too long |  $\square$ answer too long
too short |  $\square$ answer too short
inconsistent |  $\square$ inconsistent language/style/terminology
repetitive |  $\square$ repetitive
other |  $\square$ other
clarity |  The answer is clear and easy to understand.
sentences too long |  $\square$ sentences too long
too technical |  $\square$ language too technical
hard math |  $\square$ numbers/formulae hard to understand
other |  $\square$ other
correctness |  The language in the answer does not contain mistakes.
incomplete sentence |  $\square$ sentence is incomplete
incorrect spelling |  $\square$ spelling mistakes
punctuation mistakes |  $\square$ punctuation mistakes
incorrect grammar |  $\square$ grammatical errors
other |  $\square$ other
tone |  The tone of the answer is neutral and unbiased.
biased |  $\square$ the answer is biased
persuasive |  $\square$ tries to convince me of an opinions/belief
negative |  $\square$ the tone is too negative
other |  $\square$ other
Epistemological Dimensions |
accuracy |  The answer is accurate.
incorrect |  $\square$ incorrect
science out of context |  $\square$ takes scientific findings out of context
self contradictory |  $\square$ self-contradictory
wrong use of terms |  $\square$ wrong use of key terms/scientific terminology
other |  $\square$ other
specificity |  The answer addresses only what the question asks for, without adding irrelevant information.
irrelevant info |  $\square$ includes irrelevant parts
vague |  $\square$ too vague/unspecific
other |  $\square$ other
completeness |  The answer addresses everything the question asks for.
does not address main parts |  $\square$ misses important parts of the answer
does not address region |  $\square$ does not address the region the question asks about
does not address time |  $\square$ does not address time or time range the question asks about
not enough detail |  $\square$ does not give enough detail (e.g. numbers, statistics, details)
ignores science |  $\square$ ignores relevant scientific knowledge
other |  $\square$ other
uncertainty |  The answer appropriately conveys the uncertainty involved.
uncertainty missing |  $\square$ degree of (un)certainty not given when it should be
consensus missing |  $\square$ agreement in the scientific community not given when important
contradicting evidence missing |  $\square$ contradicting evidence (if existing) not mentioned
other |  $\square$ other
Table 18: (on the right) Statements as presented to the raters. We query each
dimension separately in the interface (Figure 15) and ask _”To what extent do
you agree with the statement below?”_ We also require the raters to identify
particular issues for the given list if they disagree with a statement. On the
left side we list the dimensions the statements belong in and a shorthand for
the issue names used in tables throughout this work.

For presentational and epistemological accuracy we evaluate 4 dimensions each.
Given a question-answer pair the raters are asked to what degree they agree
with one of the statements in Table 18.171717Please note that when we use the
shorthand _correctness_ in our results, this only refers to correctness _of
the language_ , i.e. presentational correctness. The corresponding
epistemological dimension is _accuracy_ , i.e. correctness _of the answer_.
The raters select agreement on a 5-point scale from _completely disagree_ to
_completely agree_. For the two lowest choices we ask for additional details
which can be selected from a list of possible issues, including _other_ which
allows free-text input. See Section M.4 for screenshots of the rating
interface.

###  M.3 Tutorial and Admission Test

We devise a special introduction session for new participants that contains a
tutorial followed by an admission test. The purpose of the session is twofold:
(1) The introduction session is designed to familiarize the raters with the
interface and the task. (2) Based on the session’s outcome we select raters
into the rating pool.

Tutorial In the tutorial (see Figure 12) we present 4 examples of increasing
difficulty in the rating interface and only ask for one dimension each. Each
example exhibits a particular main issue and we expect raters to identify this
issue correctly. A hint is given if the rater selects a wrong answer that does
not identify the issue and they can only proceed to the next item if an
acceptable answer that does identify the issue is given. Regarding other
issues than the main issue, one might disagree on some of these issues and we
allow several possible selections. Note that to identify the main issue, a low
rating (disagree completely or disagree) must be selected. Once a valid
response is selected we show positive feedback and explain why the outcome is
the desired one. We don’t collect any data during the tutorial part.

Figure 12: Screenshot of the last of 4 tutorial questions with the correct
answer selected.

Admission Test To test the raters’ ability and attention to detail we select
three realistic examples that exhibit at least one major flaw. We use the full
template and ask about all statements in Table 18. We record the responses and
assign or deduct points for every detected, undetected, and over-detected
issue. The point scheme was decided among the authors after carefully
considering possible disagreements or subjective interpretations.

Based on the performance of an early group of raters with known performance on
the task we decide on a threshold and admit raters above that score to the
pool. We believe that the tutorial and admission test were effective in
ensuring that raters were both familiar with the interface as well as the type
of assessment we expect from them, which requires close reading of question
and answer, basic knowledge of climate change, and an understanding of the
tasks dimensions and issues that allows them to rate dimensions and select
specific issues reliably.

###  M.4 Template Screenshots

We provide screenshots of our rating implementation in Figures 13, 14 and 15.

Figure 13: Screenshot of the instructions to the raters, provided at the
beginning of the first rating session. Figure 14: Screenshot of screening
template which ensures the raters are able to judge the example. If any of the
questions is answered _No_ we skip the example and proceed with the next one.
Figure 15: Screenshot of the rating interface. Here we are rating the
_completeness_ dimension. Since the rater selected a low rating, the interface
asks for specific details. For ratings of _3 = neither_ and above, the blue
box is hidden. In this example we also show the AI Assistance which is not
always available, which is rated as not helpful.

##  Appendix N Examples

###  N.1 Answers

In this section, we present examples showing good versus bad answers for each
dimension evaluated in Tables 19 to 26.

