You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


---
author:
- 'T. H. Dall'
- 'L. Schmidtobreick'
- 'N. C. Santos'
- 'G. Israelian'
bibliography:
- '2813.bib'
date: 'Received / Accepted '
subtitle: FHLeo misclassified as a novalike variable
title: 'Outbursts on normal stars[^1]'
---

Introduction
============

FHLeo is a wide visual binary consisting of and . The components form a common proper motion (CPM) star pair separated by 8.31$^{\prime\prime}$ with 98% probability of being a physical binary according to @halbwachs1986. The system has been observed with Hipparcos and has been classified as variable and as a probably novalike system (designation NL:) by @kazarovets+1999, based on the outburst appearance of its Hipparcos lightcurve.

This would have been the first cataclysmic variable (CV) found to be part of a multiple star system and its study would have cast light on formation and evolution processes of binary stars. For these reasons we decided to obtain spectra of both components of the system in order to start an investigation into the nature and variability of these objects.

According to SIMBAD it is the brighter northern source, , which is the variable star, while @downes+2001 claim that it is not yet clear which of the two stars is actually variable. Also the Hipparcos archive [@esa1997] lists both  and  under the name , and indeed both stars were included in the 38 aperture of the Hipparcos detectors. Hence, it is not clear from the Hipparcos data either on which star the outburst took place. In Sect. \[hipparcos\] we present and review the photometry collected by Hipparcos and by the American Association of Variable Star Observers [AAVSO; @mattei2004].

Our observations are presented in Sect. \[observations\]. The analysis of the two stars is given in Sect. \[analysis\], where we show from our spectroscopy that neither  nor  can possibly be CVs; rather they are both perfectly normal late-F and early-G stars. In Sect. \[outburst\] we discuss the possible mechanisms that may have caused an outburst on a normal main sequence star. Finally, in Sect. \[summary\] we provide a summary and some concluding remarks concerning further study.

The variability of  and  {#hipparcos}
========================

We have examined the longterm lightcurves, both of the Hipparcos-archive [@esa1997] and of the AAVSO [@mattei2004]. These reveal a constant brightness from JD2447880 to JD2452437, except for a 0.3$^m$ bright outburst between JD2448624 and JD244868. This outburst was observed by Hipparcos and is the actual reason for classifying the system as a novalike variable [@kazarovets+1999]. The AAVSO lightcurve covers the period JD2451966 to JD2452437, and does not show any signs of outbursts or any other type of variability.

In Fig. \[fig:hip\] we show the Hipparcos data.

![image](2813-f1a.eps){width="17cm"} ![image](2813-f1b.eps){width="17cm"}

The rise-time might have been very fast while the decay probably lasted at least 13 days with a possible second event about 170 days later. The data seem to have a very large spread at the two covered intervals on the decay slope (lower left and central plot of Fig. \[fig:hip\]). This could indicate a non-constant energy production rate during the outburst, which would require some inhomogeneous region or process. If the system had indeed contained a CV, this short term variation might have been interpreted as flickering in the accretion disk. No obvious explanation exists for the phenomenon occurring in a normal stellar atmosphere, although this does point to very localized phenomena, e.g. clumps of material ingested in the atmosphere causing hot spots or repeated flare-like outbursts.

Observations
============

We have obtained high-resolution (R$\sim$48000) spectra of  and  with the FEROS spectrograph at the ESO/MPI-2.20m telescope at ESO’s La Silla Observatory, Chile on the night of 2004-01-10. Standard data reduction was performed with the FEROS DRS pipeline, which is a MIDAS tool performing bias and flatfield correction, determination of the wavelength solution, order extraction and wavelength calibration. The spectra cover the range 3800 – 9000 Å. No spectrophotometric standard was observed during this night.

\

In Fig. \[spectra\] we show the spectra of the two stars, re-binned in order to properly display the usual classification range of 3900 – 4600 Å, revealing two seemingly normal stars.

