# Energy-efficient Wireless Image Retrieval for IoT Devices by Transmitting a
TinyML Model ††thanks: This work was supported by the Villum Investigator
Grant “WATER” from the Velux Foundation, Denmark.

Junya Shiraishi, Mathias Thorsager, Shashi Raj Pandey, and Petar Popovski
Department of Electronic Systems, Aalborg University, Denmark
Email: $\\{$jush, mdth, srp<EMAIL_ADDRESS>
###### Abstract

This work considers a scenario in which an edge server collects data from
Internet of Things (IoT) devices equipped with wake-up receivers. Although
this procedure enables on-demand data collection, there is still energy waste
if the content of the transmitted data following the wake-up is irrelevant. To
mitigate this, we advocate the use of Tiny Machine Learning (ML) to enable a
semantic response from the IoT devices, so they can send only semantically
relevant data. Nevertheless, receiving the ML model and the ML processing at
the IoT devices consumes additional energy. We consider the specific instance
of image retrieval and investigate the gain brought by the proposed scheme in
terms of energy efficiency, considering both the energy cost of introducing
the ML model as well as that of wireless communication. The numerical
evaluation shows that, compared to a baseline scheme, the proposed scheme can
realize both high retrieval accuracy and high energy efficiency, which reaches
up to $70\%$ energy reduction when the number of stored images is equal to or
larger than 8.

##  I Introductions

Energy efficiency is one of the essential Key Performance Indicator (KPIs) for
Internet of Things (IoT) networking of sixth generation (6G) communication
systems [1][2], in which Artificial Intelligence (AI) technology plays an
important role in supporting new emerging applications, including extended
reality, connected robotics, automated systems, and holographic communications
[3]. Introducing AI technology to the IoT devices, such as mobile robots,
helps to realize highly intelligent tasks but simultaneously brings challenges
for designing energy-efficient communication protocols.

The research on the energy efficiency of IoT devices is a well-investigated
topic in the area of Wireless Sensor Networks (WSNs), where many protocols
have been proposed to reduce the energy consumption of the main radio circuit
of IoT nodes. The technology enabler to realize the overall energy reduction
of IoT devices is the wake-up radio [4][5], in which ultra-low power wake-up
receiver[4][5] is installed into each device. The IoT device employing wake-up
receivers is in a sleep state when there is no communication request, in which
only the wake-up receiver is active, and the main radio circuit is turned off.
This can reduce the wasteful energy consumption of IoT devices during the idle
period. Two types of wake-up control are introduced in WSNs. The one is
Identity (ID)-based wake-up, in which the target node ID is embedded into the
wake-up signal. The other is Content-based Wake-up (CoWu) [6], which realizes
the data collection based on the observations of each IoT device.

Figure 1: An example of AI-empowered IoT data collection.

The energy-efficient protocol designs for IoT devices serving 6G applications
is more challenging than conventional WSNs, as we need to consider the energy
cost caused by the introduction of the AI/ML model as well as that of the
primary radio circuit. For instance, let us consider a toy example where an
IoT device stores four observations ($I_{1}$, $I_{2}$, $I_{3}$, and $I_{4})$
and the Edge Server (ES) wants to conduct a specific task requested by a user
by collecting data from it. In this example, the ES first needs to collect all
observations from the IoT device regardless of the content of the
observations, since it does not know in advance which IoT devices or
observations are relevant to the specific task. The indiscriminate collection
of data may lead to wasteful energy consumption. To mitigate this, we need to
design a communication protocol such that each IoT device selects a subset of
relevant images to the current query by exploiting the ML model, which
requires additional energy consumption. The paper in [7] has addressed the
above problem and introduced a framework called SEMantic DAta Soucing
(SEMDAS), in which only the relevant data can be collected by broadcasting the
semantic query, e.g., ML model to the IoT devices and by calculating matching
score [7]. Although SEMDAS is an attractive approach, it still has a challenge
to realize energy-efficient IoT data collection employing wake-up receiver, in
which we need to consider the energy cost introducing ML models as well as the
that of the main radio interface. Further, it is important to consider the
practical constraints of IoT devices, such as the memory size, where the
typical Micro Controller Unit (MCUs) for IoT devices have extremely limited
on-chip Static Random Access Memory (SRAM) memory ($<$ 512KB) and flash
storage ($<$2MB)[8][9]. To solve this problem, this paper proposes the
transmission of the TinyML model from the ES to the IoT devices considering
the query content and timing. Our work is related to the SEMDAS [7], but we
focus on the energy-efficiency of the IoT data collection and rely on the
TinyML models to send the semantic query.

Fig. 1 shows the specific example of AI-empowered data collection. In our
framework, first, the ES transmits a TinyML model [10] relating to the
specific task to facilitate subsequent semantic query to the IoT devices as
shown in Fig. 1-1. The IoT device that receives this ML model stores it in the
memory and exploits it to calculate the matching score (Fig. 1-2). After the
processing using ML model, each IoT device decides whether it transmits data
or not to the ES based on the matching score. In the example of Fig. 1, the
IoT device only transmits data $I_{3}$ whose level of relevance (matching
score) is high and suppresses the others (Fig. 1-3), by which the IoT device
can save wasteful energy consumption. From these observations, we can clearly
see the advantage of introducing the ML model in terms of energy reduction for
data transmission and new challenges in energy-efficient protocol designs, in
which we need to consider the additional cost caused by the introduction of ML
model.

In order to investigate the energy cost and the gain brought by the
introduction of ML model, this work focuses on wireless image retrieval tasks
at the specific instance in which the ES is interested in retrieving the
specific type of image requested by users, such as animal and missing child,
by collecting observations from the IoT devices [11]. Our goal is to realize
energy-efficient task-based wireless edge image retrieval [11] exploiting ML
model and wake-up radio, aiming to reduce the overall energy consumption.

The ML model transmission over the wireless channel has been considered in the
edge networks [12] and in IoT network in the context of semantic communication
[13]. In [14], the authors investigated the trade-off between convergence rate
and energy consumption through the precision of Deep Neural Networks (DNN)
model in federated learning, in which the authors investigate the energy cost
of calculation using ML model with Quantized Neural Networks (QNNs).

To the best of our knowledge, this is the first work that proposes
transmission of TinyML model to facilitate subsequent semantic query for the
wireless image retrieval task in IoT networks employing wake-up receivers and
clarifies its effectiveness in terms of total energy consumption of IoT
devices and retrieval accuracy.

##  II System Model

###  II-A Scenarios and objective of this work

We consider a scenario where an ES attempts to collect data from $N$ IoT
devices (mobile robots) at the specific time instance to conduct the specific
task requested by a user. The mobile robots patrol a given area, such as the
city, following a predetermined route and can sense the environment with the
camera-equipped at a predefined interval. The sensing data captured by the
robot $i$ are stored in a storage
$\mathcal{D}_{i}=\\{D_{i}^{1},\ldots,D_{i}^{|\mathcal{D}_{i}|}\\}$, where
$|\mathcal{D}_{i}|$ denotes the number of images stored by robot $i$. We
denote $\mathcal{M}$ a set of all available data and the total number of
images for all nodes as $|\mathcal{M}|$, where
$|\mathcal{M}|=\sum_{i=1}^{N}|\mathcal{D}_{i}|$. Each mobile robot has a main
radio interface to transmit stored images to the ES through a shared wireless
link, and a wake-up receiver. When there are no communication requests from
the ES, each mobile robot turns off its main radio interface and keeps only
the wake-up receiver to be active.

Upon the reception of a query request from a user through the cloud, the ES
first transmits wake-up signaling and then transmits a TinyML model to the IoT
devices. The wake-up receiver of the mobile robot detecting a wake-up signal
checks whether it satisfies the wake-up conditions or not. If satisfying wake-
up conditions, it activates its main radio and transmits/receives data to/from
ES. If not, it remains in a sleep state. Here, the mobile robots transmit data
following the slotted aloha policy. All nodes, including the ES, are assumed
to be located within a communication and wake-up signal range of each other,
and there are no hidden terminals. We assume that the downlink channel is
error-free, while the uplink channel is a collision channel, in which a packet
is lost only when the multiple nodes transmit the packet simultaneously.

After collecting images from the IoT devices, the ES identifies the relevant
images to the query by exploiting the larger ML model. Specifically, the ES
first conducts feature extraction for each received image using the large ML
model, whose extracted feature vectors are denoted as $\bm{h(\hat{D})}$, then
calculates the similarity measure by comparing $\bm{h(\hat{D})}$ with the
feature vector of query image $\bm{h(q)}$, where $\bm{q}$ is a query image,
such as using a cosine similarity defined by Eq. (1). The ES considers the
received image as relevant if the similarity measure is higher than the
predetermined threshold $\delta$, i.e., $\chi_{D}\geq\delta$.