Question | In what ways can peri-urban ecosystems help reduce the urban heat island effect?
---|---
| Model A | Model B
Answer |  Peri-urban ecosystems can significantly help reduce the urban heat island effect in several ways. Firstly, they act as natural coolants by providing shade and releasing moisture into the atmosphere through a process known as evapotranspiration, which can lower surrounding temperatures. Secondly, these ecosystems, which include forests, grasslands, and wetlands, can absorb and store heat, reducing the overall temperature in urban areas. Lastly, they can also help mitigate the heat island effect by reducing the need for energy-intensive cooling systems, as well-vegetated areas are naturally cooler than concrete or asphalt surfaces. |  Peri-urban ecosystems can help reduce the urban heat island effect by providing shade, evaporative cooling, and habitat for cooling breezes. Trees and other vegetation in peri-urban areas can help to block the sun’s rays, reducing the amount of heat that is absorbed by the ground. The evaporation of water from plants and soil can also help to cool the air, and vegetation can create shade that helps to block the sun’s heat. In addition, vegetation can provide habitat for animals that help to create cooling breezes. All of these factors can help to reduce the urban heat island effect, making cities more livable and sustainable.
Assistance |  |  The answer contains repetition, specifically in the explanation of how vegetation provides shade and blocks the sun’s heat.
Issues |  |  repetitive
Rating |  4.6 |  2.0
Table 19: Example for the style dimension. The Model B answer repeats the explanation on how vegetation provides shade and blocks the sun’s heat. Question | Was the name ’global warming’ changed to ’climate change’?
---|---
| Model A | Model B
Answer |  Yes |  Yes, the term ”global warming” was changed to ”climate change” in order to better reflect the broader range of impacts associated with rising greenhouse gas emissions. While global warming refers specifically to the increase in Earth’s average surface temperature, climate change encompasses a wider array of changes, including shifts in precipitation patterns, sea level rise, and the frequency and intensity of extreme weather events. The term ”climate change” is now widely used to capture the full scope of these impacts.
Assistance |  The answer lacks sufficient detail to fully address the complexity of the question. |
Issues |  too_short, vague |
Rating |  2.6 |  4.6
Table 20: Example for the clarity dimension. The Model A answer is too short. It lacks details and context to fully address the question. Question | Which areas in Nigeria are at risk of rising sea levels?
---|---
| Model A | Model B
Answer |  The coastal areas of Nigeria are at risk of rising sea levels due to climate change. These areas include Lagos, Ogun, and Delta states. Rising sea levels could cause flooding, erosion, and salinization of freshwater sources. This could have a devastating impact on the livelihoods of the people who live in these areas. |  I do not have access to the latest information on the specific areas in nigeria that are at risk of rising sea levels. however, it is important to note that nigeria, like many other countries, is vulnerable to the impacts of climate change, including sea level rise. coastal cities and communities are particularly at risk, and it is crucial for nigeria to take action to mitigate and adapt to the effects of climate change.
Assistance |  |  The answer contains a grammatical error - ”nigeria” should be capitalized as ”Nigeria”.
Issues |  |  incorrect_grammar, incorrect_spelling
Rating |  4.6 |  2.3
Table 21: Example for the correctness dimension. The Model B answer contains a grammatical error where the first letter of a location name should be capitalized. Question | Do volcanos emit more CO2 than humans?
---|---
| Model A | Model B
Answer |  No, volcanoes do not emit more CO2 than humans. According to the U.S. Geological Survey, human activities, particularly the burning of fossil fuels for energy, emit more than 60 times the amount of carbon dioxide than volcanoes each year. While volcanoes do contribute to CO2 emissions, their contribution is relatively small compared to human activities. It’s important to note that human-induced climate change is primarily driven by the increase in greenhouse gases from human activities, not natural processes like volcanic eruptions. |  No, volcanoes do not emit more CO2 than humans. While volcanic eruptions do release significant amounts of CO2 into the atmosphere, the total annual emissions from volcanoes are estimated to be about 0.3 to 0.4 billion metric tons. In contrast, human activities, such as burning fossil fuels and deforestation, emit over 35 billion metric tons of CO2 annually, which is about 100 times more than volcanic emissions.
Assistance |  |
Issues |  biased, persuasive |
Rating |  2.0 |  4.3
Table 22: Example for the tone dimension. Instead of answering with only facts, the Model A answer assigns blame on human activities as the cause of climate change which was not part of the question. Question | How does burning fossil fuels mitigate climate change
---|---
| Model A | Model B
Answer |  Burning fossil fuels does not mitigate climate change. In fact, it is one of the primary causes of climate change. When fossil fuels are burned, they release carbon dioxide and other greenhouse gases into the atmosphere, which trap heat and contribute to global warming. To mitigate climate change, we need to transition to cleaner, renewable sources of energy and reduce our overall energy consumption. |  Burning fossil fuels releases greenhouse gases into the atmosphere, which trap heat and cause the planet to warm. This is the leading cause of climate change. However, burning fossil fuels can also be used to mitigate climate change by generating electricity from renewable sources, such as solar and wind power. This can help to reduce the amount of greenhouse gases emitted into the atmosphere and slow the rate of climate change.
AI Assistance |  |  The critique is that the statement inaccurately suggests that burning fossil fuels can mitigate climate change. As per the provided paragraphs, ”the burning of fossil fuels is the main source of greenhouse gas emissions causing global warming and ocean acidification.” Furthermore, ”the International Energy Agency concluded that no new fossil fuel extraction projects could be opened if the global economy and society wants to avoid the worst impacts of climate change and meet international goals for climate change mitigation.” Therefore, burning fossil fuels contributes to climate change rather than mitigating it.