Analysis
========

The spectra of the two stars resemble normal late-F to early-G type stars with average rotation rates. There are no emission lines, especially the H and K lines are devoid of emission cores (see Fig. \[fig:caII\]), ruling out the possibility of strong magnetic activity. There are also no indications that either of the stars should be a spectroscopic binary. We can definitively rule out that any of these two stars is a cataclysmic variable, and it is indeed doubtful if they are variable at all.

The spectrum of  confirms the old F8 classification in the Henry Draper Catalog, while no classification has yet been published for the fainter companion. Only a B magnitude of 10.6 (SIMBAD) and a photographic magnitude of 10.4 [@halbwachs1986] are listed for .

Atmospheric parameters and abundances {#abundances}
-------------------------------------

We have conducted a detailed spectral analysis on both stars, determining the fundamental atmospheric parameters through the following steps: Measurement of the equivalent widths (EWs) of the lines over the full spectral region, determination of a first guess at the basic parameters of the star, calculation of the appropriate model atmosphere, and finally the abundance analysis. The method is the same as employed by @dall+2005 [in preparation], which is adopted from the procedures of @morel+2003 [@bruntt+2002] and @bruntt+2004.

The first step is the measurement of the EWs, which is accomplished using DAOSPEC[^2] [@stetson+pancino2004 in preparation], which uses an iterative Gaussian fitting and subtraction procedure to fit the lines and the effective continuum. The lines are identified using a list of lines from the VALD database [@kupka+1999; @piskunov+1995], where all lines deeper than 1% of the continuum are included. Different line-lists for different spectral types can be retrieved directly from the database. For our FEROS spectra we used only lines in the region 5000–6800Å, since for bluer wavelengths the continuum determination becomes uncertain, while beyond 6800Å the merging of orders and hence the continuum shape proved problematic. Next, an initial estimate of T$_{\mathrm{eff}}$ is found using the line depth ratios calibrated by @kovtyukh+2003. A more accurate determination of T$_{\mathrm{eff}}$ will be derived later in the process. We adopt $\log g$ and microturbulence parameter $\xi_t$ for a canonical ZAMS star, and assume solar metallicity as our starting point. With this we then calculate the initial model, using the ATLAS9 code adapted for Linux [@kurucz1993; @sbordone+2004]. With the measured EWs and the model, the abundances of the Fe-lines are calculated using the WIDTH9 code [@kurucz1993 modified for PC by V. Tsymbal], and compared line-by-line to Solar abundances, calculated from a high S/N solar spectrum obtained with the same instrumental setup, and reduced in the same way as the spectra of  and . This last step is crucial to avoid problems due to uncertain $gf$-values. The parameters of the model used to calculate the solar abundances are $T_{\mathrm{eff}}=5778$ K, $\log g = 4.44$, and $\xi_t = 1.2$ kms$^{-1}$. Finally, a sigma clipping can be applied to eliminate abundance values deviating e.g. because of errors in the EW determination or due to wrong line identifications.

For the initial $T_\mathrm{eff}$ estimate for  we used 19 line ratios, which yielded $T_\mathrm{eff} = 5952 \pm 107$ K. For  the line ratios gave a $T_\mathrm{eff}$ just outside of the valid range of the calibration, hence the initial temperature guess was assumed to be just outside the range at 6150 K.

Now the model parameters ($T_{\mathrm{eff}}$, $\log g$, $\xi_t$, \[Fe/H\], and \[$\alpha$/Fe\]) are iteratively modified until consistency is reached, defined by the following criteria: (1) That there are no trends of abundance with EW, wavelength or excitation potential, (2) that the abundances derived from and are the same, (3) that the derived metallicity and $\alpha$-element abundances are consistent with the input model.

The final model parameters adopted for the two stars are summarized in Table \[tab:params\], in the rows marked *(a)*, along with the measured $v \sin i$ and radial velocities (RVs).