$\
\chi_{D}=\textrm{sim}(\bm{h(q)},\bm{h(\hat{D})})=\frac{\bm{h(q)}\cdot\bm{h(\hat{D})}}{|\bm{h(q)}||\bm{h(\hat{D})}|}.$
(1)

Here, we define the retrieval accuracy $\gamma$, as the probability that the
estimated relevant image set is the exact ones that are relevant to the query
images. Formally, denoting by $\mathcal{T}$ the subset of images whose true
similarity measure is higher than $\delta$, and by $\mathcal{S}$ the subset of
relevant images that are successfully received by the ES. Then, the retrieval
accuracy $\gamma$ can be expressed as follows:

$\ \gamma=\textrm{Pr}(\mathcal{T}=\mathcal{S}),$ (2)

where the retrieval accuracy is one only if the results of the query always
coincide with the true set. The retrieval accuracy can be improved by
collecting all available images from the mobile robots; however, total energy
consumption becomes larger. The goal of this work is to develop a wireless
image retrieval protocol exploiting TinyML model and wake-up radio, which
realizes high energy efficiency and high retrieval accuracy.

###  II-B Observation model

Let us denote the function to extract the feature vector using the TinyML
shared by ES as $f(\cdot)$ and that of similarity measure as $g(\cdot,\cdot)$.
Then, the similarity measure of the image $V_{o}^{i}$ observed by IoT device
$j$, denoted as $z_{i}^{j}$ can be expressed as
$z_{i}^{j}~{}=~{}g(f(V_{o}^{i}),f(\bm{q}))$. Note that each IoT device can
observe the similarity measure only by exploiting the TinyML model, whose
accuracy depends on the size and the complexity of the TinyML model. If the ML
model only has a smaller capability, the observed similarity value $z_{i}^{j}$
is highly likely to deviate from the true similarity values, denoted as
$\beta_{i}^{j}$, whose range is between the minimum and maximum values of
$V_{\min}$ and $V_{\max}$. For example, we can reduce the number of parameters
by pruning and reduce the model size and computation complexity by
quantization, which, however, deteriorates the precision accuracy; for
example, top-1 accuracy of image net decreases as the model size or
quantization values becomes smaller [15][16]. In order to take into account
this cost, we model the observed similarity measure $z_{i}^{j}\in$
[$V_{\min}$, $V_{\max}$] as $z_{i}^{j}=\beta_{i}^{j}+w_{i,j}$, where $w_{i,j}$
is the observation noise, which follows
$w_{i,j}\sim\mathcal{N}(0,\sigma_{\textrm{ML}}^{2})$. Here,
$\sigma_{\textrm{ML}}$ is a standard deviation representing the degree of
model noises. Considering the trade-off between the ML model’s size with
different quantization levels and its accuracy, we set
$\sigma_{\textrm{ML}}=\frac{1}{b_{q}}$, where ${b_{q}}$ is the number of bits
for the quantization of weights. The smaller (larger) value of
$\sigma_{\textrm{ML}}$ represents the high (low) bit quantization, by which
the extracted feature of ML model includes more (less) quantization error,
whose characteristics fit to model the trade-off between the size of ML model
and its accuracy.

###  II-C QNNs

In order to reduce the energy consumption of introducing ML model, this paper
applies QNNs [17], in which we use only fixed-point representations for both
weights and activations for the calculation.

###  II-D Energy model

####  II-D1 Energy model for communication

The IoT device employing a wake-up receiver remains in a sleep state when
there are no communication requests, in which only the ultra-low power wake-up
receiver is active. We ignore the power consumption of the wake-up receiver as
its power is much smaller than that of the main radio [6]. Each activated
mobile robot consumes energy either in the transmit state or the receive
state. The power consumption at the receive/transmit state is denoted as
$\xi_{R}$/$\xi_{T}$ [W]. Then, the energy consumed for wireless communication
for an IoT device can be expressed as follows:

$\ E_{\textrm{comm}}=\xi_{R}t_{\textrm{rx}}+\xi_{T}t_{\textrm{tx}},$ (3)

where $t_{\textrm{rx}}$ and $t_{\textrm{tx}}$ are the total amount of time
spent for receive and transmit state, respectively.

####  II-D2 Energy model for computation with ML model

The energy cost per inference using ML model can be described by considering
the energy cost of Dynamic Random Access Memory (DRAM) ($E_{\textrm{DRAM}}$)
and that of processing at the hardware itself ($E_{\textrm{HW}}$) [17]. When
the ML model can not be stored in the SRAM, we need to rely on off-chip DRAM,
in which the larger energy cost is required to access it [16]. As an initial
study, we consider the ideal case, where all information on ML model can be
stored in on-chip memory. With this assumption, $E_{\textrm{DRAM}}$ can be
calculated by only considering the amount of energy consumed to access DRAM to
the input image for ML model, which can be described as follows:

$E_{\textrm{DRAM}}=E_{D}\times{I_{\textrm{In}}},$ (4)

where $E_{D}$ is the energy consumed per int $b_{q}$ DRAM access and
$I_{\textrm{In}}$ is the size of input image, which can be expressed as
$I_{\textrm{In}}=(s_{\textrm{in}}^{2}\times
c_{\textrm{in}}\times\frac{b_{\textrm{Image}}}{b_{q}})$. Here,
$s_{\textrm{in}}$, $c_{\textrm{in}}$, and $b_{\textrm{Image}}$ are,
respectively, the input image’s dimensions, the number of input channel, and
the number of bits for a single pixel.

The energy consumption for the read/write from/to the small local SRAM or
Register file $E_{L}$ is modelled to be equal to the energy of a single
Multiply-accumulation (MUAC) operation $E_{\textrm{MUAC}}$, while accessing
the main SRAM costs $E_{M}=2\texttimes E_{\textrm{MUAC}}$ [17]. Then,
$E_{\textrm{HW}}$ can be modeled as the summation of the compute energy
($E_{C}$), cost of the weight ($E_{W}$), and the activation access ($E_{A}$),
as follows [17]:

$\ E_{\textrm{HW}}=E_{C}+E_{W}+E_{A},$ (5)
$E_{C}=E_{\textrm{MUAC}}\times(N_{c}+3\times A_{s}),$ (6) $E_{W}=E_{M}\times
N_{s}+E_{L}\times N_{c}/\sqrt{p},$ (7) $E_{A}=2\times E_{M}\times
A_{s}+E_{L}\times N_{c}/\sqrt{p},$ (8)

where $N_{c}$ is the network complexity in number of MUAC operations, $N_{s}$
is the model size in number of weights and biases, $A_{s}$ is the total number
of activations throughout the whole network, and
$p=64\times\frac{b_{q}}{b_{\max}}$, where $b_{\max}$ is the full-precision
bit. Here, $E_{\textrm{MUAC}}$, $E_{L}$, $E_{M}$, and $E_{D}$ are related to
the parameter of $b_{q}$, which can be expressed as
$E_{\textrm{MUAC}}=3.7\text{pJ}\times(\frac{b_{q}}{b_{\max}})^{1.25}$,
$E_{L}=3.7\text{pJ}\times(\frac{b_{q}}{b_{\max}})$, $E_{M}=2\times
3.7\text{pJ}\times(\frac{b_{q}}{b_{\max}})$, and $E_{D}=128\times
3.7\text{pJ}\times(\frac{b_{q}}{b_{\max}})$ [17].

##  III Proposed scheme

In order to realize energy-efficient image retrieval, we propose Task-related
Neural network transmission and Content Relevance based Wake-up (TaskNet-
CoRWu), which consists of two phases: ML model transmission phase (c.f. Sec.
III-B) and image retrieval phase (c.f. Sec. III-C).

###  III-A Wake-up signaling with mode switching signal

This paper introduces two types of modes for wake-up receivers: ML-Mode and
Content Relevance-Mode (CoR-Mode). The ML-Mode is used for the ES sharing an
ML model to IoT devices, and the CoR-Mode is used for collecting relevant
images from the IoT devices. These operating modes can be switched remotely by
mode switching signals denoted as ML-Mode Signal (MLMoSg) and CoR-Mode Signal
(CoRMoSg) sent by the ES. The wake-up receiver detecting MLMoSg (CoRMoSg)
regards the following received signal as a wake-up signal for ML-Mode (CoR-
Mode). Here, the wake-up signaling and control signal are transmitted via a
secondary, low-power radio link using a simple communication method such as
On-Off Keying (OOK). For example, this can be realized by preparing a mapping
between the control signal and the duration of the wake-up signal [6].

###  III-B ML model transmission phase

In this phase, the ES attempts to share ML model related to the task and query
feature to the IoT nodes. When the ES attempts to transmit ML model to the IoT
devices, it first transmits MLMoSg to set the operation mode of each wake-up
receiver to the ML-Mode. Then the ES sends the wake-up signal, including the
information of the target node ID, e.g., node ID $A$. The IoT device receiving
the wake-up signal with its own ID wakes up and transmits wake-up
Acknowledgement (ACK) to the sink through its primary radio. After receiving
the ACK from the target IoT devices, the ES transmits the packets, including
the ML model, followed by the query feature vector. When an IoT device
receives ML model, it stores the parameter of ML model into memory (SRAM),
transmits ACK to the edge server, and turns its main radio off. Then, the ES
transmits the wake-up signal embedding the information of another node ID.
This operation will last until all nodes successfully receive the ML model and
query feature vector.