Issues |  |  incorrect, science_out_of_context, self_contradictory
Rating |  4.6 |  1.3
Table 23: Example for the accuracy dimension. The Model B answer contains a factual error which suggests that burning fossil fuels can mitigate climate change. Question | What happened to global temperatures by the mid-1970s?
---|---
| Model A | Model B
Answer |  By the mid-1970s, global temperatures began to rise at an accelerated rate. This period marked the end of a slight cooling phase that had occurred from the 1940s to the 1970s, often referred to as the ”global cooling” period. The shift in temperature trends was largely due to increased levels of greenhouse gases, particularly carbon dioxide, in the Earth’s atmosphere from human activities such as burning fossil fuels. This marked the beginning of a period of rapid global warming that continues today. |  By the mid-1970s, global temperatures had risen by about 0.2 degrees Celsius (0.36 degrees Fahrenheit) since the late 19th century. This warming trend was statistically significant, and it was consistent with the predictions of climate models that had been developed in the 1960s and 1970s.
Assistance |  The statement is incorrect in asserting that there are no vague or generic statements in the answer. The phrase ”increased levels of greenhouse gases, particularly carbon dioxide, in the Earth’s atmosphere from human activities such as burning fossil fuels” is a generic statement that could benefit from specific data or examples. As per Wikipedia, ”The 2011–2020 decade warmed to an average 1.09 °C [0.95–1.20 °C] compared to the pre-industrial baseline (1850–1900). Surface temperatures are rising by about 0.2 °C per decade, with 2020 reaching a temperature of 1.2 °C above the pre-industrial era.” This specific information could enhance the answer’s clarity and precision. |  The answer could be improved by including the specific information that ”The 2011–2020 decade warmed to an average 1.09 °C [0.95–1.20 °C] compared to the pre-industrial baseline (1850–1900)” and ”Surface temperatures are rising by about 0.2 °C per decade,” which provides a more precise context for the warming trend observed by the mid-1970s.
Issues |  vague |
Rating |  2 |  4
Table 24: Example for the specificity dimension. The Model A answer omits specific numbers on how much the global temperatures have changed which is important for the answer’s clarity and precision. Question | How much do cows contribute to climate change
---|---
| Model A | Model B
Answer |  Cows significantly contribute to climate change due to the production of methane, a potent greenhouse gas, during their digestion process. According to the United Nations’ Food and Agriculture Organization, livestock (including cows) account for about 14.5% of all human-caused greenhouse gas emissions, with cows being the largest contributor. This is equivalent to the exhaust emissions from all the vehicles on the planet. Therefore, the impact of cows on climate change is substantial and cannot be overlooked. |  Cows are a major source of methane, a powerful greenhouse gas that contributes to climate change. According to the Environmental Protection Agency (EPA), cattle and other livestock are responsible for about 5.5 percent of all human-caused greenhouse gas emissions.
Assistance |  While the answer provides a comprehensive overview of cows’ contribution to climate change, it fails to mention the potential for mitigation efforts, such as the adoption of best practices that can reduce emissions by up to 30%, as stated by the FAO. Furthermore, it does not address the variability in environmental impacts due to different agricultural practices around the world. |  While the answer provides a general overview of the contribution of cows to climate change, it fails to mention the potential mitigation strategies, such as dietary changes and adoption of best practices, which can significantly reduce emissions. As stated in the provided paragraphs, ”Mitigation options for reducing methane emission from livestock include a change in diet, that is consuming less meat and dairy” and ”FAO estimates that the adoption of already available best practices can reduce emissions by up to 30%”.
Issues |  |  not_enough_detail, does_not_address_main_parts, ignores_science
Rating |  4.6 |  2
Table 25: Example for the completeness dimension. The Model B answer lacks context and details around the answer. The assistance on missing mitigation efforts is not helpful because it is not necessary to make the answer complete. The raters are able to recognize this and give Model A answer a correct high rating. Question | Did Hansen predict that the West Side highway would be underwater in 20 years?
---|---
| Model A | Model B
Answer |  James Hansen, a prominent climate scientist, did make a statement in a 1988 interview suggesting that the West Side Highway in New York City could be underwater in 40 years. However, this was not a formal prediction based on a specific scientific study, but rather a speculative comment made to illustrate potential impacts of climate change. It’s important to note that while sea levels are indeed rising due to climate change, the exact rate and impact can vary greatly depending on a range of factors, including greenhouse gas emissions and ice melt rates. |  No, Hansen did not predict that the West Side highway would be underwater in 20 years. He did, however, predict that sea levels would rise by about 2 feet by 2100, which would put the West Side highway at risk of flooding.
Assistance |  The statement overlooks the importance of communicating uncertainty in climate science. As per the answer, Hansen’s comment was speculative and not based on a specific study, thus it’s crucial to mention this uncertainty to avoid misinterpretation of the potential impacts of climate change. |  The statement fails to acknowledge that the answer does not explicitly convey the inherent uncertainty in climate predictions, such as Hansen’s prediction about sea level rise. According to Wikipedia, ”Uncertainty is a fundamental characteristic of weather, seasonal climate, and hydrological prediction, and no forecast is complete without a description of its uncertainty.”
Issues |  |  uncertainty_missing
Rating |  4 |  2.3
Table 26: Example for the uncertainty dimension. The Model B answer states
precise predictions without acknowledging the uncertainty in climate science
as there are many factors that can influence a prediction.