  Star                        $T_\mathrm{eff}$ \[K\]        $\log g$    $\xi_t$ \[\]   $v \sin i$ \[\]            RV \[\]           \[Fe/H\]
  ------------- ----------- ------------------------ --------------- --------------- ----------------- ------------------ ------------------
                 [*(a)*]{}               6450$\pm$70   4.26$\pm$0.19     2.4$\pm$0.2       6.7$\pm$0.5   $-$3.95$\pm$0.44   $-$0.25$\pm$0.09
                 [*(b)*]{}               6493$\pm$99   4.50$\pm$0.19   2.38$\pm$0.74                                        $-$0.21$\pm$0.10
  \[0.2ex\]      [*(a)*]{}               5875$\pm$55   4.52$\pm$0.11     1.4$\pm$0.1       5.2$\pm$0.5   $-$3.19$\pm$0.37   $-$0.21$\pm$0.07
                 [*(b)*]{}               5849$\pm$54   4.45$\pm$0.13   1.23$\pm$0.13                                        $-$0.22$\pm$0.07

For the determination of the atmospheric parameters of  we used 327 and 27 lines, while for   224 and 24 lines were in common with the solar spectrum. The RVs were derived using DAOSPEC, while $v \sin i$ was measured using synthetic spectra calculated with the SYNTH code [@piskunov1992; @valenti+1996] as implemented in the VWA software [@bruntt+2002; @bruntt+2004].

To check our results we conducted an independent analysis following the procedure outlined in @gonzalez+1996 and @santos+2004, using the line-list employed by Santos et al., a grid of Kurucz ATLAS9 models, and the 2002 version of the radiative transfer code MOOG [@sneden1973]. The results show that the two methods agree within the errors, with values of $T_{\mathrm{eff}} = 6493 \pm 99$ K, $\log{g} = 4.50 \pm 0.19$, $\xi_t = 2.38 \pm 0.74$ kms$^{-1}$ and \[Fe/H\] = $-0.21 \pm 0.10$ for  and $T_{\mathrm{eff}} = 5849 \pm 54$ K, $\log{g} = 4.45 \pm 0.19$, $\xi_t = 1.23 \pm 0.13$ kms$^{-1}$ and \[Fe/H\] = $-0.22 \pm 0.07$ for  (rows marked *(b)* in Table \[tab:params\]).

The result of both methods agree very well, showing that within the errors the \[Fe/H\] are the same for the two stars, although there may be hints at a generally slightly higher metallicity in .

In Fig. \[fig:tracks\] we show the positions of the two stars among evolutionary tracks and isochrones calculated by interpolating in the grid provided by @girardi+2000.

From this we estimate an age of $\sim 2$ Gyr for ; an age which within the errors is consistent for  as well. However, a word of caution must be given regarding the uncertainties in the temperature and metallicity evolution of the models used to compute the isochrones. As demonstrated by @pont+2004 the isochrones of @girardi+2000 tend to overestimate the age of the star. Nevertheless, adopting an age estimate of 2 Gyr does not seem unreasonable, and is largely compatible with the lithium age estimate (Sect. \[li-abund\]), especially taking into account the error bars.

\[abund\] A detailed abundance analysis of the two stars were then done, using the derived stellar parameters and the corresponding models. In order to minimize systematic errors due to erroneous $\log gf$ values, we have calculated all abundances relative to the Sun on a line-to-line basis where corresponding lines are found, and relative to the values given by @grevesse+1998 where the line is not found in the solar spectrum.

