $\delta,\Delta$ that encloses a critical point
$\Delta=\pm\Delta_{c}$ and passes far from it, necessarily traverses the MI
phase, because $\Delta_{c}$ and $\Delta_{s}$ are very near each other.
Traversing with a finite velocity a gapless point produces spin excitation at
finite energy, which in turn lead to charge excitations because of the mixing
of both sectors at finite energy sdi ; rihm . This leads to oscillations in
the charge pumping and loss of quantization with the number of cycles as
determined theoretically eric  and experimentally expe . While addition of a
staggered magnetic field or Ising spin interactions lead to opening of the
spin gap and robust charge pumping eric , these terms are not experimentally
feasible at present.

Another possibility to enlarge the spin gap and the region of stability of the
SDI phase is to add a density-dependent hopping (DDH). Such a term in an
electron-hole symmetric form has been realized in cold atoms using Floquet
engineering ma ; meine ; desbu ; go1 ; messer ; goerg . The Hubbard model with
nearest-neighbor hopping dependent on the occupancy of the sites involved
(also called correlated hopping) has been derived and studied as an effective
model for the superconducting cuprates fedro ; sim ; brt , which leads to
enhancement of superconductivity for certain parameters hir ; hir2 ; lili ;
jiang . In one dimension, it has been found that when the hopping term that
changes the number of singly occupied sites [$t_{AB}$ in Eq. (1)] is larger
than the other two, a dimerized phase with a spin gap is favored jaka ;
bosolili ; phtopo ; naka2 , which is the desired effect.

The goal of this work is to study to what extent the region of the phase
diagram of the IHM occupied by the fully gapped SDI phase can be enlarged
including DDH. We use the method of crossing of excited energy levels (MCEL)
based on conformal field theory naka2 ; nomu ; naka ; naka1 ; som , already
used in Ref. phihm,  for the standard IHM. For this model including DDH, the
method also coincides with that of jumps of charge and spin Berry phases used
in Ref. phtopo, .

The paper is organized as follows. In Section II we explain the model and
methods. The resulting phase diagram is contained in Section III. Section IV
contains a summary and discussion.

##  II Model and methods

The IRMM including DDH has the form

$\displaystyle H$ $\displaystyle=$
$\displaystyle\sum_{j\sigma}\left[-1+\delta\;(-1)^{j}\right]\left(c_{j\sigma}^{\dagger}c_{j+1\sigma}+\text{H.c.}\right)$
(1)
$\displaystyle\times[t_{AA}(1-n_{j\bar{\sigma}})(1-n_{j+1\bar{\sigma}})+t_{BB}n_{j\bar{\sigma}}n_{j+1\bar{\sigma}}$
$\displaystyle+t_{AB}(n_{j\bar{\sigma}}+n_{j+1\bar{\sigma}}-2n_{j\bar{\sigma}}n_{j+1\bar{\sigma}})]$
$\displaystyle+\Delta\sum_{j\sigma}(-1)^{j}n_{j\sigma}+U\sum_{j}n_{j\uparrow}n_{j\downarrow}.$

The first term is the DDH, which is alternating for $\delta\neq 0$. The
amplitude $t_{AA}$ corresponds to the situation in which only the particle
that hops occupies the two nearest-neighbor sites involved in the hopping. For
$t_{AB}$ and $t_{BB}$ the total occupancy is 2 and 3 respectively. In the
following we assume the electron-hole symmetric case $t_{BB}=t_{AA}$, which is
the one implemented experimentally with cold atoms ma ; meine ; desbu ; go1 ;
messer ; goerg . $\Delta$ is the alternating on-site energy and $U$ is the on-
site Coulomb repulsion, both characteristic of the IHM sdi ; phihm ; manih ;
rihm ; abn ; stenzel .

Our conclusions, and our discussions below on the effect of the alternation of
the hopping $\delta$ are the same if $\delta$ affects only the hopping part
proportional to $t_{AB}$, and not the other two.