###  N.2 AI Assistance

In this section, we present examples showing AI assistance that influence
human ratings in Tables 27 to 31.

Question |  Is IPCC consensus phoney?
---|---
Answer |  No, the consensus of the Intergovernmental Panel on Climate Change (IPCC) is not phoney. The IPCC is a reputable international body that assesses the science related to climate change. It was established by the United Nations Environment Programme (UNEP) and the World Meteorological Organization (WMO) in 1988 to provide policymakers with regular scientific assessments on climate change, its implications and potential future risks, as well as to put forward adaptation and mitigation strategies. The consensus reached by the IPCC is based on rigorous scientific research and review by experts from all over the world, making it a reliable and authoritative source of information on climate change.
Assistance |  The tone of the answer, while factual, may be perceived as biased due to the strong defense of the IPCC’s credibility and authority.
Rating with Assistance |  2.3 [biased, persuasive]
Rating without Assistance |  4.6
Table 27: Example for the tone dimension. Raters identify the biased tone only with assistance. Question |  How do single-family houses contribute to higher toxic chemical emissions compared to multifamily buildings?
---|---
Answer |  Single-family houses contribute to higher toxic chemical emissions compared to multifamily buildings primarily due to their larger size and individualized systems. Each single-family home typically has its own heating, cooling, and water systems, all of which consume energy and produce emissions. Additionally, these houses often have larger lawns requiring maintenance equipment like lawnmowers and leaf blowers, which also emit harmful chemicals. Lastly, single-family homes, due to their larger size, require more materials to build and maintain, leading to higher emissions from the production and transportation of these materials.
Assistance |  While the answer provides a plausible explanation, it lacks empirical evidence or scientific findings to support the claim that single-family houses contribute to higher toxic chemical emissions compared to multifamily buildings.
Rating with Assistance |  1.6 [anecdotal, incorrect, science_out_of_context]
Rating without Assistance |  4
Table 28: Example for the accuracy dimension. Raters identify the anecdotal nature of the answer only with assistance. Question |  Are climate change solutions too expensive?
---|---
Answer |  While it’s true that implementing solutions to combat climate change requires significant financial investment, it’s important to consider the cost of inaction, which is likely to be much higher. The economic damage caused by extreme weather events, rising sea levels, and other climate-related impacts could be devastating. Moreover, many climate solutions, such as renewable energy technologies, are becoming increasingly cost-competitive. Investing in these solutions can also stimulate economic growth and create jobs, providing a return on investment. Therefore, while the upfront costs may be high, the long-term benefits both economically and environmentally make it a necessary investment.
Assistance |  The statement is incorrect as the answer contains a vague statement. The phrase ”the cost of inaction, which is likely to be much higher” is not quantified or supported with specific data or examples. As per the provided Wikipedia paragraphs, ”a 2021 study by the reinsurance company Swiss Re estimated global climate change is likely to reduce global economic output by 11-14%, or as much as $23 trillion annually by 2050, compared with output without climate change.” This specific information could have been used to substantiate the claim.
Rating with Assistance |  2 [vague, irrelevant_info]
Rating without Assistance |  4.6
Table 29: Example for the specificity dimension. Raters identify how specific information could make the answer better only with assistance. Question |  Is the Arctic ice melt a natural cycle?
---|---
Answer |  While the Arctic ice does go through natural cycles of melting and refreezing, the accelerated rate of ice melt that we are currently witnessing is not part of a natural cycle. Scientific evidence overwhelmingly points to human-induced climate change as the primary cause. Rising global temperatures, largely due to greenhouse gas emissions from human activities, are causing the Arctic ice to melt at an unprecedented rate. This rapid ice loss is having profound effects on Arctic ecosystems and contributing to rising sea levels globally.
Assistance |  While the answer provides a comprehensive explanation of the Arctic ice melt, it lacks specific details such as the decline rate of 4.7% per decade, the projection of the first ice-free conditions around 2035 under a scenario of continually accelerating greenhouse gas emissions, and the fact that Arctic ice decline between 1979 and 2011 is estimated to have been responsible for as much radiative forcing as a quarter of CO2 emissions the same period.
Rating with Assistance |  2 [not_enough_detail]
Rating without Assistance |  5
Table 30: Example for the completeness dimension. Raters identify how specific information could make the answer better only with assistance. Question |  will global warming cause an ice age
---|---
Answer |  While it may seem counterintuitive, some scientists have suggested that global warming could potentially trigger what’s known as a ”mini ice age.” This theory is based on the idea that increased melting of polar ice could disrupt ocean currents, such as the Gulf Stream, that play a crucial role in regulating global climate. If these currents were to be significantly altered or shut down, it could potentially lead to a dramatic cooling of certain regions, such as Northern Europe. However, this is just one theory and the overall consensus among scientists is that global warming will lead to a general trend of increasing temperatures worldwide.
Assistance |  While the answer acknowledges the theory of a potential ”mini ice age” due to global warming, it fails to adequately convey the scientific consensus on the matter. As stated in the provided paragraphs, ”Earth system models used in Coupled Model Intercomparison Project indicate that shutdown is only likely after high levels of warming are sustained well after 2100,” and ”paleoceanographic research suggests that the AMOC may be even more stable than what is predicted by most models.” Therefore, the answer could mislead readers into thinking that a ”mini ice age” is a more immediate and likely consequence of global warming than what is generally agreed upon by the scientific community.
Rating with Assistance |  1.6 [uncertainty_missing, consensus_missing, contradicting_evidence_missing]
Rating without Assistance |  4.6
Table 31: Example for the uncertainty dimension. Raters identify the
unlikelihood of the theory only with assistance.


author subject

XV International Conference on
Gravitational Microlensing
Conference Book

January 20–22, 2011
University of Salerno, Italy

Editors
V. Bozza, S. Calchi Novati, L. Mancini, G. Scarpetta
(Local Organizing Committee)