  --------- ------------- ---------- ---------------- ----------
  Element                                             
            \[M/H\]         \[M/Fe\] \[M/H\]            \[M/Fe\]
  Li                                 $+0.87(10)$ \*         1.08
  Mg        $-$0.25(15)         0.00 $-$0.10(15)            0.11
  Ca        $-$0.17(11)         0.08 $-$0.15(08)            0.06
  Sc        $-$0.23(10)         0.02 $-$0.13(08)            0.08
  Ti        $-$0.19(12)         0.06 $-$0.16(09)            0.05
  V         $-$0.19(14)         0.06 $-$0.19(11)            0.02
  Cr        $-$0.25(11)         0.00 $-$0.22(10)           -0.01
  Fe        $-$0.25(10)              $-$0.21(09)      
  Co        $-$0.24(19)         0.01 $-$0.20(11)            0.01
  Ni        $-$0.28(13)        -0.03 $-$0.24(08)           -0.03
  --------- ------------- ---------- ---------------- ----------

  : \[tab:abund\]The derived abundances (\[M/H\]) for  and  relative to the measured abundances in a Solar spectrum, or relative to @grevesse+1998 (marked by \*). The second column for each star lists \[M/Fe\], i.e. the abundance within the star of each element relative to iron.

The results of the abundance analysis are given in Table \[tab:abund\], with individual abundance determinations discussed in detail below. The abundance errors are estimated by combining the dispersion around the mean with the errors introduced by the uncertainties in T$_{\mathrm{eff}}$ and $\log g$.

The Li abundance {#li-abund}
----------------

In Fig. \[fig:li\] we show the $\lambda$6708 line region for the two stars.

For  we measure EWs of the Li doublet at $\lambda\lambda$6707.761,6707.912 of 15.9 mÅ and 9.6 mÅ respectively, giving an abundance $A(\mathrm{Li})=-10.06$. The abundances derived from the two lines differ by only 0.07dex. The automatic deblending performed by DAOSPEC proved inadequate, and instead we used the IRAF[^3] task *splot* for the deblending. Treating the doublet as one single line yields an EW of 26.8 mÅ, resulting in an abundance $A(\mathrm{Li})=-10.01$. We hence adopt $A(\mathrm{Li})=-10.03$ as a good estimate of the lithium abundance. The dominant error source is the EW measurement, and we estimate an error of 0.10dex. The Li lines in the solar spectrum could not be reliably measured, so we are comparing with the values of @grevesse+1998 to get \[Li/H\] = 0.87.

The Li abundance in  cannot be measured since the lines cannot be recognized, as is evident from Fig. \[fig:li\]. If we assume that the $\lambda$6707.761 line could be as strong as 4 mÅ, we estimate an upper limit for the abundance $A(\mathrm{Li})\le-10.2$, i.e. at least 0.1 – 0.2dex less than for .

Is this difference in lithium abundance significant? To address this question we note from several studies of open clusters, that the Li-gap [@boesgaard+1986] is located roughly between 6400 – 6800 K [e.g. @thorburn+1993; @deliyannis+2000; @jeffries+2002 for Hyades, NGC 752 and NGC 6633 respectively]. However, large amounts of star-to-star scatter is generally observed at any given T$_{\mathrm{eff}}$ hotter than $\sim 6000$ K, the precise temperature limit for the onset of the scatter depending on age. However, lithium depletion and the subsequent development of a Li-gap is not a straightforward relationship with age. In the Hyades ($700 \pm 50$ Myr) no depletion has occurred for stars cooler than 6200 K, while for M35 ($160 \pm 20$ Myr) depletion is already occurring down to 6000 K [@steinhauer+2004]. For the CPM star pairs investigated by @martin+2002 the situation is even more complex, although most of the systems investigated had comparable Li-abundances. It is believed that the rotational history of the star rather than the current rotation rate, is a determining factor for the amount of depletion. On the cool side of the gap, the Li abundance usually adheres to a more straightforward relation with age, thus the $A(\mathrm{Li})$ of  is consistent with an age somewhere between M67 [4.7 Gyr; @pasquini+1997] and NGC 752 [1.8 Gyr; @deliyannis+2000]. If the age of the system indeed is several Gyr, as is also suggested by Fig. \[fig:tracks\], then it is possible that severe Li-depletion could have occurred in  as the star spun down to its current low rotation rate.

Abundances of the $\alpha$-elements
-----------------------------------

The abundances of the electron donor elements Mg, Ca and Ti merit separate comments. In over-active stars these elements are often enhanced with respect to iron, especially for low \[Fe/H\] stars [@morel+2003; @dall+2005]. Hence these elements may act as probes of past or present magnetic activity.