In experiment usually the pump cycles are done in a two-dimensional space
$(\delta,p)$ in which both $\delta$ and another parameter $p$ (like $\Delta$
or $U$) depend on time and return to the original value after the cycle. In
the adiabatic limit, the charge (spin) pumped in the cycle is determined by
the evolution of the charge (spin) Berry phase $\gamma_{c}$ ($\gamma_{s}$) in
the cycle (see for example Ref. eric, ). Non trivial quantized charge (spin)
pumping takes place when a critical point at which $\gamma_{c}$ ($\gamma_{s}$)
jumps, is surrounded in the cycle. The critical points lie on the line
$\delta=0$, because for $\delta=0$, the system has inversion symmetry at each
site and as a consequence, the Berry phases can only be either 0 or $\pi$ (mod
$2\pi$). In other words, $\gamma_{c}/\pi$ and $\gamma_{s}/\pi$ become
topological numbers protected by inversion symmetry zup . In addition, the MI
phase in which the spin gap vanishes is also restricted to $\delta=0$. Then to
identify a possible cycle that encloses the charge critical point with a
ground state separated from the rest of the spectrum in the whole cycle, one
can keep $\delta=0$, where all ground-state degeneracies lie. This is what we
do in the rest of the work. The model becomes the IHM with electron-hole
symmetric DDH.

To calculate the phase diagram of the model we use the MCEL nomu ; naka ;
naka1 ; naka2 ; som . The idea of the method is that the dominant correlations
at large distances correspond to the smallest excitation energies. The
crossing of excited levels in different symmetry sectors therefore correspond
to phase transitions. The method has been used before for similar models phihm
; naka2 ; phtopo . For our model, this method and the jumps in the values of
the Berry phases give the same information phihm , but the MCEL is easier to
implement.

The crossing for both charge and spin transitions are determined using open-
shell boundary conditions (periodic if the number of sites $L$ is multiple of
4, antiperiodic for $L$ even not multiple of 4). The charge transition is
determined by a crossing in the ground state of the two singlets of lowest
energy with opposite parity under inversion. In the BI phase the ground state
is even under inversion, while it is odd in the other two phases. The spin
transition between SDI and MI phases, is determined by the crossing of the
excited even singlet with lowest energy and the lowest excited odd triplet,
which has less energy in the MI phase. In the actual calculation we have not
evaluated the total spin $S$ of the states, but used the parity under time
reversal (the singlet is even and the triplet with total spin projection
$S_{z}=0$ is odd). All these states have wave vector 0 for $\Delta\neq 0$.

Figure 1: (Color online) Critical values of $U$ for the charge and spin
transitions for $t_{AB}=1$, and other parameters indicated inside each figure.

To determine the phase diagram we have set $t_{AB}=1$ as the unit of energy.
Then for a given value of $t_{AA}$ and $\Delta$ we have calculated the values
of $U$ that correspond to the charge ($U_{c}$) and spin ($U_{s}$) transitions
using the MCEL for all even number of sites $L$ in the range $6\leq L\leq 14$.
The results were extrapolated to $L\rightarrow\infty$ using a quadratic
polynomial in $1/L$. Examples of the extrapolation are shown in Fig. 1. The
curves fits well the data and the finite-size effects are in general small,
except for the charge transition for small values of $\Delta$. In any case, a
deviation of the value of $U_{c}$ for $\Delta=0.2$ for up to 20% is very
unlikely from the trend of the curve and does not modify our conclusions.

##  III Results

Figure 2: (Color online) Phase diagram of the IHM with DDH in the $\Delta,U$
plane for $t_{AB}=1$, and two values of $t_{AA}=t_{BB}$. The region between
the full and dashes lines corresponds to the SDI.

In Fig. 2, we compare the phase diagram of the standard IHM with that in which
the hopping terms that do not alter the total number of singly occupied sites
$t_{AA}=t_{BB}$ is reduced. For fixed $\Delta$ the system is a BI for low $U$
and a MI for large $U$. Both phases are separated by a narrow region of the
SDI phase. Increasing $U$, the charge transition at $U=U_{c}$ (with a jump in
$\gamma_{c}$ from 0 to $\pi$ phihm ) corresponds to the change from the BI to
the SDI, and at the spin transition for $U=U_{s}$ (with a jump in $\gamma_{c}$
from 0 to $\pi$ phihm ) the SDI changes to the MI.

For $\Delta>\sim 3t_{AB}$ the width of the SDI phase is of the order of a
fraction of $t_{AB}$. Naturally, keeping the three hopping terms equal
$t_{\alpha\beta}=t$ and reducing $t$ the SDI phase shrinks and both
$U_{c},U_{s}\rightarrow 2\Delta$ for $t\rightarrow 0$. It is therefore
noticeable that reducing only $t_{AA}=t_{BB}$, the extension of the SDI phase
is increased and by about 20% for $\Delta>3t_{AB}$.