###  III-C Image retrieval phase

In this phase, the ES conducts an image retrieval task, in which only the IoT
devices having the images relevant to the query image wake up and transmit
data to the ES. In order to collect relevant image data from the mobile robot
in a sleep state, first, the ES transmits CoRMoSg to inform the initiation of
CoR-Mode. The wake-up receiver detecting CoRMoSg changes its operation mode to
CoR-Mode. After receiving CoR-Mode, each node processes each observed data
using the received TinyML model. Specifically, it first conducts feature
extraction, followed by similarity measure calculation applying cosine
similarity. Then, the wake-up receiver maps the range of observed features to
the wake-up condition, such as the duration of frame length [6] and keeps them
as the wake-up condition at the wake-up receivers. Then, the ES transmits a
wake-up signaling embedding the threshold of similarity measure
$V_{\textrm{th}}$ as a semantic query. We call this wake-up control as Content
Relevance based Wake-up (CoRWu). The wake-up receiver detecting CoRWu signal
checks whether the similarity measure of each image exceeds a threshold
$V_{\textrm{th}}$ or not. If so, it activates the main radio interface and
transmits its image; otherwise, it remains in a sleep state.

##  IV Theoretical Analysis of TaskNet-CoRWu

In this section, we derive the total energy consumption and retrieval accuracy
when we apply the TaskNet-CoRWu for the wireless image retrieval tasks. Here,
total energy consumption is defined as the total amount of energy consumed by
all nodes and the retrieval accuracy is defined by Eq. (2). First, we drive
the total energy consumption of TaskNet-CoRWu, considering the cost of ML
model as well as that of the main radio.

The total energy consumed for ML model installation $E_{\textrm{ML-
HW}}^{\lx@glossaries@gls@link{acronym}{proposed}{\leavevmode\textrm{TaskNet-
CoRWu}}}(N,|\mathcal{M}|)$ can be described as follows:

$\begin{split}E_{\textrm{ML-
HW}}^{\textrm{TaskNet}}(N,|\mathcal{M}|)=|\mathcal{M}|\\{E_{\textrm{DRAM}}+E_{\textrm{HW}}+n_{\textrm{MUAC}}^{F}E_{\textrm{MUAC}}\\}\\\
+N\\{(t_{\textrm{ML}}+t_{q}^{F})\xi_{R}\\},\end{split}$ (9)

where the first term is the total energy consumed at the hardware and DRAM
access when IoT device conducts feature extraction and similarity measure, the
second term is the energy consumption for receiving ML and query feature
vector, respectively. Here, the time spent for transmitting ML model and query
feature vector can be described as
$t_{\textrm{ML}}=\frac{N_{s}b_{q}+b_{\textrm{header}}^{\lx@glossaries@gls@link{acronym}{ml}{\leavevmode\textrm{ML}}}}{R_{\textrm{DL}}}$
and
$t_{q}^{F}=\frac{n_{\textrm{MUAC}}^{F}+b_{\textrm{header}}^{F}}{R_{\textrm{DL}}}$
where $R_{\textrm{DL}}$ is the transmission rate for the downlink,
$b_{\textrm{header}}^{\lx@glossaries@gls@link{acronym}{ml}{\leavevmode\textrm{ML}}}$
and $b_{\textrm{header}}^{F}$ are the number of bits for header in ML and
feature vector transmission, and $n_{\textrm{MUAC}}^{F}$ is the number of MUAC
operation to calculate one similarity measure, which is
$n_{\textrm{MUAC}}^{F}=l_{fv}(l_{fv}-1)+2l_{fv}^{2}+2$, where $l_{fv}$ is the
size of feature vector. Here, we set
$b_{\textrm{header}}^{\lx@glossaries@gls@link{acronym}{ml}{\leavevmode\textrm{ML}}}=b_{\textrm{header}}^{F}=0$
for simplified analysis.

In TaskNet-CoRWu, the probability of the number of data satisfying the wake-up
condition depends on the distribution of true similarity value $g_{T}(\beta)$,
$\sigma_{\textrm{ML}}$, $|\mathcal{M}|$, and $V_{\textrm{th}}$. Let
$P_{\textrm{th}}(V_{\textrm{th}})$ denote the probability of nodes waking up
given the threshold of $V_{\textrm{th}}$. We then have

$\
P_{\textrm{th}}(V_{\textrm{th}})=\int_{V_{\min}}^{V_{\max}}Q(\frac{V_{\textrm{th}}-\beta}{\sigma_{\textrm{ML}}})g_{T}(\beta)d{\beta},$
(10)

where $Q(x)$ is the Q-function defined as
$Q(x)=\frac{1}{\sqrt{2\pi}}\int_{x}^{\infty}\exp(-\frac{u^{2}}{2})du$.

Then, the probability of $w$ images satisfying the threshold of CoRWu, follows
binomial distribution as expressed below:

$P_{D}(w)=\binom{|\mathcal{M}|}{w}P_{\textrm{th}}(V_{\textrm{th}})^{w}(1-P_{\textrm{th}}(V_{\textrm{th}}))^{|\mathcal{M}|-w}.$
(11)

If satisfying the wake-up condition, the IoT device selects one slot for each
image whose observed similarity values are equal to or higher than
$V_{\textrm{th}}$ among the $L$ slots, wakes up, and transmits it at the
selected slot. Thus, the expected total energy consumption of nodes for image
data transmission depends on $w$, which can be expressed as follows:

$\
E_{\textrm{Data}}^{\textrm{TaskNet}}(|\mathcal{M}|)=\sum_{w=0}^{|\mathcal{M}|}P_{D}(w)w{\xi_{T}}t_{\textrm{data}},$
(12)

where $t_{\textrm{data}}$ is the time required for data transmission of single
image, which can be expressed as
$t_{\textrm{data}}=\frac{b_{\textrm{image}}c_{\textrm{in}}s_{\textrm{in}}^{2}+b_{\textrm{header}}}{R_{\textrm{UL}}}$,
where $R_{\textrm{UL}}$ is the data rate for uplink transmission.

Using the Eqs. (9) and (12), the total energy consumption of TaskNet-CoRWu can
be expressed as follows:

$\ E_{\textrm{total}}^{\textrm{TaskNet}}(N,|\mathcal{M}|)=E_{\textrm{ML-
HW}}^{\textrm{TaskNet}}(N,|\mathcal{M}|)+E_{\textrm{Data}}^{\textrm{TaskNet}}(|\mathcal{M}|).$
(13)

Next, we derive the retrieval accuracy of TaskNet-CoRWu
$\gamma_{\lx@glossaries@gls@link{acronym}{proposed}{\leavevmode\textrm{TaskNet-
CoRWu}}}$ defined by (2). Recall that retrieval accuracy is defined as the
probability that the set of images that the sink estimates as relevant to the
query coincides with the set of images whose true similarity measure is higher
than $\delta$. Let us denote the probability that the true similarity measure
of an image is equal to or higher than $\delta$ as $P_{\delta}$, which can be
expressed as follows:

$\ P_{\delta}=\int_{\delta}^{V_{\max}}g_{T}(\beta)d{\beta}.$ (14)

The probability that the ES can successfully collect all relevant images
depends on the threshold of $V_{\textrm{th}}$, $\sigma_{\textrm{ML}}$, and the
probability of succeeding data transmission for waking up nodes denoted as
$P_{s}$, which can be described as follows:

$\begin{split}P_{A}&=\frac{P_{s}}{P_{\delta}}\int_{\delta}^{V_{\max}}{Q(\frac{V_{\textrm{th}}-\beta}{\sigma_{\textrm{ML}}})}g_{T}(\beta)d{\beta}.\end{split}$
(15)

Finally, the retrieval accuracy for TaskNet-CoRWu can be computed as

$\
\gamma_{\lx@glossaries@gls@link{acronym}{proposed}{\leavevmode\textrm{TaskNet-
CoRWu}}}=\sum_{\zeta=0}^{|\mathcal{M}|}P_{A}^{\zeta}\binom{|\mathcal{M}|}{\zeta}P_{\delta}^{\zeta}(1-P_{\delta})^{|\mathcal{M}|-\zeta},$
(16)

where $\zeta$ is the number of images whose similarity values are higher than
$\delta$.

###### Remark 1

We have confirmed the validity of derived equations with numerical results,
where we conducted a simulation $10^{4}$ times using Matlab based on the
system model described in Sec. II-A. For simplicity of analysis, we generate
$g_{T}(\beta)$ based on uniform distribution with the range of
[$V_{\textrm{min}}$, $V_{\textrm{max}}$] = [0, 1]. Detailed analysis are
omitted due to page limitations.