Organized by the Astrophysics Group of the

Physics Department of the University of Salerno

Sponsored by IIASS (International Institute for Advanced Scientific Studies),

INFN (Istituto Nazionale di Fisica Nucelare), International Ph.D. in
Astrophysics, and University of Salerno

http://smc2011.physics.unisa.it

Foreword

This volume collects the abstracts in extended format of the
$15^{\mathrm{th}}$ Microlensing Conference held in the University of Salerno
on January 20-22, 2011. The Conference has gathered 68 scientists from 17
countries confirming microlensing as a mature and established tool of research
over a broad range of astrophysical issues, from dark matter searches to the
detection of new extrasolar planets of very low mass, down to Earth-size or
below. The 3-days Conference has been preceeded by a 2-days school on
“Modelling Planetary Microlensing Events” focused on this last issue. The
abstracts collected here offer an updated snapshot of the current researches
in this field. The topics include: the status of current surveys, planetary
events, dark matter searches, cosmological microlensing, theoretical
investigations and an outlook towards the future, with in particular a
discussion on the possible role to be played by microlensing searches for
exoplanets in the forecoming space missions, WFIRST and EUCLID. Finally, the
conference has been enriched by a series of topical speeches on related issues
from a non-microlensing point of view: the physics of giant planet accretion
and evolution, “new physics” and dark matter in the LHC era and an update on
the GAIA mission and its potential to characterize planetary systems with
high-precision astrometry.

Scientific Rationale

25 years after the seminal intuition by Bohdan Paczynski, microlensing has
rapidly evolved into a new promise for modern astrophysics. Indeed, the
detection of celestial bodies by their gravitational effects on the light of
background sources has proved to be a very powerful tool for the study of many
aspects of our Galaxy and beyond.

The original proposal of using microlensing to estimate the amount of baryonic
dark matter in the form of compact substellar bodies is still topical. The
observation of microlensing events toward nearby galaxies still represents a
hard challenge for present observational facilities. Very strong efforts are
under way for upgrading the current strategies in particular toward the galaxy
M31.

Hundreds of microlensing events are discovered toward the Galactic Bulge every
year. This considerable amount of statistics can be used to characterize the
stellar populations of the bulge and the disc of our Galaxy. After several
years of observations, the significance of the microlensing sample in the
characterization of our Galaxy is growing more and more.

Yet, the most intriguing perspective offered by microlensing is represented by
its power to discover new extrasolar planets of very low mass, down to Earth-
size or below. Several planetary events have already been detected and
studied, while many more are expected as soon as future dedicated telescopes
become operational. Interestingly, microlensing is already being used to
estimate the abundance of planets around stars in the disc of our Galaxy and
to characterize their distributions in distance and mass. As the planetary
anomalies typically last only a few hours, the cooperation among all observing
groups is mandatory, in order to characterize the events properly and maximize
the scientific achievements. Even amateur astronomers are now giving their
fundamental contribution. In this respect, microlensing stands as a perfect
example of how science can unite the whole mankind in a common path toward
pure knowledge.

Salerno Microlensing Conference 2011 will gather all people active in this
field, providing the state of the art of microlensing searches and the
perspectives opened by new methodologies and new observational and
computational facilities. Colloquia on dark matter searches and planet
formation theories are also foreseen as a central part of the conference. The
three-days conference will be preceded by a school dedicated to the delicate
issue of efficient modelling of planetary microlensing events, which requires
major efforts and new ideas from new talents in order to get access to the
precious physical information hidden in microlensing light curves. For one
week in January 2011, Salerno will thus be the place in which the present and
the future of microlensing will be unveiled.

Valerio Bozza
---
Local Organizing Committee

Welcome address

On behalf of the Rector of Salerno University, professor Raimondo Pasquino,
the Dean of the Science Faculty, professor Mariella Transirico, the Decan of
the Department of Physics, professor Ferdinando Mancini and the Organizing
Committee, I welcome all the participants to this exciting Conference.

This University has the peculiar status to be at the same time one of the
youngest Universities in Italy and the oldest one.

The re-establishment of Salerno University in the Modern Era dates back to
about forty years ago, and as you can see, in a very short time it has grown
in the Irno valley as a university campus, with about forty thousand students,
more than one thousand professors and researchers, distributed in ten
faculties.

Five years ago the Campus was completed with the Medical Science Faculty,
realizing the ideal link with one of the oldest Medical Schools of the West,
the so called “Scuola Medica Salernitana”.

Salerno was not the seat of the first Medieval University, but the Medical
School was the first to organize studies and diffuse culture on international
scale during the medieval period.

According to the legend, the “Scuola Medica Salernitana” traces its origins to
four erudite: the Greek Pontus, the Jew Helinus, the Arab Abdela, and the
Latin Salernus. Thanks to the encounter of these four cultures the Medical
School established its knowledge divulgating the Greek, Jewish, Arab and Latin
medical knowledge. The divulgation in the West of the Islamic and Greek
Medical Science is certainly due to Constantino the African (XI century),
thanks to his translations into Latin of the most important Arabic and Greek
medical treatises.

I like to read some words extracted from the nobel lecture of Abdus Salam
(1979)

“Scientific thought and its creation is the common and shared heritage of
mankind. In this respect, the history of science, like the history of all
civilization, has gone through cycles. Perhaps I can illustrate this with an
actual example.

Seven hundred and sixty years ago, a young Scotsman left his native glens to
travel south to Toledo in Spain. His name was Michael, […] Michael reached
Toledo in 1217 AD. […] From Toledo, Michael travelled to Sicily, to the Court
of Emperor Frederick II. Visiting the medical school at Salerno, chartered by
Frederick in 1231, Michael met the Danish physician, Henrik Harpestraeng […]
Henrik had come to Salerno to compose his treatise on blood-letting and
surgery. Henrik’s sources were the medical canons of the great clinicians of
Islam, Al-Razi and Avicenna, which only Michael the Scot could translate for
him. Toledo’s and Salerno’s schools, representing as they did the finest
synthesis of Arabic, Greek, Latin and Hebrew scholarship, were some of the
most memorable of international assays in scientific collaboration”.