As it is apparent in Fig. 3, this effect is more dramatic for
$\Delta<0.5t_{AB}$. In fact, contrary to the case of equal
$t_{\alpha\beta}=t$, there is a finite spin gap for small $U$ even at
$\Delta=0$ when $t_{AB}>t_{AA}=t_{BB}$. This result has been found before jaka
; bosolili ; phtopo ; naka2  and can be understood from analytical
calculations using bosonization jaka ; bosolili  which coincide very well with
numerical calculations phtopo  for small vales of $U$.

Figure 3: Same as Fig. 2 in a smaller region of $\Delta$.

The particular features of the phase diagram for small $\Delta$, render it
possible to perform time evolutions around a critical point for the charge
transition that transport a quantized unit of charge per cycle with open
charge and spin gaps in the whole cycle. For example for $\Delta=0.3$,
$t_{AB}=1$, and $t_{AA}=t_{BB}=0.5$, we find $U_{c}=0.91$ and $U_{s}=2.14$.
Similarly for $\Delta=0.4$ we find $U_{c}=1.22$ and $U_{s}=2.38$. Performing a
time dependent cycle in the plane either $(\delta,\Delta)$ or $(\delta,U)$
with center at the charge critical point (with $\delta=0$) and amplitude in
$\Delta$ of about $\pm 0.25$ or in $U$ near $\pm 0.5$, the cycle never reaches
the MI phase and therefore, the spin gap is always open. One point that should
be taken into account is that the spin transition is of the Kosterlitz-
Thouless type, and therefore the spin gap is exponentially small in the SDI
phase near the transition boundary phtopo . Therefore it might be convenient
to move the time cycle away from the MI-SDI boundary, keeping the critical
point inside it.

In the previous figures we have taken $t_{AA}=t_{BB}=t_{AB}/2$. In Fig. 4 we
show how the values of $U$ at both transitions change with $t_{AA}=t_{BB}$ for
a small value of $\Delta$. We can see that the change is more rapid for
$t_{AA}$ near $t_{AB}$ and the increase in $U_{s}$ is already large for
$t_{AA}/t_{AB}=3/4$. Note also that when $t_{AA}/t_{AB}$ exceeds 1 for a
significant amount $U_{c}$ becomes larger than $U_{s}$ giving rise to a new
phase in between. The properties of this phase are beyond the scope of the
present work. For $\Delta=0$, this phase corresponds to a Tomonaga-Luttinger
liquid with triplet superconducting and bond spin-density wave correlations
dominating at large distances jaka ; bosolili ; phtopo , but $\Delta$ is a
relevant perturbation that modifies the physics.

Figure 4: (Color online) Critical values of $U$ at the charge and spin
transitions as a function of $t_{AA}=t_{BB}=$ for $t_{AB}=1$ and
$\Delta=0.01$.

##  IV Summary and discussion

We have calculated the quantum phase diagram of the IHM including electron-
hole symmetric DDH, which corresponds to Eq. (1) with $\delta=0$ and
$t_{AA}=t_{BB}<t_{AB}$, using the MCEL in rings of up to 14 sites. We obtain
that a reduction of $t_{AA}=t_{BB}$ with respect to $t_{AB}$, increases the
region of the phase diagram occupied by the fully gapped SDI phase,
particularly for $|\Delta|<t_{AB}$ and $U<2t_{AB}$.

This result is of possible relevance to experiments with cold atoms for which
quantized pumping is observed, but crossing the spin gapless MI phase leads to
oscillation and the breakdown of topological pumping after the first cycle.
Floquet engineering renders it possible to achieve the region
$t_{AA}=t_{BB}<t_{AB}$ and enlarge the region of the gapped SDI phase. To
confirm the possibilities of this proposal, it would be useful to calculate
the spin gap and the internal gap between even and odd singlets in the SDI
phase. This would require a study of longer chains using density-matrix
renormalization group. It would also be useful to simulate the time dependence
in pumping cycles similar to the ones suggested here, using infinite time-
evolving block decimation.