The abundances of calcium was derived using 24 lines. As can be seen from Table \[tab:abund\] the element is slightly overrepresented in both stars with \[Ca/Fe\] of 0.08 and 0.06 for  and  respectively.

The magnesium abundances were found using the $\lambda$5528.405 line, measured by fitting a Voigt profile to the line using *splot*. While we find \[Mg/Fe\] = 0.11 for  we do not find any offset to iron for .

The titanium abundances were measured using 24 and 8 lines for  and 45 and 9 lines for . For both stars titanium is slightly enhanced.

Given the uncertainties on the magnesium abundances, we conclude that the $\alpha$ element enhancement is probably not larger than \[$\alpha$/Fe\] = 0.06 for both stars. Whether this enhancement could be due to past magnetic activity is doubtful, especially given the general pattern of enhancements of other elements with respect to iron and keeping in mind the uncertainties on the individual abundances.

A physically bound system
-------------------------

The abundances of the two stars are similar: both are underabundant, and although  may be more underabundant than , the abundances relative to iron are the same in the two stars, as evident from Table \[tab:abund\], suggesting a common origin and evolution history. Also, taking into account the uncertainties in the models, the small abundance differences may not be real, as discussed in Sect. \[abundances\].

From the spectra we also derive the radial velocities of the two components using DAOSPEC (Table \[tab:params\]). The relative radial velocity between the two stars is less than 1 , i.e. a very small velocity shift between  and , making it even more likely that they indeed constitute a physically bound system.

Using the Hipparcos parallax [@esa1997] of $8.52 \pm 1.73$*mas*, we find $d = 117$ pc, and we can reasonably adopt this as the common distance to the system. With a separation of 8, we find a lower limit for the physical separation of 936 AU.

What caused the outburst? {#outburst}
=========================

Based on our analysis in Sect. \[abund\], we rule out the possibility that an outburst occurred in a steady accretion disk of either  or . While instrumental errors can never be ruled out completely, we note that in general Hipparcos has delivered very accurate and reliable photometry. Also the duration of the event and the gradual fading argues against instrumental errors, since it is unlikely that Hipparcos should have been giving erroneous measurements over a period of about two weeks, without all other measurements during that period being affected. We note that no other star in the vicinity of FHLeo has been flagged variable in the Hipparcos catalog [@esa1997].

We see at the present the following possible explanations for the Hipparcos lightcurve:

-   Transient background or foreground objects.

-   Magnetic interaction with unseen companion.

-   A planetary accretion event.

-   A microlensing event.

In the following we will discuss these possible scenarios and their likelihood.

Transient background/foreground objects?
----------------------------------------

It is in principle possible that the outburst is caused by another object entering directly into the aperture, e.g. a planet, an asteroid or a supernova (SN) in a background galaxy. We estimated the magnitude of this object to be around $B \sim 9.9$ (i.e. even brighter than ) in order to result in the observed brightening. Neither a SIMBAD search for other objects inside the aperture, nor the FEROS guide camera images reveal any objects that could have caused such a brightening. Moreover, planets (and their satellites) and asteroids would produce an “on-off” effect as they enter and exit the aperture, not a gradual decline, and they would move much too fast to stay within the aperture for the required time. Deep imaging of the region around FHLeo may still reveal a faint distant galaxy, which could have hosted a SN bright enough to offset the Hipparcos photometry, although we deem such a bright SN in an undiscovered galaxy very unlikely.