##  V Numerical evaluation

###  V-A Simulation setting

In this section, we show the total energy consumption and retrieval accuracy
of different retrieval schemes. In this evaluation, we set
$R_{\textrm{UL}}=R_{\textrm{DL}}=10^{5}$ [bps], $\xi_{T}=$ 108 mW [18],
$\xi_{R}=$ 66.9 mW [18], $b_{\max}=16$, and ($s_{\textrm{in}}$,
$c_{\textrm{in}}$, $b_{\textrm{Image}}$) = (256, 3, 8). Here, we select the
parameter of TinyML model from EtinyNet1.0 [15], where $N_{s}$ and $N_{c}$ are
0.976 M and 117 M, and we set $A_{s}$ to 4.309 M based on our calculation for
the base EtinyNet1.0 architecture. As an initial work, we focus on the
scenario where the ES communicates with a single IoT device, i.e., $N=1$, and
the case where $L>|\mathcal{D}|$. With this setup, there is no collision for
the uplink communication; thus, $P_{s}=1$. Hereafter, we denote the number of
images stored in a single IoT device as $|\mathcal{D}|$. As a baseline scheme,
we apply the UniCast Wake-up (UCWu) control for collecting all observations,
in which the ES transmits UCWu signal embedding the information of individual
target node ID, and the nodes receiving a wake-up signal including its own
wake-up ID wake up and transmit all observed images. In this scheme, since the
ES can collect all images without collisions, retrieval accuracy is always 1,
while the total energy consumption is expressed as follows:

$\ E_{\textrm{Baseline}}=|\mathcal{M}|t_{\textrm{data}}\xi_{T}.$ (17)

###  V-B Numerical Results

Now retrieval accuracy and total energy consumption achieved by TaskNet-CoRWu
and baseline scheme are compared. The performance of TaskNet-CoRWu depends on
the parameter of $V_{\textrm{th}}$: the smaller (higher) $V_{\textrm{th}}$
realizes higher (lower) retrieval accuracy because of the increasing
(decreasing) number of wake-up nodes, while it increases (decreases) the
energy consumption for image transmission. Because of this trade-off, we
compare the minimum energy consumption that achieved the target retrieval
accuracy $\gamma_{\textrm{th}}$. To this end, first, we obtain the optimal
parameter of $V_{\textrm{th}}^{\textrm{opt}}$ that minimizes the total energy
consumption of TaskNet-CoRWu under the constraint of
$\gamma_{\lx@glossaries@gls@link{acronym}{proposed}{\leavevmode\textrm{TaskNet-
CoRWu}}}\geq\gamma_{\textrm{th}}$. Through these evaluations, we set
$\gamma_{\textrm{th}}=0.98$, $b_{q}=$ 8, 16, and $\delta=$ 0.90, 0.98.

Fig. 2 shows the optimal threshold of CoRWu $(V_{\textrm{th}}^{\textrm{opt}})$
against $|\mathcal{D}|$. First, we can see that the value of
$V_{\textrm{th}}^{\textrm{opt}}$ is always equal to or lower than $\delta$,
and $V_{\textrm{th}}^{\textrm{opt}}$ becomes lower when the value of $b_{q}$
is smaller and/or the value of $|\mathcal{D}|$ is larger. This is because as
the value of $b_{q}$ becomes smaller, the observed similarity measure is more
likely to deviate from the true one, by which the ES needs to select the lower
value of $V_{\textrm{th}}$ in order to ensure the retrieval accuracy to exceed
the predetermined threshold $\gamma_{\textrm{th}}$. Likewise, as the
$|\mathcal{D}|$ increases, the probability that at least one observed value,
which is relevant to the query, falls to the lower value than $\delta$
increases, by which the ES needs to set the lower threshold $V_{\textrm{th}}$
in order to collect all relevant images.

$0$$10$$20$$30$$40$$50$$0.4$$0.6$$0.8$$1$Number of Images
$|\mathcal{D}|$$\text{Optimal threshold
V}_{\text{th}}^{\text{opt}}$$\text{TaskNet-CoRWu (}\delta\text{ = 0.90,
b}_{\text{q}}\text{ = 8)}$$\text{TaskNet-CoRWu (}\delta\text{ = 0.98,
b}_{\text{q}}\text{ = 8)}$$\text{TaskNet-CoRWu (}\delta\text{ = 0.90,
b}_{\text{q}}\text{ = 16)}$$\text{TaskNet-CoRWu (}\delta\text{ = 0.98,
b}_{\text{q}}\text{ = 16)}$ Figure 2: Optimal threshold of $V_{\textrm{th}}$
against $|\mathcal{D}|$.

Next, Fig. 3 shows the energy consumption ratio against $|\mathcal{D}|$. Here,
the energy consumption ratio is defined as
$\frac{E_{\textrm{total}}^{\textrm{TaskNet}}(V_{\textrm{th}}^{\textrm{opt}})}{E_{\textrm{Baseline}}}$.
Note that the energy consumption ratio becomes lower than 1 if the energy
consumption of TaskNet-CoRWu is smaller than that of the baseline scheme. From
Fig. 3, first, we can see that, when the value of $|\mathcal{D}|$ is smaller
(e.g., $|\mathcal{D}|<5$), the energy consumption ratio is higher than 1,
i.e., the total energy consumption of TaskNet-CoRWu scheme is larger than that
of the baseline. This is because the proposed scheme requires consuming large
energy for receiving the ML model and extracting the similarity measure to
suppress a smaller number of image transmissions, while the baseline scheme
only transmits a small amount of stored image without consuming energy for ML
model introduction. However, as the value of $|\mathcal{D}|$ becomes larger,
we can see the proposed scheme outperforms the baseline in terms of total
energy consumption and retrieval accuracy. This is because the TaskNet-CoRWu
can suppress wasteful image transmission, which is unrelated to the query
image, thanks to the introduction of task-related ML model, leading to the
reduction of the overall energy consumption, while the baseline scheme needs
to consume substantial energy for the image transmission. Next, we can see
that the energy consumption ratio becomes lower as the value of $\delta$
increases. This is because when the value of $\delta$ becomes higher, the ES
can set the relatively larger $V_{\textrm{th}}$, by which the IoT devices can
suppress to transmit the large portions of images that are not relevant for
the query image. Finally, compared with the results of TaskNet-CoRWu for
$b_{q}=8$ and $b_{q}=16$, we can see that our proposed scheme achieves higher
gain for $b_{q}=8$ for the range of smaller value of $|\mathcal{D}|$ and for
$b_{q}=16$ for the range of larger value of $|\mathcal{D}|$. When the value of
$|\mathcal{D}|$ is smaller, the penalty caused by the low precision of
$b_{q}$, i.e., increasing energy consumption because of the lower setting of
$V_{\textrm{th}}^{\textrm{opt}}$ is relatively small and the large potion of
energy is consumed for receiving ML model, which is why we can see higher gain
for $b_{q}=8$. However, as the value of $|\mathcal{D}|$ becomes larger, the
energy cost for image transmission of TaskNet-CoRWu becomes a dominant part,
in which the amount of energy consumed for image transmission for $b_{q}=8$ is
higher than that for $b_{q}=16$, which is why we can see that higher gain for
$b_{q}=16$ in a range of larger value of $|\mathcal{D}|$.

$0$$10$$20$$30$$40$$50$$0$$1$$2$$3$Number of images $|\mathcal{D}|$Energy
consumption ratio$\text{TaskNet-CoRWu (}\delta\text{ = 0.90,
b}_{\text{q}}\text{ = 8)}$$\text{TaskNet-CoRWu (}\delta\text{ = 0.98,
b}_{\text{q}}\text{ = 8)}$$\text{TaskNet-CoRWu (}\delta\text{ = 0.90,
b}_{\text{q}}\text{ = 16)}$$\text{TaskNet-CoRWu (}\delta\text{ = 0.98,
b}_{\text{q}}\text{ = 16)}$ Figure 3: Energy consumption ratio against
$|\mathcal{D}|$.

##  VI Conclusions

In this paper, focusing on wireless image retrieval from the IoT devices
exploiting wake-up receivers, we have investigated how we can reduce overall
energy consumption when a specific query image is given. In order to reduce
wasteful data transmission from the IoT devices that do not observe the
desired image, we have proposed TaskNet-CoRWu, in which a TinyML model is
transmitted from the ES to IoT devices at the beginning of image retrieval and
only nodes having desired content wake up and transmit image data. We have
derived a theoretical equation expressing total energy consumption and
retrieval accuracy of TaskNet-CoRWu in order to analyze the performance and
effectiveness of our proposed scheme. Our numerical results show that the
proposed TaskNet-CoRWu achieves high energy efficiency while maintaining high
retrieval accuracy, especially when the number of stored images is large.

The future work includes energy-efficient protocol designs for multiple
queries and the investigation of optimal model transmission timing in terms of
energy efficiency and retrieval accuracy.

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# Round Table Discussion at the Final Session of FPCP 2008:
The Future of Flavor Physics and CP

Jeffrey A.Appel  Fermilab, Batavia, IL 60510 USA  Jen-Feng Hsu  Hsiang-nan Li
Institute of Physics, Academia Sinica, Taipei, Taiwan

###### Abstract

The final session of FPCP 2008 consisted of a round-table discussion among
panelists and audience. The panelists included Jeffrey Appel(moderator),
Martin Beneke, George W.S. Hou, David Kirkby, Dmitri Tsybychev, Matt Wingate,
and Taku Yamanaka. What follows is an edited transcript of the session.

##  I Question: What are the big questions in flavor physics at FPCP08?

Jeff Appel

Many of us from many places have to write trip reports when we get back. And
perhaps when writing the trip reports we could start with the big questions in
flavor physics that came up here. This is meant to help to you write the trip
report as well as to focus the discussions to come. A number of topics were
suggested by people who sent an email. So you can read them here.

  * •

$CP$ violation in charged vs neutral $B$ decays?

  * •

Mixing induced $CP$ violation in the $B_{s}$ system?