## Acknowledgments

We thank Konrad Viebahn, Eric Bertok and Fabian Heidrich-Meisner for useful
discussions. AAA acknowledges financial support provided by PICT 2017-2726 and
PICT 2018-01546 of the ANPCyT, Argentina.

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# The demise of the filesystem and multi level service architecture

William O’Mullane  Large Synoptic Survey Telescope (LSST/AURA)  Niall Gaffney
Texas Advanced Computing Center  Frossie Economou  Large Synoptic Survey
Telescope (LSST/AURA)  Arfon M. Smith  Space Telescope Science Institute  J.
Ross Thomson  Google  Tim Jenness  Large Synoptic Survey Telescope (LSST/AURA)

(August 27, 2024)

###### Abstract

Many astronomy data centres still work on filesystems. Industry has moved on;
current practice in computing infrastructure is to achieve Big Data
scalability using object stores rather than POSIX file systems. This presents
us with opportunities for portability and reuse of software underlying
processing and archive systems but it also causes problems for legacy
implementations in current data centers.

Astronomy, Astrophysics, Data Management, Computing, HPC, HTC, Networking,
Cloud, Files

##  1 Introduction

Executive summary: the filesystem notion limits our ability to scale
processing and has long since been dropped by industry. Astronomy needs to
move on with a new architecture.

Object Stores are nothing new to Astronomy. Flexible Image Transport System
(FITS) and IRAF tapes are examples of object stores that were used when file
systems were unable to handle the volumes of data being produced. Even then,
standards for migrating from Object Store to file systems were created,
allowing for objects to be retrieved into a predefined namespace on disk. The
explosion of individual POSIX disk capacity and POSIX-like file systems have
produced generations of researchers who have never used an Object Store. While
this growth has supported data systems up till now, the size and complexity of
data being produced by surveys and even pointed telescope archives is reaching
scales where the requirements placed on file access by the POSIX standard are
significantly hindering our ability to work with data. Different parallel file
systems have different strengths and weaknesses.

At large scale, data service providers such as Dropbox and Amazon Web Services
(AWS) do not store files in POSIX systems. Rather they present the illusion of
directory structure layered over large scale object stores. This allows for
faster file access, with only CRUD style functions taking place on each
object. Further, as the pseudo-filesystem layer is simply a view of structure
typically provided by a graph database, users can arrange or potentially have
real time query driven structure for the file organization, removing how many
now organize data through a sea of nested symlinks. Some provide local POSIX
caches of that users view of the pseudo-filesystem, allowing for POSIX style
applications to access the files with fopen, fscan, and fclose standard
commands. Additionally, these providers do not show users how data are stored.
One can simply request data in the format needed (e.g., Excel, Comma Separated
Values (CSV), or as I assume it is the JSON format the web apps use for
sheets). At scale, applications often forgo such POSIX layers and simply use
the CRUD interfaces to the objects to load them into memory, act on the
objects, and then update or delete them, in the format they need as input and
with the format they naively produce. Further, the data providers need not
update their data archive when formats change, simply provide a new updated
data access format that can be fueled by legacy data formats.

It is time for Astronomy data researchers to follow this curve. As users have
migrated from using tools on their laptops to support collaboration while
reducing individuals need to manage their systems (Jupyter Hubs, Overleaf,
Google Slides), so should astronomical data processing and analysis. We
propose the adoption of a common Astronomical data access Application
Programming Interface (API) layer.

##  2 Recommendations

  1. 1.

Develop a community wide architecture supporting Science as a Service
following an industry standard layered architecture for astronomy processing
and data access as depicted in Figure 1.

Figure 1: Industry standard Cyber infrastructure model (left) and an astronomy
instantiation of such a model (right)

  2. 2.

Compel all funded funded astronomical projects with _software deliverables_ to
leverage the architecture and APIs for data access.

  3. 3.

Develop _data and metadata transform services_ to support these common API
layers to aid interoperation.

  4. 4.

Adopt and subscribe to a _common federated identity service_ (e.g., InCommon
or Globus Auth) that is supported by most university and research
organizations.