The “Scuola Medica Salernitana” was at the height of its fame in the XIV
century and carried on its teaching for nine centuries, until Giocchino
Murat’s decree, dated the 25th of January 1812, prescribed the closure.

After two centuries, we all, coming here in the Salerno University from east
and west countries, renew in some sense the old tradition, establishing an
ideal link with the cultural heritage of the “Scuola Medica Salernitana” .

I hope you will enjoy your stay in Salerno and I wish you good and useful
work.

Gaetano Scarpetta
---
Chair of the Local Organizing Committee

Local Organizing Committee

V. Bozza |
---|---
S. Calchi Novati |
L. Mancini |
G. Scarpetta (Chair) |

Scientific Organizing Committee
---
J.-P. Beaulieu | France
D. Bennett | USA
I. Bond | New Zealand
S. Calchi Novati (Chair) | Italy
M. Dominik | UK
A. Gould | USA
C. Han | South Korea
Ph. Jetzer | Switzerland
E. Kerins | UK
M. Moniez | France
T. Sumi | Japan
Y. Tsapras | UK
A. Udalski | Poland
L. Wyrzykowski | UK

Scientific Secretary
---
O. De Pasquale
V. Di Marino
T. Nappi
S. Russo

CONTENTS

Foreword iii
Scientific Rationale v
welcome vi
Organization ix
Participants xvi
School Program xix
Conference Program xx

School on Modelling Planetary Microlensing Events 1

Introduction to microlensing 2
Philippe Jetzer

From microlensing observations to science 3
Martin Dominik

The theory and phenomenology of planetary microlensing 4
Scott Gaudi

From raw images to lightcurves: how to make sense of your data 5
Yiannis Tsapras

The efficient modeling of planetary microlensing events 6
David Bennett

Contour integration and downhill fitting 7
Valerio Bozza

Microlensing modelling and high performance computing 8
Ian Bond

Conference topical speeches 9

Giant planet accretion and dynamical evolution: considerations
on systems around small-mass stars 10
Alessandro Morbidelli

The dark matter - LHC endeavour to unveil TeV new physics 14
Antonio Masiero

Characterization of planetary systems with high-precision
astrometry: the Gaia potential 15
Alessandro Sozzetti

Status of current surveys 18

Status of the OGLE-IV survey 19
Andrzej Udalski

MOA-II observation in 2010 season 20
Takahiro Sumi

The RoboNet 2010 season 22
Yiannis Tsapras

Cosmological Microlensing 25

Dark matter determinations from Chandra observations of
quadruply lensed quasars 26
David Pooley

Cosmic equation of state from strong gravitational lensing systems 27
Marek Biesiada & Beata Malec

Galactic Microlensing: the dark matter search 31

PAndromeda - the Pan-STARRS M31 survey for dark matter 32
Arno Riffeser, Stella Seitz, Ralf Bender, C.-H. Lee, Johannes Koppenhoefer

Final OGLE-II and OGLE-III results on microlensing towards
the LMC and SMC 34
Lukasz Wyrzykowski

Analysis of microlensing events towards the LMC 37
Luigi Mancini & Sebastiano Calchi Novati

Simulation of short time scale pixel lensing towards the Virgo cluster 39
Sedighe Sajadian & Sohrab Rahvar

M31 pixel lensing and the PLAN project 40
Sebastiano Calchi Novati

Planetary events 44

MOA-2009-BLG-266LB: the first cold Neptune with a measured
mass 45
David Bennett

Increasing the detection rate of low-mass planets in high-magnification
events and MOA-2006-BLG-130 46
Julie Baudry & Philip Yock

The complete orbital solution for OGLE-2008-BLG-513 49
Jennifer Yee

Planetary microlensing event MOA-2010-BLG-328 51
Kei Furusawa

Binary microlensing event OGLE-2009-BLG-020 gives orbit predictions
verifiable by follow-up observations 53
Jan Skowron

Theoretical investigations 59

Microlensing and planet populations - What do we know,
and how could we learn more 60
Martin Dominik

The Frequency of extrasolar planet detections with microlensing
simulations 65
Rieul Gendron & Shude Mao

A semi-analytical model for gravitational microlensing events 66
Denis Sullivan, Paul Chote, Michael Miller

GPU-assisted contouring for modeling binary microlensing events 70
Markus Hundertmark, Frederic V. Hessman, Stefan Dreizler

Red noise effect in space-based microlensing observations 74
Achille Nucita, Daniele Vetrugno, Francesco De Paolis, Gabriele Ingrosso,
Berlinda M. T. Maiolo, Stefania Carpano

Light curve errors introduced by limb-darkening models 76
David Heyrovsky

Isolated, stellar-mass black holes through microlensing 77
Kailash Sahu, Howard E. Bond, Jay Anderson, Martin Dominik,
Andrzej Udalski, Philip Yock

The observability of isolated compact remnants with microlensing 80
Nicola Sartore & Aldo Treves

Gravitational microlensing by the Ellis wormhole 82
Fumio Abe

The deflection of light ray in strong field: a material medium
approach 100
Asoke Kumar Sen

Rapidly rotating lenses - repeating orbital motion features in
close binary microlensing 104
Matthew Penny, Eamonn Kerins, Shude Mao

Towards the future: new facilities/instrumentation/procedures 107

Microlensing with the SONG global network 108
Uffe G. Jørgensen, Kennet B. W. Harpsøe, Per K. Rasmussen, Michael I.
Andersen, Anton N. Sørensen, Jørgen Christensen-Dalsgaard, Søren Frandsen,
Frank Grundahl, Hans Kjeldsen

Next-generation microlensing pilot planet search and the frequency of
planetary systems 112
Dan Maoz & Yossi Shvartzvald