Another, more likely possibility is that light from a nearby bright planet could have entered the aperture indirectly. During the observed brightening, Jupiter was only $\sim 6$ away, and it is possible that scattered light somehow may have entered the Hipparcos instruments. To test the likelihood of this hypothesis we examined the Hipparcos lightcurves of close-by stars. On JD2,448,624.6 (i.e. the time of the main event) Jupiter was at RA = 11:05.5, DEC = $+$07:07, which is about 6away from FHLeo and about the same distance from nearby . The lightcurve of HIP54274 (Fig. \[fig:hip74\]) may show a slight brightening of $\sim 0.1$ in $H$ at the time of the main event, and shows one spurious data point corresponding to almost 3 brightening in $V_T$ and $B_T$ at the time of the secondary event, with Jupiter now half a degree away. No brightening in $H$ can be seen at this epoch.

Also at the time of the second event, located $\sim 8$from Jupiter showed a 0.7 brightening in the $V_T$ filter, while being constant in $H$ and $B_T$ (Fig. \[fig:hip82\]). This brightening is obviously of spurious nature, since the data points jump up and down with 0.5 in a few hours. We also checked the lightcurves of and , both of which at some point were closer than 30 to Jupiter, but both showed constant lightcurves.

Based on the fact that other Hipparcos lightcurves show similar brightenings, it is quite likely that the apparent outburst of FHLeo may be caused by scattered light from Jupiter. However, the distance from Jupiter is large, and the alleged effect seem to have a random element since not all stars in the area show similar brightenings and not necessarily at the expected time. We note however, that caution is needed in the interpretation of Hipparcos lightcurves, since errors can be larger than what is suggested by the listed error bars.

A quick inspection of the distribution of Hipparcos unsolved variables on the sky, do not suggest a larger concentration near the Ecliptic plane, as would be expected if scattered light were a major source of mistaken variability.

Magnetic interaction with unseen companion? {#activity}
-------------------------------------------

It is immediately obvious from the spectra that neither of the stars are over-active. The H and K lines do not show any emission cores (Fig. \[fig:caII\]) and a direct comparison with the FEROS solar spectrum shows that they are both less active than the Sun. Also the infrared Ca triplet shows no signs of emission cores, and none of the Balmer lines show any trace of fill-in emission. The system has also gone undetected by all the high energy satellite missions.

Hence, magnetic activity would need to have been confined to the past, for example induced by some close-in companion in an eccentric orbit, bringing the companion into contact with the star at periastron passage, possibly spurring accretion and disruption of the atmosphere and the magnetic field inducing enhanced magnetic activity. The orbital period would have to be large enough to allow the intermittent magnetic activity to die away completely. As we find no traces of a companion in the spectrum of either star, a neutron star or a giant planet are the most likely assumptions for the companion. The observed high scatter in the Hipparcos light curve during the outburst would then be due to flickering activity in the transient accretion disk or due to continuous rapid flaring activity during the periastron passage.

Chromospheric heating has been discussed by @santos+2003 for and by @shkolnik+2003 for . In these cases chromospheric heating occur due to magnetic interaction between the star and a giant planet or brown dwarf in a very close, short period orbit [@saar+2001]. A similar mechanism may be at work in the FHLeo system, but possibly only during periastron passage.

Giant planets have been found in very eccentric orbits e.g.  [@naef+2001], which harbors a giant planet in a $e = 0.927$ orbit. In such a case the direct cause of the outburst could be a superflare [@rubenstein+2000], where the snapping of field lines during a very close periastron passage could have produced enough energy for the outburst, and temporarily disrupted any remaining field.

Another possibility is a compact companion: This scenario would be similar to an Be/X-ray transient [@negueruela1998], which due to the lack of wind or disk signatures, would have to be in a very eccentric long-period orbit. However, these transients are known to exist with early type stars, while no such objects have been found with G–type companions, which makes this scenario rather unlikely.

With current instrumentation [i.e. HARPS; @harps2003] the detection of even planetary-size companions would be possible, and this possibility should be investigated further.

Planetary accretion?
--------------------

Several discussions of possible planetary engulfments have been published recently [@siess+1999; @sandquist+2002; @israelian+2001; @israelian+2003]. Such an event would leave a “polluted” stellar atmosphere and thus lead to enhanced abundances, especially of the volatiles , , and . Unfortunately, FEROS cannot resolve the + blend, and it cannot reach the Be lines near the atmospheric UV cutoff.