##  3 Commodity services and software based community architecture

The astronomy and astrophysics community have historically relied on the
development and use of bespoke software and hardware infrastructure to solve
challenges related to the managing and analyzing datasets at a scale that was
difficult to find in industry or other scientific domains. These requirements
are no longer unique and we have access to a wealth of open source software,
commodity hardware, and managed cloud services (offered by commercial
providers and federally-funded institutions) that are well positioned to meet
the needs of astronomers and astrophysicists (Momcheva et al., 2019;
Bektesevic et al., 2019). By providing documentation and reference
implementations of the “astronomy stack ” using these technologies and making
it easier for researchers and missions to access cloud computing services, we
can reduce operations costs, accelerate time to science, and increase the
scientific return on Federally-funded research in astronomy and astrophysics.

Figure 1 shows the layers of the Cyber Infrastructure (CI) from the interfaces
for service access exposed at multiple levels, the common domain wide enabled
services, and a collection of system level components that support the higher
levels of the CI. The lower down the diagram are commodity layers based on
well established and supported components. As one moves up from these layers,
more abstraction can be done to expose these pieces in domain, or highly
specific subdomain, level interfaces. By making these abstractions, more
universal service can be developed that can be applied more globally across
the entirety of the CI as a whole.

An example of this would be authentication, where each university or agency
may provide their own authentication method but unifying services like CILogon
can bring those together to give global spaced identity for a wide range of
users based on disparate authentication systems. By providing this structure
along with a reference architecture of these System Services based on well
supported software components, providers are easily able to both deploy and
support these common services which enable cross mission and center
interoperability. This structure also reflects how this architecture allows
for greater reusability as one gets closer to the actual implementation of
these services while supporting greater flexibility and general usability as
one works further from the core components. Alternatives such as using github
authentication may be more flexible but lack the rigor of InCommon which
assures the individual is a member of an academic body — we must also work
with these industry standards though.

This service architecture should be based on using standard reusable software
from many of the established standards developed outside of astronomy (e.g.,
common authentication mechanisms such as CILogon, standard data and metadata
management systems). Standard API interfaces should also be used to expose
these components to higher level API s. Data formatting and metadata structure
can be exposed at the service level, allowing for more data and metadata
reuse. An example of a storage agnostic data/metadata layer is the Large
Synoptic Survey Telescope (LSST) data butler (Jenness et al., 2018). Creation
has been driven by the need to abstract data access away from algorithms. The
algorithm code deals with Python objects and never directly with data formats
or even storage. The data butler is a lot more than a data access layer, it
includes a full registry of all data objects and how to locate them. This
means it may sit atop a filesystem or an object store — a prototype S3 plugin
is now available and we are testing it in a pipeline. The data butler is
astronomy oriented — it has a built in understanding of certain relationships
such as between observations and calibrations or between observations and
region of the sky. Since all metadate is held in a registry provenance queries
can be answered by the butler and it already can act as the registry to find
objects in an object store.

Part of a Cyber Infrastructure model such as depicted in Figure 1 is an object
store oriented API— this should be used for data sharing. Such APIs exist such
as Amazon’s S3. The API layers must _expose both data and metadata in common
transferable and transformable formats_ (e.g., Common Archive Observation
Model (CAOM)).

There must also be an authentication source for users at institutions without
such means and for citizen science efforts.

##  4 Why we should kill the filesystem

Users should not care and repositories should not be tied to legacy formats
and storage representations because of legacy constraints at other
repositories. The rest of the world has already moved on, Google, Amazon,
GitHub, Netflix etc. do not host large filesystems and and can scale because
they are not limited by this antiquated formalism.

Filesystems with name spaces are very fragile at large scale. As we get larger
data sets we have to trick the filesystem to not run out of Inodes, we make
countless sub directories to cope with our thousands of files. This is turn
leads to countless hours spent fighting over how to organize files the _right
way_ in a filesystem. Countless years have been spent fighting over data
formats (FITS vs Hierarchical Data Format (HDF) (Mink et al., 2015) vs CSV vs
Pandas). If we move code then perhaps the filesystem is not organised in the
same manner and the code may not work — remote access to allow caching is not
always an option.

We need to foster better remote collaboration. The laptop is the bane of file
sharing. This has changed with cloud based pseudo-file systems but require
storage in a single cloud providers infrastructure. By creating a Filesystem
as a Service (FSAAS) federated across data and cloud providers, we will win.