  * •

$D-\bar{D}$ mixing: How soon can we measure mixing parameter $x$?

  * •

Spectroscopy: What are the $XYZ$ states in the charm sector (counterparts in
the bottom sector?)?

I don’t need to go through them one by one, but I will ask our panel members
to begin with what among these topics they found most important; what they
think missing from the list. Martin why don’t we begin with you?

Martin Beneke

The list includes most of the hot topics discussed at this conference. The
first two items refer to phenomena connected with $b\to s$ transitions, where
the window to new physics is still open widest. However, we have learned in
the past few years that the standard flavor theory is working quite well. The
much discussed hints in the $b\to s$ sector are either not conclusive (second
item) or possess alternative hadronic standard-model interpretations (first
item). The actual observation of $D-\bar{D}$ mixing is exciting as a
phenomenon, but because of theoretical uncertainties, does not tell us much
that we did not know before about new physics.

Matt Wingate

From the lattice QCD perspective, the most interesting thing discussed here
was the discrepancy between the HPQCD calculation of $f_{D_{s}}$ and the
experimental measurement. The lattice result is quite sound: the non-strange
decay constant $f_{D}$ is the one which requires more work, namely
extrapolating lattice data to the physical up/down quark mass. The fact that
$f_{D}$ agrees with experiment while $f_{D_{s}}$ does not is an interesting
puzzle. The precision quoted for the lattice result is very impressive, and
further details from the authors will allow other lattice experts to judge the
quality of the fits involved. It doesn’t seem plausible to me that the source
of the discrepancy could be blamed on the fourth-root hypothesis used in
staggered-quark calculations.

One thing which I am investigating is: What more can be done on the lattice in
studying $b\to s$ decays? There are difficulties for the lattice here which
are not present in $b\to u$ decays or neutral $B$ meson mixing. Nevertheless,
the $b\to s$ decays are of such great interest that all approaches, including
lattice QCD, should be pushed as far as possible. I think there are
calculations we can do which will add to the picture.

Dmitri Tsybychev

I just want to add that whether there is mixing induced $CP$ violation in the
$B_{s}$ system will remain a hot topic for next couple of years, and hopefully
both D0 and CDF experiments will have updates on their results; if not in the
summer 2008, then in the fall. There is room for improvement on the precision
of measurements of $\phi_{s}$ for both experiments. With continuing successful
running of the Tevatron, both experiments plan to collect up to 8 $fb^{-1}$ of
data. CDF already has a sample of 3 $fb^{-1}$. Their current result is based
on a data sample of only 1.3 $fb^{-1}$. The D0 experiment has already used the
full sample of 2.8 $fb^{-1}$ available to date. Therefore it will be able to
increase its sample only when new data are collected. However, D0 plans to
improve the selection of $B_{s}$ mesons decaying into $J/\psi\phi$. As was
already mentioned, D0 can increase the statistical significance of its sample
by 20% through a better selection. This will directly translate to an
improvement of the measurement.

Additionally, a question still remains involving SU(3) or U-symmetry. D0
constrains the strong phases involved in the $B_{s}$ angular analysis to the
similar phases that appear in $B_{d}\rightarrow J/\psi K^{*}$ decays, and are
measured at B-factories. The constraint is rather weak, and allows for SU(3)
symmetry breaking, which may be as big as 10%. Polarization amplitudes,
measured in $B_{s}$ and $B_{d}$ decays, are compatible within measured
uncertainties. This may indicate that such symmetry exists. The result on
$phi_{s}$ does not change significantly if the phase constraints are removed.
However there is no consensus whether such a constraint should be applied, and
one can benefit from a stronger theoretical motivation.

Jeff Appel

You think that the systematic errors are not coming soon for how well you can
do on this?

Dmitri Tsybychev

The fit result for the case of free strong phases is provided in the D0
article in PRL, and agrees very well within statistical uncertainty with
result of the constrained fit.

Jeff Appel

Anybody else? Does anybody in the audience want to add to this list?

David Kirkby

I think the main question in flavor physics is where the new physics is going
to show up, if anywhere. We should remember also that there are certainly
topics in flavor physics that have intrinsic interest: spectroscopy, for
example. But how likely is it for new physics to show up there? To get the
audience more involved, how about a show of hands? Where do you think that the
new physics is likely to come from? Raise your hand once at which one of these
four you think is the most promising. So, how about the first one?

Jeff Appel

You have to leave your hands long enough for count. 1, 2, 3, 4..

David Kirkby

So how about the second one, the $B_{s}$? Which one of the four is the new
physics most likely to show up?

Rahul Sinha

They are connected. If you find $\Delta_{S}$ not equal to zero in $B$ mixing
you are likely to find other signals of new physics such as a deviation in the
small $B_{s}$ mixing phase among other things. They are connected, since
$\Delta_{S}$ can be written in terms of the small $B_{s}-\bar{B}_{s}$ mixing
phase.

David Kirkby

The second one. What is generated from the $B_{s}$ system? Can we find new
physics there? How about $D-\bar{D}$ mixing? Well you don’t know, but what’s
your intuition? What’s your gut feeling?

Choong Sun Kim

I thought of the story of the $D-\bar{D}$ mixing. There is no standard model
prediction. How can you find new physics?

David Kirkby

How likely do you think you are going to find something there?

Rahul Sinha

Yes, you can measure the $D-\bar{D}$ mixing phase with a precision of about
1degree at Super-$B$, but we need 50 inverse attobarns.

David Kirkby

How about spectroscopy? Beyond the standard model? QCD is not new physics.

Unidentified voice

It’s kind of obvious that new physics will show up there, and new particles
can contribute to the amplitudes like penguin decays or $B\to\tau$ decays. In
my opinion, this will be the best place to look for new physics.

Jose Ocariz

I agree with the previous comment that it’s a necessary condition; but it’s
not sufficient. For example, if we think of item 1, I have a feeling that this
is more or less motivated by the measurement of the different $CP$ asymmetry
in $B\to K\pi$ decay. This is a non-controversial measurement, but the
interpretation is not uncontroversial. There is no way of falsifying the
standard model by this kind of measurement despite the fact there is potential
sensitivity to contributions from non-standard physics.

[Comment by Tom Browder added in preparing this report: The discussion seemed
to imply that there is no possible future resolution of this issue. However,
the isospin sum rule proposed by Gronau and Rosner is a model-independent test
for new physics. It requires much more data ($>$ a factor of ten) and much
more precise measurements of $A_{CP}(B\rightarrow K^{0}\pi^{0})$.]

Gerald Eigen

Martin, you brought up the $b\to s$ transitions. I agree with you that these
are important. Since point 1 is rather general, wouldn’t you rather split them
into subtopics that are associated with different points than including them
all under point 1?

Martin Beneke

I was thinking of mixing-induced $CP$ violation. Would you like to include
$b\to s\ell\ell$?

Gerald Eigen

Yes, and also the $b$ transitions involving $s\bar{s}$, like $\phi K_{s}$,
$\eta^{\prime}K_{s}$, etc. The leptonic penguins clearly belong under point 1,
while the gluonic penguins fit better under point 2.

(George) Wei-Shu Hou

I know I am viewed as a fanatic, saying that fourth generation this and that.,
fourth generation for everything. I actually quite agree with what Martin and
Jose said, and that this kind of discussion can be endless, and we are not
going to go very far. But the converse is not true; that if you show that in
some new physics model you can generate an observed effect, it would still be
of interest. So [going into a short presentation] this result here is
published in 2005, and I give you the diagram. I have said many times during
the conference, that having a t’ would bring in large Yukawa couplings and new
$CP$ violating CKM elements. Our study was re-done at next to leading order in
PQCD, and the effect on DCPV difference was not diluted. And there is another
thing, that it does push down $\Delta_{S}$.