Kohyama Astronomical Observatory: current status 116
Atsunori Yonehara, Mizuki Isogai, Akira Arai, Hiroki Tohyama

Optimal imaging for gravitational microlensing 118
Kennet B.W. Harpsøe, Uffe G. Jørgensen, Per K. Rasmussen, Michael I. Andersen,
Anton N. Sørensen, Jørgen Christensen-Dalsgaard, Søren Frandsen, Frank
Grundahl, Hans Kjeldsen

IPAC s role as the science center for NASA s WFIRST mission 121
Kaspar von Braun

EUCLID microlensing planet hunt 122
Jean-Philippe Beaulieu & Matthew Penny

Space-based microlensing exoplanet survey: WFIRST and/or Euclid 124
David Bennett

Microlensing with Gaia satellite 125
Lukasz Wyrzykowski

Poster session 127

Critical curve topology in special triple lens configurations 128
Kamil Danek

PAndromeda - a dedicated deep survey of M31 with
Pan-STARRS 1 129
Chien-Hsiu Lee, Arno Riffeser, Stella Seitz, Ralf Bender, Johannes
Koppenhoefer

SMC2011 Participants

Abe, Fumio | Nagoya University, Japan
---|---
Baudry, Julie | University of Orsay, France
Bachelet, Etienne | University of Toulouse, France
Beaulieu, Jean-Philippe | Institut d’Astrophysique de Paris, France
Bennett, David | University of Notre Dame, USA
Bond, Ian | Massey University, New Zealand
Bonino, Donata | INAF - Turin Astronomical Observatory, Italy
Bozza, Valerio | University of Salerno, Italy
Browne, Paul | University of St Andrews, UK
Calchi Novati, Sebastiano | University of Salerno, Italy
Danek, Kamil | Charles University, Czech Republic
De Paolis, Francesco | University of Salento, Italy
Dominik, Martin | University of St Andrews, UK
Dominis Prester, Dijana | University of Rijeka, Croatia
Fouqu$\acute{\mathrm{e}}$, Pascal | University of Toulouse, France
Furusawa, Kei | Nagoya University, Japan
Gardiol, Daniele | INAF - Turin Astronomical Observatory, Italy
Gaudi, Scott | Ohio State University, USA
Gendron, Riel | University of Manchester, UK
Gould, Andrew | Ohio State University, USA
Harpsøe, Kennet | Niels Bohr Institute, Denmark
Harris, Pauline | Victoria University of Wellington, New Zealand
Henderson, Calen | Ohio State University, USA
Heyrovsky, David | Charles University, Czech Republic
Horne, Keith | University of St Andrews, UK
Hundertmark, Markus | University of Göttingen, Germany
Jetzer, Philippe | University of Zurich, Switzerland
Jørgensen, Uffe G. | Niels Bohr Institute, Denmark
Lambiase, Gaetano | University of Salerno, Italy
Lee, Chien-Hsiu | University Observatory Munich
Liebig, Christine | University of St Andrews
Lubini, Mario | University of Zurich, Switzerland
Malec, Beata | Copernicus Center for Interdisciplinary Studies, Poland
Mancini, Luigi | University of Salerno, Italy
Maoz, Dan | Tel-Aviv University, Israel
Masiero, Antonio | University of Padova, Italy
Mirzoyan, Sergey | University of Salerno, Italy
Miyake, Noriyuki | Nagoya University, Japan
Morbidelli, Alessandro | Observatoire de la Cote d’Azur, France
Muraki, Yasushi | Konan University, Japan
Nucita, Achille | University of Salento, Italy
Orio, Marina | INAF - Padova Astronomical Observatory, Italy
Paulin-Henriksson, St$\acute{\mathrm{e}}$phane | CEA - Paris, France
Payandeh, Farrin | Payame Noor University Tabriz, Iran
Penny, Matthew | University of Manchester, UK
Pooley, David | Eureka Scientific, USA
Retana Montenegro, Edwin F. | Universidad de Costa Rica, Costa Rica
Riffeser, Arno | Max Planck Institute for Extraterrestrial Physics, Germany
Sahu, Kailash | Space Telescope Science Institute, USA
Sajadian, Sedighe | Sharif University of Technology, Iran
Sartore, Nicola | INAF - IASF Milano, Italy
Scarpetta, Gaetano | University of Salerno, Italy
Sen, Asoke Kumar | Sen Assam University, India
Shvartzvald, Yossi | Tel-Aviv University, Israel
Skowron, Jan | Ohio State University, USA
Sozzetti, Alessandro | INAF - Turin Astronomical Observatory, Italy
Sullivan, Denis | Victoria University of Wellington, New Zealand
Sumi, Takahiro | Nagoya University, Japan
Tortora, Crescenzo | University of Zurich, Switzerland
Tsapras, Yiannis | Queen Mary University, UK
Udalski, Andrzej | Warsaw University Observatory, Poland
Vetrugno, Daniele | University of Salento, Italy
Vilasi, Gaetano | University of Salerno, Italy
von Braun, Kaspar | California Institute of Technology, USA
Yee, Jennifer | Ohio State University, USA
Yock, Philip | University of Auckland, New Zealand
Yonehara, Atsunori | Kyoto Sangyo University, Japan
Wyrzykowski, Lukasz | University of Cambridge, UK

School on Modelling Planetary Microlensing Events
Program

Tuesday, January 18, 2011
---
09:00 | Introduction to microlensing |  Philippe Jetzer
10:50 | Coffee Break
11:15 | From microlensing observations to science |  Martin Dominik
13:00 |  Lunch Break
14:45 | The theory and phenomenology of planetary |  Scott Gaudi
| microlensing
16:45 | Coffee Break
17:15 | From raw images to lightcurves: how to make |  Yiannis Tsapras
| sense of your data
Wednesday, January 19, 2011
09:00 | The efficient modeling of planetary microlensing |  David Bennett
| events
10:50 | Coffee Break
11:15 | Contour integration and downhill fitting |  Valerio Bozza
13:00 |  Lunch Break
14:45 | Microlensing modelling and high performance |  Ian Bond
| computing
16:45 | Coffee Break