The amount of energy released in a planetary engulfment process can be estimated as follows: The outburst amplitude of 0.35mag corresponds to a ratio of energy of 1.38. Assuming solar luminosity for the quiescence star we integrate the energy emitted during the outburst to $\Delta E = 10^{32}$ W. Assuming that all this energy is provided by the gravitational energy $E = {\rm G}\,M_{\rm star}\,m\,R_{\rm star}^{-1}$ of the accreted material, and taking the solar values for the mass $M_{\rm star}$ and radius $R_{\rm star}$ of the star, we derive the mass $m$ of the accreted matter $m = 5\,10^{20}$ kg, which is about the mass of a large asteroid like Pallas or Vesta.

A scenario where  accreted a planetary-sized companion could explain both the Hipparcos outbursts, the possible slight overabundances found in  with respect to , and the presence of lithium in . One crucial test of this explanation would be to measure the / isotopic ratio as done by @israelian+2001 [@israelian+2003], and the abundance of beryllium.

Microlensing?
-------------

The low time resolution and poorly resolved shape of the outburst as well as the absence of color information make it impossible to judge the event as caused by microlensing. However, as the system has high proper motion (-14.04, -61.85) $\pm$ (1.81, 1.35) mas/yr, at least the probability for such an event exists. Deep imaging of the region around the system might reveal a faint object in the path of either star which was either lensed or functioned as a lens, and would thus strengthen this interpretation of the brightening. Note though that microlensing would not naturally explain the minor event that occurred 150 days later.

Summary
=======

In this paper we have shown that the variable FHLeo cannot possibly be a CV as previously thought. We have found the atmospheric parameters of the two stars in the system and from their derived abundances, RVs and rotation rates, shown them to be perfectly normal main sequence stars.

However, the outburst observed by the Hipparcos satellite remains a mystery. While it may be caused by scattered light entering the instrument from nearby Jupiter, the effect is neither obvious nor reproducible when checking the lightcurves of nearby Hipparcos targets. This analysis showed however, that great care must be exercised when interpreting Hipparcos lightcurves, since deviations much larger than the internal errors can occur. Certainly, it would be worthwhile investigating in detail whether there exist correlations between unsolved Hipparcos variables and the proximity of Solar system objects to the field of view. Our quick inspection did not suggest any correlations though.

The most severe constraints on the possible physical explanations are provided by the lack of activity on either star, which also makes it extremely interesting to determine the proper cause of the outburst: If it was indeed caused by some process involving a very close companion inducing magnetic activity, then we have a unique possibility to gain insight into the time evolution of magnetic phenomena. Hence, the explanations presented in this paper should be assessed: Deep imaging of the immediate surroundings of the system could reveal a lensing object or a background galaxy. Accurate radial velocity monitoring with high spectral resolution could reveal any planets or compact companions in orbit around either star, and the combined spectra could provide the high signal-to-noise needed for a measurement of the / isotopic ratio which is a crucial test for the engulfment scenario.

This research has made use of the SIMBAD database, operated at CDS, Strasbourg, France

Support from Fundação para a Ciência e Tecnologia (Portugal) to NCS in the form of a scholarship is gratefully acknowledged.

We are greatly indebted to the referee Dr. D. Bohlender for his constructive criticism.

THD wishes to thank C. H. F. Melo and H. Bruntt for helpful discussions.

[^1]: Based on observations collected at the La Silla Observatory, ESO (Chile), with the FEROS spectrograph at the 2.20 MPI/ESO telescope.

[^2]: DAOSPEC has been written by P. B. Stetson for the Dominion Astrophysical Observatory of the Herzberg Institute of Astrophysics, National Research Council, Canada.

[^3]: IRAF is distributed by the National Optical Astronomy Observatories, which are operated by the Association of Universities for Research in Astronomy, Inc., under cooperative agreement with the National Science Foundation, U.S.A.