It’s not sufficient to generate the central value of the experiment, but to me
that is very interesting. The two things mentioned in this conference are of
note to me. One thing.Maybe I pull this slide [from Derek Strom’s talk] back.
If you look at this, here is the Standard Model expectation for $\phi_{s}$,
and here are all four different, related measurements. All the measured values
fall to the left. And here is the actual published prediction from 4th
generation (which is smack in the middle of the experiments). I already stated
something like this, large $\sin(2\Phi_{B_{s}})$, in 2005. This is on the
record. At the moment, I am not a UT-fitter fan, and nobody here is. I am not
on the IAC. I would have voted for them to be here, just for the debate. At
the moment, you know, experimentally one can not yet say too much. It’s not
inconsistent with the Standard Model. I do point out that these numbers
normally would be scattered (if the SM is correct), but they are not. The
error bars will get reduced, say in next two years, from 1.35 inverse
femtobarns of data, to 3 to 5 to 8. In the last year or two, I used to say
that if the central value stays, I would then be willing to bet a good bottle
of red wine that the 4th generation is real. Starting a year ago at FPCP in
Slovenia, the data seem to be heading in this direction. Now here [another
slide on $A_{FB}$ from Eigen’s talk] is one thing that Gerald brought up but
didn’t really go through. The green line in the Belle plot is marked ”C9, C10
sign-flipped”, which is equivalent to C7 sign flip. The blue line in the BaBar
plot is for the Standard Model, almost zero, but slightly negative. Now the
upper figure was actually shown by Dmitri [Tsybychev] in his talk. The blue
dashed curve, is the fourth generation differential $A_{FB}$, and the marked
red line gives roughly the lower $q^{2}$ bin here. So you can understand why
the Standard Model is slightly negative and close to zero; because below the
zero is negative. Sorry that the sign convention is opposite to the B-factory
experiment. And above the zero is positive but there is a bit more negative
than positive so that you get the blue zero, or close to zero, of the SM in
the BaBar plot. But in our fourth generation analysis the line moves down. So
the zero moves further down, and there is not much negative part but large
positive part; so it’s more consistent with Belle/BaBar results. And I think
it was Uli who raised this issue, you know, complaining what is still called
by experimentalists the C7 sign flip. This is basically a way that
experimentalists say that there is a deviation. And this is why I stressed
that I want to treat these things more generally, to allow complex Wilson
coefficients. This gives the shaded area. I don’t want to go into any further
details. Let me change tone and say — I am willing to bet a good bottle of
Champagne now, if you want to take up the order. Why? Now this [yet another
slide] is the standard folklore that Standard Model $CP$ violation is
$10^{-20}$. Here is the Jarlskog invariant, and A here, the invariant CPV
area, is like $10^{-}5$. But the real suppression is coming from these small
masses. So if you put in numbers, when you normalize properly with, say, the
electroweak phase transition temperature, you get this $10^{-20}$. Now you see
the fourth generation does miraculous stuff here because it naturally has
large Yukawa couplings. So if you shift by one generation, this
$m_{c}^{2}-\mu^{2}$ becomes $m_{t}^{2}-m_{c}^{2}$, etc. This gives rise to a
very large enhancement. Well, it is still a suppression factor, but the
$m_{b}^{2}-m_{s}^{2}$ alone is the only suppression. So this gives a $10^{15}$
gain, where about a factor of 30 is from the $b\rightarrow s$ $CP$ violating
analysis. OK, but the factor of 30 compared to $10^{15}$ is nothing, so long
that this factor of 30 is not $10^{10}$, or something. So we have a very large
enhancement factor compared to the Standard Model three generation Jarlskog
invariant. I think this is another proof that Nature is more ingenious than
anyone of us here. But for me, to be able to jump back to put the $CP$
violation within Yukawa sector to be relevant for baryogenesis, that’s why I
say I am willing to bet a good bottle of Champagne now, … but only for ten
people, OK?

Choong Sun Kim

I do not know all the details of fourth generation, but I have some simple
questions. First, as you know, and as everyone knows, this fourth generation
neutrino mass is quite heavy, $>$ 45 GeV. So why do we have such a heavy
neutrino, much different from the first three generations? That’s very strange
to me. This kind of thing comes out more naturally if we have something like a
string-inspired E(6) model, which predicts rather heavy vector-like quarks,
unlike the fourth generation.

(George) Wei-Shu Hou

Well, there is a very simple answer to that. Vector like quarks will not have
this enhancement. These are not masses, these are Yukawa couplings. Dirac
masses go into the denominators, propagators and decoupling. So we can not
have enhancement.

Choong Sun Kim

Something like Kaluza-Klein or some other excited states. I think probably a
similar result will come out generally without a so-heavy neutrino problem.

(George) Wei-Shu Hou

Yea, OK. I can not argue with Kaluza-Klein. They are all legitimate, but this
one (4th generation) is within Standard Model dynamics! Now for neutrinos, we
firmly know there are only three light ones. But since 1998, as compared to
1989, we also learned that neutrinos have mass. So it’s a much richer sector
than we knew of. Furthermore, you didn’t mention electroweak precision tests,
right? There is a recent paper by Kribs et al (Plehn, Spannowsky and Tait),
which refutes the very stringent application of precision test against the
fourth generation in the PDG. list. So it’s not ruled out. But whatever you
say, I am just saying this more than ten-order-of-magnitude gain is so
enormous. I use this to argue that, despite electroweak precision tests, even
the neutrino stuff, the 4th generation is fairly legitimate. The thing is,
when you have high scale $CP$ violation for baryogenesis, such as
leptogenesis, you tend not to have a laboratory test. It’s a matter of physics
in the usual sense.

Taku Yamanaka

I didn’t vote for any of the four items up there. Since I am an
experimentalist, and since I work on kaons, I will vote for kaon physics
experiments. The sensitivity of a $K_{L}\rightarrow\pi^{0}\nu\bar{\nu}$
experiment will first go down by three orders-of-magnitude, from O(1E-8) to
O(1E-11). Even beyond the Grossman-Nir limit, there is a two-orders-of-
magnitude parameter space for new physics to appear. So, do you want to vote
for a 10 percent effect, or do you want to vote for a large parameter space
with two orders-of-magnitude? I would vote for a two-orders-of-magnitude
effect.

##  II Question: What are the big flavor-physics questions to come?

Jeff Appel

There is another way to continue this discussion which is the second question.
That is, what are likely to be the big flavor-physics questions after the
first Tevatron or LHC signal beyond the standard model? And a corollary
question is what would be the flavor-physics questions if we don’t see a new
signal at LHC?

The answer given for the first part is that the interesting flavor-physics
question will depend on what you see. However, almost anything you see will
have multiple possible answers, multiple models which can explain it. This may
mean that there are sensitivities to flavor physics across the board. In fact,
I don’t think a signal in a particular channel will lead to only one flavor-
physics parameter that you want to look at. That’s how I guess I would put it.

Tom Browder

If a signal really shows up early at the LHC, I think the big question will be
how any new particles at LHC do not produce flavor changing neutral currents.
The theorists will have to find brilliant ways for cancellations to not
produce flavor changing neutral currents, not just produce a new model.

Jeff Appel

So you don’t think there will be big signals from LHC? I didn’t mean to put
too many words into your mouth. Anybody on the panel want to respond to this
more ambiguous question?

David Kirkby

I think it is easy to imagine new physics at LHC where you wouldn’t really
know what to do at the Super-B-factory. So maybe the challenge to the audience
is ”Can you think of something we may find at the LHC where it would be
unclear what to do in flavor physics?” Are there other scenarios? Let’s talk
about that.

Rahul Sinha

If you see a signal of something at the LHC, you want to make sure that the
theoretical parameters corresponding to your favorite model/scenario, and that
are consistent with the signal, are not actually ruled out by precision tests;
and $B$ physics would provide a precision constraint, through loop
contributions. Therefore, you want to make sure that $B$ data is consistent
with the scenario and the observed signal. That is one way again of using
flavor physics.

David Kirkby

There are strong constraints from the data we already have.

Rahul Sinha

This is not enough. As to whether the current flavor constraints are good
enough - let me say we need to improve; we need as much improvement as
possible. With the LHC alone, we may see a signal of new physics, but we may
not be able to figure out what kink of new physics it corresponds to. Here is
where flavor physics comes in, ruling out or finding consistency among
different models given a particular signal. The better the precision, the
better the constraints. One requires flavor physics to enable pinning down
what is the new physics.

Martin Beneke

We discuss flavor physics in the context of the TeV scale. In doing that, we
almost always implicitly assume that electroweak symmetry breaking is caused
by some weak-coupling phenomena. That’s not guaranteed. An entirely different
way of seeing things would be needed if it turns out that electroweak symmetry
breaking happens through some QCD-like strong-coupling mechanism. Then the
flavor-physics puzzle is more severe, because if there is no weak coupling at
the TeV scale, we would know that flavor physics is probing much higher scales
which are disconnected from TeV scale. So, indirectly, one of the big flavor-
physics questions to come and be answered is what causes electroweak symmetry
breaking.

Keh-Fei Liu

I wonder if one of you could comment on neutron electric dipole moment in
terms of its discovery potential, and if there can be some effect found in the
next couple of years. Will the new physics be orthogonal or complimentary to
this flavor physics?

Jeff Appel

The coupling to the neutron electric dipole moment for any of these questions.
George?

(George) Wei-Shu Hou

You mean something specific. I actually asked Junji Hisano, the expert.
Basically 4th generation effects can enter through loops. I think that’s what
you are referring to. So that should be studied, yes.

Keh-Fei Liu

In the program of looking for new physics, I want to see whether there is a
discovery in a channel that would be complementary to the study here in flavor
physics. Or, is there some orthogonal result?

Dmitri Tsybychev

I think it’s a general problem. If you see something at the LHC, how do you
reconstruct the underlying physics? Say that 200 models can give you the same
signal. It will take more than just one significant deviation in one channel
to really understand the nature of the new physics.

Rahul Sinha

Typically, one talks about the missing $E_{T}$ signal at the LHC. I would like
to get an opinion as to whether flavor physics can help in pinning down the
nature of the new physics. With flavor-physics constraints included, it would
be interesting to come up with signals that can help to say whether it is SUSY
or not SUSY.

Dmitri Tsybychev

If you have missing $E_{T}$, it could be anything. It could be supersymmetry.
It could be a leptoquark. It could be extra dimensions. There are a number of
scenarios that will result in large missing $E_{T}$.

Rahul Sinha

Sure. But, what is it that should be really watched out for, say, for SUSY or
other new physics, and what kind of measurements in flavor physics can
actually help distinguish between the kinds of scenarios. Is it possible to do
that? Anybody?