SMC2011 Program

Thursday, January 20, 2011
---
09:00 | Registration
09:30 |  Greetings
09:40 | Communications |
|  | Chair: Gaetano Scarpetta
Status of current Surveys I |  |
09:50 | Status of the OGLE-IV survey |  Andrzej Udalski
10:20 | MOA-II observation in 2010 season |  Takahiro Sumi
10:50 | Coffee Break
Topical Speech I |  |
11:20 | Formation and evolution of our |  Alessandro Morbidelli
| solar system
Theoretical investigations I |  |
12:10 | Microlensing and planet populations: |  Martin Dominik
| what do we know, and how could we
| learn more?
12:40 | The frequency of extrasolar planet |  Rieul Gendron
| detections with microlensing simulations
13:00 |  Lunch Break
|  | Chair: Philippe Jetzer
Dark Matter Search |  |
14:40 | PAndromeda - the Pan-STARRS M31 |  Arno Riffeser
| survey for dark matter
15:10 | Final OGLE-II and OGLE-III results on |  Lukasz Wyrzykowski
| microlensing towards the LMC and SMC
15:30 | Analysis of microlensing events towards the LMC |  Luigi Mancini
15:50 | Simulation of short time scale pixel lensing |  Sedighe Sajadian
| towards the Virgo cluster
16:10 | M31 pixel lensing and the PLAN project |  Sebastiano Calchi Novati
16:30 | Coffee Break
Towards the future I |  |
17:00 | Microlensing with the SONG global network |  Uffe G. Jørgensen
17:20 | Next-generation microlensing pilot planet search |  Dan Maoz
| and the frequency of planetary systems
17:40 | Kohyama Astronomical Observatory: |  Atsunori Yonehara
| current status
18:00 | The lucky imaging technique for microlensing |  Kennet Harpsøe
| observations
Friday, January 21, 2011
|  | Chair: P. Yock
Status of current Surveys II |  |
09:00 | The 2010 MicroFUN season |  Jennifer Yee
09:30 | The RoboNet 2010 season |  Yiannis Tsapras
Theoretical investigations II |  |
10:00 | A semi-analytical model for gravitational |  Denis Sullivan
| microlensing events
10:20 | GPU-assisted contouring for modeling |  Markus Hundertmark
| binary microlensing events
10:40 | Rapidly rotating lenses - repeating orbital motion |  Matthew Penny
| features in close binary microlensing
11:00 | Coffee Break
Topical Speech II |  |
11:30 | The dark matter - LHC endeavour to unveil |  Antonio Masiero
| TeV new physics
Cosmological microlensing |  |
12:20 | Dark matter determinations from Chandra |  David Pooley
| observations of quadruply lensed quasars
12:40 | Cosmic equation of state from strong |  Beata Malec
| gravitational lensing systems
13:00 |  Lunch Break
|  | Chair: Pascal Fouqu$\acute{\mathrm{{\bf e}}}$
Planetary events |  |
14:30 | MOA-2009-BLG-266LB: the first cold Neptune |  David Bennett
| with a measured mass
14:50 | Increasing the detection rate of low-mass |  Julie Baudry
| planets in high-magnification events and
| MOA-2006-BLG-130
15:10 | The complete orbital solution for |  Jennifer Yee
| OGLE-2008-BLG-513
15:30 | Planetary microlensing event MOA-2010-BLG-328 |  Kei Furusawa
15:50 | Binary microlensing event OGLE-2009-BLG-020 |  Jan Skowron
| gives orbit predictions verifiable by follow-up
| observations
16:10 | Coffee Break
17:30 | Tour of the old town of Salerno
20:00 | Social dinner
Saturday, January 22, 2011
|  | Chair: Francesco De Paolis
Towards the future II |  |
09:00 | IPAC s role as the science center for |  Kaspar von Braun
| NASA s WFIRST mission
09:30 | EUCLID microlensing planet hunt |  Jean-Philippe Beaulieu
09:50 | Simulating the planet hunting capability of Euclid |  Matthew Penny
10:10 | Space-based microlensing exoplanet survey: |  David Bennett
| WFIRST and/or Euclid
10:40 | Coffee Break
Topical Speech III |  |
11:10 | Characterization of planetary systems with |  Alessandro Sozzetti
| high-precision astrometry: the Gaia Potential
12:00 | Microlensing with Gaia satellite |  Lukasz Wyrzykowski
Theoretical investigations III |  |
12:20 | Red noise effect in space-based microlensing |  Achille Nucita
| observations
12:40 | Light curve errors introduced by limb-darkening |  David Heyrovsky
| models
13:00 |  Lunch Break
|  | Chair: Scott Gaudi
14:40 | Isolated, stellar-mass black holes through |  Kailash Sahu
| microlensing
15:00 | The observability of isolated compact |  Nicola Sartore
| remnants with microlensing
15:20 | Gravitational microlensing by the Ellis wormhole |  Fumio Abe
15:40 | The deflection of light ray in strong field: |  Asoke Kumar Sen
| a material medium approach
16:00 | How to stop a runaway (Monte Carlo Markov) |  Keith Horne
16:20 | Coffee Break
16:50 | Open session |
Poster Session
| Critical curve topology in special triple lens |  Kamil Danek
| configurations
| PAndromeda - a dedicated deep survey of M31 |  Chien-Hsiu Lee
| with Pan-STARRS 1