This would imply that _POSIX based file access be deprecated in software
development_ and only used when applications require thread safe data access
(something that is currently not possible with FITS files). We should however
develop a pseudo-directory structure system to integrate local and remote
files into a dynamic namespace for each user and potentially each users use-
case (e.g., the Box sync interface or the FUSE based WholeTale file system
(Brinckman et al., 2019))

This "Infrastructure as Code" (Morris, 2016) approach lowers the bar to entry
and allows for easier adoption of more standardized services that will enable
large-scale astronomical research in ways that are well demonstrated in plant
genomics (CyVerse and Galaxy), natural hazards (Designsafe), and surface water
research (Hydroshare). (See also the decadal paper on Cloud infrastructure by
Arfon Smith et. Al.)

###  4.1 The catch

Switching to an object store removes the filesystem bottle neck however it
also removes the filesystem index. This implies that a registry of the objects
must be contained. We frequently do this anyway usually sucking meta data into
a databases to allow searching — just in the case of an object store this
would no longer be optional.

##  5 Conclusion

We should agree on an _astronomy stack_ of services with agreed interfaces
such that we can concentrate on building domain specific layers on top of
industry standard tools.

We should stop worrying about filesystems in astronomy — we should agree on a
decent API for object storage and a registry to go with it. The registry
should build on existing agreements i.e., based on CAOM-2 (Dowler et al.,
2007).

Adoption of a limited set of services will aid ease of use and cut down on
wasted effort by all data providers.

## References

  * Bektesevic et al. (2019) Bektesevic, D., Mehta, P., Juric, M., et al. 2019, in American Astronomical Society Meeting Abstracts, Vol. 233, American Astronomical Society Meeting Abstracts #233, 245.05
  * Brinckman et al. (2019) Brinckman, A., Chard, K., Gaffney, N., et al. 2019, Future Generation Computer Systems, 94, 854
  * Dowler et al. (2007) Dowler, P. D., Gaudet, S., Durand, D., et al. 2007, in Astronomical Society of the Pacific Conference Series, Vol. 376, Astronomical Data Analysis Software and Systems XVI, ed. R. A. Shaw, F. Hill, & D. J. Bell, 347
  * Jenness et al. (2018) Jenness, T., Bosch, J. F., Schellart, P., et al. 2018, arXiv e-prints, arXiv:1812.08085
  * Mink et al. (2015) Mink, J., Mann, R. G., Hanisch, R., et al. 2015, in Astronomical Society of the Pacific Conference Series, Vol. 495, Astronomical Data Analysis Software an Systems XXIV (ADASS XXIV), ed. A. R. Taylor & E. Rosolowsky, 11
  * Momcheva et al. (2019) Momcheva, I., Smith, A. M., & Fox, M. 2019, in American Astronomical Society Meeting Abstracts, Vol. 233, American Astronomical Society Meeting Abstracts #233, 457.06
  * Morris (2016) Morris, K. 2016, Infrastructure as Code: Managing Servers in the Cloud, Safari Books Online (O’Reilly Media)

## Glossary

algorithm

    A computational implementation of a calculation or some method of processing.
API

    Application Programming Interface
AWS

    Amazon Web Services
CAOM

    Common Archive Observation Model
CI

    Cyber Infrastructure
CRUD

    Create Retrieve Update and Destroy
CSV

    Comma Separated Values
FITS

Flexible Image Transport System

    an international standard in astronomy for storing images, tables, and metadata in disk files. See the IAU FITS Standard for details.
FSAAS

    Filesystem as a Service
FUSE

    a user space filesystem framework
HDF

    Hierarchical Data Format
IRAF

    Image Reduction and Analysis Facility
JSON

    JavaScript Object Notation
LSST

    Large Synoptic Survey Telescope
metadata

    General term for data about data, e.g., attributes of astronomical objects (e.g. images, sources, astroObjects, etc.) that are characteristics of the objects themselves, and facilitate the organization, preservation, and query of data sets. (E.g., a FITS header contains metadata).
pipeline

    A configured sequence of software tasks (Stages) to process data and generate data products. Example: Association Pipeline.
POSIX

    Portable Operating System Interface
provenance

    Information about how LSST images, Sources, and Objects were created (e.g., versions of pipelines, algorithmic components, or templates) and how to recreate them.
stack

    a grouping, usually in layers (hence stack), of software packages and services to achieve a common goal. Often providing a higher level set of end user oriented services and tools