Jeff Appel

I think the point is that too many things have missing-energy signals to say
that this or that is the specific answer.

Tom Browder

There is a sort of a worldwide effort, at CERN and other places. People are
writing very thick yellow books about the connection between flavor physics
and the physics at LHC. They do consider lots of different scenarios in the
possible impact of all the observables in B physics. You may find reading
these articles boring now because we don’t have a new physics signal at the
LHC to look at. But there have been pretty substantial efforts and a lot of
papers on this.

Enrico Lunghi

I have a general comment on the first two questions. ATLAS and CMS are mostly
”flavor-diagonal” experiments. On the one hand, they will tell us the mass
scales and the tree-level structure of whatever new physics model is realized
in nature. On the other hand, the quantum structure of the theory (e.g. loop
effects) will be hardly accessible. The latter task is perfectly suited for
flavor-physics experiments, that will act as a tie-breaker among the several
equivalent new physics models that will emerge from the first analyses of LHC
data. Of course, these kinds of studies require inputs from ATLAS and CMS.
Once a few masses and processes are known, one can construct complete models
and predict which flavor observables are expected to deviate from the SM
predictions. It is also possible that ATLAS and CMS will not find any new
physics. In this case, flavor physics (including lepton flavor violation) will
allow us to access to much higher scales (e.g. hundreds of TeV). There are two
scenarios. If ATLAS and CMS find TeV-scale new physics, flavor physics will
help to find out the detailed structure of the theory. If, on the other hand,
new physics turns out to be beyond the reach of direct production at the LHC,
we can still explore it via super-rare processes (e.g. lepton flavor
violation).

Choong Sun Kim

I have some unrelated questions for Hsiang-nan and Martin about the previous
discussions. Everyone knows that we, within the standard model, can not
calculate the $B$ to $\pi^{0}\pi^{0}$ branching fractions. Is that new
physics?

Martin Beneke

No.

Choong Sun Kim

Because the error is quite small. The experiment error is small.

Martin Beneke

But the theoretical error is not so small.

Choong Sun Kim

But you can explain all others except for $\pi^{0}\pi^{0}$. Even $B$ to
$\rho^{0}\rho^{0}$, which has exactly same quark diagrams as $\pi^{0}\pi^{0}$,
can be predicted rather well. When the measurements began, it was quite
different - theory predicted only 1/3 of the experimentally measured branching
fraction. So I think today’s value is kind of a post-diction. You just changed
the input parameters. Therefore, even though we think it is rather trivial,
like the color-suppressed tree, it can be something else - like beyond the
standard model.

Martin Beneke

We have learned that the dynamics behind the color-suppressed tree amplitude
is very different from the naive factorization picture, and also understand
why the theoretical uncertainties are large for this amplitude.

Rahul Sinha

I just want to ask something since you raised the question about factorization
and naive factorization. Naive factorization works so well in $D$ decays. We
all remember the classic paper of Bauer, Stech and Wirbel. Factorization,
however, does not work so well in $B$ decays as is evident from data. Is there
a good explanation for that? Why does factorization work better for $D$ decays
and not that well for $B$ decays?

Martin Beneke

I wouldn’t say that this is true. In $B$ decays, we discuss many more
challenging observables than just branching fractions of tree-dominated
decays; such as penguin-dominated decays, $CP$ asymmetries, and strong phases.

Rahul Sinha

Let us just go back to branching ratios for modes like $K\pi$, $\pi\pi$ and …
These things work so well in $D$ decays, but not that well in $B$ decays.

Hsiang-nan Li

But I think this question does not belong to this category. I think it’s still
too early to have any concrete conclusion because currently the theoretical
precision is just up to next-to-leading order, right? So there is next-to-
next-to-leading order, next-to-next-to-next to leading order. There is a long
way to go.

##  III Question: What are the connections between observations in the quark
and lepton sectors?

Jeff Appel

This is pretty technical for the round-table level of discussion. I guess I’d
like to move on to our next question. I don’t have a lot of questions. Don’t
get too scared. I wonder about the connection between the flavor observations
in the quark and lepton sectors. Do we understand these? Or, do we have to
wait to get to Plank scale to figure it out.

Choong Sun Kim

The $\sin(\theta_{12})$ in neutrino-sector mixing and $\sin(\theta_{12})$ in
the quark sector, now adding up those 2 mixing angles comes up to about 45
degrees. It could be an accident. Or maybe there is some kind of connection
between the quark sector and the lepton sector. People say it’s
complementarity, something like that. Quark-lepton complementarity. Maybe
there is some reason behind it, or is it an accident?

##  IV Question: Is there a flavor-physics community, and if so, has it
articulated its case well enough?

Jeff Appel

One reason why I put this question in here is to address the nature of this
conference and our community. I use the singular form, our community, the
flavor-physics community which covers quarks and leptons. This is the physics
we have discussed at FPCP 2008. Have quarks and leptons been brought together
at this meeting more strongly than in the past because of $CP$ violation only,
or there is something more fundamental that makes them part of the same
community? And if so, has this community articulated the case for support of
both axes strongly enough? I am thinking of the priorities that have been
expressed in the United Kingdom and in the United States. We also have heard
about the delay in kaon physics at J-PARC, and so on.

Taku Yamanaka

Well, let me first speak about the situation in Japan. The High Energy Physics
Committee in Japan, of which I am also a member, wrote up a report on what to
do in the future. In that report, we stated two things. One is, approach the
high energy frontier, including LHC and ILC etc. We also stated that the
intensity frontier, especially flavor physics, is important. This is
especially true because in Japan we have Belle and the neutrino program. The
experiments are very popular and are being supported. J-PARC is the key
facility for neutrino and kaon experiments. Even the people pushing for the
ILC are supporting the J-PARC program, because if J-PARC fails, then there is
no linear collider. From the viewpoint of the funding agency, that’s very
clear.

If the question is, is there a flavor-physics community in Japan, the answer
is yes. The people working on kaons, $B$ physics, and neutrino physics,
experimentalists and theorists, have joined forces and won a ”Grant-in-Aid for
Scientific Research on Priority Areas”, titled ”New Developments of Flavor
Physics”. The project is supported for 6 years, and the fund is being used for
building the T2K and Opera experiments, the J-PARC kaon experiment, $B$
physics at CDF, and Belle. We get together every year to have a small workshop
to present all the new findings. This is really making a close community of
people ranging from young students to older professors working on various
experiments and theories, all on flavor physics.

Martin Beneke

It may be unpopular to say this, but talking to people outside and even within
the flavour physics community, one may get an impression that flavor
physicists had their chance to find new physics. They did not, so it is time
to move on to the next thing - LHC physics. If something shows up there, then
we can go back to flavor physics to try to sort things out. We may be blamed
ourselves for that because we have been talking too much about new physics and
obscure 2$\sigma$ effects, and didn’t succeed to create interest in the
intrinsic physics itself, in the phenomena.

I am fascinated and mystified how neutrino physics is succeeding in this
respect – measuring a mass matrix in the lepton sector, which is after all not
so different from measuring the CKM matrix. And there is even less prospect of
discovering new physics by determining $\theta_{13}$ than there is in
$V_{ub}$!

Jeff Appel

There is an interesting corollary to the way you put it. In terms of selling
the physics these days, one tries to sell physics as ”paradigm-changing”
discoveries. What is the argument you would make to sell our physics, whatever
it is? The first thing one looks for is what people call paradigm-changing
discoveries, right? How would you sell the physics that you are talking about
in the world?

Martin Beneke

Once neutrinos have masses, there is no paradigm change in measuring mixing
angles or even CP violation. Nevertheless, there is some intrinsic interest in
investigating neutrino properties, because neutrinos are considered
mysterious, while quarks are not. In any case, returning to your question,
advertising paradigm change is dangerous, since paradigms usually change by
observations that come unexpectedly, not because of a systematic search.

Jeff Appel

Martin, that’s in fact exactly right. The neutrinos are interesting because we
were surprised. And it’s more a matter of surprise which sells newspapers,
rather than continuing to observe the things we expected to observe, the so
called standard model. That doesn’t sell newspapers. The articles we read
about 600 physicists ”failing” to find this, ”failing” to find that. We have a
problem selling the more precision measurement and standard things.

Bruce Yabsley

You asked how do you sell something more subtle when someone else is pushing
the paradigm-changing. The answer is: it’s damn hard! If you send your
children to their grandparents, and the grandparents feed them candy, they are
attacking kids’ weakness. I am sorry. We always push that this would change
the world, whatever. Think of all that has been happening in spectroscopy,
some of the most interesting stuff to come up in the $B$ factory. I don’t
believe that it’s nuclear physics.

Jeff Appel

And it’s interesting because it was a surprise? Or interesting for another
reason?

Bruce Yabsley

Again, it’s interesting because it’s a surprise. Now, if we get into a
position where we discover something that is both surprising and interesting!
Maybe we have to spend a few years in training on how to talk to guys from the
newspapers. Maybe we just do.

David Kirkby

Maybe one way to answer your question is to look at the nuclear physics
community because they are, at least in the US, well funded; and what they are
doing is not so different from spectroscopy in heavy quarks.

Rahul Sinha

The fact is that we initially set up the $B$ factories to test the CKM
hypothesis. We have succeeded; we have done that. We have not only succeeded
in doing that, but we have learned a lot more. We have new resonances and many
puzzles about them. This is at the very least ”surprising”. So in that sense,
there is no way to say that we have not actually had very good physics output.
Somehow, $B$ physics efforts have become the victim of various constraints
dictating the directions in physics, e.g. our desire to find a way probe the
Plank scale as fast as possible.

Eli Rosenberg

Let me say something that has already been said. The first slide you put up
there. It all had to do with where new physics is going to be found. You
already brought in the concept that to sell anything, it has to be something
new. And on your second slide, the reaction to what happens in the Tevatron
and LHC. God help this field if nothing is found in those places. This
conversation becomes entirely irrelevant simply because we have oversold the
idea that we have to find something new. Now I have a feeling that if we went
back to 30, 40 or 50 years ago, when particle physics was a virgin, people
were working on precision measurements of electromagnetic interactions. We
must have felt exactly the same way you are feeling in this room now - that
somehow we were undervalued by looking at things where you could make precise
measurements. And the real argument is, we are working in the area where you
can make precise measurements, where you can look for new things like lepton
flavor violation. We’d like to measure $D$ mixing because we didn’t expect to
see much of it. It’s interesting, and it has intrinsic interest of its own,
period. Whether it’s going to be something new or not, that is a different
issue. Now, how you sell that to our funding agencies is where the problem
seems to come in. The same thing happens in the $K$ meson sector. The $K$
meson sector had a resurgence at one point after being pushed down for a long
time. So this has been a continuing problem. But I think part of the problem
is that we have gotten so big and so expensive that we oversell everything.
The field as a whole has oversold everything. This is what you have to do.
That’s why you read the headline about 600 physicists failing to find this or
that; because we said we were going to find it. You know, we sold the SSC as
if we could do everything except cure baldness. So I think we just have a PR-
reality problem about what science is about.

(George) Wei-Shu Hou

I would like to make several remarks touching on all that has been said. I
think that on neutrino physics, I held back on one question that I used to
ask. If I take $V_{ub}$, it’s very hard to extract, correct? But if we take
the $V_{ub}$ analogy, because neutrino people have had ten spectacular years,
this is in part because of the very large mixing angles. They could not ordain
that, right? So if I take $V_{ub}$ or even $V_{cb}$, our $\theta_{13}$ or
$\theta_{23}$ for neutrinos, I don’t see a program yet to measure something of
that strength for $\theta_{13}$. They are entering a hard time. Without that
(a large $\theta_{13})$, forget about $CP$ violation in the lepton sector. OK,
Majorana neutrinos, (neutrinoless) double beta decay, there is always some
discovery potential. But they are not really doing better than we are. I don’t
know how, in the last ten minutes, we entered such a very gloomy mood. I think
we actually have a good situation. The LHC is starting. The Tevatron is still
working very hard. We are seeing things here and there. We are, of course,
used to seeing things disappear from before our eyes. But that’s how it is;
right? Seeing something emerge and then disappear; hoping that one of them is
true. And I think this mixing-dependent $CP$ violation phase (in $B_{s}$) is
of course the way to go. But, maybe we are overselling it. It may be a PR
problem, but we do have genuine indications, not just challenges. So I like
what Enrico said, I think at LHC, ATLAS and CMS analyses will find the scale.
The New Particles will likely be extrinsic to flavor. However there is also
LHCb, right? I guess we go back to Question 2. What if we see nothing beyond
the Standard Model? Maybe we see the Higgs, maybe we don’t. But if we see
nothing, and LHCb will measure $\sin(2\phi_{s})$ to plus or minus 4 percent,
no charged Higgs, no SUSY. Then no matter what PR we do, you can not get the
next big machine.

But I am optimistic about both LHC proper, the high energy frontier, and LHCb
also. I am also a full supporter of the Super KEKB or Super $B$-factory.
Because it’s really a PR question again. A Super $B$-factory is a multi-
purpose facility. And speaking from Asia, I am even more supportive of this.
Asia is rising. It has the population, etc. I would fully support it even just
only on that account. That it is a project to work on, to go forward. And if
not a discovery at this stage, then there will be a discovery at the next
stage. To me, Super KEKB is a regional cooperation concern.

Jeff Appel

In order to move to a more positive direction, perhaps there are other
questions people would like to address to the panel, or to each other before I
get to my last question?

Bruce Yabsley

Just inspired by the previous discussion, I would note that when the LHC turns
on, the field is going to undergo a kind of basic change. The kind of
information we are using to decide what studies to do, and how to do it, is
going to change. Now, the moment someone puts a preprint on hep-ph, everyone
at the $B$-factories, drops everything they are doing to pursue the suggested
analysis, or something like this. What’s going to happen now is that we are
going to get some sign of a particular mass scale. And that’s going to have an
influence on the things we should be studying. But the influence is going to
be a hundred percent, because it’s going to determine what the new physics is,
presumably, and more than one model will be possible. Here my question is: do
we have a mechanism so that we have a while to think about how we are going to
be influenced by the new information. Or, are we going to be driven by some
prejudice that what we see, is what we know, and so suddenly everyone rushes
in particular directions like ten-year-olds playing soccer. The situation
really is going to change. I am wondering if we thought forward to what
happens when we see data.

Jeff Appel

I think there is plenty of evidence that the community is a very good at
rushing together in singular directions, in effect, ten-year-olds playing
soccer as you called it. We also did this when the $J/\psi$ was discovered.
Every experiment asked if they could see evidence of that signal.

Enrico Lunghi

I would like to make a comment on the impossibility of a null result at the
LHC. In fact, unitarity tells us that either we’ll find at least one Higgs
particle. Otherwise, some other phenomena have to happen (e.g. strongly-
interacting vector bosons, new strong resonances, …). In any case, even if
just a SM-like Higgs is found, we still need a linear collider to study its
properties. I don’t think that we can really go there and see nothing.

Eli Rosenberg

Because you are so convinced, and we have been told that we will. And if we
see nothing, it is the most fascinating physics result of all - except that it
will kill the field. Aside from that, … I rest my case. Then why do we have to
build it? Because we are going to see something.

Choong Sun Kim

I have one question not related to politics or anything like that. We know
that George proposes a fourth generation. But if there is a fourth generation,
it is supposed to violate unitarity in three generations because, effectively,
the 3 by 3 part of the larger 4 by 4 matrix is non-unitary. OK. What I want to
ask is another thing, about gamma in the unitary triangle. The gamma or alpha
measurement is not actually measuring gamma or alpha. It’s beta plus gamma,
for example. So my question is, is it possible that LHCb, or Super-B, or any
future B-factory can find the 3 by 3 CKM matrix non-unitary? Is it possible to
find non-unitarity or not?

Jeff Appel

Yes, anybody working in $B$ factories would say yes, you can find the triangle
does not close. It is not unitary and there is going to be something else,
some new physics.

Chung-Sun Kim

The measurement of gamma or alpha is from the $\pi-(\alpha+\beta)$. So by
definition, you are just taking the angles as from a triangle.

Jeff Appel

The sides have to work too, right?

Eli Rosenberg

Gamma, perhaps from a Dalitz analysis, maybe from the $\Upsilon(5S)$. Does
that beta plus gamma match the beta plus gamma you get when they interfere?
That’s the test. And that’s equivalent to test unitarity; whether the standard
model is working. That’s what is, in short hand, called alpha. I agree with
you. Nobody measures alpha, but measures $\pi-(\beta+\gamma)$.

Rahul Sinha

The one thing to note is that $\gamma$, or one of the angles measured, has to
be from outside of the $B_{d}$, to see a breakdown of unitarity. It is well
known that if you measure the three phases using just $B_{d}$, the effect of
new physics will cancel out. In addition, the other thing one can do is to
measure both sides and the angle and then check if the triangle closes.

Jeff Appel

The same triangle.

Choong Sun Kim

The measurement of $\gamma$ or $\alpha$ is from $\pi-(\alpha+\beta)$ or
$\pi-(\beta+\gamma)$. So, by definition, you are just forcing a triangle if
you do not measure the 3 angles independently. Also, beta from $B\rightarrow
J/\psi K_{s}$ can effectively include new physics, too.

Rahul Sinha

Yes. But, you can also measure gamma, outside the $B_{d}$ system. There is a
method to measure it using $B_{s}\rightarrow DK$. If you do that, then there
is no problem. You can detect the breakdown of unitarity without measuring the
side.

Jose Ocariz

Another way of saying it is that you are measuring 4 parameters with 10
observables. If you have no consistency, you have no unitarity.

##  V A final question.

Jeff Appel

We are reaching the end of our scheduled time. I do want end on one new
question, our last question, which is ”How can we thank our hosts enough for
their hospitality, the careful and caring organization of this meeting, their
holding back the worst of the rains for the excursion, and clearing the sky as
well for the highest level of FPCP banquet ever held? So, I think we should
close this session and thank our hosts very much.

(applause)

And I personally want to thank the panelists and all of you in the audience
for the very stimulating discussion. Good luck on your trips home, whether
near or far. And, again, thank you all.